Virtual and Augmented Reality in school context: A literature review

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Immersive virtual reality as a pedagogical tool in education: a systematic literature review of quantitative learning outcomes and experimental design

  • Open access
  • Published: 11 July 2020
  • Volume 8 , pages 1–32, ( 2021 )

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  • D. Hamilton   ORCID: orcid.org/0000-0002-8659-4385 1 ,
  • J. McKechnie 1 ,
  • E. Edgerton   ORCID: orcid.org/0000-0001-7389-527X 1 &
  • C. Wilson   ORCID: orcid.org/0000-0003-1054-4928 1  

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The adoption of immersive virtual reality (I-VR) as a pedagogical method in education has challenged the conceptual definition of what constitutes a learning environment. High fidelity graphics and immersive content using head-mounted-displays (HMD) have allowed students to explore complex subjects in a way that traditional teaching methods cannot. Despite this, research focusing on learning outcomes, intervention characteristics, and assessment measures associated with I-VR use has been sparse. To explore this, the current systematic review examined experimental studies published since 2013, where quantitative learning outcomes using HMD based I-VR were compared with less immersive pedagogical methods such as desktop computers and slideshows. A literature search yielded 29 publications that were deemed suitable for inclusion. Included papers were quality assessed using the Medical Education Research Study Quality Instrument (MERSQI). Most studies found a significant advantage of utilising I-VR in education, whilst a smaller number found no significant differences in attainment level regardless of whether I-VR or non-immersive methods were utilised. Only two studies found clear detrimental effects of using I-VR. However, most studies used short interventions, did not examine information retention, and were focused mainly on the teaching of scientific topics such as biology or physics. In addition, the MERSQI showed that the methods used to evaluate learning outcomes are often inadequate and this may affect the interpretation of I-VR’s utility. The review highlights that a rigorous methodological approach through the identification of appropriate assessment measures, intervention characteristics, and learning outcomes is essential to understanding the potential of I-VR as a pedagogical method.

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Introduction

The increasing financial feasibility of virtual reality (VR) has allowed for educational institutions to incorporate the technology into their teaching. According to research, 96% of universities and 79% of colleges in the UK are now utilising augmented or virtual reality in some capacity (UKAuthority 2019 ). In addition, the rising power of personal computers and associated hardware has led to a revolution in graphical fidelity, with ever more complex and realistic simulations and virtual worlds (Slater 2018 ). As Dickey ( 2005 ) alludes to, this has both challenged and expanded the very conceptual definition of what is defined as a learning environment. Where once this would have been restricted to classroom teaching or field trips, VR’s innate ability to give users a sense of presence and immersion has opened new possibilities in education if implemented appropriately (Häfner et al. 2018 ).

The use of technology-aided education as a pedagogical method is not a modern phenomenon, and investigations into its utility have been studied for almost half a century. As far back as the 1970s, Ellinger and Frankland ( 1976 ) found that the use of early computers to teach economic principles produced comparative learning outcomes with traditional didactic methods such as lectures. However, as Jensen and Konradsen ( 2018 ) allude to, it was with the release of the Oculus Rift in 2013 that VR became synonymous with head-mounted-display (HMD) based VR. This had several ramifications. First, HMDs became economically feasible for consumers and educational institutions to acquire en masse , due to a significant drop in price (Hodgson et al. 2015 ). As Olmos et al. ( 2018 ) remarks, the economic viability of VR has tackled one of the main entry barriers to adopting the technology. And secondly, academic research into the potential benefits of I-VR in education starts to expand, as well as its applied use in pedagogical settings (Hodgson et al. 2019 ). One of VR’s most important contributions to education is that it has allowed students to repeatedly practice complex and demanding tasks in a safe environment. This is particularly true of procedural tasks such as surgical operations or dental procedures that cannot be carried out for real until a certain level of competency has been achieved (Alaraj et al. 2011 ; Larsen et al. 2012 ). Additionally, VR has allowed for students to gain cognitive skills by way of experiential learning, such as exposing them to environments that would be too logistically problematic to visit in reality (Çalişkan 2011 ). For instance, by using a HMD, Bailenson et al. ( 2018 ) were able to expose students to an underwater environment to facilitate learning about climate change. VR has made an important contribution to education in that it has allowed for students to directly experience environments or situations that are difficult to replicate by using traditional teaching methods such as lectures, slideshows, or 2D videos.

A concise definition of VR’s key characteristics is challenging due to the ever-changing nature of the technology. However, Sherman and Craig ( 2003 ) proposed that there are a number of constituent elements that must underpin the VR experience, ultimately leading to the life-like perception of the virtual environment. These include the necessity for VR to be immersive, in that the participant’s own cognitive faculties produce a sense of being present and involved in the virtual space, often with reduced awareness of what is happening in the real-world around them. Additionally, the virtual space should offer a degree of interactivity, in that the user can manipulate the environment and test variables. This can include interacting with objects, virtual avatars, or even collaborating with other real-life users within the computer-generated space.

Definition of key terms

Due to the multidisciplinary nature of VR research and its pedagogical applications, it is important to define key terms used. VR can broadly be broken down into two main categories: desktop VR (D-VR), and immersive-VR (I-VR). D-VR is typically classified as non-immersive, in that a headset is not used, and the participant will be controlling and manipulating the virtual environment on a computer screen with traditional keyboard and mouse hardware (Lee et al. 2010 ). On the other hand, I-VR is typically multi-modal in nature by providing a sense of immersion in the environment through 360° visuals by aid of a HMD, auditory stimulation through the use of earphones, and increasingly the proprioception of limbs by way of controllers and tracking (Freina and Ott 2015 ; Howard-Jones et al. 2015 ; Murcia-López and Steed 2016 ). Although there are a range of HMDs on the market, from high-end hardware like the HTC Vive, to viable low-cost options like the Google Cardboard, they all utilise the same core principals of operation (Brown and Green 2016 ). Typically, a HMD will feature a set of embedded liquid crystal displays (LCD) which will present each eye an image from a slightly different angle. This mimics natural optic function by allowing the wearer to view a stereoscopic image complete with depth perception and a wide field of view. Mobile VR headsets can achieve the same effect using a single display by dividing the screen down the middle and presenting each half to the corresponding eye. Therefore, the current review defines a HMD as a device worn over the head, which provides a stereoscopic computer-generated or 360 ° video image to the user. This includes tethered (connected to a computer), stand-alone (no computer needed), or mobile VR headsets (mobile/cell phone connected to a HMD).

Previous literature and reviews

There have been a number of systematic reviews that have previously explored the relationship between VR and pedagogical attainment. Lee ( 1999 ) reviewed 19 studies from as far back as 1976 and found that 66% of students in simulation groups outperformed those in their respective control groups. However, this review did not focus exclusively on an educational level or age range, so featured both young kindergarten children, as well as higher education students. As a result, the generalisability of VR’s effectiveness as a pedagogical method is difficult to ascertain, with significant differences in age, task difficulty, and applications. Furthermore, all the studies are dated in terms of the technology utilised and feature early D-VR programmes and rudimental computer simulations. This early technology may be primitive when compared with the high-fidelity graphics and immersive components of contemporary technology. Nevertheless, these early studies do help exemplify that the use of technology in education is not a new concept, and computer-based simulations have long been employed as a way of facilitating learning.

A more recent analysis was undertaken by Merchant et al. ( 2014 ), and looked at three specific sub-categories of VR: games, simulations, and virtual worlds. Games give the actor autonomy and freedom to move around the virtual world, testing hypotheses, achieving goals, and eliciting motivation and learning through immersion (Gee 2004 ). Simulations attempt to recreate a real-world environment that can help facilitate learning by allowing for the testing of variables and resulting outcomes. Finally, virtual worlds can provide an immersive or non-immersive sense of presence in a three-dimensional (3D) world, and the ability to manipulate, interact, or construct objects. Furthermore, virtual worlds can give the opportunity for multiple users to interact with one another within the digital environment (Dickey 2005 ). The meta-analysis showed that although game-based VR produced the highest learning outcomes, simulations and virtual worlds were also effective at increasing educational attainment. Once again, the limitation of this review is that it did not restrict its analysis to exclusively one domain of education. Although higher education made up the greatest number of studies, research from elementary and middle school were also included in the analysis.

One of the most recent systematic reviews to look exclusively at I-VR through the utilisation of HMDs was carried out by Jensen and Konradsen ( 2018 ). In their comprehensive search of existing literature published between 2013 and 2017, the review identified 21 quantitative and qualitative papers that focused on both learning outcomes in I-VR, and subjective attitudes and experiences on the part of the user. The review found limited effectiveness of HMD in the acquisition of cognitive, psychomotor, and affective skills when compared with less immersive technologies. However, Jensen and Konradsen ( 2018 ) did highlight the relatively low quality of studies included as a concern, and this may impede the ability to draw firm conclusions about the educational utility of I-VR.

Rationale for review

There are several fundamental reasons that necessitate an updated assessment of the topic area, such as the increase in relevant published literature, as well as the narrow scope of previous reviews. The last major review looking at I-VR and HMDs as an educational tool was carried out by Jensen and Konradsen ( 2018 ), with the most recent studies featured in that paper being published in 2016. Since then, there has been a significant increase in relevant published literature, with > 70% of the papers included in the current review being published since 2017, and therefore not included in the previous systematic review. Additionally, unlike previous reviews, the current examination of I-VR’s pedagogical utility focuses exclusively on studies where I-VR is directly compared to a less immersive method of learning. As a result, the current paper is able to highlight not only whether I-VR is an effective medium, but also whether it is more effective when compared to alternative methods. Additionally, no other systematic review looking at I-VR and HMDs has had a particular focus on the experimental design, assessment measures, and intervention characteristics of the included studies. The review also addresses the underlying methodology of the included studies, to offer an understanding of how I-VR is being employed in experimental literature. Based upon the findings of previous studies as well as areas yet to be sufficiently explored, this paper has a number of core research questions:

To assess the subject area, discipline, and learning domain that I-VR has been employed in.

Understand where I-VR confers an educational benefit in terms of quantitative learning outcomes over non-immersive and traditional teaching methods.

To examine the experimental design of studies, focusing on how learning outcomes are assessed, and how the I-VR intervention is delivered.

To inform future experimental and applied practice in the field of pedagogical I-VR application.

Methodology

Search strategy.

The current systematic review included peer-reviewed journal articles and conference proceedings that passed all the inclusion criteria detailed. An initial scoping review identified seven databases that could be utilised in a comprehensive literature review, as well as associated keywords and search terms. These included Web of Science (Core Collection), Science Direct, Sage, IEEE Xplore, EBSCO, Taylor & Francis, and Google Scholar. These databases encompass a mixture of general, social science, and technological literature.

Each of the seven databases was searched using a series of keywords based on the following Boolean logic string:

("Virtual Reality" OR "Virtual-Reality" OR “Immersive Virtual Reality” OR “Head Mounted Display” OR “Immersive Simulation”) AND (Education OR Training OR Learning OR Teaching)

Due to the scope and parameters of the research objectives, only peer-reviewed literature published between January 2013 and December 2018 was included in the final review. Early access articles due to be published in 2019 were also included if these were found using the database searches. Date criteria was based upon an initial scoping review that found a substantial growth in relevant I-VR literature from 2013 onwards. A major contributing factor was the release of the Oculus Rift Development Kit 1 (DK-1) in early 2013, which is regarded as one of the first economically viable and high quality HMDs that could be used both within educational institutions, and at home (Lyne 2013 ).

The literature search across the databases yielded more than 12,000 references from a variety of sources. After the removal of duplicate records, 9,359 unique references were included for the title and abstract screening stage of the review.

Selection and screening

The open and general nature of the search string used led to a large number of references being returned for screening. As Jensen and Konradsen ( 2018 ) already alluded to in the last major review, VR research transcends various academic disciplines. The result is a lack of a clear taxonomy of definitions and terms. This means a wide net must be cast to ensure comprehensive capture of relevant material. This review defined I-VR as either a completely computer-generated environment, or the viewing of captured 360 ° video through the use of a HMD. Studies that utilised surgical or dental simulators and trainers such as the da Vinci Surgical System, were excluded as these represent a separate domain of both technological and pedagogical application. For example, surgical simulation based VR typically combines computer-generated visuals with simulated surgical tools, haptic feedback, and robotic components (Li et al. 2017 ). This type of technology would therefore not be applicable for general pedagogical application. Additionally, references were excluded if they: (1) focused on using I-VR as a rehabilitation or therapeutic tool; (2) were not in English; or (3) where the full-text was not available.

After title and abstract screening was performed, 197 references remained to be included in the full-text review. Each reference had to pass an inclusion flowchart based on each of the following criteria:

The population being sampled was from a high school, further or higher education establishment, or was an adult education student.

Population sampled did not have a developmental or neurological condition, nor could VR be used as a rehabilitation tool.

Paper described an experimental or quasi-experimental trial with at least one control group.

At least one group had to have undergone an educational HMD I-VR experience, and was compared with another group who underwent a non-immersive or traditional pedagogical method of education (e.g. Desktop VR, PowerPoint, traditional lecture).

A quantitative and objective learning outcome such as tests scores, completion time, or knowledge retention was used to assess effectiveness.

After full-text screening, 29 references passed all stages and were included in the systematic review. See Fig.  1 for a summary of the selection process by stage.

figure 1

Stage-by-stage selection process

Inter-rater reliability checks were conducted at the title and abstract screening stage to assess the agreement of included studies. There were four individual evaluators that assessed the suitability of each reference based upon the inclusion criteria, which yielded an average agreement of 96%. Where any disagreement existed, the paper was discussed among all assessors until a unanimous decision was reached as to its suitability.

Quality assessment tool

To assess the quality of the studies, the Medical Education Research Study Quality Instrument (MERSQI) was used (Reed et al. 2007 ). Although this tool was primarily designed to examine the quality of studies in the field of medical education, it is in practice subject neutral. As the MERSQI assesses not only the quality of experimental design and outcomes measures, but also the assessment instrumentation used, it was viewed as a suitable and comprehensive tool for quality appraisal. In addition, the same instrument was used in a previously peer-reviewed systematic review examining VR, by Jensen and Konradsen ( 2018 ).

The MERSQI tool covers six quality assessment domains. These include: study design, sampling, type of data, validity of evaluation instrument, data analysis, and outcomes. Each domain is scored out of three, with a maximum overall score of 18. Unlike Jensen and Konradsen ( 2018 ), the current review gave full points in the study design category for experimental trials with participant randomisation, as well as appropriate pre-intervention measures. This decision was made as true randomised control trials featuring random sampling is unrealistic in I-VR pedagogical research, as the participant sample can only be drawn from an educational establishment.

Quality of studies

The first domain examined for quality was the study design of the papers. There were 20 studies (69%) that featured an experimental design with stated random allocation of participants between control and experimental group. The review featured nine studies (31%) that were quasi-experimental in nature, meaning there was non-random allocation of participants into experimental groups.

Only one of the studies featured participants being studied at more than one institution, with most of the studies included ( N  = 28) only sampling from a single establishment. All studies produced response rates of over 75%, which means they were given the highest score in that domain.

In terms of the type of data presented, all included studies featured an objective measure of learning outcomes such as test scores or completion times. No studies used self-assessment on the part of the participant to gauge learning outcomes.

The most pronounced weakness of the studies included in the review was the validity of the evaluation instrument used to assess learning outcomes. This domain pertained to the physical assessment instrumentation such as the quiz, test, or questionnaire that was given to the participant. Only six of the included studies (21%) reported the internal structure sufficiently through dimensionality, measurement invariance, or reliability using the criteria set down by Rios and Wells ( 2014 ). In addition, only 10 studies (34%) stated how the content was validated, with the majority ( N  = 19) not reporting this information. Only three studies (Kozhevnikov et al. 2013 ; Makransky et al. 2017 ; Molina-Carmona et al. 2018 ) appropriately outlined both the internal structure and validity of evaluation content. The majority of studies ( N  = 16) did not report either item.

Of the 29 studies in the current review, 26 scored full marks on the data analysis domain with both an appropriate and sufficiently complex analysis and reporting of the findings. Three studies scored lower than this due to reporting descriptive statistics only (Angulo and de Velasco 2013 ; Babu et al. 2018 ; Ray and Deb 2016 ).

Overall, the average quality score of a study in this systematic review was 12.7 with a range of 10.5–14.5 (SD = 1.0). This was 1.8 points higher than the review carried out by Jensen and Konradsen ( 2018 ), which could in part be due to differences in study design criteria which was previously outlined. A full summary of the MERSQI scores for each study can be found in Table 2 in the Appendix.

Subject areas and learning domains

Table 1 provides a summary of all 29 articles that were included in the review. Studies were first categorised by the population that was sampled. Most I-VR studies took place in a higher education establishment (college or university) using undergraduate or postgraduate students ( N  = 25). A smaller number of studies used high school pupils ( N  = 2), or adult education students ( N  = 2) such as those in vocational or work-based programmes.

Each of the included studies were then examined for the topic and subject area they pertained to. This was based upon the nature of the VR experience, participant pool, and intervention. In total, six main subject areas were identified. This included: medicine ( N  = 4), science (biology, chemistry, and physics) ( N  = 13), social science (human geography) ( N  = 1), computer science ( N  = 2), engineering and architecture ( N  = 7), and safety education ( N  = 1). One of the included studies (Molina-Carmona et al. 2018 ) did not neatly fit into one of the pre-defined categories as it utilised I-VR to teach abstract spatial concept abilities to multimedia engineering students. It was therefore categorised as ‘other’. Figure  2 shows the percentage of papers included by subject area.

figure 2

Percentage of papers per subject area

In addition to the subject area, the learning outcomes were also categorised into three specific domains based upon the findings of previous systematic reviews, as well as the taxonomy of learning developed by Bloom et al. ( 1956 ). The first was cognitive which related to studies that intended to teach specific declarative information or knowledge. The second was procedural which intends to teach the user how to perform a specific task or learn psychomotor skills that pertain to a certain activity. Finally, the third learning outcome was affective skills which can be defined as a growth in areas relating to emotion and attitude. Most of the included studies ( N  = 24) concentrated on the cognitive domain, with two studies focusing on purely procedural and psychomotor skills. The remaining studies were a blend of two domains with Sankaranarayanan et al. ( 2018 ) and Smith et al. ( 2018 ) examining both cognitive and procedural skills, and Gutiérrez-Maldonado et al. ( 2015 ) utilising both cognitive knowledge and affective awareness in psychiatric diagnosis training. Figure  3 shows the percentage of studies included by learning domain.

figure 3

Percentage of papers per learning domain

Experimental design

Outcome measures.

A thorough understanding of the role of I-VR as a pedagogical practice can only be fully appreciated when consideration is given to the assessment instrumentation and outcome measures used to assess its utility. As previously mentioned, when analysing the quality of the included studies, it was the evaluation instrumentation itself that was shown to have the most pronounced weakness.

To assess the evaluation instruments being employed, the measures were broken down into two broad domains: outcome measures, and assessment instrumentation. Outcome measures can broadly be defined as how learning outcomes were quantified (e.g. by comparing test scores). Assessment instrumentation pertains to the evaluative instrument itself that is used to measure the learning outcomes (e.g. multiple-choice questionnaire, exam style questions). Twenty-seven of the included studies (93%) used test scores to assess learning outcomes, with the majority using this as their sole method. There were four studies that used completion time as a metric of learning outcome, although only one study (Bharathi and Tucker 2015 ) used this method exclusively. There was one study (Sankaranarayanan et al. 2018 ) that used the correct order of operation in a procedural task as one of its main outcome measures. There were three papers that utilised other outcome measures that could not be easily categorised. For instance Greenwald et al. ( 2018 ) used counting the number of moves needed to complete a task, Webster ( 2016 ) used the performance on a virtual jigsaw puzzle, and Angulo and de Velasco ( 2013 ) used a mixture of scores and evaluations of an architectural space.

Assessment instrumentation

In terms of the direct assessment instrumentation used to examine outcome measures, there was a heavy reliance on the multiple-choice questionnaire (MCQ). There were eighteen (62%) studies that utilised this method of assessment, with the majority of those using it as their sole evaluation instrument. Only five studies used extended answer questions (long or short form) to probe for a deeper understanding of the educational content, which was usually done in combination MCQs. The studies that included the teaching of procedural skills used marking criteria and checklists to assess whether the correct order was being followed. For instance Yoganathan et al. ( 2018 ) had an expert assessor use marking criteria to assess the knot tying skills of students. Similarly, Smith et al. ( 2018 ) had evaluators observe students with a decontamination checklist which evaluated performance based upon certain key tasks that were performed.

There were a smaller number of studies that used more novel instrumentation and methods for evaluation, such as the utilisation of labelling and identifying parts of a 3D model (e.g. Babu et al. 2018 ; Moro et al. 2017 ; Stepan et al. 2017 ). Fogarty et al. ( 2017 ) probed spatial and conceptual understanding in their assessment instrument by having participants draw shapes based on their understanding of structural engineering principles. Additionally, Alhalabi ( 2016 ) used quizzes on both mathematical knowledge, and the appropriate understanding of graphics and charts as an assessment measure for engineering students.

There were three studies (Liou and Chang 2018 ; Madden et al. 2018 ; Ray and Deb 2016 ) where the nature of the assessment instrumentation could not be definitively ascertained from the description.

The majority of studies (62%) utilised the pretest–posttest design by comparing the test scores pre-intervention with those after the I-VR experience. The remainder of the studies tended to assess post-intervention scores only, usually by comparing the difference in learning outcome between I-VR and one or more control group. Less conventional means of post-intervention comparison was sometimes utilised, such as Johnston et al. ( 2018 ) comparing the average score on a specific exam question that pertained to an I-VR experience that some student did or did not undertake.

There were four studies that examined the short to medium term retention rate of information and learning through follow-up assessment. This ranged from as soon as 1 day after the initial I-VR experience (Babu et al. 2018 ), through to 6 months post-intervention (Smith et al. 2018 ). Olmos-Raya et al. ( 2018 ) and Stepan et al. ( 2017 ) had follow-up assessments at 1-week and 8-weeks, respectively.

Intervention characteristics

In addition to having appropriate assessment measures, it is also important to examine the nature of the I-VR intervention itself. The most popular HMDs used were the Oculus ( N  = 13) and HTC Vive ( N  = 7). There were seven studies that used a form of mobile VR headset such as the Google Cardboard or Samsung Gear VR. In one study (Yoganathan et al. 2018 ) the exact HMD system used could not be definitively ascertained. Figure  4 provides a breakdown of the HMDs used in the included studies.

figure 4

HMDs used in studies

Most studies (72%) featured only a single intervention with the I-VR experience, meaning that the student was exposed to the technology just once. There were a few exceptions to this, with Ostrander et al. ( 2018 ) having seven individual I-VR experiences in their manufacturing lesson, as well as Ray and Deb ( 2016 ) utilising smartphone based I-VR over the course of 16 sessions. Other studies allowed a greater degree of freedom in the number of interventions or times that a student could use I-VR. This was usually a result of time being dedicated to the technology through scheduled classes or lab times (e.g. Akbulut et al. 2018 ; Alhalabi 2016 ; Molina-Carmona et al. 2018 ). Despite this, the I-VR intervention was usually a single and isolated one.

As well as most of the studies featuring a single intervention, the exposure duration was also typically short, ranging from 6 to 30 mins. Generally, the exception to this was when the I-VR exposure lasted as long as it took the participant to complete a specific task, assessment, or procedure within the immersive environment (e.g. Babu et al. 2018 ; Bharathi and Tucker 2015 ; Greenwald et al. 2018 ; Sankaranarayanan et al. 2018 ). Molina-Carmona et al. ( 2018 ) supplemented the limited intervention duration by allowing participants to take the HMD away with them, so they could access the educational content for 2 weeks outside the classroom. However, just as with the number of interventions, exposure duration tended to be short, lasting on average 13 mins for those I-VR experiences that had a set time limit.

Most of the studies (62%) utilised I-VR as the sole method of learning, and did not combine the technology with additional pedagogical practices or materials to encourage learning. Only a limited number of studies (38%) supplemented the I-VR lesson by providing additional aids that were designed to complement the educational experience. For example, Smith et al. ( 2018 ) and Stepan et al. ( 2017 ) both had participants use web-based modules and textbooks in addition to the I-VR experience before testing them on learning outcomes. A number of the included studies also utilised lecture based instruction or scheduled class time to operate in tandem with the I-VR environments (e.g. Akbulut et al. 2018 ; Fogarty et al. 2017 ; Johnston et al. 2018 ; Ray and Deb 2016 ; Sankaranarayanan et al. 2018 ).

Theoretical frameworks

A fundamental component of any educational tool or activity is to ground its use in learning theory or educational paradigms. Learning theories can broadly be broken down and defined by proposals regarding how student imbibe, process, and retain the information that they have learned (Pritchard 2017 ; Schunk 2011 ). When applied to educational I-VR, these theories should provide a pedagogical framework and foundation as how best to design interventions. Papers were examined for explicit statements regarding the theoretical basis for the study. Those papers that only mentioned theoretical approaches as part of the introduction or literature review were not deemed to have explicitly stated them. The majority of studies ( N  = 24) made no mention of a theoretical approach underpinning the intervention. There were two studies that applied a generative learning framework (Makransky et al. 2017 ; Parong and Mayer 2018 ). This can be defined as an approach where the learner will actively integrate new knowledge with information that is already stored in the brain (Osborne and Wittrock 1985 ). Webster ( 2016 ) employed Mayer's ( 2009 , 2014 ) Cognitive Theory of Multimedia Learning (CTML). CTML proposes a dual channel approach where visual and auditory information is actively processed, organised, and then stored in the brain. This is contingent on neither channel (visual or auditory) becoming overloaded with information. Smith et al. ( 2018 ) used the NLN Jeffries Simulation Theory as their theoretical basis. This theory, most commonly employed in nursing education, is where students learn information as part of a simulated experience (Jeffries et al. 2015 ). For the teaching of vocational skills, Babu et al. ( 2018 ) stated that their approach aligned with situated learning. Situated learning employs a constructivist approach in that students learns professional skills by actively participating in the experience (Huang et al. 2010 ).

Learning outcomes

For I-VR to gain wide-spread acceptance as a reliable pedagogical method, it must be shown to confer a tangible benefit in terms of learning outcomes over less immersive or traditional teaching methods.

Cognitive studies

There were twenty-four included studies that fell into the cognitive domain and aimed to teach specific declarative information or knowledge through the I-VR environment. The current review found that most studies demonstrated benefits in terms of learning outcomes when using I-VR compared to less immersive methods of learning. A smaller number of studies found no significant advantage regardless of the pedagogical method being utilised. The results of these cognitive studies have been broken down by subject area.

Science based cognitive studies

The review found that cognitive learning activities requiring a high degree of visualisation and experiential understanding may be best facilitated using immersive technologies. For instance, both Liou and Chang ( 2018 ) and Maresky et al. ( 2019 ) found that anatomical learning facilitated by complex 3D visualisations of the human body were more conducive to learning in I-VR compared to traditional learning or independent study. Similarly Lamb et al. ( 2018 ) used a virtual environment that allowed for the manipulation and movement of strands of DNA, which produced better learning outcomes in content tests than a lecture or a serious educational game. Greater attention and engagement with the I-VR environment as measured with infrared spectroscopy was one of the possible explanations given for the effectiveness of the technology. In a study by Johnston et al. ( 2018 ), participants volunteered to take part in a cell biology experience either because they were engaged with the subject matter itself, or wanted supplementary instruction. Johnston et al. ( 2018 ) compared the exam scores of those students who volunteered to take part with those who did not. The study found that participants who underwent the I-VR experience scored 5% higher on the related exam question compared to the rest of the assessment. Those who did not undergo the cell biology I-VR experienced scored on average 35% worse on the same question.

The increase in graphical fidelity afforded by I-VR has allowed not only for the creation of complex computer-generated environments, but also the viewing of high resolution 360° video. In one such study, Rupp et al. ( 2019 ) had participants watch a six minute 360° video about the International Space Station with either a HMD which created a sense of immersion and presence, or on a mobile screen. The research found that those participants in the HMD condition scored significantly higher in a learning outcome test (MCQ) than those who watched the video in the non-immersive condition.

Although I-VR has been shown to confer a benefit in science education, there is evidence to suggest that not all learning objectives can be learned equally well. For instance, in task devised by Allcoat and von Mühlenen ( 2018 ), the researchers found that I-VR conferred a benefit over video or textbook learning when questions required remembering , but not ones pertaining to understanding of the material. The authors suggest that unfamiliarity and the novelty of the I-VR environments could have contributed to the lack of an obvious benefit in the latter domain. Another study that examined specific question types to understand I-VR’s effectiveness was undertaken by Kozhevnikov et al. ( 2013 ). In this study, participants learned more conceptual and abstract relative motion concepts using either I-VR or D-VR. The study demonstrated that those in the I-VR condition performed significantly better in the two-dimensional problems than their D-VR counterparts, although there was no significant difference between groups in problems featuring only one spatial dimension.

There were several studies in the domain of science that showed no obvious benefits to using I-VR over traditional pedagogical methods. Two studies (Greenwald et al. 2018 ; Moro et al. 2017 ) compared science learning in I-VR with desktop based VR and 2D videos. Results showed no clear benefit of I-VR based instruction when comparing the difference and significance of learning outcomes between mediums. Similarly, Stepan et al. ( 2017 ) found that I-VR was no more effective than online textbooks for the teaching of neuroanatomy. Interestingly, the same study found no difference in information retention rates when the participants were reassessed 8-weeks later. Madden et al. ( 2018 ) used I-VR, D-VR, and the traditional ball and stick method to teach astronomy principles pertaining to phases of the moon. The study found that I-VR and D-VR produced comparable test score results, with no significant differences in attainment. However, the authors commented on the encouraging finding that despite being a novel technology to most participants, I-VR still facilitated comparable learning outcomes to more traditional methods.

Despite the majority of studies demonstrating that I-VR learning is more effective or at least on par with traditional pedagogical methods, some studies have shown a detrimental effect of I-VR. Makransky et al. ( 2017 ) used a combination of assessment and EEG to find that an I-VR lab simulation produced significantly poorer test scores than a non-immersive alternative. Similarly, during another science experiment, Parong and Mayer ( 2018 ) found that students who used I-VR during a biology lesson scored significantly poorer than those who learned using a PowerPoint. Both of these studies cited Mayer's ( 2009 , 2014 ) Cognitive Theory of Multimedia Learning as a possible explanation for the poorer performance for I-VR. The researchers postulate that the high-fidelity graphics and animations could have significantly increased cognitive load, which would have detracted from the learning task at hand. It was therefore proposed that a less immersive, yet well designed PowerPoint presentation would facilitate better learning outcomes than a graphically rich I-VR experience.

Engineering and architectural based cognitive studies

I-VR was effective in engineering and architectural education as a tool to visualise key concepts within the discipline. For example, Fogarty et al. ( 2017 ) allowed students to volunteer for an I-VR experience who struggled with the comprehension of spatial arrangements in structural engineering. Before the intervention, those students who volunteered to take part scored significantly poorer than their non-intervention counterparts. At post-test, not only did those who underwent the I-VR experience score significantly higher than they did at pre-test, but they also eliminated the significant difference with the non-intervention group. This would suggest that I-VR could serve an important function in supplementing or assisting learning in those students who are struggling to grasp complex problems relating to their discipline. Interestingly, Angulo and de Velasco ( 2013 ) used many of these same spatial and visualisation principles in a more applied setting. Their study split students into groups who were tasked with designing an architectural space (a health clinic waiting room), either with the assistance of an I-VR design tool (experimental group) or a physical model (control group). The study found the space that gained the most positive affect was designed by the I-VR group.

Webster ( 2016 ) created a graphically rich immersive environment which combined active and passive media with elements of gamification and interactivity to teach corrosion concepts to US army personnel. The study found that although both the I-VR environment and a traditional lecture were effective pedagogical methods for teaching these principles, it was the I-VR condition that produced the highest gain in knowledge acquisition.

There was also some evidence to suggest that I-VR interventions could assist in short-term retention of information in engineering related activities. Babu et al. ( 2018 ) found that although participants performed similarly in a mechanical labelling task using either I-VR or a tablet computer immediately post-intervention, the I-VR group had better retention of knowledge when the test was re-administered 1 day later. Furthermore, those participants in the I-VR group were also less likely to wrongly recall information compared to the non-immersive group on the retention test.

Interestingly, Ostrander et al. ( 2018 ) examined cognitive learning outcomes over seven separate manufacturing tasks utilising I-VR in one group, and a traditional class-based environment in the other. The study found that in six out of seven tasks, I-VR was no more effective than a traditional class where students could interact with the instructor or the physical models that they were accustomed to.

Medical based cognitive studies

Although papers featuring surgical simulators did not form part of this review, there were several applications of I-VR in the field of general medical education. Harrington et al. ( 2018 ) had medical students watch a ten-minute 360° video with slides containing surgical information superimposed over it. This was viewed either on a large television screen, or through a Gear VR headset. The study found no significant differences in knowledge retention scores between those who viewed the information through a HMD, or a traditional television screen. Despite not showing a distinct advantage in cognitive learning outcomes, the authors did suggest that the 360° surgical experience may facilitate a better understanding of how teamwork and interaction takes place within an operating theatre. This type of learning may be more difficult to measure using assessment instrumentation such as the MCQ, but nevertheless it could be that the experiential nature of I-VR may facilitate an understanding of interactions and communications. Smith et al. ( 2018 ) used either I-VR or D-VR on a computer to teach students about decontamination protocols. The research found that I-VR was no more effective than D-VR in a MCQ immediately post-intervention, or at 6-weeks follow-up.

Computer science based cognitive studies

Two studies demonstrated a significant advantage in using I-VR to teach computer science information. For instance, Akbulut et al. ( 2018 ) found that students who underwent an I-VR experience that focused on software engineering principles scored 12% higher than students who did not undergo I-VR learning. Interestingly, in a study by Ray and Deb ( 2016 ) that ran over 16 sessions on microcontrollers in computing, the I-VR group performance lagged behind that of the control group who used slideshows for the first four sessions. It was only on session number five that the I-VR group outperformed the control group, and this performance enhancement remained relatively stable in the majority of the remaining 11 sessions. In effect, it took the I-VR group some time to catch up with the control group, but once they did, they tended to outperform them in the remaining lessons. The authors propose that this may have been due to the novelty of the I-VR equipment which participants took time to become comfortable and competent with.

Other cognitive studies

I-VR was also used by Molina-Carmona et al. ( 2018 ) as a means of spatial ability acquisition and visualisation. The study showed that learning outcomes as assessed by a spatial visualisation test were higher among those who undertook the task in an immersive, compared to a non-immersive environment. There was only one study in the field of social science that used I-VR to teach cognitive information. Olmos-Raya et al. ( 2018 ) used either I-VR or a tablet-based system to teach high school students about human geography. The research found that I-VR produced higher learning gains on a MCQ than the tablet-based system. Further, those who used I-VR performed better than the non-immersive group on a knowledge retention quiz when administered 1-week later.

Procedural studies

Three of the four studies that attempted to utilise I-VR as a means of teaching procedural skills showed a distinct advantage over less immersive methods. Bharathi and Tucker ( 2015 ) found that engineering students were faster in assembling a household appliance in a virtual functional analysis activity in I-VR compared to D-VR. Yoganathan et al. ( 2018 ) also found that medical students were more accurate in knot tying practice when using I-VR as a training tool as opposed to a control group who used a standard video. Medical and surgical residents were also studied by Sankaranarayanan et al. ( 2018 ) who used I-VR as a teaching tool for emergency fire response in an operating theatre environment. This study found that 70% of those who utilised the I-VR training were able to perform the correct procedure in the correct order. This was 50% higher than the control group who were exposed to a presentation and reading material only and did not experience I-VR.

One of the studies found no significant advantage to using I-VR as a learning tool. Smith et al. ( 2018 ) split nursing students into an I-VR group, a D-VR group (desktop PC based), or a written instruction group to learn about appropriate protocols for decontamination. The study found that there was no significant difference in performance between the groups as measured by a decontamination checklist, or the time taken to complete the task. Furthermore, reassessment 6 months later showed that I-VR conferred no advantage in procedural knowledge retention (accuracy and speed) compared to less immersive methods.

Affective studies

Only one of the studies attempted to use I-VR as a pedagogical tool to teach applied behavioural and affective skills. Gutiérrez-Maldonado et al. ( 2015 ) used I-VR in the field of diagnostic psychiatry in an attempt to improve interview skills when assessing patients for an eating disorder. Participants were exposed to a series of virtual patient avatars in either the I-VR condition, or a D-VR condition using stereoscopic glasses. Analysis showed that both conditions were equally as effective, and no significant differences were shown in the acquisition of skills between the two groups. Nevertheless, this was a novel study as it traversed the boundaries between traditional cognitive skill acquisition and applied behavioural and affective change.

Discussion and implications

The purpose of this review was to investigate I-VR’s effectiveness as a pedagogical method in education, as well as examining the experimental design and characteristics of the included studies. In particular, the review found that the utilisation of I-VR is typically restricted to a small number of subject areas such as science and engineering. Furthermore, a heavy reliance has been placed on the MCQ and test score measures to assess learning outcomes. In addition, I-VR interventions were typically short and isolated, and were not complemented with additional or supplementary learning material. Despite this, most studies did find a significant advantage of using I-VR over less immersive methods of learning. This was the case particularly when the subject area was highly abstract or conceptual, or focused on procedural skills or tasks.

Is the utilisation of I-VR within education restrictive?

The findings of the review suggest a relatively homogenous application of I-VR in terms of both the subject areas represented, as well as the learning domain being taught. Almost 70% of the studies were from the field of science or engineering, with other subjects being marginally represented. It is worth noting, however, that although medical disciplines made up a small proportion of the studies included (14%), this was because most medical applications of I-VR feature surgical simulators and therefore were not part of the current review’s inclusion criteria. Most studies utilised I-VR as a way of teaching cognitive skills, with only a handful examining the procedural or affective applications.

The findings of the review raise several issues when trying to assess the general effectiveness of I-VR in education. Similar to the findings of others (e.g. Jensen and Konradsen 2018 ; Radianti et al. 2020 ), the arts, humanities, and social sciences were underrepresented in in the current review. This makes generalisable conclusions as to the cognitive benefit of the technology in these subjects challenging. One major reason for this under representation may be the lack of I-VR learning content, experiences, and teaching tools. Jensen and Konradsen ( 2018 ) highlighted that instructors are restricted to the material published and produced by VR designers, and this may not necessarily meet the individual needs of the teacher, or the learning outcome trying to be achieved. The skillset needed to produce and create wholly virtual environments that can be rendered and displayed in a HMD is still demanding, despite the release of affordable VR creation suites. Therefore, the bespoke I-VR experiences required to teach social science lessons (or indeed any subject) is completely dependent on an appropriate I-VR tool already existing or having the technical proficiency to create one. A potential solution to the lack of bespoke material could be the examination of the pedagogical effectiveness of HMD 360° video in the classroom, as opposed to computer-generated environments. This content is comparatively easier to create using appropriate video equipment and can be tailored to the individual needs of the instructor or student group. Widespread research that examines the potential of I-VR in a multitude of diverse disciplines and learning domains will continue to be constrained by the availability of the requisite material. That is until such a time where bespoke and individually tailored I-VR experiences become more accessible.

Implications of outcome measures and assessment instrumentation

One of the most striking characteristics of the assessment instrumentation used in the studies was the reliance on the MCQ to assess learning outcomes. Although there have been many debates on the respective advantages and disadvantages of utilising the MCQ, it has generally been considered that it is most appropriate for testing large amounts of surface knowledge over the course of an entire module or syllabus (Excell 2000 ). As O’Dwyer ( 2012 ) points out, the assessment instrumentation encourages comprehensive learning of the entirety of the taught material, as opposed to just specific components. However, since most of the studies featured single interventions of between 6 and 30 mins, doubts are cast on whether MCQs are the most appropriate way to assess learning. Since the MCQ was most commonly administered immediately after the I-VR experience, much of the information may still be stored in short-term memory, and this may not give an accurate reflection of more comprehensive learning or long-term retention.

A second disadvantage associated with the heavy reliance on the MCQ is the limited breadth of knowledge that can be assessed. In Jensen and Konradsen’s ( 2018 ) systematic review, the researchers found that none of the cognitive studies went beyond teaching lower level cognitive skills as defined by Bloom’s taxonomy (Bloom et al. 1956 ). Similar results were found in the current review, with most studies requiring only a knowledge of previously learned material to successfully achieve the desired learning goal. Previous research on pedagogical assessment material (e.g. Ozuru et al. 2013 ) has suggested that the MCQ cannot assess higher levels of cognitive understanding or conceptual knowledge. Therefore, it may not only be the nature of the I-VR experience itself that restricts the learning of higher level cognitive skills, but also the restrictive nature of the assessment instrumentation that may impede an appropriate demonstration of learning outcomes. The utilisation of short or long form answers could be able to provide a more appropriate measure of the depth of learning achieved, giving the student an opportunity to demonstrate their conceptual knowledge of a given subject. Furthermore, I-VR research could benefit by expanding the very definition of what constitutes a learning outcome. This could be achieved by not relying exclusively on test score comparisons, but rather examine how I-VR could be used to foster deeper conceptual understanding through experiential learning and subsequent classroom discussions with peers or instructors.

Implication of intervention characteristics for learning outcomes

The current review examined how I-VR is being utilised in experimental and applied settings, and the implications this has for assessing its pedagogical suitability. In most studies, the participant took part in a single I-VR experience that was also short in duration. This presents several key challenges. Most importantly, the novelty of the I-VR technology itself may have impeded the learning experience of the user, especially if they had never used the technology before or were unfamiliar with it. This seemed to be demonstrated by Ray and Deb ( 2016 ) who found that in the initial sessions of I-VR learning, performance was on average poorer than those who underwent traditional teaching methods. It was only after the participants began to become familiar with the technology (on session number five) that learning surpassed the control group. Similarly, studies that allowed for extended exposure to I-VR (e.g. Akbulut et al. 2018 ; Alhalabi 2016 ; Molina-Carmona et al. 2018 ), either through free navigation, repeated sessions, or scheduled class time, tended to show an advantage of using I-VR over non-immersive or traditional methods. It is therefore important to address the potentially negative influence that I-VR’s novelty as a learning tool may have, especially when outcomes are directly compared to another medium or method. Scepticism for media comparison studies was highlighted in the 1980s by Clark ( 1983 ), and then later re-addressed by Parong and Mayer ( 2018 ). As Parong and Mayer ( 2018 ) put it, the side-by-side comparison of two learning methods is an “apples-to-oranges type of comparison” (p. 788). This “apples-to-oranges” comparison is made starker when considering that I-VR is an unfamiliar technology to most in an educational capacity, and its pedagogical outcomes are being directly compared with familiar methods such as textbooks or lectures. It is important to consider that the novelty of HMDs and I-VR may hinder learning outcomes and classroom application, and it is therefore prudent to ensure that the degree of familiarity with I-VR technology is factored into any direct comparison with other methods. In practice, this could mean that participants require extended familiarisation trials or free navigation before the start of experimental studies as a means of mitigating against potential problems caused by technological novelty.

In addition to the short intervention and exposure time, most studies did not complement I-VR with an additional method of teaching or self-learning. The limited number of studies that did tended to utilise web-based textbooks or modules, as well as lectures and scheduled class time. Encouragingly, those studies that combined or supplemented traditional class-based learning with I-VR (e.g. Akbulut et al. 2018 ; Fogarty et al. 2017 ; Johnston et al. 2018 ; Sankaranarayanan et al. 2018 ; Yoganathan et al. 2018 ) tended to show a learning advantage. This suggests that I-VR may be best employed as form of blended or multi-modal learning to supplement and complement class-based instruction (Garrison and Kanuka 2004 ). An area for investigation would be to examine I-VR’s application longitudinally in a natural classroom environment. The current review contained only a limited number of studies that employed this approach, however, by implementing and studying how I-VR can be adopted and integrated into a module or syllabus, a clearer picture of its capabilities can emerge.

Learning theories ultimately provide a theoretical framework and foundation as how best to design educational interventions (Pritchard 2017 ; Schunk 2011 ). However, the review found that few papers explicitly state that any predetermined learning theory was used to advise the characteristics or methods of the study. Similar findings were reported in a systematic review by Radianti et al. ( 2020 ) examining I-VR use in higher education exclusively. Radianti et al.’s ( 2020 ) review found that in around 70% of the 38 studies included, no learning theory was mentioned as forming the foundation of the VR activity. Several studies have shown that educators regard clear pre-defined intervention characteristics and objectives as essential components of I-VR teaching (Fransson et al. 2020 ; Lee and Shea 2020 ). It is therefore essential that future experimental and applied research is based on a sound theoretical basis that can advise how the technology can be appropriately utilised and assessed.

Learning outcomes in I-VR

The current review examined learning outcomes across three domains: cognitive, procedural, and affective. By far the most popular domain was the teaching of cognitive skills and knowledge which made up 83% of the studies in the current review. Around half of those demonstrated a positive effect on learning when using I-VR over less immersive pedagogical methods. Most of the remaining studies showed no significant effect either way, with only a small number of papers exhibiting detrimental results. Researchers have suggested that the increased levels of immersive content that stimulate multisensory engagement can ultimately lead to more effective learning outcomes (Webster 2016 ). When this is implemented in cognitive learning activities that require a high degree of spatial understanding and visualisation (e.g. Maresky et al. 2019 ), I-VR can allow the user to gain insights that are difficult to reproduce in reality. This review has already identified scientific subjects such as biology and physics as promising avenues for educational I-VR implementation. However, other scientific disciplines that require abstract or conceptual understanding (e.g. chemistry, mathematics) could also benefit from the visualisation afforded by I-VR.

Studies that utilised I-VR for the teaching of procedural skills and knowledge produced encouraging results, with three of the four studies finding a significantly positive increase in learning (Bharathi and Tucker 2015 ; Sankaranarayanan et al. 2018 ; Yoganathan et al. 2018 ). Interestingly, two of the studies featured a transfer component by having the user first practice the procedure in I-VR, and then use this form of experiential learning to complete a task in the real world. Yoganathan et al. ( 2018 ) had students practice how to tie a surgical knot in I-VR and then complete this task for real in-front of an expert. Sankaranarayanan et al. ( 2018 ) had medical students learn how to deal with an operating theatre fire by first practicing the procedure in I-VR, and then applying this knowledge to a mock emergency in a real operating room. Both studies found a positive effect of using I-VR as the training method by demonstrating improved results when performed in a real environment. These are encouraging findings for I-VR’s effectiveness in psychomotor and procedural education, as there has been a degree of scepticism over whether I-VR simply produces a “getting good at the game” effect. For instance, Jensen and Konradsen ( 2018 ) point out that the honing of procedural skills within I-VR may simply lead to the participant becoming proficient when performing the task virtually, and this may not necessarily transfer to the real world. The current review has identified that the two procedural studies that implemented a transfer task did indeed demonstrate a significant benefit to using I-VR as an initial education method. This demonstrates that virtual training can be a successful precursor to implementation in the real world. This suggests that I-VR could be useful in educating students in dangerous vocational subjects such as electrical engineering without risk to themselves or others. However, this view is based on a small number of studies, and it is therefore important that future procedural tasks utilise a transfer activity to understand the potential scope and parameters surrounding I-VR training and real-world application.

Only one of the studies had a firm focus on the training of affective skills, namely by using I-VR as a way of teaching diagnostic interview techniques in a psychiatric setting (Gutiérrez-Maldonado et al. 2015 ). Although this study found no clear advantage to using I-VR, other research out with the domain of education has demonstrated promising results in utilising the technology for affective and behavioural change. This included applying the technology successfully in areas such as exposure therapy, anxiety disorder treatment, and empathy elicitation (Botella et al. 2017 ; Maples-Keller et al. 2017a , b ; Schutte and Stilinović 2017 ). As a result of the strong non-educational body of literature suggesting I-VR can facilitate affective and behavioural change, future research should examine how this can be applied in an educational context, and then transferred to real-world scenarios. For instance, in their psychiatric interview experience, Gutiérrez-Maldonado et al. ( 2015 ) had users interact solely with virtual avatars, and did not have the participants demonstrate their learning with a real actor or patient. Therefore, just like with procedural skill acquisition, affective I-VR experiences should seek to understand how virtual learning can then be applied to real situations.

Implications and future practice

The current review has been able to identify a body of experimental and applied research that show the potential benefits of using I-VR in education. It has already been noted that I-VR has traditionally been used to teach low level or fundamental skills and knowledge, and has not necessarily been used to facilitate what Bloom et al. ( 1956 ) would consider higher level learning. This would include analysing and evaluating experience. By expanding the definition of learning outcomes to encompass potential benefits such as an increased depth of understanding or the ability to identify complex themes, pedagogical practice can take advantage of the inherent strength of the medium. These should be comprehensively analysed to investigate learning outcomes that go beyond simple test scores.

The review has also been able to identify areas for improvement in future studies, which would address confounding variables and expand the scope of research. Firstly, as Allcoat and von Mühlenen ( 2018 ) suggest, the novelty of I-VR could hamper learning outcomes due to unfamiliarity with the technology. Therefore, it is important to factor in an extended familiarisation or free navigation period that would help alleviate this concern. Additionally, follow-up qualitative analysis such as interviews or focus groups could help explore the phenomenology or direct experience of using I-VR, and highlight concerns relating to unfamiliarity or technological anxiety. The biggest concern relating to the assessment instrumentation was the over reliance on the MCQ (62% of studies used it as the sold method of assessment). Although this method is deemed appropriate for assessing large amounts of surface knowledge, it may not reveal more nuanced forms of learning that extend beyond mere recall of information. Therefore, long form essay questions, oral examinations, or group discussions could be used to facilitate students’ ability to present their in-depth understanding and applied knowledge. Future research must base the nature of these interventions on a sound theoretical framework. This would assist in identifying specific learning objectives and methods of assessments. An explicit theoretical approach was commonly lacking in the included studies.

I-VR has already been demonstrated to be an effective tool in non-pedagogical behaviour change, such as treating phobias, mental health conditions, or as a tool for rehabilitation (Botella et al. 2017 ; Maples-Keller et al. 2018; Ravi et al. 2017 ). Research should therefore concentrate on I-VR’s potential as an acquisition tool for affective skills. There is already a strong body of evidence suggesting I-VR experiences can elicit high levels of empathetic response and perspective taking, and this should be explored within an educational context (Herrera et al. 2018 ; Shin 2018 ). For example, Dyer et al. ( 2018 ) used I-VR to allow health care students to take the perspective of an older patient with age-related medical conditions, which led to increased empathy. Future studies should investigate whether this perspective taking ability can lead to higher domains of learning, such as evaluating one’s actions, applying problem solving skills, or creating new solutions as a direct result of the insights they received from I-VR. This will require researchers and instructors to carefully consider their tools for evaluation and assessment, perhaps incorporating mixed-methods to give a more holistic overview of learning achieved.

Conclusions

The current review found that I-VR conferred a learning benefit in around half of cognitive studies, especially where highly complex or conceptual problems required spatial understanding and visualisation. Although many studies found no significant benefit of using I-VR over less immersive technology, only a small number resulted in detrimental effects on learning outcomes. However, the homogenous nature of assessment instrumentation, such as an over reliance on the MCQ may have stifled the ability for participants to demonstrate learning outcomes beyond low level cognitive knowledge. Short exposure times and isolated interventions could also pose a problem as the novel nature of the technology could negatively impact the amount of learning able to be imbibed. Encouragingly, most procedural tasks did show a benefit to utilising I-VR, and furthermore, there was evidence that virtual skill acquisition could be transferred successfully to real world problems and scenarios. The ability to repeatedly practice a procedure in a safe environment whilst expending little resources could be one of the most advantageous and intrinsic benefits of I-VR technology. Although affective behavioural change has been widely studied in non-educational applications of I-VR, the domain was underrepresented in the current review, and is an important area for future investigation.

Over the coming years, technological advancement, an increase in creative content, and the possibilities for instructors to create bespoke I-VR experiences will all contribute to I-VR’s potential as a teaching tool. It is essential therefore that the implementation of such technology is based on sound theoretical and experimental evidence in order to ensure that the I-VR is utilised correctly, and to its full potential.

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Hamilton, D., McKechnie, J., Edgerton, E. et al. Immersive virtual reality as a pedagogical tool in education: a systematic literature review of quantitative learning outcomes and experimental design. J. Comput. Educ. 8 , 1–32 (2021). https://doi.org/10.1007/s40692-020-00169-2

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Some Students Do Better in Online School

Though detrimental to most, in los angeles, virtual learning actually improved test scores for 10 percent of students..

  • By Dylan Walsh
  • March 12, 2024
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When COVID-19 spread globally in spring 2020, hundreds of millions of students across the world had no choice but to attend school remotely. The consensus now is that the outcomes were overwhelmingly negative. Closing schools created sizable learning losses and likely widened racial and economic achievement gaps.

Yet schools continue to offer—and even expand—remote-learning options. And demand has grown strongly. Between 2021 and 2022, there was a 47 percent increase in families enrolling in exclusively virtual schools, according to the National Center for Education Statistics.

Why are schools and families opting for online learning given the evidence from the past few years? Investigating this question, Brown’s Jesse Bruhn , Chicago Booth’s Christopher Campos , and University of Texas’s Eric Chyn  find that while remote schooling may be detrimental to learning for most students, a specific subset appears to have benefited from it.

The researchers ran a two-part survey in Los Angeles, where the school district fully returned after more than a year of remote learning in fall 2021 but said it would maintain an online option—and then opened 60 new virtual academies in 2023. In the first survey, conducted in April 2022, Bruhn, Campos, and Chyn asked 100,000 families with children in grades 3–8 or 11 questions about their experience with remote learning, including whether they were satisfied with the virtual option and whether they felt their child excelled relative to in-person learning.

Who benefited from a virtual classroom? 

For most students, the research finds, online schooling brought down test scores. But students whose families had a high preference for remote learning saw an improvement, possibly because these students learn best at their own pace or with less social pressure.

The second part of the survey gave parents 10 hypothetical scenarios, each asking which of three schools they preferred. The schools varied along three attributes: distance from survey takers’ home, academic achievement of the student body, and instruction being either remote or in person. By pooling answers to these surveys, the researchers were able to construct a picture of school preference, including how much demand families have for remote learning. They matched these results with test scores from the 2021–22 school year to connect this demand with student outcomes. (The sample of parents who responded to survey tended to have higher-achieving students who were less likely to be in special education.)

In many ways, the results reinforce the current narrative of remote schooling: 62 percent of parents, reflecting back on a year when school buildings were closed, said their child did not enjoy remote learning, and nearly 80 percent said they were unlikely to choose remote learning in the future. The hypothetical choice experiment reveals that academic achievement at a given school would need to increase by 40 percent for most parents to accept remote over in-person learning. That’s an unlikely scenario, since academic performance for the average student dropped when attending school remotely.

But 22 percent of survey takers said their student excelled in remote learning. While most students who went remote saw a decline in test scores, about 10 percent performed better—and their parents expressed a preference for remote learning. The researchers can’t explain why this small group of students benefited, but several theories exist. Among them, is that bullying declined during remote learning, as a team of researchers from Boston University find, in which case it’s possible that reduced social pressure led to academic gains.

The findings reveal a gap in how educators and policy makers understand the potential of remote learning. To accept the average experience of students over the course of the pandemic as universally true, Campos says, ignores the fact that some kids benefit from staying home, that there is important variability in how receptive families are to the upsides of virtual schooling.

“Discourse in the press and academia thus far tends to simply lump the issue into negative territory,” he says. “This does tend to be true on average, but policy makers need to understand these families in the other 10 percent, and perhaps better target them with remote options. There is a lot more to be learned about remote learning in the postpandemic landscape.”

Works Cited

  • Esteban M. Aucejo, Jacob French, Maria Paola Ugalde Araya, and Basit Zafar, “The Impact of COVID-19 on Student Experiences and Expectations: Evidence from a Survey,” Journal of Public Economics, November 2020.
  • Andrew Bacher-Hicks, Joshua Goodman, Jennifer Greif Green, and Melissa K. Holt, “The COVID-19 Pandemic Disrupted Both School Bullying and Cyberbullying,” American Economic Review, September 2022.
  • Jesse Bruhn, Christopher Campos, and Eric Chyn, “Who Benefits from Remote Schooling? Self-Selection and Match Effects,” Working paper, July 2023.

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The reality of virtual schools: A review of the literature

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2009, Computers & Education

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Thomas C Reeves , Michael Barbour

Virtual schooling was first employed in the mid-1990s and has become a common method of distance education used in K-12 jurisdictions. The most accepted definition of a virtual school is an entity approved by a state or governing body that offers courses through distance delivery – most commonly using the Internet. While virtual schools can be classified in different ways, the three common methods of delivery are by independent, asynchronous or synchronous means. Presently, the vast majority of virtual school students tended to be a select group of academically capable, motivated, independent learners. The benefits associated with virtual schooling are expanding educational access, providing high-quality learning opportunities, improving student outcomes and skills, allowing for educational choice, and achieving administrative efficiency. However, the research to support these conjectures is limited at best. The challenges associated with virtual schooling include the conclusion that the only students typically successful in online learning environments are those who have independent orientations towards learning, highly motivated by intrinsic sources, and have strong time management, literacy, and technology skills. These characteristics are typically associated with adult learners. This stems from the fact that research into and practice of distance education has typically been targeted to adult learners. The problem with this focus is that adults learn differently than younger learners. Researchers are calling for more research into the factors that account for K-12 student success in distance education and virtual school environments and more design research approaches than traditional comparisons of student achievement in traditional and virtual schools.

literature review virtual schools

Michael Barbour

A new report compares the performance of Florida Virtual School (FLVS) students with students in traditional brick-and-mortar schools and concludes the FLVS students perform about the same or somewhat better on state tests and at a lower cost. The report claims to be the first empirical study of K-12 student performance in virtual education. This is not correct, and the report in fact confirms the findings and repeats the methodological flaws and limitations of previous research. The report’s findings fail to account for the potential bias of student selectivity in the FLVS sample, the potential impact of regression effects, differential mortality in the two groups, and the fact that the virtual environment is simply a delivery medium. Given the limitations of research such as this new study, researchers have moved beyond simply investigating whether one medium is better than the other and begun—and need to continue—investigating under what conditions K-12 online and blended learning can be effectively designed, delivered, and supported.

kevoliver.com

Ruchi Patel

Charles Hodges , Michael Barbour

Are you about to start developing new virtual schooling opportunities for your students in a K-12 school or university setting? Bring your questions and concerns to this panel of online learning experts where we will address any pertinent issue from recruiting faculty and starting new programs to evaluating and improving existing programs to the benefits and drawbacks of private/public partnerships. No topic is off limits. This panel session will depend heavily on audience participation so come prepared with your questions and concerns to drive the discussion and to take advantage of the expertise of this diverse group of online learning experts—all on one panel!

Cathy Cavanaugh

The community of K–12 education has seen explosive growth over the last decade in distance learning programs, defined as learning experiences in which students and instructors are separated by space and/or time. While elementary and secondary students have learned through the use of electronic distance learning systems since the 1930s, the development of online distance learning schools is a relatively new phenomenon. Online virtual schools may be ideally suited to meet the needs of stakeholders calling for school choice, high school reform, and workforce preparation in 21st century skills. The growth in the numbers of students learning online and the importance of online learning as a solution to educational challenges has increased the need to study more closely the factors that effect student learning in virtual schooling environments. This meta-analysis is a statistical review of 116 effect sizes from 14 webdelivered K–12 distance education programs studied between 1999 and 2004. The analysis shows that distance education can have the same effect on measures of student academic achievement when compared to traditional instruction. The study-weighted mean effect size across all outcomes was -0.028 with a 95 percent confidence interval from 0.060 to -0.116, indicating no significant difference in performance between students who participated in online programs and those who were taught in face-to-face classrooms. No factors were found to be related to significant positive or negative effects. The factors that were tested included academic content area, grade level of the students, role of the distance learning program, role of the instructor, length of the program, type of school, frequency of the distance learning experience, pacing of instruction, timing of instruction, instructor preparation and experience in distance education, and the setting of the students.

This qualitative study examined a Canadian virtual school learning experience for students and the kinds of support and assistance most frequently used and valued by students learning in a virtual environment. Students were interviewed and observed during their virtual school classes. In-school teachers were also interviewed and online teachers were also observed. Data were analyzed using the constant comparative method. Findings indicated that during their scheduled asynchronous class time students were often assigned seatwork or provided time to work on assignments, however, students rarely used this time to complete virtual schoolwork. It was during their synchronous class time that both the students and the online teachers were most productive. Students sought assistance from local classmates before turning to online teacher or in-school teachers, and did not use the other support systems provided by the virtual school.

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Impacts of digital technologies on education and factors influencing schools' digital capacity and transformation: A literature review

Stella timotheou.

1 CYENS Center of Excellence & Cyprus University of Technology (Cyprus Interaction Lab), Cyprus, CYENS Center of Excellence & Cyprus University of Technology, Nicosia-Limassol, Cyprus

Ourania Miliou

Yiannis dimitriadis.

2 Universidad de Valladolid (UVA), Spain, Valladolid, Spain

Sara Villagrá Sobrino

Nikoleta giannoutsou, romina cachia.

3 JRC - Joint Research Centre of the European Commission, Seville, Spain

Alejandra Martínez Monés

Andri ioannou, associated data.

Data sharing not applicable to this article as no datasets were generated or analysed during the current study.

Digital technologies have brought changes to the nature and scope of education and led education systems worldwide to adopt strategies and policies for ICT integration. The latter brought about issues regarding the quality of teaching and learning with ICTs, especially concerning the understanding, adaptation, and design of the education systems in accordance with current technological trends. These issues were emphasized during the recent COVID-19 pandemic that accelerated the use of digital technologies in education, generating questions regarding digitalization in schools. Specifically, many schools demonstrated a lack of experience and low digital capacity, which resulted in widening gaps, inequalities, and learning losses. Such results have engendered the need for schools to learn and build upon the experience to enhance their digital capacity and preparedness, increase their digitalization levels, and achieve a successful digital transformation. Given that the integration of digital technologies is a complex and continuous process that impacts different actors within the school ecosystem, there is a need to show how these impacts are interconnected and identify the factors that can encourage an effective and efficient change in the school environments. For this purpose, we conducted a non-systematic literature review. The results of the literature review were organized thematically based on the evidence presented about the impact of digital technology on education and the factors that affect the schools’ digital capacity and digital transformation. The findings suggest that ICT integration in schools impacts more than just students’ performance; it affects several other school-related aspects and stakeholders, too. Furthermore, various factors affect the impact of digital technologies on education. These factors are interconnected and play a vital role in the digital transformation process. The study results shed light on how ICTs can positively contribute to the digital transformation of schools and which factors should be considered for schools to achieve effective and efficient change.

Introduction

Digital technologies have brought changes to the nature and scope of education. Versatile and disruptive technological innovations, such as smart devices, the Internet of Things (IoT), artificial intelligence (AI), augmented reality (AR) and virtual reality (VR), blockchain, and software applications have opened up new opportunities for advancing teaching and learning (Gaol & Prasolova-Førland, 2021 ; OECD, 2021 ). Hence, in recent years, education systems worldwide have increased their investment in the integration of information and communication technology (ICT) (Fernández-Gutiérrez et al., 2020 ; Lawrence & Tar, 2018 ) and prioritized their educational agendas to adapt strategies or policies around ICT integration (European Commission, 2019 ). The latter brought about issues regarding the quality of teaching and learning with ICTs (Bates, 2015 ), especially concerning the understanding, adaptation, and design of education systems in accordance with current technological trends (Balyer & Öz, 2018 ). Studies have shown that despite the investment made in the integration of technology in schools, the results have not been promising, and the intended outcomes have not yet been achieved (Delgado et al., 2015 ; Lawrence & Tar, 2018 ). These issues were exacerbated during the COVID-19 pandemic, which forced teaching across education levels to move online (Daniel, 2020 ). Online teaching accelerated the use of digital technologies generating questions regarding the process, the nature, the extent, and the effectiveness of digitalization in schools (Cachia et al., 2021 ; König et al., 2020 ). Specifically, many schools demonstrated a lack of experience and low digital capacity, which resulted in widening gaps, inequalities, and learning losses (Blaskó et al., 2021 ; Di Pietro et al, 2020 ). Such results have engendered the need for schools to learn and build upon the experience in order to enhance their digital capacity (European Commission, 2020 ) and increase their digitalization levels (Costa et al., 2021 ). Digitalization offers possibilities for fundamental improvement in schools (OECD, 2021 ; Rott & Marouane, 2018 ) and touches many aspects of a school’s development (Delcker & Ifenthaler, 2021 ) . However, it is a complex process that requires large-scale transformative changes beyond the technical aspects of technology and infrastructure (Pettersson, 2021 ). Namely, digitalization refers to “ a series of deep and coordinated culture, workforce, and technology shifts and operating models ” (Brooks & McCormack, 2020 , p. 3) that brings cultural, organizational, and operational change through the integration of digital technologies (JISC, 2020 ). A successful digital transformation requires that schools increase their digital capacity levels, establishing the necessary “ culture, policies, infrastructure as well as digital competence of students and staff to support the effective integration of technology in teaching and learning practices ” (Costa et al, 2021 , p.163).

Given that the integration of digital technologies is a complex and continuous process that impacts different actors within the school ecosystem (Eng, 2005 ), there is a need to show how the different elements of the impact are interconnected and to identify the factors that can encourage an effective and efficient change in the school environment. To address the issues outlined above, we formulated the following research questions:

a) What is the impact of digital technologies on education?

b) Which factors might affect a school’s digital capacity and transformation?

In the present investigation, we conducted a non-systematic literature review of publications pertaining to the impact of digital technologies on education and the factors that affect a school’s digital capacity and transformation. The results of the literature review were organized thematically based on the evidence presented about the impact of digital technology on education and the factors which affect the schools’ digital capacity and digital transformation.

Methodology

The non-systematic literature review presented herein covers the main theories and research published over the past 17 years on the topic. It is based on meta-analyses and review papers found in scholarly, peer-reviewed content databases and other key studies and reports related to the concepts studied (e.g., digitalization, digital capacity) from professional and international bodies (e.g., the OECD). We searched the Scopus database, which indexes various online journals in the education sector with an international scope, to collect peer-reviewed academic papers. Furthermore, we used an all-inclusive Google Scholar search to include relevant key terms or to include studies found in the reference list of the peer-reviewed papers, and other key studies and reports related to the concepts studied by professional and international bodies. Lastly, we gathered sources from the Publications Office of the European Union ( https://op.europa.eu/en/home ); namely, documents that refer to policies related to digital transformation in education.

Regarding search terms, we first searched resources on the impact of digital technologies on education by performing the following search queries: “impact” OR “effects” AND “digital technologies” AND “education”, “impact” OR “effects” AND “ICT” AND “education”. We further refined our results by adding the terms “meta-analysis” and “review” or by adjusting the search options based on the features of each database to avoid collecting individual studies that would provide limited contributions to a particular domain. We relied on meta-analyses and review studies as these consider the findings of multiple studies to offer a more comprehensive view of the research in a given area (Schuele & Justice, 2006 ). Specifically, meta-analysis studies provided quantitative evidence based on statistically verifiable results regarding the impact of educational interventions that integrate digital technologies in school classrooms (Higgins et al., 2012 ; Tolani-Brown et al., 2011 ).

However, quantitative data does not offer explanations for the challenges or difficulties experienced during ICT integration in learning and teaching (Tolani-Brown et al., 2011 ). To fill this gap, we analyzed literature reviews and gathered in-depth qualitative evidence of the benefits and implications of technology integration in schools. In the analysis presented herein, we also included policy documents and reports from professional and international bodies and governmental reports, which offered useful explanations of the key concepts of this study and provided recent evidence on digital capacity and transformation in education along with policy recommendations. The inclusion and exclusion criteria that were considered in this study are presented in Table ​ Table1 1 .

Inclusion and exclusion criteria for the selection of resources on the impact of digital technologies on education

To ensure a reliable extraction of information from each study and assist the research synthesis we selected the study characteristics of interest (impact) and constructed coding forms. First, an overview of the synthesis was provided by the principal investigator who described the processes of coding, data entry, and data management. The coders followed the same set of instructions but worked independently. To ensure a common understanding of the process between coders, a sample of ten studies was tested. The results were compared, and the discrepancies were identified and resolved. Additionally, to ensure an efficient coding process, all coders participated in group meetings to discuss additions, deletions, and modifications (Stock, 1994 ). Due to the methodological diversity of the studied documents we began to synthesize the literature review findings based on similar study designs. Specifically, most of the meta-analysis studies were grouped in one category due to the quantitative nature of the measured impact. These studies tended to refer to student achievement (Hattie et al., 2014 ). Then, we organized the themes of the qualitative studies in several impact categories. Lastly, we synthesized both review and meta-analysis data across the categories. In order to establish a collective understanding of the concept of impact, we referred to a previous impact study by Balanskat ( 2009 ) which investigated the impact of technology in primary schools. In this context, the impact had a more specific ICT-related meaning and was described as “ a significant influence or effect of ICT on the measured or perceived quality of (parts of) education ” (Balanskat, 2009 , p. 9). In the study presented herein, the main impacts are in relation to learning and learners, teaching, and teachers, as well as other key stakeholders who are directly or indirectly connected to the school unit.

The study’s results identified multiple dimensions of the impact of digital technologies on students’ knowledge, skills, and attitudes; on equality, inclusion, and social integration; on teachers’ professional and teaching practices; and on other school-related aspects and stakeholders. The data analysis indicated various factors that might affect the schools’ digital capacity and transformation, such as digital competencies, the teachers’ personal characteristics and professional development, as well as the school’s leadership and management, administration, infrastructure, etc. The impacts and factors found in the literature review are presented below.

Impacts of digital technologies on students’ knowledge, skills, attitudes, and emotions

The impact of ICT use on students’ knowledge, skills, and attitudes has been investigated early in the literature. Eng ( 2005 ) found a small positive effect between ICT use and students' learning. Specifically, the author reported that access to computer-assisted instruction (CAI) programs in simulation or tutorial modes—used to supplement rather than substitute instruction – could enhance student learning. The author reported studies showing that teachers acknowledged the benefits of ICT on pupils with special educational needs; however, the impact of ICT on students' attainment was unclear. Balanskat et al. ( 2006 ) found a statistically significant positive association between ICT use and higher student achievement in primary and secondary education. The authors also reported improvements in the performance of low-achieving pupils. The use of ICT resulted in further positive gains for students, namely increased attention, engagement, motivation, communication and process skills, teamwork, and gains related to their behaviour towards learning. Evidence from qualitative studies showed that teachers, students, and parents recognized the positive impact of ICT on students' learning regardless of their competence level (strong/weak students). Punie et al. ( 2006 ) documented studies that showed positive results of ICT-based learning for supporting low-achieving pupils and young people with complex lives outside the education system. Liao et al. ( 2007 ) reported moderate positive effects of computer application instruction (CAI, computer simulations, and web-based learning) over traditional instruction on primary school student's achievement. Similarly, Tamim et al. ( 2011 ) reported small to moderate positive effects between the use of computer technology (CAI, ICT, simulations, computer-based instruction, digital and hypermedia) and student achievement in formal face-to-face classrooms compared to classrooms that did not use technology. Jewitt et al., ( 2011 ) found that the use of learning platforms (LPs) (virtual learning environments, management information systems, communication technologies, and information- and resource-sharing technologies) in schools allowed primary and secondary students to access a wider variety of quality learning resources, engage in independent and personalized learning, and conduct self- and peer-review; LPs also provide opportunities for teacher assessment and feedback. Similar findings were reported by Fu ( 2013 ), who documented a list of benefits and opportunities of ICT use. According to the author, the use of ICTs helps students access digital information and course content effectively and efficiently, supports student-centered and self-directed learning, as well as the development of a creative learning environment where more opportunities for critical thinking skills are offered, and promotes collaborative learning in a distance-learning environment. Higgins et al. ( 2012 ) found consistent but small positive associations between the use of technology and learning outcomes of school-age learners (5–18-year-olds) in studies linking the provision and use of technology with attainment. Additionally, Chauhan ( 2017 ) reported a medium positive effect of technology on the learning effectiveness of primary school students compared to students who followed traditional learning instruction.

The rise of mobile technologies and hardware devices instigated investigations into their impact on teaching and learning. Sung et al. ( 2016 ) reported a moderate effect on students' performance from the use of mobile devices in the classroom compared to the use of desktop computers or the non-use of mobile devices. Schmid et al. ( 2014 ) reported medium–low to low positive effects of technology integration (e.g., CAI, ICTs) in the classroom on students' achievement and attitude compared to not using technology or using technology to varying degrees. Tamim et al. ( 2015 ) found a low statistically significant effect of the use of tablets and other smart devices in educational contexts on students' achievement outcomes. The authors suggested that tablets offered additional advantages to students; namely, they reported improvements in students’ notetaking, organizational and communication skills, and creativity. Zheng et al. ( 2016 ) reported a small positive effect of one-to-one laptop programs on students’ academic achievement across subject areas. Additional reported benefits included student-centered, individualized, and project-based learning enhanced learner engagement and enthusiasm. Additionally, the authors found that students using one-to-one laptop programs tended to use technology more frequently than in non-laptop classrooms, and as a result, they developed a range of skills (e.g., information skills, media skills, technology skills, organizational skills). Haßler et al. ( 2016 ) found that most interventions that included the use of tablets across the curriculum reported positive learning outcomes. However, from 23 studies, five reported no differences, and two reported a negative effect on students' learning outcomes. Similar results were indicated by Kalati and Kim ( 2022 ) who investigated the effect of touchscreen technologies on young students’ learning. Specifically, from 53 studies, 34 advocated positive effects of touchscreen devices on children’s learning, 17 obtained mixed findings and two studies reported negative effects.

More recently, approaches that refer to the impact of gamification with the use of digital technologies on teaching and learning were also explored. A review by Pan et al. ( 2022 ) that examined the role of learning games in fostering mathematics education in K-12 settings, reported that gameplay improved students’ performance. Integration of digital games in teaching was also found as a promising pedagogical practice in STEM education that could lead to increased learning gains (Martinez et al., 2022 ; Wang et al., 2022 ). However, although Talan et al. ( 2020 ) reported a medium effect of the use of educational games (both digital and non-digital) on academic achievement, the effect of non-digital games was higher.

Over the last two years, the effects of more advanced technologies on teaching and learning were also investigated. Garzón and Acevedo ( 2019 ) found that AR applications had a medium effect on students' learning outcomes compared to traditional lectures. Similarly, Garzón et al. ( 2020 ) showed that AR had a medium impact on students' learning gains. VR applications integrated into various subjects were also found to have a moderate effect on students’ learning compared to control conditions (traditional classes, e.g., lectures, textbooks, and multimedia use, e.g., images, videos, animation, CAI) (Chen et al., 2022b ). Villena-Taranilla et al. ( 2022 ) noted the moderate effect of VR technologies on students’ learning when these were applied in STEM disciplines. In the same meta-analysis, Villena-Taranilla et al. ( 2022 ) highlighted the role of immersive VR, since its effect on students’ learning was greater (at a high level) across educational levels (K-6) compared to semi-immersive and non-immersive integrations. In another meta-analysis study, the effect size of the immersive VR was small and significantly differentiated across educational levels (Coban et al., 2022 ). The impact of AI on education was investigated by Su and Yang ( 2022 ) and Su et al. ( 2022 ), who showed that this technology significantly improved students’ understanding of AI computer science and machine learning concepts.

It is worth noting that the vast majority of studies referred to learning gains in specific subjects. Specifically, several studies examined the impact of digital technologies on students’ literacy skills and reported positive effects on language learning (Balanskat et al., 2006 ; Grgurović et al., 2013 ; Friedel et al., 2013 ; Zheng et al., 2016 ; Chen et al., 2022b ; Savva et al., 2022 ). Also, several studies documented positive effects on specific language learning areas, namely foreign language learning (Kao, 2014 ), writing (Higgins et al., 2012 ; Wen & Walters, 2022 ; Zheng et al., 2016 ), as well as reading and comprehension (Cheung & Slavin, 2011 ; Liao et al., 2007 ; Schwabe et al., 2022 ). ICTs were also found to have a positive impact on students' performance in STEM (science, technology, engineering, and mathematics) disciplines (Arztmann et al., 2022 ; Bado, 2022 ; Villena-Taranilla et al., 2022 ; Wang et al., 2022 ). Specifically, a number of studies reported positive impacts on students’ achievement in mathematics (Balanskat et al., 2006 ; Hillmayr et al., 2020 ; Li & Ma, 2010 ; Pan et al., 2022 ; Ran et al., 2022 ; Verschaffel et al., 2019 ; Zheng et al., 2016 ). Furthermore, studies documented positive effects of ICTs on science learning (Balanskat et al., 2006 ; Liao et al., 2007 ; Zheng et al., 2016 ; Hillmayr et al., 2020 ; Kalemkuş & Kalemkuş, 2022 ; Lei et al., 2022a ). Çelik ( 2022 ) also noted that computer simulations can help students understand learning concepts related to science. Furthermore, some studies documented that the use of ICTs had a positive impact on students’ achievement in other subjects, such as geography, history, music, and arts (Chauhan, 2017 ; Condie & Munro, 2007 ), and design and technology (Balanskat et al., 2006 ).

More specific positive learning gains were reported in a number of skills, e.g., problem-solving skills and pattern exploration skills (Higgins et al., 2012 ), metacognitive learning outcomes (Verschaffel et al., 2019 ), literacy skills, computational thinking skills, emotion control skills, and collaborative inquiry skills (Lu et al., 2022 ; Su & Yang, 2022 ; Su et al., 2022 ). Additionally, several investigations have reported benefits from the use of ICT on students’ creativity (Fielding & Murcia, 2022 ; Liu et al., 2022 ; Quah & Ng, 2022 ). Lastly, digital technologies were also found to be beneficial for enhancing students’ lifelong learning skills (Haleem et al., 2022 ).

Apart from gaining knowledge and skills, studies also reported improvement in motivation and interest in mathematics (Higgins et. al., 2019 ; Fadda et al., 2022 ) and increased positive achievement emotions towards several subjects during interventions using educational games (Lei et al., 2022a ). Chen et al. ( 2022a ) also reported a small but positive effect of digital health approaches in bullying and cyberbullying interventions with K-12 students, demonstrating that technology-based approaches can help reduce bullying and related consequences by providing emotional support, empowerment, and change of attitude. In their meta-review study, Su et al. ( 2022 ) also documented that AI technologies effectively strengthened students’ attitudes towards learning. In another meta-analysis, Arztmann et al. ( 2022 ) reported positive effects of digital games on motivation and behaviour towards STEM subjects.

Impacts of digital technologies on equality, inclusion and social integration

Although most of the reviewed studies focused on the impact of ICTs on students’ knowledge, skills, and attitudes, reports were also made on other aspects in the school context, such as equality, inclusion, and social integration. Condie and Munro ( 2007 ) documented research interventions investigating how ICT can support pupils with additional or special educational needs. While those interventions were relatively small scale and mostly based on qualitative data, their findings indicated that the use of ICTs enabled the development of communication, participation, and self-esteem. A recent meta-analysis (Baragash et al., 2022 ) with 119 participants with different disabilities, reported a significant overall effect size of AR on their functional skills acquisition. Koh’s meta-analysis ( 2022 ) also revealed that students with intellectual and developmental disabilities improved their competence and performance when they used digital games in the lessons.

Istenic Starcic and Bagon ( 2014 ) found that the role of ICT in inclusion and the design of pedagogical and technological interventions was not sufficiently explored in educational interventions with people with special needs; however, some benefits of ICT use were found in students’ social integration. The issue of gender and technology use was mentioned in a small number of studies. Zheng et al. ( 2016 ) reported a statistically significant positive interaction between one-to-one laptop programs and gender. Specifically, the results showed that girls and boys alike benefitted from the laptop program, but the effect on girls’ achievement was smaller than that on boys’. Along the same lines, Arztmann et al. ( 2022 ) reported no difference in the impact of game-based learning between boys and girls, arguing that boys and girls equally benefited from game-based interventions in STEM domains. However, results from a systematic review by Cussó-Calabuig et al. ( 2018 ) found limited and low-quality evidence on the effects of intensive use of computers on gender differences in computer anxiety, self-efficacy, and self-confidence. Based on their view, intensive use of computers can reduce gender differences in some areas and not in others, depending on contextual and implementation factors.

Impacts of digital technologies on teachers’ professional and teaching practices

Various research studies have explored the impact of ICT on teachers’ instructional practices and student assessment. Friedel et al. ( 2013 ) found that the use of mobile devices by students enabled teachers to successfully deliver content (e.g., mobile serious games), provide scaffolding, and facilitate synchronous collaborative learning. The integration of digital games in teaching and learning activities also gave teachers the opportunity to study and apply various pedagogical practices (Bado, 2022 ). Specifically, Bado ( 2022 ) found that teachers who implemented instructional activities in three stages (pre-game, game, and post-game) maximized students’ learning outcomes and engagement. For instance, during the pre-game stage, teachers focused on lectures and gameplay training, at the game stage teachers provided scaffolding on content, addressed technical issues, and managed the classroom activities. During the post-game stage, teachers organized activities for debriefing to ensure that the gameplay had indeed enhanced students’ learning outcomes.

Furthermore, ICT can increase efficiency in lesson planning and preparation by offering possibilities for a more collaborative approach among teachers. The sharing of curriculum plans and the analysis of students’ data led to clearer target settings and improvements in reporting to parents (Balanskat et al., 2006 ).

Additionally, the use and application of digital technologies in teaching and learning were found to enhance teachers’ digital competence. Balanskat et al. ( 2006 ) documented studies that revealed that the use of digital technologies in education had a positive effect on teachers’ basic ICT skills. The greatest impact was found on teachers with enough experience in integrating ICTs in their teaching and/or who had recently participated in development courses for the pedagogical use of technologies in teaching. Punie et al. ( 2006 ) reported that the provision of fully equipped multimedia portable computers and the development of online teacher communities had positive impacts on teachers’ confidence and competence in the use of ICTs.

Moreover, online assessment via ICTs benefits instruction. In particular, online assessments support the digitalization of students’ work and related logistics, allow teachers to gather immediate feedback and readjust to new objectives, and support the improvement of the technical quality of tests by providing more accurate results. Additionally, the capabilities of ICTs (e.g., interactive media, simulations) create new potential methods of testing specific skills, such as problem-solving and problem-processing skills, meta-cognitive skills, creativity and communication skills, and the ability to work productively in groups (Punie et al., 2006 ).

Impacts of digital technologies on other school-related aspects and stakeholders

There is evidence that the effective use of ICTs and the data transmission offered by broadband connections help improve administration (Balanskat et al., 2006 ). Specifically, ICTs have been found to provide better management systems to schools that have data gathering procedures in place. Condie and Munro ( 2007 ) reported impacts from the use of ICTs in schools in the following areas: attendance monitoring, assessment records, reporting to parents, financial management, creation of repositories for learning resources, and sharing of information amongst staff. Such data can be used strategically for self-evaluation and monitoring purposes which in turn can result in school improvements. Additionally, they reported that online access to other people with similar roles helped to reduce headteachers’ isolation by offering them opportunities to share insights into the use of ICT in learning and teaching and how it could be used to support school improvement. Furthermore, ICTs provided more efficient and successful examination management procedures, namely less time-consuming reporting processes compared to paper-based examinations and smooth communications between schools and examination authorities through electronic data exchange (Punie et al., 2006 ).

Zheng et al. ( 2016 ) reported that the use of ICTs improved home-school relationships. Additionally, Escueta et al. ( 2017 ) reported several ICT programs that had improved the flow of information from the school to parents. Particularly, they documented that the use of ICTs (learning management systems, emails, dedicated websites, mobile phones) allowed for personalized and customized information exchange between schools and parents, such as attendance records, upcoming class assignments, school events, and students’ grades, which generated positive results on students’ learning outcomes and attainment. Such information exchange between schools and families prompted parents to encourage their children to put more effort into their schoolwork.

The above findings suggest that the impact of ICT integration in schools goes beyond students’ performance in school subjects. Specifically, it affects a number of school-related aspects, such as equality and social integration, professional and teaching practices, and diverse stakeholders. In Table ​ Table2, 2 , we summarize the different impacts of digital technologies on school stakeholders based on the literature review, while in Table ​ Table3 3 we organized the tools/platforms and practices/policies addressed in the meta-analyses, literature reviews, EU reports, and international bodies included in the manuscript.

The impact of digital technologies on schools’ stakeholders based on the literature review

Tools/platforms and practices/policies addressed in the meta-analyses, literature reviews, EU reports, and international bodies included in the manuscript

Additionally, based on the results of the literature review, there are many types of digital technologies with different affordances (see, for example, studies on VR vs Immersive VR), which evolve over time (e.g. starting from CAIs in 2005 to Augmented and Virtual reality 2020). Furthermore, these technologies are linked to different pedagogies and policy initiatives, which are critical factors in the study of impact. Table ​ Table3 3 summarizes the different tools and practices that have been used to examine the impact of digital technologies on education since 2005 based on the review results.

Factors that affect the integration of digital technologies

Although the analysis of the literature review demonstrated different impacts of the use of digital technology on education, several authors highlighted the importance of various factors, besides the technology itself, that affect this impact. For example, Liao et al. ( 2007 ) suggested that future studies should carefully investigate which factors contribute to positive outcomes by clarifying the exact relationship between computer applications and learning. Additionally, Haßler et al., ( 2016 ) suggested that the neutral findings regarding the impact of tablets on students learning outcomes in some of the studies included in their review should encourage educators, school leaders, and school officials to further investigate the potential of such devices in teaching and learning. Several other researchers suggested that a number of variables play a significant role in the impact of ICTs on students’ learning that could be attributed to the school context, teaching practices and professional development, the curriculum, and learners’ characteristics (Underwood, 2009 ; Tamim et al., 2011 ; Higgins et al., 2012 ; Archer et al., 2014 ; Sung et al., 2016 ; Haßler et al., 2016 ; Chauhan, 2017 ; Lee et al., 2020 ; Tang et al., 2022 ).

Digital competencies

One of the most common challenges reported in studies that utilized digital tools in the classroom was the lack of students’ skills on how to use them. Fu ( 2013 ) found that students’ lack of technical skills is a barrier to the effective use of ICT in the classroom. Tamim et al. ( 2015 ) reported that students faced challenges when using tablets and smart mobile devices, associated with the technical issues or expertise needed for their use and the distracting nature of the devices and highlighted the need for teachers’ professional development. Higgins et al. ( 2012 ) reported that skills training about the use of digital technologies is essential for learners to fully exploit the benefits of instruction.

Delgado et al. ( 2015 ), meanwhile, reported studies that showed a strong positive association between teachers’ computer skills and students’ use of computers. Teachers’ lack of ICT skills and familiarization with technologies can become a constraint to the effective use of technology in the classroom (Balanskat et al., 2006 ; Delgado et al., 2015 ).

It is worth noting that the way teachers are introduced to ICTs affects the impact of digital technologies on education. Previous studies have shown that teachers may avoid using digital technologies due to limited digital skills (Balanskat, 2006 ), or they prefer applying “safe” technologies, namely technologies that their own teachers used and with which they are familiar (Condie & Munro, 2007 ). In this regard, the provision of digital skills training and exposure to new digital tools might encourage teachers to apply various technologies in their lessons (Condie & Munro, 2007 ). Apart from digital competence, technical support in the school setting has also been shown to affect teachers’ use of technology in their classrooms (Delgado et al., 2015 ). Ferrari et al. ( 2011 ) found that while teachers’ use of ICT is high, 75% stated that they needed more institutional support and a shift in the mindset of educational actors to achieve more innovative teaching practices. The provision of support can reduce time and effort as well as cognitive constraints, which could cause limited ICT integration in the school lessons by teachers (Escueta et al., 2017 ).

Teachers’ personal characteristics, training approaches, and professional development

Teachers’ personal characteristics and professional development affect the impact of digital technologies on education. Specifically, Cheok and Wong ( 2015 ) found that teachers’ personal characteristics (e.g., anxiety, self-efficacy) are associated with their satisfaction and engagement with technology. Bingimlas ( 2009 ) reported that lack of confidence, resistance to change, and negative attitudes in using new technologies in teaching are significant determinants of teachers’ levels of engagement in ICT. The same author reported that the provision of technical support, motivation support (e.g., awards, sufficient time for planning), and training on how technologies can benefit teaching and learning can eliminate the above barriers to ICT integration. Archer et al. ( 2014 ) found that comfort levels in using technology are an important predictor of technology integration and argued that it is essential to provide teachers with appropriate training and ongoing support until they are comfortable with using ICTs in the classroom. Hillmayr et al. ( 2020 ) documented that training teachers on ICT had an important effecton students’ learning.

According to Balanskat et al. ( 2006 ), the impact of ICTs on students’ learning is highly dependent on the teachers’ capacity to efficiently exploit their application for pedagogical purposes. Results obtained from the Teaching and Learning International Survey (TALIS) (OECD, 2021 ) revealed that although schools are open to innovative practices and have the capacity to adopt them, only 39% of teachers in the European Union reported that they are well or very well prepared to use digital technologies for teaching. Li and Ma ( 2010 ) and Hardman ( 2019 ) showed that the positive effect of technology on students’ achievement depends on the pedagogical practices used by teachers. Schmid et al. ( 2014 ) reported that learning was best supported when students were engaged in active, meaningful activities with the use of technological tools that provided cognitive support. Tamim et al. ( 2015 ) compared two different pedagogical uses of tablets and found a significant moderate effect when the devices were used in a student-centered context and approach rather than within teacher-led environments. Similarly, Garzón and Acevedo ( 2019 ) and Garzón et al. ( 2020 ) reported that the positive results from the integration of AR applications could be attributed to the existence of different variables which could influence AR interventions (e.g., pedagogical approach, learning environment, and duration of the intervention). Additionally, Garzón et al. ( 2020 ) suggested that the pedagogical resources that teachers used to complement their lectures and the pedagogical approaches they applied were crucial to the effective integration of AR on students’ learning gains. Garzón and Acevedo ( 2019 ) also emphasized that the success of a technology-enhanced intervention is based on both the technology per se and its characteristics and on the pedagogical strategies teachers choose to implement. For instance, their results indicated that the collaborative learning approach had the highest impact on students’ learning gains among other approaches (e.g., inquiry-based learning, situated learning, or project-based learning). Ran et al. ( 2022 ) also found that the use of technology to design collaborative and communicative environments showed the largest moderator effects among the other approaches.

Hattie ( 2008 ) reported that the effective use of computers is associated with training teachers in using computers as a teaching and learning tool. Zheng et al. ( 2016 ) noted that in addition to the strategies teachers adopt in teaching, ongoing professional development is also vital in ensuring the success of technology implementation programs. Sung et al. ( 2016 ) found that research on the use of mobile devices to support learning tends to report that the insufficient preparation of teachers is a major obstacle in implementing effective mobile learning programs in schools. Friedel et al. ( 2013 ) found that providing training and support to teachers increased the positive impact of the interventions on students’ learning gains. Trucano ( 2005 ) argued that positive impacts occur when digital technologies are used to enhance teachers’ existing pedagogical philosophies. Higgins et al. ( 2012 ) found that the types of technologies used and how they are used could also affect students’ learning. The authors suggested that training and professional development of teachers that focuses on the effective pedagogical use of technology to support teaching and learning is an important component of successful instructional approaches (Higgins et al., 2012 ). Archer et al. ( 2014 ) found that studies that reported ICT interventions during which teachers received training and support had moderate positive effects on students’ learning outcomes, which were significantly higher than studies where little or no detail about training and support was mentioned. Fu ( 2013 ) reported that the lack of teachers’ knowledge and skills on the technical and instructional aspects of ICT use in the classroom, in-service training, pedagogy support, technical and financial support, as well as the lack of teachers’ motivation and encouragement to integrate ICT on their teaching were significant barriers to the integration of ICT in education.

School leadership and management

Management and leadership are important cornerstones in the digital transformation process (Pihir et al., 2018 ). Zheng et al. ( 2016 ) documented leadership among the factors positively affecting the successful implementation of technology integration in schools. Strong leadership, strategic planning, and systematic integration of digital technologies are prerequisites for the digital transformation of education systems (Ređep, 2021 ). Management and leadership play a significant role in formulating policies that are translated into practice and ensure that developments in ICT become embedded into the life of the school and in the experiences of staff and pupils (Condie & Munro, 2007 ). Policy support and leadership must include the provision of an overall vision for the use of digital technologies in education, guidance for students and parents, logistical support, as well as teacher training (Conrads et al., 2017 ). Unless there is a commitment throughout the school, with accountability for progress at key points, it is unlikely for ICT integration to be sustained or become part of the culture (Condie & Munro, 2007 ). To achieve this, principals need to adopt and promote a whole-institution strategy and build a strong mutual support system that enables the school’s technological maturity (European Commission, 2019 ). In this context, school culture plays an essential role in shaping the mindsets and beliefs of school actors towards successful technology integration. Condie and Munro ( 2007 ) emphasized the importance of the principal’s enthusiasm and work as a source of inspiration for the school staff and the students to cultivate a culture of innovation and establish sustainable digital change. Specifically, school leaders need to create conditions in which the school staff is empowered to experiment and take risks with technology (Elkordy & Lovinelli, 2020 ).

In order for leaders to achieve the above, it is important to develop capacities for learning and leading, advocating professional learning, and creating support systems and structures (European Commission, 2019 ). Digital technology integration in education systems can be challenging and leadership needs guidance to achieve it. Such guidance can be introduced through the adoption of new methods and techniques in strategic planning for the integration of digital technologies (Ređep, 2021 ). Even though the role of leaders is vital, the relevant training offered to them has so far been inadequate. Specifically, only a third of the education systems in Europe have put in place national strategies that explicitly refer to the training of school principals (European Commission, 2019 , p. 16).

Connectivity, infrastructure, and government and other support

The effective integration of digital technologies across levels of education presupposes the development of infrastructure, the provision of digital content, and the selection of proper resources (Voogt et al., 2013 ). Particularly, a high-quality broadband connection in the school increases the quality and quantity of educational activities. There is evidence that ICT increases and formalizes cooperative planning between teachers and cooperation with managers, which in turn has a positive impact on teaching practices (Balanskat et al., 2006 ). Additionally, ICT resources, including software and hardware, increase the likelihood of teachers integrating technology into the curriculum to enhance their teaching practices (Delgado et al., 2015 ). For example, Zheng et al. ( 2016 ) found that the use of one-on-one laptop programs resulted in positive changes in teaching and learning, which would not have been accomplished without the infrastructure and technical support provided to teachers. Delgado et al. ( 2015 ) reported that limited access to technology (insufficient computers, peripherals, and software) and lack of technical support are important barriers to ICT integration. Access to infrastructure refers not only to the availability of technology in a school but also to the provision of a proper amount and the right types of technology in locations where teachers and students can use them. Effective technical support is a central element of the whole-school strategy for ICT (Underwood, 2009 ). Bingimlas ( 2009 ) reported that lack of technical support in the classroom and whole-school resources (e.g., failing to connect to the Internet, printers not printing, malfunctioning computers, and working on old computers) are significant barriers that discourage the use of ICT by teachers. Moreover, poor quality and inadequate hardware maintenance, and unsuitable educational software may discourage teachers from using ICTs (Balanskat et al., 2006 ; Bingimlas, 2009 ).

Government support can also impact the integration of ICTs in teaching. Specifically, Balanskat et al. ( 2006 ) reported that government interventions and training programs increased teachers’ enthusiasm and positive attitudes towards ICT and led to the routine use of embedded ICT.

Lastly, another important factor affecting digital transformation is the development and quality assurance of digital learning resources. Such resources can be support textbooks and related materials or resources that focus on specific subjects or parts of the curriculum. Policies on the provision of digital learning resources are essential for schools and can be achieved through various actions. For example, some countries are financing web portals that become repositories, enabling teachers to share resources or create their own. Additionally, they may offer e-learning opportunities or other services linked to digital education. In other cases, specific agencies of projects have also been set up to develop digital resources (Eurydice, 2019 ).

Administration and digital data management

The digital transformation of schools involves organizational improvements at the level of internal workflows, communication between the different stakeholders, and potential for collaboration. Vuorikari et al. ( 2020 ) presented evidence that digital technologies supported the automation of administrative practices in schools and reduced the administration’s workload. There is evidence that digital data affects the production of knowledge about schools and has the power to transform how schooling takes place. Specifically, Sellar ( 2015 ) reported that data infrastructure in education is developing due to the demand for “ information about student outcomes, teacher quality, school performance, and adult skills, associated with policy efforts to increase human capital and productivity practices ” (p. 771). In this regard, practices, such as datafication which refers to the “ translation of information about all kinds of things and processes into quantified formats” have become essential for decision-making based on accountability reports about the school’s quality. The data could be turned into deep insights about education or training incorporating ICTs. For example, measuring students’ online engagement with the learning material and drawing meaningful conclusions can allow teachers to improve their educational interventions (Vuorikari et al., 2020 ).

Students’ socioeconomic background and family support

Research show that the active engagement of parents in the school and their support for the school’s work can make a difference to their children’s attitudes towards learning and, as a result, their achievement (Hattie, 2008 ). In recent years, digital technologies have been used for more effective communication between school and family (Escueta et al., 2017 ). The European Commission ( 2020 ) presented data from a Eurostat survey regarding the use of computers by students during the pandemic. The data showed that younger pupils needed additional support and guidance from parents and the challenges were greater for families in which parents had lower levels of education and little to no digital skills.

In this regard, the socio-economic background of the learners and their socio-cultural environment also affect educational achievements (Punie et al., 2006 ). Trucano documented that the use of computers at home positively influenced students’ confidence and resulted in more frequent use at school, compared to students who had no home access (Trucano, 2005 ). In this sense, the socio-economic background affects the access to computers at home (OECD, 2015 ) which in turn influences the experience of ICT, an important factor for school achievement (Punie et al., 2006 ; Underwood, 2009 ). Furthermore, parents from different socio-economic backgrounds may have different abilities and availability to support their children in their learning process (Di Pietro et al., 2020 ).

Schools’ socioeconomic context and emergency situations

The socio-economic context of the school is closely related to a school’s digital transformation. For example, schools in disadvantaged, rural, or deprived areas are likely to lack the digital capacity and infrastructure required to adapt to the use of digital technologies during emergency periods, such as the COVID-19 pandemic (Di Pietro et al., 2020 ). Data collected from school principals confirmed that in several countries, there is a rural/urban divide in connectivity (OECD, 2015 ).

Emergency periods also affect the digitalization of schools. The COVID-19 pandemic led to the closure of schools and forced them to seek appropriate and connective ways to keep working on the curriculum (Di Pietro et al., 2020 ). The sudden large-scale shift to distance and online teaching and learning also presented challenges around quality and equity in education, such as the risk of increased inequalities in learning, digital, and social, as well as teachers facing difficulties coping with this demanding situation (European Commission, 2020 ).

Looking at the findings of the above studies, we can conclude that the impact of digital technologies on education is influenced by various actors and touches many aspects of the school ecosystem. Figure  1 summarizes the factors affecting the digital technologies’ impact on school stakeholders based on the findings from the literature review.

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Factors that affect the impact of ICTs on education

The findings revealed that the use of digital technologies in education affects a variety of actors within a school’s ecosystem. First, we observed that as technologies evolve, so does the interest of the research community to apply them to school settings. Figure  2 summarizes the trends identified in current research around the impact of digital technologies on schools’ digital capacity and transformation as found in the present study. Starting as early as 2005, when computers, simulations, and interactive boards were the most commonly applied tools in school interventions (e.g., Eng, 2005 ; Liao et al., 2007 ; Moran et al., 2008 ; Tamim et al., 2011 ), moving towards the use of learning platforms (Jewitt et al., 2011 ), then to the use of mobile devices and digital games (e.g., Tamim et al., 2015 ; Sung et al., 2016 ; Talan et al., 2020 ), as well as e-books (e.g., Savva et al., 2022 ), to the more recent advanced technologies, such as AR and VR applications (e.g., Garzón & Acevedo, 2019 ; Garzón et al., 2020 ; Kalemkuş & Kalemkuş, 2022 ), or robotics and AI (e.g., Su & Yang, 2022 ; Su et al., 2022 ). As this evolution shows, digital technologies are a concept in flux with different affordances and characteristics. Additionally, from an instructional perspective, there has been a growing interest in different modes and models of content delivery such as online, blended, and hybrid modes (e.g., Cheok & Wong, 2015 ; Kazu & Yalçin, 2022 ; Ulum, 2022 ). This is an indication that the value of technologies to support teaching and learning as well as other school-related practices is increasingly recognized by the research and school community. The impact results from the literature review indicate that ICT integration on students’ learning outcomes has effects that are small (Coban et al., 2022 ; Eng, 2005 ; Higgins et al., 2012 ; Schmid et al., 2014 ; Tamim et al., 2015 ; Zheng et al., 2016 ) to moderate (Garzón & Acevedo, 2019 ; Garzón et al., 2020 ; Liao et al., 2007 ; Sung et al., 2016 ; Talan et al., 2020 ; Wen & Walters, 2022 ). That said, a number of recent studies have reported high effect sizes (e.g., Kazu & Yalçin, 2022 ).

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Current work and trends in the study of the impact of digital technologies on schools’ digital capacity

Based on these findings, several authors have suggested that the impact of technology on education depends on several variables and not on the technology per se (Tamim et al., 2011 ; Higgins et al., 2012 ; Archer et al., 2014 ; Sung et al., 2016 ; Haßler et al., 2016 ; Chauhan, 2017 ; Lee et al., 2020 ; Lei et al., 2022a ). While the impact of ICTs on student achievement has been thoroughly investigated by researchers, other aspects related to school life that are also affected by ICTs, such as equality, inclusion, and social integration have received less attention. Further analysis of the literature review has revealed a greater investment in ICT interventions to support learning and teaching in the core subjects of literacy and STEM disciplines, especially mathematics, and science. These were the most common subjects studied in the reviewed papers often drawing on national testing results, while studies that investigated other subject areas, such as social studies, were limited (Chauhan, 2017 ; Condie & Munro, 2007 ). As such, research is still lacking impact studies that focus on the effects of ICTs on a range of curriculum subjects.

The qualitative research provided additional information about the impact of digital technologies on education, documenting positive effects and giving more details about implications, recommendations, and future research directions. Specifically, the findings regarding the role of ICTs in supporting learning highlight the importance of teachers’ instructional practice and the learning context in the use of technologies and consequently their impact on instruction (Çelik, 2022 ; Schmid et al., 2014 ; Tamim et al., 2015 ). The review also provided useful insights regarding the various factors that affect the impact of digital technologies on education. These factors are interconnected and play a vital role in the transformation process. Specifically, these factors include a) digital competencies; b) teachers’ personal characteristics and professional development; c) school leadership and management; d) connectivity, infrastructure, and government support; e) administration and data management practices; f) students’ socio-economic background and family support and g) the socioeconomic context of the school and emergency situations. It is worth noting that we observed factors that affect the integration of ICTs in education but may also be affected by it. For example, the frequent use of ICTs and the use of laptops by students for instructional purposes positively affect the development of digital competencies (Zheng et al., 2016 ) and at the same time, the digital competencies affect the use of ICTs (Fu, 2013 ; Higgins et al., 2012 ). As a result, the impact of digital technologies should be explored more as an enabler of desirable and new practices and not merely as a catalyst that improves the output of the education process i.e. namely student attainment.

Conclusions

Digital technologies offer immense potential for fundamental improvement in schools. However, investment in ICT infrastructure and professional development to improve school education are yet to provide fruitful results. Digital transformation is a complex process that requires large-scale transformative changes that presuppose digital capacity and preparedness. To achieve such changes, all actors within the school’s ecosystem need to share a common vision regarding the integration of ICTs in education and work towards achieving this goal. Our literature review, which synthesized quantitative and qualitative data from a list of meta-analyses and review studies, provided useful insights into the impact of ICTs on different school stakeholders and showed that the impact of digital technologies touches upon many different aspects of school life, which are often overlooked when the focus is on student achievement as the final output of education. Furthermore, the concept of digital technologies is a concept in flux as technologies are not only different among them calling for different uses in the educational practice but they also change through time. Additionally, we opened a forum for discussion regarding the factors that affect a school’s digital capacity and transformation. We hope that our study will inform policy, practice, and research and result in a paradigm shift towards more holistic approaches in impact and assessment studies.

Study limitations and future directions

We presented a review of the study of digital technologies' impact on education and factors influencing schools’ digital capacity and transformation. The study results were based on a non-systematic literature review grounded on the acquisition of documentation in specific databases. Future studies should investigate more databases to corroborate and enhance our results. Moreover, search queries could be enhanced with key terms that could provide additional insights about the integration of ICTs in education, such as “policies and strategies for ICT integration in education”. Also, the study drew information from meta-analyses and literature reviews to acquire evidence about the effects of ICT integration in schools. Such evidence was mostly based on the general conclusions of the studies. It is worth mentioning that, we located individual studies which showed different, such as negative or neutral results. Thus, further insights are needed about the impact of ICTs on education and the factors influencing the impact. Furthermore, the nature of the studies included in meta-analyses and reviews is different as they are based on different research methodologies and data gathering processes. For instance, in a meta-analysis, the impact among the studies investigated is measured in a particular way, depending on policy or research targets (e.g., results from national examinations, pre-/post-tests). Meanwhile, in literature reviews, qualitative studies offer additional insights and detail based on self-reports and research opinions on several different aspects and stakeholders who could affect and be affected by ICT integration. As a result, it was challenging to draw causal relationships between so many interrelating variables.

Despite the challenges mentioned above, this study envisaged examining school units as ecosystems that consist of several actors by bringing together several variables from different research epistemologies to provide an understanding of the integration of ICTs. However, the use of other tools and methodologies and models for evaluation of the impact of digital technologies on education could give more detailed data and more accurate results. For instance, self-reflection tools, like SELFIE—developed on the DigCompOrg framework- (Kampylis et al., 2015 ; Bocconi & Lightfoot, 2021 ) can help capture a school’s digital capacity and better assess the impact of ICTs on education. Furthermore, the development of a theory of change could be a good approach for documenting the impact of digital technologies on education. Specifically, theories of change are models used for the evaluation of interventions and their impact; they are developed to describe how interventions will work and give the desired outcomes (Mayne, 2015 ). Theory of change as a methodological approach has also been used by researchers to develop models for evaluation in the field of education (e.g., Aromatario et al., 2019 ; Chapman & Sammons, 2013 ; De Silva et al., 2014 ).

We also propose that future studies aim at similar investigations by applying more holistic approaches for impact assessment that can provide in-depth data about the impact of digital technologies on education. For instance, future studies could focus on different research questions about the technologies that are used during the interventions or the way the implementation takes place (e.g., What methodologies are used for documenting impact? How are experimental studies implemented? How can teachers be taken into account and trained on the technology and its functions? What are the elements of an appropriate and successful implementation? How is the whole intervention designed? On which learning theories is the technology implementation based?).

Future research could also focus on assessing the impact of digital technologies on various other subjects since there is a scarcity of research related to particular subjects, such as geography, history, arts, music, and design and technology. More research should also be done about the impact of ICTs on skills, emotions, and attitudes, and on equality, inclusion, social interaction, and special needs education. There is also a need for more research about the impact of ICTs on administration, management, digitalization, and home-school relationships. Additionally, although new forms of teaching and learning with the use of ICTs (e.g., blended, hybrid, and online learning) have initiated several investigations in mainstream classrooms, only a few studies have measured their impact on students’ learning. Additionally, our review did not document any study about the impact of flipped classrooms on K-12 education. Regarding teaching and learning approaches, it is worth noting that studies referred to STEM or STEAM did not investigate the impact of STEM/STEAM as an interdisciplinary approach to learning but only investigated the impact of ICTs on learning in each domain as a separate subject (science, technology, engineering, arts, mathematics). Hence, we propose future research to also investigate the impact of the STEM/STEAM approach on education. The impact of emerging technologies on education, such as AR, VR, robotics, and AI has also been investigated recently, but more work needs to be done.

Finally, we propose that future studies could focus on the way in which specific factors, e.g., infrastructure and government support, school leadership and management, students’ and teachers’ digital competencies, approaches teachers utilize in the teaching and learning (e.g., blended, online and hybrid learning, flipped classrooms, STEM/STEAM approach, project-based learning, inquiry-based learning), affect the impact of digital technologies on education. We hope that future studies will give detailed insights into the concept of schools’ digital transformation through further investigation of impacts and factors which influence digital capacity and transformation based on the results and the recommendations of the present study.

Acknowledgements

This project has received funding under Grant Agreement No Ref Ares (2021) 339036 7483039 as well as funding from the European Union’s Horizon 2020 Research and Innovation Program under Grant Agreement No 739578 and the Government of the Republic of Cyprus through the Deputy Ministry of Research, Innovation and Digital Policy. The UVa co-authors would like also to acknowledge funding from the European Regional Development Fund and the National Research Agency of the Spanish Ministry of Science and Innovation, under project grant PID2020-112584RB-C32.

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Mayo Clinic School of Continuous Professional Development

You are here, mayo clinic oncology review 2024 - livestream (virtual).

  • Accreditation

literature review virtual schools

Course Director: Thor R. Halfdanarson, MD

July 20, 2024 - Internet Live Activity - St. Paul, Minnesota

This one-day CME course provides hematology and oncology clinicians, nurse practitioners, and physician assistants with an overview of the most recent advances in the treatment of various oncologic malignancies, based on abstracts presented at the June 2024 annual meeting of the American Society of Clinical Oncology (ASCO). Invited speakers choose exciting and relevant abstracts presented at the ASCO meeting and discuss their clinical relevance to daily practice.

Target Audience

This course is designed for physicians, physician assistants, nurses, nurse practitioners, pharmacists, pharmacy technicians, allied health professionals, resident fellows, and scientist researchers.

Learning Objectives

Upon completion of this activity, participants should be able to:

  • Interpret new, practice-relevant data published or presented at ASCO, ESMO, ASH and other key clinical meetings for hematologists and oncologists.
  • Interpret the method for Integrating evidence-based treatment strategies into clinical practice in various fields of medical oncology focusing on immunotherapy.
  • Assess the usefulness of biomarker-based treatment approaches in oncology.
  • Apply new, practice-relevant data published or presented at ASCO, ESMO, ASH and other key clinical meetings for hematologists and oncologists.

Attendance at any Mayo Clinic course does not indicate or guarantee competence or proficiency in the skills, knowledge or performance of any care or procedure(s) which may be discussed or taught in this course.

  • 5.50 AAPA Category 1
  • 5.50 AMA PRA Category 1 Credit ™
  • 5.50 Attendance

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All travel and lodging expenses are the sole responsibility of the individual registrant.

Course Director:

Thor R. Halfdanarson, MD

literature review virtual schools

Credit Statement(s):

AMA Mayo Clinic College of Medicine and Science designates this live activity for a maximum of 5.50 AMA PRA Category 1 Credits ™. Physicians should claim only the credit commensurate with the extent of their participation in the activity. ANCC Mayo Clinic College of Medicine and Science designates this activity for a maximum of 5.50 ANCC contact hours. Nurses should claim only the credit commensurate with the extent of their participation in the activity. AAPA Mayo Clinic College of Medicine and Science has been authorized by the American Academy of PAs (AAPA) to award AAPA Category 1 CME credit for activities planned in accordance with AAPA CME Criteria. This activity is designated for 5.50 AAPA Category 1 CME credits. PAs should only claim credit commensurate with the extent of their participation. Other Healthcare Professionals: A record of attendance will be provided to all registrants for requesting credits in accordance with state nursing boards, specialty societies or other professional associations.

For disclosure information regarding Mayo Clinic School of Continuous Professional Development accreditation review committee member(s) and staff, please go here to review disclosures .

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Mayo Clinic Oncology Review 2024 course is pleased to offer the opportunity for commercial companies to interact with health care providers and highlight their products and services.  If you are interested in exhibiting at this course, please complete the following:

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Mayo Clinic School of Continuous Professional Development (MCSCPD) strives to foster a learning environment in which individual differences are valued, allowing all to achieve their fullest potential.  ​ 

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  1. PDF Literature Review Virtual Schools

    cently, however, many virtual schools have shifted their focus to credit recovery as a way to provide failing or at-risk students with an alternative to traditional credit recovery courses. This Literature Review summarizes research conducted on the impact of virtual schools on students' achievement, course retention rates, and levels of ...

  2. The reality of virtual schools: A review of the literature

    There have been others who have trumpeted virtual schools as a means to enact innovative educational reform going back many years (Jones, 1997, Perelman, 1992), but there has been a deficit of rigorous reviews of the literature related to virtual schools. This review of the literature is intended to provide a critical analysis of virtual ...

  3. Effectiveness of online and blended learning from schools: A systematic

    This systematic review of the research literature on online and blended learning from schools starts by outlining recent perspectives on emergency remote learning, as occurred during the Covid-19 pandemic. We give aims for the study and explore the original contribution of this paper. ... Worryingly, some studies of purely virtual schools in ...

  4. Online Teaching in K-12 Education in the United States: A Systematic Review

    A wide variety of terminology is used in varied and nuanced ways in educational literature to describe student learning mediated by technology, including terms such as virtual learning, distance learning, remote learning, e-learning, web-based learning, and online learning (e.g., Moore, Dickson-Deane, & Galyen, 2011; Singh & Thurman, 2019).For example, in a systematic review of the literature ...

  5. Effects of virtual learning environments: A scoping review of literature

    Virtual schools need to take an active role in overseeing students' progress, which may require additional staff resources. ... Literature Review. 39 studies: DS: The findings of 39 studies: VR/AR technology can improve learning outcomes and are advantageous in terms of time and financial investment in K-12, higher and tertiary educational ...

  6. The reality of virtual schools: A review of the literature

    Abstract. Virtual schooling was first employed in the mid-1990s and has become a common method of distance education used in K-12 jurisdictions. The most accepted definition of a virtual school is an entity approved by a state or governing body that offers courses through distance delivery - most commonly using the Internet.

  7. Barbour, M. K., & Reeves, T. C. (2009). The reality of virtual schools

    The reality of virtual schools: A review of the literature. Computers and Education, 52(2), 402-416. Michael Barbour Thomas C Reeves. Virtual schooling was first employed in the mid-1990s and has become a common method of distance education used in K-12 jurisdictions. The most accepted definition of a virtual school is an entity approved by a ...

  8. PDF Collaboration and Virtual Learning in New Zealand Rural Primary Schools

    In this literature review, the authors examined three key areas that were chosen as relevant to the challenges . faced by small rural schools, and collaborative practice between schools working in virtual learning environments in New Zealand. The first area was rural education, where definitions of rurality and the

  9. (PDF) Virtual Schools 2021

    Methods A systematic literature review was conducted that included 25 peer‐reviewed studies and unpublished reports from 2000 to 2019 related to K‐12 students. ... Virtual Schools in the U.S ...

  10. The reality of virtual schools: A review of the literature

    2011. TLDR. This study will examine the third and fourth rounds of data collection from an action research project designed to help in-service teachers become better virtual school facilitators (currently being analyzed) and one university's continuing efforts to address this growing need in teacher education. Expand.

  11. [PDF] Literature Review Virtual Schools

    Semantic Scholar extracted view of "Literature Review Virtual Schools" by C. Blazer. Skip to search form Skip to main content Skip to account menu. Semantic Scholar's Logo. Search 213,988,500 papers from all fields of science. Search. Sign In Create Free Account. Corpus ID: 177888625;

  12. Systematic literature review and bibliometric analysis on virtual

    The objective of this study is to identify and analyze the scientific literature with a bibliometric analysis to find the main topics, authors, sources, most cited articles, and countries in the literature on virtual reality in education. Another aim is to understand the conceptual, intellectual, and social structure of the literature on the subject and identify the knowledge base of the use ...

  13. PDF Virtual SchoolS in the u.S. 2019

    time, publicly funded K-12 virtual schools; reviews the relevant available research related to virtual school practices; provides an overview of recent state legislative efforts to craft virtual schools policy; and offers policy recommendations based on the available evidence. Virtual Schools in the U.S. 2019 is organized into three sections:

  14. The reality of virtual schools: A review of the literature

    Virtual schooling was first employed in the mid-1990s and has become a common method of distance education used in K-12 jurisdictions. The most accepted definition of a virtual school is an entity ...

  15. Students' experience of online learning during the COVID‐19 pandemic: A

    Traditional brick‐and‐mortar schools are forced to transform into full‐time virtual schools to provide students with ongoing education ... Interactivity in computer‐mediated college and university education: A recent review of the literature. Journal of Educational Technology & Society, 7 (1), 12-20.

  16. The Reality of Virtual Schools: A Review of the Literature

    Virtual schooling was first employed in the mid-1990s and has become a common method of distance education used in K-12 jurisdictions. The most accepted definition of a virtual school is an entity approved by a state or governing body that offers courses through distance delivery--most commonly using the Internet. While virtual schools can be classified in different ways, the three common ...

  17. Virtual and Augmented Reality in school context: A literature review

    Virtual and Augmented reality has established itself in many sectors including education. The virtual is progressively entering the classrooms. MOOCs (Massive Open Online Course), those online interactive lessons available for all, are useful tools to complete the traditional school system. There are also more and more e-learning platforms that propose online lessons and follow-up for any ...

  18. Virtual and Augmented Reality in school context: A literature review

    161-Texte de l'article-1072-1-10-20210129. Recently, many technological innovations have appeared in education. Two of these technologies, virtual reality and augmented reality, interest us ...

  19. Systematic literature review and bibliometric analysis on virtual

    The objective of this study is to identify and analyze the scientific literature with a bibliometric analysis to find the main topics, authors, sources, most cited articles, and countries in the literature on virtual reality in education. Another aim is to understand the conceptual, intellectual, and social structure of the literature on the ...

  20. Immersive virtual reality as a pedagogical tool in education: a

    The challenges of using head mounted virtual reality in K-12 schools from a teacher perspective. Education and Information Technologies., 2, 20-22. Google Scholar Freina, L., & Ott, M. (2015). A literature review on immersive virtual reality in education: State of the art and perspectives.

  21. Some Students Do Better in Online School

    Yet schools continue to offer—and even expand—remote-learning options. And demand has grown strongly. Between 2021 and 2022, there was a 47 percent increase in families enrolling in exclusively virtual schools, according to the National Center for Education Statistics.

  22. The reality of virtual schools: A review of the literature

    1) There have been others who have trumpeted virtual schools as a means to enact innovative educational reform going back many years (Jones, 1997; Perelman, 1992), but there has been a deficit of rigorous reviews of the literature related to virtual schools. This review of the literature is intended to provide a critical analysis of virtual ...

  23. Impacts of digital technologies on education and factors influencing

    Eng, 2005 (review) Learning platforms (LPs) (virtual learning environments, management information systems, communication technologies and information and resource sharing technologies) ... Predictors of e-learning satisfaction in teaching and learning for school teachers: A literature review. International Journal of Instruction. 2015; 8 (1 ...

  24. Mayo Clinic Oncology Review 2024

    Course Director: Thor R. Halfdanarson, MD. July 20, 2024 - Internet Live Activity - St. Paul, Minnesota. This one-day CME course provides hematology and oncology clinicians, nurse practitioners, and physician assistants with an overview of the most recent advances in the treatment of various oncologic malignancies, based on abstracts presented at the June 2024 annual meeting of the American ...