2009)
Berge and Mrozowski (2001) reviewed 890 research articles and dissertation abstracts on distance education from 1990 to 1999. The four distance education journals chosen by the authors to represent distance education included, American Journal of Distance Education, Distance Education, Open Learning, and the Journal of Distance Education. This review overlapped in the dates of the Tallent-Runnels et al. (2006) study. Berge and Mrozowski (2001) categorized the articles according to Sherry's (1996) ten themes of research issues in distance education: redefining roles of instructor and students, technologies used, issues of design, strategies to stimulate learning, learner characteristics and support, issues related to operating and policies and administration, access and equity, and costs and benefits.
In the Berge and Mrozowski (2001) study, more than 100 studies focused on each of the three themes: (1) design issues, (2) learner characteristics, and (3) strategies to increase interactivity and active learning. By design issues, the authors focused on instructional systems design and focused on topics such as content requirement, technical constraints, interactivity, and feedback. The next theme, strategies to increase interactivity and active learning, were closely related to design issues and focused on students’ modes of learning. Learner characteristics focused on accommodating various learning styles through customized instructional theory. Less than 50 studies focused on the three least examined themes: (1) cost-benefit tradeoffs, (2) equity and accessibility, and (3) learner support. Cost-benefit trade-offs focused on the implementation costs of distance education based on school characteristics. Equity and accessibility focused on the equity of access to distance education systems. Learner support included topics such as teacher to teacher support as well as teacher to student support.
Tallent-Runnels et al. (2006) reviewed research on online instruction from 1993 to 2004. They reviewed 76 articles focused on online learning by searching five databases, ERIC, PsycINFO, ContentFirst, Education Abstracts, and WilsonSelect. Tallent-Runnels et al. (2006) categorized research into four themes, (1) course environment, (2) learners' outcomes, (3) learners’ characteristics, and (4) institutional and administrative factors. The first theme that the authors describe as course environment ( n = 41, 53.9%) is an overarching theme that includes classroom culture, structural assistance, success factors, online interaction, and evaluation.
Tallent-Runnels et al. (2006) for their second theme found that studies focused on questions involving the process of teaching and learning and methods to explore cognitive and affective learner outcomes ( n = 29, 38.2%). The authors stated that they found the research designs flawed and lacked rigor. However, the literature comparing traditional and online classrooms found both delivery systems to be adequate. Another research theme focused on learners’ characteristics ( n = 12, 15.8%) and the synergy of learners, design of the online course, and system of delivery. Research findings revealed that online learners were mainly non-traditional, Caucasian, had different learning styles, and were highly motivated to learn. The final theme that they reported was institutional and administrative factors (n = 13, 17.1%) on online learning. Their findings revealed that there was a lack of scholarly research in this area and most institutions did not have formal policies in place for course development as well as faculty and student support in training and evaluation. Their research confirmed that when universities offered online courses, it improved student enrollment numbers.
Zawacki-Richter et al. (2009) reviewed 695 articles on distance education from 2000 to 2008 using the Delphi method for consensus in identifying areas and classified the literature from five prominent journals. The five journals selected due to their wide scope in research in distance education included Open Learning, Distance Education, American Journal of Distance Education, the Journal of Distance Education, and the International Review of Research in Open and Distributed Learning. The reviewers examined the main focus of research and identified gaps in distance education research in this review.
Zawacki-Richter et al. (2009) classified the studies into macro, meso and micro levels focusing on 15 areas of research. The five areas of the macro-level addressed: (1) access, equity and ethics to deliver distance education for developing nations and the role of various technologies to narrow the digital divide, (2) teaching and learning drivers, markets, and professional development in the global context, (3) distance delivery systems and institutional partnerships and programs and impact of hybrid modes of delivery, (4) theoretical frameworks and models for instruction, knowledge building, and learner interactions in distance education practice, and (5) the types of preferred research methodologies. The meso-level focused on seven areas that involve: (1) management and organization for sustaining distance education programs, (2) examining financial aspects of developing and implementing online programs, (3) the challenges and benefits of new technologies for teaching and learning, (4) incentives to innovate, (5) professional development and support for faculty, (6) learner support services, and (7) issues involving quality standards and the impact on student enrollment and retention. The micro-level focused on three areas: (1) instructional design and pedagogical approaches, (2) culturally appropriate materials, interaction, communication, and collaboration among a community of learners, and (3) focus on characteristics of adult learners, socio-economic backgrounds, learning preferences, and dispositions.
The top three research themes in this review by Zawacki-Richter et al. (2009) were interaction and communities of learning ( n = 122, 17.6%), instructional design ( n = 121, 17.4%) and learner characteristics ( n = 113, 16.3%). The lowest number of studies (less than 3%) were found in studies examining the following research themes, management and organization ( n = 18), research methods in DE and knowledge transfer ( n = 13), globalization of education and cross-cultural aspects ( n = 13), innovation and change ( n = 13), and costs and benefits ( n = 12).
These three systematic reviews provide a broad understanding of distance education and online learning research themes from 1990 to 2008. However, there is an increase in the number of research studies on online learning in this decade and there is a need to identify recent research themes examined. Based on the previous systematic reviews ( Berge & Mrozowski, 2001 ; Hung, 2012 ; Tallent-Runnels et al., 2006 ; Zawacki-Richter et al., 2009 ), online learning research in this study is grouped into twelve different research themes which include Learner characteristics, Instructor characteristics, Course or program design and development, Course Facilitation, Engagement, Course Assessment, Course Technologies, Access, Culture, Equity, Inclusion, and Ethics, Leadership, Policy and Management, Instructor and Learner Support, and Learner Outcomes. Table 2 below describes each of the research themes and using these themes, a framework is derived in Fig. 1 .
Research themes in online learning.
Research Theme | Description | |
---|---|---|
1 | Learner Characteristics | Focuses on understanding the learner characteristics and how online learning can be designed and delivered to meet their needs. Online learner characteristics can be broadly categorized into demographic characteristics, academic characteristics, cognitive characteristics, affective, self-regulation, and motivational characteristics. |
2 | Learner Outcomes | Learner outcomes are statements that specify what the learner will achieve at the end of the course or program. Examining learner outcomes such as success, retention, and dropouts are critical in online courses. |
3 | Engagement | Engaging the learner in the online course is vitally important as they are separated from the instructor and peers in the online setting. Engagement is examined through the lens of interaction, participation, community, collaboration, communication, involvement and presence. |
4 | Course or Program Design and Development | Course design and development is critical in online learning as it engages and assists the students in achieving the learner outcomes. Several models and processes are used to develop the online course, employing different design elements to meet student needs. |
5 | Course Facilitation | The delivery or facilitation of the course is as important as course design. Facilitation strategies used in delivery of the course such as in communication and modeling practices are examined in course facilitation. |
6 | Course Assessment | Course Assessments are adapted and delivered in an online setting. Formative assessments, peer assessments, differentiated assessments, learner choice in assessments, feedback system, online proctoring, plagiarism in online learning, and alternate assessments such as eportfolios are examined. |
7 | Evaluation and Quality Assurance | Evaluation is making a judgment either on the process, the product or a program either during or at the end. There is a need for research on evaluation and quality in the online courses. This has been examined through course evaluations, surveys, analytics, social networks, and pedagogical assessments. Quality assessment rubrics such as Quality Matters have also been researched. |
8 | Course Technologies | A number of online course technologies such as learning management systems, online textbooks, online audio and video tools, collaborative tools, social networks to build online community have been the focus of research. |
9 | Instructor Characteristics | With the increase in online courses, there has also been an increase in the number of instructors teaching online courses. Instructor characteristics can be examined through their experience, satisfaction, and roles in online teaching. |
10 | Institutional Support | The support for online learning is examined both as learner support and instructor support. Online students need support to be successful online learners and this could include social, academic, and cognitive forms of support. Online instructors need support in terms of pedagogy and technology to be successful online instructors. |
11 | Access, Culture, Equity, Inclusion, and Ethics | Cross-cultural online learning is gaining importance along with access in global settings. In addition, providing inclusive opportunities for all learners and in ethical ways is being examined. |
12 | Leadership, Policy and Management | Leadership support is essential for success of online learning. Leaders perspectives, challenges and strategies used are examined. Policies and governance related research are also being studied. |
Online learning research themes framework.
The collection of research themes is presented as a framework in Fig. 1 . The themes are organized by domain or level to underscore the nested relationship that exists. As evidenced by the assortment of themes, research can focus on any domain of delivery or associated context. The “Learner” domain captures characteristics and outcomes related to learners and their interaction within the courses. The “Course and Instructor” domain captures elements about the broader design of the course and facilitation by the instructor, and the “Organizational” domain acknowledges the contextual influences on the course. It is important to note as well that due to the nesting, research themes can cross domains. For example, the broader cultural context may be studied as it pertains to course design and development, and institutional support can include both learner support and instructor support. Likewise, engagement research can involve instructors as well as learners.
In this introduction section, we have reviewed three systematic reviews on online learning research ( Berge & Mrozowski, 2001 ; Tallent-Runnels et al., 2006 ; Zawacki-Richter et al., 2009 ). Based on these reviews and other research, we have derived twelve themes to develop an online learning research framework which is nested in three levels: learner, course and instructor, and organization.
In two out of the three previous reviews, design, learner characteristics and interaction were examined in the highest number of studies. On the other hand, cost-benefit tradeoffs, equity and accessibility, institutional and administrative factors, and globalization and cross-cultural aspects were examined in the least number of studies. One explanation for this may be that it is a function of nesting, noting that studies falling in the Organizational and Course levels may encompass several courses or many more participants within courses. However, while some research themes re-occur, there are also variations in some themes across time, suggesting the importance of research themes rise and fall over time. Thus, a critical examination of the trends in themes is helpful for understanding where research is needed most. Also, since there is no recent study examining online learning research themes in the last decade, this study strives to address that gap by focusing on recent research themes found in the literature, and also reviewing research methods and settings. Notably, one goal is to also compare findings from this decade to the previous review studies. Overall, the purpose of this study is to examine publication trends in online learning research taking place during the last ten years and compare it with the previous themes identified in other review studies. Due to the continued growth of online learning research into new contexts and among new researchers, we also examine the research methods and settings found in the studies of this review.
The following research questions are addressed in this study.
This five-step systematic review process described in the U.S. Department of Education, Institute of Education Sciences, What Works Clearinghouse Procedures and Standards Handbook, Version 4.0 ( 2017 ) was used in this systematic review: (a) developing the review protocol, (b) identifying relevant literature, (c) screening studies, (d) reviewing articles, and (e) reporting findings.
The Education Research Complete database was searched using the keywords below for published articles between the years 2009 and 2018 using both the Title and Keyword function for the following search terms.
“online learning" OR "online teaching" OR "online program" OR "online course" OR “online education”
The initial search of online learning research among journals in the database resulted in more than 3000 possible articles. Therefore, we limited our search to select journals that focus on publishing peer-reviewed online learning and educational research. Our aim was to capture the journals that published the most articles in online learning. However, we also wanted to incorporate the concept of rigor, so we used expert perception to identify 12 peer-reviewed journals that publish high-quality online learning research. Dissertations and conference proceedings were excluded. To be included in this systematic review, each study had to meet the screening criteria as described in Table 3 . A research study was excluded if it did not meet all of the criteria to be included.
Inclusion/Exclusion criteria.
Criteria | Inclusion | Exclusion |
---|---|---|
Focus of the article | Online learning | Articles that did not focus on online learning |
Journals Published | Twelve identified journals | Journals outside of the 12 journals |
Publication date | 2009 to 2018 | Prior to 2009 and after 2018 |
Publication type | Scholarly articles of original research from peer reviewed journals | Book chapters, technical reports, dissertations, or proceedings |
Research Method and Results | There was an identifiable method and results section describing how the study was conducted and included the findings. Quantitative and qualitative methods were included. | Reviews of other articles, opinion, or discussion papers that do not include a discussion of the procedures of the study or analysis of data such as product reviews or conceptual articles. |
Language | Journal article was written in English | Other languages were not included |
Fig. 2 shows the process flow involved in the selection of articles. The search in the database Education Research Complete yielded an initial sample of 3332 articles. Targeting the 12 journals removed 2579 articles. After reviewing the abstracts, we removed 134 articles based on the inclusion/exclusion criteria. The final sample, consisting of 619 articles, was entered into the computer software MAXQDA ( VERBI Software, 2019 ) for coding.
Flowchart of online learning research selection.
A review protocol was designed as a codebook in MAXQDA ( VERBI Software, 2019 ) by the three researchers. The codebook was developed based on findings from the previous review studies and from the initial screening of the articles in this review. The codebook included 12 research themes listed earlier in Table 2 (Learner characteristics, Instructor characteristics, Course or program design and development, Course Facilitation, Engagement, Course Assessment, Course Technologies, Access, Culture, Equity, Inclusion, and Ethics, Leadership, Policy and Management, Instructor and Learner Support, and Learner Outcomes), four research settings (higher education, continuing education, K-12, corporate/military), and three research designs (quantitative, qualitative and mixed methods). Fig. 3 below is a screenshot of MAXQDA used for the coding process.
Codebook from MAXQDA.
Research articles were coded by two researchers in MAXQDA. Two researchers independently coded 10% of the articles and then discussed and updated the coding framework. The second author who was a doctoral student coded the remaining studies. The researchers met bi-weekly to address coding questions that emerged. After the first phase of coding, we found that more than 100 studies fell into each of the categories of Learner Characteristics or Engagement, so we decided to pursue a second phase of coding and reexamine the two themes. Learner Characteristics were classified into the subthemes of Academic, Affective, Motivational, Self-regulation, Cognitive, and Demographic Characteristics. Engagement was classified into the subthemes of Collaborating, Communication, Community, Involvement, Interaction, Participation, and Presence.
Frequency tables were generated for each of the variables so that outliers could be examined and narrative data could be collapsed into categories. Once cleaned and collapsed into a reasonable number of categories, descriptive statistics were used to describe each of the coded elements. We first present the frequencies of publications related to online learning in the 12 journals. The total number of articles for each journal (collectively, the population) was hand-counted from journal websites, excluding editorials and book reviews. The publication trend of online learning research was also depicted from 2009 to 2018. Then, the descriptive information of the 12 themes, including the subthemes of Learner Characteristics and Engagement were provided. Finally, research themes by research settings and methodology were elaborated.
Publication patterns of the 619 articles reviewed from the 12 journals are presented in Table 4 . International Review of Research in Open and Distributed Learning had the highest number of publications in this review. Overall, about 8% of the articles appearing in these twelve journals consisted of online learning publications; however, several journals had concentrations of online learning articles totaling more than 20%.
Empirical online learning research articles by journal, 2009–2018.
Journal Name | Frequency of Empirical Online Learning Research | Percent of Sample | Percent of Journal's Total Articles |
---|---|---|---|
International Review of Research in Open and Distributed Learning | 152 | 24.40 | 22.55 |
Internet & Higher Education | 84 | 13.48 | 26.58 |
Computers & Education | 75 | 12.04 | 18.84 |
Online Learning | 72 | 11.56 | 3.25 |
Distance Education | 64 | 10.27 | 25.10 |
Journal of Online Learning & Teaching | 39 | 6.26 | 11.71 |
Journal of Educational Technology & Society | 36 | 5.78 | 3.63 |
Quarterly Review of Distance Education | 24 | 3.85 | 4.71 |
American Journal of Distance Education | 21 | 3.37 | 9.17 |
British Journal of Educational Technology | 19 | 3.05 | 1.93 |
Educational Technology Research & Development | 19 | 3.05 | 10.80 |
Australasian Journal of Educational Technology | 14 | 2.25 | 2.31 |
Total | 619 | 100.0 | 8.06 |
Note . Journal's Total Article count excludes reviews and editorials.
The publication trend of online learning research is depicted in Fig. 4 . When disaggregated by year, the total frequency of publications shows an increasing trend. Online learning articles increased throughout the decade and hit a relative maximum in 2014. The greatest number of online learning articles ( n = 86) occurred most recently, in 2018.
Online learning publication trends by year.
The publications were categorized into the twelve research themes identified in Fig. 1 . The frequency counts and percentages of the research themes are provided in Table 5 below. A majority of the research is categorized into the Learner domain. The fewest number of articles appears in the Organization domain.
Research themes in the online learning publications from 2009 to 2018.
Research Themes | Frequency | Percentage |
---|---|---|
Engagement | 179 | 28.92 |
Learner Characteristics | 134 | 21.65 |
Learner Outcome | 32 | 5.17 |
Evaluation and Quality Assurance | 38 | 6.14 |
Course Technologies | 35 | 5.65 |
Course Facilitation | 34 | 5.49 |
Course Assessment | 30 | 4.85 |
Course Design and Development | 27 | 4.36 |
Instructor Characteristics | 21 | 3.39 |
Institutional Support | 33 | 5.33 |
Access, Culture, Equity, Inclusion, and Ethics | 29 | 4.68 |
Leadership, Policy, and Management | 27 | 4.36 |
The specific themes of Engagement ( n = 179, 28.92%) and Learner Characteristics ( n = 134, 21.65%) were most often examined in publications. These two themes were further coded to identify sub-themes, which are described in the next two sections. Publications focusing on Instructor Characteristics ( n = 21, 3.39%) were least common in the dataset.
The largest number of studies was on engagement in online learning, which in the online learning literature is referred to and examined through different terms. Hence, we explore this category in more detail. In this review, we categorized the articles into seven different sub-themes as examined through different lenses including presence, interaction, community, participation, collaboration, involvement, and communication. We use the term “involvement” as one of the terms since researchers sometimes broadly used the term engagement to describe their work without further description. Table 6 below provides the description, frequency, and percentages of the various studies related to engagement.
Research sub-themes on engagement.
Description | Frequency | Percentage | |
---|---|---|---|
Presence | Learning experience through social, cognitive, and teaching presence. | 50 | 8.08 |
Interaction | Process of interacting with peers, instructor, or content that results in learners understanding or behavior | 43 | 6.95 |
Community | Sense of belonging within a group | 25 | 4.04 |
Participation | Process of being actively involved | 21 | 3.39 |
Collaboration | Working with someone to create something | 17 | 2.75 |
Involvement | Involvement in learning. This includes articles that focused broadly on engagement of learners. | 14 | 2.26 |
Communication | Process of exchanging information with the intent to share information | 9 | 1.45 |
In the sections below, we provide several examples of the different engagement sub-themes that were studied within the larger engagement theme.
Presence. This sub-theme was the most researched in engagement. With the development of the community of inquiry framework most of the studies in this subtheme examined social presence ( Akcaoglu & Lee, 2016 ; Phirangee & Malec, 2017 ; Wei et al., 2012 ), teaching presence ( Orcutt & Dringus, 2017 ; Preisman, 2014 ; Wisneski et al., 2015 ) and cognitive presence ( Archibald, 2010 ; Olesova et al., 2016 ).
Interaction . This was the second most studied theme under engagement. Researchers examined increasing interpersonal interactions ( Cung et al., 2018 ), learner-learner interactions ( Phirangee, 2016 ; Shackelford & Maxwell, 2012 ; Tawfik et al., 2018 ), peer-peer interaction ( Comer et al., 2014 ), learner-instructor interaction ( Kuo et al., 2014 ), learner-content interaction ( Zimmerman, 2012 ), interaction through peer mentoring ( Ruane & Koku, 2014 ), interaction and community building ( Thormann & Fidalgo, 2014 ), and interaction in discussions ( Ruane & Lee, 2016 ; Tibi, 2018 ).
Community. Researchers examined building community in online courses ( Berry, 2017 ), supporting a sense of community ( Jiang, 2017 ), building an online learning community of practice ( Cho, 2016 ), building an academic community ( Glazer & Wanstreet, 2011 ; Nye, 2015 ; Overbaugh & Nickel, 2011 ), and examining connectedness and rapport in an online community ( Bolliger & Inan, 2012 ; Murphy & Rodríguez-Manzanares, 2012 ; Slagter van Tryon & Bishop, 2012 ).
Participation. Researchers examined engagement through participation in a number of studies. Some of the topics include, participation patterns in online discussion ( Marbouti & Wise, 2016 ; Wise et al., 2012 ), participation in MOOCs ( Ahn et al., 2013 ; Saadatmand & Kumpulainen, 2014 ), features that influence students’ online participation ( Rye & Støkken, 2012 ) and active participation.
Collaboration. Researchers examined engagement through collaborative learning. Specific studies focused on cross-cultural collaboration ( Kumi-Yeboah, 2018 ; Yang et al., 2014 ), how virtual teams collaborate ( Verstegen et al., 2018 ), types of collaboration teams ( Wicks et al., 2015 ), tools for collaboration ( Boling et al., 2014 ), and support for collaboration ( Kopp et al., 2012 ).
Involvement. Researchers examined engaging learners through involvement in various learning activities ( Cundell & Sheepy, 2018 ), student engagement through various measures ( Dixson, 2015 ), how instructors included engagement to involve students in learning ( O'Shea et al., 2015 ), different strategies to engage the learner ( Amador & Mederer, 2013 ), and designed emotionally engaging online environments ( Koseoglu & Doering, 2011 ).
Communication. Researchers examined communication in online learning in studies using social network analysis ( Ergün & Usluel, 2016 ), using informal communication tools such as Facebook for class discussion ( Kent, 2013 ), and using various modes of communication ( Cunningham et al., 2010 ; Rowe, 2016 ). Studies have also focused on both asynchronous and synchronous aspects of communication ( Swaggerty & Broemmel, 2017 ; Yamagata-Lynch, 2014 ).
The second largest theme was learner characteristics. In this review, we explore this further to identify several aspects of learner characteristics. In this review, we categorized the learner characteristics into self-regulation characteristics, motivational characteristics, academic characteristics, affective characteristics, cognitive characteristics, and demographic characteristics. Table 7 provides the number of studies and percentages examining the various learner characteristics.
Research sub-themes on learner characteristics.
Learner Characteristics | Description | Frequency | Percentage |
---|---|---|---|
Self-regulation Characteristics | Involves controlling learner's behavior, emotions, and thoughts to achieve specific learning and performance goals | 54 | 8.72 |
Motivational Characteristics | Learners goal-directed activity instigated and sustained such as beliefs, and behavioral change | 23 | 3.72 |
Academic Characteristics | Education characteristics such as educational type and educational level | 19 | 3.07 |
Affective Characteristics | Learner characteristics that describe learners' feelings or emotions such as satisfaction | 17 | 2.75 |
Cognitive Characteristics | Learner characteristics related to cognitive elements such as attention, memory, and intellect (e.g., learning strategies, learning skills, etc.) | 14 | 2.26 |
Demographic Characteristics | Learner characteristics that relate to information as age, gender, language, social economic status, and cultural background. | 7 | 1.13 |
Online learning has elements that are different from the traditional face-to-face classroom and so the characteristics of the online learners are also different. Yukselturk and Top (2013) categorized online learner profile into ten aspects: gender, age, work status, self-efficacy, online readiness, self-regulation, participation in discussion list, participation in chat sessions, satisfaction, and achievement. Their categorization shows that there are differences in online learner characteristics in these aspects when compared to learners in other settings. Some of the other aspects such as participation and achievement as discussed by Yukselturk and Top (2013) are discussed in different research themes in this study. The sections below provide examples of the learner characteristics sub-themes that were studied.
Self-regulation. Several researchers have examined self-regulation in online learning. They found that successful online learners are academically motivated ( Artino & Stephens, 2009 ), have academic self-efficacy ( Cho & Shen, 2013 ), have grit and intention to succeed ( Wang & Baker, 2018 ), have time management and elaboration strategies ( Broadbent, 2017 ), set goals and revisit course content ( Kizilcec et al., 2017 ), and persist ( Glazer & Murphy, 2015 ). Researchers found a positive relationship between learner's self-regulation and interaction ( Delen et al., 2014 ) and self-regulation and communication and collaboration ( Barnard et al., 2009 ).
Motivation. Researchers focused on motivation of online learners including different motivation levels of online learners ( Li & Tsai, 2017 ), what motivated online learners ( Chaiprasurt & Esichaikul, 2013 ), differences in motivation of online learners ( Hartnett et al., 2011 ), and motivation when compared to face to face learners ( Paechter & Maier, 2010 ). Harnett et al. (2011) found that online learner motivation was complex, multifaceted, and sensitive to situational conditions.
Academic. Several researchers have focused on academic aspects for online learner characteristics. Readiness for online learning has been examined as an academic factor by several researchers ( Buzdar et al., 2016 ; Dray et al., 2011 ; Wladis & Samuels, 2016 ; Yu, 2018 ) specifically focusing on creating and validating measures to examine online learner readiness including examining students emotional intelligence as a measure of student readiness for online learning. Researchers have also examined other academic factors such as academic standing ( Bradford & Wyatt, 2010 ), course level factors ( Wladis et al., 2014 ) and academic skills in online courses ( Shea & Bidjerano, 2014 ).
Affective. Anderson and Bourke (2013) describe affective characteristics through which learners express feelings or emotions. Several research studies focused on the affective characteristics of online learners. Learner satisfaction for online learning has been examined by several researchers ( Cole et al., 2014 ; Dziuban et al., 2015 ; Kuo et al., 2013 ; Lee, 2014a ) along with examining student emotions towards online assessment ( Kim et al., 2014 ).
Cognitive. Researchers have also examined cognitive aspects of learner characteristics including meta-cognitive skills, cognitive variables, higher-order thinking, cognitive density, and critical thinking ( Chen & Wu, 2012 ; Lee, 2014b ). Lee (2014b) examined the relationship between cognitive presence density and higher-order thinking skills. Chen and Wu (2012) examined the relationship between cognitive and motivational variables in an online system for secondary physical education.
Demographic. Researchers have examined various demographic factors in online learning. Several researchers have examined gender differences in online learning ( Bayeck et al., 2018 ; Lowes et al., 2016 ; Yukselturk & Bulut, 2009 ), ethnicity, age ( Ke & Kwak, 2013 ), and minority status ( Yeboah & Smith, 2016 ) of online learners.
While engagement and learner characteristics were studied the most, other themes were less often studied in the literature and are presented here, according to size, with general descriptions of the types of research examined for each.
Evaluation and Quality Assurance. There were 38 studies (6.14%) published in the theme of evaluation and quality assurance. Some of the studies in this theme focused on course quality standards, using quality matters to evaluate quality, using the CIPP model for evaluation, online learning system evaluation, and course and program evaluations.
Course Technologies. There were 35 studies (5.65%) published in the course technologies theme. Some of the studies examined specific technologies such as Edmodo, YouTube, Web 2.0 tools, wikis, Twitter, WebCT, Screencasts, and Web conferencing systems in the online learning context.
Course Facilitation. There were 34 studies (5.49%) published in the course facilitation theme. Some of the studies in this theme examined facilitation strategies and methods, experiences of online facilitators, and online teaching methods.
Institutional Support. There were 33 studies (5.33%) published in the institutional support theme which included support for both the instructor and learner. Some of the studies on instructor support focused on training new online instructors, mentoring programs for faculty, professional development resources for faculty, online adjunct faculty training, and institutional support for online instructors. Studies on learner support focused on learning resources for online students, cognitive and social support for online learners, and help systems for online learner support.
Learner Outcome. There were 32 studies (5.17%) published in the learner outcome theme. Some of the studies that were examined in this theme focused on online learner enrollment, completion, learner dropout, retention, and learner success.
Course Assessment. There were 30 studies (4.85%) published in the course assessment theme. Some of the studies in the course assessment theme examined online exams, peer assessment and peer feedback, proctoring in online exams, and alternative assessments such as eportfolio.
Access, Culture, Equity, Inclusion, and Ethics. There were 29 studies (4.68%) published in the access, culture, equity, inclusion, and ethics theme. Some of the studies in this theme examined online learning across cultures, multi-cultural effectiveness, multi-access, and cultural diversity in online learning.
Leadership, Policy, and Management. There were 27 studies (4.36%) published in the leadership, policy, and management theme. Some of the studies on leadership, policy, and management focused on online learning leaders, stakeholders, strategies for online learning leadership, resource requirements, university policies for online course policies, governance, course ownership, and faculty incentives for online teaching.
Course Design and Development. There were 27 studies (4.36%) published in the course design and development theme. Some of the studies examined in this theme focused on design elements, design issues, design process, design competencies, design considerations, and instructional design in online courses.
Instructor Characteristics. There were 21 studies (3.39%) published in the instructor characteristics theme. Some of the studies in this theme were on motivation and experiences of online instructors, ability to perform online teaching duties, roles of online instructors, and adjunct versus full-time online instructors.
The research methods used in the studies were classified into quantitative, qualitative, and mixed methods ( Harwell, 2012 , pp. 147–163). The research setting was categorized into higher education, continuing education, K-12, and corporate/military. As shown in Table A in the appendix, the vast majority of the publications used higher education as the research setting ( n = 509, 67.6%). Table B in the appendix shows that approximately half of the studies adopted the quantitative method ( n = 324, 43.03%), followed by the qualitative method ( n = 200, 26.56%). Mixed methods account for the smallest portion ( n = 95, 12.62%).
Table A shows that the patterns of the four research settings were approximately consistent across the 12 themes except for the theme of Leaner Outcome and Institutional Support. Continuing education had a higher relative frequency in Learner Outcome (0.28) and K-12 had a higher relative frequency in Institutional Support (0.33) compared to the frequencies they had in the total themes (0.09 and 0.08 respectively). Table B in the appendix shows that the distribution of the three methods were not consistent across the 12 themes. While quantitative studies and qualitative studies were roughly evenly distributed in Engagement, they had a large discrepancy in Learner Characteristics. There were 100 quantitative studies; however, only 18 qualitative studies published in the theme of Learner Characteristics.
In summary, around 8% of the articles published in the 12 journals focus on online learning. Online learning publications showed a tendency of increase on the whole in the past decade, albeit fluctuated, with the greatest number occurring in 2018. Among the 12 research themes related to online learning, the themes of Engagement and Learner Characteristics were studied the most and the theme of Instructor Characteristics was studied the least. Most studies were conducted in the higher education setting and approximately half of the studies used the quantitative method. Looking at the 12 themes by setting and method, we found that the patterns of the themes by setting or by method were not consistent across the 12 themes.
The quality of our findings was ensured by scientific and thorough searches and coding consistency. The selection of the 12 journals provides evidence of the representativeness and quality of primary studies. In the coding process, any difficulties and questions were resolved by consultations with the research team at bi-weekly meetings, which ensures the intra-rater and interrater reliability of coding. All these approaches guarantee the transparency and replicability of the process and the quality of our results.
This review enabled us to identify the online learning research themes examined from 2009 to 2018. In the section below, we review the most studied research themes, engagement and learner characteristics along with implications, limitations, and directions for future research.
Three out of the four systematic reviews informing the design of the present study found that online learner characteristics and online engagement were examined in a high number of studies. In this review, about half of the studies reviewed (50.57%) focused on online learner characteristics or online engagement. This shows the continued importance of these two themes. In the Tallent-Runnels et al.’s (2006) study, the learner characteristics theme was identified as least studied for which they state that researchers are beginning to investigate learner characteristics in the early days of online learning.
One of the differences found in this review is that course design and development was examined in the least number of studies in this review compared to two prior systematic reviews ( Berge & Mrozowski, 2001 ; Zawacki-Richter et al., 2009 ). Zawacki-Richter et al. did not use a keyword search but reviewed all the articles in five different distance education journals. Berge and Mrozowski (2001) included a research theme called design issues to include all aspects of instructional systems design in distance education journals. In our study, in addition to course design and development, we also had focused themes on learner outcomes, course facilitation, course assessment and course evaluation. These are all instructional design focused topics and since we had multiple themes focusing on instructional design topics, the course design and development category might have resulted in fewer studies. There is still a need for more studies to focus on online course design and development.
Three out of the four systematic reviews discussed in the opening of this study found management and organization factors to be least studied. In this review, Leadership, Policy, and Management was studied among 4.36% of the studies and Access, Culture, Equity, Inclusion, and Ethics was studied among 4.68% of the studies in the organizational level. The theme on Equity and accessibility was also found to be the least studied theme in the Berge and Mrozowski (2001) study. In addition, instructor characteristics was the least examined research theme among the twelve themes studied in this review. Only 3.39% of the studies were on instructor characteristics. While there were some studies examining instructor motivation and experiences, instructor ability to teach online, online instructor roles, and adjunct versus full-time online instructors, there is still a need to examine topics focused on instructors and online teaching. This theme was not included in the prior reviews as the focus was more on the learner and the course but not on the instructor. While it is helpful to see research evolving on instructor focused topics, there is still a need for more research on the online instructor.
The research themes from this review were compared with research themes from previous systematic reviews, which targeted prior decades. Table 8 shows the comparison.
Comparison of most and least studied online learning research themes from current to previous reviews.
Level | 1990–1999 ( ) | 1993–2004 ( ) | 2000–2008 ( ) | 2009–2018 (Current Study) | |
---|---|---|---|---|---|
Learner Characteristics | L | X | X | X | |
Engagement and Interaction | L | X | X | X | |
Design Issues/Instructional Design | C | X | X | ||
Course Environment Learner Outcomes | C L | X X | |||
Learner Support | L | X | |||
Equity and Accessibility | O | X | X | ||
Institutional& Administrative Factors | O | X | X | ||
Management and Organization | O | X | X | ||
Cost-Benefit | O | X |
L = Learner, C=Course O=Organization.
In this review there is a greater concentration of studies focused on Learner domain topics, and reduced attention to broader more encompassing research themes that fall into the Course and Organization domains. There is a need for organizational level topics such as Access, Culture, Equity, Inclusion and Ethics, and Leadership, Policy and Management to be researched on within the context of online learning. Examination of access, culture, equity, inclusion and ethics is very important to support diverse online learners, particularly with the rapid expansion of online learning across all educational levels. This was also least studied based on Berge and Mrozowski (2001) systematic review.
The topics on leadership, policy and management were least studied both in this review and also in the Tallent-Runnels et al. (2006) and Zawacki-Richter et al. (2009) study. Tallent-Runnels categorized institutional and administrative aspects into institutional policies, institutional support, and enrollment effects. While we included support as a separate category, in this study leadership, policy and management were combined. There is still a need for research on leadership of those who manage online learning, policies for online education, and managing online programs. In the Zawacki-Richter et al. (2009) study, only a few studies examined management and organization focused topics. They also found management and organization to be strongly correlated with costs and benefits. In our study, costs and benefits were collectively included as an aspect of management and organization and not as a theme by itself. These studies will provide research-based evidence for online education administrators.
As with any systematic review, there are limitations to the scope of the review. The search is limited to twelve journals in the field that typically include research on online learning. These manuscripts were identified by searching the Education Research Complete database which focuses on education students, professionals, and policymakers. Other discipline-specific journals as well as dissertations and proceedings were not included due to the volume of articles. Also, the search was performed using five search terms “online learning" OR "online teaching" OR "online program" OR "online course" OR “online education” in title and keyword. If authors did not include these terms, their respective work may have been excluded from this review even if it focused on online learning. While these terms are commonly used in North America, it may not be commonly used in other parts of the world. Additional studies may exist outside this scope.
The search strategy also affected how we presented results and introduced limitations regarding generalization. We identified that only 8% of the articles published in these journals were related to online learning; however, given the use of search terms to identify articles within select journals it was not feasible to identify the total number of research-based articles in the population. Furthermore, our review focused on the topics and general methods of research and did not systematically consider the quality of the published research. Lastly, some journals may have preferences for publishing studies on a particular topic or that use a particular method (e.g., quantitative methods), which introduces possible selection and publication biases which may skew the interpretation of results due to over/under representation. Future studies are recommended to include more journals to minimize the selection bias and obtain a more representative sample.
Certain limitations can be attributed to the coding process. Overall, the coding process for this review worked well for most articles, as each tended to have an individual or dominant focus as described in the abstracts, though several did mention other categories which likely were simultaneously considered to a lesser degree. However, in some cases, a dominant theme was not as apparent and an effort to create mutually exclusive groups for clearer interpretation the coders were occasionally forced to choose between two categories. To facilitate this coding, the full-texts were used to identify a study focus through a consensus seeking discussion among all authors. Likewise, some studies focused on topics that we have associated with a particular domain, but the design of the study may have promoted an aggregated examination or integrated factors from multiple domains (e.g., engagement). Due to our reliance on author descriptions, the impact of construct validity is likely a concern that requires additional exploration. Our final grouping of codes may not have aligned with the original author's description in the abstract. Additionally, coding of broader constructs which disproportionately occur in the Learner domain, such as learner outcomes, learner characteristics, and engagement, likely introduced bias towards these codes when considering studies that involved multiple domains. Additional refinement to explore the intersection of domains within studies is needed.
One of the strengths of this review is the research categories we have identified. We hope these categories will support future researchers and identify areas and levels of need for future research. Overall, there is some agreement on research themes on online learning research among previous reviews and this one, at the same time there are some contradicting findings. We hope the most-researched themes and least-researched themes provide authors a direction on the importance of research and areas of need to focus on.
The leading themes found in this review is online engagement research. However, presentation of this research was inconsistent, and often lacked specificity. This is not unique to online environments, but the nuances of defining engagement in an online environment are unique and therefore need further investigation and clarification. This review points to seven distinct classifications of online engagement. Further research on engagement should indicate which type of engagement is sought. This level of specificity is necessary to establish instruments for measuring engagement and ultimately testing frameworks for classifying engagement and promoting it in online environments. Also, it might be of importance to examine the relationship between these seven sub-themes of engagement.
Additionally, this review highlights growing attention to learner characteristics, which constitutes a shift in focus away from instructional characteristics and course design. Although this is consistent with the focus on engagement, the role of the instructor, and course design with respect to these outcomes remains important. Results of the learner characteristics and engagement research paired with course design will have important ramifications for the use of teaching and learning professionals who support instruction. Additionally, the review also points to a concentration of research in the area of higher education. With an immediate and growing emphasis on online learning in K-12 and corporate settings, there is a critical need for further investigation in these settings.
Lastly, because the present review did not focus on the overall effect of interventions, opportunities exist for dedicated meta-analyses. Particular attention to research on engagement and learner characteristics as well as how these vary by study design and outcomes would be logical additions to the research literature.
This systematic review builds upon three previous reviews which tackled the topic of online learning between 1990 and 2010 by extending the timeframe to consider the most recent set of published research. Covering the most recent decade, our review of 619 articles from 12 leading online learning journal points to a more concentrated focus on the learner domain including engagement and learner characteristics, with more limited attention to topics pertaining to the classroom or organizational level. The review highlights an opportunity for the field to clarify terminology concerning online learning research, particularly in the areas of learner outcomes where there is a tendency to classify research more generally (e.g., engagement). Using this sample of published literature, we provide a possible taxonomy for categorizing this research using subcategories. The field could benefit from a broader conversation about how these categories can shape a comprehensive framework for online learning research. Such efforts will enable the field to effectively prioritize research aims over time and synthesize effects.
Florence Martin: Conceptualization; Writing - original draft, Writing - review & editing Preparation, Supervision, Project administration. Ting Sun: Methodology, Formal analysis, Writing - original draft, Writing - review & editing. Carl Westine: Methodology, Formal analysis, Writing - original draft, Writing - review & editing, Supervision
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
1 Includes articles that are cited in this manuscript and also included in the systematic review. The entire list of 619 articles used in the systematic review can be obtained by emailing the authors.*
Appendix B Supplementary data to this article can be found online at https://doi.org/10.1016/j.compedu.2020.104009 .
Research Themes by the Settings in the Online Learning Publications
Research Theme | Higher Ed ( = 506) | Continuing Education ( = 58) | K-12 ( = 53) | Corporate/Military ( = 3) |
---|---|---|---|---|
Engagement | 153 | 15 | 12 | 0 |
Presence | 46 | 2 | 3 | 0 |
Interaction | 35 | 4 | 4 | 0 |
Community | 19 | 2 | 4 | 0 |
Participation | 16 | 5 | 0 | 0 |
Collaboration | 16 | 1 | 0 | 0 |
Involvement | 13 | 0 | 1 | 0 |
Communication | 8 | 1 | 0 | 0 |
Learner Characteristics | 106 | 18 | 9 | 1 |
Self-regulation Characteristics | 43 | 9 | 2 | 0 |
Motivation Characteristics | 18 | 3 | 2 | 0 |
Academic Characteristics | 17 | 0 | 2 | 0 |
Affective Characteristics | 12 | 3 | 1 | 1 |
Cognitive Characteristics | 11 | 1 | 2 | 0 |
Demographic Characteristics | 5 | 2 | 0 | 0 |
Evaluation and Quality Assurance | 33 | 3 | 2 | 0 |
Course Technologies | 33 | 2 | 0 | 0 |
Course Facilitation | 30 | 3 | 1 | 0 |
Institutional Support | 24 | 0 | 8 | 1 |
Learner Outcome | 24 | 7 | 1 | 0 |
Course Assessment | 23 | 2 | 5 | 0 |
Access, Culture, Equity, Inclusion and Ethics | 26 | 1 | 2 | 0 |
Leadership, Policy and Management | 17 | 5 | 5 | 0 |
Course Design and Development | 21 | 1 | 4 | 1 |
Instructor Characteristics | 16 | 1 | 4 | 0 |
Research Themes by the Methodology in the Online Learning Publications
Research Theme | Mixed Method ( = 95) | Quantitative ( = 324) | Qualitative ( = 200) |
---|---|---|---|
Engagement | 32 | 78 | 69 |
Presence | 11 | 25 | 14 |
Interaction | 9 | 20 | 14 |
Community | 2 | 9 | 14 |
Participation | 6 | 8 | 7 |
Collaboration | 2 | 5 | 10 |
Involvement | 2 | 6 | 6 |
Communication | 0 | 5 | 4 |
Learner Characteristics | 16 | 100 | 18 |
Self-regulation Characteristics | 5 | 43 | 6 |
Motivation Characteristics | 4 | 15 | 4 |
Academic Characteristics | 1 | 15 | 3 |
Affective Characteristics | 2 | 12 | 3 |
Cognitive Characteristics | 4 | 8 | 2 |
Demographic Characteristics | 1 | 6 | 0 |
Evaluation and Quality Assurance | 5 | 22 | 11 |
Course Technologies | 4 | 20 | 11 |
Course Facilitation | 7 | 14 | 13 |
Institutional Support | 12 | 9 | 12 |
Learner Outcome | 3 | 23 | 6 |
Course Assessment | 5 | 20 | 5 |
Access, Culture, Equity, Inclusion & Ethics | 3 | 13 | 13 |
Leadership, Policy and Management | 5 | 9 | 13 |
Course Design and Development | 2 | 8 | 17 |
Instructor Characteristics | 1 | 8 | 12 |
The following are the Supplementary data to this article:
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The purpose of this study is to analyze the effect of online education, which has been extensively used on student achievement since the beginning of the pandemic. In line with this purpose, a meta-analysis of the related studies focusing on the effect of online education on students’ academic achievement in several countries between the years 2010 and 2021 was carried out. Furthermore, this study will provide a source to assist future studies with comparing the effect of online education on academic achievement before and after the pandemic. This meta-analysis study consists of 27 studies in total. The meta-analysis involves the studies conducted in the USA, Taiwan, Turkey, China, Philippines, Ireland, and Georgia. The studies included in the meta-analysis are experimental studies, and the total sample size is 1772. In the study, the funnel plot, Duval and Tweedie’s Trip and Fill Analysis, Orwin’s Safe N Analysis, and Egger’s Regression Test were utilized to determine the publication bias, which has been found to be quite low. Besides, Hedge’s g statistic was employed to measure the effect size for the difference between the means performed in accordance with the random effects model. The results of the study show that the effect size of online education on academic achievement is on a medium level. The heterogeneity test results of the meta-analysis study display that the effect size does not differ in terms of class level, country, online education approaches, and lecture moderators.
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Information and communication technologies have become a powerful force in transforming the educational settings around the world. The pandemic has been an important factor in transferring traditional physical classrooms settings through adopting information and communication technologies and has also accelerated the transformation. The literature supports that learning environments connected to information and communication technologies highly satisfy students. Therefore, we need to keep interest in technology-based learning environments. Clearly, technology has had a huge impact on young people's online lives. This digital revolution can synergize the educational ambitions and interests of digitally addicted students. In essence, COVID-19 has provided us with an opportunity to embrace online learning as education systems have to keep up with the rapid emergence of new technologies.
Information and communication technologies that have an effect on all spheres of life are also actively included in the education field. With the recent developments, using technology in education has become inevitable due to personal and social reasons (Usta, 2011a ). Online education may be given as an example of using information and communication technologies as a consequence of the technological developments. Also, it is crystal clear that online learning is a popular way of obtaining instruction (Demiralay et al., 2016 ; Pillay et al., 2007 ), which is defined by Horton ( 2000 ) as a way of education that is performed through a web browser or an online application without requiring an extra software or a learning source. Furthermore, online learning is described as a way of utilizing the internet to obtain the related learning sources during the learning process, to interact with the content, the teacher, and other learners, as well as to get support throughout the learning process (Ally, 2004 ). Online learning has such benefits as learning independently at any time and place (Vrasidas & MsIsaac, 2000 ), granting facility (Poole, 2000 ), flexibility (Chizmar & Walbert, 1999 ), self-regulation skills (Usta, 2011b ), learning with collaboration, and opportunity to plan self-learning process.
Even though online education practices have not been comprehensive as it is now, internet and computers have been used in education as alternative learning tools in correlation with the advances in technology. The first distance education attempt in the world was initiated by the ‘Steno Courses’ announcement published in Boston newspaper in 1728. Furthermore, in the nineteenth century, Sweden University started the “Correspondence Composition Courses” for women, and University Correspondence College was afterwards founded for the correspondence courses in 1843 (Arat & Bakan, 2011 ). Recently, distance education has been performed through computers, assisted by the facilities of the internet technologies, and soon, it has evolved into a mobile education practice that is emanating from progress in the speed of internet connection, and the development of mobile devices.
With the emergence of pandemic (Covid-19), face to face education has almost been put to a halt, and online education has gained significant importance. The Microsoft management team declared to have 750 users involved in the online education activities on the 10 th March, just before the pandemic; however, on March 24, they informed that the number of users increased significantly, reaching the number of 138,698 users (OECD, 2020 ). This event supports the view that it is better to commonly use online education rather than using it as a traditional alternative educational tool when students do not have the opportunity to have a face to face education (Geostat, 2019 ). The period of Covid-19 pandemic has emerged as a sudden state of having limited opportunities. Face to face education has stopped in this period for a long time. The global spread of Covid-19 affected more than 850 million students all around the world, and it caused the suspension of face to face education. Different countries have proposed several solutions in order to maintain the education process during the pandemic. Schools have had to change their curriculum, and many countries supported the online education practices soon after the pandemic. In other words, traditional education gave its way to online education practices. At least 96 countries have been motivated to access online libraries, TV broadcasts, instructions, sources, video lectures, and online channels (UNESCO, 2020 ). In such a painful period, educational institutions went through online education practices by the help of huge companies such as Microsoft, Google, Zoom, Skype, FaceTime, and Slack. Thus, online education has been discussed in the education agenda more intensively than ever before.
Although online education approaches were not used as comprehensively as it has been used recently, it was utilized as an alternative learning approach in education for a long time in parallel with the development of technology, internet and computers. The academic achievement of the students is often aimed to be promoted by employing online education approaches. In this regard, academicians in various countries have conducted many studies on the evaluation of online education approaches and published the related results. However, the accumulation of scientific data on online education approaches creates difficulties in keeping, organizing and synthesizing the findings. In this research area, studies are being conducted at an increasing rate making it difficult for scientists to be aware of all the research outside of their expertise. Another problem encountered in the related study area is that online education studies are repetitive. Studies often utilize slightly different methods, measures, and/or examples to avoid duplication. This erroneous approach makes it difficult to distinguish between significant differences in the related results. In other words, if there are significant differences in the results of the studies, it may be difficult to express what variety explains the differences in these results. One obvious solution to these problems is to systematically review the results of various studies and uncover the sources. One method of performing such systematic syntheses is the application of meta-analysis which is a methodological and statistical approach to draw conclusions from the literature. At this point, how effective online education applications are in increasing the academic success is an important detail. Has online education, which is likely to be encountered frequently in the continuing pandemic period, been successful in the last ten years? If successful, how much was the impact? Did different variables have an impact on this effect? Academics across the globe have carried out studies on the evaluation of online education platforms and publishing the related results (Chiao et al., 2018 ). It is quite important to evaluate the results of the studies that have been published up until now, and that will be published in the future. Has the online education been successful? If it has been, how big is the impact? Do the different variables affect this impact? What should we consider in the next coming online education practices? These questions have all motivated us to carry out this study. We have conducted a comprehensive meta-analysis study that tries to provide a discussion platform on how to develop efficient online programs for educators and policy makers by reviewing the related studies on online education, presenting the effect size, and revealing the effect of diverse variables on the general impact.
There have been many critical discussions and comprehensive studies on the differences between online and face to face learning; however, the focus of this paper is different in the sense that it clarifies the magnitude of the effect of online education and teaching process, and it represents what factors should be controlled to help increase the effect size. Indeed, the purpose here is to provide conscious decisions in the implementation of the online education process.
The general impact of online education on the academic achievement will be discovered in the study. Therefore, this will provide an opportunity to get a general overview of the online education which has been practiced and discussed intensively in the pandemic period. Moreover, the general impact of online education on academic achievement will be analyzed, considering different variables. In other words, the current study will allow to totally evaluate the study results from the related literature, and to analyze the results considering several cultures, lectures, and class levels. Considering all the related points, this study seeks to answer the following research questions:
What is the effect size of online education on academic achievement?
How do the effect sizes of online education on academic achievement change according to the moderator variable of the country?
How do the effect sizes of online education on academic achievement change according to the moderator variable of the class level?
How do the effect sizes of online education on academic achievement change according to the moderator variable of the lecture?
How do the effect sizes of online education on academic achievement change according to the moderator variable of the online education approaches?
This study aims at determining the effect size of online education, which has been highly used since the beginning of the pandemic, on students’ academic achievement in different courses by using a meta-analysis method. Meta-analysis is a synthesis method that enables gathering of several study results accurately and efficiently, and getting the total results in the end (Tsagris & Fragkos, 2018 ).
The required literature for the meta-analysis study was reviewed in July, 2020, and the follow-up review was conducted in September, 2020. The purpose of the follow-up review was to include the studies which were published in the conduction period of this study, and which met the related inclusion criteria. However, no study was encountered to be included in the follow-up review.
In order to access the studies in the meta-analysis, the databases of Web of Science, ERIC, and SCOPUS were reviewed by utilizing the keywords ‘online learning and online education’. Not every database has a search engine that grants access to the studies by writing the keywords, and this obstacle was considered to be an important problem to be overcome. Therefore, a platform that has a special design was utilized by the researcher. With this purpose, through the open access system of Cukurova University Library, detailed reviews were practiced using EBSCO Information Services (EBSCO) that allow reviewing the whole collection of research through a sole searching box. Since the fundamental variables of this study are online education and online learning, the literature was systematically reviewed in the related databases (Web of Science, ERIC, and SCOPUS) by referring to the keywords. Within this scope, 225 articles were accessed, and the studies were included in the coding key list formed by the researcher. The name of the researchers, the year, the database (Web of Science, ERIC, and SCOPUS), the sample group and size, the lectures that the academic achievement was tested in, the country that the study was conducted in, and the class levels were all included in this coding key.
The following criteria were identified to include 225 research studies which were coded based on the theoretical basis of the meta-analysis study: (1) The studies should be published in the refereed journals between the years 2020 and 2021, (2) The studies should be experimental studies that try to determine the effect of online education and online learning on academic achievement, (3) The values of the stated variables or the required statistics to calculate these values should be stated in the results of the studies, and (4) The sample group of the study should be at a primary education level. These criteria were also used as the exclusion criteria in the sense that the studies that do not meet the required criteria were not included in the present study.
After the inclusion criteria were determined, a systematic review process was conducted, following the year criterion of the study by means of EBSCO. Within this scope, 290,365 studies that analyze the effect of online education and online learning on academic achievement were accordingly accessed. The database (Web of Science, ERIC, and SCOPUS) was also used as a filter by analyzing the inclusion criteria. Hence, the number of the studies that were analyzed was 58,616. Afterwards, the keyword ‘primary education’ was used as the filter and the number of studies included in the study decreased to 3152. Lastly, the literature was reviewed by using the keyword ‘academic achievement’ and 225 studies were accessed. All the information of 225 articles was included in the coding key.
It is necessary for the coders to review the related studies accurately and control the validity, safety, and accuracy of the studies (Stewart & Kamins, 2001 ). Within this scope, the studies that were determined based on the variables used in this study were first reviewed by three researchers from primary education field, then the accessed studies were combined and processed in the coding key by the researcher. All these studies that were processed in the coding key were analyzed in accordance with the inclusion criteria by all the researchers in the meetings, and it was decided that 27 studies met the inclusion criteria (Atici & Polat, 2010 ; Carreon, 2018 ; Ceylan & Elitok Kesici, 2017 ; Chae & Shin, 2016 ; Chiang et al. 2014 ; Ercan, 2014 ; Ercan et al., 2016 ; Gwo-Jen et al., 2018 ; Hayes & Stewart, 2016 ; Hwang et al., 2012 ; Kert et al., 2017 ; Lai & Chen, 2010 ; Lai et al., 2015 ; Meyers et al., 2015 ; Ravenel et al., 2014 ; Sung et al., 2016 ; Wang & Chen, 2013 ; Yu, 2019 ; Yu & Chen, 2014 ; Yu & Pan, 2014 ; Yu et al., 2010 ; Zhong et al., 2017 ). The data from the studies meeting the inclusion criteria were independently processed in the second coding key by three researchers, and consensus meetings were arranged for further discussion. After the meetings, researchers came to an agreement that the data were coded accurately and precisely. Having identified the effect sizes and heterogeneity of the study, moderator variables that will show the differences between the effect sizes were determined. The data related to the determined moderator variables were added to the coding key by three researchers, and a new consensus meeting was arranged. After the meeting, researchers came to an agreement that moderator variables were coded accurately and precisely.
27 studies are included in the meta-analysis. The total sample size of the studies that are included in the analysis is 1772. The characteristics of the studies included are given in Table 1 .
Publication bias is the low capability of published studies on a research subject to represent all completed studies on the same subject (Card, 2011 ; Littell et al., 2008 ). Similarly, publication bias is the state of having a relationship between the probability of the publication of a study on a subject, and the effect size and significance that it produces. Within this scope, publication bias may occur when the researchers do not want to publish the study as a result of failing to obtain the expected results, or not being approved by the scientific journals, and consequently not being included in the study synthesis (Makowski et al., 2019 ). The high possibility of publication bias in a meta-analysis study negatively affects (Pecoraro, 2018 ) the accuracy of the combined effect size, causing the average effect size to be reported differently than it should be (Borenstein et al., 2009 ). For this reason, the possibility of publication bias in the included studies was tested before determining the effect sizes of the relationships between the stated variables. The possibility of publication bias of this meta-analysis study was analyzed by using the funnel plot, Orwin’s Safe N Analysis, Duval and Tweedie’s Trip and Fill Analysis, and Egger’s Regression Test.
After determining the probability of publication bias of this meta-analysis study, the statistical model used to calculate the effect sizes was selected. The main approaches used in the effect size calculations according to the differentiation level of inter-study variance are fixed and random effects models (Pigott, 2012 ). Fixed effects model refers to the homogeneity of the characteristics of combined studies apart from the sample sizes, while random effects model refers to the parameter diversity between the studies (Cumming, 2012 ). While calculating the average effect size in the random effects model (Deeks et al., 2008 ) that is based on the assumption that effect predictions of different studies are only the result of a similar distribution, it is necessary to consider several situations such as the effect size apart from the sample error of combined studies, characteristics of the participants, duration, scope, and pattern of the study (Littell et al., 2008 ). While deciding the model in the meta-analysis study, the assumptions on the sample characteristics of the studies included in the analysis and the inferences that the researcher aims to make should be taken into consideration. The fact that the sample characteristics of the studies conducted in the field of social sciences are affected by various parameters shows that using random effects model is more appropriate in this sense. Besides, it is stated that the inferences made with the random effects model are beyond the studies included in the meta-analysis (Field, 2003 ; Field & Gillett, 2010 ). Therefore, using random effects model also contributes to the generalization of research data. The specified criteria for the statistical model selection show that according to the nature of the meta-analysis study, the model should be selected just before the analysis (Borenstein et al., 2007 ; Littell et al., 2008 ). Within this framework, it was decided to make use of the random effects model, considering that the students who are the samples of the studies included in the meta-analysis are from different countries and cultures, the sample characteristics of the studies differ, and the patterns and scopes of the studies vary as well.
Meta-analysis facilitates analyzing the research subject with different parameters by showing the level of diversity between the included studies. Within this frame, whether there is a heterogeneous distribution between the studies included in the study or not has been evaluated in the present study. The heterogeneity of the studies combined in this meta-analysis study has been determined through Q and I 2 tests. Q test evaluates the random distribution probability of the differences between the observed results (Deeks et al., 2008 ). Q value exceeding 2 value calculated according to the degree of freedom and significance, indicates the heterogeneity of the combined effect sizes (Card, 2011 ). I 2 test, which is the complementary of the Q test, shows the heterogeneity amount of the effect sizes (Cleophas & Zwinderman, 2017 ). I 2 value being higher than 75% is explained as high level of heterogeneity.
In case of encountering heterogeneity in the studies included in the meta-analysis, the reasons of heterogeneity can be analyzed by referring to the study characteristics. The study characteristics which may be related to the heterogeneity between the included studies can be interpreted through subgroup analysis or meta-regression analysis (Deeks et al., 2008 ). While determining the moderator variables, the sufficiency of the number of variables, the relationship between the moderators, and the condition to explain the differences between the results of the studies have all been considered in the present study. Within this scope, it was predicted in this meta-analysis study that the heterogeneity can be explained with the country, class level, and lecture moderator variables of the study in terms of the effect of online education, which has been highly used since the beginning of the pandemic, and it has an impact on the students’ academic achievement in different lectures. Some subgroups were evaluated and categorized together, considering that the number of effect sizes of the sub-dimensions of the specified variables is not sufficient to perform moderator analysis (e.g. the countries where the studies were conducted).
Effect size is a factor that shows how much the independent variable affects the dependent variable positively or negatively in each included study in the meta-analysis (Dinçer, 2014 ). While interpreting the effect sizes obtained from the meta-analysis, the classifications of Cohen et al. ( 2007 ) have been utilized. The case of differentiating the specified relationships of the situation of the country, class level, and school subject variables of the study has been identified through the Q test, degree of freedom, and p significance value Fig. 1 and 2 .
The purpose of this study is to determine the effect size of online education on academic achievement. Before determining the effect sizes in the study, the probability of publication bias of this meta-analysis study was analyzed by using the funnel plot, Orwin’s Safe N Analysis, Duval and Tweedie’s Trip and Fill Analysis, and Egger’s Regression Test.
When the funnel plots are examined, it is seen that the studies included in the analysis are distributed symmetrically on both sides of the combined effect size axis, and they are generally collected in the middle and lower sections. The probability of publication bias is low according to the plots. However, since the results of the funnel scatter plots may cause subjective interpretations, they have been supported by additional analyses (Littell et al., 2008 ). Therefore, in order to provide an extra proof for the probability of publication bias, it has been analyzed through Orwin’s Safe N Analysis, Duval and Tweedie’s Trip and Fill Analysis, and Egger’s Regression Test (Table 2 ).
Table 2 consists of the results of the rates of publication bias probability before counting the effect size of online education on academic achievement. According to the table, Orwin Safe N analysis results show that it is not necessary to add new studies to the meta-analysis in order for Hedges g to reach a value outside the range of ± 0.01. The Duval and Tweedie test shows that excluding the studies that negatively affect the symmetry of the funnel scatter plots for each meta-analysis or adding their exact symmetrical equivalents does not significantly differentiate the calculated effect size. The insignificance of the Egger tests results reveals that there is no publication bias in the meta-analysis study. The results of the analysis indicate the high internal validity of the effect sizes and the adequacy of representing the studies conducted on the relevant subject.
In this study, it was aimed to determine the effect size of online education on academic achievement after testing the publication bias. In line with the first purpose of the study, the forest graph regarding the effect size of online education on academic achievement is shown in Fig. 3 , and the statistics regarding the effect size are given in Table 3 .
The flow chart of the scanning and selection process of the studies
Funnel plot graphics representing the effect size of the effects of online education on academic success
Forest graph related to the effect size of online education on academic success
The square symbols in the forest graph in Fig. 3 represent the effect sizes, while the horizontal lines show the intervals in 95% confidence of the effect sizes, and the diamond symbol shows the overall effect size. When the forest graph is analyzed, it is seen that the lower and upper limits of the combined effect sizes are generally close to each other, and the study loads are similar. This similarity in terms of study loads indicates the similarity of the contribution of the combined studies to the overall effect size.
Figure 3 clearly represents that the study of Liu and others (Liu et al., 2018 ) has the lowest, and the study of Ercan and Bilen ( 2014 ) has the highest effect sizes. The forest graph shows that all the combined studies and the overall effect are positive. Furthermore, it is simply understood from the forest graph in Fig. 3 and the effect size statistics in Table 3 that the results of the meta-analysis study conducted with 27 studies and analyzing the effect of online education on academic achievement illustrate that this relationship is on average level (= 0.409).
After the analysis of the effect size in the study, whether the studies included in the analysis are distributed heterogeneously or not has also been analyzed. The heterogeneity of the combined studies was determined through the Q and I 2 tests. As a result of the heterogeneity test, Q statistical value was calculated as 29.576. With 26 degrees of freedom at 95% significance level in the chi-square table, the critical value is accepted as 38.885. The Q statistical value (29.576) counted in this study is lower than the critical value of 38.885. The I 2 value, which is the complementary of the Q statistics, is 12.100%. This value indicates that the accurate heterogeneity or the total variability that can be attributed to variability between the studies is 12%. Besides, p value is higher than (0.285) p = 0.05. All these values [Q (26) = 29.579, p = 0.285; I2 = 12.100] indicate that there is a homogeneous distribution between the effect sizes, and fixed effects model should be used to interpret these effect sizes. However, some researchers argue that even if the heterogeneity is low, it should be evaluated based on the random effects model (Borenstein et al., 2007 ). Therefore, this study gives information about both models. The heterogeneity of the combined studies has been attempted to be explained with the characteristics of the studies included in the analysis. In this context, the final purpose of the study is to determine the effect of the country, academic level, and year variables on the findings. Accordingly, the statistics regarding the comparison of the stated relations according to the countries where the studies were conducted are given in Table 4 .
As seen in Table 4 , the effect of online education on academic achievement does not differ significantly according to the countries where the studies were conducted in. Q test results indicate the heterogeneity of the relationships between the variables in terms of countries where the studies were conducted in. According to the table, the effect of online education on academic achievement was reported as the highest in other countries, and the lowest in the US. The statistics regarding the comparison of the stated relations according to the class levels are given in Table 5 .
As seen in Table 5 , the effect of online education on academic achievement does not differ according to the class level. However, the effect of online education on academic achievement is the highest in the 4 th class. The statistics regarding the comparison of the stated relations according to the class levels are given in Table 6 .
As seen in Table 6 , the effect of online education on academic achievement does not differ according to the school subjects included in the studies. However, the effect of online education on academic achievement is the highest in ICT subject.
The obtained effect size in the study was formed as a result of the findings attained from primary studies conducted in 7 different countries. In addition, these studies are the ones on different approaches to online education (online learning environments, social networks, blended learning, etc.). In this respect, the results may raise some questions about the validity and generalizability of the results of the study. However, the moderator analyzes, whether for the country variable or for the approaches covered by online education, did not create significant differences in terms of the effect sizes. If significant differences were to occur in terms of effect sizes, we could say that the comparisons we will make by comparing countries under the umbrella of online education would raise doubts in terms of generalizability. Moreover, no study has been found in the literature that is not based on a special approach or does not contain a specific technique conducted under the name of online education alone. For instance, one of the commonly used definitions is blended education which is defined as an educational model in which online education is combined with traditional education method (Colis & Moonen, 2001 ). Similarly, Rasmussen ( 2003 ) defines blended learning as “a distance education method that combines technology (high technology such as television, internet, or low technology such as voice e-mail, conferences) with traditional education and training.” Further, Kerres and Witt (2003) define blended learning as “combining face-to-face learning with technology-assisted learning.” As it is clearly observed, online education, which has a wider scope, includes many approaches.
As seen in Table 7 , the effect of online education on academic achievement does not differ according to online education approaches included in the studies. However, the effect of online education on academic achievement is the highest in Web Based Problem Solving Approach.
Considering the developments during the pandemics, it is thought that the diversity in online education applications as an interdisciplinary pragmatist field will increase, and the learning content and processes will be enriched with the integration of new technologies into online education processes. Another prediction is that more flexible and accessible learning opportunities will be created in online education processes, and in this way, lifelong learning processes will be strengthened. As a result, it is predicted that in the near future, online education and even digital learning with a newer name will turn into the main ground of education instead of being an alternative or having a support function in face-to-face learning. The lessons learned from the early period online learning experience, which was passed with rapid adaptation due to the Covid19 epidemic, will serve to develop this method all over the world, and in the near future, online learning will become the main learning structure through increasing its functionality with the contribution of new technologies and systems. If we look at it from this point of view, there is a necessity to strengthen online education.
In this study, the effect of online learning on academic achievement is at a moderate level. To increase this effect, the implementation of online learning requires support from teachers to prepare learning materials, to design learning appropriately, and to utilize various digital-based media such as websites, software technology and various other tools to support the effectiveness of online learning (Rolisca & Achadiyah, 2014 ). According to research conducted by Rahayu et al. ( 2017 ), it has been proven that the use of various types of software increases the effectiveness and quality of online learning. Implementation of online learning can affect students' ability to adapt to technological developments in that it makes students use various learning resources on the internet to access various types of information, and enables them to get used to performing inquiry learning and active learning (Hart et al., 2019 ; Prestiadi et al., 2019 ). In addition, there may be many reasons for the low level of effect in this study. The moderator variables examined in this study could be a guide in increasing the level of practical effect. However, the effect size did not differ significantly for all moderator variables. Different moderator analyzes can be evaluated in order to increase the level of impact of online education on academic success. If confounding variables that significantly change the effect level are detected, it can be spoken more precisely in order to increase this level. In addition to the technical and financial problems, the level of impact will increase if a few other difficulties are eliminated such as students, lack of interaction with the instructor, response time, and lack of traditional classroom socialization.
In addition, COVID-19 pandemic related social distancing has posed extreme difficulties for all stakeholders to get online as they have to work in time constraints and resource constraints. Adopting the online learning environment is not just a technical issue, it is a pedagogical and instructive challenge as well. Therefore, extensive preparation of teaching materials, curriculum, and assessment is vital in online education. Technology is the delivery tool and requires close cross-collaboration between teaching, content and technology teams (CoSN, 2020 ).
Online education applications have been used for many years. However, it has come to the fore more during the pandemic process. This result of necessity has brought with it the discussion of using online education instead of traditional education methods in the future. However, with this research, it has been revealed that online education applications are moderately effective. The use of online education instead of face-to-face education applications can only be possible with an increase in the level of success. This may have been possible with the experience and knowledge gained during the pandemic process. Therefore, the meta-analysis of experimental studies conducted in the coming years will guide us. In this context, experimental studies using online education applications should be analyzed well. It would be useful to identify variables that can change the level of impacts with different moderators. Moderator analyzes are valuable in meta-analysis studies (for example, the role of moderators in Karl Pearson's typhoid vaccine studies). In this context, each analysis study sheds light on future studies. In meta-analyses to be made about online education, it would be beneficial to go beyond the moderators determined in this study. Thus, the contribution of similar studies to the field will increase more.
The purpose of this study is to determine the effect of online education on academic achievement. In line with this purpose, the studies that analyze the effect of online education approaches on academic achievement have been included in the meta-analysis. The total sample size of the studies included in the meta-analysis is 1772. While the studies included in the meta-analysis were conducted in the US, Taiwan, Turkey, China, Philippines, Ireland, and Georgia, the studies carried out in Europe could not be reached. The reason may be attributed to that there may be more use of quantitative research methods from a positivist perspective in the countries with an American academic tradition. As a result of the study, it was found out that the effect size of online education on academic achievement (g = 0.409) was moderate. In the studies included in the present research, we found that online education approaches were more effective than traditional ones. However, contrary to the present study, the analysis of comparisons between online and traditional education in some studies shows that face-to-face traditional learning is still considered effective compared to online learning (Ahmad et al., 2016 ; Hamdani & Priatna, 2020 ; Wei & Chou, 2020 ). Online education has advantages and disadvantages. The advantages of online learning compared to face-to-face learning in the classroom is the flexibility of learning time in online learning, the learning time does not include a single program, and it can be shaped according to circumstances (Lai et al., 2019 ). The next advantage is the ease of collecting assignments for students, as these can be done without having to talk to the teacher. Despite this, online education has several weaknesses, such as students having difficulty in understanding the material, teachers' inability to control students, and students’ still having difficulty interacting with teachers in case of internet network cuts (Swan, 2007 ). According to Astuti et al ( 2019 ), face-to-face education method is still considered better by students than e-learning because it is easier to understand the material and easier to interact with teachers. The results of the study illustrated that the effect size (g = 0.409) of online education on academic achievement is of medium level. Therefore, the results of the moderator analysis showed that the effect of online education on academic achievement does not differ in terms of country, lecture, class level, and online education approaches variables. After analyzing the literature, several meta-analyses on online education were published (Bernard et al., 2004 ; Machtmes & Asher, 2000 ; Zhao et al., 2005 ). Typically, these meta-analyzes also include the studies of older generation technologies such as audio, video, or satellite transmission. One of the most comprehensive studies on online education was conducted by Bernard et al. ( 2004 ). In this study, 699 independent effect sizes of 232 studies published from 1985 to 2001 were analyzed, and face-to-face education was compared to online education, with respect to success criteria and attitudes of various learners from young children to adults. In this meta-analysis, an overall effect size close to zero was found for the students' achievement (g + = 0.01).
In another meta-analysis study carried out by Zhao et al. ( 2005 ), 98 effect sizes were examined, including 51 studies on online education conducted between 1996 and 2002. According to the study of Bernard et al. ( 2004 ), this meta-analysis focuses on the activities done in online education lectures. As a result of the research, an overall effect size close to zero was found for online education utilizing more than one generation technology for students at different levels. However, the salient point of the meta-analysis study of Zhao et al. is that it takes the average of different types of results used in a study to calculate an overall effect size. This practice is problematic because the factors that develop one type of learner outcome (e.g. learner rehabilitation), particularly course characteristics and practices, may be quite different from those that develop another type of outcome (e.g. learner's achievement), and it may even cause damage to the latter outcome. While mixing the studies with different types of results, this implementation may obscure the relationship between practices and learning.
Some meta-analytical studies have focused on the effectiveness of the new generation distance learning courses accessed through the internet for specific student populations. For instance, Sitzmann and others (Sitzmann et al., 2006 ) reviewed 96 studies published from 1996 to 2005, comparing web-based education of job-related knowledge or skills with face-to-face one. The researchers found that web-based education in general was slightly more effective than face-to-face education, but it is insufficient in terms of applicability ("knowing how to apply"). In addition, Sitzmann et al. ( 2006 ) revealed that Internet-based education has a positive effect on theoretical knowledge in quasi-experimental studies; however, it positively affects face-to-face education in experimental studies performed by random assignment. This moderator analysis emphasizes the need to pay attention to the factors of designs of the studies included in the meta-analysis. The designs of the studies included in this meta-analysis study were ignored. This can be presented as a suggestion to the new studies that will be conducted.
Another meta-analysis study was conducted by Cavanaugh et al. ( 2004 ), in which they focused on online education. In this study on internet-based distance education programs for students under 12 years of age, the researchers combined 116 results from 14 studies published between 1999 and 2004 to calculate an overall effect that was not statistically different from zero. The moderator analysis carried out in this study showed that there was no significant factor affecting the students' success. This meta-analysis used multiple results of the same study, ignoring the fact that different results of the same student would not be independent from each other.
In conclusion, some meta-analytical studies analyzed the consequences of online education for a wide range of students (Bernard et al., 2004 ; Zhao et al., 2005 ), and the effect sizes were generally low in these studies. Furthermore, none of the large-scale meta-analyzes considered the moderators, database quality standards or class levels in the selection of the studies, while some of them just referred to the country and lecture moderators. Advances in internet-based learning tools, the pandemic process, and increasing popularity in different learning contexts have required a precise meta-analysis of students' learning outcomes through online learning. Previous meta-analysis studies were typically based on the studies, involving narrow range of confounding variables. In the present study, common but significant moderators such as class level and lectures during the pandemic process were discussed. For instance, the problems have been experienced especially in terms of eligibility of class levels in online education platforms during the pandemic process. It was found that there is a need to study and make suggestions on whether online education can meet the needs of teachers and students.
Besides, the main forms of online education in the past were to watch the open lectures of famous universities and educational videos of institutions. In addition, online education is mainly a classroom-based teaching implemented by teachers in their own schools during the pandemic period, which is an extension of the original school education. This meta-analysis study will stand as a source to compare the effect size of the online education forms of the past decade with what is done today, and what will be done in the future.
Lastly, the heterogeneity test results of the meta-analysis study display that the effect size does not differ in terms of class level, country, online education approaches, and lecture moderators.
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Ulum, H. The effects of online education on academic success: A meta-analysis study. Educ Inf Technol 27 , 429–450 (2022). https://doi.org/10.1007/s10639-021-10740-8
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Editor’s Note: This is part of a series on the practical takeaways from research.
The times have dictated school closings and the rapid expansion of online education. Can online lessons replace in-school time?
Clearly online time cannot provide many of the informal social interactions students have at school, but how will online courses do in terms of moving student learning forward? Research to date gives us some clues and also points us to what we could be doing to support students who are most likely to struggle in the online setting.
The use of virtual courses among K-12 students has grown rapidly in recent years. Florida, for example, requires all high school students to take at least one online course. Online learning can take a number of different forms. Often people think of Massive Open Online Courses, or MOOCs, where thousands of students watch a video online and fill out questionnaires or take exams based on those lectures.
In the online setting, students may have more distractions and less oversight, which can reduce their motivation.
Most online courses, however, particularly those serving K-12 students, have a format much more similar to in-person courses. The teacher helps to run virtual discussion among the students, assigns homework, and follows up with individual students. Sometimes these courses are synchronous (teachers and students all meet at the same time) and sometimes they are asynchronous (non-concurrent). In both cases, the teacher is supposed to provide opportunities for students to engage thoughtfully with subject matter, and students, in most cases, are required to interact with each other virtually.
Coronavirus and Schools
Online courses provide opportunities for students. Students in a school that doesn’t offer statistics classes may be able to learn statistics with virtual lessons. If students fail algebra, they may be able to catch up during evenings or summer using online classes, and not disrupt their math trajectory at school. So, almost certainly, online classes sometimes benefit students.
In comparisons of online and in-person classes, however, online classes aren’t as effective as in-person classes for most students. Only a little research has assessed the effects of online lessons for elementary and high school students, and even less has used the “gold standard” method of comparing the results for students assigned randomly to online or in-person courses. Jessica Heppen and colleagues at the American Institutes for Research and the University of Chicago Consortium on School Research randomly assigned students who had failed second semester Algebra I to either face-to-face or online credit recovery courses over the summer. Students’ credit-recovery success rates and algebra test scores were lower in the online setting. Students assigned to the online option also rated their class as more difficult than did their peers assigned to the face-to-face option.
Most of the research on online courses for K-12 students has used large-scale administrative data, looking at otherwise similar students in the two settings. One of these studies, by June Ahn of New York University and Andrew McEachin of the RAND Corp., examined Ohio charter schools; I did another with colleagues looking at Florida public school coursework. Both studies found evidence that online coursetaking was less effective.
This essay is the fifth in a series that aims to put the pieces of research together so that education decisionmakers can evaluate which policies and practices to implement.
The conveners of this project—Susanna Loeb, the director of Brown University’s Annenberg Institute for School Reform, and Harvard education professor Heather Hill—have received grant support from the Annenberg Institute for this series.
To suggest other topics for this series or join in the conversation, use #EdResearchtoPractice on Twitter.
Read the full series here .
It is not surprising that in-person courses are, on average, more effective. Being in person with teachers and other students creates social pressures and benefits that can help motivate students to engage. Some students do as well in online courses as in in-person courses, some may actually do better, but, on average, students do worse in the online setting, and this is particularly true for students with weaker academic backgrounds.
Students who struggle in in-person classes are likely to struggle even more online. While the research on virtual schools in K-12 education doesn’t address these differences directly, a study of college students that I worked on with Stanford colleagues found very little difference in learning for high-performing students in the online and in-person settings. On the other hand, lower performing students performed meaningfully worse in online courses than in in-person courses.
But just because students who struggle in in-person classes are even more likely to struggle online doesn’t mean that’s inevitable. Online teachers will need to consider the needs of less-engaged students and work to engage them. Online courses might be made to work for these students on average, even if they have not in the past.
Just like in brick-and-mortar classrooms, online courses need a strong curriculum and strong pedagogical practices. Teachers need to understand what students know and what they don’t know, as well as how to help them learn new material. What is different in the online setting is that students may have more distractions and less oversight, which can reduce their motivation. The teacher will need to set norms for engagement—such as requiring students to regularly ask questions and respond to their peers—that are different than the norms in the in-person setting.
Online courses are generally not as effective as in-person classes, but they are certainly better than no classes. A substantial research base developed by Karl Alexander at Johns Hopkins University and many others shows that students, especially students with fewer resources at home, learn less when they are not in school. Right now, virtual courses are allowing students to access lessons and exercises and interact with teachers in ways that would have been impossible if an epidemic had closed schools even a decade or two earlier. So we may be skeptical of online learning, but it is also time to embrace and improve it.
A version of this article appeared in the April 01, 2020 edition of Education Week as How Effective Is Online Learning?
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Updated 11 Mar 2024
Education research plays a crucial role in advancing our understanding of teaching and learning. However, for students, finding a compelling research topic can be a daunting task. That's why we're here to help! In this article, we have curated a collection of the latest education research topics and ideas to inspire you. From exploring how to best utilize technology in classrooms, to evaluating how certain teaching methods can improve learning outcomes, there is a wide range of topics that can be investigated. If you're seeking further support, don't hesitate to reach out and say, " Do my research paper !" We are here to simplify the process and help you excel in your academic pursuits. So let's delve into the exciting world of education research together!
Education research paper topics refer to a wide range of subjects that students can explore in the field of education. Here is a list of topics for your inspiration:
This subtopic explores the impact of higher education on career prospects, the cost and affordability of college, the effectiveness of online learning, and the benefits of international study programs. Conducting research on these topics can lead to a better understanding of higher education and help achieve positive outcomes.
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This topic covers a broad range of research topics, including the effects of nature and nurture on child development, the impact of early childhood experiences on later development, the role of play in learning, and the influence of family and cultural factors on child development.
Discover how to make a positive difference in the world of education through innovative and effective action research. Learn about topics for action research that are relevant to current educational practices and trends. Get started on making your mark through thoughtful exploration of educational topics for action research!
Research into education is groundbreaking, with new discoveries and ideas being created every day. This list of provocative research topics focuses on the most timely and important questions in education today. From educational technology to teaching methods and beyond, these questions are sure to spark intriguing conversations and novel insights.
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Choosing a good topic on education is essential for engaging your audience and making an impact. To do this successfully, consider the following steps:
Choosing the right research topic is vital for students in the field of education. Staying informed about current trends and developments is key. This article provides a diverse list of top education research paper topics, allowing students to select an intriguing idea that aligns with their interests and goals. To save time and effort, you can choose to pay for papers , guaranteeing expertly crafted research papers while you concentrate on your academic goals.
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How teens navigate school during covid-19.
A majority of teens prefer in-person over virtual or hybrid learning. Hispanic and lower-income teens are particularly likely to fear they’ve fallen behind in school due to COVID-19 disruptions.
53% of parents of K-12 students say schools in the United States should be providing a mix of in-person and online instruction this winter.
Here is what our surveys found about the students most likely to lack the home internet connectivity needed to finish schoolwork.
38% of parents with children whose K-12 schools closed in the spring said that their child was likely to face digital obstacles in schoolwork.
Americans with lower incomes are particularly likely to have concerns related to the digital divide and the digital “homework gap.”
As schools close and classes and assignments shift online, some students do not have reliable access to the internet at home.
Some 15% of U.S. households with school-age children do not have a high-speed internet connection at home. Some teens are more likely to face digital hurdles when trying to complete their homework.
The U.S. has more foreign students enrolled in its colleges and universities than any other country in the world. Explore data about foreign students in the U.S. higher education system.
Americans fall along a spectrum of preparedness when it comes to using tech tools to pursue learning online, and many are not eager or ready to take the plunge
Only 12% of teachers say their students are “very likely” to use printed books in a research assignment.
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Home » 500+ Educational Research Topics
Education is a fundamental human right that plays a vital role in shaping the future of individuals, communities, and societies. In order to improve the effectiveness of education, it is crucial to engage in rigorous educational research that seeks to understand how people learn, what factors influence their learning outcomes, and how educational systems can be designed to promote equitable access and success for all learners. Educational research topics cover a wide range of issues, from exploring new teaching methods to examining the impact of technology on learning. In this blog post, we will delve into some of the most important and relevant educational research topics, highlighting their significance and potential impact on the field of education.
Educational Research Topics are as follows:
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Education is the cornerstone of human development, and its continuous improvement relies on diligent research and exploration. Educational research topics serve as beacons, guiding scholars and practitioners toward innovations that enhance teaching methodologies, student engagement, and overall learning outcomes. These educational research topics delve into the depths of educational systems, dissecting their intricacies to identify effective strategies and interventions.
From investigating the impact of technology integration on student achievement to exploring the benefits of inclusive education, educational research delves into diverse areas of study.
In this blog series, we embark on an enlightening journey, shedding light on a myriad of educational research topics. By examining these subjects, we aim to unravel valuable insights that can shape the future of education, fostering an enriching learning experience for all.
Choosing the right educational research topic requires careful consideration. Here are some steps to help you select a suitable topic:
Start by reflecting on your own interests within the field of education. What topics or issues capture your attention? Consider areas such as student learning, teaching methods, educational policies, or educational technology.
Read widely in the field of education to familiarize yourself with current research trends and gaps in knowledge. Identify areas where more research is needed or where existing studies have conflicting results.
Think about the practical implications of the research topic. Is it relevant to current educational challenges or issues? Will the findings have the potential to inform and improve educational practice?
Seek guidance from professors, researchers, or professionals in the field of education. Discuss your potential research topics with them and get their insights and recommendations. They can provide valuable feedback and suggest areas that align with your research goals.
Once you have a general idea, narrow down your topic to make it more focused and manageable. Consider the available resources, time constraints, and the feasibility of conducting research in that specific area.
Clearly define your research objectives and questions. What specific aspects of the topic do you want to explore? Ensure that your research objectives are specific, measurable, achievable, relevant, and time-bound (SMART).
Consider the availability of data and resources required to conduct research on your chosen topic. Evaluate whether you have access to relevant literature, data sources, or research participants. Additionally, consider ethical considerations and any potential constraints that may impact your research.
Share your potential research topic with peers or mentors and seek their feedback. They can provide valuable insights, suggest improvements, or offer alternative perspectives.
Remember, selecting a research topic is an iterative process. It’s essential to be flexible and open to adjustments as you gather more information and refine your research objectives.
Here are some tips to help you write effective educational research topics:
Identify a specific research problem: Start by identifying a specific issue or problem within the field of education that you want to investigate. Narrow down your topic to a specific aspect or area that interests you.
Be clear and concise: Formulate your research topic in a clear and concise manner. Avoid using vague or general terms. Make sure your topic is specific enough to guide your research and provide focus.
Consider the significance and relevance: Ensure that your research topic is significant and relevant to the field of education. Think about the potential impact and contribution of your research to the existing knowledge base.
Conduct a literature review: Before finalizing your research topic, conduct a literature review to familiarize yourself with the existing research and identify any gaps or areas for further investigation. This will help you refine your topic and ensure its originality.
Consult with experts: Seek feedback from your professors, advisors, or other experts in the field of education. They can provide valuable insights and suggestions for refining your research topic.
Formulate research questions or objectives: Once you have identified your research problem, formulate specific research questions or objectives that you aim to address in your study. These will guide your research and provide a clear focus.
Consider feasibility: Evaluate the feasibility of your research topic in terms of available resources, data availability, and ethical considerations. Make sure your topic is manageable within the given constraints.
Stay flexible: Keep in mind that your research topic may evolve as you delve deeper into the literature and conduct your research. Be open to adjustments and modifications along the way to ensure that your topic remains relevant and aligned with your research goals.
By following these tips, you can develop a strong and focused educational research topic that will serve as the foundation for your study.
In conclusion, educational research topics play a crucial role in advancing our understanding of various aspects of education. These topics provide opportunities to explore innovative teaching methods, evaluate the impact of interventions, and investigate factors that influence student learning and well-being.
By conducting research in high school settings, we can identify effective instructional strategies, examine the role of technology, and understand the importance of student-teacher relationships. Additionally, research topics in education shed light on the significance of parental involvement, extracurricular activities, and social-emotional learning in promoting student success.
Through rigorous investigation, educational research topics contribute to evidence-based practices that can enhance educational outcomes and create a positive impact on the lives of high school students.
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May 2, 2022.
The prospect of returning to UCLA for in-person classes after the pandemic was scary, but in the end, I found some of my worries were overblown.
La unified's independent study less chaotic, but parental complaints persist, february 7, 2022.
L.A. Unified parents say the district’s independent study program has improved from the fall, yet they remain frustrated with its format and curriculum.
Legislature reaffirms quarantined students must be in independent study to be funded, september 13, 2021.
Some changes in the independent study law may help districts, but a teacher shortage remains the biggest obstacle to providing instruction.
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August 26, 2021.
Independent study is this year's at-home alternative to in-person instruction for parents worried about contracting Covid. How will it work?
Many small districts complain california shorted their funding during the pandemic, august 23, 2021.
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August 9, 2021.
Families have a right to independent study instead of in-person instruction; worry about the delta variant may determine how many choose it.
July 15, 2021.
The bill will enable local governments and nonprofits to bypass private companies and build their own broadband infrastructure.
California voters give schools and teachers top grades in year-end survey, july 8, 2021.
Were voters "grading on a curve" in recognition of hard work amid a pandemic? Polling also found growing tensions on race and politics.
July 7, 2021.
The education trailer bill extends independent study to students whose health would be put at risk by in-person instruction.
July 1, 2021.
Almost 35,000 California families filed a private school affidavit to home-school their children during the 2020-21 school year — more than double the number filed before the pandemic.
Grading changes, other covid accommodations await gov. newsom’s signature, june 24, 2021.
An extra year in high school, a Pass or No Pass option and minimum graduation requirements would help undo damage from the pandemic.
June 7, 2021.
Parents and education advocacy groups are urging Gov. Gavin Newsom to extend distance learning provisions for the upcoming school year.
May 18, 2021.
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Over half of california public school students remain in distance learning, may 5, 2021.
An EdSource analysis found far fewer low-income students have returned for in-person instruction and large variations by region.
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HGSE's research, coursework, professional development programs, and faculty expertise spans a broad array of education topics. Browse a sampling of the topics we cover to find content and programs to meet your interests.
Educational research topics: navigating the path to knowledge and innovation.
Educational research is the cornerstone of progress in the field of education. It catalyzes change, informing pedagogical practices, shaping policies, and addressing the diverse needs of learners. The exploration of educational research topics is a journey into the intricacies of teaching and learning, revealing insights that contribute to the ongoing evolution of educational systems worldwide.
Educational research is a systematic inquiry into various aspects of the educational process. It aims to deepen our understanding of how students learn, the effectiveness of teaching methods, and the impact of educational policies. This knowledge, derived from rigorous research, empowers educators, policymakers, and stakeholders to make informed decisions that shape the trajectory of education.
1. technology integration in education.
Exploring the impact of digital tools, online platforms, and interactive technologies on teaching and learning. Investigating the effectiveness of blended learning models and the implications of artificial intelligence in education.
Examining strategies for creating inclusive classrooms that cater to students with diverse learning needs. Assessing the impact of inclusive practices on student achievement and well-being.
Educational Research Topics helps Investigate factors that influence student motivation and engagement in the learning process. Exploring the role of intrinsic and extrinsic motivators in fostering a positive learning environment.
Examining the effectiveness of traditional and alternative assessment methods in gauging student understanding. Investigating strategies for fair and equitable evaluation, considering diverse learning styles.
Researching the impact of professional development programs on teacher effectiveness. Exploring innovative approaches to continuous learning for educators.
Investigating the long-term effects of early childhood education on cognitive and social development. Exploring effective teaching methods for young learners.
Examining the role of SEL in enhancing student well-being and academic success. Investigating the impact of SEL programs on school climate and community dynamics.
Exploring the challenges and opportunities associated with online and distance learning. Assessing the effectiveness of virtual classrooms and the accessibility of online education. Researching various Educational Research Topics may result in more understanding
Investigating the qualities and practices of effective educational leaders. Exploring the impact of leadership on school culture, teacher morale, and student outcomes.
Comparing educational systems across different countries and cultures. Examining the role of education in addressing global challenges and fostering international collaboration.
1 . neuroeducation.
Investigating the intersection of neuroscience and education to understand how the brain learns. Exploring the implications of neuroscientific findings for instructional practices.
Examining the integration of environmental education into curricula. Investigating the Educational Research Topics like the impact of eco-friendly practices and outdoor learning on students’ environmental consciousness.
Exploring the use of data analytics to inform educational decision-making. Assessing the ethical considerations of data use in education.
Research strategies to address educational disparities based on race, socio-economic status, and other factors. Investigating the impact of inclusive practices on overall student success.
Challenges:.
Educational research is a dynamic and multifaceted endeavor, delving into an array of topics that collectively shape the future of education. From the integration of technology to the exploration of global education systems, researchers play a pivotal role in advancing our understanding of effective teaching and learning practices.
As we navigate the vast landscape of educational research topics, it becomes clear that the quest for knowledge is both a challenge and an opportunity. The challenges of funding constraints, ethical considerations, and the implementation gap are met with opportunities for interdisciplinary collaboration, technological integration, and global cooperation.
In essence, educational research topics are the driving force behind innovation in education. It empowers educators with evidence-based practices, guides policymakers in shaping effective policies, and ultimately enriches the learning experiences of students worldwide. As researchers continue to explore new frontiers and address persistent challenges, the collective efforts in educational research pave the way for a more inclusive, equitable, and transformative education system.
Also Read: Multiple Intelligences: What Does the Research Say?
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Graduate student debt is out of control.
Among master’s degree holders, the average debt is $83,651—over double that of undergraduates. In total, 60% of all master’s degree holders have some form of student loan debt. These numbers are according to data compiled by the Education Data Initiative .
The staggering rise in graduate student debt is what inspired a recent report studying the financial returns of online graduate education , published by ThirdWay , a self-described center-left think tank.
The report analyzed more than 1,700 online graduate programs and determined that nearly half—837—did not provide any earnings boost for graduates beyond what they earned four years after a bachelor’s degree.
Chazz Robinson, the report’s author and education policy advisor at ThirdWay, says graduate students largely measure value from an economic boost and that too many programs are just leaving students with mounds of debt—and no salary boost to help pay it off.
While ThirdWay chose not to release the specific degree names of the “no ROI” programs, Robinson explains to Fortune that even in public service fields like social work and nursing assisting, in which salaries may be lower, it doesn’t mean graduate school—especially online–should be expensive.
“Our issue is that if they’re super expensive grad degrees, we want policymakers and institutions alike to really be addressing how much these programs cost and the compensation for these programs, so students are not saddled with these insurmountable debts with degrees that aren’t necessarily paying off for them economically,” Robinson says.
Of the hundreds of schools with “no ROI” programs (many of which are for-profit), nine schools in particular were among the top offenders, including Strayer University , Walden University , and Grand Canyon University . Together, the nine institutions take in a reported $4.6 billion in taxpayer-funded student loans.
The researchers took the median earnings of graduates with an online master’s degree four years after attending each program and compared it to national median earnings of bachelor’s degree.
A lack of transparency from schools about the cost of their programs and the potential outcomes when it comes to jobs and salary can truly hurt students more than others, particularly low-income, minority students, Robinson explains.
“If I already came in with, say, a low income background in debt from undergrad, and then I’m expecting that a grad degree is going to help me be the generational income level to overcome the social stratification I’ve been dealing with, and then that doesn’t happen—that is detrimental,” he says.
More transparency, he says, would not only help policymakers analyze the education world and make changes but it also helps consumers better weigh the pros and cons of a particular institution or even career path.
Fortune reached out to several of the universities mentioned in the report who were noted as having multiple “no ROI” online graduate programs.
Strayer University said in a statement they were unable to comment on a report that they were not privy to its methodology, but added:
“It’s important to keep in mind that Strayer University is an open access institution that primarily serves working adult students who have historically been underserved by traditional higher education. Strayer is committed to helping all students achieve economic mobility and is proud of the successes we have achieved in providing high-quality education to working adults.”
GCU explained to Fortune that “ROI lists” like the one published by ThirdWay are not an adequate measure of student experience and the school makes tuition affordable and has low student loan default rates
“As is the case with the gainful employ m ent regulations , not all academic programs can be measured simply by first-year salary levels,” the GCU spokesperson says. “For example, many students choose degrees in theology, teaching, social work or counseling not because they are high-paying jobs but because it is a lifestyle choice. They deem the work more meaningful to their quality of life.”
“Ivy League schools and expensive private or public universities may not make this “ROI list” because they don’t have a significant number of online programs, but charging $50,000+ for a teaching degree or social work degree with low pay levels is the bigger issue that needs to be addressed,” the spokesperson adds.
The U.S. Department of Education classifies GCU as a “private, for-profit” institution, but the school told Fortune that the state of Arizona and the IRS recognizes it as non-profit.
In October 2021, the Federal Trade Commission put 70 for-profit colleges “on notice” that false promises about graduates’ job and earning prospects could result in significant financial penalties.
Before enrolling in graduate education, it is more important than ever to understand what you are signing up for. Know how much the cost of attendance will be, including tuition, fees, and required textbooks. If you have to sign a student loan, take the time to read the fine print on when you have to start making payments.
While some online graduation programs may not provide income boosts to students, hundreds more do provide career accelerations. For example, online MBAs generally lead students to a promising future in business.
It can also be a great idea to find a recent alumni of the program via LinkedIn or other means and see if they would be willing to discuss their experience during and after schooling. Were they able to land a job after graduating? In what field? What’s their salary like? Was the degree worth it?
Above all, keep an eye out for red flags and know you can carve your own path. There are thankfully hundreds of different opportunities when it comes to online graduate education—at both for- and non-profit schools. If a program is not overly transparent with tuition or career pathways, then maybe check out somewhere new; make sure your educational journey is worth your time and money—and will lead you to where you want to go.
Note: Fortune Education does not invite for-profit institutions to participate in its graduate program rankings .
Mba rankings.
Keeping benefits packages competitive.
The SHRM Employee Benefits Survey returns with new insights for 2024, headlined by modern additions and updated definitions across a wide berth of potential benefits offerings. Evolving upon nearly 30 years of employee benefits research, this comprehensive annual survey of HR professionals captures the prevalence across the spectrum of various employee benefits and perks provided by organizations.
A competitive job market comes with a need for organizations to provide equally competitive benefits offerings. As organizations face labor shortages, those who adapt their total compensation and benefits packages with creative and modern offerings put themselves in better positions to attract and retain talent. The goal of the SHRM Employee Benefits Survey is to gain an accurate representation of benefits offerings throughout the United States. SHRM members can use the findings to discover and benchmark the benefits changes organizations have implemented. With the inclusion of even more items in 2024—as well as new research diving into the average vacation, sick, and PTO days granted by employers—SHRM hopes to provide an even more comprehensive picture of the employee benefits landscape than ever before.
To help you compare your organization’s benefits against those surveyed, we’ve provided an online, interactive benchmarking tool. The power is in your hands to explore results for the last five year and to filter results according to your organization’s industry, size and location. Do you work in health care in California? Results are available specifically for an organization like yours. What about a medium-sized trucking company in the South? Yep, results are available for that as well.*
This tool not only equips you to see the overall results of the SHRM Employee Benefits Survey, but also allows you to call up custom-filtered results any time you need them. You can also export the results for later reference.
We’re excited to share these results and equip you with the information to help you build better workplaces. Select any of the benefits categories on the navigation bar to get started.
*For confidentiality purposes, a minimum of five responses is required to show filtered results. For filters resulting in 5-19 responses, results will display with an asterisk to denote a low response count.
By using the employee benefits survey results interactive online tool you agree to our license agreement. click to see full details..
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Below you'll find a list of education-related research topics and idea kickstarters. These are fairly broad and flexible to various contexts, so keep in mind that you will need to refine them a little. Nevertheless, they should inspire some ideas for your project. The impact of school funding on student achievement.
Metrics. The coronavirus pandemic has forced students and educators across all levels of education to rapidly adapt to online learning. The impact of this — and the developments required to make ...
Online Education Research Paper Topics. This comprehensive guide to online education research paper topics is designed to assist students and researchers in the field of education. The guide provides a wide array of topics divided into ten categories, each with ten unique topics, offering a diverse range of areas to explore in the field of ...
Tallent-Runnels et al. (2006) reviewed research late 1990's to early 2000's, Berge and Mrozowski (2001) reviewed research 1990 to 1999, and Zawacki-Richter et al. (2009) reviewed research in 2000-2008 on distance education and online learning. Table 1 shows the research themes from previous systematic reviews on online learning research.
Table 1 summarizes the 12 topics in online learning research in the current research and compares it to Martin et al. 's (2020) study , as shown in Figure 1. The top research theme in our
The purpose of this study is to analyze the effect of online education, which has been extensively used on student achievement since the beginning of the pandemic. In line with this purpose, a meta-analysis of the related studies focusing on the effect of online education on students' academic achievement in several countries between the years 2010 and 2021 was carried out. Furthermore, this ...
Online Learning Perception and Effectiveness. While the solution allowed students to access information and continue their studies, there was apprehension in regard to the efficacy of online learning and the outcomes such shifts have on students' academic performances. Virtual Learning: Yes and No Argumentation.
Students who struggle in in-person classes are likely to struggle even more online. While the research on virtual schools in K-12 education doesn't address these differences directly, a study of ...
A year into the outbreak, an increasing share of U.S. adults said that K-12 schools have a responsibility to provide all students with laptop or tablet computers in order to help them complete their schoolwork at home during the pandemic. About half of all adults (49%) said this in the spring 2021 survey, up 12 percentage points from a year ...
Lana Parker, University of Windsor. A policy of "choice" for full-time online schooling would weaken public education, erode funding for in-classroom supports and drive those who can afford it ...
Education research paper topics refer to a wide range of subjects that students can explore in the field of education. Here is a list of topics for your inspiration: Impact of Online Learning on Student Engagement and Academic Performance. Effectiveness of Project-Based Learning in Promoting Critical Thinking Skills.
Nearly one-in-five teens can't always finish their homework because of the digital divide. Some 15% of U.S. households with school-age children do not have a high-speed internet connection at home. Some teens are more likely to face digital hurdles when trying to complete their homework. fact sheetNov 20, 2017.
ERIC is an online library of education research and information, sponsored by the Institute of Education Sciences (IES) of the U.S. Department of Education.
Educational Research Topics are as follows: The effects of personalized learning on student academic achievement. The impact of teacher expectations on student achievement. The effectiveness of flipped classroom models on student engagement and learning outcomes. The impact of classroom design on student behavior and learning.
250+ Educational Research Topics: Exploring the Path to Educational Excellence. Education is the cornerstone of human development, and its continuous improvement relies on diligent research and exploration. Educational research topics serve as beacons, guiding scholars and practitioners toward innovations that enhance teaching methodologies ...
Harvard's flagship education podcast, acting as a space for education-related discourse with thought leaders in the field of education. Translating new research into easy-to-use strategies for teachers, parents, K-12 leaders, higher ed professionals, and policymakers. From world-class research to innovative ideas, our community of students ...
The coronavirus crisis has forced school districts, colleges and universities to shift to teaching and learning online. But distance learning poses myriad challenges in a state of 40 million people where many students still lack reliable access to the internet and the devices they need to succeed in online learning. Under this topic, you will find EdSource's stories exploring these challenges ...
Browse a sampling of the topics we cover to find content and programs to meet your interests. Arts in Education. Assessment. Career and Lifelong Learning. Climate Change and Education. Cognitive Development. College Access and Success. Counseling and Mental Health. Disruption and Crises.
Interactions and Intersections in Education: Challenges and Trends to foster Learning and Wellbeing. A multidisciplinary journal that explores research-based approaches to education for human development. It focuses on the global challenges and opportunities education faces, ultimately aiming to i...
Here are 10 Diverse Educational Research Topics: 1. Technology Integration in Education. Exploring the impact of digital tools, online platforms, and interactive technologies on teaching and learning. Investigating the effectiveness of blended learning models and the implications of artificial intelligence in education. 2.
Future in Educational Research (FER) focuses on new trends, theories, methods, and policies in the field of education. We're a double anonymized peer-reviewed journal. Our original articles advance empirical, theoretical, and methodological understanding of education and learning. We deliver high quality research from developed and emerging ...
Online and On-Ground Education. This paper aims to compare and contrast online and on-ground education and indicate which of the two is more appropriate in the modern world. Distant Education or Traditional Education. Essay aims to analyze and study both types of education to compare and highlight key features.
Still, Google Books is a great first step to find sources that you can later look for at your campus library. 6. Science.gov. If you're looking for scientific research, Science.gov is a great option. The site provides full-text documents, scientific data, and other resources from federally funded research.
The Benefits of Online Education in a Virtual Classroom Drexel University School of Education. Similar to attending a physical campus and learning in person, there are advantages and disadvantages of attending a virtual classroom and learning online. Among the many benefits of online learning, you'll find that virtual education allows you to enjoy a more flexible schedule, can reduce the ...
New research highlights that hundreds of online graduate-level programs—at both for- and non-profit schools—yield no income boost to graduates. Students from hundreds of schools—both for ...
Evolving upon nearly 30 years of employee benefits research, this comprehensive annual survey of HR professionals captures the prevalence across the spectrum of various employee benefits and perks ...
Anatomical Sciences Education journal provides an international forum for the exchange of ideas, innovations and research in topics related to anatomy education. Bodies in the anatomy laboratory: A note on terminology - Štrkalj - Anatomical Sciences Education - Wiley Online Library