Ms. Gardenia's Speech Room

Using Word Associations in Speech Therapy

Word associations have been used in speech therapy for ages. We use them in word finding activities, as semantic prompts when a patient has difficulty answering questions, to increase vocabulary, as a memory strategy, and much more!

These word association presents were created as a gift to you for your ongoing support and encouragement. I hope you can use them in your school or adult therapy setting.

I like to use this type of activity in a co-treatment with Physical or Occupational therapy. It is great for language and also attention. If a patient is standing, have them match the associated pairs of words on a table or standing frame.

You may be able to complete some on-site documentation while the patient works along side of you, matching the cards.

Printing on bright, colorful paper (like these Astrobrights) make the activity more visually engaging. (Affiliate link)

word association tasks speech therapy

Click on the picture above or HERE to download your free gift for working on association pairs from Ms. Gardenia’s Speech Room!

For more speech and language activities created with the adult patient in mind, please click here.

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Word Association Game and Describing Activities – In the Doghouse

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A word association game that will build description skills too.

In this fun dog-themed game, students match the pictures that go together, then describe how they are related using visual support. This resource is great for describing by naming attributes, similarities, differences and comparing and contrasting too.

Differentiation is made easy with the provided visual supports for sentence structure, associations, and description. I’ve included multiple activities with this word association game, so you’ll easily be able to use this resource for a variety of ages and skill levels, from Pre-K to 4th!

Use the In the Doghouse word association game in small group speech therapy, literacy centers, or for RTI instruction. This kid-pleasing open-ended board game features a mischievous little dog who gets into a bit of trouble on his way back to his doghouse. You can use this versatile game with the included association word pair cards, or with any prompts for any goal.

➤ Here’s What’s Included::

  • 30 pairs/ 60 picture cards of associated objects
  • Word Asociation Pairs Reference Cards
  • How are they similar? Visual Cue Card to help children identify commonalities
  • How are they Different? Visual Cue Card to help children identify differences
  • Sentence Mat to support children in constructing a sentence describing how pairs are associated.
  • 3 Graphic organizers:
  • Write the Similarities
  • Write the Differences
  • Compare and Contrast
  • In The Doghouse! A fun word association game or use it open-ended for any goal. 
  • A black & white ink-saving version is included

How to Use this Resource:

  • The describing cue cards: How are they similar? and How are they different? Describing can be a tough skill to learn! There are two cue cards that will help children describe how pairs are related. For readers, place the card in front of the student as they describe the features of the pictured objects. For students who do not yet read, you may read each cue to them and help them brainstorm the answers.
  • The sentence mat helps children describe the relationship in a complete sentence. Place the associated pair of cards on the puzzle pieces. For non-readers, point to each card as you say the sentence, and have your student repeat the sentence when describing. If your student is a reader, have your student read and use the sentence to begin their description. ” ___ and ___ are alike because___.”
  • In the Doghouse! Word Association Game: Put the word association cards together in matched pairs. The child takes a pair and describes how they are related, then spins the spinner and moves the game piece. The object is to get the mischievous little puppy dog back to his doghouse. The game includes four game “circles” to use as markers as your children play the game. Use a binder clip to keep the game pieces upright or use any game pawn you may already have.
  • Play a Memory game: Turn the cards face down, then turn over two at a time. When an associated match is found the child keeps the pair and describes how the pair is related. The wordlist cards can be used to help identify matches.
  • The graphic organizers can be used with the B&W pictures to help children as they write the similarities and differences. Cut and paste a pair of pictures on the organizer, then write/ describe the relationship between the two words using the graphic organizer. Great for homework too!


❤ If you like this product, you may enjoy these activities:

Category Bingo Riddles Make working on naming categories and categories and category members super fun with this bingo game that has rhyming riddle clues.

Pronouns and Plurals Dress Me Community Helpers Perfect for preschool,  kindergarten, and first grade, your students will love dressing the community helpers as they practice vocabulary and grammatical structures. Make a cookie sheet activity or use the black and white printables.

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word association tasks speech therapy

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The Oxford Handbook of the Word

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The Oxford Handbook of the Word

26 Word Associations

Simon De Deyne, University of Leuven, Belgium

Gert Storms, Laboratory for Experimental Psychology, University of Leuven, Belgium

  • Published: 03 March 2014
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Word associations have been the topic of intensive study in psychology as they offer one of the most direct ways to learn about the mental lexicon. This chapter provides an overview of the role of word associations in psycholinguistic research. The first part explains what associative responses are, how they relate to lexical contiguities derived from language, and how recent developments have made possible the representation of the mental lexicon as a network using large association data sets. The second part discusses the implications of this network, concentrating on how lexical availability enhances word processing. This is followed by a discussion of new developments regarding the study of the global structure of large word association networks as they grow over time, and of lexical search and retrieval through the process of spreading activation. The chapter concludes with some suggestions for future directions.

26.1 Introduction

The word association task is one of the most archetypical experiments in psychology. In a typical word association task, a person is asked to write down the first word(s) that spontaneously come to mind after reading a cue word. This straightforward task is referred to as a free association task, since no restrictions are imposed on the type of answers that are produced. In this sense it is different from related procedures such as verbal fluency tasks, in which one must, for example, name as many animals or words beginning with a given letter as possible.

For over a century, psychologists and psychiatrists like Galton (1880) and Bleuler (1911 /1950) have been fascinated by the way word associations offer a window on structures and processes in the human mind. Even today, the word association task remains an influential tool in cognitive science for the same reasons.

While the basic experimental paradigm has not changed much, the implications, usage, and understanding of the word association task has changed significantly throughout its history. Many of these changes reflect the evolution of the last decades, such as advances in neuro-imaging and electrophysiological techniques, further theoretical developments in network theory, and the availability of large amounts of data and massive computational power. A first surge in the study of word associations reflected the prevalent behaviourist ideas of the time by focusing on the notion of direct association strength, where associations represented a conditioned language response to a verbal cue. This associative strength reflects the fact that most people give similar responses in a word association task. For example, when they are presented the cue word hammer , the associate response nails is given by almost half of all participants and with twice the probability of the response wood . The notion of strength is still important in explanations of several psychological phenomena such as our ability to recall words from episodic memory. A frequently used paradigm to test how associative strength affects the ease of recall is the cued recall task (for an overview see Nelson, Schreiber, and McEvoy 1992 ) . In this task participants are asked to memorize a list of words and are later asked to recall as many words as possible in response to an associated cue. For example, the success of recalling the studied word cork when presented with the cue bottle will depend on the associative strength between these words ( Nelson and Bajo 1985 ). Associative strength is also central to semantic priming, a phenomenon where recognizing a target word (e.g. butter ) is enhanced by an earlier presented cue word, or prime, that is strongly related (e.g. bread ) in contrast to a weakly related one (e.g. jam ). In most cases, the target is recognized or named faster, and the magnitude of this effect depends on the strength of the relationship between prime and target; this can be expressed by the number of associates they share (see Lucas 2000 for a detailed discussion).

From the 1960s researchers proposed that the focus on associative strength between isolated word pairs was not suited for the study of the meanings of words. Especially the work by Deese indicated a radical departure from a narrow view on word associations based on strength between single pairs of words ( Deese 1965 ; Szalay and Deese 1978 ). According to this new approach, the central issue is not the single connection but how the meaning of a word is conveyed by the entire set of connections to the stimulus in a larger network of knowledge. This shifts the focus from stimulus–response properties, such as associative strength between two words, to their response distributions. It offers a way of quantifying how closely related two words are by looking at the commonalities between two words. In this second approach, the words blood and accident might not be directly associated, but the overlap of these words with common associations such as wound , hurt provides insight into the way they are related. This idea was initially explored in Deese’s (1965) 1 factor analytic studies on nouns and adjectives, and inspired many modern approaches to semantic memory that rely on distributional similarity, such as Latent Semantic Analysis (LSA: Landauer and Dumais 1997; Steyvers, Shiffrin, and Nelson 2004 ) and topic models ( Andrews, Vinson, and Vigliocco 2008 ). These models are founded on the notion that the meaning of a word can be derived from the context in which it is used. Since we are exposed to thousands of words every day, this context is rich, and tracking regularities in language allows us to discover a significant part of the meaning of words. The strength of these models hinges on the massive amounts of information available in co-occurrences in written and spoken language which allows the inference of meaning beyond the contexts in which a word occurs. This way, statistical techniques similar to the factor analytic studies by Deese (1965) allow us to infer that the words cosmonaut and astronaut have the same meaning, even though are not strongly associated and rarely co-occur in the same text. If they occur in a sufficiently large number of similar contexts, this is a strong indication that their meanings are related. In the case of word associations, two words will have a similar meaning not because they are associated, but because they have many associates in common. This approach has been very successful in the study of semantic similarity of words, vocabulary acquisition, and episodic and semantic priming described earlier.

Most recently, the global structure of the network has become a frontier to the field. This approach demonstrates how networks or graphs derived from association data are used to learn about the development of language and the way words are retrieved efficiently. The large networks in which related words are connected show structure that is not apparent by looking at the strength of the connection between pairs of words or the associations they share. One of the key findings is the fact that the mental lexicon is organized as a small world network, where similar words are clumped together and any word can be reached by taking only a few hops in the network ( Steyvers and Tenenbaum 2005 ; De Deyne and Storms 2008b ). Such an organization promotes the ease of retrieval of words from the lexicon and makes the network more resilient to damage.

These three lines of research correspond to a shift from local interactions between pairs of words to interactions within a subgraph (meaning derived from distributional measures) and global characteristics of the network (network topology and centrality). These three levels, reflect the microscopic, mesoscopic, and macroscopic structure in the network and represent a recurring theme useful for discussing how recent findings from word associations inform us about structure of the mental lexicon at different scales. Section 26.2 describes the large-scale word association norms that are available. Next, Section 26.3 explains how they are characterized in terms of their semantic content and how different theories account for the variety of associative responses. Not surprisingly, word associations are closely related to the language used in daily life, but there are important points of divergence that are often overlooked. These will be discussed at the end of this section.

When studying the mental lexicon 2 through word associations, we often think of it as a network where nodes are automatically activated through spreading activation. This network-based view helps us to understand many word processing advantages that underlie effects of word frequency and context variability. The last part of this Chapter (Section 26.5 ) focuses on networks derived from word associations. It starts with a discussion of how a weighted directed network can be constructed as an approximation of the mental lexicon, and considers how empirical findings of various lexical and semantic centrality effects can be explained by such a network. This section closes with a macroscopic view of the network by looking at its global properties, specifically from the perspective of how the network might change and grow over time. Using knowledge about the global network structure, this section ends with a discussion of spreading activation as a mechanism for retrieving information from the network. Especially the surge of interest from network science in other fields including psychology has led to a renewed interest in network approaches to the lexicon. In the final section we speculate on how very recent developments are likely to shape our future understanding of the mental lexicon.

26.2 Word association data sets

Before discussing the theoretical and empirical findings derived from the word association task, a short overview of the availability of norms is in place. While there is a large collection of norms available based both on normal and non-normative populations (cf. Cramer 1968 ), few studies have attempted to compile a reasonably sized approximation of a semantic network. The largest British English word association databases are the Edinburgh Associative Thesaurus (EAT: Kiss et al. 1973 ) and the Birkbeck norms ( Moss and Older 1996 ). The EAT associations consist of responses for 8,400 cues collected between 1968 and 1971 from 100 speakers, while the Birkbeck norms include 40–50 responses for a total of 2,646 cues. For American English, the University of South Florida dataset (USF: Nelson, Schreiber, and McEvoy 2004 ) describes norms based on 5,018 cues collected from the late 1970s onwards and has been used in numerous studies.

Large sets of associations (for more than 1,000 words) have also been collected in languages other than English, including Korean ( Jung, Na, and Akama 2010 ), Japanese ( Okamoto and Ishizaki 2001 ), and Dutch. Currently, the Dutch dataset represents the largest resource publicly available. It consists of 12,000 cues and more than 3 million responses ( De Deyne, Navarro, and Storms 2013 ). In contrast to previous studies in English, it uses a continued rather than discrete procedure, in which each participant gives three associates to every word on a list of cue words. In this study, new cue words are gradually added using a snowballing principle by which, starting from a small seeding set of words, new words are added based on the frequency with which they occur as responses. 3

26.3 Composition and origins of word associations

While the free association task itself is straightforward, its unconstrained nature makes it difficult at first to grasp what association responses actually tell us about the lexicon. Many accounts hinge on the intuition that word associations reflect our experience with written and spoken language in a verbal stimulus–response kind of manner. However, such a view might oversimplify matters. To understand the nature of word association responses, we can investigate the syntactic and semantic properties of the responses. The most obvious observation is that associative responses are far from homogeneous. They include clang responses ( butter – batter ) which indicate a phonological or orthographic relationship and different kinds of semantic relationships such as contrast ( man– woman, dark – bright ), coordination ( apple – pear, green – red ), near synonymy ( sour – tart ), and thematically defined relations ( hammer – nail, mouse – cheese ). The responses can also be distinguished according to whether the cue–response relationship is syntagmatic or paradigmatic. In a syntagmatic relationship ( smelly – cheese ), cue and response have a different syntactic role in a sentence and can belong to different part-of-speech classes. A syntagmatic relation need not be one that is current in normal speech, as with yellow and banana . In a paradigmatic relation ( cheese – socks ), the words have the same syntactic function in a sentence.

(a) Distribution of paradigmatic and syntagmatic responses for adjective, noun, and verb cues; (b) semantic composition of association responses.

Differences between responses depend on the individual, on the response position in continued association procedures, and on the characteristics of the cue. Clang responses, for example, often occur faster than semantically related responses, and are quite frequent with second language learners ( McCarthy 1990 ) and patient groups. Paradigmatic responses are the most common type in adults, while children until the age of 9 provide more syntagmatic responses ( Nelson 1977 ). This difference has been explained in terms of increasing word understanding, especially through reading ( Cronin 2002 ). Fig. 26.1 shows the distribution from De Deyne et al. (2008) of syntagmatic vs. paradigmatic responses over various word classes as well as a characterization of their semantic composition. Fig. 26.1(a) illustrates the dominance of paradigmatic responses for nouns and syntagmatic responses (mostly nouns) for adjectives and verbs; Fig. 26.1(b) shows the semantic distribution of the responses. Taxonomic responses include contrast, coordination mentioned earlier, but also superordinate or hypernymy ( apple – fruit ) and subordinate or hyponomy ( apple – jonagold ) responses. Entity or meronymy responses correspond to attributes or features that are part of the concept ( dog – tail ). While both entity and taxonomic responses contribute to what is often understood as the denotation of a word or the semantic content necessary for defining a concept, the most common responses in word association data are those that capture thematic relations, indicating some sort of contiguity in time and space rather than similarity in meaning. Together with introspective judgements such as sunset – nice , thematic responses indicate that the task is very sensitive to the connotation of words. Finally, many non-semantic responses indicate purely lexical information such as compounding ( water – fall ), idiomatic uses ( sour – grapes ), or rhyme ( talk – walk ). Apart from the relative importance derived from response counts, reaction times and the sequence of different responses in continued word association tasks indicate that some types of semantic information are more readily available than other types ( Barsalou et al. 2008 ; De Deyne et al. 2008b ). Taxonomic and lexicon information including clang and compounding responses in particular are more readily available than other types of responses. Learning about the types of responses using this qualitative approach offers a first way to refine semantic theories about how the mental lexicon is organized and how it interacts with other types of representation. This will now be discussed.

26.3.1 Theories of semantic memory and word associations

Word associations are part of many models of word processing, but the debate about their origin and role is still ongoing. There are at least two different points of view worth mentioning. According to one, word associations mainly reflect word co-occurrence in language. A second view acknowledges this contribution from language, but proposes that word associations reflect an additional kind of process. This process gives rise to distinct mental properties that go beyond the information captured in written or spoken text. Recent revisions of this idea describe these additional properties in terms of an embodied view (e.g. Barsalou 2008 ) which would allow a contribution of more thematic or situated sensory-dependent simulations in the process of generating word associations.

26.3.2 Word associations as a manifestation of lexical co-occurrence

One school of thought treats word associations purely as a variable to be explained. According to this view, words that frequently co-occur will become associated and consequently activate each other in the lexicon ( Spence and Owens 1990 ). As a consequence, word associations mirror the same statistical patterns as those derived from lexical co-occurrence.

Studies that compare association response frequencies with predictions from computational models using text co-occurrences show that such a relationship is indeed present ( Griffiths and Steyvers 2003 ; Hahn and Sivley 2011 ; Wettler, Rapp, and Sedlmeier 2005 ). This view is also supported by experimental findings where new word associations are added to the lexical network. In a lexical decision task, Schrijnemakers and Raaijmakers (1997) showed that associations initially established in episodic memory by simple co-occurrence activate different semantically related words from those that are already represented in the adult lexicon. However, this might not be the complete story, as results of these studies are far from univocal. The findings from word co-occurrences derived from text invariably report only a moderate correlation with association frequencies. One possible reason for the limited success is the treatment of documents as a ‘bag-of-words’ in many large-scale co-occurrence models. This ‘bag-of-words’ term indicates that only the occurrence of a word in a document or paragraph is considered. It ignores other potentially important information such as syntax, word order, or the more abstract mental representations we need to construct when interpreting a sentence (cf. Kintsch 1988 ). These limitations are confirmed by other empirical findings on how word associations are formed. For example, Prior and Bentin (2003) showed that incidental associations were formed more easily if words were presented in a sentential context than when words were presented as isolated pairs. These findings were interpreted as evidence for the integration of lexical associations during a late stage of processing in which a mental model is constructed and related to existing world knowledge.

Finally, the word association task itself poses different constraints for responses than those in ordinary conversation: they are free from a speaker’s intention to communicate some particular conceptual content in a given discourse context. Instead, they are simply the expression of thought ( Szalay and Deese 1978 ). In part, this attempt to approach a language of thought is what makes word associations unique and useful compared to methods based on statistical patterns in spoken and written text.

26.3.3 Dual process and embodied accounts

The heterogeneous character of word association responses and the typical order in which these types are generated highlighted in the previous section suggests the existence of qualitatively different underlying processes or representations. Many theoretical proposals on how people generate word associates draw strongly on dual process accounts. For example, de Groot (1980) proposes that these responses depend on both a fast process for directly connected words and a relatively slow process that makes no use of automatic connections between associated words but which depends on meaningful interpretation of the cue. Along the same lines, Barsalou and colleagues have presented a dual process account that relies on both linguistic and situated simulations ( Barsalou et al. 2008 ; Santos et al. 2011 ). According to this theory, certain types of information become activated very quickly. This is attributed to distributional properties of language, such as the frequent co-occurrence of words. Other information only becomes available after extended processing, which requires the situated simulation of conceptual properties. Supporting evidence comes from neuro-imaging studies where fMRI measurements showed that during a property generation task and an association task, linguistic areas such as Broca’s area became activated during early responses and areas such as the precuneus, which are often associated with mental imagery, became activated during late responses ( Simmons et al. 2008 ).

A final aspect of the mental lexicon that is often overlooked relates to the fact that words like trouble and vacation and many others differ in terms of valence, i.e. the degree to which they carry a positive or negative connotation. Particularly through word association data, valence is revealed to be an important structural property of the lexicon, as shown in Deese’s (1965) work on adjectives. The way modality specific information including emotions affect word associations indicates considerable overlap between the types of semantic properties encoded in a lexico-semantic system and modality-specific representations based on perceptual simulations. This is supported by recent studies showing that purely linguistic context provides enough information to account for findings previously explainable in an embodied account only. These studies show how linguistic co-occurrence data can predict whether a word encodes auditory, olfactory, or visual information ( Louwerse and Connell 2011 ), the location of places on a map ( Louwerse and Benesh 2012 ), or the valence of words ( Hutchinson and Louwerse 2012 ). The fact that different aspects of meaning become encoded in both a lexico-semantic and more sensory-specific system reflects some redundancy, which is not that surprising considering that language reflects the structure of the physical environment. Studying the semantic types of word association responses and the time-course of these responses in word associations offer us the opportunity to study this issue in depth. As noted earlier, the goals of communication and lexicosemantic representation are likely to offer only indirect access to certain semantic properties such as valence while previous work suggests that word associations provide a privileged route to this knowledge.

The conclusion from this review echoes the claims found in the literature on corpus linguistics and associations reviewed by Mollin (2009) and in the domain of lexicalized concepts by McRae, Khalkhali, and Hare (2011) , stating that the association task does not reflect authentic language production, but should rather be seen as tapping into the semantic information of the mental lexicon. Such a proposal also aligns with the original ideas of Collins and Loftus (1975) , in which the network depends both on semantic similarity and lexical co-occurrence in language. The idea of a network and its intimate connection with word associations has recently experienced a surge of interest. In the following section we will show how the implementation of these ideas in a realistic sized network offers a new perspective on the structure and growth of the mental lexicon.

26.4 Word association networks

The metaphor of the mental lexicon as a web of connected words goes back to the 1960s, when notions of graph or network theory were first applied in the context of word associations ( Pollio 1966 ; Kiss 1968 ). In contrast to distributed semantic networks, where the meaning of a single word involves multiple processing units (e.g. Plaut et al. 1996 ), such a network is often constructed as a localist network, where each node in the network corresponds to a word. Apart from word associations, such networks can also be based on other resources such as written text corpora, feature norms, or linguistic expert knowledge (cf. WordNet: Fellbaum 1998 , and this volume). In the case of word associations, the network consists of nodes corresponding to cue words and unlabelled links connecting them. The network captures the aggregated responses from numerous people. Given that communication is central to language, one can expect that convergence to a shared underlying network might be beneficial. As such, the mental network represents a cultural artefact accessed by language users with different vocabularies but who share a broadly similar linguistic environment. While this network is still a gross simplification of how words are represented in the brain at the level of the individual, representing our knowledge of words in networks offers advantages of flexibility and interpretability. First of all, networks scale well: we can easily represent the knowledge of tens of thousands of words and the connections between them. Second, networks imply processes that operate on them. One example is spreading activation, discussed in the next section. Third, network links can be directed, weighted, and qualitatively varied. For example, a directed network can account for asymmetry effects in priming, where the prime engine will strongly facilitate processing the target car , but not vice versa (e.g. Koriat 1981 ). It can also explain asymmetry in relatedness judgements for pairs like china–korea , where Korea is considered more similar to China than vice versa ( Tversky 1977 ).

There are also disadvantages to approximating the mental lexicon with networks derived from word associations. A first one has to do with the size of the network. If a person responds with an association that was never presented as a cue, little can be inferred about its connectivity in the network, as its node has no outgoing links. Since only words that were presented as cues can be considered, the reliability of network-derived measures depends entirely on the number of cues in the study. To know how many nodes are needed to get a fairly good coverage of the mental lexicon, one can look at estimates of vocabulary size. However, such estimates vary considerably, depending on how words are counted and what is understood as knowing a word: 40,000 is often quoted as the number of words known by the average American high school graduate ( Aitchison 2012 ). A measure of the coverage of the network would be more useful. As reflected by Zipf’s law, most words are very rare and a few words occur extremely frequently. If the words in the network are weighted by their token count, a network of 12,000 nodes captures more than 90 per cent of the words encountered in written texts ( De Deyne et al. 2012 ).

A second limitation concerns the absence of weak links in the networks. Most studies use a discrete free association task, meaning that each person generates only a single response per cue. For a cue like tulip , 69 per cent of the participants respond flower . This illustrates how strong associations mask the presence of weaker ones. In discrete tasks, response frequencies are only reliable for very strong associations, while weaker links are unreliable or missing ( Nelson, McEvoy, and Dennis 2000 ). This absence of weak associations is seen as an important drawback of the association procedure ( Aitchison 2012 ). It also led to questioning the results of previous findings in mediated priming (e.g. Ratcliff and McKoon 1994 ), where prime and target are only indirectly related through a mediator (e.g. lion → tiger → stripes ; see Fig. 26.2 for an illustration). The difference in reliability between weakly and strongly related words presumably affects a host of other tasks that require access to the mental lexicon. Additional evidence for the missing weak links comes from studies where participants judge the associative strength of word pairs: participants judge pairs to be related, even if they never co-occurred as cues and associates ( Maki 2007 ). Fortunately, this last limitation is mostly practical in nature. Recent studies address this problem by using a continued procedure where each participant provides multiple associates to each cue, covering weak links and increasing the density of the network. As predicted, these weak links are important at a behaviour level, and explain the variability in numerous semantic and word processing tasks ( De Deyne, Navarro, and Storms 2013 ).

26.4.1 Lexical and semantic richness effects in terms of network centrality

One of the best-documented findings in visual word processing concerns differences in the ease of processing certain words over others. These differences are explained by a range of extrinsic variables such as word length, printed word frequency, imageability, the age at which the word is acquired (age of acquisition, or AoA), and context variability. Possible accounts of how these extrinsic factors determine word processing often resort to explanations in terms of connectivity differences between words in a network representation of the lexicon. To date, only a few of these theoretical claims have been directly tested. In the case of word imageability, concrete words are thought to have a different number of connections compared with abstract words ( de Groot 1989 ). For AoA, the word processing advantage for early acquired words can be explained by the incremental acquisition of the lexicon which positions these early-acquired words more centrally in the network than later-acquired words (see De Deyne, Navarro, and Storms 2013 ). Similar network accounts exist for word frequency, number of dictionary meanings, and context diversity. The distinction between strongly connected words and sparsely connected ones is also framed in a more intrinsic fashion using studies that look at semantic richness effects in word processing ( Pexman, Holyk, and Monfils 2003 ). In these studies, the number of different associates of a cue (i.e. its set size or out-degree) consistently affects the results of various visual word recognition tasks including lexical decision and word-naming reaction times, but also tasks where semantic involvement has been limited or semantic effects have been inconclusive, such as perceptual identification or sentence reading ( Duñabeitia, Avilés, and Carreiras 2008 ). All these accounts share the idea that the structure of the mental lexicon determines how efficiently people can retrieve and produce words.

However, there are many ways to measure network structure which could affect the ease of word processing. Consider the network in Fig. 26.2 that shows the structure around the node tiger . The importance of the node can be judged by the number of incoming links (less important than lion ) or the number of outgoing links (more important than bear ).

Because simple measures like the number of incoming and outgoing links do not fully exploit the information encoded in the network, more sophisticated measures might provide more detailed answers. A richer index of centrality would be one that also takes into account the structure among the connected nodes such as the degree to which the neighbours of tiger themselves are connected. Examples of such measures include clustering coefficients, betweenness, and PageRank. Each of these measures goes beyond counting the number of incoming or outgoing links. The clustering coefficient measure is related to in- and out-degree, but is more sophisticated by considering how often the direct neighbours of a node (i.e. the nodes directly connected to it) are connected themselves. Thus, words with strongly interconnected neighbours are considered to be semantically coherent. The neighbours for a word like bank might reflect a more loose semantic coherence, due to the presence of multiple senses. Other measures like betweenness and PageRank include information of the whole network to determine how central or important a node is in the network structure. Betweenness captures how many times you can encounter a node by traversing paths in the network. PageRank is slightly different in the sense that it is a recursive measure. It detects nodes that are central by taking into account the centrality of the neighbours of a node as well. While no systematic studies have compared multiple tasks and indices, a couple of studies suggest such measures have potential. In these studies, elaborate measures like PageRank capture effects of both semantic processing ( De Deyne and Storms 2008b ; De Deyne, Navarro, and Storms 2013 ; Griffiths, Steyvers, and Firl 2007 ), in which networks are formed based on shared meaning or associations, and phonological processing, using networks where words with similar phonology like cat – hat are linked ( Vitevitch 2008 ).

Simplified network around the node for tiger . Nodes with more incoming links (i.e. larger in-degree) are larger. Edges with stronger weights are darker.

26.4.2 Global network properties, network growth, and spreading activation

While looking at the interconnectedness of a single node or a pair of nodes in the network is useful for studying how central and meaning-related words are, the properties of large-scale networks that become apparent only when this network is studied as a whole. A number of studies (e.g. De Deyne and Storms 2008b ; Steyvers and Tenenbaum 2005 ) have found that, similar to other growing networks, the global structure of word association networks does not have an arbitrary organization but corresponds to a small world structure with on average 3–4 nodes between any two words. Such a structure was also found in a study by Milgram (1967) , who reported that any two persons in the United States are separated by on average six other persons who know each other pairwise. A similar structure was found for many other networks, and the chapter on word frequency by Joseph Sorell (this volume) provides a more detailed discussion using examples from text corpora and the World Wide Web.

In addition to short average path lengths, small world networks exhibit small diameters and high clustering. These properties allow efficient word search and retrieval and make the network robust against damage ( Steyvers and Tenenbaum 2005 ). One property of this topology is the presence of a small number of hubs, i.e. nodes with degree values much higher than average. Table 26.1 gives ten examples of hubs for three recent datasets and Fig. 26.3 shows their role in the network as a whole. The rankings in Table 26.1 are very similar, regardless of the measure used (in-degree or PageRank) or the type of network. Although speculative, this might indicate that certain properties are universally more central in the human semantic system. The list of hubs also indicates how word associations reflect psychological or subjective meaning. For instance, if we ignore pronouns and articles but look at the most frequent adjectives and nouns in English and Dutch using the SUBTLEX frequency counts ( Brysbaert, New, and Keuleers 2012 ; Keuleers, Brysbaert, and New 2010 ), the most important hubs, indicated by word frequency counts, are { good , time , man , way , sorry , people , thing , sir , little , night } in English and { good , man , people , day , woman , time , beautiful , year , death , life } in Dutch. Despite the fact that words at the high-end spectrum of the frequency distribution tend to be stable, they agree only moderately with respect to which entries of the mental lexicon are considered central. Moreover, a similar pattern of divergence between psychological centrality and linguistic centrality can be observed in the hubs reported by Steyvers and Tenenbaum (2005) for the networks based on Roget’s thesaurus (Roget 1911): { light , cut , hold , set , turn } or WordNet ( Miller 1995 ): { break , cut , run , make , clear }.

Visualization of the Dutch word association lexicon based on the first response for over 12,000 words in the word association task from De Deyne et al. (2012) . The size of the nodes indicates the importance of a word in terms of in-degree. A small number of these nodes have an in-degree that is much larger most other nodes. These nodes are considered network hubs and some examples that also occur in Table 26.1 are labelled.

A possible approach to the small world structure of the mental lexicon is to regard such a structure as the manifestation of an underlying growth process, a property shared with other dynamic networks such as networks of scientific collaboration, neural networks, and the World Wide Web ( Watts and Strogatz 1998 ). The most influential account is based on preferential attachment whereby new nodes become connected to the network in proportion to the number of existing connections they have with neighbouring nodes. While this idea works well using an aggregate network, the growth of the mental lexicon in a single individual might require a slightly different attachment scheme. For example, according to the mechanism of preferential acquisition, new nodes might become preferentially attached to other nodes depending on the structure of the learning environment ( Hills et al. 2009 ). Regardless of the differences between these accounts, both are able to predict a number of interesting phenomena. For instance, the network growth model by Steyvers and Tenenbaum (2005) explains how the age at which a word is acquired and its frequency in language independently contribute to the ease with which a word is processed. In addition to large-scale modelling approaches, studies on the development of individual networks in children have shown that small world connectivity is indicative of later vocabulary development, where children with more cohesive and structured networks are more proficient language learners ( Beckage, Smith, and Hills 2010 ).

One of the hallmarks of the small world architecture is efficient search due to the short distances in the network and its clustered structure. One way of accessing the mental lexicon is based on the idea of searching a network through a mechanism of spreading activation ( Bock and Levelt 1994 ; Collins and Loftus 1975 ). When a word represented by a node in the network becomes activated, for instance during reading, connected nodes are also activated. This spreading activation mechanism has been very influential, as it describes a plausible mechanism for searching and retrieving words in the mental lexicon. It explains a whole range of findings including automatic priming ( Neely 1977 ) and the occurrence of hesitation pauses within sentences ( Schachter et al. 1994 ). This activation process is supposed to be largely autonomous and parallel in the sense that lexical retrieval entails automatic access to the meaning of a word. For instance, when participants are presented with ambiguous words, the different senses automatically become activated ( Seidenberg et al. 1982 ).

Spreading activation has also been criticized, since it might be too flexible and unconstrained ( Ratcliff and McKoon 1994 ). Due to the short distances in a small world network, any two words can be reached in fewer than three steps. This would imply that the entire network becomes activated every time activation spreads. Additional assumptions are needed. A first solution assumes that activation decays over distance where distant nodes receive less activation than close ones. In addition, one could also assume that nodes with many links will result in a more diffuse activation. The idea of spreading activation is often implemented as a Markov chain or random walk over the network (e.g. De Deyne et al. 2012 ; Ramage, Rafferty, and Manning 2009 ), closely similar in spirit to the PageRank measure introduced earlier. For example, in a study by De Deyne et al. (2012) , participants were presented with triads such as cup , teacher , and hail that were drawn randomly from a large set of cue words. Many sampled triads were not directly associated. Even when there was no direct association and little semantic overlap, participants showed reliable agreement about which pairs from a triad were most related. The absence of direct association shows an additional effect of the spreading activation mechanism by its ability to enrich the sparse network with additional information derived from indirect links between nodes. While such a model was quite successful in predicting the participants’ preferences among the triads, it corroborates the point made by Deese (1965) that valuable information is encoded in the network structure itself, rather than in the single strengths.

26.5 Future directions

The availability of large mental lexicons derived from word associations and the recent developments in graph theory highlight the direction for future research in the field. A first development follows from a better understanding of the growth and evolution of networks. In line with the network growth models described in the previous section, it would be interesting to see how such a network evolves over time, especially in old age, where the few studies available have not been able to sketch out a coherent picture of the ageing lexicon. For example, similar to qualitative changes in children (see the paradigmatic–syntagmatic shift discussed earlier), evidence from Alzheimer patients suggests that a reverse shift towards syntagmatic responses might occur in old age ( Baker and Seifert 2001 ). However, it remains unclear whether this holds for ageing in general. Other studies show a shift away from responses with negative valence in the ageing lexicon. The structure of the network might also explain semantic errors in many degenerative conditions such as aphasia or the findings of hyper-activation of weakly linked words in schizophrenia (e.g. Rossel and David 2006 ). Moreover, as the web of words is in constant motion whenever new words are added and old ones reinforced, it can be expected that further advances in this field will allow a more dynamic view of the network, which could provide us with better insights into how information becomes activated in a particular context and how the network as a cultural artefact evolves over time.

A related topic is the study of semantic networks at different scales, ranging from a single individual to comparative studies of different cultures and groups of second language learners. A starting point for the latter type of studies was pioneered by Szalay and Deese (1978) , who used a continued procedure to compare the relative importance of certain concepts in different cultures.

A second advancement in graph theory is the way large multiplex graphs are modelled. Combined with a dynamic network view, this might inform us how different types of information become activated over time. Such a multiplex network allows us to incorporate labelled edges in the network, similar to the IS-A, HAS-A labels in earlier network accounts (see Collins and Loftus 1975 ). Identifying these edge-labels might help us to estimate the contribution of different types of information such as thematic, lexical, or perceptual information in a single network.

As is often the case in psychology, perhaps the biggest challenge will lie in further integrating these findings. This will involve integrating the rich research programme on episodic memory using paradigms such as cued recall (e.g. Nelson and Zhang 2000 ), with advanced semantic and word processing theories and models. In sum, representing the mental lexicon as a vast semantic network has been a useful metaphor for many years and its potential to connect at least some missing bits and pieces deserves the large-scale systematic inquiry that has recently taken place.

While an extensive and up-to-date review of the literature on word associations is lacking, the works of Deese (1965) and the review by Cramer (1968) are still relevant. Especially the work by Deese was visionary, as it stresses the importance of the structure of the network of associations rather than the strength of single cue–response pairs, and proposes a method that inspired many distributional lexico-semantic models, influential in the late 1990s.

In contrast to other scholars (e.g. Levelt 1992 ), we focus in this chapter on semantic aspects of the mental lexicon without going into the phonological and morphological properties of words.

At the moment, the same procedure is being used to compile a new English word association dataset. The new study can be accessed at and currently contains associations for 8,000 cue words.

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In Spontaneous Speech

Teaching students to speak clearly and effectively

word association tasks speech therapy

Tag Archives: Word association skills

Speech therapy tasks for our high school level students.

word association tasks speech therapy

I know finding speech therapy materials for high school students can be difficult.  I also know that some students still benefit from  having skills broken down into specific learning modules.  They get lost when presented passages containing complex sentences and unknown vocabulary. Teachers Pay Teachers is having their annual Cyber Sale so I thought I would take advantage by showcasing two of my products that work with the High School crowd.

Recently, I have been a substitute Speech Language Pathologist (SLP) at a high school location.  I found at the  high school level it is often more relevant for students to bring their class work for speech therapy.  However, the students being served often forget and come empty handed.  I try to have activities on hand to make the time productive.  I thought I would showcase 2 activities that have worked well with encompassing what they are working on. They are Word Association Cards for vocabulary development  and Sentence Sequence Task Cards for complex sentence comprehension and development. There are free samples in the Vocabulary section of this blog for the Association cards and in the Expressive section for the Sentence Sequence Task Cards.   If you haven’t tried them yet you should.  If you want to get the full sets at my TPT store, they happen to be part of the  Cyber Sale which makes them a real bargain.  Click on the covers for a direct link to TPT

word association tasks speech therapy

Our speech students are often behind with developing vocabulary.  This affects them throughout all their classes. One way to boost vocabulary is to develop word association skills. They need to be able to compare and contrast new words to integrate them into the vocabulary they already have. I often tell them this analogy: Your brain is a closet with different shelves and drawers  holding different words. You try to place things together that are similar such as your socks in a sock drawer.   If you just try to memorize words without making connections with other words you know, it is like throwing everything  in one big pile on the floor and trying to find a brown sock to match another brown sock.   You won’t be able to find or remember what you have when you need it. It seems many of them can relate to this.   Therefore categorizing and making associations is an important skill to learn for their academic career.   This is a skill that gets better with practice.

word association tasks speech therapy

High School students are often required to take notes on subjects that use a lot of   complex sentence forms.  They they need to be able to consolidate information and retain the meaning in their notes.  Sequencing events using complex sentence forms is a natural way to get students to produce complex sentences and practice this.  These cards present two different activities to address production and comprehension and promote better note taking.

In Activity 1, the students are instructed to use the main details of the three given sentences to form one complex sentence using connecting words such as; and, so, but, because, before, after, when, while, that, and then. In sentence production, students replace parts of the sentence with pronouns to prevent redundancy. They  need to consider which information is most important, hold information into memory, think about time sequence, and then manipulate the ideas into one sentence.  These skills are used in note taking as well as comprehending complex sentences in reading passages.

In Activity 2 the student is presented sentence examples. The students may have developed some of these while completing the first activity. One of the sentences does not have the same meaning as the other two or is an incorrect use of the conjunction.  The students are instructed to find the incorrect sentence. The answer is provided in a QR code in the lower right corner of the card  or by using the answer sheet. Students can correct the error sentence for additional practice.  Student are often motivated by using technology and appreciate the QR code. It means the cards can also be used for independent practice.

I hope you find these products useful and they free up your time from lesson planning. Happy Holidays.

Readers Notice: This blog has been updated to let readers know the products now have the TPT interactive layer added and are appropriate for distance learning.  This allows students to circle or underline the answers or  hide the answers if you wish.

word association tasks speech therapy

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Camp Go-Together: Associations and Analogies

word association tasks speech therapy

I loved going to camp when I was little, so when I came across this clip art I had to use it. A lot of my students have goals for associations. And after spending more hours than I can count going over the new Common Core Standards they will be expected to be able to complete analogies by second grade. With, what to me seems like a huge shift in expectations, I needed to create something to start preparing my students.  This activity has 56 association cards and 48 analogy cards.

word association tasks speech therapy

There is a reference mat included for students to use. It states the most common areas of relation: category, function, appearance, material, parts, and location. If you have the Expanding Expression Tool this ties into the beads. 

word association tasks speech therapy

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Meet Maureen

Hey there! I’m Maureen Wilson, a school-base SLP who is data driven and caffeine powered. My passion is supporting other pediatric SLPs by teaching them how to harness the power of literacy and data to help their students achieve their goals…without sacrificing time they don’t have.

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Get the basics you need to administer and analyze Dynamic Assessments in a school setting.  Dynamic Assessments are great for:

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Your visual poster for defining an association is GREAT! Looks like a wonderful set. Felice (thedabblingspeechie)

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word association tasks speech therapy

How and why to Teach Categories in Speech Therapy

  • allisonfors
  • August 24, 2019
  • Speech Resources , Therapy Ideas


Categories are a group or class of items with shared characteristics. We use categories in our daily lives without even realizing it! It’s how we organize our pantry, find a specific item in the store, and recall names of less used words in conversation. Categories are a foundation for how we learn, relate, store, and recall words. 

Categorization is important in language because it gives us a way to group our thoughts, process information, store and retrieve ideas, and describe items! “Arranging thoughts, concepts, and words into categories facilitate meaning, memory, and retrieval” (Roth & Troia, 2005) Categories give a connection between words based upon similarities and differences.

Working on categories is a great way to build and expand vocabulary. Learning new vocabulary by categories allows for better comprehension and retention, and helps “file it away” better for easier recall. Those with language disorders have a difficult time organizing and remembering words, and categorization is a great way to address these difficulties.


Preschool – animals, body parts, clothes, shoes, jewelry, colors, letters, shapes, numbers, family members, days of the week, desserts, food, names, rooms of the house, furniture, sounds, toys

Early Elementary – snacks, drinks, dairy foods, vegetables, pets, book parts, buildings, characters, coins, condiments, containers, dinosaurs, directions, emotions, flowers, fruits, holidays, ingredients, instruments, jobs, jungle animals, liquids, months, movies, patterns, planets, punctuation, reptiles, insects, rhyming words, seasons, senses, kitchen utensils, sizes, solids, sounds, sports, transportation, tools, vowels, writing utensils, school supplies

Late Elementary – mythical creatures, adjectives, verbs, parts of speech, school subjects, businesses, cities, states, consonants, countries, continents, currency, exercises, habitats, mammals, measure units, metals, nouns, oceans, odd/even numbers, presidents, punctuation, seasonings, symbols, textures, trees, weather

Middle/High School – adverbs, ancient civilizations, constellations, cuisine, elements, famous landmarks, government types, gasses, gems, internal organs, languages, minerals, mountain ranges, music types, religions, traditions


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When beginning to work on categories, target more concrete concepts then work towards more abstract concepts. Also, keep in mind it’s easier to receptively identify a category compared to expressively naming items in a category. Convergent naming: Name the category (An apple, orange, and banana are…)

Divergent naming: Listing items in a category (Name 3 types of transportation.)

What goes together: Find 2 or more items that go together and discuss why. Matching is a great way to work on this skill!

What doesn’t belong:  Find the item listed that doesn’t belong and discuss why 

Sorting tasks: There are lots of ways to sort. I like using tangible objects when beginning; you can also use pictures. Sort by feature, function, or sort items into 2-3 groups. 

Similarities and differences/comparing and contrasting: Comparing and contrasting allows us to classify words, helping with comprehension, storage, and retrieval. Talk about similarities and differences and use tables or Venn diagrams when appropriate. 

word association tasks speech therapy


  • Categories Concepts – Perfect for introducing categories and classes in repetitive, consistent activities that keep kids engaged. No prep, print and go pages (or just open on your device)! Includes naming/expressive, what doesn’t belong, and comparing/contrasting activities.
  • Digital Boom Cards Categories – Digital, self-grading task cards! Includes convergent naming, divergent naming, what doesn’t belong, what goes together, and sorting activities. 
  • No Print Categories – A no print matching activity with 5 categories: sports, holidays, animal habitats, community helpers, and food. 
  • Home Themed Categories – Target home themed categories, associations, vocabulary, and negation with this NO PREP, print and go activity! Includes matching, what doesn’t belong, convergent, and divergent naming activities.
  • Comparing and Contrasting Mazes – Work on more complex similarities and differences with these mazes! Great for higher elementary and middle school. 
  • FREE Category Match Up – A way to work on matching for what belongs together and discussing why.
  • FREE What Doesn’t Belong – A way to work on finding what doesn’t belong and what goes together.
  • Categories with Splingo
  • Category Therapy by Tactus Therapy

How do you work on categories in speech therapy? Tell me in the comments!

Roth, F. P., & Troia, G. A. (2005). Vocabulary instruction for children and adolescents with oral language and literacy deficits. Paper presented at the 2005 Council for Exceptional Children Annual Convention, Baltimore, MD.

word association tasks speech therapy

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3 Responses

I liked how you mentioned that you should find 2 or more things that go together to help become a better speech therapist. My girlfriend is wanting to become a speech pathologist and she was wondering how she can engage with kids better. I’ll be sure to tell her that she should try grouping things when helping kids with speech pathology.

Hi! I was wondering how you determined what was preschool, elementary school, middle school, and high school? Thanks!

They are based on vocabulary!

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word association tasks speech therapy

195 Memory and Attention Tasks for Speech Therapy Practice

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Attention Tasks

  • Begin with "A-1" and continue alternating between numbers and letters until I say "Stop". For example: A-1, B-2, C-3…
  • Begin with the number "1" and name an object for each letter of the alphabet starting with "A" and continue until I say "Stop". For example: 1 Apple, 2 Balls, 3 Cars...
  • Tell me boys names for each letter of the alphabet starting with the letter "A".
  • Tell me girls names for each letter of the alphabet starting with the letter "A".
  • Imagine the alphabet printed in capital letters. Now from the beginning recite only those with curves in them." (Answer:  B  C  D  G  J  O  P  Q  R  S  U) 

Memory Tasks

Immediate memory - number sequences.

17  92

23  17

60  58

64  12

92  39

65  78

61  85

43  59

21  66

83  24

7  1  3

6  8  6

8  3  2

1  6  5

4  9  2

9  4  3

8  1  7

1  4  3

9  2  4

7  4  1

68  92  74

13  27  92

58  65  31

64  12  22

99  32  19

17  75  47

60  81  11

43  59  61

27  46  86

84  23  53

3  9  6  2

9  7  4  1

1  5  9  7

2  1  5  8

8  6  3  9

3  3  6  4

6  2  8  3

4  8  2  5

5  4  1  6

7  5  7  1

68  92  74  21

13  27  92  48

58  65  31  72

64  12  22  49

99  32  19  46

17  75  47  53

60  81  11  92

43  59  61  70

27  46  86  51

84  23  53  67

9  3  8  2  7

4  9  7  6  1

7  5  9  1  6

2  8  5  1  3

3  6  4  9  8

6  4  3  5  2

1  3  8  7  5

5  2  6  3  9

8  1  2  4  4

2  7  1  2  6

35  21  68  74  92

56  92  13  48  27

49  72  65  58  31

22  64  58  49  12

87  46  32  99  19

17  28  47  53  96

73  11  92  60  81

62  59  43  70  61

93  51  27  86  46

39  53  67  84  23

SEE ALSO:   The Best Free App for Speech Therapy

word association tasks speech therapy

Immediate Memory - Word Sequences

cat  bear

ball  star

cup  chair

cup  top

door  month

foot  light

hair  dust

horse  bird

hot  pear

ice  kite

pad  plane

rug  bike

shoe  fix

spring  seen

time  night

truck  book

wing  bath

wood  pen

zoo  milk

step  ear  air

bean  rose  plane

bear  shovel  pants

bed  clip  box

beets  pill  slide

board  vase  horse

book  tag  shirt

doll  game  sand

door  light  glass

lamp  toe  silk

leaf  eye  floor

light  hair  plant

lock  dot  bed

log  bath  tree

nail  cup  bed

pan  shoe  knife

pen  sled  beef

soap  hat  bus

soap  jacks  dog

watch  pick  knot

ball  stand  comb  owl

ant  paint  bell  whale

bell  flag  ink  clay

brick  nut  frog  pie

dress  lamp  bed  plant

drum  pond  bag  cake

dust  broom  can  tea

foot  land  back  fish

hole  tug  shop  lake

jam  skate  moth  pan

peach  beard  spoon  pot

race  cat  desk  tack

scale  oil  bead  salt

seed  tie  fork  eye

silk  ghost  bin  shelf

sit  crib  bow  train

soap  fort  tray  nurse

stove  grass  pail  jet

tape  fire  key  spool

wheel  gown  blue  box

bone  heart  ice  sand  tin  

ball  pin  ant  saw  tent

boot  chest  hair  oar  board

cloud  brush  mop  cave  rink

coach  star  dog  boot  coal

dance  dump  dirt  bull  ox

felt  fish  beach  oar  skate

kite  glue  rock  stone  smoke

paste  milk  chalk  clock  wall

rail  spike  gate  barn  nest

rake  toy  vase  chest  sheet  mop

sand  sun  mud  wire  print

seed  pond  fly  dock  lamb

shell  house  string  drop  rain

sit  squash  net  cage  pole

stalk  suds  glass  barn  rose

stool  queen  egg  shell  dig

switch  stork  stairs  swan  coat

wheel  cone  clown  car  horn

wrench  sheet  cup  drop  bee

Recent Memory

  • Besides the people who work here, who have you seen today?
  • How long have you been in this location?
  • What building are you in?
  • What day of the week is it?
  • What did you do right before you came to see me?
  • What did you eat for breakfast today?
  • What is the first thing you did this morning?
  • What month is it?
  • What will you do when you finish here?
  • Who is your doctor (or teacher for a child)?

SEE ALSO:   The Best Books for Speech Therapy Practice

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Remote Memory

  • What are two primary political parties?
  • What war involved the North and the South?
  • Where is our nation's capitol?
  • Where is the state capitol?
  • Who discovered America?
  • Who freed the slaves?
  • Who is our Governor?
  • Who is our President?
  • Who was Helen Keller?
  • Who was the first President?

Temporal Orientation

  • About what time do you think it is?
  • How long have you been in this building?
  • What date is it?
  • What is next month?
  • What season are we in?
  • What was last month?
  • What was our last holiday?
  • What year is it?

We know life is busy , but if you're reading this you're probably someone who cares about helping their loved one as much as you can.

Practice 5-10 minutes whenever you can, but try to do it on a consistent basis (daily).

Please, please, please use this list to practice.

It will be a great benefit to you and your loved one's progress.

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  1. Categories + Word Associations

    Categories + Word Associations. One facet of your vocabulary, or word-level, therapy should include developing a better, more efficient cognitive organization of vocabulary words. The goal is to build solid semantic networks that link words to other similar words so that a child's vocabulary is better organized, more easily retrieved, and ...

  2. Word Association Cards

    For examples of speech activities using meta linguistics tasks, go to the top navigation heading and click on the section labeled Vocabulary. Making word association is a great task for encouraging meta linguist skills. There is a good sampling of cards for download in that section.

  3. Using Word Associations in Speech Therapy

    Word associations have been used in speech therapy for ages. We use them in word finding activities, as semantic prompts when a patient has difficulty answering questions, to increase vocabulary, as a memory strategy, and much more! These word association presents were created as a gift to you for your ongoing support and encouragement.

  4. Word Associations Speech Therapy

    Word Association Task Cards. Word Association Task Cards. $7.00. This is a digital download. You receive an instant email with PDF's in a Zip file. No physical materials are mailed. "Always came back to this resource each time I needed something to use to target associations. Thanks!". "Comprehensive and engaging resource to work on ...

  5. Word Associations Speech Therapy Worksheet Teaching Resources

    This word associations for speech therapy PDF and Boom Cards is the most effective way to introduce a large number of words at once so that students must discover the relationship between the words and create a series and sequence to form word associations for language expansion and sentence construction.This resource contains 120 vocabulary ...

  6. Vocabulary Building

    Word association tasks can enhance vocabulary development and improve metalinguistic awareness. Metalinguistics awareness is the ability to think about language beyond its structure. In these activities, students compare and contrast the meanings of 4 words and determine which one doesn't belong.

  7. Word Association Tasks for Teaching Vocabulary

    Figuring out the similarities and differences in word meanings is a good way to study and retain the information. click for direct link click for direct link click for direct link. My word association task cards are based on this principal. I made this post to tell you about additional features that are now included.

  8. Word Association Game and Describing Activities

    In the Doghouse! Word Association Game: Put the word association cards together in matched pairs. The child takes a pair and describes how they are related, then spins the spinner and moves the game piece. The object is to get the mischievous little puppy dog back to his doghouse. The game includes four game "circles" to use as markers as ...

  9. Word Retrieval / Word Finding Strategies & Activities

    Word Retrieval / Word Finding Strategies for Children who Struggle to Think of the Right Word - Speech Therapy and Home Practice Ideas. What Is Word Retrieval / Word Finding? Word finding, also called "word retrieval", is a person's ability to think of the right word when he/she needs it, such as during conversation. We all have those moments ...

  10. Word associations speech therapy Receptive Associations & What Goes

    Support your students' understanding of word associations and receptive language with this Word Associations Speech Therapy bundle. This set of 4 activities, focused on Receptive Associations and " What Goes Together " tasks, builds language skills through engaging activities. It comes complete with digital tasks, adaptive books, flashcards ...

  11. Full article: Using a word association task to investigate semantic

    Word association tasks. Word associations have a long tradition in a range of disciplines, including psychology, linguistics, and speech and language therapy. Word association tasks have been used for different purposes, such as diagnosing psychiatric disorders, tracking developmental change, and, to some extent, identifying language disorder.

  12. Word Associations

    Speech and Language Therapy. Anaesthetics General Anaesthesia. Neuroanaesthesia. Clinical Medicine Acute Medicine ... In a typical word association task, a person is asked to write down the first word(s) that spontaneously come to mind after reading a cue word. This straightforward task is referred to as a free association task, since no ...

  13. Word association skills

    Speech Therapy Tasks for our High School Level Students. 26 Nov. November 26, 2017 Cindy 0. I know finding speech therapy materials for high school students can be difficult. ... They are Word Association Cards for vocabulary development and Sentence Sequence Task Cards for complex sentence comprehension and development.

  14. Categories, Describing, & More: Speech Therapy

    Why We Work on Categories in Speech Therapy. There are two ways to describe how we learn vocabulary, or semantics. Fast mapping is when we hear a word paired with an object and then we know what that object is called. We don't understand all the nuances, but we've been exposed to the word/object pair and generally understand it.

  15. Camp Go-Together: Associations and Analogies

    I loved going to camp when I was little, so when I came across this clip art I had to use it. A lot of my students have goals for associations. And after spending more hours than I can count going over the new Common Core Standards they will be expected to be able to complete analogies by second grade. With, what to me seems like a huge shift in expectations, I needed to create something to ...

  16. Results for word associations speech therapy

    Teach Speech Now. Christmas Word Associations is a 2-page excerpt from our 128-page Christmas unit that is filled with charming illustrations and 23 fun speech and language activities for school-age children. Enough materials to keep you and your students busy for the entire month of December. Great for homework!

  17. Fill-in-the-Blank Associations Activity

    Fill-in-the-Blank Associations Activity. Description: Here's a great activity for children who need to work on word retrieval skills. For this one, you'll take a short phrase and remove one word. The idea is for the child to make an association in his brain to fill in that word. This will help the brain organize those language areas so that ...

  18. SLP Madness Speech Therapy Activities

    These association speech therapy activities include worksheets, flashcards, task cards, and association naming games to use with students in speech therapy lessons. Targeting language proc. Begin teaching the language processing hierarchy skills by teaching word associations and what goes together. These association speech therapy activities ...

  19. How and Why to Teach Categories in Speech Therapy

    Categories are a foundation for how we learn, relate, store, and recall words. Categorization is important in language because it gives us a way to group our thoughts, process information, store and retrieve ideas, and describe items! "Arranging thoughts, concepts, and words into categories facilitate meaning, memory, and retrieval" (Roth ...

  20. 195 Memory and Attention Tasks for Speech Therapy Practice

    Begin with the number "1" and name an object for each letter of the alphabet starting with "A" and continue until I say "Stop". For example: 1 Apple, 2 Balls, 3 Cars... Tell me boys names for each letter of the alphabet starting with the letter "A". Tell me girls names for each letter of the alphabet starting with the letter "A".

  21. 55 Aphasia Treatment Activities

    Hum the word or phrase at a rate of 1 syllable per second (use a higher-pitched note on the stressed syllable or word). Sing the word or phrase twice. You tap the patient's left hand on each syllable as you hum.