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Toward the Establishment of a Data-Driven Learning Model: Role of Learner Factors in Corpus-Based Second Language Vocabulary Learning
Abstract
We investigated how learner factors, such as vocabulary proficiency, strategy use, and working memory, are associated with successful corpus-based second language (L2) vocabulary learning, in which learners are encouraged to analyze and explore large, structured collections of authentic language data (i.e., corpora) to resolve their lexical issues (i.e., data-driven learning [DDL]). After measuring L2 vocabulary proficiency and working memory capacity, 35 South Korean college students performed a DDL activity during an English reading task using a think-aloud protocol to document their strategy use. Through this we identified participants' lexical inferencing strategy use, including DDL-focused strategies, based on qualitative coding. Using path analysis, we identified that participants' DDL-focused strategy use largely influenced their vocabulary acquisition and retention, highlighting the pedagogical advantages of these strategies for successful DDL. We found that participants' L2 vocabulary proficiency and working memory contributed to their vocabulary acquisition and retention, indicating the roles of these factors in managing cognitive load in DDL. Future investigation into the causal relationship between improved working memory and corpus-based L2 vocabulary learning and the role of other learner factors, including motivation and learning style, is needed to extend our understanding of DDL.
... Inspired by the use of corpus for educational purposes, Johns (1990) introduced Data-Driven Learning (DDL) whereby learners analyze and explore authentic corpora to resolve their language-related issues (Boulton & Cobb, 2017;Lee et al., 2020). Vast compilations of authentic lines selected from a wide range of authentic texts can be created to target specific aspects of language learning (Bernardini, 2000). ...
... The effect of DDL and corpus-based instructions on various language skills and subskills has shown promising results. Research has indicated the positive effects of DDL on phraseology learning (Ackerley, 2017), L2 lexical acquisition (Lee et al., 2019;Lee et al., 2020), collocation (Akinci & Yildiz, 2017;Chang, 2023;Saeedakhtar et al., 2020;Vyatkina, 2016), and technical words (Chang, 2023). Other studies have shown improvements in students' writing following the use of corpora (Chen & Flowerdew, 2018;Crosthwaite, 2020;Muftah, 2023;Yoon & Hirvela, 2004;Yoon & Jo, 2014). ...
... While the latter is a good choice for improving academic English, the former two corpora suit general linguistic purposes and cover a wide range of text types (Romer, 2008). The three online corpora have been previously used by past studies or recommended by the relevant literature (Akinci & Yildiz, 2017;Lee et al., 2020;Lin, 2021;Lin & Lee, 2017;Romer, 2011). ...
Purpose. This study evaluated the effect of indirect Data-Driven Learning (DDL) and Traditional Deductive Approach (TDA) on the knowledge of cohesive devices in a virtual classroom.
Design/Methodology/Approach. Thirty-one English as a foreign language learners (EFL) (mean age = 16.25) were randomly assigned to DDL or TDA conditions. The DDL (treatment) group (N = 16) was required to study materials derived from authentic corpora, prepared by their instructor. The TDA (control) group (N = 15) was taught using a formulaic and mechanical structure. Participants took a pre-test, immediate post-test, and delayed post-test of cohesive devices. The DDL participants also completed a semi-structured interview.
Findings. The results revealed that although both groups enhanced the knowledge of cohesive devices, indirect DDL yielded more learning gains at post-test. However, the DDL group showed equal learning retention compared to the TDA group at follow-up. Finally, an interview with the indirect DDL participants demonstrated that most of them held positive attitudes toward applying indirect DDL to virtual classrooms.
Originality/Value. The study concludes with DDL educational implications and the importance of implementing DDL for young EFL students with intermediate English proficiency using virtual tools. We provide some limitations of the current study and offer suggestions for future research on DDL.
... The robust effect of discovery learning is that learners remember more often the greater detail of concept and knowledge they generate than materials provided by an instructor (Alfieri et al., 2011). As DDL was implemented to Korean students for L2 vocabulary learning, it is found out that L2 vocabulary proficiency, DDL-focused strategy use, and working memory were significantly associated with L2 vocabulary acquisition and retention (Lee et al., 2020). When Taiwanese teachers applied DDL to their students, they found that DDL successfully aroused their students' interest to learn grammar, increased their in-class participation and learning motivation, and it was believed to have helped the students to learn better and improved their long-term retention of the grammar acquired (Lin & Lee, 2015). ...
... Another study compared DDL with traditional grammar learning for the purpose of unlearning overgenerated be in secondary-level EFL classrooms in Korea and the results pointed that the DDL group showed statistically significant retention as well as immediate effects in grammar learning (Moon & Oh, 2017). In the end, it has been confirmed that DDL should yield greater learning experience, comprehension, and retention (Lee et al., 2020;Lin & Lee, 2015;Moon & Oh, 2017). Considering that DDL could create direct learner autonomy and enhance immediate retention as suggested by previous studies, the current study investigates learners' memory and independent practice of DDL in the long-run after one semester has passed since they last learned using corpus data. ...
... Some students also stated that they used the corpus website in their listening and reading classes, although they did not specifically state their purposes. On another research, learners used corpus data (COCA) to investigate words and phrases discovered in listening materials (Geluso & Yamaguchi, 2014) and to enhance lexical repertoire and thereby improve their reading comprehension (Gordani, 2013;Lee et al., 2020). The students who answered 'No' (37%) stated that they did not use the corpus website because they used other learning resources and the lecturers in the second semester did not instruct them to use the corpus websites. ...
Data-driven Learning (DDL) has been widely used in language classrooms and suggested to promote learner autonomy and retention. The current study would confirm if the findings of research in other countries are also found in Indonesian context within different time span. Therefore, this study investigates Indonesian EFL students’ long-term practice of DDL after one semester has passed since they learned with DDL using corpus data. The participants of this study were university students specializing in English Language Education and the setting of this study was at one public university in Central Kalimantan Province of Indonesia where English is a foreign language. Survey research with one-shot design was conducted and questionnaire comprising of three dimensions (learners’ retention of learning materials and current knowledge of DDL, current practice of DDL, and future plan) was distributed to collect data. The results show positive trends that the students had retention of the learning materials they learned in the previous semester through DDL, they currently employed DDL independently outside classrooms, and they would apply DDL in the future.
... Over recent decades, corpus linguistics has contributed to developing dictionaries, assessment tools, instructional materials, educational research, publishing, and second language education (Boulton, 2010; Boulton & Tyne, 2013; Crosthwaite, 2020). Inspired by the use of corpus for educational purposes, Johns (1990) introduced Data-Driven Learning (DDL) whereby learners analyze and explore authentic corpora to resolve their language-related issues (Boulton & Cobb, 2017;Lee et al., 2020). According to Johns (1990), corpus-aided language learning avails information technology and classroom concordancing, enabling learners to access corpora lines to make meaning pro les. ...
... It is argued that the cognitive load of DDL can impede its bene ts for learners (Lin & Lee, 2017). The cognitive load of DDL has been noted by Lee et al. (2020) proving the effectiveness of DDL in second language vocabulary learning as well. This can be a rmed by the treatment group's interview indicating that DDL was much more demanding than other approaches and should be used for less di cult grammatical points. ...
This study evaluated the effect of indirect Data-Driven Learning (DDL) and Traditional Deductive Approach (TDA) on the knowledge of cohesive devices in a virtual classroom. Thirty-one English as a foreign language learners (EFL) (mean age = 16.25) were randomly assigned to DDL or TDA conditions. The DDL (treatment) group (N = 16) was required to study materials derived from authentic corpora, prepared by their instructor. The TDA (control) group (N = 15) was taught using a formulaic and mechanical structure. Participants took a pre-test, immediate post-test, and delayed post-test of cohesive devices. The DDL participants also completed a semi-structured interview.
The results revealed that although both groups enhanced the knowledge of cohesive devices, indirect DDL yielded more learning gains at post-test. However, the DDL group showed equal learning retention compared to the TDA group at follow-up. Finally, an interview with the indirect DDL participants demonstrated that most of them held positive attitudes toward applying indirect DDL to virtual classrooms.
The study concludes with DDL educational implications and the importance of implementing DDL for young EFL students with intermediate English proficiency using virtual tools. We provide some limitations of the current study and offer suggestions for future research on DDL.
... Yanez-Bouza and Gonzalez-Diaz [1] conducted related research on the content and compilation process of APU writing and English reading corpora through the operation process of children's language comprehension [1]. Starting from the English reading corpus, Lee et al. [2] studied the correlation between the English corpus and learners' mastery of vocabulary and solved the problem of vocabulary learning by encouraging learners to self-analyze and construct an English reading corpus [2]. Shatz [3] analyzed the role of capitalization in language processing and writing assessment during reading from the capitalization error patterns in an English reading corpus constructed from 133,000 texts of 38,000 foreign learners [3]. ...
... Yanez-Bouza and Gonzalez-Diaz [1] conducted related research on the content and compilation process of APU writing and English reading corpora through the operation process of children's language comprehension [1]. Starting from the English reading corpus, Lee et al. [2] studied the correlation between the English corpus and learners' mastery of vocabulary and solved the problem of vocabulary learning by encouraging learners to self-analyze and construct an English reading corpus [2]. Shatz [3] analyzed the role of capitalization in language processing and writing assessment during reading from the capitalization error patterns in an English reading corpus constructed from 133,000 texts of 38,000 foreign learners [3]. ...
English is a universal language in the world. It has become the consensus of society as a subject of education in primary and secondary schools and even universities. Therefore, how to improve English reading ability has also become a focus area of school education and students. The current research on English reading is mainly based on the sense of reading questions, reading patterns, answering skills, etc. and lacks the analysis of English reading corpus. In view of this, this paper used a self-built English reading corpus, adopts the feature extraction method, and combines the convolutional neural network (CNN) to build a model to carry out numerical analysis on the self-built English reading corpus, optimized the model, and compared and analyzed the results obtained. The optimal dropout rate and iteration times were obtained by updating experimental parameters. In order to make the experimental results more convincing, the W2V-SVM and W2V-CNN models that combine different feature extraction and classification methods are designed. Compared with the optimized CNN model, the accuracy rate, recall rate, and F1 value of the optimized CNN model were 89.81%, 92.39%, and 92.8%, respectively. The accuracy, recall, and F1 value of the W2V-SVM model are 81.31%, 82.09%, and 81.25%, respectively. The accuracy, recall, and F1 value of the W2V-CNN model are 85.24%, 84.98%, and 85.12%, respectively. It shows that the optimized CNN feature classification model has better feature classification effect on the self-built English reading corpus. The experimental results meet the expected value.
... The learners are supposed to have a high quality of thinking and to manage to utilize the data resources [20]. Lee mentions that DDL-focused methods have influenced the learners' vocabulary acquisition and long-term maintenances [21]. Men believe that there is a distinct improvement in learners' behavior on collocation production in language idiomaticity by using a datadriven learning strategy [22]. ...
... Considering the large space in corpus data, the learners will have more alternatives and options to search for the right answers by themselves. However, according to Alruwaili and Lee, the efficiency of DDL is linked to learners' vocabulary proficiency, working memory and familiarity with this new approach [20,21]. ...
... In terms of the benefits of corpora and data-driven learning, the relevant literature has demonstrated the efficacy of corpus in various aspects of SL/FL learning. Numerous studies have demonstrated the effectiveness of corpora in vocabulary acquisition (Karras, 2016;Lee et al., 2020;Lee & Lin, 2019;Li & Zhang, 2024;Otto, 2021;Yao, 2019), grammar comprehension (Crosthwaite & Steeples, 2022;Lin, 2021;Lin & Lee, 2015), writing proficiency (Chen et al., 2019;Crosthwaite, 2020;Larsen-Walker, 2017;Luo, 2016;Muftah, 2023;Sun & Hu, 2023), reading skills (Hadley & Hadley, 2021;Wilkinson, 2012), and pragmatic understanding (Li, 2019;Vyatkina & Belz, 2006;Zhang, 2021). Moreover, in addition to the effectiveness of corpora on language skills and components, several studies have shown that analysing learner corpora allows researchers to identify common errors among learners (Lee et al., 2009;Rosen et al., 2014;Thewissen, 2013). ...
The incorporation of corpora into language education has garnered a substantial amount of interest particularly within the context of second language and foreign language settings, with regard to language skills, components, and the teacher development. This systematic review explored emerging issues in corpus applications in English Language Teaching (ELT) by examining thirty-eight studies published in prominent journals from 2016 to 2023. In this review, the corpus studies were analysed with reference to the focused research topics, methodological design they employed, and the major findings that were presented. This systematic review provided valuable insights into the current state of corpus applications in ELT. The findings identified a predominance of quantitative research designs, highlighting a need for more qualitative and longitudinal studies to fully understand the dynamics of corpus use in language teaching and learning. Key findings revealed that while corpus applications as a Data-Driven Learning (DDL) tool enhanced learners’ vocabulary, grammar, reading, writing, and pragmatic skills, there was limited focus on teachers’ interaction with corpora. Increasing teachers’ corpus literacy and fostering collaborative learning were found to be critical for teachers’ effective integration of corpus tools into classroom practice. The review underscored the importance of comprehensive training and support for teachers to maximize the potential of corpus-based pedagogy.
... A small but growing number of DDL studies have responded to calls for SLA researchers to adopt more advanced analyses used in sister disciplines such as psychology and economics (for more, see Gass et al., 2021). For instance, some scholars have leveraged techniques such as path analysis (e.g., Lee et al., 2020) as well as other types of regression models (e.g., Crosthwaite et al., 2020) for understanding the relationships between different variables and L2 learning outcomes. However, the use of such advanced statistics still tends to be quite rare in quantitative DDL designs. ...
This encyclopedia entry introduces readers to quantitative research methods involved in investigations of data-driven learning (DDL). The piece opens by briefly defining two key terms, DDL and quantitative research methods, in addition to the underlying assumptions of quantitative approaches more broadly. Then, readers are introduced to common quantitative designs and samples that have been used in prior DDL research. Next, the piece transitions to highlighting some of the most common targets of inquiry in quantitative DDL designs. Typically, this has consisted of L2 linguistic foci involving writing skills, vocabulary, and lexico-grammar, among others. Finally, the piece closes with a discussion of frequently used instruments such as surveys, tests, student-produced essays, and tracking data, which have been analyzed using both descriptive and inferential statistics.
... This corroborates research on corpus use in L2 learning context which found that learner style is an important factor influencing corpus use (Bridle, 2019). Unlike previous findings that a higher level of self-evaluation of learning abilities is related to greater engagement and better outcomes (Chen & Pajares, 2010;Lee et al., 2020), the low self-rated translation competence and learning motivation expressed by S1 and S2 prompted them to place a high value on the parallel corpus, which also acted as a motivator for their engagement with the parallel corpus in compensation. This accords with previous research that motivation is essential to facilitate student engagement (Mystkowska-Wiertelak & Bielak, 2023; Zare et al., 2024). ...
While emerging research has contributed significantly to our understanding of the efficacy of parallel corpora in translation education, specifically concerning student performance and perception. However, there remains a noticeable gap in the literature regarding the examination of student engagement with parallel corpora during the translation process. To address this research gap, the present study seeks to comprehensively analyse the behavioural, cognitive, and affective engagement of three M.A. students when utilizing parallel corpora in Chinese-English translation tasks. A multiple case study design was implemented, drawing upon a diverse range of data sources, including screencasts capturing students’ translation processes, the resultant translation outputs, corpus search logs, and in-depth interviews. The findings of this investigation reveal distinct engagement patterns exhibited by individual students and underscore the intricate interplay of these three dimensions of engagement. Furthermore, student engagement with the parallel corpus significantly influences their translation performance. This research also unveils various factors that impact student engagement patterns, including the perceived affordances of the parallel corpus, students’ self-perception, and learning motivation.
... Examples in the 2020 Outputs Technology and apps (Enayati and Gilakjani 2020); (Tai et al. 2020); (Obermeier 2020) Data-driven approaches (Talib 2020); (Lee et al. 2020); (Dang 2020) Listening vocabulary (Masrai 2020); (Zhang and Graham 2020) Gestures (Andrä et al. 2020) Vocabulary Networks (Aotani and Takahashi 2020); (Spätgens and Schoonen 2020) CLIL (Baten et al. 2020); (Benatti 2020) Neurolinguistic Approaches ; (Zeller 2020); (Liu and Hell 2020) Gaming approaches (Bahari 2020); (Thompson and Gillern 2020) Trilingual speakers (Chen and Liu 2020); (Efeoglu et al. 2020); (Gudmundson 2020) Young learners (Alexiou and Milton 2020); (Nordlund and Norberg 2020) Availability (Akbarian et al. 2020) Learner Autonomy (Denison and Custance 2020); (Kambakis-Vougiouklis and Katsarou 2020) Spaced learning (Sararoodi and Farvardin 2020); (Lafleur 2020) Good vocabulary learners (Sasao 2020); (Nahavandi et al. 2020) Teaching strategies (Herrera Caldas et al. 2020) Space does not allow me to follow up this idea here, and we cannot investigate the characteristics of these sub-threshold clusters in any detail. However, I will be reporting an analysis that tries to establish objective criteria for identifying clusters of this sort in a follow-up paper. ...
This paper presents an author co-citation analysis of the research on L2 vocabulary acquisition that was published in the 2020 calendar year. The most significant influence at this time is Paul Nation—cited in 85% of the publication set—but a number of other important influences can also be identified, notably, Laufer, Hulstijn, Schmitt and Webb. This paper draws some comparisons with data from 1990, and speculates on how “research fronts” might be identified in an author co-citation data set.
... Both of these two studies focus on learners' interactions with web-based concordancers. Regarding the use of printed concordance-based materials, from which learners can greatly benefit, there is just one very recent study by Lee et al. (2020). They examined the relationship between vocabulary proficiency, strategy use, working memory and L2 lexical learning. ...
Data-driven learning (DDL), the direct use of corpus by learners in the second language classroom, has been shown to be effective in improving learners’ acquisition of various English linguistic items (Boulton & Cobb, 2017). However, it is still limited to our knowledge regarding how learners interact with DDL-related materials or tools and how DDL works in the learning/teaching of languages other than English. This study aims to closely examine the cognitive processes of six learners of Chinese in using printed concordance-based materials to learn Chinese resultative constructions. These materials contained adapted complete concordance sentences drawn from the Lancaster Corpus for Mandarin Chinese (McEnery & Xiao, 2004). The results show that in general, learners employed various strategies when scrutinising the concordance lines, particularly cognitive strategies such as summarising and grouping . Differences among individual learners were also found: learners who used more diverse strategies with higher frequencies could successfully infer the regularities, which led to learning gains. The study provides some implications for effective teacher guidance in DDL.
... The outcomes showed that learning through vocabulary has a certain promotion effect on English teaching. Lee's [5] research team to address the problem of inadequate English vocabulary among university students, a datadriven learning model was developed based on assessing students' vocabulary levels and working memory capacity; A lexical reasoning strategy was identified; The outcomes showed that the method was beneficial to university students' vocabulary learning and working memory levels. Gholaminejad and Sarab [6] addressed the problem of developing disciplinary vocabulary lists by designing an academic glossary with a specific genre and time span, with paired word lists representing 7.1% of the corpus coverage. ...
With the rapid development of information technology, the application of VR to English language teaching has gradually become an emerging trend. As the driving force of English learning, the establishment of ESL vocabulary corpus is of great significance for making great progress in teaching in colleges and universities. By analyzing the characteristics of VR technology, the study establishes a data-driven teaching platform for ESL vocabulary corpus in colleges and universities based on this technology. Then, based on the improved graph neural network, the text classification of the ESL vocabulary corpus was carried out to achieve the integration of ESL vocabulary corpus resources. The results show that the improved graph neural network vocabulary text classification model converges at 145 iterations, and the convergence speed is improved by up to 100 generations; Among different datasets, the recognition accuracy of the SADE-GNN model on the MR, R8, SST1, and SUBJ datasets is 90%, 99%, 63%, and 96%, respectively. In the recognition and classification of ESL vocabulary corpora in universities, the accuracy of this model is stable at around 95%, with a maximum value of 97%. In practical teaching applications, students' English listening, reading, writing, and speaking scores have all increased to varying degrees, with the top 50% of students achieving 95 or above in both reading and speaking. The above results indicate that the teaching platform under the research model has high accuracy in text classification, can significantly improve the effectiveness of English teaching, providing new reference ideas for the construction of ESL vocabulary corpus and teaching method reform in universities.
... Existing studies are rich in investigating learners' perceptions of DDL implementation (e.g., Bernardini, 2004;Kennedy & Miceli, 2010;Lee et al., 2020;O' Sullivan & Chambers, 2006;Yoon, 2008;Yoon & Hirvela, 2004), but no conclusive results have been identified. Some studies found learners' positive attitudes toward DDL (e.g., Mizumoto & Chujo, 2015) while others found negative attitudes (e.g., Quan, 2016) or mixed attitudes within the same cohort of learners (e.g., Kennedy & Miceli, 2001). ...
This study evaluates student perceived effectiveness of a guided inductive approach for synonym learning through a 36-week, two-round data-driven learning (DDL) and task-based instruction design. Presented as a student-centered “mini-lecture” task, it integrates pre-task training, during-task guidance, and post-task feedback. Data were collected from 23 business English university students via questionnaires and interviews. Results show that learners generally held consistent positive attitudes toward this long-term data-driven learning. Enhanced instruction in the second round underscored the importance of scaffolding, reducing learners’ anxiety, and promoting cognitive development. Task complexity and language proficiency seemed unrelated to learner perceptions. Although task motivations influenced learners’ perceptions, learners with lower motivation were not overwhelmed by technical difficulties involved in DDL, supporting the effectiveness of the long-term practice in improving learners’ corpus query skills. Learners often used their native language to explain key concepts in the “mini-lecture” presentation. The results suggest the task-based “mini-lecture” design is effective and that guided inductive DDL is a promising alternative in language pedagogy. Based on the findings, a task-based data-driven synonym learning model is proposed.
... In order to obtain accurate data chain vocabulary features, the data chain vocabulary itself is extracted [19][20]. The modulation style of the data chain vocabulary is the key feature of the vocabulary, and according to the unique characteristics of the data chain, it can be seen that the modulation styles that need to be extracted are single-sideband, frequency shift keying, and minimum frequency shift keying. ...
In this paper, under the data chain model, the form of envelope modulation is first utilized to identify the lexical feature quantity precision based on the horizontal energy clustering point of lexical distribution. Then, the reconstruction of the teaching model is accomplished by clustering assessment of modulation means and optimal experience through subtractive clustering. Finally, the multivariate array parameter distribution method is used to realize the node optimization deployment design of the data chain system, and at the same time, the teaching quality weight coefficients are obtained according to the overlap probability and the energy domain detection probability. After applying the six-step teaching model, the passing rate of the third level is about 40%, and the scoring rate of the experimental group is higher than that of the control group by 1.64%. When the vocabulary frequency is 200HZ, the P-value is 0.0039 less than 0.05 effect is significant, which can enhance the students’ subjective initiative, and the English teaching mode realizes a better innovative effect.
... g., Jin & Lee, 2022;Kline, 2011;Lee, Warschauer, & Lee, 2020, Lee, Jung, & Lee, 2022: (1) chi-square test (p > 0.05 or χ 2 /df < 5 for acceptable fit); (2) root mean square error of approximation (RMSEA <0.08 for acceptable fit); (3) comparative fit index (CFI >0.90 for acceptable fit); and (4) Tucker-Lewis index (TLI >0.90 for acceptable fit). Table 1 presents the descriptive statistics, such as means, standard deviations, 95% CI, internal reliabilities (when applicable), and normality test results, for the six observed variables for the path analysis model. ...
A R T I C L E I N F O Keywords: Anxiety Competence Language mindset Motivation Non-recursive path analysis Proficiency Vicious cycle of language anxiety A B S T R A C T From a socio-psychological perspective, learners with high second language (L2) learning anxiety are likely to avoid using L2, missing substantial L2 learning opportunities to improve their L2 competence, which would result in negatively impacting their L2 anxiety, forming a circulation process, also known as "vicious cycle of language anxiety" (Lou & Noels, 2020a). In this study, we explored the reciprocal relationship between self-perceived language competence, language anxiety, and language proficiency using two structural models applied to second language learning settings by recruiting 270 undergraduate students learning English as their foreign language, and building a recursive (i.e., a structural equation model) and a non-recursive (i.e., a path analysis with a feedback loop) structural models to investigate how to end the cycle of anxiety. Evidently, we found that there existed a reciprocal relationship between these factors, and building a growth language mindset, previous proficiency, and motivation would alleviate the "vicious cycle of language anxiety" in light of the results from the non-recursive path analysis model. Our findings are a major step forward from prior suggestions of piecemeal solutions that only partially affect a cyclical element to eventually break this so-called vicious cycle, such as fostering learners' growth mindset to mitigate their anxiety.
... It should be noted that successful vocabulary learning via DDL seems to depend greatly on the individual learner (Lee, Warschauer, & Lee, 2020). Researchers suggest that DDL approaches should make learners aware of both the general characteristics of the corpus being used (i.e. ...
The patterns inherent to written text often remain opaque to second language learners due to the considerable cognitive demands that reading places on working memory. Learners must attend to the meaning of unknown words, the grammatical structure of sentences, and the meaning of the text as a whole-and this all simultaneously. One solution for helping learners to better attend to existing form, function, and frequency patterns within texts is through systematic visual attention cues, which may offload some of the burden on working memory. Lex-See is a Chrome browser extension that highlights words within a user-supplied text in a variety of shades and colors based on underlying corpus-based data about frequency and word class, and also provides further information about forms, definitions, and phonetic similarity, on mouse-over. Currently Lex-See is optimized for Czech, a less-commonly taught, morphologically rich language with a clear need for easily accessible corpus-informed language learning tools, but it is designed to work with any language for which lemma frequency, form, dictionary, and phonetic data can be supplied.
... Teachers have recognized that a new word and its context can affect vocabulary learning (Qoura et al., 2018). When using corpora in vocabulary teaching, a list of concordance lines automatically appears on the screen from the corpus data, providing vital, valuable, and relevant information about the target word (Lee, 2018). Corpora teach students the most frequent words and expressions, with examples within corpora from spoken and written English (Abdulrahman, 2015). ...
Using corpora as a learning tool in Second Language writing has gained popularity recently. The present study aimed to explore how Saudi EFL students perceive and engage with direct corpus consultation activities in academic writing as an effective method of overcoming their vocabulary errors. Hopefully, this study will provide insights into the issue of raising awareness among both EFL university students and writing teachers about the benefits of direct corpus consultation in academic writing, as well as highlighting the potential challenges students might face. Two specific questions were addressed in the study: How do Saudi EFL students perceive direct corpus consultation as a method for overcoming vocabulary errors in academic writing? What are the challenges that EFL students encounter when they use direct corpus consultation? Based on convenience sampling, a total of 32 Saudi female students majoring in English participated in the study. The study employed a mixed-method approach to increase the credibility of the study results. The study data were collected from a structured questionnaire based on a 6-point Likert scale and semi-structured interviews. The corpus used was the Corpus of Contemporary American English. The findings of both the quantitative and qualitative analysis revealed that the participants were positive about using direct corpus consultation to improve vocabulary and academic writing. In addition, some challenges associated with using direct corpus consultation were outlined in the study findings. The study concluded with several recommendations for future research and pedagogical implications.
... /fpsyg. . vocabulary acquisition (Lee and Lin, 2019;Lee et al., 2020), reading comprehension (Hadley and Charles, 2017), and translation (Gavioli, 2005, p. 114-118;Zanettin, 2009;Giampieri, 2019). Among studies on the DDL approach in translation practice, less attention has been paid to the self-translation of academic discourse. ...
This article reports on an experiment on the use of data-driven learning (DDL) in the revision of self-translation by a Chinese medical student. The think-aloud method is employed to investigate the difficulties the student encountered in self-translation and the effectiveness of DDL in improving the quality of self-translation. Results show that difficulties in the self-translation of medical abstracts are mostly associated with markers of rhetorical moves, terminologies, and conventional academic expressions and that they can be effectively solved by such corpus consultation strategies as checking possible options in bilingual dictionaries, using the most certain keywords to find collocations, and using the most possible accompanying words to find contexts. A comparison of translations before and after the application of DDL reveals that it could help improve translation quality in lexical choices, syntactic structures, and discourse practice. An immediate interview shows that the participant holds a positive attitude toward DDL.
... GLB = general language intelligence beliefs; L2B = second language aptitude beliefs; ASB = age-sensitivity beliefs. The standards for goodness of fit for the CFA analyses, the following rules of thumbs (Jin & Lee, 2022;Lee et al., 2020 Notes. GLB = general language intelligence beliefs; L2B = second language aptitude beliefs; ASB = age-sensitivity beliefs. ...
This study examined changes in undergraduate students' language mindsets and academic writing competence as a result of taking a one-semester English for academic purposes (EAP) writing course with a pre-post intervention on mindset. A total of 319 students participated in the study and completed a 10-week EAP course. The participants were administered the mindset questionnaire and the writing test at two different time-points. The results showed that the participants' level in one component of growth language mindset (general language intelligence beliefs), and scores on the writing test increased significantly. The results of the latent profile analysis revealed three distinctive profiles among the participants at both time-points: Growth profile, Mixed profile, and Fixed profile. The Growth and Mixed profiles were found to perform significantly better than the Fixed profile on the writing tests. Finally, the result of a latent transition analysis revealed that dynamic shifts in the profile membership could occur through the mindset intervention.
... Several correlational studies reported inconsistent or no signifcant correlations between executive working memory and child L2 learners' vocabulary knowledge (Engel de Abreu & Gathercole, 2012;Jean & Geva, 2009). However, executive working memory has proven to be a consistent predictor in experimental studies with adults, including both studies investigating vocabulary learning in learning novel languages (Kempe et al., 2010;Martin & Ellis, 2012) and studies involving familiar languages (Lee et al., 2020;Malone, 2018). Therefore, it would seem that the efects of working memory can be more easily observed in studies in which variables are carefully controlled and manipulated than in correlational studies in which variables are not manipulated. ...
Working memory is a cognitive space for simultaneous information manipulation and storage. In the field of second language acquisition, working memory has been investigated as a key individual difference variable mediating various aspects of the process and outcome of language learning. Despite the voluminous body of research, there has been confusion over its conceptualization, measurement, and mechanism, and the research has yielded disparate, and sometimes contradictory, findings. This chapter seeks to clarify the construct and navigate through the empirical evidence that has been accumulated over the past three decades with a view to extracting meaningful patterns and trends emerging from the research. The chapter starts with a discussion of the nature, scope, and architecture of working memory, followed by an introduction to the various tests that have been used to measure the construct and its components. The chapter proceeds to discuss the research on the role of working memory in second language acquisition including theoretical perspectives and empirical evidence on the associations between working memory and learning outcomes or processes. The chapter ends by identifying areas for future research.
... As a combination of computing latent variables and implementing a series of regression analyses at the same time, the SEM using Stata 16 software (StataCorp, 2019) was the primary data analysis method used in the present study. In view of Kline's (2012) suggestion, as well as those of other previous studies (Jin & Lee, 2022;Lee et al., 2020Lee et al., , 2022, we used the following five indices for the SEM analysis: the chi-square test (a testing model should not significantly differ from a saturated model, p > .05 for acceptable fit); the root mean square error of approximation (RMSEA < .08 for acceptable fit); the comparative fit index (CFI > .90 for acceptable fit); the Tucker Lewis index (TLI > .90 for acceptable fit); and the standardized root mean square residual (SRMR < .08 for acceptable fit). ...
This study explores the complex relationships between language learning motivation, vocabulary learning strategies, and two components of second language vocabulary knowledge (i.e., vocabulary size and depth), within the framework of self-regulated learning. Responses to questionnaires were gathered from 185 secondary-level Korean adolescent learners of English as a foreign language, regarding their motivation and vocabulary learning strategy use; additionally, the results of their vocabulary size and depth tests were collected. We adopted structural equation modeling for analysis, with vocabulary learning strategies consisting of memory, cognitive, and metacognitive categories, and vocabulary knowledge consisting of vocabulary size and depth. The results showed that motivation directly predicted vocabulary learning strategies and vocabulary knowledge, and indirectly predicted vocabulary knowledge via vocabulary learning strategies. When further classified, intrinsic motivation was found to have a stronger influence on the use of vocabulary learning strategies and vocabulary knowledge than extrinsic motivation. We discuss the implications of increasing learners’ motivation and repertoire of strategies for improving vocabulary size and depth.
... Second, using the computed pooled correlation matrix, we estimated our hypothesized SEM model for SV2R (Model 1; 81 samples; N = 10,526), as shown in Figure 3. To confirm a successful fit between our dataset and the hypothesized model, we carried out the SEM goodness-of-fit test (i.e., χ 2 test; either p > .05 or chi-square to df ratio [χ 2 /df] ≤ 5 for acceptable fit) and checked four widely used SEM model fit indices (e.g., Kline, 2005;Lee et al., 2020): (1) root mean square error of approximation (RMSEA; < .08 for acceptable fit), (2) root mean square residual (SRMR; < .08 for acceptable fit), (3) comparative fit index (CFI; > .90 for acceptable fit), and (4) Tucker-Lewis index (TLI; > .95 for acceptable fit). ...
Purpose
The present study aimed to systemically summarize the structural relationships among correlated components of second language (L2) reading comprehension to investigate the extent to which the two major components – language comprehension abilities and decoding skills – could account for reading comprehension in L2 contexts in accordance with the model of Simple View of Reading.
Method
We used a meta-analytic structural equation modeling. This study included 81 samples (from 67 studies) including 10,526 participants, and the collected dataset successfully fitted the proposed model of Simple View of L2 Reading.
Results
L2 comprehension abilities and L2 decoding skills accounted for over 60% of the variation in L2 reading comprehension, with the former having a larger contribution. Considering age and L2 proficiency as moderator variables, it was revealed that L2 decoding skills played less important roles for more proficient and older learners, whereas L2 comprehension abilities maintained their importance across different ages and L2 proficiency levels. The moderators related to language differences between learners’ first language and L2 did not show significant moderating effects.
Conclusion
The study presented acceptable model fit indices for its models. Future studies can incorporate more pooled correlation coefficients and variables to investigate an effective instruction for L2 reading.
... Lastly, learners' expectancy of being successful in language learning and value of engaging in language learning practices were included as the two motivational factors, and the TOEIC score variable was included as the learners' English achievement in the model. To ensure the goodness of fit of the SEM model, we adopted five model fit indices suggested by Kline (2012) and previous literature (Acock, 2013;Lee et al., 2020): the chi-squared test (a testing model should not significantly differ from a saturated model, p > .05), root mean square error of approximation (RMSEA < .05), ...
As digital technology is becoming an increasingly critical component of education, learners’ socioeconomic status (SES) and technology use are becoming more important in their learning. In the context of English learning, the present study modeled how learners’ SES and their perception of technology use for language learning are linked to their motivation for learning English as a foreign language (EFL) and level of English achievement. To this end, 306 South Korean college students’ learner factors, motivation, and English achievement were measured. The results of the structural equation modeling analysis indicated that learners’ SES was positively associated with their perception of technology use and motivation and indirectly associated with their language learning achievement. Furthermore, we found that learners’ perception of technology use in language learning is associated with their motivation and achievement. In addition, among the several learner factors measured in this study, learners’ expectancy of being successful in language learning as part of achievement motivation emerged as the strongest predictor of their language learning achievement. An in-depth discussion of pedagogical and policy implications is also provided.
... capitalized on much empirical evidence. For example, many scholars have found DDL effective for learning collocations (Daskalovska, 2015;Saeedakhtar et al., 2020;Uçar & Yükselir, 2015;Wu et al., 2019), writing (M. Chen et al., 2015;Crosthwaite, 2020;Mizumoto et al., 2017;Poole, 2016;Sun & Hu, 2020), and vocabulary (Karras, 2016;H. Lee et al., 2017H. Lee et al., , 2020P. Lee & Lin, 2019;Tsai, 2019). Some researchers have also reported that their students react positively to the DDL approach (M. Chen et al., 2015;Mizumoto et al., 2017;Sun & Hu, 2020). Even so, Kılıçkaya (2015) warned that such a discovering approach may be inappropriate in educational contexts where learners are used to learning from t ...
This article reports a pre–post comparative study investigating whether the data-driven learning (DDL) approach has different pedagogical effects on grammar students of English as a foreign language (EFL) with different levels of English proficiency. The study entailed a treatment group (TG) of 95 first-year undergraduates who learned grammar using DDL and a control group (CG) of 84 students who received no grammar treatment. Most of the participants were 18 or 19 years old, with only a few outliers, aged 17 or 20. The grammar performance and learning attitudes in both groups (their motivation and self-efficacy) were quantitatively examined through grammar achievement tests and a questionnaire. The data obtained from the groups were then compared at three proficiency levels: high, intermediate, and low. The results of an analysis of covariance show that in grammar performance, the proficiency levels in all the TG students rose significantly and in the posttest they outperformed their counterparts in the CG. However, neither the members of the TG nor those of the CG made any statistically significant improvement in their learning attitudes; no significant differences were found between the groups at any proficiency level. The mixed findings make an important contribution to the field, confirming that DDL is pedagogically suitable for enhancing the linguistic knowledge of university-level grammar learners, regardless of their proficiency, but warning that practitioners who treat the development of learner attitudes (e.g., motivation and self-efficacy) as important should be cautious with this approach.
... The improved vocabulary achievement, motivation, and self-confidence might be attributed to different vocabulary learning approaches per se for three possible reasons. First, the presentation types between two vocabulary learning approaches are distinctively different from each other, which is likely to invoke different loads of working memory (Lee et al., 2020). Compared with the unimodal presentation of the conventional paper-based wordlist learning approach, students who used the game-based vocabulary learning APP can first set up a vocabulary learning goal and then enjoy the game playing by making full use of multimodal presentation types (Mayer, 2009). ...
Game-based vocabulary learning that is well documented to improve students’ vocabulary learning outcomes is gaining increasing attention. However, no consensus has been reached regarding the impact of game-based vocabulary learning application (APP) on the vocabulary learning achievement, motivation, and self-confidence among Chinese EFL (English as a foreign language) students, so large a population that should never be neglected. To address the issues, a total of 70 college students in two groups participated in a quasi-experiment. One is the experimental group in which students received the game-based vocabulary learning; the other is the control group in which students received the conventional paper-based wordlist learning. Each group consisted of 35 students. The experiment was carried out to evaluate how the implementation of game-based vocabulary learning influences students’ vocabulary learning achievement, motivation, and self-confidence. In addition, a regression analysis was exploited to examine the influence of motivation and self-confidence on vocabulary achievement. Results demonstrated that the game-based vocabulary learning APP benefited students in vocabulary achievement, motivation, and self-confidence. Furthermore, learning self-confidence and motivation did not predict learning achievement. Implications of the study were also given.
... Additionally, given the incremental nature of L2 vocabulary learning (Schmitt, 2008), more proficient learners are likely to have a greater amount of partial knowledge of unfamiliar words, which will assist their vocabulary learning through L2 glosses. Furthermore, since more proficient learners may access more cognitive resources to engage in the learning of unfamiliar vocabulary (Lee, Warschauer & Lee, 2020), L2 glosses may be cognitively less demanding for this group than for their lower-proficiency counterparts. ...
Glossing is a widely used and examined vocabulary learning tool, and one of the major branches of glossing research has compared the relative effects of first language (L1) and second language (L2) glosses on reading comprehension and vocabulary learning. However, the findings in this literature have not been consistent, calling for a comprehensive and systematic review. To this end, we conducted a meta-analysis to investigate the relative effects of L1 and L2 glossing on L2 reading comprehension and L2 vocabulary learning. Based on 78 effect sizes gathered from 26 studies representing 30 independent samples (N = 2,189), we found that L1 glossing was more effective than L2 glossing in general (Hedge’s g = .33, SE = .09, p < .001), but the effect size may vary depending on the target outcome measure. The relative effectiveness of L1 glossing was particularly supported by the results of immediate posttests of vocabulary, rather than delayed posttests of vocabulary and reading comprehension tests. Further, among a few selected moderator variables, the results of meta-regression revealed that learners’ L2 proficiency level significantly influenced the average effectiveness, such that L1 glossing is particularly effective for beginner learners compared to those with intermediate or higher L2 proficiency levels.
Audiovisual learning is gaining increasing attention, with factors such as working memory and task type potentially influencing learning outcomes. This study examined English vocabulary acquisition among 110 Chinese high school English as a foreign language learners with varying levels of working memory (high and low) and different types of tasks (input-based and output-based). After engaging in an audiovisual activity, the learners were divided into six groups: a high capacity input group, a high capacity output group, a high capacity control group, a low capacity input group, a low capacity output group, and a low capacity control group. Two vocabulary tests were administered—one immediately after the tasks and the other two weeks later. Using repeated measures ANOVA, the findings revealed that (1) the high capacity learners significantly outperformed the low capacity learners on both the immediate and delayed tests; and (2) while the output groups showed better performance than the input groups on both tests, the differences were not statistically significant. These results add to the findings of existing research on second language (L2) vocabulary acquisition and provide valuable pedagogical insights aimed at improving L2 vocabulary instruction.
As an innovative approach to language pedagogy, Computer-Assisted Language Learning (CALL) research has been gaining traction in recent decades. However, the novel incorporation of technology in the classroom context presents some unique challenges unprecedented in conventional language learning contexts. The present study is an attempt at identifying the factors prohibiting the successful implementation of CALL, with particular attention on the context of Iran. To this end, an exploratory mixed-methods sequential design was adopted. Fifteen Iranian EFL instructors were interviewed and the data were analyzed through thematic analysis. Built upon the findings of the interviews, a questionnaire was developed to assess the generalizability of the interview findings. The 33-item questionnaire was developed and distributed online among 200 EFL teachers. It was revealed that certain factors, including EFL teachers and learners' knowledge of computers, cultural and religious background, institutional support policy, and human factors such as learners' learning style and age could hinder the successful incorporation of CALL in language learning contexts. Principal Component Analysis (PCA) confirmed the generalizability of the identified prohibitive factors. The findings are discussed under the light of Rogers’ (2003)Diffusion of Innovation Theory (DIT) to further contextualize the implications of the study for macro- and micro-level policymakers, curriculum developers, and language teachers.
Introduction: Data-driven learning has emerged as a powerful method in language teaching and has drastically changed the traditional methods of teaching and learning, especially in academic writing. So, the present study was conducted to investigate the effect of data-driven learning on the English academic writing of medical students. Method: In this quasi-experimental intervention study, 29 MSc students of different fields of medical sciences participated in a training intervention program using a data-driven learning approach focusing on self-generated corpora of academic articles related to their fields of study. Students were asked to write an academic text related to their fields at the beginning and end of the course. Written texts were graded based on the Hemp-Lyons academic writing rubric, and the data collected from the pre-and post-test assessments were analyzed using the paired-sample t-test. Results: Comparison of pre-test scores with a mean of 59 (SD = 2.26) and post-test scores with a mean of 78.53 (SD = 2.33) indicated a significant improvement in the writing of the participants of this study (p < 0.05). Conclusion: In light of confirming the educational suitability of the data-driven approach and recognizing the need for students to engage in English article writing and publication, these findings serve as a valuable aid to MSc students studying medical sciences, facilitating their academic writing in English.
This study focuses on the development of lexical competence of tertiary level EFL learners who have reached C1 level according to CEFR during their course of study, but who still have difficulty in recognizing and producing academic words in terms of their correct and appropriate use in various contexts. Following a data-driven learning (DDL) approach within an action research paradigm, this study aims to discover whether corpus investigation makes a difference in students’ vocabulary knowledge and how they react to corpus data in learning vocabulary. To this end, the study was carried out in a listening/speaking course of two C1 level classes in an EFL classroom at an English preparatory school in Higher Education. In one of the classes, conventional lesson materials, and in the other, corpus-based lesson materials were used to teach the selected vocabulary items. The effect of corpus-based lesson materials on vocabulary learning was examined in relation to conventional materials. The data obtained from pre and post-tests showed that although there was a significant increase in students’ scores from pre-test to post-test, corpus use made statistically no significant difference in their scores as compared to the conventional method that had been adopted during the regular course of study based on the contextual guesswork involved in the coursebook. Students’ reactions throughout the implementation of corpus-based materials and the feedback sessions held with the students, shed light on the results and suggested some pedagogical guidelines for using corpora in teaching L2 vocabulary.
This study used a meta-analytic structural equation modeling approach to build extended versions of the simple view of reading (SVR) model in second and foreign language (SFL) learning contexts (i.e., SVR-SFL). Based on the correlation coefficients derived from primary studies, we replicated and integrated two previous extended meta-analytic SVR models, that is, Quinn and Wagner’s (2018) model with an English-speaking population with a cognitive factor and Peng et al.’s (2021) model with Chinese-speaking readers with metalinguistic skills. A total of 180 independent samples (N = 36,235) obtained from 152 empirical studies in SFL contexts were included in our meta-analytic structural equation model. The results revealed that the collected data successfully replicated H. Lee et al.’s (2022) SVR model in SL contexts (SV2R) in terms of overall model fit and moderation effects; in addition, the results confirmed that the data fit well with the extended SVR-SFL models.
This Element provides a systematic overview and synthesis of corpus-based research into collocations focusing on the learning and use of collocations by second language (L2) users. Underlining the importance of collocation as a key notion within the field of corpus linguistics, the text offers a state-of-the-art account of the main findings related to the applications of corpora and corpus-based measures for defining, identifying and analysing collocations as related to second language acquisition. Emphasising the quality of L2 collocation research, the Element illustrates key methodological issues to be considered when conducting this type of corpus analysis. It also discusses examples of pertinent research questions and points to representative studies treated as models of good practice. Aiming at researchers both new and experienced, the Element also points to avenues for future work and shows the relevance of corpus-based analysis for improving the process of learning and teaching of L2 collocations.
Introduction. The introduction of information technologies into the educational process is an integral part of the successful work of the teacher and the achievement of learning objectives; therefore, the use of text corpora and corpus technologies as a means of supporting the foreign language teaching is one of the urgent trends of improving the teaching methods. The purpose of the study is to provide a theoretical justification, develop a set of tasks and practical confirmation of the effectiveness of the methodology for the formation of lexical and grammatical skills of students in German based on the corpus-based technologies. Materials and methods. The German corpora such as the Leipzig Corpus of Modern German (Wortschatz Universität Leipzig) and the German corpus DWDS (Digitales Wörterbuch der deutschen Sprache) were used as the authentic sources for compiling the set of tasks. In particular, the program QuAX-DaF (Quantitative Analyze von TeXten für Deutsch als Fremdsprache), which provides the statistical text processing, was used. 60 students of the 3rd-4th courses of Kazan Federal University, studying in the field of study “Pedagogical Education (with two educational program specializations)” (Bachelor’s degree), took part in the pedagogical experiment. The Welch’s test was used to establish the statistically significant differences between the experimental and control groups. Study results. As a result of the study, a set of tasks for the formation of lexical and grammatical skills was created and introduced into the educational process. The conducted pedagogical experiment confirms the effectiveness of the inclusion of corpus technologies in the formation of lexical and grammatical skills of students (t = 1.11; p≤0.05). After classes using materials that include working with concordance, building a lexical / collocation profile of a word with the subsequent compilation of a thematic dictionary, the number of students with a high level of formation of lexical and grammatical skills increased by 6%, with an average level – improved by 7%, and with a low level – decreased by 13%. Conclusions. The results of the study contribute to the development of the corpus-based linguodidactics; the set of developed tasks may become an incentive for more intensive use of corpus-based technologies in foreign language teaching.
Audiovisual input has received increasing attention from the Second Language Acquisition (SLA) and the Computer-Assisted Language Learning (CALL) domains during the past few decades due to its vividness, authenticity, and easy accessibility. Videos with on-screen texts, as a widespread way of audiovisual input in second language (L2) teaching and learning, influence L2 learners’ performance in various aspects, including their vocabulary learning. The wide application and profound influence of such kind of input call for a systemic review on this important domain of research. Accordingly, this paper reviews the empirical studies on the effects of on-screen texts on L2 vocabulary learning. Specifically, it seeks to evaluate the role of different types of on-screen texts (i.e., subtitles, captions, and dual subtitles) and various modes of captions (i.e., full captions, keyword captions, glossed captions, annotated captions, and enhanced captions) in L2 vocabulary development. It also discusses other factors that concur with on-screen texts and influence L2 vocabulary gains from audiovisual input, such as learners’ vocabulary size, L2 proficiency, frequency of occurrence, number of viewing, instructional strategy, and test time. Finally, some suggestions are provided for future research.
This study aimed to synthesize the structural relationships among willingness to communicate (WTC) and its high-evidence factors in second language (L2) learning contexts by adopting meta-analytic structural equation modeling (MASEM). The MASEM approach is designed to construct a structural equation model (SEM) to explain correlations between variables by pooling correlation coefficients reported in previous literature. This study integrated 44 independent samples (N = 12,094) and built a MASEM model to investigate the structural relations of WTC, its three high-evidence factors (learners’ perceived L2 competence, L2 motivation, and L2 anxiety), and frequency of learners’ L2 use. The results of meta-analysis successfully supported our proposed model of L2 WTC. Furthermore, among the three high-evidence factors, it was found that learners’ perceived L2 competence influenced L2 WTC the most. In addition, the results of the moderator analyses indicated that learners’ L2 proficiency and WTC contexts (inside vs. outside classrooms) significantly influenced the relationships between L2 WTC and its high-evidence factors. The implications of these results are discussed in further depth and detail.
This study discusses the educational roles afforded by the use of linguistic corpora as a teaching tool in pre-tertiary education and explores upper secondary students’ opinions and experiences of educational roles following corpus-based lessons. The data were collected through group interviews of 20 students following a two-week period where the students’ regular English teacher collaborated with the researcher/author to plan and implement a corpus-based approach in two first-year upper secondary school classes. The interview subjects were selected from the 69 total students across the two classes based on the teacher’s recommendations and the researcher’s observations throughout the implementation period. The results show that during the largely student-centered, corpus-based approach, students felt that the teacher was absent and unengaging at times, but that they were used to “self-study” in his lessons. The students also wanted more variation in the approaches taken by their teacher beyond purely student-centered ones. This paper advocates for a diversification of educational roles where both teachers and learners adopt and change between different roles depending on the particular situation. At the same time, the call for role shifts in the corpus-based education literature is criticized in favor of a change in discourse toward one of role diversification.
One of the most important aspects of defining military English communication skills is learners' collocational knowledge, which can be defined as the extent to which learners understand recurring but arbitrary combinations of words, such as friendly fire or surgical strike. So, the current study was motivated to investigate if language educations for learners' collocational knowledge are overall effective.
Furthermore, it aimed to understand how the identified instructional features and learner factors influenced the effectiveness. Based on a total of 82 effect sizes calculated from 28 independent samples with 1,637 participants, the results indicated that second language interventions had an overall positive medium-sized short-term (d = .79, SE = .13, p < .001) as well as long-term (d = .64, SE = .17,
p < .001) impact on improving learners' collocational knowledge. Further, we identified six moderator variables and found that instructions were most effective for adult EFL learners, especially when delivered in corpus-based instructions during longer periods of time. How to effectively improve military English education based on the findings is further discussed.
The present study investigates the effects of two different vocabulary learning conditions in digital reading environments equipped with electronic textual glossing. The first condition presents the concordance lines of a target lexical item, thereby making learners infer its meaning by reading the referenced sentences. The second condition additionally offers the definition of a target lexical item after learners consult the concordance lines, thus enabling learners to confirm their meaning inference. A total of 138 English as a Foreign Language students completed a meaning-recall vocabulary pre-test, and three different reading tasks, which were followed by meaning-recall vocabulary post-tests in a repeated measures design with a control condition. Overall, the findings showed that the second condition resulted in higher vocabulary gains than both the first condition andthe control condition. Yet, a closer look at the interactions of (a) the participants’ clicking behaviors, (b) the difficulty of selected concordance lines, (c) the surrounding contexts around target lexical items, and (d) the participants’ prior knowledge of the target lexical items showed that each target lexical item may require different treatments for it to be recalled most efficiently and effectively. Through this investigation, the present study suggests that glossary information, such as concordance lines, may involve more complex and unexpected learner interactions.
This study applied systematic meta‐analytic procedures to summarize findings from experimental and quasi‐experimental investigations into the effectiveness of using the tools and techniques of corpus linguistics for second language learning or use, here referred to as data‐driven learning (DDL). Analysis of 64 separate studies representing 88 unique samples reporting sufficient data indicated that DDL approaches result in large overall effects for both control/experimental group comparisons ( d = 0.95) and for pre/posttest designs ( d = 1.50). Further investigation of moderator variables revealed that small effect sizes were generally tied to small sample sizes. Research has barely begun in some key areas, and durability/transfer of learning through delayed posttesting remains an area in need of further investigation. Although DDL research demonstrably improved over the period investigated, further changes in practice and reporting are recommended.
Open Practices
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There are many questions about how EFL learners infer word meanings from context and what distinguishes successful from less successful inferencers. This study explored the lexical inferencing strategies used by EFL learners and the characteristics which distinguish successful from less successful inferencers. To this end, 15 EFL students in an intact class were selected. The participants were supposed to think aloud while they were reading the passages and trying to infer the meanings of unknown words. Two passages were given to them and 20 words were highlighted as the target words. Afterwards, the number of used strategies and percentage of the participants’ correct inferencing were identified. Then, the participants were divided into two groups of successful and less successful inferencers. Mann-Whitney U tests were conducted to examine the two groups in terms of the strategies used by the participants. The results revealed no significant differences between the successful and less successful inferencers in terms of the number of strategies. However, they differed concerning the quality of each strategy type (i.e., the way they made use of lexical inferencing strategies). The results can be of significance for teachers and learners of English to consider the quality of inferential strategies more than the quantity.
This study describes the influence of an explicit focus on keywords in news texts for classroom activities on reading comprehension of news items. The general objective was to examine whether exploiting keywords through various tasks can aid learners in subsequent decoding of information in a text. The specific objective was to conduct a study with business English students at B1 level in which electronic data-driven learning (DDL) is compared with more conventional paper-based activities. The experimental DDL group exploited KWIC concordances of news keywords, while the other group read and answered reading comprehension exercises targeting the same items. Pre-tests and post-tests were used to compare the progress of the two groups, while direct observation, logs and questionnaires provided further insight. From the test results and the participants' feedback, DDL activities focusing on news keywords seem to work favorably for the students' comprehension of news.
The present article deals with the issue of how to create and operate a customizable on-line concordancer from viewpoints of language teachers and with their own laptops. It aims to introduce how to use and manage this application without relying on computer engineers for various pedagogical purposes, focusing on the four beneficial dimensions of its interface and technical features: accessibility, simplicity, functionality, and manageability. In addition, the carefully written directions illustrate how to implement this open-source application on laptops using pre-established or customized corpora. For those in the field of language teaching and learning, this application is designed to allow teachers to operate different types or levels of corpora in separate spaces on one server and to enable multiple simultaneous connections in classroom contexts. Ultimately, the authors believe that this application will not only allow students to actively experience data-driven learning anywhere and anytime, but also will help teachers manage their own version of this on-line concordancer by autonomously uploading any kinds of source texts for corpus analysis at their pedagogical discretion.
One of the many new features of English language learners’ dictionaries derived from the technological developments that have taken place over recent decades is the presence of corpus-based examples to illustrate the use of words in context. However, empirical studies have generally not been able to produce conclusive evidence about their actual worth. In Frankenberg-Garcia (2012a), I argued that these studies – and indeed learners’ dictionaries themselves – do not distinguish sufficiently between examples meant to aid language comprehension and examples that focus on enhancing language production. The present study reports on an experiment with secondary school students carried out to test the usefulness of separate corpus examples for comprehension and production. The results support the need for different types of examples for comprehension and production, and provide evidence in support of data-driven learning, particularly if learners have access to more than one example.
Working memory (WM), the ability to store and manipulate information for short periods of time, is an important predictor of scholastic aptitude and a critical bottleneck underlying higher-order cognitive processes, including controlled attention and reasoning. Recent interventions targeting WM have suggested plasticity of the WM system by demonstrating improvements in both trained and untrained WM tasks. However, evidence on transfer of improved WM into more general cognitive domains such as fluid intelligence (Gf) has been more equivocal. Therefore, we conducted a meta-analysis focusing on one specific training program, n-back. We searched PubMed and Google Scholar for all n-back training studies with Gf outcome measures, a control group, and healthy participants between 18 and 50 years of age. In total, we included 20 studies in our analyses that met our criteria and found a small but significant positive effect of n-back training on improving Gf. Several factors that moderate this transfer are identified and discussed. We conclude that short-term cognitive training on the order of weeks can result in beneficial effects in important cognitive functions as measured by laboratory tests.
Background:
Metacognition and working memory (WM) have been found associated with success in reading comprehension, but no studies have examined their combined effect on the training of reading comprehension. Another open question concerns the role of listening comprehension: In particular, it is not clear whether training to improve reading comprehension must necessarily be based on processing written material or whether, as suggested in a recent study by Clarke et al. (2010, Psychol. Sci., 21, 1106), a programme based on verbal language could also be effective.
Aims:
The study examined the feasibility of improving text comprehension in school children by comparing the efficacy of two training programmes, both involving metacognition and WM, but one based on listening comprehension, the other on reading comprehension.
Participants:
The study involved a sample of 159 pupils attending eight classes in the fourth and fifth grades (age range 9-11 years).
Method:
The listening and reading programmes focused on the same abilities/processes strictly related to text comprehension, and particularly metacognitive knowledge and control, WM (per se and in terms of integrating information in a text). The training programmes were implemented by school teachers as part of the class's normal school activities, under the supervision of experts. Their efficacy was compared with the results obtained in an active control group that completed standard text comprehension activities.
Results:
Our results showed that both the training programmes focusing on specific text comprehension skills were effective in improving the children's achievement, but training in reading comprehension generated greater gains than the listening comprehension programme.
Conclusions:
Our study suggests that activities focusing specifically on metacognition and WM could foster text comprehension, but the potential benefit is influenced by the training modality, that is, the Reading group obtained greater and longer-lasting improvements than the Active control or Listening groups.
Although working memory (WM) figures centrally in many theories of second language (L2) proficiency development and processing, some have argued that the importance of WM is overstated (e.g., Juffs, Transactions of the Philological Society, 102, 199-225, 2004). Despite many studies over the past two decades, the literature lacks a quantitative synthesis of the extant results. In this article, we report a meta-analysis of data from 79 samples involving 3,707 participants providing 748 effect sizes. The results indicate that WM is positively associated with both L2 processing and proficiency outcomes, with an estimated population effect size (ρ) of .255. In additional analyses, we assessed whether the WM-criterion relationship was modulated by potential covariates identified in the literature search (i.e., participant characteristics, WM measure features, criterion measure factors, and publication status). The results of the covariate analyses indicated larger effect sizes for the executive control (vs. storage) component of WM, and for verbal (vs. nonverbal) measures of WM. Minimal publication bias was detected, suggesting that WM has a robust, positive relationship with L2 outcomes. We discuss the implications of these results for models of WM and theories of L2 processing and L2 proficiency development.
This study analyzed phonological short-term memory (PSTM) and working memory (WM) and their relationship with vocabulary and grammar learning in an artificial foreign language. Nonword repetition, nonword recognition, and listening span were used as memory measures. Participants learned the singular forms of vocabulary for an artificial foreign language before being exposed to plural forms in sentence contexts. Participants were tested on their ability to induce the grammatical forms and to generalize the forms to novel utterances. Individual differences in final abilities in vocabulary and grammar correlated between 0.44 and 0.76, depending on the measure. Despite these strong associations, the results demonstrated significant independent effects of PSTM and WM on L2 vocabulary learning and on L2 grammar learning, some of which were mediated by vocabulary and some of which were direct effects.
In recent years the study of second language (L2) vocabulary learning through reading has attracted much attention in the field of L2 acquisition. A specific area that has received wide interest is the examination of the processes involved in deriving word meanings from context. The purpose of the present study was to examine the relationships between the ease with which learners infer word meanings from context, the inferential strategies they use, and their subsequent retention of these words. Eleven ESL learners read and inferred the meanings of 10 unknown words in an academic text. Think-aloud procedures were used to collect data about learners’ inferential strategies and their correct inferences during reading. A pre-test and a post-test were used to examine learners’ degrees of retention. The results showed an inverse relationship between ease of inference and retention. Quantitative and qualitative analyses of learners’ inferential strategies showed a significant relationship between the type and frequency of use of inferential strategies and retention. The findings confirm that a distinction needs to be made between ease of inferencing and the retention of the word meanings inferred from the context. Findings also suggest that the degree of retention depends on the type of strategies used.
The authors provide a basic set of guidelines and recommendations for information that should be included in any manuscript that has confirmatory factor analysis or structural equation modeling as the primary statistical analysis technique. The authors provide an introduction to both techniques, along with sample analyses, recommendations for reporting, evaluation of articles in The Journal of Educational Research using these techniques, and concluding remarks.
This article overviews current research on second language vocabulary learning. It concludes that a large vocabulary is necessary to function in English: 8000—9000 word families for reading, and perhaps as many as 5000—7000 families for oral discourse. In addition, a number of word knowledge aspects need to be learned about each lexical item. Taken together, this amounts to a substantial lexical learning challenge, one which many/most learners fail to meet. To facilitate adequate vocabulary learning, four vocabulary learning partners (students, teachers, materials writers, and researchers) need to contribute to the learning process. Vocabulary learning programs need to include both an explicit, intentional learning component and a component based around maximizing exposure and incidental learning. The four learning strands (meaning-focused input, meaning-focused output, language-focused learning, and fluency development) suggested by Nation (2001) provide a structure by which to integrate intentional and incidental vocabulary learning. The overriding principle for maximizing vocabulary learning is to increase the amount of engagement learners have with lexical items. All four learning partners need to acknowledge the incremental nature of vocabulary learning, and to develop learning programs which are principled, long-term, and which recognize the richness and scope of the lexical knowledge that needs to be mastered.
This book explores implications for applied linguistics of recent developments in technologies used in second language teaching and assessment, language analysis, and language use. Focusing primarily on English language learning, the book identifies significant areas of interplay between technology and applied linguistics, and it explores current perspectives on perennial questions such as how theory and research on second language acquisition can help to inform technology-based language learning practices, how the multifaceted learning accomplished through technology can be evaluated, and how theoretical perspectives can offer insight on data obtained from research on interaction with and through technology. The book illustrates how the interplay between technology and applied linguistics can amplify and expand applied linguists’ understanding of fundamental issues in the field. Through discussion of computer-assisted approaches for investigating second language learning tasks and assessment, it illustrates how technology can be used as a tool for applied linguistics research.
The notion of language learning with technology is one that has been extensively explored in the field of computer-assisted language learning, or CALL. One key feature highlighted by this research is the way in which technological innovations have extended the reach of course design. For example, the effect of internet connectivity has often been to break down the four walls of the classroom, allowing teachers and learners to connect with a wider, global public and learn flexibly at a time and place of their own choosing. These affordances are reflected in some recent developments of CALL research.
This volume includes articles on theory and research in pedagogical grammar written by authorities from around the world. In the paperback edition, Professor Odlin brings together eleven authorities from various parts of the world to update current theory and research in pedagogical grammar. The first section addresses grammatical analysis, covering Chomskyan Universal Grammar and a number of alternative models. The second section shows how lexicon and discourse rules interact with and influence the grammatical system. A final section deals directly with applications, outlining effective methods of teaching grammar in different areas of the language curriculum.
This book is about investigating the way people use language in speech and writing. It introduces the corpus-based approach to linguistics, based on analysis of large databases of real language examples stored on computer. Each chapter focuses on a different area of linguistics, including lexicography, grammar, discourse, register variation, language acquisition, and historical linguistics. Example analyses are presented in each chapter to provide concrete descriptions of the research methods and advantages of corpus-based techniques. Ten methodology boxes provide clear and concise explanations of the issues in doing corpus-based research and reading corpus-based studies and there is a useful appendix of resources for corpus-based investigation. This lucid and comprehensive introduction to the subject will be welcomed by a broad range of readers, from undergraduate students to professional researchers.
The influence of cognitive processing on second language acquisition (SLA), and on the development of second language (SL) instruction, has always been a subject of major interest to both SLA researchers and those involved in SL pedagogy. Recent theoretical research into SLA and SL pedagogy has shown renewed interest in the role of cognitive variables such as attention, short, working, and long term memory, and automaticity of language processing. This volume first examines the theoretical foundations of research into the cognitive processes underlying SLA, and then describes various implications for pedagogically oriented research and for SL classroom practice. The blend of research from the cognitive sciences and applied linguistics make it an excellent introduction to applied linguists and language teachers interested in the psycholinguistic processes underlying SLA.
Since the publication of Ericsson and Simon's ground-breaking work in the early 1980s, verbal data has been used increasingly to study cognitive processes in many areas of psychology, and concurrent and retrospective verbal reports are now generally accepted as important sources of data on subjects' cognitive processes in specific tasks. In this revised edition of the book that first put protocol analysis on firm theoretical ground, the authors review major advances in verbal reports over the past decade, including new evidence on how giving verbal reports affects subjects' cognitive processes, and on the validity and completeness of such reports.
In a substantial new preface Ericsson and Simon summarize the central issues covered in the book and provide an updated version of their information-processing model, which explains verbalization and verbal reports. They describe new studies on the effects of verbalization, interpreting the results of these studies and showing how their theory can be extended to account for them. Next, they address the issue of completeness of verbally reported information, reviewing the new evidence in three particularly active task domains. They conclude by citing recent contributions to the techniques for encoding protocols, raising general issues, and proposing directions for future research.
All references and indexes have been updated.
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In this study, we used a data-mining approach to identify hidden groups in a corpus-based second language (L2) vocabulary experiment. After a vocabulary pre-test, a total of 132 participants performed three online reading tasks (in random orders) equipped with the following glossary types: (1) concordance lines and definitions of target lexical items, (2) concordance lines of target lexical items, and (3) no glossary information. Although the results of a previous study based on variable-centred analysis (i.e. multiple regression analysis) revealed that more glossary information could lead to better learning outcomes (Lee, Warschauer & Lee, 2017), using a model-based clustering technique in the present study allowed us to unearth learner types not identified in the previous analysis. Instead of the performance pattern found in the previous study (more glossary led to higher gains), we identified one learner group who exhibited their ability to make successful use of concordance lines (and thus are optimized for data driven learning, or DDL; Johns, 1991), and another group who showed limited L2 vocabulary learning when exposed to concordance lines only. Further, our results revealed that L2 proficiency intersects with
vocabulary gains of different learner types in complex ways. Therefore, using this technique in computer assisted language learning (CALL) research to understand differential effects of accommodations can help us better identify hidden learner types and provide personalized CALL instruction.
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This study investigates the effects of corpus use on second language (L2) vocabulary learning as well as the influence of moderators on effectiveness. Based on 29 studies representing 38 unique samples, all of which met several criteria for inclusion (e.g. with control groups), we found an overall positive medium-sized effect of corpus use on L2 vocabulary learning for both short-term (77 posttest effect sizes; Hedges’ g = 0.74, SE = 0.09, p < .001) and long-term periods (34 follow-up effect sizes; Hedges’ g = 0.64, SE = 0.17, p < .001). Furthermore, large variation in adjusted mean effect sizes across moderators was revealed. Above all, for the different dimensions of L2 vocabulary knowledge, in-depth knowledge (i.e. referential meanings as well as syntactic features of vocabulary) was associated with a large effect size. Moreover, the results revealed that learners’ L2 proficiency and several features of corpus use (i.e. interaction types, corpus types, training, and duration) influence the magnitude of the effectiveness of corpus use in improving L2 vocabulary learning.
This study aimed to determine as to whether or not the text type and strategy usage affect the EFL learners’ lexical inferencing performance. The participants were comprised of 87 first-year English majors at a technical university. Data were collected from (1) a lexical inferencing test with excerpts of narrative and expository texts, for which both multiple-choice and definition tasks were designed, respectively, and then (2) the responses from the learners’ self-reported strategy usage. The quantitative analyses demonstrated that the text types significantly affected the EFL learners’ lexical inferencing performance, in which the EFL learners performed better for the narrative excerpt than for the expository texts. However, significant coefficients between the strategy use and the lexical inferencing performance were not found in this study. The results further implied that the text structure and the lexical inferencing strategies should be explicitly taught to the EFL learners.
The role of working memory in vocabulary acquisition has been well established in the literature. In this study, we proposed and empirically tested the multicomponent view of vocabulary acquisition, which states that multiple language and cognitive skills are involved to facilitate phonological and semantic representations needed for vocabulary acquisition. Working memory and attention were hypothesized to be directly and indirectly related to vocabulary, whereas inference and morphosyntactic knowledge were hypothesized to be directly related to vocabulary (measured by the Picture Vocabulary Test of the Woodcock–Johnson III battery). Results from 262 kindergartners using path analysis revealed that all the multiple cognitive and language skills were directly related to vocabulary after controlling for age, gender, racial/ethnic backgrounds, socioeconomic status (as measured by free or reduced-price lunch eligibility), and each other. Furthermore, working memory and attention also made indirect contributions via inference and morphosyntactic knowledge. Total effects (beta weights), accounting for direct and indirect effects, were .33 for working memory, .23 for attention, .18 for inference, and .18 for morphosyntactic knowledge. These results indicate that although working memory is important, contributions of other language and cognitive skills should be considered in vocabulary acquisition. Theoretical and practical implications are discussed.
Verbal reports, specifically in the form of concurrent verbalizations (i.e., think-alouds [TAs]), have played a foundational role in the production of knowledge in applied linguistics. Most often drawn upon because the talk they generate is deemed to accurately reflect individual learners’ thought or cognitive processes as they complete an L2 task, concurrent verbalization methods have been central to investigations of and claims about the learning, use, and assessment of L2 vocabulary, listening, speaking, reading, and writing (among others). And although critical discussion concerning the quality of spoken data obtained through concurrent verbalization methods continues among L2 researchers (e.g., Cohen, Andrew D. 1987. Using verbal reports in research on language learning. In Claus Færch & Gabriele Kasper (eds.)
Cognitive Individual Differences in Second Language Processing and Acquisition contains 14 chapters that focus on the role of cognitive IDs in L2 learning and processing. The book brings together theoretical and methodological approaches to the study of cognitive IDs, as well as empirical studies that investigate the mediating role of cognitive IDs in various linguistic domains. Chapters include contributions from researchers working within second language acquisition (SLA), psycholinguistics, and cognitive psychology, sharing a common interest in the application of cognitive IDs to their respective areas of study. The interdisciplinary understanding of cognitive IDs presented in this book makes the book of interest to a wide readership of graduate students, faculty members, and academic researchers in the fields of SLA, psycholinguistics, cognitive psychology, and education.
Research on data-driven learning (DDL), or teaching and learning languages with the help of electronic corpora, has shown that it is both effective and efficient. Nevertheless, DDL is still far from common pedagogical practice, not least because the empirical research on it is still limited and narrowly focused. This study addresses some gaps in that research by exploring the effectiveness of DDL for teaching low-proficiency learners lexico-grammatical constructions (verb-preposition collocations) in German, a morphologically rich language. The study employed a pretest-posttest design with intact third- and fourth-semester classes for German as a foreign language at a US university. The same collocations were taught to each group during one class period, with one group at each course level taking a paper-based DDL lesson with concordance lines from a native-speaker corpus and the other one taking a traditional rule-based lesson with textbook exercises. These constructions were new to third-semester students, whereas fourth-semester students had been exposed to them in the previous semester. The results show that, whereas the DDL method and the traditional method were both effective and resulted in lexical and grammatical gains, DDL was more effective for teaching new collocations. The study thus argues in favor of using paper-based DDL in the classroom at lower proficiency levels and for languages other than English.
The abstract for this document is available on CSA Illumina.To view the Abstract, click the Abstract button above the document title.
Research results over the past decades have consistently demonstrated that a key reason why many second language learners fail--while some learners do better with less effort--lies in various learner attributes such as personality traits, motivation, or language aptitude. In psychology, these attributes have traditionally been called "individual differences." The scope of individual learner differences is broad--ranging from creativity to learner styles and anxiety--yet there is no current, comprehensive, and unified volume that provides an overview of the considerable amount of research conducted on various language learner differences, until now.
This study investigated the effects of three different types of electronic textual glosses, tooltip-type glossing, frame-type glossing, and concordance glossing on foreign language vocabulary learning. While the first two glossing types provide the definitions of glossed words, with the only difference being their user interface designs, the third type provides authentic concordance sentences for glossed words. A total of 83 university students of English as a foreign language (EFL) participated in the study. They completed a computer-based reading task, meaning-recall vocabulary tests at three different points in time, and a post-reading questionnaire. The results showed that the intermediate EFL learners were affected not by a difference in terms of glossing formats, but by the type of information provided, with tooltip-type and frame-type glosses bringing about more positive learning outcomes. While the three groups all experienced a similar cognitive load, the findings further revealed that the tooltip-type and frame-type groups made greater gains of target vocabulary than their concordance counterpart. Moreover, the participants from the two former groups consequently rated their respective glossing more positively than those from the latter group.
The abstract for this document is available on CSA Illumina.To view the Abstract, click the Abstract button above the document title.
This study compares the effectiveness of online textual glosses enhanced with modified corpus-extracted sentences presented in concordance lines and textual glosses enhanced with dictionary definitions drawn from an online learner’s dictionary for academic vocabulary learning at higher proficiency levels. Particularly, the study aimed to determine which textual gloss technique would be most beneficial in helping intermediate to advanced language learners, who likely possess foundational receptive knowledge, i.e. they recognize the word and know the definition, gain productive knowledge of academic lexical items. While the usefulness of multimedia and image-based glosses are not disputed, lexical items from an academic word list may not be easily glossed through these techniques, and the development of a concordance-based modality may prove beneficial for more proficient learners seeking productive vocabulary knowledge. Also investigated were learner attitudes towards the textual annotation techniques. Participants in both experimental groups exhibited post test gains in receptive and judgment tasks, but only the concordance-based group displayed improvement on the productive assessment. Further, the concordance-based group responded that the glosses were beneficial and likely to be used for subsequent language study, while the dictionary group indicated the glosses would not be later used as the annotations were perceived as ineffective.
Working memory (WM) capacity is highly correlated with general cognitive ability and has proven to be an excellent predictor for academic success. Given that WM can be improved by training, our aim was to test whether WM training benefited academic abilities in elementary-school children. We examined 28 participants (mean age = 8.3 years, SD = 0.4) in a pretest-training-posttest-follow-up design. Over 14 training sessions, children either performed adaptive WM training (training group, n = 14) or nonadaptive low-level training (active control group, n = 14) on the same tasks. Pretest, posttest, and follow-up at 3 months after posttest included a neurocognitive test battery (WM, task switching, inhibition) and standardized tests for math and reading abilities. Adaptive WM training resulted in larger training gains than nonadaptive low-level training. The benefits induced by the adaptive training transferred to an untrained WM task and a standardized test for reading ability, but not to task switching, inhibition, or performance on a standardized math test. Transfer to the untrained WM task was maintained over 3 months. The analysis of individual differences revealed compensatory effects with larger gains in children with lower WM and reading scores at pretest. These training and transfer effects are discussed against the background of cognitive processing resulting from WM span training and the nature of the intervention.
The present study assessed the impact of sample size on the power and fit of struc-tural equation modeling applied to functional brain connectivity hypotheses. The data consisted of time-constrained minimum norm estimates of regional brain activity dur-ing performance of a reading task obtained with magnetoencephalography. Power analysis was first conducted for an autoregressive model with 5 latent variables (brain regions), each defined by 3 indicators (successive activity time bins). A series of simu-lations were then run by generating data from an existing pool of 51 typical readers (aged 7.5-12.5 years). Sample sizes ranged between 20 and 1,000 participants and for each sample size 1,000 replications were run. Results were evaluated using chi-square Type I errors, model convergence, mean RMSEA (root mean square error of approxi-mation) values, confidence intervals of the RMSEA, structural path stability, and D-Fit index values. Results suggested that 70 to 80 participants were adequate to model relationships reflecting close to not so close fit as per MacCallum et al.'s recommen-dations. Sample sizes of 50 participants were associated with satisfactory fit. It is
This study examines the use of strategies and knowledge sources in L2 lexical inferencing and their relationship with inferential success. Data consist of introspective and retrospective think-aloud protocols of 21 intermediate ESL learners who attempted to infer new word meanings from context. Analysis reveals that (a) overall, the rate of success was low even when learners used the strategies and knowledge sources they had at their disposal, (b) different strategies contributed differentially to inferencing success, and (c) success was related more to the quality rather than the quantity of the strategies used. Findings challenge a unidimensional conception of the role of strategies in L2 lexical inferencing and instead support an inferencing model that distinguishes between strategies and the ability to use them appropriately and effectively in conjunction with various sources of knowledge in lexical inferencing. This article discusses the pedagogical as well as theoretical implications of the findings for an integrated model of lexical inferencing.
Determining sample size requirements for structural equation modeling (SEM) is a
challenge often faced by investigators, peer reviewers, and grant writers. Recent
years have seen a large increase in SEMs in the behavioral science literature, but
consideration of sample size requirements for applied SEMs often relies on outdated
rules-of-thumb. This study used Monte Carlo data simulation techniques to
evaluate sample size requirements for common applied SEMs. Across a series of
simulations, we systematically varied key model properties, including number of
indicators and factors, magnitude of factor loadings and path coefficients, and
amount of missing data. We investigated how changes in these parameters affected
sample size requirements with respect to statistical power, bias in the parameter
estimates, and overall solution propriety. Results revealed a range of sample size
requirements (i.e., from 30 to 460 cases), meaningful patterns of association
between parameters and sample size, and highlight the limitations of commonly
cited rules-of-thumb. The broad ‘‘lessons learned’’ for determining SEM sample
size requirements are discussed.
This chapter discusses various language learning theories underpinning data-driven learning, namely the noticing hypothesis, constructivist learning and Vygotskyan sociocultural theories. A variety of pedagogic initiatives are used to illustrate the relationship between data-driven learning and language learning theories. The paper also reports on experimental studies which examine students' performance in relation to these three language learning theories as well as learning style preferences. The general consensus from these experimental studies is that while data-driven learning shows promise, additional larger-scale studies of a longitudinal nature are needed to give a more in-depth picture of its beneficial effects.