The effects of working memory and declarative memory on instructed second language vocabulary learning: Insights from intelligent CALL

Abstract

The extent to which learners benefit from instruction may be largely dependent on their individual abilities. However, there is relatively little work on the interaction between instructional effectiveness in second language learning and learner individual factors. In this study, we investigated the relationship between instruction, individual differences in cognitive abilities (working memory and declarative memory), and second language vocabulary acquisition in the context of web-based intelligent computer assisted language learning (ICALL). To this end, 127 adult learners of English, predominantly advanced-level, German-speaking learners, read news texts on the web for about two weeks using an ICALL system under two instructional conditions: form-focused and meaning-focused instruction. Learners in the form-focused condition read and completed automatically-generated multiple-choice gaps where phrasal verbs appeared in the text, while learners in the meaning-focused condition simply read and did not complete any gaps. Mixed-effects regression analyses showed that working memory was associated with vocabulary acquisition and that this association depended on the instructional context, with working memory being predictive of learning only in the form-focused condition, suggesting an aptitude-treatment interaction. Furthermore, declarative memory abilities were related to learning only as measured by the Continuous Visual Memory Task, and the relationship was not moderated by instructional condition. Overall, the study contributes to accounting for variability in second language learning in general, as well as in instructional contexts supported by intelligent CALL.

Effectiveness of captioned videos for incidental vocabulary learning and retention: the role of working memory

“…This model assumes that processing knowledge can be effectively enhanced when textual information is simultaneously demonstrated in both verbal and pictorial forms via audio-visual input. There is ample evidence that WM plays a significant role in vocabulary learning (Ellis & Sinclair, 1996;Kim, 2018;Morra & Camba, 2009;Ruiz & Meurers, 2021;Teng & Zhang, 2021). WM, which is widely acknowledged as having limited capacity, is crucial in language learning (Baddeley, 1992).…”

Evaluation of the Effectiveness Computer-Assisted Language Teaching by Big Data Analysis

“…In this study, two natural classes of the second year in a middle school in Weifang City were selected as the experimental class and the control class. e tests and surveys of the students in the two classes before the experiment revealed that the students in the two classes were relatively similar in terms of English-speaking level and learning attitude [18]. e main reasons for choosing the second-year students as the subjects of the study are: on the one hand, compared with the third-year students, the second-year students do not have the pressure of the midterm examination and have more class time for teaching oral English every week, which is convenient for the oral teaching study; on the other hand, the second-year students have accumulated a certain amount of vocabulary and English main grammar, which is suitable to be the experimental subjects of oral teaching.…”

Evaluating the impact of spaced practice using computer-assisted language learning (CALL) on vocabulary learning in the classroom

“…WM has been identified as key predictor of L2 learning (Al-Hammadi, 2012;Larsen-Freeman, 2014;Linck et al, 2014) and has been found to impact lexical learning, particularly under instructional conditions (e.g. intentional vocabulary learning) involving simultaneous attention to form and meaning (Ruiz et al, 2021). Therefore, the present study utilised WMTs to assess the learners' ability to retrieve and manipulate auditory information and to detect any variation in the students' recall ability (Climie & Rostad, 2011;Elsayyad, 2014).…”