The instructional effectiveness of automatically generated exercises for learning French grammatical gender: preliminary results

Abstract

Research into Automatic Exercise Generation (AEG) contributes new tools aimed at reducing the barrier to creating practice material, but few have been deployed in actual instruction with real learners. The present study extends previous work by employing AEG technology in instruction with L2 learners to evaluate its pedagogical effectiveness. Thirty-two second language learners of French were assigned to either a treatment condition, who practised with generated exercises, or a control condition that did no extra work. Both groups completed pre-, post-, and delayed post-tests. Participants in the treatment condition also completed questionnaires that elicited data on their in-practice emotions and the situations in which they arose. Our preliminary results suggest that AEG-based instruction can be pedagogically effective and support positive learning experiences, help to identify aspects of the instruction that could be improved, and suggest that a peer review mechanism could have an important role in future CALL platforms that use generated exercises.

Generation of exercises for derivational morphology using the Démonette database

“…The same type of exercise can be used to explore the notion of morphological families and their alignment in derivational paradigms (Bonami & Strnadová, 2019;Hathout & Namer, 2019, 2022. For example, the pair contestataire/contestation can be completed by lexemes such as contester 'to contest V ' and contestable 'contestable'.…”

“…Automatic exercise generation has been the subject of numerous studies, including (Wilson, 2014;Baptista et al, 2016;Chinkina & Meurers, 2017;Kledilson et al, 2018;Agirrezabal et al, 2019;Bodnar, 2022;Heck & Meurers, 2022). The main contribution of the demonstrator we present here is to illustrate the quality of the Démonette database and to give an idea of the range of exercises it can produce.…”

EuroCALL 2023. CALL for all Languages - Short Papers

“…With applications such as example sentence selection systems (Pilán et al, 2016), difficulty classifiers (Tack, 2021) and exercise generation tools (Bodnar, 2022;, the integration of Intelligent Computer-Assisted Language Learning (ICALL) in language learning courses can be a valuable addition to the arsenal of teaching methods, for example as a complement to on-campus vocabulary learning activities (Ruiz et al, 2021). Nevertheless, using ICALL also comes with its limitations.…”

Making ICALL’s intelligence accessible and understandable: evaluation, validation, and future directions of ICALL ecosystems

“…With applications such as example sentence selection systems (Pilán et al, 2016), difficulty classifiers (Tack, 2021) and exercise generation tools (Bodnar, 2022;Heck & Meurers, 2022), the integration of Intelligent Computer-Assisted Language Learning (ICALL) in language learning courses can be a valuable addition to the arsenal of teaching methods, for example as a complement to on-campus vocabulary learning activities (Ruiz et al, 2021). Nevertheless, using ICALL also comes with its limitations.…”