Student perceived effectiveness of task-based instructional design of data-driven synonym learning featuring “mini-lecture”
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 guidan...
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Format: | Article |
Language: | English |
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De Gruyter
2024-03-01
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Series: | Journal of China Computer-Assisted Language Learning |
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Online Access: | https://doi.org/10.1515/jccall-2023-0024 |
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author | Yang Yingying Chen Lin Tian Xumin |
author_facet | Yang Yingying Chen Lin Tian Xumin |
author_sort | Yang Yingying |
collection | DOAJ |
description | 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. |
format | Article |
id | doaj-art-1f48b393e6a440fcb37f79e4d7392e07 |
institution | Kabale University |
issn | 2748-3479 |
language | English |
publishDate | 2024-03-01 |
publisher | De Gruyter |
record_format | Article |
series | Journal of China Computer-Assisted Language Learning |
spelling | doaj-art-1f48b393e6a440fcb37f79e4d7392e072025-01-20T11:08:49ZengDe GruyterJournal of China Computer-Assisted Language Learning2748-34792024-03-01417411410.1515/jccall-2023-0024Student perceived effectiveness of task-based instructional design of data-driven synonym learning featuring “mini-lecture”Yang Yingying0Chen Lin1Tian Xumin2School of Education, Institute of Corpus Studies and Applications, Shanghai International Studies University, Shanghai, ChinaSchool of Education, Shanghai International Studies University, Shanghai, ChinaBijie Institute of Education Science, Bijie, ChinaThis 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.https://doi.org/10.1515/jccall-2023-0024guided inductive approachtask-basedddlperceptionssynonym learning |
spellingShingle | Yang Yingying Chen Lin Tian Xumin Student perceived effectiveness of task-based instructional design of data-driven synonym learning featuring “mini-lecture” Journal of China Computer-Assisted Language Learning guided inductive approach task-based ddl perceptions synonym learning |
title | Student perceived effectiveness of task-based instructional design of data-driven synonym learning featuring “mini-lecture” |
title_full | Student perceived effectiveness of task-based instructional design of data-driven synonym learning featuring “mini-lecture” |
title_fullStr | Student perceived effectiveness of task-based instructional design of data-driven synonym learning featuring “mini-lecture” |
title_full_unstemmed | Student perceived effectiveness of task-based instructional design of data-driven synonym learning featuring “mini-lecture” |
title_short | Student perceived effectiveness of task-based instructional design of data-driven synonym learning featuring “mini-lecture” |
title_sort | student perceived effectiveness of task based instructional design of data driven synonym learning featuring mini lecture |
topic | guided inductive approach task-based ddl perceptions synonym learning |
url | https://doi.org/10.1515/jccall-2023-0024 |
work_keys_str_mv | AT yangyingying studentperceivedeffectivenessoftaskbasedinstructionaldesignofdatadrivensynonymlearningfeaturingminilecture AT chenlin studentperceivedeffectivenessoftaskbasedinstructionaldesignofdatadrivensynonymlearningfeaturingminilecture AT tianxumin studentperceivedeffectivenessoftaskbasedinstructionaldesignofdatadrivensynonymlearningfeaturingminilecture |