WEB 2.0 AND LANGUAGE LEARNERS’ MOTIVATION: AN ACTION RESEARCH STUDY
Bibliographic record
Abstract
Based on the observation that most of my students use computer-based technology (CBT) in their daily activities, I used computer assisted language learning (CALL) as an intervention in this action research study, carried out at a university in Bangladesh. This CALL curriculum was focused on Web 2.0 and its applications for educational purposes. The main objective of the study was to understand the effects of a CALL curriculum on the participants’ learning motivation. To meet this objective, I designed CALL and non-CALL lessons to teach English to a class of first-year undergraduate students. Throughout this course, I observed students’ behaviours and attitudes and collected data from different artifacts and student responses. Comparison between student behaviours during the CALL and non-CALL lessons and analysis of the triangulated data indicated that the use of Web 2.0 in the CALL curriculum contributed to an increase in students’ motivation as well as their learning of the target language.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.017 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".