Evaluating Integrated Task Based Activities and Computer Assisted Language Learning (CALL)
Bibliographic record
Abstract
his study is to evaluate the implementation of Task Activities based on CALL which consist of observing, questioning, exploring, and communicating. The developed materials are nine chapters that had been implemented in two different classes of SMPN 1 Gresik and SMPM 4 Gresik in Indonesia. Of quesionnaires and interviews, the results indicate that the materials that have been developed already meet the standards for preparing and getting excellent response from users, especially teachers and students in several aspects, namely; competencies and objectives, content material, relevant activities, media which was authentic and interesting, and the fulfillment of the diversity of types of exercises that are available in each chapter. So that these materials can conclusively give the student easier understanding, interesting, and fun learning, because these materials have been equipped with the exercises both in class and individually. This study implies that combination of task based activities and CALL really generates better opportunities to create English Teaching more innovative.
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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 | 0.006 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".