Backward design and authentic performance tasks to foster English skills: Perspectives of Hungarian teacher candidates
Bibliographic record
Abstract
This quasi-experimental research aimed to describe the syllabus design process using the backward design model and its features to determine the teacher candidates’ perceptions of its application in the English Skills Development course. To achieve these objectives, the syllabus based on the BDM was designed before starting the course; after that, it was applied to sixteen students enrolled in a teacher preparation program at a Hungarian university in Budapest. At the end of the course, the participants developed sixteen final projects related to the main topic of the course, teaching English as a Foreign Language in Hungary and following the Goal, Role, Audience, Situation, Product, Standard (GRASPS) framework to conduct authentic performance tasks. This research method involves collecting data through written reflections, focus-group interviews and content analysis of the conducted performance tasks. The results show that BDM and authentic performance tasks can be used as a coherent, organized, and flexible syllabus design that supports EFL students by providing differentiated instruction to foster their English skills, creativity, problem-solving and critical thinking skills, long life and autonomous learning, and digital competencies. Furthermore, the results of the study make an essential contribution to the context of EFL by suggesting that planning the syllabus based on the BDM creates strong connections between course objectives, assessment, content, teaching strategies, and technology, thereby offering a practical framework for educators to enhance their teaching practices in the digital age.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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 teacher head, 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".