A Comparative Study on the Competency-Based Backward Curriculum Design: Focusing on College Level
Bibliographic record
Abstract
[Purpose] This study aims to explore the nature of competency for the effective operation of competency-based curriculum in university education and conduct a case comparison study focusing on the design of the backword curriculum. The focus of the discussion is on competency-based education and compares competency-based education operated by universities in Australia, Finland, the United States, and Canada. In particular, at the university education level, the design and development of competency-based curriculum were compared with a focus on backward design. [Methods] To achieve this purpose, first, in terms of literature research, we explore the possibility of integrating competency-based education and backward curriculum design. In addition, competency-based education in university education operated in four countries is analyzed based on the established comparative criteria, focusing on case studies. [Results] Based on the commonalities and differences of comparison results, a plan to realize a competency-based curriculum was proposed, focusing on the possibility of integrating competency-based curriculum development and backward design. As a result of major research, a backword design that can be used in university education was proposed, focusing on the possibility of integration of competency-based backword curriculum design. Therefore, in terms of goals, the selection of competencies related to the professional world and goals that reflect the needs of learners are set. In addition, it presents performance tasks and feedback related to life in terms of evaluation that can confirm goals. Finally, it is the stage of teaching and learning development that can learn all cognitive, affective, and psychological areas. We design this series of competency-based steps and present systematic development steps to evaluate all courses. [Conclusion]In order to establish systematic development of competency-based education from a practical and effective perspective, it is necessary to develop a curriculum based on backward design.
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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 | 0.011 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".