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Record W4383346322 · doi:10.20306/kces.2023.6.30.107

A Comparative Study on the Competency-Based Backward Curriculum Design: Focusing on College Level

2023· article· en· W4383346322 on OpenAlexaboutno aff

Bibliographic record

VenueKorean Comparative Education Society · 2023
Typearticle
Languageen
FieldComputer Science
TopicEducation and Learning Interventions
Canadian institutionsnot available
Fundersnot available
KeywordsCurriculumMathematics educationMedical educationPsychologyComputer scienceEngineeringPedagogyMedicine

Abstract

fetched live from OpenAlex

[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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.720
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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.

Opus teacher head0.210
GPT teacher head0.403
Teacher spread0.193 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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