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Record W4233845937 · doi:10.1504/ijiie.2017.086475

An exploratory study of undergraduate students' learning from case study competitions in the United Arab Emirates

2017· article· en· W4233845937 on OpenAlexaff
Hameedah Sayani, Muneeza Shoaib, Vijaya Kumar, Neelofer Mashood

Bibliographic record

VenueInternational Journal of Innovation in Education · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicSocioeconomic Development in MENA
Canadian institutionsTD Bank Group
Fundersnot available
KeywordsPsychologyPerspective (graphical)Descriptive statisticsCognitionExploratory researchCompetition (biology)Mathematics educationMedical educationSociologyComputer scienceMedicine

Abstract

fetched live from OpenAlex

This exploratory study aims to evaluate the effectiveness of case study competitions as learning tools from the perspective of undergraduate students who have already participated in such competitions in the UAE. The study considers the affective, cognitive and skills development aspects of learning. Quantitative data is collected by surveying undergraduate students from various universities in the UAE who participated in any case study competition. This is done to understand the cognitive, affective, and skill development these students perceive to derive from participating in such competitions. The data is analysed with the help of frequency tables and descriptive statistics. The findings of the study affirm the benefits of the case method in promoting student learning and engagement even in a competitive environment.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.390
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.069
GPT teacher head0.428
Teacher spread0.359 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations2
Published2017
Admission routes1
Has abstractyes

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