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Record W2047360901 · doi:10.1177/104687810003100102

Improving Students’ Self-Efficacy in Strategic Management: The Relative Impact of Cases and Simulations

2000· article· en· W2047360901 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSimulation & Gaming · 2000
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Marketing Education
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsCapstone courseCapstoneTask (project management)PsychologyStrategic thinkingSelf-efficacyPersistence (discontinuity)Sample (material)Knowledge managementMathematics educationStrategic planningComputer scienceSocial psychologyBusinessManagementEngineeringMarketing

Abstract

fetched live from OpenAlex

Taught as the “capstone” course in most universities, strategic management is designed to teach the skills of strategic thinking and analysis rather than mere facts or concepts. So, educators should have some assurance that their students learn to “do” strategy. Self-efficacy enhances a person’s task interest, persistence, willingness to exert effort, and, ultimately, task performance. This article investigates the relative contribution of simulations and case studies for improving students’ self-efficacy in strategic management. Using pre-and posttest data from a sample of 252 students, the authors conclude that simulations result in significantly higher improvements in self-efficacy than case studies.

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.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.204
Threshold uncertainty score0.487

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.025
GPT teacher head0.306
Teacher spread0.281 · 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