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Record W2125032964 · doi:10.19030/ajbe.v4i12.6614

Marketing Plan Competition For Experiential Learning

2011· article· en· W2125032964 on OpenAlex
Emin Çivi, Elif S. Persinger

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

VenueAmerican Journal of Business Education (AJBE) · 2011
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Marketing Education
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsExperiential learningCompetition (biology)MarketingVariety (cybernetics)AmbiguityPlan (archaeology)MemorizationPsychologyMathematics educationComputer scienceBusinessArtificial intelligence

Abstract

fetched live from OpenAlex

Many students find traditional lectures, routine memorization, and restatement of facts and terms tedious and boring (Munoz and Huser, 2008). This requires professors to employ a variety of teaching techniques, for example, live case classroom projects. Such an experiential learning opportunity encourages students to become involved with the materials they are attempting to learn by requiring them to apply theory to real-life situations where ambiguity, change, and risk exist (Lewis and Williams, 1994). This paper presents an assessment of a semester long marketing plan competition, which was incorporated into the Marketing Management Course. The competition required all student teams to deal with the assigned client and compete with each other to produce the winning marketing plan. Student feedbacks indicated they enjoyed the experiential learning opportunity and the competition format.

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)0.001
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.777
Threshold uncertainty score0.684

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.235
Teacher spread0.217 · 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