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Record W3043177678 · doi:10.1177/2379298120933999

Mitigating Information Overload: An Experiential Exercise Using Role-Play to Illustrate and Differentiate Theories of Motivation

2020· article· en· W3043177678 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueManagement Teaching Review · 2020
Typearticle
Languageen
FieldPsychology
TopicMotivation and Self-Concept in Sports
Canadian institutionsHEC Montréal
FundersFonds de Recherche du Québec-Société et Culture
KeywordsExpectancy theorySession (web analytics)PsychologyDebriefingGoal theorySelf-determination theoryExperiential learningLearning theoryClass (philosophy)Mathematics educationSocial psychologyComputer scienceAutonomy

Abstract

fetched live from OpenAlex

Work motivation is a core component of many management courses. However, its effective teaching can be hampered by the fragmentation and seeming incoherence of the various theories of work motivation. To address this challenge, we describe an interactive role-play activity that induces students to synthesize, apply, and compare several theories of motivation. In the first part of the exercise, students work in small groups to prepare a role-play skit illustrating a specific theory of motivation. In the second part, groups present their role-play skits in front of the class, and the rest of the students try to determine which theories were performed. Next, the debriefing session encourages students to discuss, compare, and contrast the theories. Though the present exercise focuses on four theories—the hierarchy of needs, the two-factor theory, expectancy theory, and self-determination theory—the activity can be easily adapted to incorporate other models of motivation.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.737
Threshold uncertainty score0.606

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.029
GPT teacher head0.305
Teacher spread0.276 · 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