MétaCan
Menu
Back to cohort
Record W4289516490 · doi:10.3998/ticker.2931

"The Da Vinci Code for IP Research": Case Study of a Course-Integrated Educational Escape Room for Entrepreneurship Education

2022· article· en· W4289516490 on OpenAlexvenueno aff
Sarah Hartman‐Caverly

Bibliographic record

VenueTicker The Academic Business Librarianship Review · 2022
Typearticle
Languageen
FieldPsychology
TopicEducational Games and Gamification
Canadian institutionsnot available
FundersPennsylvania State UniversityCentre of Excellence for Environmental Decisions, Australian Research CouncilUniversity of Pennsylvania
KeywordsMindsetEntrepreneurshipEnthusiasmInformation literacyScholarshipPedagogyPsychologyComputer scienceMathematics educationSociologyKnowledge managementBusinessPolitical science

Abstract

fetched live from OpenAlex

Educational escape rooms can engage students in the development of information literacy skills while interacting with information formats and environments authentic to their disciplines. In business and entrepreneurship education, escape rooms offer the additional benefit of developing the characteristics of the entrepreneurial mindset, such as adaptive thinking, problem solving, enthusiasm, and decisiveness. This case study explores game-based learning for library instruction in entrepreneurship education. Using Eukel and Morrell’s (2021) escape room design cycle as a framework, it analyzes the development, testing, implementation, and results of an original escape room, Exfiltration! A Competitive Intelligence Virtual Escape Room, implemented as a course-integrated information literacy learning activity in an upper-level undergraduate new venture creation course. Limitations of the escape room are identified, and opportunities for iterative improvement are described. Recent scholarship on the application of entrepreneurial mindset, business research competencies, gamification, escape room pedagogy, and escape rooms in library instruction is discussed. This case study responds to the call from Taraldsen et al. (2020) for more small-scale studies of educational escape rooms outside of the STEM and health science disciplines.

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)0.005
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.682
Threshold uncertainty score0.938

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.002
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)0.0010.000

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 head0.186
GPT teacher head0.450
Teacher spread0.264 · 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 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

Citations2
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueTicker The Academic Business Librarianship ReviewSame topicEducational Games and GamificationFrench-language works237,207