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Record W2327441702 · doi:10.24059/olj.v8i3.1822

EXPERIMENTAL ONLINE CASE STUDY FOR A BREAKTHROUGH IN STUDENT ENGAGEMENT: FOCUS GROUP RESULTS

2019· article· en· W2327441702 on OpenAlexaboutno aff
James M. Theroux, Cari Carpenter, Clare Kilbane

Bibliographic record

VenueOnline Learning · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Marketing Education
Canadian institutionsnot available
Fundersnot available
KeywordsFocus groupInteractivitySubject (documents)Student engagementThe InternetFocus (optics)Process (computing)PsychologyPublic relationsMathematics educationComputer scienceMarketingBusinessMultimediaWorld Wide WebPolitical science

Abstract

fetched live from OpenAlex

A new type of case study, called the real-time case (RTC), was produced in the fall of 2001 and distributed via the Internet to business classes at four universities in the US and Canada. The real-time case presented the story of one company's growth and development throughout a 14-week semester. A case writer stationed full-time at the subject company published case installments weekly on the Web, allowing students to view the company-building process as it happened. The 14-week coverage of RTC enabled students to study the subject company in unprecedented depth and detail. RTC's real-time interactivity allowed students to share their analyses and best thinking with the company leadership during the company’s decision-making process.A major objective in producing the case was to heighten student engagement with the case material. To evaluate whether this objective was achieved, a survey and a focus group discussion were conducted with one of the participating MBA classes. Results from the survey and the focus group showed a high degree of engagement, plus many other benefits from the new type of case study.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.022
metaresearch head score (Gemma)0.043
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.115

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.043
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0050.002
Scholarly communication0.0020.003
Open science0.0030.004
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0140.003

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 head0.028
GPT teacher head0.327
Teacher spread0.299 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

Citations7
Published2019
Admission routes1
Has abstractyes

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