MétaCan
Menu
Back to cohort
Record W2989073263 · doi:10.5539/elt.v12n12p12

A Case Study of Project-based English Learning Experience in a Simulated Business Context

2019· article· en· W2989073263 on OpenAlexvenueno aff
Yi-Ching Huang, Hsin‐Yi Cyndi Huang

Bibliographic record

VenueEnglish Language Teaching · 2019
Typearticle
Languageen
FieldComputer Science
TopicSoftware Engineering Techniques and Practices
Canadian institutionsnot available
Fundersnot available
KeywordsBusiness EnglishContext (archaeology)PsychologyApprenticeshipBusiness planTeamworkProject-based learningWork (physics)Medical educationPedagogyMarketingManagementEngineeringBusiness

Abstract

fetched live from OpenAlex

Simulation technique could be effective if it is cleverly manipulated and incorporated in a project-based learning context. This current study aims to explore students’ learning experience in a project-based simulated business context. The participants were 51 second and third year students who took Business English as an elective course at a private university in central Taiwan. In the project, the participants modeled an episode in a reality TV show, The Apprentice, and tried to plan their projects of selling beverages to the students on campus using English. The students were engaged in the whole process from initial project planning to the final oral report of presenting their selling strategies. The results from the participants’ questionnaire responses and interview data revealed that they felt the course was more motivating, interactive and practical than traditional business course. It is also suggested that this simulated business project provide students with opportunities for social interaction and a psychologically safe team environment to work collaboratively, which both contributed the development in synergistic knowledge.

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)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation 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 score0.294
Threshold uncertainty score0.762

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
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 science0.0010.000
Research integrity0.0000.001
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 head0.019
GPT teacher head0.298
Teacher spread0.279 · 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 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

Citations3
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueEnglish Language TeachingSame topicSoftware Engineering Techniques and PracticesFrench-language works237,207