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Record W4407935700 · doi:10.19173/irrodl.v26i1.8106

Comparative Effectiveness of Approaches to Students’ Labour Education in Universities in the New Era With the Use of Information Technologies

2025· article· en· W4407935700 on OpenAlexvenueno aff
Ting Xu

Bibliographic record

VenueThe International Review of Research in Open and Distributed Learning · 2025
Typearticle
Languageen
FieldComputer Science
TopicEducational Innovations and Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsInformation technologyHigher educationEducational technologyElectronic learningSociologyPedagogyMathematics educationMedical educationComputer scienceKnowledge managementPsychologyEconomic growthMedicineEconomics

Abstract

fetched live from OpenAlex

This study aimed to identify and compare the efficiency of different theoretical (competence-oriented) and practical (system-activity) approaches to labour education of college students in China using the Open edX online learning platform. The study was conducted at the Shengda College of Economics and Business Management. It involved 150 first-year college students and two full-time teacher-employees from the Labour Protection Department who had responsibility to ensure the quality of labour education and supervise the process of its introduction. The practical approach was 75% more effective when college students were allowed to choose work according to their preferences. The study showed that the practical approach decreased students’ motivation to work by 3%, while the average motivation with a theoretical approach was 45% higher than with a practical one, due to lack of physical work and exhaustion at work.

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)0.003
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.945
Threshold uncertainty score0.251

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.207
GPT teacher head0.450
Teacher spread0.243 · 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 designTheoretical or conceptual
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

Citations0
Published2025
Admission routes1
Has abstractyes

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