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Record W4362464344 · doi:10.5430/jct.v12n3p100

University Changes in the 4.0 Educational Era: A Study into Moroccan Students' Interests

2023· article· en· W4362464344 on OpenAlexvenueno aff
Najia Amini, Abdelhak Chakli, Fadwa Mahiri, Abderrahim Aassoul, Mohamed Radid

Bibliographic record

VenueJournal of Curriculum and Teaching · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education and Employability
Canadian institutionsnot available
Fundersnot available
KeywordsEmployabilityHigher educationPerceptionPsychologyPedagogyPolitical scienceSociologyMedical educationMathematics educationPublic relationsMedicine

Abstract

fetched live from OpenAlex

Faced with the challenges presented by the transition to Industry 4.0, deep and rapid transformation is required for higher education to meet the demands of the fourth industrial revolution. This article aims to investigate students' perceptions of various components of their academic ecosystem. our study is interested in examining the preferred teaching models, competencies, and fields of study that higher education should develop and national/international mobility. A questionnaire survey was conducted using a quantitative approach to collect students' perceptions; 97 students from Hassan 2 University participated in the study. The findings indicate that students are interested in blended learning, that they require programs to build their managerial and employability skills, that mobility is a fundamental element of education 4.0, and that its impact on employability development is recognized. The study enhances our understanding of higher education students' interactions within their university ecosystem. This study might be beneficial for policymakers and educational decision-makers in the transformation toward a university 4.0.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.730

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.024
GPT teacher head0.383
Teacher spread0.359 · 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 designObservational
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

Citations5
Published2023
Admission routes1
Has abstractyes

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