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Record W4402752997 · doi:10.5539/jel.v14n1p115

Entrepreneurial Intention in High School: Systematic Literature Review of the Period 2000–2022

2024· article· en· W4402752997 on OpenAlexvenueno aff
Marly Aparecida Machado Angelo, Elzo Alves Aranha

Bibliographic record

VenueJournal of Education and Learning · 2024
Typearticle
Languageen
FieldComputer Science
TopicEducational Innovations and Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsPeriod (music)PsychologyMathematics educationHigher educationPedagogySocial psychologyPolitical science

Abstract

fetched live from OpenAlex

Researchers have devote little attention to exploring entrepreneurial intention (EI) in high school education. The lack of academic papers that seek to analyze the state of academic production of EI in high school education opens a gap in the academic literature. This study aims to analyze the academic production of EI in high school in the period 2000–2022, adopting the systematic literature review. The study is descriptive, quantitative and exploratory in nature, using the Scopus, Web of Science and ERIC databases and the Bibliometrix tool. After using the screening protocol 33 articles were selected for analysis. One of the main findings of the study is the mapping of four thematic lines: a) testing conceptual model of EI; b) influence of different factors on the EI of high school students; c) EI can be studied using different constructs; d) validation of the EI questionnaire. The findings are innovative and contribute to filling a gap in the academic literature. The results have many practical implications. For example: a) high school principals, coordinators and teachers can use the results to stimulate reflection on the centrality of the student in the teaching and learning processes, aiming to develop entrepreneurial competencies and skills; b) thematic lines could help in buiding a research agenda with several research avenues.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.601
Threshold uncertainty score0.155

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0000.000
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 head0.012
GPT teacher head0.287
Teacher spread0.275 · 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 designSystematic review
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
Published2024
Admission routes1
Has abstractyes

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