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Record W3153799352 · doi:10.5430/ijhe.v10n4p268

Education for Sustainable Development: A Qualitative Analytical Study on the Impact of the Jordanian Universities’ Role in Supporting Innovation among University Students

2021· article· en· W3153799352 on OpenAlexvenueno aff
Amani Jarrar

Bibliographic record

VenueInternational Journal of Higher Education · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicDiverse Educational Innovations Studies
Canadian institutionsnot available
Fundersnot available
KeywordsGrounded theoryContext (archaeology)SociologySustainable developmentQualitative researchPopulationMathematics educationHigher educationPedagogyPsychologyPolitical scienceSocial scienceGeography

Abstract

fetched live from OpenAlex

This study aimed at exploring and theorizing the role of Jordanian Universities in supporting innovation among university students within the context of education for sustainable development from the point of view of Jordanian University students. For that, the researcher adopted the grounded theory methodology by Strauss and Corbin. The study was conducted at two Jordanian Universities: the University of Jordan and Philadelphia University in the academic year (2019-2020), and the study population consisted of students from the two universities. The researcher chose (300) students from both genders from different faculties and academic years. By applying the grounded theory, the study concluded that the key category that emerged after analyzing the student’s responses describing the impact of the Jordanian Universities’ role in supporting innovation among university students for educational sustainable development is the emphasis on the need for developing proper University innovation ecosystems in their educational systems. Also, the respondents- through online interviews - have emphasized this concept of proper University innovation ecosystems. The key category of this study found that positive and negative impacts could result from applying or neglecting to apply this concept, which generated behaviors toward the concept, which could be considered as the phenomena in the current research.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.305
Threshold uncertainty score0.238

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 head0.037
GPT teacher head0.384
Teacher spread0.348 · 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

Citations2
Published2021
Admission routes1
Has abstractyes

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