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Record W4399331747 · doi:10.1177/10525629241256317

Impact of Connectivism on Knowledge and Willingness of Students in Higher Education

2024· article· en· W4399331747 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueOrganizational Behavior Teaching Review · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education and Employability
Canadian institutionsThompson Rivers University
Fundersnot available
KeywordsConnectivismHigher educationPsychologyWillingness to communicatePedagogyMedical educationSociologySocial psychologyPolitical scienceLearning theory

Abstract

fetched live from OpenAlex

This study investigates the impact of connectivism on knowledge acquisition and the willingness of higher education students to apply that knowledge in practical settings. Using an experimental design, it investigates how connectivism manifests in learning processes, particularly focusing on a collaborative online international session (COIL) with 92 business management students from the UAE and South Korea. These students participated in a COIL session aimed at enhancing their understanding of diversity and inclusion management concepts. The study utilized an independent t-test to evaluate the effectiveness of COIL, comparing groups exposed to different modes of participation (connectivism mode and nonconnectivism mode). The results highlight connectivism’s role in increasing students’ willingness to utilize acquired knowledge. As a connectivism approach, COIL proves pivotal in applying learning practically. This research offers significant insights for curriculum designers, educators, and scholars, demonstrating the impact of social connectivism on learning enhancement. It provides valuable information for incorporating connectivism into traditional educational models, thereby enriching the theoretical and methodological understanding of the relationship between connectivism, COIL, knowledge acquisition, and application willingness. This study is particularly relevant for educators looking to integrate innovative methods in their teaching and expand the scope of knowledge and skill development for future 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.

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 score0.037
Threshold uncertainty score0.893

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.048
GPT teacher head0.455
Teacher spread0.406 · 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