MétaCan
Menu
Back to cohort
Record W4392856664 · doi:10.34190/ejkm.22.1.3258

Critical Aspects of a Higher Education Reform for Continuous Lifelong Learning Opportunities in a Digital Era

2024· article· en· W4392856664 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

VenueElectronic Journal of Knowledge Management · 2024
Typearticle
Languageen
FieldComputer Science
TopicEducational Innovations and Challenges
Canadian institutionsAthabasca University
Fundersnot available
KeywordsLifelong learningDigital learningPolitical scienceMathematics educationPsychologyPedagogy

Abstract

fetched live from OpenAlex

In the knowledge society today, there is a strong need for providing continuous lifelong learning opportunities. Recently, the Covid-19 pandemic has acted as a catalyst for technology enhanced learning, involving new challenges for higher education. The main focus for this study has been the ongoing reform of higher education for providing lifelong learning opportunities. This study is the second phase of a Delphi study on higher education reform. Data were gathered by email interviews with an expert panel, where all respondents have genuine knowledge in the field of technology enhanced lifelong learning. The interview answers were analysed according to the Grounded Theory concepts of open coding and axial coding. The central main category for the axial coding was ‘Higher education reform for the provision of lifelong learning opportunities. This category was later found to be dependent on ‘Infrastructure’, ‘Multimodal delivery’, ‘Pedagogical change’, ‘Financial aspects’, and ‘Quality and organisation’, ‘Digital literacy’, ‘Accessibility’, and ‘Equity, diversity and inclusion’.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.886
Threshold uncertainty score0.310

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 communication0.0000.001
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 head0.030
GPT teacher head0.320
Teacher spread0.289 · 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