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A Literature Review of Higher Education Reform and Lifelong Learning in a Digital Era

2020· review· en· W3125681345 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

VenueEDEN Conference Proceedings · 2020
Typereview
Languageen
FieldSocial Sciences
TopicHigher Education Learning Practices
Canadian institutionsAthabasca University
Fundersnot available
KeywordsLifelong learningEmployabilityHigher educationCompetition (biology)Selection (genetic algorithm)PedagogyPolitical scienceSociologyComputer science

Abstract

fetched live from OpenAlex

Policy documents have long emphasized lifelong learning, social development, global competition and employability. At the same time, how higher education needs to be transformed to meet this demand for creating opportunities for lifelong learning is an important issue. This study seeks to take on the literature through the exploration of two main constructs: lifelong learning and higher education reform, answering the question of which key themes of lifelong learning, if any, are emerging in higher education reforms. Using a systematic review of relevant, foundational, and current published literature on lifelong learning and higher education reform, the twostep selection of the publications is presented. Key themes are discussed as well as next steps in the continued study with the systematic literature review in which selected articles will be read by and expert panel. How lifelong learning and higher education reform can create a diverse higher education system which will address diverse students and required competencies in diverse, dynamic societies will be of importance for future study.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.884
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.051
GPT teacher head0.398
Teacher spread0.347 · 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