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Record W2623903396 · doi:10.5430/ijhe.v6n3p147

University Pedagogy: A New Culture is Emerging in Greek Higher Education

2017· article· en· W2623903396 on OpenAlexvenueno aff
Katerina Kedraka, Georgia Rotidi

Bibliographic record

VenueInternational Journal of Higher Education · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicReflective Practices in Education
Canadian institutionsnot available
Fundersnot available
KeywordsExcellenceHigher educationPedagogySociologyElement (criminal law)Reflection (computer programming)Political scienceEngineering ethicsMathematics educationPsychologyEngineeringComputer science

Abstract

fetched live from OpenAlex

The aim of this paper is to highlight University Pedagogy as a field that focuses on academics’ teaching role in Greek higher education. EU has recognized the need of improvement of the teaching skills of academics and urges the member states to recognize them as an important element of their professional profile. Only recently academics in Greece have launched the debate on innovative teaching and learning methods and practices. A Symposium that took place in 2016 and a significant empirical research are presented, because they are considered to mark the beginning of an emerging university culture, which incorporates the concern on teaching and learning excellence within higher education approaches in our country. The results of these initiatives indicate that critical self-reflection on teaching can lead to the transformation and to the adoption of alternative teaching practices, since the critically reflective process is a crucial point for the enhancement of an academic’s pedagogical, curricular and instructional knowledge.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0050.022
Scholarly communication0.0150.008
Open science0.0010.010
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0020.000

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 head0.042
GPT teacher head0.472
Teacher spread0.430 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations25
Published2017
Admission routes1
Has abstractyes

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