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AI and the Sense of Learner Identity for Generation Z

2025· article· W4415923878 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

VenueREVISTA PARAGUAYA DE EDUCACIÓN A DISTANCIA (REPED) · 2025
Typearticle
Language
FieldSocial Sciences
TopicGenerational Differences and Trends
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPersonaIdentity (music)CreativityTransactional leadershipExploratory researchHigher education

Abstract

fetched live from OpenAlex

Generation Z seems both transactional and more of a consumer than an engaged, adaptive, resilient or exploratory learner. Their persona is strongly tied to their understanding that learning leads to jobs. Their use of AI and related technologies is strongly linked to this persona, and this is also their rationale for using AI for "cheating." Higher education is about more than consumption. It is about personal growth and development, adaptability, creativity and imagination. It is about what the Japanese call Ikigai. This paper explores the personas at play in higher education, the nature of Ikigai, and the changes that are needed to shift Generation Z to adopt a broader understanding of the purpose of their education and strengthen their Ikigai.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.763
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
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 head0.021
GPT teacher head0.352
Teacher spread0.331 · 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