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Record W1779112980 · doi:10.2478/eurodl-2014-0013

The Temporal Perspective in Higher Education Learners: Comparisons Between Online and Onsite Learning

2014· article· en· W1779112980 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

VenueEuropean Journal of Open Distance and E-Learning · 2014
Typearticle
Languageen
FieldPsychology
TopicPsychological and Temporal Perspectives Research
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsFlexibility (engineering)CatalanPerspective (graphical)PreferenceOnline learningDropout (neural networks)Context (archaeology)PsychologyMathematics educationPopulationOrientation (vector space)E learningComputer scienceMultimediaEducational technologySociologyMathematicsGeographyStatisticsArtificial intelligenceHumanities

Abstract

fetched live from OpenAlex

Higher Education increases flexibility with online learning solutions. Nevertheless, dropout rates in online university are large. Among the reasons, one aspect deserving further study is students’ Time Perspective (TP), which has been studied in onsite HE. It is necessary to know the TP profile of the growing population of online students, and consider its relation with students’ preference and convenience factors for choosing online or onsite contexts. In this study, learners’ TP in an online and an onsite Catalan HE institutions are compared. Results show that HE students present a high future orientation in general, while online students showed a higher orientation to past negativism. Basic guides are given to help institutions and students in the choice of the better suited learning context according to their TP.

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)0.003
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 score0.233
Threshold uncertainty score0.775

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
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 integrity0.0000.002
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 head0.104
GPT teacher head0.406
Teacher spread0.302 · 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