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Record W1515565693 · doi:10.5539/ass.v11n13p269

Are Students Ready to Adopt E-Portfolio? Social Science and Humanities Context

2015· article· en· W1515565693 on OpenAlexvenueno aff
Syamsul Nor Azlan Mohamad, Mohamed Amin Embi, Norazah Nordin

Bibliographic record

VenueAsian Social Science · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicReflective Practices in Education
Canadian institutionsnot available
Fundersnot available
KeywordsCronbach's alphaPortfolioEmployabilityCourseworkContext (archaeology)Mathematics educationPsychologyVariety (cybernetics)PedagogyKnowledge managementComputer scienceBusinessPsychometrics

Abstract

fetched live from OpenAlex

This paper presents the learners readiness towards the implementation of E-Portfolio as means of solving the persistent problems in educational setting. The purpose of the study was to examine the learner’s readiness towards the implementation E-Portfolio in higher education. Initially, this paper was conducted a study with a total number of 300 students form Social Sciences and Humanites cluster and then practicing portfolio in their coursework. The pilot study was conducted and showed the reliability coefficient with Cronbach’s alpha () is 0.825. The instrument was divided into five components which involved (1) technology accessibility (2) online skills and relationship (3) motivation (4) internet discussion and (5) importance to success, to measure the learners’ readiness. The findings were reported that students are ready to have an E-Portfolio as a learning tool in constructing their knowledge and experience of learning. The E-Portfolio will extend the opportunity from paper-based into the electronic based with a variety of online learning features in gaining students interest and motivation in learning. At the end of the day, the E-Portfolio will not only benefit the students and the faculty but also towards the employability.

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 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)0.007
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.747
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0060.008
Scholarly communication0.0010.003
Open science0.0020.000
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 head0.114
GPT teacher head0.462
Teacher spread0.348 · 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; both teacher heads agree on what is shown here.

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

Citations13
Published2015
Admission routes1
Has abstractyes

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