Are Students Ready to Adopt E-Portfolio? Social Science and Humanities Context
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".