Designing E-Portfolio with ARCS Motivational Design Strategies to Enhance Self-Directed Learning
Bibliographic record
Abstract
<p>This paper presents the instructional design effect on motivation towards the implementation of e-Portfolio with ARCS Motivational design strategies to enhance self-directed learning. The purpose of the study was to examine the learners’ motivation level after the implementation of e-Portfolio. Initially, this paper was conducted to study a total number of twenty-four students as a small group evaluation. The survey instrument was divided into four subscales which involved (1) attention, (2) relevance, (3) confidence, and (4) satisfaction to measure the motivation subscales among learners. The findings reported that learners’ motivation has a significant effect to create a desire and awareness in constructing, developing and exploring their knowledge. The e-Portfolio with ARCS motivational design strategies will enforce the learner in gaining their interest in learning. The integration of e-Portfolio and ARCS motivational design strategies will create an opportunity to enhance the transmission and instruction approach in teaching and learning for higher education environment.</p>
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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 teacher head, 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".