The Impact of the E-book on Levels of Bloom's Pyramid at ECT Students in Light of the Internal and External Motivation to Learn Mathematics and Statistics
Bibliographic record
Abstract
The purpose of the present study was to examine the effects of E-book of the Pyramid Bloom levels on the Emirates College of Technology (ECT) students at both internal and external motivation levels. The business statistics unit developed in two different methods. This study utilized the quasi experimental type methodology. The independent variables were the methods, traditional and E-book. The dependent variables were the Pyramid Bloom levels, which will be determined by the final mark on the post-test. The moderator variables are motivation levels, internal and external. The study sample consisted of 61 undergraduate ECT students, and were randomly selected, via simple random sample, from 127 students. ANOVA procedure was used to determine the significant differences of the pretest scores among the two methods. An analysis of covariance, ANCOVA, was carried out to examine the main effects of the independent variables on the dependent variables. The findings of this study showed that students who have learned through the E-book method achieve design efficiently better in their post-test scores than those in the traditional method. Students at the internal motivation level perform design efficiently better in their post-test scores than those at external motivation level. The E-book method proved to help students with external motivation in their post-test score motivation.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".