Impact of blended learning approach on students’ achievement and mental effort
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.
Bibliographic record
Abstract
Most researchers are interested in investigating the impact of a blended learning approach (BLA) on students’ performance, yet this approach’s instructional efficiency has not yet been quantified. Therefore, this research aims to determine the impact of teacher-created online Moodle-based materials in combination with face-to-face learning on student achievement and mental effort, that is, to determine the instructional efficiency of applied teaching approaches at physics classes in high school. For this research, we chose to teach students physical principles of direct current, which involves abstract concepts. Using BLA, students can prepare better for a real experiments in the lab, and this approach also creates a safe environment for students while allowing them to demonstrate the learned physical phenomena. The Moodle platform course is developed for this purpose and implemented in a BLA environment. Students are gradually guided from easier to more difficult concepts in this research, considering the working memory’s capacity and the teaching material requirements. Our results show that the students who used BLA achieved higher scores on the knowledge test, and they also used less mental effort than students that used a conventional teaching approach. We also show that instructional efficiency for BLA is positive and significantly higher than the instructional efficiency of the conventional approach. This research’s results are primarily designed for physics teachers to better understand the effects of the BLA and apply teaching approaches that respect the principles of children’s cognitive development.
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 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 | 0.000 |
| 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) | 0.000 | 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 it