Text-Based Video: The Effectiveness of Learning Math in Higher Education Through Videos and Texts
Why this work is in the frame
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Bibliographic record
Abstract
The Text-Based Video (TBV) model is a particular case of the more general Video-Based Learning (VBL) model in which an instructor’s curriculum is fully covered by high-quality videos and texts. The aim of this study is to test the effectiveness of the TBV model by examining and comparing its two main components: Videos and texts. The model is based on the creation of high-quality texts which form the basis for high-quality video clips. It is designed to improve learning in quantitative courses in higher education. The research was based on a sample of students  who enrolled in the course Mathematics for Business Administration at the Neri Bloomfield School of Design and Education, Haifa, Israel that was based on the TBV model. The course was given during the five academic years 2016-2021 using different teaching formats: face-to-face learning, distance learning and blended learning. Learners were asked to answer an online questionnaire that assessed the characteristics and advantages/disadvantages of TBV. The findings show that although students preferred watching videos based on texts over reading those texts alone, students opined that the combination of video and text was by far the most effective instructional method. All results were identical regardless of whether face-to-face, distance or blended learning was used.
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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 | 0.002 | 0.002 |
| 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