The Effect of Digital Learning on the Academic Achievement and Motivation of Natural Sciences Learners: A Case Study of a South African Independent School
Bibliographic record
Abstract
The South African basic education system is characterized by inadequate learner performance in science as a result of the provision of limited opportunities for learner-centred instruction. Digital resources can be used in science classrooms to enhance learner engagement and motivation. Digital resources include interactive game-based applications that can be used in online learning environments. This study examined the effect of digital learning on the academic achievement and motivation of grade 9 Natural Sciences learners in a South African independent school. The empirical investigation adopted a mixed method approach as part of a quasi-experimental design. Quantitative data was collected through the administration of questionnaires while qualitative data was collected through semi-structured interviews. A questionnaire based on the Skeletal System and a motivation questionnaire were administered as pre-tests and post-tests to establish the effectiveness of the use of digital resources as an instructional intervention on the academic achievement and motivation of grade 9 Natural Sciences learners. The empirical investigation is underpinned by the Cultural Historical Activity Theory as the underlying theoretical framework. Key findings revealed significant difference between the pre-test and post-test scores as a result of the use of digital resources as an instructional intervention. Theoretical implications for technology-enhanced teaching and learning are discussed.
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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 | 0.004 | 0.001 |
| 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 | 0.001 |
| 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 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".