A Mixed-Methods Study of Secondary Student and Teacher Attitudes towards Mobile Education Apps in Lagos
Bibliographic record
Abstract
With the advent of smartphones, laptops, and other various portable devices, the ability to incorporate technology into the classroom has increased dramatically in the last few decades. This study evaluates the perceptions and attitudes of both students and teachers in relation to mobile apps that assist in classroom learning. The research used a mixed-methods approach that collected demographic information and conducted qualitative interviews to determine the perceptions of mobile apps to students and teachers. Cross-sectional data was collected from participants and analyzed for associations. 43 students and 6 teachers were recruited and interviewed. The participants were asked about their thoughts on mobile educational apps, and their interviews were audio recorded and transcribed. Inductive thematic analysis was used to analyze the data and 5 themes were identified for students: barriers to educational app adoption, barriers to continued use of education apps, tracking progress, tracking of progress, and goal setting. For teachers, themes identified included factors to mobile app use, and criteria used for mobile app selection. These findings may provide school boards and scientists with insights on how to best develop educational apps to fit the needs of students.
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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 | 0.003 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 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".