Nontraditional Students’ Perceptions and Experiences Using Technology in a Teacher Preparation Program
Bibliographic record
Abstract
AbstractTechnology integration is a key part of a 2-year teacher education program at the Canadian university; nontraditional students seemed unprepared to use technology for learning. The purpose of this study was to investigate nontraditional students’ perceptions and experiences about their successes and challenges using technology in the program. The study was guided by Knowles’s andragogy theory, which presents a learner-centred perspective on adult learning. The research questions focused on nontraditional students’ successes and challenges using technology in coursework. A basic qualitative design was used to capture the insights of 10 purposefully selected, nontraditional university students through semistructured interviews. Themes were identified through open coding. The trustworthiness of the study was established through member checking, rich and detailed descriptions, and research reflexivity. The findings revealed that nontraditional students, especially at the start of the program, encountered difficulties learning to use new technology tools, experienced technology user unfriendliness, and struggled with a shift to online learning. The findings also showed that nontraditional students developed technology self-efficacy as they progressed through the program, aiding them in applying educational technology tools. The successes have been attributed to personal, instructor, and institutional factors as well as peer support. A white paper was developed with suggestions for streamlining the learning management system and technology tools, offering peer mentoring, enhancing technology training, and allowing extra time for technology practice. The implications for positive social change included providing insights for improving nontraditional students’ learning experiences and those of their future students.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".