Does Perceived Ease of Use Mitigate Computer Anxiety and Stimulate Self-regulated Learning for Pre-Service Teacher Students?
Bibliographic record
Abstract
The aim of this study is to contribute to a better understanding of challenges and factors which influence learning efficiency with electronic-portfolios. Based on the Technology Acceptance Model (TAM; Davis, Bagozzi, & Warshaw, 1989) we analyzed external variables (e.g., computer-anxiety) that influence technology acceptance and the actual system use in form of self-regulated learning. Additionally we included computer related attitudes and correlated them with external variables as well as measures of self-regulated learning. To foster learning efficacy with electronic portfolios the program Microsoft OneNote was used. A group of N = 32 preservice teachers worked on an electronic-portfolio in OneNote for 14 weeks.Results showed that computer-anxiety and the challenge of working with an electronic portfolio decreased over time. The more the computer was rated as a useful tool for learning and teaching, the less computer-anxiety, the more challenge and interest and better mood students reported. In contrast the more the computer was seen as uninfluential tool for working and learning, the more computer anxiety, hopelessness, anxiety and less positive mood, interest and joy to work on the electronic-portfolio has been reported. So, students’ computer related attitudes should be considered when working with an electronic-portfolio to better tailor instruction to learner needs.
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.
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 | 0.000 | 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 | 0.001 |
| Open science | 0.001 | 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".