Tablet PCs and reconceptualizing learning with technology: a case study in higher education
Bibliographic record
Abstract
Purpose This study aims to examine the experience of 31 university students who were issued tablet PCs for their use during an academic year. The primary research problem which drove this project revolved around the student perceptions of the benefits of technology to provide opportunities to restructure their learning experiences. Design/methodology/approach The students were surveyed twice during the year and they were invited to participate in either individual interviews or a series of focus groups. A number of lectures were also visited and observed. The survey results provided quantitative data regarding student usage of the technology. The interviews, focus groups and observed classes provided data around the reasons why the students used the technology in the ways they did. Findings Little evidence was found to support a contention that meaningful learning with technology had occurred and, in spite of their comfort and familiarity with the technology, there is no evidence of changing attitudes with respect to meaningful learning on the part of the students surveyed in this study. Research limitations/implications A major application of this should be directed towards similar studies focused on combining the redefinition usage potential of new touch interface‐driven devices, such as the iPad, with a new pedagogical approaches to support learners to use the technology as cognitive tools. Originality/value It is important to note that the introduction of a new technology, even if it makes a wide variety of affordances available for use, cannot by itself, instigate redefinition of learning tasks to allow for meaningful learning to occur.
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 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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".