Not just digital natives: Integrating technologies in professional education contexts
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In 2001, Prensky characterised a new generation of learners entering higher education as digital natives – naturally digitally literate and inherently proficient users of technology. While many educational technology researchers have long argued for the need to move beyond the digital native assumptions proposed by Prensky and other futurists, a critical review of the literature reveals that this concept remains influential in academia broadly and within professional education specifically. In light of this, we propose an alternative approach to technology integration in professional education settings that aims to avoid unhelpful digital native stereotypes by instead developing digital literacies in ways that leverage technological affordances. By building digital literacies across the procedural and technical, cognitive, and sociocultural domains connected to professional competencies, learners can effectively adopt and utilise emerging technologies through professional digital practices.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 it