The Digital Native Debate in Higher Education: A Comparative Analysis of Recent Literature / Le débat sur les natifs du numérique dans l'enseignement supérieur: une analyse comparative de la littérature récente
Bibliographic record
Abstract
More than a decade after Prensky’s influential articulation of digital natives and immigrants, great disagreement exists around these characterizations of students and the impact of such notions within higher education. Perceptions of today’s undergraduate learners as tech-savvy “digital natives” (Prensky, 2001a), who both want and need the latest emerging technologies in all learning situations, continue to dominate the discourse in education technology research and practice. Popular yet largely unsubstantiated conceptions of digital natives are often embedded within the assumptions of contemporary research on student perceptions of emerging technologies, seemingly without regard for a growing body of evidence questioning such notions. In order to promote critical discussion in the higher education community considering potential directions for further research of these issues, especially within the Canadian context, the purpose of this review of recent literature is to analyze key themes emerging from contemporary research on the Net generation as digital natives. Plus d'une décennie après la célèbre distinction de Prensky entre les natifs et les immigrants du monde numérique, un désaccord important existe à propos de ces caractérisations des élèves et de leur impact dans l'enseignement supérieur. Le discours dominant dans la recherche et la pratique des technologies de l’éducation perpétue une représentation des étudiants d’aujourd’hui comme étant des «natifs du numérique» hautement qualifiés (Prensky, 2001a), désirant et requérant à la fois les dernières technologies dans toutes les situations d'apprentissage. Ces conceptions populaires mais controversées continuent à être au coeur de plusieurs hypothèses de la recherche contemporaine sur les perceptions des élèves à l’égard des nouvelles technologies, et ce, au mépris d’un nombre croissant de preuves contraires. Afin de promouvoir la discussion critique dans la communauté de l'enseignement supérieur, laquelle s’est engagée dans une réflexion sur les orientations possibles pour des recherches plus poussées sur ces questions, en particulier dans le contexte canadien, cette revue de la littérature récente a pour but d'analyser les principaux thèmes et problèmes issus de la recherche contemporaine sur la génération de l’Internet ou des natifs du monde numérique.
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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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.011 | 0.028 |
| Science and technology studies | 0.005 | 0.008 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".