Bibliographic record
Abstract
New technology, like the internet and cellphones, play a significant role in adolescents’ lives today, and this role is rapidly growing, transforming adolescents’ everyday lives in profound ways. Adolescents all over the world use new technology and their numbers are still rising. Some adolescents, particularly in South Africa, have, however, hardly been touched by new technology. This could be ascribed to a lack of interest, understanding or opportunity. It is important to understand the digital divide in South Africa before one can begin to understand the role of interactive media (e.g. computers, video games, educational software, the internet and cellphones) in adolescents’ lives. The article provides a review and theoretical background of matters such as how many adolescents have access to the internet, where they are likely to get it, and what effects exposure to digital media have. The research was conducted with the objective to investigate the relationship between the digital divide and digital technologies (including the internet and cellphones) and their use by South African adolescents. The article also attempts to investigate the extent to which South African adolescents engage in online activities that can involve risks, awareness of (parents and secondary schools) and competencies to address the challenges adolescents face online. The method used in this study was content analysis of previously published material, and evaluation of this material provides an understanding of the progress of research in clarifying the current problem of digital divide. An historical overview is relevant to consider in implementing programmes in digital and media literacy. Findings indicate that new forms of digital media are well positioned to play a constructive role in advancing powerful solutions to national educational challenges. Schools must determine what they want learners to experience and learn from their use of new technology so that they are empowered to take control of this powerful new tool in their lives. This article highlights the need for digital media literacy programmes in South African schools that adequately prepare learners for the complex and dynamic life of the 21st century.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".