Urban adolescent students and technology: access, use and interest in learning language and literacy
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
Adolescents today have vastly different opportunities to learn and process information via pervasive digital technologies and social media. However, there is scant literature on the impact of these technologies on urban adolescents with lower socioeconomic status. This study of 531 urban students in grades 6–8 used a self-reported survey to collect information about (1) students' access to and frequency of using desktop, laptop and tablet computers, and mobile phones, (2) their ownership of mp3 players, iPods, touch pads, cellphones, and smartphones, (3) whether they had accounts with any of 10 communication and social media platforms, and (4) their interest in using Facebook, Twitter, YouTube, and text messaging for language and literacy learning purposes. Students reported significantly more access to these technologies at home than school. Grade 8 students had the most access to cellphones and laptop computers, and were most likely to own smartphones. English language learners indicated a significantly higher interest in using social media for language and literacy learning than their native English-speaking peers. The results indicate a great potential to integrate technology strategically with language instruction for urban adolescent students with linguistically diverse backgrounds. The educational implications of these findings are discussed.
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.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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