Towards narrative-centred digital texts for advanced second language learners
Bibliographic record
Abstract
Recently, there has been a steady influx of language development software and games intended for use both at home and in the classroom. Although some of these technologies are effective for language learners to develop certain skills such as sight word recognition, many of them lack aspects of advanced level literacy such as expanded narrative and character development, which can allow for higher cognitive function and thus greater language mastery. While recent research emphasizes the pedagogical possibilities for video games and interactive fiction when teaching basic L1 literacy and literature respectively (Simanowski, Schäfer and Gendolla, 2010; Beavis, O’Mara and McNeice, 2012), this paper makes the argument that similar texts and media can help advanced L2 language learners further develop a knowledge of figurative, culturally imbued language which they could analyze and substantiate in relatively autonomous environments. Furthermore, these digital texts function as dynamic, pedagogical tools that can elicit critical technological literacy, a skill that is ever more crucial in our increasingly mediatised and technological age.
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 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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".