Chronicles of Change: The Narrative Turn and E-Learning Research
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
Narrative case research has been widely utilized in educational inquiry to investigate different and changing positions and perspectives on questions of identity, curriculum and classroom practice. Despite the fact that case-study research of this kind is well suited to the investigation of changing technologies and their interpretation in different classroom settings, narrative methods have been little utilized in e-learning research. This article addresses this situation first of all by presenting psychologist Jerome Bruner's understanding of narrative as both a pervasive mode of cognition and a formal mode of inquiry – a dual emphasis that is central to understanding narrative as a research method. It then describes the elicitation of an individual teacher's narrative in an ‘active interview’ context, and presents her account of the adaptation of blog technology in a writing class. The article examines the ways in which teacher and technology are presented as agents of change in this narrative, and compares this to other, more common but less explicitly ‘narrative’ accounts in e-learning research. In doing so, the article makes significant reference to Jean-Francois Lyotard's notion of ‘meta-narratives’, arguing that that the overarching meta-narrative of technological progress still informs a great deal of research in e-learning. It concludes by making the case that the influence of this particular meta-narrative should be balanced by attention to multiple ‘micro-narratives’, which tend to tell rather different stories.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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