Digital Narrative and the Humanities: An Evaluation of the Use of Digital Storytelling in an Australian Undergraduate Literary Studies Program
Bibliographic record
Abstract
A growing number of university teachers advocate the benefits of multimedia and digital technologies in their classrooms. Such technologies are promoted: as a means to ensure the relevance of subject disciplines; and, as tools of engagement to assist students to meet their learning outcomes. Digital storytelling or narration is one example of how educators can utilise technology to introduce innovative teaching methods. In its broadest sense, digital narration involves using digital resources in learning environments for the production by students of multimedia narratives. This paper reports on the results, over a two-year period, of an evaluation of the use of digital narratives in an advanced undergraduate unit on contemporary Australian literature in one Australian university. The evaluation explored students’ and the teacher’s experiences of digital storytelling. In particular, it examined participants’ satisfaction with and anxieties about the use of digital narratives. It also considered the issues that the use of digital narratives raises vis-à-vis the constructive alignment with the themes, aims, and objectives of the unit, as well as the kinds and levels of technical training and assistance required to support students and staff. The results of this evaluation will be of interest to academics considering the use of multimedia technologies in their undergraduate classes.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| 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".