Learner-Created Podcasts: Fostering Information Literacies in a Writing Course
Bibliographic record
Abstract
This paper describes an experimental learner-created podcasting assignment in a first-year undergraduate research skills course for professional writers. The podcasting assignment serves as a contextualized experiential writing project that invites students to refine their research skills by participating in the invention of an emerging genre of radio storytelling. The power of the podcast assignment lies in the liminal space it creates for learners. It moves students beyond familiar and regimented essay conventions to an unstable writing environment where digital tools for producing, publishing, and negotiating meaning offer a range of possible audiences, modalities, forms, and modes of meaning making. This space creates the pedagogical conditions for epistemic development, through which students adopt as their own the research practices of adept and experienced writers. The multiple demands of this course on writing, research, and digital environments generates the beginnings of interdisciplinary writing pedagogy involving Kent’s (1993, 1999) postprocess mindset, the ACRL’s (2015) Framework for Information Literacy in Higher Education, Baxter Magolda’s (1999) constructive-developmental pedagogy, and Arroyo's (2013) elaboration of participatory digital writing pedagogy.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".