Weaving together media, technologies and people
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
Purpose Students in flipped classrooms are challenged to orchestrate an increasingly heterogeneous collection of learning objects, including audiovisual materials as well as traditional learning objects, such as textbooks and syllabi. This study aims to examine students' information practices interacting with and synthesizing across learning objects, technologies and people in flipped classrooms. Design/methodology/approach This grounded theory study explores the information practices of 12 undergraduate engineering students as they learned in two flipped classrooms. An artifact walkthrough was used to elicit descriptions of how students conceptualize and work around interoperability problems between the diverse and distributed learning objects by weaving them together into information tapestries. Findings Students maintained a notebook as an information tapestry, weaving fragmented information snippets from the available learning objects, including, but not limited to, instructional videos and textbooks. Students also connected with peers on Facebook, a back-channel that allowed them to sidestep the academic honesty policy of the course discussion forum, when collaborating on homework assignments. Originality/value The importance of the interoperability of tools with elements of students' information space and the significance of designing for existing information practices are two outcomes of the grounded theory approach. Design implications for educational technology including the weaving of mixed media and the establishment of spaces for student-to-student interaction are also 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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 it