Using Multimedia Feedback to Enhance Cognitive, Affective, and Psychomotor Learning
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
Providing high-quality assessment feedback for learners is one of the most important activities faculty can do to positively affect learning. Recent advancements in information, communication, and multimedia technologies present opportunities for us to examine how, when, and where we provide assessment feedback. Yet, a scan of the academic research literature shows that technologies are used widely for teaching in higher education, but not necessarily for assessment.\nThis exploratory study utilized an inductive, naturalistic inquiry approach to investigate student perceptions of receiving assessment feedback in digital multimedia format. Findings revealed that students reported positive effects on their cognitive, affective, and psychomotor learning through what they perceived as regularly occurring student-faculty interaction. Although this study had a relatively small and homogeneous sample, these findings indicate that providing digital multimedia assessment feedback asynchronously, online, has the potential to enhance faculty-student interactions, while contributing to student learning, satisfaction, and motivation.
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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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