Including Student Voices in Instructional Design: Community College Students with Below-Proficient Skills Talk About IL Instruction
Bibliographic record
Abstract
First-year college students with below-proficient IL skill levels were identified through a standardized IL test. Interviews and focus groups were conducted with a subset of these students. This paper will focus on the findings of the focus groups and describe how these findings are informing the design of the intervention.Les étudiants universitaires de première année ayant une maîtrise de l'information inadéquate ont été identifiés au moyen d'un test normalisé sur la maîtrise de l'information. Des entrevues et des groupes de discussion se sont déroulés avec un sous-groupe de ces étudiants. Cette communication s'attarde aux résultats des groupes de discussion et décrit comment les résultats sont pris en compte dans la conception de l'intervention.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.080 |
| Open science | 0.003 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".