The Intersection between Instructor Expectations and Student Interpretations of Academic Skills
Bibliographic record
Abstract
Numerous studies exist on how and to what extent course instructors in higher education are embedding or directly teaching writing, learning and information literacy skills in their courses (Cilliers, 2012; Crosthwaite et al., 2006; Mager & Spronken-Smith, 2014). Yet, disparity within the literature demonstrates that there is no consistent approach to the scaffolded development of these necessary skills within courses, programs, disciplines, or across disciplines. This study sought to explore the skills expectations of instructors and whether students are capable of identifying or articulating the academic skills they are required to develop in to succeed in third-year undergraduate university courses. We discovered a discrepancy rate of approximately 63% between instructor and student responses when exploring differences in instructor expectations and student interpretations of academic skills indicated on course outlines. Data from this study suggests that instructors and students do not always share the same understanding of the skills required to complete course work and to be successful in assessments. With the support of learning, writing, and research specialists, instructors can embed academic skill development in the curriculum.
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.
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 | 0.013 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.010 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".