Student perception of academic grading: Personality, academic orientation, and effort
Bibliographic record
Abstract
Factors influencing student perceptions of academic grading were examined, with an emphasis on furthering understanding of the relevance of effort to students’ conceptualization of grading. Students demonstrated a conceptualization of grading where effort should be weighted comparably to actual performance in importance to the composition of a grade, with the expectation that grade allocation should reflect this perception. Students suggested a compensatory effect of effort in grade assignment, where a subjectively perceived high level of effort was expected to supplement low performance on a task. Furthermore, students perceived professors as less fair and less competent when they were perceived to not be able to adequately account for students’ subjective perception of effort. In addition, student perceptions of grading were examined in relation to student-possessed learning orientation (LO), grade orientation (GO), and aspects of personality. Prototypically, individuals high in LO tend to be motivated by the acquisition of knowledge, while those high in GO tend to be driven by the acquisition of high grades. Conscientiousness, openness and age contributed significantly to and positively predicted LO. Inversely, conscientiousness, openness and age contributed significantly to and negatively predicted GO while neuroticism positively predicted this orientation. Students appear to place a heavy amount of importance on professor consideration of effort, despite recognizing the realistic difficulties in determining effort. The potential for an emerging student mentality is discussed, where students’ perception of grading is distorted by a subjective appraisal of their own effort.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".