Development of the Online Course Overload Indicator and the Student Mental Fatigue Survey
Bibliographic record
Abstract
The purpose of this study is to develop and examine the psychometric properties of the Online Course Overload Indicator (OCOI) and the Student Mental Fatigue Survey (SMFS). The OCOI was designed to measure students’ perceptions of cognitive overload in online courses. The SMFS was used to assess students’ perceptions of mental fatigue while taking online courses. An exploratory factor analysis was conducted on a sample of 378 undergraduate students from various institutions offering online courses across the United States. Results of a factor and reliability analyses confirmed that the instruments are valid and reliable measures of students’ perceived mental fatigue and overload from online course elements. The analysis supported the model that students’ perceptions of overload in online courses consist of four constructs—information relevance, information overload, course design, and facilitation—in addition to the one-factor structure of the SMFS, which consists of the student mental fatigue construct.
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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 | 0.010 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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; 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".