STUDY APPROACHES OF POSTGRADUATE STUDENTS IN ODL SYSTEM: A LONGITUDINAL SURVEY
Bibliographic record
Abstract
The study aimed to analyze the study approach of the postgraduate students across various semesters of studies. Longitudinal survey design was adopted to conduct this study. The participants of study were enrolled in Education degree program in university (Pakistan). There were two cohorts of students who participated in this study with 12 students in cohort-1 and 10 students in cohort-2. Approaches and Study Skills Inventory for Students (ASSIST- short version with 52 items) was used to collect data from students at three different times i.e., first time at the start of the second (coursework) semester, second time at end of second semester (development of research proposal stage) and third time during the dissertation stage. Similarly, the data were analyzed using descriptive and inferential statistical techniques. The study results reported that the students used deep and strategic approach to study more than surface approach to study however, the percentage of using the surface approach was also quite high. It was also found that there was no gender wise difference in the surface, deep and strategic approaches of both cohorts of the research study. It is recommended to provide the students with guidance and facilitation for shifting their study approach from surface to deep approach.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".