Bibliographic record
Abstract
Most postgraduate programmes, that have research components, require students to take at least one course of research statistics. Not all postgraduate programmes are science based, there are a significant number of postgraduate students who are from the social sciences that will be taking statistics courses, as they try to complete their postgraduate studies. As postgraduate students come from varied backgrounds, from those who have left school for more than a decade, to those who just completed their undergraduate studies, postgraduate statistics course may be one of the toughest to teach. These students come into the course with preconceived thoughts and attitude, which would either increase their anxiety towards statistics, or decrease their anxiety. Previous studies have shown that students reported high level of statistics anxiety during a statistics course. Unfortunately, there are limited studies on statistics anxiety in the Malaysian postgraduate population. Therefore, this study aims to determine the level of anxiety towards statistics among postgraduate student. This study also aims to explore factors that are associated with statistics anxiety among postgraduate students at the Faculty of Education, UKM. As a secondary outcome, this study explores the type of evaluation preferred by postgraduate students in relation to a statistics course. All postgraduate students who registered for the Research Statistics course at the Faculty of Education, National University of Malaysia, during the study period were invited to participate in the study. A total of 141 students completed the questionnaire and was included in this paper. This study found that a significant (21.7%) of the students surveyed have anxiety in at least one of the statistics anxiety domain, either in anxiety towards class activities, attitude towards class, attitude towards Mathematics or self-perception of ability to perform in statistics. This study found that ethnicity was associated with higher anxiety towards class activities, with the Malays being more anxious compared to the non-Malays. Both ethnicity and bachelor’s degree were associated with attitude towards class and attitude towards Mathematics. For these two domains, the male students and students from non-science based bachelor’s degree, showed more anxiety compared to female students. Self-perception of ability to perform in statistics was not associated with any socio-demographic factors included in this study. Students in this study overwhelmingly preferred individual assignment as an evaluation method, followed by mid-semester examination, and the final semester examination. Least preferred were online participation and presentation.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.005 | 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".