The Influence of Cognitive Learning Style and Learning Independence on the Students’ Learning Outcomes
Bibliographic record
Abstract
Students of Open University are strongly required to be able to study independently. They rely heavily on the cognitive learning styles that they have in attempt to get maximum scores in every final exam. The participants of this research were students in the Physics Education program taking Thermodynamic subject course. The research analysis employed a two-way ANOVA statistical analysis with the following findings. First, the significance value of the students’ cognitive learning styles variable equals to 0,000 < α =5%, so it was concluded that the students’ cognitive learning styles strongly influenced their learning outcomes in Thermodynamic Science course manifested in the form of either dependent or independent cognitive styles. Second, the students’ learning independence variable turned out to be not having any significant relationship with the students’ learning outcomes in Thermodynamic. The learning independence variable had no significant influence on the students’ learning outcomes with the level of significance of dependent cognitive style 0.007 < α =5%, so it was concluded that the dependent cognitive learning style influenced the learning outcomes, and the learning independence as well as cognitive learning styles, especially the dependent type, altogether influenced the students’ learning outcomes in Thermodynamic. The learning independence variable significantly had no influence on the learning outcomes, with 0.007 < α =5% meaning that the dependent cognitive learning style strongly influenced the learning outcomes.
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 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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".