Empirical Research on Relationship between College Students’ Social Identity and Online learning Performance: A case Study of Guangdong Province
Bibliographic record
Abstract
From “God’s favored person” to “ordinary worker”, college students become indifferent to life and addicted to web gaming because they face a rapid devaluation of college student identity in China. At the same time, MOOC and other online learning resources are bringing students better personal learning environment and requiring the students to be more self-disciplined and self-educated oriented. Correlation was found among academic performance, life satisfaction and personal identity. The relationship between students’ online learning performance, life satisfaction and social identity has become a key issue for the Chinese educators and academic institutions. This paper investigates college student’s social identity and identify how online learning performance influences their life satisfaction and social identity based on 490 questionnaires using Jonathan M. Cheek relational identity orientation scale for the AIQ. The results suggest that the demographic feature of students has different influence on their social identity, and the effect of online learning performance and life satisfaction on social identity shows a significant difference. Besides, implications for improving college students’ social identity are also discussed.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".