The impact of the student–instructor relationship on student-centric measures
Bibliographic record
Abstract
Purpose On the basis of the justice, attachment, social support, self-determination theories, this research paper examines the impact of the student–instructor relationship construct on the customer-centric measures of overall student satisfaction, and perceived value for money and their impact of the behavioral intentions as an endogenous construct. We considered universities as providers of complex services focusing on students' service quality and students as the customers of the higher education institutions. Design/methodology/approach A survey instrument was used to collect data among undergraduate and graduate business students in a medium-sized Canadian university (N = 178). Partial least squares structural equation modeling was used to analyze the strength, significance, and effect sizes of the relationships between the key constructs. Findings The results indicate that the student–instructor relationship is significantly related to student satisfaction and value for money perceptions. Also, the student satisfaction and behavioral intentions, value for money and student satisfaction, and value for money and behavioral intentions relationship were significant. Originality/value The perceived quality of student–instructor relationship and its relationship to customer-centric measures like satisfaction, value for money and behavioral intentions has received relatively little attention in previous research and was discovered to be an important contributor to the perceived student satisfaction and value for money. The importance of the student–instructor relationship is further emphasized indirectly via the perceived value for money construct to student satisfaction.
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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 | 0.009 | 0.044 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".