Development of a Scale of Skills in Teaching Work and Innovation in University Education
Bibliographic record
Abstract
This study aimed to validate a scale for subjectively measuring teaching competencies for innovation in higher education. The scale was developed by creating a set of items that underwent content validity through the Delphi technique and face validity. A survey was then conducted with 523 higher education professors. The resulting scale, called the STW-ICE Scale, consists of four dimensions: continuing education, creativity, digital fluency, and scientificity. We found that the scale has psychometric properties that allow for subjective measurement of the proposed competencies. The SmartPLS and SPSS software were used for data assessment. Additionally, we found high levels of teaching skills in the sample for all dimensions. Based on these findings, this study successfully achieved its goal of developing and validating a scale. We hope that this scale will be used not only for classificatory diagnoses but also to encourage reflection on teaching practices in higher education with a focus on innovation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".