Listening to the Voice Within Effectiveness of a Spirituality-Oriented College Career Planning Course
Bibliographic record
Abstract
This action research anchors on the integration of spiritual cultivation related activities into career planning courses in college. Based on Krumholtz’s Planned Happenstance Career Theory approach and applying the concepts of psychology, this study examines the curriculum of this spirituality-oriented college course in career planning. It is hoped that students establish the good habit of “listening” by leveraging chance events in life to create surprises in life and career development. The action research is centered in the 18-week program and based on single-group post-test experiment design. The teaching effectiveness is evaluated with two questionnaires, “Measurement of Satisfaction with Curriculum and Teaching and Feedback Form” issued to students and “teaching assessment” issued throughout the campus. The results indicate that students think positively of the curriculum. The mean of the level of satisfaction with integration of spirituality-related activities into teaching is 4.74 and the standard deviation is 0.44. The mean of the level of satisfaction with overall teaching and planning is 4.81 and the standard deviation is 0.40. Furthermore, the mean of the level of satisfaction with teaching of this curriculum is 4.78 and the standard deviation is 0.42 according to the questionnaire survey on teaching (based on a 5-point scale). Effectiveness is evidenced with the high means shown in the questionnaire on learning satisfaction and the assessment of teaching. This curriculum model achieved a high level of satisfaction among students. The qualitative analysis of open feedback finds that this curriculum model helps to enhance learning satisfaction. Self-concept reinforced by listening to the voice within and learning enhances the ability to think positively and deal with pressure. The pondering of meanings of life, life philosophy and goals in life during the course helps one’s career development. Finally, the findings of this action research suggest that it is feasible to promote the teaching model of spirituality-oriented career planning courses for college students in higher education. Hopefully the resulting ripple effect can advocate and drive long-term vision of spirituality-oriented career planning courses for college students in higher education.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".