Bibliographic record
Abstract
Higher educational institutions (HEIs) play a substantial role in the development of knowledge and skills that can cope with the demands of industries in the fourth industrial revolution (4IR). This study examined the alignment between the current assessment practices used by HEIs and the competencies demanded by the hospitality and tourism industry. It also aimed to develop an assessment strategy typology that could specifically target the competencies required by the industry. In addition, the study was able to determine the three most and the three least preferred assessment methods as perceived by the hotel and restaurant management students in a private university in Mandaluyong City, Philippines. The findings revealed the common assessment methods employed by teachers in Hospitality and Tourism Managemnt (HTM) major courses. The study argues that the use of these identified assessment methods likewise contribute in developing the emerging skills in the 4IR such as sense-making, social intelligence, novel and adaptive thinking, and new media literacy. Further, the innovative strategies in the application of the assessment methods were found to be effective in student learning. Accordingly, hospitality educators are encouraged to continuously hone their knowledge and skills to provide quality education and produce competent graduates ready to face the challenges of today’s technological era.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".