Field Studies in Heritage Education: Assessing Impact on Tourism and Sustainability at Bujang Valley, Kedah, Malaysia
Bibliographic record
Abstract
This article aims to analyse the importance of a field study of the Bujang Valley archaeological site in Kedah among students in the context of reinforcing heritage education. This study involved 400 university students who were randomly selected. A questionnaire instrument was used to elicit feedback, including the respondents' background, knowledge about Bujang Valley, knowledge about a guided tour of the exhibition gallery, knowledge about a guided tour of the archaeological site, knowledge about a demonstration technique and an archaeological excavation method, and knowledge about a field study of the archaeological site. The findings indicate that conducting the field study via activities during the guided tour of the exhibition galleries at the Bujang Valley Archaeological Museum (MALB) and the Hindu-Buddhist temple site is highly effective in enhancing heritage education. Indeed, it was able to impart knowledge about the significance of Bujang Valley to students enrolled in higher learning institutions (Mean=3.67 to Mean=5.00). Knowledge about Bujang Valley between education-based (UPSI) and non-education-based (UKM) students was equivalent, and there was no difference in any of the five variables (p> .05). This study is supposed to contribute in assisting the demonstration technique and archaeological excavation method crucial in reinforcing students' knowledge of the value of conservation and preservation of national heritage sites. Hence, the field study of the archaeological site and historical place needs to continue at higher learning institutions to further reinforce students' knowledge about the history and heritage of the country.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".