Methmal H.K.R.
NIIBS Campus

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Reconciling Tourism Growth and Cultural Heritage Conservation in Sri Lanka's Cultural Triangle: A Mixed-Methods Governance Framework Methmal H.K.R.; Nishadi H.T.B.
Jurnal Sosial Humaniora dan Pendidikan Vol 2 No 1 (2026): Auguss: Jurnal Sosial Humaniora dan Pendidikan: Scripta Humanika
Publisher : CV SCRIPTA INTELEKTUAL MANDIRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65310/sa31a466

Abstract

Sri Lanka's post-pandemic tourism recovery has renewed pressure on cultural heritage destinations to reconcile visitor growth, revenue generation, authenticity, community interests, and physical conservation. This study examines that governance problem in the Cultural Triangle by retaining the original mixed-method design, which included a quantitative tourist sample of 384 participants and qualitative engagement with local communities, Department of Archaeology officials, and Sri Lanka Tourism Development Authority managers. The original thematic and SPSS-based quantitative analyses were supplemented by verified secondary statistics from national tourism and Central Cultural Fund records. International arrivals increased from 719,978 in 2022 to 2,362,521 in 2025, while Central Cultural Fund sites recorded 1,974,888 visits in 2025 and Sigiriya alone accounted for 55% of that total. The integrated evidence indicates that tourism growth is concentrated at a small set of heritage nodes, while authenticity, community participation, and conservation capacity require stronger institutional protection. The study proposes a governance framework combining conservation thresholds, community co-governance, timed and data-informed visitor management, transparent conservation-linked revenue governance, augmented and virtual interpretation, and heritage digital twins. The framework reframes tourism success from volume maximization toward conservation-conditioned value creation and provides a practicable basis for aligning tourism development with long-term cultural heritage stewardship.
A Bounded Bibliometric Profile of Artificial Intelligence Education Research Kongkon Bordoloi; Muhammad Yani; Moh. Imron Rosidi; Teofilus Ardian Hopeman; Muhammad Talha Zubair Yaqub; Methmal H.K.R.
International Journal of Social Sciences, Language, and Education Vol. 1 No. 2 (2026): : April: Didakta: International Journal of Social Sciences, Language, and Educa
Publisher : CV SCRIPTA INTELEKTUAL MANDIRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65310/74crjk87

Abstract

Bibliometric profiles based on relevance-ranked searches may conflate patterns of research publication with patterns of record retrieval. This study examined the descriptive characteristics and interpretive limits of a bounded Crossref corpus on artificial intelligence in education. On 17 September 2026, the first 100 records returned for the query artificial intelligence education, restricted to journal articles published during 2016–2025, were obtained. Records were assessed in retrieval order, and the first 30 with an author field and the complete phrase artificial intelligence in their titles, excluding editorial or corrective items, formed the analytical corpus. Publication year, journal, authorship, Crossref citation counts, and seven non-exclusive title dictionaries were analysed descriptively. Twenty-six records (86.7%) were published in Computers and Education: Artificial Intelligence and four (13.3%) in the International Journal of Artificial Intelligence in Education; 25 appeared during 2022–2025. School-related terms occurred in eight titles, teacher-related terms in five, and ethics-related terms in two. Median authorship was two, and the median recorded citation count was 100. These distributions reflect a fixed search and stopping rule, not population-wide publication frequencies. The study demonstrates how transparent metadata analysis can identify observable patterns while exposing the inferential constraints introduced by search formulation, ranked retrieval, and restrictive eligibility criteria.