Article Per Year (5 Year)
p-Index From 2021 - 2026
4.544
P-Index
This Author published in this journals
All Journal International Journal of Informatics and Communication Technology (IJ-ICT) Indonesian Journal of Science and Technology Jurnal CoreIT Buletin Ilmiah Sarjana Teknik Elektro IJIIS: International Journal of Informatics and Information Systems Journal of Applied Data Sciences International Journal of Robotics and Control Systems Munaddhomah: Jurnal Manajemen Pendidikan Islam International Journal for Applied Information Management Indonesian Journal of Teaching in Science Journal of Digital Market and Digital Currency Journal of Current Research in Blockchain International Journal Research on Metaverse
Sangsawang, Thosporn
Unknown Affiliation
Religion Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Environmental Science Mathematics Social Sciences Other

Published : 35 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 22 Documents
Search
Journal : journal of applied data sciences

 1   2   3 
Factor Analysis on Teaching Quality Management for Art Design Students Using Data Driven Approach Junru, Chen; Sangsawang, Thosporn; Pigultong, Metee; Watkraw, Wasan
Journal of Applied Data Sciences Vol 6, No 3: September 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v6i3.746

Abstract

This study aimed to improve teaching quality management for Art Design students using a data-driven approach through three objectives: (1) synthesizing key factors influencing instructional quality, (2) analyzing those factors using expert consensus, and (3) evaluating student satisfaction after applying the data-driven methodology. The Delphi Method was used to gather insights from 17 education experts, while 30 purposively selected Art Design students participated in satisfaction assessments. Data collection involved questionnaires and interviews, with analysis techniques including mean, standard deviation, Coefficient of Variation (CV), and t-tests. Cronbach’s α was 0.98, indicating high internal reliability. Results showed expert consensus on relevant teaching quality factors (M = 3.92, SD = 0.33, CV = 19.96, p = .002). Key aspects identified included instructional design, digital integration, feedback mechanisms, and curriculum alignment. Post-intervention analysis revealed significant student improvement, with average skill levels increasing from 16.12 (SD = 0.89) to 20.34 (SD = 0.566, p = .002). Student satisfaction reached 78.59%, with a mean of 3.90 (SD = 0.72, CV = 18.78). All statistical terms were properly defined and contextualized. The findings underscore the role of structured data analysis and expert-informed models in enhancing instructional strategies, aligning teaching with professional expectations, and promoting continuous improvement in Art and Design education.
Designing a Data-Driven, Innovative Practical Model for Minority Dance Courses in Higher Education Institutions Zhou, Dan; Sangsawang, Thosporn; Vipahasna, Kitipoom; Prammanee, Noppadol; Watkraw, Wasan
Journal of Applied Data Sciences Vol 6, No 3: September 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v6i3.768

Abstract

This study aimed to design and evaluate a data-driven, innovative practical teaching model for minority dance courses in higher education by integrating constructivist learning theory, multicultural education, and experiential learning. The objectives were threefold: (1) to develop a systematic instructional design framework, (2) to measure students' knowledge improvement before and after applying the model, and (3) to assess student satisfaction with the model, particularly regarding cultural identity, learning experience, and engagement. A total of 17 expert instructors from Chinese universities and Kunming University were selected through purposive sampling to contribute to the design process using the Delphi Method. Additionally, 402 first-year dance students participated in evaluating the model’s effectiveness. Quantitative analysis was conducted using means, standard deviations, coefficients of variation, and t-tests. The experts' evaluation of the teaching model yielded a mean of 4.63 (SD = 0.31, CV = 17.84, p = .002), indicating moderate agreement. Student performance significantly improved after intervention, with average skill scores rising from 16.11 (SD = 0.884) to 20.33 (SD = 0.564), p = .002. Student satisfaction reached 78.58% (mean = 3.90, SD = 0.72, CV = 18.78). The hybrid teaching model—blending traditional methods with interactive digital tools and interdisciplinary content (effectively enhanced students' dance proficiency, cultural awareness, and engagement). These findings support the use of blended learning and data-informed instructional strategies to drive innovation and improve outcomes in minority dance education.
Co-Authors Aang Subiyakto Abdul Karim Atanda Balogun, Naeem Bakti Gama, Cipta Boonsong, Sutthiporn Chankham, Nawaphas Chen, Mei Chen, Rui Cheng, Fan Darboth, Kanokwan Dulklang, Thanyathorn Dwi Yuniarto Evi Triandini Evy Nurmiati Fetrina, Elvy Forca, Adrian Jaleco Fu, Ying Huang, Lihua Huda, Muhammad Qomarul Intarapreecha, Navinee Isman, Aytekin Junru, Chen Kim, Sangbum Kulnattarawong, Thidarat Li Guo Li, Shu Liu Yang Luaensutthi, Aammuay Luhuringbudi, Teguh Meinarini Catur Utami Mesraini Mesraini N., Nuryasin Nashrul Hakiem Pasawano, Tiamyod Pigultong, Matee Pigultong, Metee Prammanee, Noppadol Punyayodhin, Sulaganya Q. Huda, Muhammad R. Alghifari, Muhammad Rahman, Hadi Rangkuti, Rahmah Yasinta Sawetmethikul, Pakornkiat Shuang Li Siramaneerat, Issara Tang, Lin Thepnuan, Naruemon Thepnuan, Narumom Vipahasna, Kitipoom Vipahasna, Piyanan Pannim Viva Arifin Wang, Ning Watkraw, Wasan Wen, Tingbin Yang Wang Yongmei Li Yudhanta, Satya Yuni Sugiarti, Yuni Yuri Pamungkas Zhang, Yongfeng Zhang, Zhang Zhong, Junhua Zhou, Dan Zhou, Lin