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Watkraw, Wasan
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management

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Applying Factor Analysis to Assess Employment Competitiveness Strategies: A Data Science Perspective Wang, Yang; Sangsawang, Thosporn; Vipahasna, Piyanan Pannim; Vipahasna, Kitipoom; Watkraw, Wasan
Journal of Applied Data Sciences Vol 6, No 1: JANUARY 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v6i1.650

Abstract

This study aims to identify and analyze the factors influencing the employment competitiveness of graduates from higher vocational colleges in China and evaluate the impact of targeted programs designed to enhance these factors on graduates' employability. The research involved 17 experts and 100 instructors from Sichuan University of Science and Engineering, utilizing purposive sampling to explore effective career guidance models for improving employment ability. The Delphi technique was applied to synthesize expert opinions on key factors affecting graduate employment competitiveness. Additionally, a sample of undergraduate students participated in the study, with data collected through questionnaires. The findings demonstrate the transformative potential of focused career guidance programs, showing a significant improvement in students' employability post-intervention. These results emphasize the importance of targeted initiatives that equip students with the necessary skills, resources, and career insights to succeed in the job market. By bridging the gap between academia and industry expectations, such programs play a crucial role in preparing students for a smooth transition from university to the professional world, helping them secure meaningful employment opportunities.
Utilizing Systematic Digital Platforms and Instructional Design in Health Communication: A Data-Driven Approach in China's Curriculum Fu, Ying; Sangsawang, Thosporn; Pigultong, Metee; Watkraw, Wasan
Journal of Applied Data Sciences Vol 6, No 1: JANUARY 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v6i1.651

Abstract

This study explores the integration of systematic instructional design and digital platforms in health communication courses in China, with a focus on evaluating the effectiveness of these approaches in enhancing medical interns' knowledge and satisfaction. The research involved 17 experienced physicians and 30 medical interns, utilizing the Delphi Method for expert input and various data collection methods, including in-person surveys, telephone interviews, and email-based questionnaires. The study aimed to assess the impact of digital platforms and instructional design on knowledge acquisition and overall satisfaction. The findings suggest that the integration of systematic instructional design with digital platforms significantly improved medical interns' knowledge and engagement with the health communication curriculum. Additionally, expert consensus supported the effectiveness of this approach in addressing critical gaps in digital literacy and practical health communication skills. The study introduces the Chinese IDSDPS Health Communication Model, a dynamic, culturally relevant framework designed to bridge gaps in digital literacy, communication tactics, data analysis, and interdisciplinary learning. By incorporating locally relevant health content and ensuring alignment with China's public health needs, the model presents a scalable approach to improving health communication education. This research emphasizes the transformative potential of combining instructional design and digital technologies to enhance educational outcomes in health communication, offering valuable insights for addressing broader public health challenges both in China and globally.
Data-Driven Development of an Elderly Training Package Using the GCC Model Cheng, Fan; Sangsawang, Thosporn; Pigultong, Metee; Watkraw, Wasan
Journal of Applied Data Sciences Vol 6, No 1: JANUARY 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v6i1.662

Abstract

This study aimed to design and assess the effectiveness of an elderly training package for first-year students at Yibin University, China, based on the GCC Model for geriatric rehabilitation. The goal was to integrate theoretical knowledge with practical skills in geriatric care, using data-driven approaches to evaluate its impact on student learning outcomes. A purposive sample of 17 experts and 30 first-year students enrolled in geriatric rehabilitation courses participated in the study. Data were collected through a combination of in-person surveys, telephone interviews, and email interviews using the Delphi Method. The training package focused on critical aspects of geriatric care, including aging-related health issues, physical rehabilitation, psychological support, and social integration. Additionally, it incorporated technology, practical simulations, case studies, and feedback mechanisms to enhance healthcare professionals’ skills. Data analysis demonstrated a significant improvement in students' knowledge and practical abilities post-intervention, with moderate satisfaction expressed by both experts and students regarding the effectiveness of the package. The study underscores the importance of blending theoretical learning with hands-on experience, utilizing data-driven evaluation methods to assess the impact on educational outcomes. These findings provide valuable insights for the development of effective geriatric care training models that combine data science and educational practices to optimize learning in healthcare education.
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 Cheng, Fan Fu, Ying Junru, Chen Pigultong, Metee Prammanee, Noppadol Sangsawang, Thosporn Vipahasna, Kitipoom Vipahasna, Piyanan Pannim Yang Wang Zhou, Dan