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All Journal 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
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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

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Journal : Journal of Applied Data Sciences

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Statistical Analysis the Influence of Internal and External Factors on Entrepreneurial Intentions Wen, Tingbin; Boonsong, Sutthiporn; Siramaneerat, Issara; Sangsawang, Thosporn; Sawetmethikul, Pakornkiat
Journal of Applied Data Sciences Vol 5, No 1: JANUARY 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v5i1.167

Abstract

This study aimed to explore and analyze the internal and external factors influencing statistical analysis the influence of internal and external factors on entrepreneurial intentions. The specific focus was on conducting an in-depth analysis of how these factors manifest within the data science demographic. The study involved a sample group of 432 university students, employing an anonymous questionnaire to gather reliable feedback and achieving a commendable response rate of 93%. Through an established random sampling scheme, 402 valid responses were obtained for data analysis. The data processing and analysis were conducted utilizing SPSS software, incorporating descriptive statistics, hypothesis testing, and multiple regression analysis to uncover insights within the data science context. The study yielded significant results: 1) Gender emerged as a robust variable with a significant t-value=3.28 and a low p-value = .001, indicating a notable gender-based disparity in entrepreneurial intention among students in the data science domain. Work experience also exhibited noteworthy t and p-values (t = -2.45, p = .015), emphasizing the influential role of prior work experience on students' entrepreneurial inclination within the data science field; 2) A comprehensive examination of data related to determinants of university students' entrepreneurial intention revealed distinct differences in the realm of individual traits (personality: ????̅ = 3.94, SD. = .74; values: ????̅ = 4.01, SD. = .70; motivation: mean = 3.87, SD. = .74), social-cultural influences (????̅ = 3.89, SD. = .70), family (????̅ = 3.78, SD. = .86), peers (????̅ = 3.77, SD. = .72), mentors (????̅ = 3.72, SD. = .89), dimensions related to data science entrepreneurship education (innovation education: ????̅ = 3.80, SD. = .87; training: ????̅ = 3.76, SD. = 0.94; courses: ????̅ = 3.71, SD. = .93), and economic environmental factors (financial pressures: ????̅ = 3.93, SD. = .77; financing: ????̅ = 3.89, SD. = .72; market opportunities: mean = 3.83, SD. = .80) exhibited pronounced trends towards convergence within the data science sector. These findings highlight the necessity of comprehensively considering multiple interconnected factors specific to data science in fostering entrepreneurial spirit among university students; 3) All secondary indicators of the four hypothesized factors - individual traits, social support, data science entrepreneurship education, and economic environment - were significant at the .01 level (p .01), affirming positive correlations between all hypothesized factors and the dependent variable of entrepreneurial intention within the data science context.
Data Analytics of Online Lessons in Social Studies and Buddhism: Enhancing Dhamma Teaching and Tripitaka Understanding Among Teachers and Students Luaensutthi, Aammuay; Sangsawang, Thosporn
Journal of Applied Data Sciences Vol 4, No 3: SEPTEMBER 2023
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v4i3.125

Abstract

The objectives were to (1) determine the effectiveness of online lessons of Social Studies and Buddhism on Dhamma’s teaching regarding Tripitaka for teachers; (2) compare the pre-test and post-test achievements of teachers and primary school 6 (Grade 6) students; 3) examine the satisfaction of teachers and students using online lessons of Social Studies and Buddhism on Dharma’s teachings according to the Tripitaka. The samples were 12 teachers, and 30 students studying primary school 6 (Grade 6) at Wat Proifon School. The instruments were online lessons of the Social Studies and Buddhism course on Buddha's Teaching Tripitaka, pre-test and post-test, and the questionnaire of teachers’ and students’ satisfaction towards studying the online lessons in the Social Studies and Buddhism course on Buddha's teaching regarding the Tripitaka.Statistics used were percentage, mean, standard deviation, and t-test for dependent samples. The findings revealed that the efficiency of online lessons in the Social Studies and Buddhism course on Buddha's teaching regarding Tripitaka was 81.92/80.83 on average based on the criteria. The teachers’ learning achievements after using online lessons in the Social studies and Buddhism course on Buddha's teaching regarding the Tripitaka was higher than that of the pre-test 11.40, SD.=1.51, while the average score of the post-test was 18.17, SD.=1.10, and the t-test between   the pre-test and post-tests was 6.77, which were significantly distinctive at the level of .05., and the students’ learning achievements after using online lessons on the Social studies and Buddhism course on Buddha's teaching regarding the Tripitaka was higher than that of the pre-test: 10.40, SD.=1.61, while the average score of the post-test was 16.17, SD.=1.11, and the t-test between the pre-test and post-tests was 5.77, which were significantly distinctive at the level of .05. Teachers' satisfaction was at high level with an average of 4.47, SD.=.55, and the students’ satisfaction gained a very high level with an average of 4.50, SD.=.44.
Statistical Approach to Evaluating the Efficacy of Career Guidance Programs on University Graduate Employability in China Guo, Li; Sangsawang, Thosporn; Vipahasna, Piyanan Pannim; Pigultong, Matee; Punyayodhin, Sulaganya; Darboth, Kanokwan
Journal of Applied Data Sciences Vol 5, No 1: JANUARY 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v5i1.172

Abstract

This study aimed to develop a career guidance model for improving employment ability among Chinese undergraduate students and assess the impact of this model on students’ employment ability. The research involved 17 Chinese experts and 100 instructors from 10 universities in Sichuan, China. The Delphi technique was employed to gather expert perspectives, while data on employment ability were collected using the College Student Employment Ability Questionnaire. The Cronbach's coefficient of the questionnaire is .869, and Cronbach's α .80 indicates excellent internal consistency, affirming the authenticity and credibility of the data in this study. Based on the statistical criteria defined from the results of the fourth-round inquiries, each Course needs to meet any two of the following conditions: arithmetic x ̅ 3.5964, Full Score Rate .1020, and Cronbach's α .3883 to be preliminarily retained. The results of the third-round expert inquiries show that the course offerings meet the Arithmetic x ̅ 3.3548 criteria, Full Score Rate .1987, and Cronbach's α .5590. The study found a significant improvement in students’ employment ability after participating in the model, with the average score increasing from 16.11 to 20.33. These results underscore the effectiveness of targeted career guidance in enhancing undergraduate students’ employment prospects. Most experts have passed all courses and course content by this round, with viable ideas identified. Career Education and Orientation received the highest response percentage (90.67%), followed by self-assessment (89.50%), industry-oriented skill development (87.50%), mentor support and networking (85.50%), industry insights and trend analysis (89.50%), job search and application assistance (90.80%), continuous review and improvement (87.50%), and follow-up counseling and support (89.50%).
Unveiling Entrepreneurial Development in Data Science Using CCIP-PF Model and Statistical Analysis Zhong, Junhua; Boonsong, Sutthiporn; Siramaneerat, Issara; Sangsawang, Thosporn; Sawetmethikul, Pakornkiat
Journal of Applied Data Sciences Vol 5, No 1: JANUARY 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v5i1.168

Abstract

This study aims to explore the intricacies of entrepreneurial development within the realm of data science, shedding light on both internal and external factors that play pivotal roles in shaping the entrepreneurial landscape. Through the lens of the CCIP-PF model and employing rigorous statistical analysis, this research endeavors to provide insights crucial for fostering entrepreneurial growth in this dynamic field. The objectives of this study are: 1)To develop the CCIP-PF model and establish an assessment index system for mental health literacy training in junior high schools; and 2)To apply the evaluation index system to junior high school mental health literacy training, thereby promoting the enhancement of educational quality. The sample group consisted of 17 experts who participated in discussions and generated 162 viewpoints on the constituent elements of evaluation for junior high school mental health literacy training. The methodology employed the Delphi method; the instrument utilized a qualitative assessment approach, employing questionnaires to ensure anonymity and provide reliable feedback. A questionnaire survey was conducted among 422 participants in Sichuan Province's relevant educational administrative authorities, middle school mental health education teachers, university lecturers and professors in mental health education, and psychological counselors. The response rate reached 96.2%. The study analyzed the data using mathematical statistics and SPSSAU22.0, focusing on the reliability of the entire questionnaire and its dimensions. The findings of this study are as follows:1)primary indicators at mean 4.794, SD = 0.473, IQR = 0.125; secondary indicators at mean 4.823, SD = 0.379, IQR = 0.25; tertiary indicators at mean 4.790, SD = 0.424, IQR = 0.302. A factor contribution rate of 74.175% demonstrates efficacy. 2)Empirical research was conducted in various districts of Zigong City, yielding outcomes that align with reality and meet the anticipated objectives.
Assessing Factors and Simulating Innovation: A Study of Innovative Capacities Among Data Science Professionals in China Zhang, Yongfeng; Sangsawang, Thosporn; Vipahasna, Piyanan Pannim
Journal of Applied Data Sciences Vol 4, No 3: SEPTEMBER 2023
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v4i3.123

Abstract

This study aims to analyze the multifaceted factors influencing the innovative capabilities of data science professionals in China and assess the impact of simulations on their innovative skills. The sample comprises seventeen experts who actively participated in discussions and provided 36 perspectives on the factors affecting their innovation abilities. The research methodology utilized the Delphi method, involving four rounds of questionnaires distributed to 363 data science professionals to evaluate the factors affecting their innovation capacity. The data was rigorously analyzed using mathematical statistics and SPSS, with a strong emphasis on questionnaire validity and reliability. In the reliability analysis, Cronbach's α was found to be 0.98, indicating a high level of internal consistency. The research results yielded an average score of 4.79, SD = 0.39, IQR = 1, reflecting a strong consensus among experts in agreement with the research findings. Exploratory factor analysis was employed for validity assessment, revealing that the 12th factor accounted for a cumulative variance explanation rate of 76.54%, exceeding the threshold of 60%, signifying the robust structural validity of the questionnaire data. The study also utilized AMOS software to simulate sample data and assess the influence coefficients of individual, organizational, and family characteristics on innovation capacity, resulting in values of 0.53, 0.39, and 0.22, respectively, all greater than 0, indicating favorable influence relationships. Building upon these findings, a comprehensive model of creativity abilities among Chinese data science professionals is proposed. This research critically examines the innovation potential of data science professionals in Chinese academia, with the overarching goal of enhancing their creative skills and competitiveness within the data science field. Additionally, it lays the theoretical groundwork for fostering innovation within the university setting.
Quantitative Analysis of Educational Techniques for Psychological Development in Vocational Students in China Li, Shuang; Sangsawang, Thosporn; Thepnuan, Narumom; Pigultong, Matee; Punyayodhin, Sulaganya; Darboth, Kanokwan
Journal of Applied Data Sciences Vol 5, No 1: JANUARY 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v5i1.173

Abstract

The research of objective were to: 1) examines environment, educational system, teacher-student relationship, self-awareness, and other aspects affecting Chinese vocational school students' psychological quality., and 2) development Psychological Quality for Vocational School Students in China Model for address unique psychological challenges and foster personal development in vocational education. Populations and sampling group were stents tests 7,000 Zigong, Rong County, and Dujiangyan vocational and technical students. The questionnaires used a percentage- based scoring standard, with a score below 50 indicating “strongly disagree,” 51 to 70 indicating “neutral,” 71 to 90 indicating “moderately agree,” and 91 to 100 indicating “strongly agree.” Data processing affects Zigong, Rong County, and Dujiangyan Chinese vocational school students' mental health. Statistical percentage of students picking each option. Guttman half coefficient was .802 after Split-Half Method testing of the data, indicating good split-half reliability and internal consistency. The questionnaire reveals how survey questions, sample size, and data processing affect Chinese vocational school students' mental health. The questions asked Zigong, Rong County, and Dujiangyan vocational and technical school students about mental health. 4,768 people completed 6,458 surveys. After deleting 97 low-reliability questionnaires with similar answers to seven consecutive items, 4,671 were valid. The Countermeasure Developing Model in China enhances the psychological quality of vocational school students by implementing multi-level therapy, methodical mental health education, and a supportive learning environment.
Research on the Influencing Factors of College Students' Deep Meaningful Learning in Blended Learning Mode Li, Shu; Pasawano, Tiamyod; Sangsawang, Thosporn
Journal of Applied Data Sciences Vol 5, No 2: MAY 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v5i2.254

Abstract

This study examines the factors that impact deep and meaningful learning in blended learning environments and their connections. The sample included 397 college students from a university in Sichuan Province, selected through random sampling. Data was collected using a questionnaire based on Bandura's ternary interaction theory, encompassing learners, helpers, environment, and interaction dimensions. The following text should be remembered: "Hypotheses were developed based on existing literature, and a survey with established scales was created. Quantitative analysis was conducted using SPSS and AMOS software. The mean, standard deviation, Variance, skewness, and kurtosis values were within reasonable ranges. The model's latent variables showed strong convergent validity, with standardized factor loadings (SFL) ranging from 0.807 to 0.965, average Variance extracted (AVE) from 0.697 to 0.946, and composite reliability (C.R.) from 0.919 to 0.946. Model fit indices indicated acceptable fit (CMIN/DF: 2.303, NFI: 0.966, CFI: 0.980, RMSEA: 0.058, RMR: 0.008, PNFI: 0.789). The study optimized the model through path analysis, culminating in the final structural equation model (SEM)." Findings indicate (1) Learner, environmental, and interaction factors positively influence deep meaningful learning, while helper factors show a negative correlation; (2) learner, interaction, and helper factors mediate the environment's impact on deep, meaningful learning; and (3) environmental factors hold the most significant sway over helper factors, followed by interaction and learner factors. Helpers wield significant influence over learners, enhancing deep understanding. These insights guide effective, deep, meaningful learning strategies in blended learning
Data-Driven Analysis of Teaching Quality Impact on Graduate Employment in Higher Vocational Colleges of Hefei Wang, Ning; Pasawano, Tiamyod; Sangsawang, Thosporn; Pigultong, Matee
Journal of Applied Data Sciences Vol 5, No 1: JANUARY 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v5i1.169

Abstract

The objectives were to identify the influence of teaching quality in higher vocational colleges on the employment quality of graduates, and to develop instructional design through both theoretical and empirical analysis, to synthesize the relationships among teaching quality, human capital, and employment quality. In collaboration with 17 experts, they were selected through purposive sampling and involving 100 instructors within higher vocational colleges in China. The instruments using the Delphi Technique through a round questionnaire of vocational colleges' teaching quality positively influenced both graduates' human capital and employment quality. The findings revealed that vocational colleges' teaching quality positively influenced both graduates' human capital and employment quality. Vocational education has a favorable effect on employment quality, with human capital playing a crucial role in enhancing teaching quality. This paper distributed 600 questionnaires in total and collected 527 valid questionnaires, with an effective recovery rate of 87.83%. Data processing and analysis were carried out on the valid questionnaires. However, the relationship between teaching quality and employment quality is mediated by professional cognition and growth ability. These results offer important insights for vocational colleges, pointing to the crucial significance of human capital and educational quality in improving employment quality. In higher vocational colleges, the study investigates the connection between human capital, employment quality, and instructional quality. The teaching quality positively affects graduates' human capital and employment quality, according to data from Hefei grads. The link between teaching and learning is moderated by human capital. The research uses AMOS software to analyze vocational teaching variables, revealing a direct effect of higher colleges' teaching quality on graduates' employment quality and human capital. The significance level of these effects is .001, indicating a strong capacity for explanatory reasoning.
A Mixed-Methods Data Approach Integrating Importance-Performance Analysis (IPA) and Kaiser-Meyer-Olkin (KMO) in Applied Talent Cultivation Zhang, Zhang; Sangsawang, Thosporn; Vipahasna, Kitipoom; Pigultong, Matee
Journal of Applied Data Sciences Vol 5, No 1: JANUARY 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v5i1.170

Abstract

This study endeavors to establish an assessment framework for cultivating undergraduate applied talent, specifically emphasizing data science competencies, in alignment with the development of China's regional economy. A mixed-methods approach, integrating focus group interviews and questionnaire surveys conducted over three rounds of data collection, was employed. The collected data underwent rigorous reliability and validity analyses utilizing SPSS software. An Importance-Performance Analysis (IPA) was executed to construct a performance chart, evaluating the effectiveness of a 24-item framework designed to encompass key aspects of data science education. The initial internal consistency α coefficients for Questionnaire 2 and Questionnaire 3 were found to be .892 and .913, respectively, surpassing the 0.7 threshold, indicating a high level of reliability for all items related to data science competencies. The Kaiser-Meyer-Olkin (KMO) measurements approaching approximately 0.9 affirmed the efficiency of the questionnaire, specifically designed to gauge the relevance and effectiveness of data science-related indicators in the context of applied talent cultivation and regional economic development. Furthermore, the study underscores the significance of indicators such as teamwork, regional market research, and business opportunity identification within the domain of data science. It identifies gaps between key indicators and lower-performing indicators, proposing strategic improvement measures to enhance the alignment of applied talent cultivation objectives with the evolving needs of regional economic development, particularly in the data science landscape. The research findings not only contribute to a foundational understanding of data science competencies in applied talent cultivation but also lay the groundwork for innovative reforms in future talent cultivation models. By clarifying objectives and better aligning them with the dynamic demands of regional economic development, this study sets the stage for transformative advancements in the field of applied talent cultivation, particularly within the realm of data science.
Incorporating Augmented Reality to Enhance Learning for Students with Learning Disabilities: A Focus on Spatial Orientation in Physical Intarapreecha, Navinee; Sangsawang, Thosporn
Journal of Applied Data Sciences Vol 4, No 3: SEPTEMBER 2023
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v4i3.126

Abstract

This research endeavors to integrate Augmented Reality (AR) technology into the realm of physical education, with a specific emphasis on improving spatial orientation skills among students with learning disabilities. The study pursues three core objectives: (1) To assess the efficacy of utilizing AR-based instructional tools to enhance spatial orientation abilities; (2) To scrutinize the academic advancements of students with learning disabilities post-AR intervention; (3) To gauge the satisfaction levels of these students with the AR-enhanced learning experience. The study cohort comprises nine students with learning disabilities, drawn from an educational institution situated in Pathum Thani Province, Wat Pathum Nayok school, using a targeted sampling methodology. Data is gathered through immersive AR experiences within the context of physical education, with a focus on spatial awareness. The analytical approach encompasses a diverse array of statistical techniques, including percentages, means, and standard deviations. Furthermore, the t-test is deployed to statistically compare pre and post-learning outcomes, maintaining a significance level of α = 0.05. The research outcomes substantiate that AR-driven educational activities in physical education effectively enhance spatial orientation skills among students (E1/E2: 82.40/81.33). Preceding the intervention, students recorded an average score of 8.80 with a standard deviation of 2.33, which significantly escalated to 16.27 with a standard deviation of 1.48 following AR-assisted learning. The t-test underscores the statistically significant disparity (p 0.05) in scores prior and subsequent to the AR intervention. Furthermore, students with learning disabilities express considerable satisfaction with the application of AR in physical education, with an average satisfaction rating of 4.51. This research carries substantial implications, particularly within the realm of data science, as it pertains to the collection and analysis of data relating to students' educational achievements and satisfaction levels.
Co-Authors Aang Subiyakto Abdul Karim Bakti Gama, Cipta Boonsong, Sutthiporn Chankham, Nawaphas Chen, Mei Chen, Rui Cheng, Fan Darboth, Kanokwan Dulklang, Thanyathorn 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 Nashrul Hakiem Pasawano, Tiamyod Pigultong, Matee Pigultong, Metee Prammanee, Noppadol Punyayodhin, Sulaganya Rahman, Hadi Rangkuti, Rahmah Yasinta Sawetmethikul, Pakornkiat Shuang Li Siramaneerat, Issara Tang, Lin Thepnuan, Naruemon Thepnuan, Narumom Vipahasna, Kitipoom Vipahasna, Piyanan Pannim 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