The Mobile Applications for Predicting the Study Results of Learning Strategies and Learning Achievement for Lifelong Learning ------------------------------------------------------------------------------------- Pratya Nuankaew, School of Information and Communication Technology pratya.nu@up.ac.th

The Importance of Research Research Methodology Mobile Web-Application Presentation Layout: The Importance of Research Research Methodology Mobile Web-Application Evaluation of Applications Conclusion and Future Work

Thailand's Formal Education System Thailand's education system is free for its citizens and takes 12 years to complete. The structure follows as "6-3-3" plan, with 6 years of primary education, 3 years of lower secondary level education and 3 years of upper secondary level education.

The Importance of Research In parts of Kindergarten, It represents a number more than the population.

Problems and Failures in Thailand’s Education

Problems and Failures in Thailand’s Education What is the problem ? The difference between school size, students competencies, and appropriate education support (Nuankaew et al., 2017). The same criteria, but the quality is not the same. O - NET (Ordinary National Educational Test) A - NET (Advanced National Educational Test) Nuankaew, W., Nuankaew, P., Bussaman, S., & Tanasirathum, P. (2017). Hidden academic relationship between academic achievement and higher education institutions. In 2017 International Conference on Digital Arts, Media and Technology (ICDAMT) (pp. 308–313). https://doi.org/10.1109/ICDAMT.2017.7904982

Problems and Failures in Thailand’s Education What’s reasonable academic relationship between academic achievement and higher education institutions (Pupara et al., 2016). K. Pupara, W. Nuankaew, and P. Nuankaew, “An institution recommender system based on student context and educational institution in a mobile environment,” in 2016 International Computer Science and Engineering Conference (ICSEC), 2016, pp. 1–6.

Research Methodology and Approach Students’ achievement refer to the measure of overall learning out-come called Grade Point Average (GPA) To determine student performance: Group I: passing criteria, an average score higher than 2.00. Group II: fail criteria, GPA is less than 2.00. Data collected from 668 students, 8 majors, including Science and Mathematics, Mathematics and Linguistics, Linguistics and Social Science, French, Chinese, Vietnamese, Business courses, and Music courses

Development and Analysis of Model Decision Tree Model 1 2 Data collection, 8 majors from 668 students accuracy of 98.35% Association Rules 3

Mobile Web-Application 2 3 1 4

Application Satisfaction After application created, it tested with 95 samples from 23 IT specialists and 72 general users at Rajabhat Mahasarakham University, Thailand.

Conclusion and Future Work Summary: It aims to develop applications to provide tools and support for students in Thailand. It uses 668 students to create apps and 95 samples to test satisfaction. The modeling results showed that the model has highly accuracy (94.51%). The satisfaction rate for use at a high level as well (4.61). Next steps: Because universities in Thailand are varieties. The research team is committed to offering courses and universities that are appropriate for learners.

References P. Nuankaew and P. Temdee, “Determining of compatible different attributes for online mentoring model,” in 2014 4th International Conference on Wireless Communications, Vehicular Technology, Information Theory and Aerospace Electronic Systems (VITAE), 2014, pp. 1–5. P. Nuankaew and P. Temdee, “Of online community: Identifying mentor and mentee with compatible different attributes and decision tree,” in 2015 12th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON), 2015, pp. 1–6. K. Pupara, W. Nuankaew, and P. Nuankaew, “An institution recommender system based on student context and educational institution in a mobile environment,” in 2016 International Computer Science and Engineering Conference (ICSEC), 2016, pp. 1–6. J. Wood, M. Campbell, K. Wood, and D. Jensen, “Enhancing the teaching of machine design by creating a basic hands-on environment with mechanical ‘breadboards,’” International Journal of Mechanical Engineering Education, vol. 33, no. 1, pp. 1–25, 2005. E. M. Silk, R. Higashi, and C. D. Schunn, “Resources for robot competition success: Assessing math use in grade-school-level engineering design,” in American Society for Engineering Education, 2011. P. Nuankaew and P. Temdee, “Online Mentoring Model by Using Compatible Different Attributes,” Wireless Pers Commun, vol. 85, no. 2, pp. 565–584, Nov. 2015. P. H. Winne, “How software technologies can improve research on learning and bolster school reform,” Educational Psychologist, vol. 41, no. 1, pp. 5–17, 2006. P. H. Winne and D. Jamieson-Noel, “Self-regulating studying by objectives for learning: Students’ reports compared to a model,” Contemporary Educational Psychology, vol. 28, no. 3, pp. 259–276, 2003. S. Wood, “Generation Z as consumers: trends and innovation,” Institute for EMERGING ISSUES: NC State University, pp. 1–3, 2013. U. G. Assembly, “Transforming Our World: The 2030 Agenda for Sustainable Development. Resolution adopted by the General Assembly on 25 September 2015,” New York: United Nations, http://www. un. org/ga/search/view_doc. asp, 2015. Office of the National Education Commission, Office of the Prime Minister, “National Education Act B.E. 2542 (1999),” Office of the National Education Commission, Thailand, 1999.

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