Attitudes and learning styles can affect academic achievement at different levels. While analyzing attitudes and learning styles can not only use basic statistics, using advanced tools to analyze the students' in-depth elements is discussed. Therefore, this research offers an appropriate method for clustering academic achievement (GPA) that support student’s attitudes and learning styles. At the same time, this research is aimed to study the level of attitudes towards learning styles in different academic achievement of students at the University of Phayao. The data collection was conducted from 195 students from 17 schools and colleges at the University of Phayao, Thailand. The results show that there is a variety of cluster in students’ attitudes and learning styles with a significant pattern (types of success) of the students’ model, while the model performance has a very high efficiency to the model. In future work, it will be applied with other universities in Thailand and also used in developing applications for providing a program recommended for appropriate educational programs.

This study was conducted to examine the moderating effects of positive thinking and job satisfaction on the connection between job stress and organizational commitment. This study surveyed 201 salespeople in the Thai food business to establish the links between moderating influences using hierarchical regression analysis. Job satisfaction had a negative connection with organizational commitment; positive thinking had a moderating effect on the relationship between job satisfaction and organizational commitment; and job satisfaction had a statistically significant moderating influence on the relationship between job stress and organizational commitment. Assessing the moderating effects of positive thinking and job satisfaction on 201 salesmen in the Thai food business, the results suggested that employees should engage in positive thinking while management should create resources that best meet the needs of employees in order to lower job stress levels and increase organizational commitment. Managers and human resource departments should be aware of the detrimental effects of job stress on the positive thinking and job satisfaction of their employees, which reduces their organizational commitment. This study contributes to the existing knowledge on the effects of job satisfaction on organizational commitment by elucidating the effects of positive thinking and job satisfaction on the link between job satisfaction and organizational commitment.

The Self-Regulated Learning (SRL) strategies can be the best. It can be achieved by a sub-goal that will be more important in the younger generation. This paper proposes the process of developing factors (attributes) which are related to the development of learning styles through self-regulated strategies. The objectives of this paper are (1) to study the perception and attitude toward the attributes of students with self-regulated learning of the students in higher education, and (2) to find the level of acceptance towards the factor of SRL using applied statistics and machine learning technology. The results show that two tools have proved the respondents and the factors of SRL in the accepted level. Besides, the results found that Thai higher education students still focus on formal learning, which conflicts with the behavior and us-age of Internet and telephone in the classroom. In future work, the author is committed to develop and apply a self-regulated learning strategy model with a combination of collaborative learning strategies of blended learning. Also, it supports undergraduate students in analyzing the factors and studying the behavior patterns of learners in suitable modern learning.

In this day and age, many universities in Thailand have specific targets for students to achieve academic success and earn honours degrees. Such targets are based in part on the unique identity of each university. This paper aimed to provide a modelling and recommender application, which gathers and utilises the characteristics and attitudes of students in order to accurately predict and select the most appropriate learning institution for particular students through data analytics techniques. The system consisted of three main processes to recommend students for the appropriate university, including design tools, development tools, and analytical tools. The data for the instant research was gathered from 1,109 students at three universities, including Rajabhat Mahasarakham University, Mahasarakham University, and the University of Phayao. The methods used to formulate suggestions were decision tree and association rule. The results indicated that accuracy was significant for four factors in the application, including the popularity of the universities, trust in the institutions, the skills of learners, and family income. The constructed model had 69.03 % accuracy, supporting the proposition that the model revealed a reasonable relationship between students and appropriate universities when utilising this decision-support system.

The COVID-19 situation has a serious global impact on the education system. Thus, the research purpose is aimed to construct the models of online learning strategies for Thailand students on learning management in the coronavirus 2019 scenario. The research methodology was conducted according to the process of the cross-industry standard process for data mining, known as the CRISP-DM model for developing the best research. The data collected 487 students from the University of Phayao (UP), and Rajabhat Maha Sarakham University (RMU) from the 1st semester in academic year 2020. The collected data has been agreed upon in accordance with research ethics. The results of the study revealed that the factors influencing the model consisted of 8 out of 38 attributes, with a high predictive accuracy (85.14%). Finally, the researchers can plan for the management of teaching and learning for students at the University of Phayao to solve the Coronavirus 2019 Scenario in the academic year 2021 and the future.