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In this work, a new machine learning-based model is proposed to predict undergraduate students' reading scores using their listening scores as the primary data. The performance of several machine learning techniques, including neural networks, gaussian process regression, and random forests, was calculated and compared in order to predict the reading test results of the students. The dataset included the listening and reading test results of 1145 students who took the English proficiency exam at Lampang Rajabhat University's language center in Lampang, Thailand. According to the results, the suggested model has a classification accuracy range of 64–75%. Only three different types of parameters—listening scores, departmental data, and faculty data—were used to make the predictions.

This study was aimed to analyze how students' mathematical ideas emerged through a flow of lesson in mathematics classroom using Lesson Study and Open Approach. A context of the study was the Open Approach as a teaching approach and the Lesson Study as a way to improve the quality of teaching (Inprasitha, 2015a). The flow of lesson, likewise, is considered to be a tool for accessing to students' ideas when the students are involved in problem solving and connection between students' real world and mathematical world (Inprasitha, 2017b). Ethnographic study was employed as a research methodology in this qualitative study by using a participative research design to form a lesson study team for collaborative designing of lesson plans guided by Thai version of Japanese mathematics textbooks. Research results were shown that the students' mathematical ideas emerged, through the flow of lesson, when the students' ideas of a problem solving were mathematized as follows: 1) the mathematical ideas were extended through representations of real world, 2) the mathematical ideas were extended and generalized through semi-concrete aids, and 3) the mathematical ideas were generalized through representations of mathematical world. The processes of mathematization (Isoda & Katagiri, 2012), furthermore, were accomplished when the students' mathematical ideas become "how to" or tools for learning for the next lessons.

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