• The Journal of Korean Society for School & Community Health Education
• /
• v.17 no.2
• /
• pp.17-30
• /
• 2016

Objectives: The purpose of this study was to examine differences between the traditional lecture teaching learning method and action learning teaching learning method of nursing students' leadership, problem solving competence, creativity, and critical thinking disposition. Methods: This study was carried out from February 24, 2014 to May 30, 2014 with 171 nursing students (an experimental group of 88 students and a control group of 83 students) assigned among $2^{nd}$ year students attending nursing departments in U city. The Action learning teaching learning method applied to the experimental group by two experts. The Traditional lecture teaching learning method applied to the control group. In order to compare the differences, a pre and post questionnaire were used. The data gathered was analyzed using the SPSS 22. Results: Upon completion of education the nursing students' leadership, problem solving competence and creativity significantly increased both in the experimental group and in the control group compared to the pre testing phase. The critical thinking disposition significantly increased after education in the experimental group, but there was no significant change in the critical thinking disposition of the control group. Conclusion: To improve nursing students' leadership, problem solving competence, creativity, and critical thinking disposition the action learning teaching learning method appears to be more effective than the traditional lecture teaching learning method.

• Education of Primary School Mathematics
• /
• v.26 no.4
• /
• pp.333-348
• /
• 2023

Clear analysis and diagnosis of various characteristic factors of individual students is the most important in order to realize individual customized teaching and learning, which is considered the most essential function of math artificial intelligence-based digital textbooks. In this study, analysis factors and tools for individual customized learning diagnosis and construction models for data collection and analysis were derived from mathematical AI digital textbooks. To this end, according to the Ministry of Education's recent plan to apply AI digital textbooks, the demand for AI digital textbooks in mathematics, personalized learning and prior research on data for it, and factors for learner analysis in mathematics digital platforms were reviewed. As a result of the study, the researcher summarized the factors for learning analysis as factors for learning readiness, process and performance, achievement, weakness, and propensity analysis as factors for learning duration, problem solving time, concentration, math learning habits, and emotional analysis as factors for confidence, interest, anxiety, learning motivation, value perception, and attitude analysis as factors for learning analysis. In addition, the researcher proposed noon data on the problem, learning progress rate, screen recording data on student activities, event data, eye tracking device, and self-response questionnaires as data collection tools for these factors. Finally, a data collection model was proposed that time-series these factors before, during, and after learning.