• School Mathematics
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• v.12 no.4
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• pp.473-491
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• 2010

In the TIMSS assessment goal and open TIMSS 2007, Singapore recorded a lower overall achievement level compared with Korea; however, the excellent results shown by Singapore furnished an opportunity for various countries to research into the education in Singapore. This paper conducted a comparative analysis of the "Proportion, Proportional Expression, and Percentile" area out of the three topics involving "Fractions and Decimals", "Proportion, Proportional expression, and Percentile", and "Measurement", in all of which Singapore exhibited a higher percentage of correct answers than Korea. The paper was able to discover the following differences through a comparative analysis of how Korean and Singaporean textbooks deal with the open questions of TIMSS 2007 after looking into them according to four assessment goals. First, the Singaporean textbook introduced the concept of proportion one year ahead of the Korean textbook. Second, the Singaporean textbook repeatedly coped with the topic of "Proportion, Proportional Expression, and Percentile" in depth and by academic year, and its volume was larger than that of the Korean textbook. Third, there was a difference in the introduction and definition of the concept of proportion. Fourth, the way of introducing a proportional expression was also different, and the Singaporean textbook proposed many more questions that utilize this expression in ordinary life. Based on these differences, the paper suggested implications that could be applied to the Korean curriculum and textbook.

• Journal of Internet of Things and Convergence
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• v.9 no.3
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• pp.35-43
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• 2023

This study tried to find out the applicability and effectiveness of the AI-based adaptive learning system in university classes by operating an AI-based adaptive learning system on a pilot basis. To this end, an AI-based adaptive learning system was applied to analyze the operation results of 42 learners who participated in basic mathematics classes, and a survey and in-depth interviews were conducted with students and professors. As a result of the study, the use of an AI-based customized learning system improved students' academic achievement. Both instructors and learners seem to contribute to improving learning performance in basic concept learning, and through this, the AI-based adaptive learning system is expected to be an effective way to enhance self-directed learning and strengthen knowledge through concept learning. It is expected to be used as basic data related to the introduction and application of basic science subjects for AI-based adaptive learning systems. In the future, we suggest a strategy study on how to use the analyzed data and to verify the effect of linking the learning process and analyzed data provided to students in AI-based customized learning to face-to-face classes.

• Journal of The Korean Association For Science Education
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• v.38 no.6
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• pp.875-883
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• 2018

This study examined overall effect of STEAM programs on student learning through meta-analysis of journal articles published for the past six years. We examined the areas of effects that the research tested and analyzed overall effect across the research. We first identified academic journal articles that utilized quasi-experimental design in examining STEAM effects on student learning and presented appropriate data for meta-analysis such as effect size. A total of 63 articles were identified to be appropriate for meta-analysis. Using R packages, we first identified outliers and eliminated them in the analysis of mean effect size. Thus, 172 effect sizes from 60 studies were analyzed. The results showed that the mean effect was medium (effect size = 0.52). Analysis showed that moderators of the effect were affective measures, thinking skills, character measures, and career aspirations, which meant the studies that measured these variables had more effect than achievement measures. On the other hand, the school level (elementary, middle, and high school), the absence or presence of student products as program requirements, hours of intervention, and sample size did not moderate the effect. Thus, regardless of these variables STEAM programs produced medium effect in general. Based on these results, further research areas and topics are suggested.

• Korean Journal of Cognitive Science
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• v.27 no.2
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• pp.159-219
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• 2016

Mathematical ability is important for academic achievement and technological renovations in the STEM disciplines. This study concentrated on the relationship between neural basis of mathematical cognition and its mechanisms. These cognitive functions include domain specific abilities such as numerical skills and visuospatial abilities, as well as domain general abilities which include language, long term memory, and working memory capacity. Individuals can perform higher cognitive functions such as abstract thinking and reasoning based on these basic cognitive functions. The next topic covered in this study is about individual differences in mathematical abilities. Neural efficiency theory was incorporated in this study to view mathematical talent. According to the theory, a person with mathematical talent uses his or her brain more efficiently than the effortful endeavour of the average human being. Mathematically gifted students show different brain activities when compared to average students. Interhemispheric and intrahemispheric connectivities are enhanced in those students, particularly in the right brain along fronto-parietal longitudinal fasciculus. The third topic deals with growth and development in mathematical capacity. As individuals mature, practice mathematical skills, and gain knowledge, such changes are reflected in cortical activation, which include changes in the activation level, redistribution, and reorganization in the supporting cortex. Among these, reorganization can be related to neural plasticity. Neural plasticity was observed in professional mathematicians and children with mathematical learning disabilities. Last topic is about mathematical creativity viewed from Neural Darwinism. When the brain is faced with a novel problem, it needs to collect all of the necessary concepts(knowledge) from long term memory, make multitudes of connections, and test which ones have the highest probability in helping solve the unusual problem. Having followed the above brain modifying steps, once the brain finally finds the correct response to the novel problem, the final response comes as a form of inspiration. For a novice, the first step of acquisition of knowledge structure is the most important. However, as expertise increases, the latter two stages of making connections and selection become more important.