• The Mathematical Education
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• v.56 no.2
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• pp.161-175
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• 2017

The purpose of this study is to compare and analyze the impact on low-achievers in mathematics who studied mathematics using Blended e-learning and Personalized system of instruction after school. Blended e-learning is defined as the management of e-learning using the e-study run by the education office in local. Personalized system of instruction was proceeded as follows; (1) all students are given a syllabicated learning task and a study guide, (2) students study the material autonomously according to their own pace for a certain period of time, (3) the teacher strengthens the students' motivation through grading and feedback after students study a subject and solve the evaluation problem. The learning materials for Personalized system of instruction are re-edited the offline education contents provided by the blended e-learning to the level of students. The 118 $7^{th}$ grade students from the D middle school participated in this study. The results were verified by achievement tests before and after the study, as well as survey regarding their attitude toward mathematics. The results are as follows. First, Blended e-learning has more positive impacts than Personalized system of instruction in mathematics achievement. Second, there was no difference in mathematics achievement according to their self-directed learning between Blended e-learning and Personalized system of instruction. Third, both types utilizing Blended e-learning and Personalized system of instruction have positive effect on attitude toward mathematics, and there is not their difference between two methods of teaching and learning mathematics.

• Communications of Mathematical Education
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• v.36 no.3
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• pp.417-438
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• 2022

The purpose of this study is to suggest implications for mathematics teaching and learning when using AI-based educational platforms that support personalized mathematics learning. To this end, we selected five platforms(Knock-knock! Math Expedition, knowre, Khan Academy, MATHia, CENTURY) and analyzed how the AI-based educational platforms for mathematics reflect the three elements(PLP, PLN, PLE) to support personalized learning. The results of this study showed that although the characteristics of PLP, PLN, and PLE implemented on each platform varied, they were designed to form PLEs that allow learners to make their autonomous decisions about learning based on PLP and PLN. The significance of this study can be found in that it has improved the understanding and practicability of personalized mathematics learning with the AI-based educational platforms.

• The Mathematical Education
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• v.62 no.3
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• pp.303-326
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• 2023

Mathematics is a discipline with a strong systemic structure, and learning deficits in previous stages have a great influence on the next stages of learning. Therefore, it is necessary to frequently check whether students have learned well and to provide immediate feedback, and for this purpose, intelligent tutoring system(ITS) can be used in math education. For this reason, it is necessary to reveal how the intelligent tutoring system is effective in personalized adaptive learning. The purpose of this study is to investigate the functions and applications of intelligent tutoring system for personalized adaptive learning in mathematics. To achieve this goal, literature reviews and surveys with students were applied to derive implications. Based on the literature reviews, the functions of intelligent tutoring system for personalized adaptive learning were derived. They can be broadly divided into diagnosis and evaluation, analysis and prediction, and feedback and content delivery. The learning and lesson plans were designed by them and it was applied to fifth graders in elementary school for about three months. As a result of this study, intelligent tutoring system was mostly supporting personalized adaptive learning in mathematics in several ways. Also, the researcher suggested that more sophisticated materials and technologies should be developed for effective personalized adaptive learning in mathematics by using intelligent tutoring system.

• The Mathematical Education
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• v.59 no.4
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• pp.373-387
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• 2020

The purpose of this study is to verify the effects of personalized learning platforms applied with machine learning recommendation modules that upgrade recommended algorithms by themselves through learning big data analysis on students' learning time, self-directed learning ability, mathematics achievement, and attitudes toward mathematics, and the correlation between them. According to the study, customized learning affected learning time, self-directed learning ability and mathematics attitude, while learning time affected self-directed learning ability. Self-directed learning ability has had a significant impact on the attitude of mathematics and mathematical achievements. As a result of the mediated effectiveness test, the indirect impact of customized learning on mathematics attitude and mathematics performance was significant through the medium of learning time and self-directed learning ability.

• Journal of the Korean School Mathematics Society
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• v.13 no.1
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• pp.125-141
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• 2010

The aim of this paper is to develop a web-based Virtual Learning System for discrete mathematics learning using CAS (Computer Algebra System), The system contains a series of contents that are common between secondary und university curriculum in discrete mathematics such as sets, relations, matrices, graphs etc. We designed and developed web-based virtual learning contents contained in the proposed system based on Mathematia, webMathematica and phpMath taking advantages of rapid computation and visualization. The virtual learning system for discrete math provides movie lectures and 'practice mode' authored with phpMath in order to enhance conceptual understanding of each movie lesson. In particular, matrix learning is facilitated with conceptual diagram that provides interactive quizzes. Once the quiz results are submitted, Bayesian inference network diagnoses strong and weak parts of learning nodes for generating diagnostic reports to facilitate personalized learning. As part of formative evaluation, the overall responses were collected for future revision of the system with 10 university students.

• School Mathematics
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• v.2 no.2
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• pp.333-355
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• 2000

In this paper, possibility of practical use of cryptarithmetic problems in teaching and learning of mathematics is discussed. There might be seven cases to use them practically like followings: (1) Cryptarithmetic problems might be used for deepening the mathematical knowledges. (2) Cryptarithmetic problems might be used for fostering mathematical thinking abilities. (3) Cryptarithmetic problems might be used for fostering problem solving abilities. (4) Cryptarithmetic problems might be used as open ended problems. (5) Cryptarithmetic problems might be used as materials for personalized learning. (6) Cryptarithmetic problems might be used as materials for cooperative learning. (7) Cryptarithmetic problems might be used as materials for problems posing.

• Proceedings of the Korea Information Processing Society Conference
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• 2014.04a
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• pp.981-984
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• 2014

개인화된 서술형 수학 문제(mathematics word problem)는 오랫동안 연구된 분야로 학생들의 학업 성취도와 수학에 대한 태도에 관심을 가져왔다. 본 연구에서는 2013년 도입된 스토리텔링 수학에 개인화된 콘텐츠를 접목하여 그 효과를 알아보고자 하였다. 초등학생 26명을 대상으로 하여 약 110분 동안 수업을 진행하였으며, 무게에 대한 새로운 개념을 배우는 데 그 목적을 두었다. 각각 13명씩 개인화 그룹과 비 개인화 그룹으로 나누어 수업을 진행하였다. 학업 성취도(Learning Achievement)에서는 사전 시험(pre-test) 점수가 너무 높아 두 그룹 간에 서로간의 유의한 차이점을 발견하지 못했다. 수학에 대한 태도 부분과 몰입도(Flow) 부분에서는 다소 개인화 그룹의 값이 높았지만, 통계적으로 유의한 정도는 차이는 아니었다. 하지만 정성적 분석에서는 차이가 있었다. 개인화 그룹(Personalized group)은 비 개인화 그룹(non-personalized group)에 비해 개인화(personalization)가 수업의 재미있는 요소로서 보다 중요한 작용을 했다고 느꼈다. 또한, 테스트나 측정(measure) 부분에서 생겼던 문제점을 개선하여 재 실험이 있을 시엔 유의미한 값을 나타낼 것으로 기대된다.

• Education of Primary School Mathematics
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• v.15 no.2
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• pp.135-145
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• 2012

In this research, we observed how students perform as they followed the teachers' instruction, and consequently perform their realized potential. As the accountability of school education is emphasized, various attempts try to disconnect the vicious cycle of producing low achievers. Efforts are allocated into developing a method to minimize cumulative effect of the lag in educational benefit by focusing on the elementary education. Based on the 2007 revised curriculum, mathematics achievement level and assessment criteria were developed. These criteria were used to standardize the course and assessment objectives for 4th through 6th grade students' mathematics studies, and to assess lower performing students and the lag in their mathematical understanding. The educational materials and assessment criteria can be expected to lead lower performing students by giving them the personalized lesson plans to minimize the lag of mathematical understanding, and eventually expedite their progress and prevent cumulative effect of the lag in the following curriculum.

• Journal of Practical Engineering Education
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• v.15 no.3
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• pp.605-614
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• 2023

In In the era of digital transition, AI-based personalized services are emerging in the field of education. This research aims to examine the development strategies for implementing AI-based learning services in school. Focusing on AI-based math learning service "Math Cell" developed by i-Scream Edu, this study surveyed the functional requirements from the perspective of an educator. The results were analyzed for importance and suitability using IPA, and expert opinions were surveyed to explore specific development directions for the service. Consequently, importance in all areas such as diagnosis, learning, evaluation, and management averaged 4.82 and performance averaged 4.56, showing excellent results in most questions, and in particular, importance was higher than performance. Among certain detailed functions, concept learning, customized task presentation, evaluation result analysis function, dashboard-related functions, and learning materials in the dashboard were not intuitive for students to understand and had to be supplemented. This study provides meaningful insights by summarizing expert opinions on AI-based personalized mathematics learning services, thereby contributing to the exploration of the development strategies for "Math Cell".

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