• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.17 no.12
• /
• pp.3266-3285
• /
• 2023

With the popularity of online learning, intelligent tutoring systems are starting to become mainstream for assisting online question practice. Surrounded by abundant learning resources, some students struggle to select the proper questions. Personalized question recommendation is crucial for supporting students in choosing the proper questions to improve their learning performance. However, traditional question recommendation methods (i.e., collaborative filtering (CF) and cognitive diagnosis model (CDM)) cannot meet students' needs well. The CDM-based question recommendation ignores students' requirements and similarities, resulting in inaccuracies in the recommendation. Even CF examines student similarities, it disregards their knowledge proficiency and struggles when generating questions of appropriate difficulty. To solve these issues, we first design an enhanced cognitive diagnosis process that integrates students' affection into traditional CDM by employing the non-compensatory bidimensional item response model (NCB-IRM) to enhance the representation of individual personality. Subsequently, we propose an affection-enhanced personalized question recommendation (AE-PQR) method for online learning. It introduces NCB-IRM to CF, considering both individual and common characteristics of students' responses to maintain rationality and accuracy for personalized question recommendation. Experimental results show that our proposed method improves the accuracy of diagnosed student cognition and the appropriateness of recommended questions.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.20 no.2
• /
• pp.49-61
• /
• 2024

This study developed an online learning support program to provide academic support for students on academic probation by considering the positive perception and advantages of online education and at the same time reflecting the difficulty in contacting students who have been placed on academic probation. The program consisted of topics and contents that could increase academic self-management and academic resilience of college students on academic probation, and the purpose was to verify the effectiveness of the online learning support program after operation. The research results are as follows. There was a significant difference in academic self-management, learning regulation, and positive attitude of college students on academic probation. This can be seen as the fact that college students on academic probation acquired the knowledge, skills, and attitudes necessary for studying, and their determination to study had a positive effect on their academic resilience. The significance of this study is that it developed a program that can help improve the academic resilience of college students on academic probation and analyzed its effectiveness.

• Geomechanics and Engineering
• /
• v.25 no.1
• /
• pp.1-16
• /
• 2021

Machine learning models have been widely used for landslide susceptibility assessment (LSA) in recent years. The large number of inputs or conditioning factors for these models, however, can reduce the computation efficiency and increase the difficulty in collecting data. Feature selection is a good tool to address this problem by selecting the most important features among all factors to reduce the size of the input variables. However, two important questions need to be solved: (1) how do feature selection methods affect the performance of machine learning models? and (2) which feature selection method is the most suitable for a given machine learning model? This paper aims to address these two questions by comparing the predictive performance of 13 feature selection-based machine learning (FS-ML) models and 5 ordinary machine learning models on LSA. First, five commonly used machine learning models (i.e., logistic regression, support vector machine, artificial neural network, Gaussian process and random forest) and six typical feature selection methods in the literature are adopted to constitute the proposed models. Then, fifteen conditioning factors are chosen as input variables and 1,017 landslides are used as recorded data. Next, feature selection methods are used to obtain the importance of the conditioning factors to create feature subsets, based on which 13 FS-ML models are constructed. For each of the machine learning models, a best optimized FS-ML model is selected according to the area under curve value. Finally, five optimal FS-ML models are obtained and applied to the LSA of the studied area. The predictive abilities of the FS-ML models on LSA are verified and compared through the receive operating characteristic curve and statistical indicators such as sensitivity, specificity and accuracy. The results showed that different feature selection methods have different effects on the performance of LSA machine learning models. FS-ML models generally outperform the ordinary machine learning models. The best FS-ML model is the recursive feature elimination (RFE) optimized RF, and RFE is an optimal method for feature selection.

• Human Ecology Research
• /
• v.60 no.2
• /
• pp.187-209
• /
• 2022

The objective of this study was to conduct a 'Theory of Home Economics Education' class using online problem-based learning(PBL) for prospective home economics(HE) teachers. The aim was to enable teachers to analyze the learning experience in the classroom, and to prepare operational strategies for online PBL on this basis. In order to achieve this, online PBL was applied to 31 students participating in the 'Theory of Home Economics Education' at the Department of HE in a university in Seoul, and the results were collected from the learning process. This also involved a reflective journal, a survey on the learning experience and the impacts was conducted. Moreover, analysis was undertaken on the learning activities, learning difficulties, and improvements. The main research results are as follows. Firstly, students accessed Webex, an online video conferencing program, and performed two PBL tasks: 'Making Home Economics Promotion Materials' and 'Presenting Teaching Strategies to Improve Learner's Immersion in Online Classes'. Secondly, learners established their own identity of HE learned about the HE class plans themselves. They also encountered realistic experience as HE teachers and learned communication and collaboration skills. Furthermore, they acquired creative problem-solving and self-directed learning ability, community consciousness, as well as the attitude of consideration and respect. Thirdly, students lacked knowledge of learning content and encountered difficulty in solving data research, analysis processes, and unstructured problems. They were affected by a lack of time and encountered problem in communicating with other team members in an online environment. As an improvement in online class operation, it was considrered necessary to reduce the learning burden by securing time and reducing the number of assignments, as well as to explain active interaction with instructors and PBL.

• Journal of Educational Research in Mathematics
• /
• v.9 no.1
• /
• pp.295-309
• /
• 1999

The primary purpose of this study is to investigate problems with the current mathematics textbook. According to a survey, the following were the findings: Textbook is only a tool-book for introducing mathematical facts. It is a unique book for all students possessing different level of mathematical ability. There is difficulty in teaming math using technological devices and in activating(mental and concrete) manipulative activities. There is difficulty in communicating while doing mathematics. There is lack of defined and developed layout of textbook, et. al. It can be however found that these problems can be solved to some degrees, when mathematics textbook is developed based on constructivism. Recently, in mathematics education, it has been gradually emphasized that constructivism can be powerful in teaching and learning mathematics. There are however some difficulties in developing mathematics textbooks to reflect constructivism, such as to fill the gap between the contents written in the national curriculum determined in advance and the contents which students construct psychologically or socially in mathematics class.

• The Journal of Korean Association of Computer Education
• /
• v.6 no.2
• /
• pp.121-135
• /
• 2003

This paper proposes a web-based adaptive tutoring system based on fuzzy set that provides learning materials and questions dynamically according to students' knowledge state, and gives advices for the learning after an evaluation. For this, we design a courseware knowledge structure systematically and then construct a fuzzy level set on the basis of it considering importance of learning targets, difficulty of learning materials and relation degree between learning targets and learning materials. Using the fuzzy level set, our system offers learning materials and questions to adapt to individual students. Moreover, a result of the test is evaluated with fuzzy linguistic variable. Appling the fuzzy concept to the tutoring system could naturally consider and deal with various and uncertain items of learning environment thus could offer more flexible and effective instruction-learning methods.

• Journal of the Korea Convergence Society
• /
• v.9 no.6
• /
• pp.209-215
• /
• 2018

The college liberal arts mathematics is opened as a required course in science and engineering field, but students with low achievement experience difficulty in learning. Therefore, flip learning, which is well known as an effective teaching method based on self-led and learner, is suggested as an alternative. However, some problems are pointed out in this pedagogy. As an alternative to flip learning, we apply flip PBL classes that apply PBL to flip learning to general math subjects to supplement the problems of existing flip learning classes and increase interest in mathematics I want to know the effectiveness of whether it can be done. In this study, we investigated the educational effectiveness of the comparison study between the experimental group applying flip PBL class and the control group applying the existing flip learning class. First, the experimental group showed higher than the control group by 22 points Second, in the reflection journal analysis, in contrast to the control group, there was a positive effect on the improvement of the interest of the mathematics in the experimental group, It is expected that it will be applied as a teaching method that can complement the learning.

• Journal of The Korean Association For Science Education
• /
• v.21 no.1
• /
• pp.59-75
• /
• 2001

While previous studies have recognized and have researched the resistance of students' scientific conception to change and the difficulty of the change of a conception's status, few have investigated the idea of conceptual ecology as a context of conceptual change learning, including the role that affective and motivational aspects might play when students are exposed to conceptual change learning, The present study was conducted to describe in detail high school students' views about learning and knowing science by summarizing of students' conceptual ecologies. The study was interpretive, using multiple data sources to achieve a triangulation of data. Three students from a public high school for boys serve as cases representative of students' views about learning and knowing science. Students' enthusiasm to pursue science was closely connected to their views about learning and knowing science. Students' views about learning and knowing science are influenced by their views regarding science and science class including the nature of knowledge, learning, and their epistemological commitments, They influence students' self-efficacy and motivation on learning science.

• Korean Medical Education Review
• /
• v.15 no.1
• /
• pp.46-53
• /
• 2013

The purpose of this study was to analyze the relationship among medical students' learning motivation, characteristics of multiple intelligence, and academic achievement. The participants were 144 medical students. The data were collected by administering learning motivation tests (self-confidence, self-efficacy, level of task, emotion of learning, learning behavior, failure tolerance, task difficulty, and academic self-efficacy), a multiple intelligence test (linguistic intelligence, logical-mathematical intelligence, musical intelligence, bodily-kinesthetic intelligence, spatial intelligence, interpersonal intelligence, intrapersonal intelligence, and naturalistic intelligence), and two semesters of grades. There is a correlation between multiple intelligences and learning motivation. Among academic self-efficacy of academic motivation, the self-control efficacy (0.28) and behavior (0.18) subscales are significantly positively correlated with academic achievement. However, the emotion subscale (-0.18) was significantly negatively correlated. Learning motivation was correlated with two of the eight multiple intelligence profiles: the intrapersonal intelligence (0.18) and bodily-kinesthetic intelligence (-0.19). The structural equation modeling analysis showed that the behavior and self-control efficacy subscales of intrapersonal intelligence had an impact on academic achievement. An analysis according to the academic achievement group showed significant differences in self-control efficacy and emotion subscales with intrapersonal intelligence. A positive relationship can be observed between learning motivation and some characteristics of multiple intelligence of medical school students. In light of the findings, it is worth examining whether we can control medical students' learning motivation through educational programs targeting self-control efficacy and intrapersonal intelligence.

• Journal of Digital Convergence
• /
• v.19 no.5
• /
• pp.57-67
• /
• 2021

This study explores what factors influence college students' synchronous online learning satisfaction and what advantages and disadvantages exist when it comes to taking synchronous online learning courses. In-depth interview results suggest that advantages of synchronous online learning are convenience (no need for travel, no limitation for study place), saving money, and no worry for contracting Corona 19. However, disadvantages of synchronous online learning are instability of online learning system, lack of interaction between learners and educators, difficulty of instant communication, low education quality, and unfairness of exams. This study found that college students taking synchronous online course think that synchronous online learning is more appropriate for theory-based course than practice-based courses in that theory-based courses are lecture-oriented while practice-based courses require interactivity between learners and educators. This study provides educators a baseline understanding on how college students think over synchronous online learning and how to enhance students' satisfaction with synchronous online learning.