• The Journal of the Korea Contents Association
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• v.18 no.6
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• pp.63-72
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• 2018

This study was conducted to explore the impact of learning strategies on the level of participation in the online collaborative learning process. To do this, We studied 91 students who took professorship courses at A university in the Seoul metropolitan area. At the beginning of the semester, the learning strategies were measured through MSLQ, rehearsal, elaboration, organizing, critical thinking, metacognition, learning management, effort control, peer learning, and seeking help. Next, cooperative tasks were carried out to measure the interaction, and group composition consisted of 4-5 persons. The level of participation was measured by scores given to the messages created for interaction. The process of collaborative learning was divided into the steps of identifying learning goals, learning plans, performing individual learning, sharing learning results, and writing reports. The effects of learning strategies on participation level were analyzed through multiple regression analysis (stepwise selection method). As a result, the learning goal step influenced the highest level of metacognition, and the learning plan is the management of the learning time, the demonstration of the learning execution, the adjustment of the effort, the acquisition of help, the collegial learning, Writing was influenced by organization, elaboration, critical thinking, and critical thinking, metacognition, and elaboration.

• Journal of Engineering Education Research
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• v.25 no.2
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• pp.13-21
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• 2022

In many existing studies, the analyses on the application and effect of the project-based learning model (PBL), a student-centered teaching and learning strategy, have been emphasized and carried out in various majors and courses. This case study analyzes the effects of applying a project-based learning model to the engineering accounting course for engineering students in 2021 in the context of the COVID-19 pandemic, compared with the offline course in 2019 and the simple online course in 2020. Project team consisting of 2-3 students carried out online collaborative learning activities for solving open-ended problems through the 5-step PBL procedure including presenting the final result. Except for this online PBL application in 2021, textbooks, lecture contents, assignments, and tests were implemented the same for each semester for three years. Through lecture evaluation and survey by students, the online PBL application semester showed higher effects in inducing student-centered learning, lecture satisfaction, and student competency improvement compared to the non-applying semesters, further, it was evaluated that the online PBL application to the course and evaluation method were more appropriate than other semesters. It is expected that the online PBL method and operation procedure applied in this study can be utilized as a best practice for the design and operation of various online courses for student-centered collaborative learning activities and educational effects.

• Journal of The Korean Association of Information Education
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• v.11 no.3
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• pp.359-369
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• 2007

Model-centered instruction which presents expert mental model before or during learning can facilitate and help novice learners' problem solving process. During six phases of cognitive apprenticeship model which is a method for applying model centered instruction theory, collaborative learning strategy can maximize articulation and reflection of novice learners. This article presents results of a study that investigated the effects of model-centered instruction and collaborative learning on the learning of instructional design process for pre-service teachers attending a computer education class at an education university.

• Journal of the Korea Society of Computer and Information
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• v.19 no.4
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• pp.101-109
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• 2014

This paper aims to design and implement a collaborative learning system based on the augmented reality. The existing augment reality-based learning systems have just focused on interactivity between a system and learners without consideration of cooperability, thereby leading to an ineffective approach to encouraging an learning system to be more supportive and conducive of and to cooperation among learners. The collaborative learning system is a learning method, with which learners achieve a common objective through critical thinking and cooperative teamwork so as to seek solutions to such fulfillment. This requires positive interdependence, proactive interactions, a sense of responsibility shared by individuals as well as the group, and development of teamwork among learners. Educators and systems assume a critical role in helping the collaborative education be effective. An educator is responsible for defining a project at the outset of learning activities, organizing groups for learners, and providing evaluation criteria applied to a group's project activities. Meanwhile, a system shall support interactions to take place while facilitating learning activities. Furthermore, an educator shall provide a system for managing and evaluating activities involving interactions among learners. This paper suggests and embodies a collaborative learning system based on the augmented reality with consideration of the aforementioned collaborative education.

• Journal of the Korean Society for Library and Information Science
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• v.48 no.3
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• pp.193-215
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• 2014

This study examines undergraduate nursing students' user satisfaction and affective experience of collaborative information behavior in a group-based learning through survey method to see the relationship between these factors. For this purpose, the affective experiences (positive and negative aspects) of collaborative information search were examined using the PANAS scale through the same questionnaire. Correlation between students' experiences of collaborative information search and affective aspects were examined, and statistical significance using the t-test were also conducted to measure the relationship among students' demographic factors, experiences of collaborative information search and affective aspects. The results revealed that there was a significant correlation between experiences of collaborative information search and affective aspects. Also, there were significant relationships among students' demographic factors, experiences of collaborative information search and affective aspects. In particular, there were signigicant differences in students' overall satisfaction of collaboration and positive aspects between male and female students who experienced collaborative information search. This study found out the possibilities for a follow-up study for affective aspects in collaborative information behavior.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.7
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• pp.2399-2413
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• 2021

A recommendation system is an information filter tool, which uses the ratings and reviews of users to generate a personalized recommendation service for users. However, the cold-start problem of users and items is still a major research hotspot on service recommendations. To address this challenge, this paper proposes a high-efficient hybrid recommendation system based on Fuzzy C-Means (FCM) clustering and supervised learning models. The proposed recommendation method includes two aspects: on the one hand, FCM clustering technique has been applied to the item-based collaborative filtering framework to solve the cold start problem; on the other hand, the content information is integrated into the collaborative filtering. The algorithm constructs the user and item membership degree feature vector, and adopts the data representation form of the scoring matrix to the supervised learning algorithm, as well as by combining the subjective membership degree feature vector and the objective membership degree feature vector in a linear combination, the prediction accuracy is significantly improved on the public datasets with different sparsity. The efficiency of the proposed system is illustrated by conducting several experiments on MovieLens dataset.

• Journal of The Korean Association of Information Education
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• v.19 no.1
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• pp.87-98
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• 2015

Robotics education in elementary school, It is difficult for girls to continue the motivation and willingness to learn because of a negative attitude and low recognition against the machine. In this paper, we studied method to improve the learning attitude through STEAM-based robotics education utilizing storytelling and robot smart learning system for elementary school girls. The curriculum is composed of nine themes which are selected from famous classic fairy tales for girls and we developed robot smart learning system which allows girls to enjoy robot design&control, collaborative learning, and sharing their ideas by using smart-phone. As a t-test results of learning attitude, the two groups showed statistically significant difference, the experimental group was higher average than the control group in terms of learning attitude. The robot smart learning system is effective for collaborative learning activities and maintaining learning motivation of elementary school girls.

• The Journal of Korean Academic Society of Nursing Education
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• v.20 no.4
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• pp.577-586
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• 2014

Purpose: This study investigates patterns of small group interaction and examines the influence among graduate nursing students of online collaborative learning strategies on small group interaction patterns, task performance and learning attitude in web-based team learning environments. Method: To analyze patterns of small group interaction, group discussion dialogues were reviewed by two instructors. Groups were divided into two categories depending on the type of feedback given (passive or active). For task performance, evaluation of learning processes and numbers of postings were examined. Learning attitude toward group study and coursework were measured via scales. Results: Explorative interactions were still low among graduate nursing students. Among the students given active feedback, considerable individual variability in interaction frequency was revealed and some students did not show any specific type of interaction pattern. Whether given active or passive feedback, groups exhibited no significant differences in terms of task performance and learning attitude. Also, frequent group interaction was significantly related to greater task performance. Conclusion: Active feedback strategies should be modified to improve task performance and learning attitude among graduate nursing students.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.12
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• pp.3266-3285
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• 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 the Institute of Electronics Engineers of Korea CI
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• v.47 no.4
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• pp.11-17
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• 2010

In this paper, we propose a recommendation system for supporting self-directed programming language education. The system is a recommendation system using collaborative filtering based on learners' level and stage. In this study, we design a recommendation system which uses collaborative filtering based on learners' profile of their level and correlation profile between learning topics in order to increase self-directed learning effects when students plan their learning process in e-learning environment. This system provides a way for solving a difficult problem, that is providing programming problems based on problem solving ability, in the programming language education system. As a result, it will contribute to improve the quality of education by providing appropriate programming problems in learner"s level and e-learning environment based on teaching and learning method to encourage self-directed learning.