• Korean Medical Education Review
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• v.21 no.1
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• pp.51-58
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• 2019

Although 'assessment for learning' rather than 'assessment of learning' has been emphasized recently, student learning before examinations is still unclear. The purpose of this study was to investigate pre-assessment learning activities (PALA) and to find mechanism factors (MF) that influence those activities. Moreover, we compared the PALA and MF of written exams with those of the clinical performance examination/objective structured clinical examination (CPX/OSCE) in third-year (N=121) and fourth-year (N=108) medical students. Through literature review and discussion, questionnaires with a 5-point Likert scale were developed to measure PALA and MF. PALA had the constructs of cognitive and meta-cognitive activities, and MF had sub-components of personal, interpersonal, and environmental factors. Cronbach's ${\alpha}$ coefficient was used to calculate survey reliability, while the Pearson correlation coefficient and multiple regression analysis were used to investigate the influence of MF on PALA. A paired t-test was applied to compare the PALA and MF of written exams with those of CPX/OSCE in third and fourth year students. The Pearson correlation coefficients between PALA and MF were 0.479 for written exams and 0.508 for CPX/OSCE. MF explained 24.1% of the PALA in written exams and 25.9% of PALA in CPX/OSCE. Both PALA and MF showed significant differences between written exams and CPX/OSCE in third-year students, whereas those in fourth-year students showed no differences. Educators need to consider MFs that influence the PALA to encourage 'assessment for learning'.

• The Journal of Korean Association of Computer Education
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• v.13 no.4
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• pp.61-68
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• 2010

One often thinks that those doing any activity on the Internet are likely to be addicted to it so that they tend to rather restrain the educational use of what the Internet can provide. However, the online edu-games deserve a good learning material which can not only provoke learners' interest but also draw out a smoother interaction between teachers and learners. Even the preliminary study on immersion verified that the Internet could work positively for the learners. Considering that online edu-games can be a useful tool for individual learning, more studies on immersion should be conducted focusing on the individualization in the future. This paper shows the differences among the components of learning immersion depending on the different individual cognitive styles in the online edu-games.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.5
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• pp.1043-1050
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• 2018

In this paper, we propose a reinforce learning based on cooperative sensing scheme to select optimal secondary users(SUs) to enhance the detection performance of spectrum sensing in Cognitive radio(CR) networks. The SU with high accuracy is identified based on the similarity between the global sensing result obtained through cooperative sensing and the local sensing result of the SU. A fusion center(FC) uses similarity of SUs as reward value for Q-learning to determine SUs which participate in cooperative sensing with accurate sensing results. The experimental results show that the proposed method improves the detection performance compared to conventional cooperative sensing schemes.

• 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.

• Research in Mathematical Education
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• v.12 no.1
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• pp.1-26
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• 2008

The concept field is defined as the schema of all equivalent definitions of a mathematics concept. Concept system is defined as the schema of a group concept network where there are mathematics relations. Proposition field is defined as the schema of all equivalent proposition sets. Proposition system is defined as a schema of proposition sets where one mathematics proposition at least is "derived" from the other proposition. CPFS structure that consists of concept field, concept system proposition field, proposition system describes more precisely mathematics cognitive structure, and reveals the unique psychological phenomena and laws in mathematics learning.

• Journal of Information Processing Systems
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• v.13 no.1
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• pp.8-25
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• 2017

This survey paper explores the application of multimodal feedback in automated systems for motor learning. In this paper, we review the findings shown in recent studies in this field using rehabilitation and various motor training scenarios as context. We discuss popular feedback delivery and sensing mechanisms for motion capture and processing in terms of requirements, benefits, and limitations. The selection of modalities is presented via our having reviewed the best-practice approaches for each modality relative to motor task complexity with example implementations in recent work. We summarize the advantages and disadvantages of several approaches for integrating modalities in terms of fusion and frequency of feedback during motor tasks. Finally, we review the limitations of perceptual bandwidth and provide an evaluation of the information transfer for each modality.

• Korean Journal of Cognitive Science
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• v.12 no.1_2
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• pp.25-34
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• 2001

지식을 관리하는 것에 주력했던 기존의 인공지능 연구 방향은 동적으로 움직이는 외부 환경에서 적응할 수 있는 시스템 구축으로 변화하고 있다. 이러한 시스템의 기본 능력을 이루는 많은 학습방법 중에서 비교적 최근에 제시된 강화학습은 일반적인 사례에 적용하기 쉽고 동적인 환경에서 뛰어난 적응 능력을 보여주었다. 이런 장점을 바탕으로 강화학습은 에이전트 연구에 많이 사용되고 있다. 하지만, 현재까지 연구결과는 강화학습으로 구축된 에이전트로 해결할 수 있는 작업의 난이도에 한계가 있음을 보이고 있다. 특히, 복수의 부분 작업으로 구성되어 있는 작업을 처리할 경우에 기본의 강화학습 방법은 문제 해결에 한계를 보여주고 있다. 본 논문에서는 복수의 부분 작업으로 구성된 작업이 왜 처리하기 힘든가를 분석하고, 이런 문제를 처리할 수 있는 방안을 제안한다. 본 논문에서 제안하고 있는 EQ-Learning의 강화학습 방법의 대표적인 Q-Learning을 확장시켜 문제를 해결한다. 이 방법은 각각의 부분 작업 해결 방안을 학습시키고 그 학습 결과들의 적절한 순서를 찾아내 전체 작업을 해결한다. EQ-Learning의 타당성을 검증하기 위해 격자 공간에서 복수의 부분작업으로 구성된 미로 문제를 통하여 실험하였다.

• Journal of The Korean Association For Science Education
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• v.16 no.4
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• pp.441-450
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• 1996

Various contexts are involved in the processes of science learning and instruction. In the perspective that the results of science learning and instruction usually depend on the nature of learning task content and context, content effects or context effects have been researched up to now. But, the discrimination between them was very ambiguous. For the clarity of them, it was supposed that science content would be composed of decontextualized knowledges and contexts, which were respectively dichotomized in common and special ones among disciplines of science. Science learning and instruction was discussed in view of interactions between cognitive, learning task, and social-cultural contexts. Especially, it was emphasized that task contexts, as a bridging role among contexts should be constructed considering cognitive and social cultural contexts.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.3
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• pp.98-112
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• 2024

As digital education progresses, MOOC (Massive Open Online Courses) are increasingly utilized by learners, making research on MOOC learning outcomes a necessary endeavor. In this study, we systematically investigated the impact of audiovisual elements on learning outcomes in MOOC, highlighting the nuanced role these components play in enhancing educational effectiveness. Through a comprehensive survey and rigorous analysis involving descriptive statistics, reliability metrics, and regression techniques, we quantified the influence of text, graphics, color, teacher images, sound effects, background music, and teacher's voice on learner attention, cognitive load, and satisfaction. We discovered that background music and text layout significantly improve engagement and reduce cognitive burden, underscoring their pivotal role in the instructional design of MOOC. We findings contribute new insights to the field of digital education, emphasizing the critical importance of integrating audiovisual elements thoughtfully to foster better learning environments and outcomes. Not only advances academic understanding of multimedia learning impacts but also offers practical guidance for educators and course designers seeking to enhance the efficacy of MOOC.

• The Journal of Information Systems
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• v.27 no.2
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• pp.1-28
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• 2018

Purpose More than 7.6 million mobile apps could be approved on both Apple iTunes Store and Google Play. For managing those existed Apps, Apple Inc. established twenty-four primary categories, as well as Google Play had thirty-three primary categories. However, all of their categorizations have appeared more and more problems in managing and classifying numerous apps, such as app miscategorized, cross-attribution problems, lack of categorization keywords index, etc. The purpose of this study focused on introducing individual information cognitive processing as the classification criteria to update the current categorization on Apple iTunes Store. Meanwhile, we tried to observe the effectiveness of the new criteria from a classification process on Apple iTunes Store. Design/Methodology/Approach A research approach with four research stages were performed and a series of mixed methods was developed to identify the feasibility of adopting individual information cognitive processing as categorization criteria. By using machine-learning techniques with Term Frequency-Inverse Document Frequency and Singular Value Decomposition, keyword lists were extracted. By using the prior research results related to car app's categorization, we developed individual information cognitive processing. Further keywords extracting process from the extracted keyword lists was performed. Findings By TF-IDF and SVD, keyword lists from more than five thousand apps were extracted. Furthermore, we developed individual information cognitive processing that included a categorization teaching process and learning process. Three top three keywords for each category were extracted. By comparing the extracted results with prior studies, the inter-rater reliability for two different methods shows significant reliable, which proved the individual information cognitive processing to be reliable as criteria of categorization on Apple iTunes Store. The updating suggestions for Apple iTunes Store were discussed in this paper and the results of this paper may be useful for app store hosts to improve the current categorizations on app stores as well as increasing the efficiency of app discovering and locating process for both app developers and users.