• Journal of the Korean School Mathematics Society
• /
• v.19 no.3
• /
• pp.261-275
• /
• 2016

Many students have dualistic beliefs about mathematics and its learning- for example, there is always just one right answer in mathematics and their role in the classroom is receiving and absorbing knowledge from teacher and textbook. This article investigated some epistemic implications and limitations of common mathematics teaching practices, which often present mathematical facts(or procedures) and treat students' errors in a certain and absolute way. Langer and Piper's (1987) experiment and Oliveira et al.'s (2012) study suggested that presenting knowledge in conditional language which allows uncertainty can foster students' productive epistemological beliefs. Changing the focus and patterns of classroom communication about students' errors could help students to overcome their dualistic beliefs. This discussion will contribute to analyze the implicit epistemic messages conveyed by mathematics instructions and to investigate teaching strategies for stimulating students' epistemic development in mathematics.

• Journal of Gifted/Talented Education
• /
• v.11 no.3
• /
• pp.99-129
• /
• 2001

The purpose of the present study is to determine antecedents in the area of subject matters and to compare these factors between average student group and gifted student group, based on the implicit theory proposed by Sternberg(1993). The average group consisted of 350 primary school students (boy 172; girl 178) from a primary school and 380 middle school students (boy 221; girl 159) from a middle school in Taejeon Metropolitan City. The gifted group consisted of 181 primary school students (boy 130; girl 51) and 154 middle school students (boy 92; girl 62) from the Center for the Gifted Education of the Kong Ju National University. A questionnaire was developed by the authors. It consisted of 30 research questions related to reasons why they studied those subject matters hard. It took about 40 minutes to complete the questionnaire. Several exploratory factor analyses and confirmative analyses were conducted. The main results obtained were as follows: The subject matters all the students of the present study were English and Math. The main reasons why they studied those subject matters hard were interest, utility, competition, self-esteem, entrance examination, recognition, punishment avoidance, etc. A factor analysis revealed that, for the elementary school students, recognition and interest were factors for the average students, whereas knowledge acquisition was an unique factor for the gifted. Utility was common factor for both groups. A factor analysis revealed that, for the middle school students, knowledge acquisition was the main factor for the average students, whereas competition was the unique factor for the gifted. Recognition, interest, and utility were common factors for the both groups.

• (The) Korean Journal of Educational Psychology
• /
• v.32 no.3
• /
• pp.421-442
• /
• 2018

This study aimed to explore the constructs of the characteristics of at-risk learners with diverse educational needs in the blind spots of education, in order to understand them comprehensively and detect them early in schools. Participants were 156 elementary, middle, and high school teachers who filled out a semi-structured questionnaire consisting of open questions about their implicit knowledge of the characteristics of at-risk learners in the blind spots of education. Qualitative data were analyzed using a modified consensual qualitative research method. The main findings of this study are as follows. First, five domains and 16 categories were derived as the main constructs of the characteristics of learners in the blind spots of education. Second, the most listed of the five domains was the "domain of low learning and cognition," whereas the least listed domain was the "everyday life domain." Finally, deficiencies of interpersonal skills and interactive communications and categories related to family structure and functions frequently appeared among the 16 categories. Based on these results, implications and potentials for follow-up studies were further discussed.

• Journal of KIISE:Software and Applications
• /
• v.37 no.4
• /
• pp.282-296
• /
• 2010

OWL is an ontology language for the Semantic Web, and suited to modelling the knowledge of a specific domain in the real-world. Ontology also can infer new implicit knowledge from the explicit knowledge. However, the modeled knowledge cannot be complete as the whole of the common-sense of the human cannot be represented totally. Ontology do not concern handling nonmonotonic reasoning to detect incomplete modeling such as the integrity constraints and exceptions. A default rule can handle the exception about a specific class in ontology. Integrity constraint can be clear that restrictions on class define which and how many relationships the instances of that class must hold. In this paper, we propose a practical reasoning system for open and closed-world reasoning that supports a novel hybrid integration of ontology based on open world assumption (OWA) and non-monotonic rule based on closed-world assumption (CWA). The system utilizes a method to solve the problem which occurs when dealing with the incomplete knowledge under the OWA. The method uses the answer set programming (ASP) to find a solution. ASP is a logic-program, which can be seen as the computational embodiment of non-monotonic reasoning, and enables a query based on CWA to knowledge base (KB) of description logic. Our system not only finds practical cases from examples by the Protege, which require non-monotonic reasoning, but also estimates novel reasoning results for the cases based on KB which realizes a transparent integration of rules and ontologies supported by some well-known projects.

• Journal of The Korean Association For Science Education
• /
• v.40 no.2
• /
• pp.127-140
• /
• 2020

This study investigated the influence of an explicit and reflective modeling instruction on the metamodeling knowledge of fourth-graders. Two fourth-grade classes in an elementary school in Seoul were selected and each class was assigned to an experimental group and a control group, respectively. The experimental group was engaged in explicit and reflective modeling instruction, whereas the control group was engaged in implicit modeling instruction. The two groups were surveyed before and after instruction on the basis of five metamodeling knowledge categories: definition, purpose, design/construction, changeability, and multiplicity. The experimental group showed positive changes in model's meaning, examples, purpose, changeability as well as multiplicity. In contrast, fewer students in the control group understood the meaning of the model and modeling. They also showed limited changes in their understandings with regards to the modeling instruction, and could not expand their understanding of the nature of model and modeling. The findings indicate that an explicit and reflective modeling instruction has positive influence on elementary students' metamodeling knowledge.

• Journal of Korea Spatial Information System Society
• /
• v.1 no.1 s.1
• /
• pp.5-18
• /
• 1999

Recently, the necessity of automatic knowledge extraction from spatial data stored in spatial databases has been increased. Spatial data mining can be defined as the extraction of implicit knowledge, spatial relationships, or other knowledge not explicitly stored in spatial databases. In order to extract useful knowledge from spatial data, an object management system that can store spatial data efficiently, provide very fast indexing & searching mechanisms, and support a distributed computing environment is needed. In this paper, we designed and implemented an open object management system for spatial data mining, that supports efficient management of spatial, aspatial, and knowledge data. In order to develop this system, we used Open OODB that is a widely used object management system. However, the lark of facilities for spatial data mining in Open OODB, we extended it to support spatial data type, dynamic class generation, object-oriented inheritance, spatial index, spatial operations, etc. In addition, for further increasement of interoperability with other spatial database management systems or data mining systems, we adopted international standards such as ODMG 2.0 for data modeling, SDTS(Spatial Data Transfer Standard) for modeling and exchanging spatial data, and OpenGIS Simple Features Specification for CORBA for connecting clients and servers efficiently.

• The KIPS Transactions:PartD
• /
• v.9D no.3
• /
• pp.365-380
• /
• 2002

Temporal data mining, the incorporation of temporal semantics to existing data mining techniques, refers to a set of techniques for discovering implicit and useful temporal knowledge from large quantities of temporal data. Temporal knowledge, expressible in the form of rules, is knowledge with temporal semantics and relationships, such as cyclic pattern, calendric pattern, trends, etc. There are many examples of temporal data, including patient histories, purchaser histories, and web log that it can discover useful temporal knowledge from. Many studies on data mining have been pursued and some of them have involved issues of temporal data mining for discovering temporal knowledge from temporal data, such as sequential pattern, similar time sequence, cyclic and temporal association rules, etc. However, all of the works treated data in database at best as data series in chronological order and did not consider temporal semantics and temporal relationships containing data. In order to solve this problem, we propose a theoretical framework for temporal data mining. This paper surveys the work to date and explores the issues involved in temporal data mining. We then define a model for temporal data mining and suggest SQL-like mining language with ability to express the task of temporal mining and show architecture of temporal mining system.

• The Journal of Information Systems
• /
• v.21 no.2
• /
• pp.161-180
• /
• 2012

One of them is online community which is popular among this modern society. However, it is not appropriate to suggest that online community is solely for personal usage or solely for work-related usage. The usage of online community goes beyond only one purpose. On the other hand, our daily activities whether personal or work-related activities are usually accompanied with preconception ideas whether it is a fun activity or not. However, even with this preconception, individuals are still enjoying themselves while doing activities that are considered as boring or mundane. Furthermore, individuals are really into the activities that they forgot about their surrounding and found themselves being in flow while conducting these activities. Unfortunately, there is little research done in South Korea addressing this emotion related factors. Because of that, more research concerning emotion related factors need to be conducted to better understand users behavior especially in online environment. With regards to that concern, this research studied two distinct everyday activities which are studying and playing games in online community. It is expected that when an individual feels more enjoyable and feels more comfortable, it will be more likely for them to be more satisfied. This satisfaction will lead them to being in a flow state. Hence, this study proposed three hypotheses. In order to investigate these three hypotheses, studies were conducted in two stages. The first stage was conducted in order to derive the implicit knowledge about fun from the participants. The second stage was done by an empirical study. It was conducted with two sample groups. The first group is the study group and the second group is the play games group. There were asked a set of questionnaires related to their enjoyment, comfort, satisfaction and flow while conducting the relevant activity. The results showed that both groups reached the state of flow regardless whether they belong to the study group or play games group. Therefore, the preconception idea about an activity does not promote or prevent individuals from feeling enjoyment, feeling comfortable and achieve satisfaction while conducting those activities.

• Journal of Digital Convergence
• /
• v.15 no.6
• /
• pp.107-119
• /
• 2017

This article explores early childhood teachers' practices from bottom-up perspectives on the relationship between theory and practice. Results of the review of literature are as follows: 1) From top-down perspectives early childhood teachers' practices and their classroom behaviors have been traditionally defined within the framework of theories of child development, the notion of developmentally appropriate practice, and designed program models; 2) From bottom-up perspectives researchers have a focus on how teachers' practices lead theories and how they construct the act of teaching through reflective thinking; 3) empirical research on preservice and inservice teachers demonstrates that preservice teachers develop their own theories of teaching from their previously held assumptions, gained knowledge from preparation programs, and their individual experiences. It also shows that inservice teachers construct teaching through their implicit knowledge and the use of strategies to negotiate problems. Implications for future studies on teachers's practices are discussed.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.30 no.6C
• /
• pp.505-511
• /
• 2005

Autonomic machines interacting with human should have capability to perceive the states of emotion and attitude through implicit messages for obtaining voluntary cooperation from their clients. Voice is the easiest and most natural way to exchange human messages. The automatic systems capable to understanding the states of emotion and attitude have utilized features based on pitch and energy of uttered sentences. Performance of the existing emotion recognition systems can be further improved withthe support of linguistic knowledge that specific tonal section in a sentence is related with the states of emotion and attitude. In this paper, we attempt to improve recognition rate of emotion by adopting such linguistic knowledge for Korean ending boundary tones into anautomatic system implemented using pitch-related features and multilayer perceptrons. From the results of an experiment over a Korean emotional speech database, the improvement of $4\%$ is confirmed.