• Title/Summary/Keyword: 지능형 교육시스템

Search Result 210, Processing Time 0.036 seconds

Toward understanding learning patterns in an open online learning platform using process mining (프로세스 마이닝을 활용한 온라인 교육 오픈 플랫폼 내 학습 패턴 분석 방법 개발)

  • Taeyoung Kim;Hyomin Kim;Minsu Cho
    • Journal of Intelligence and Information Systems
    • /
    • v.29 no.2
    • /
    • pp.285-301
    • /
    • 2023
  • Due to the increasing demand and importance of non-face-to-face education, open online learning platforms are getting interests both domestically and internationally. These platforms exhibit different characteristics from online courses by universities and other educational institutions. In particular, students engaged in these platforms can receive more learner autonomy, and the development of tools to assist learning is required. From the past, researchers have attempted to utilize process mining to understand realistic study behaviors and derive learning patterns. However, it has a deficiency to employ it to the open online learning platforms. Moreover, existing research has primarily focused on the process model perspective, including process model discovery, but lacks a method for the process pattern and instance perspectives. In this study, we propose a method to identify learning patterns within an open online learning platform using process mining techniques. To achieve this, we suggest three different viewpoints, e.g., model-level, variant-level, and instance-level, to comprehend the learning patterns, and various techniques are employed, such as process discovery, conformance checking, autoencoder-based clustering, and predictive approaches. To validate this method, we collected a learning log of machine learning-related courses on a domestic open education platform. The results unveiled a spaghetti-like process model that can be differentiated into a standard learning pattern and three abnormal patterns. Furthermore, as a result of deriving a pattern classification model, our model achieved a high accuracy of 0.86 when predicting the pattern of instances based on the initial 30% of the entire flow. This study contributes to systematically analyze learners' patterns using process mining.

An Adaptive Lesson Plan Generator Based on Case-Based Planning (케이스기반플랜기법에 의한 적응력있는 레슨플렌생성기)

  • Jae-innLee
    • Korean Journal of Cognitive Science
    • /
    • v.4 no.2
    • /
    • pp.85-114
    • /
    • 1994
  • One of the major research topics in the area of the development of intelligent tutoring system(ITS)is the control of instructional mechanism consisting of lesson plans,curriculum plans,and discourse plans.This paper describes a method of building the lesson plans among these three instructional plans based on the case-based planning.It is more efficient to retrieve the lesson plan from the plan memoru than to generate it whenever an instructional goal is selected.The retrieved lesson plan may be modified to build more adaptive plan for the current goal.We have developed a lesson plan generator that has such capabilities as a component of an ITS for teching indefinite intergration.We also have devised a description language to represeint the generalized form for the given arithmetic expression as an instructional goal and a curriculum tree to represent the lesson units required to master the subject matter.The result of this research could be used either by a developer of the lesson plan generator in the other area of ITS or by human teacher as a curriculum in the actual class.

Future Promising Industries and Its Associated Ppuri-Technologies that will Change the World Expected by MOTIE R&D Program Directors(PD) (산업기술 R&D PD가 바라보는 미래 유망산업분야와 뿌리기술)

  • June, Younggun;Ahn, Hyungsu;Kim, Sungduk
    • Transactions of the KSME C: Technology and Education
    • /
    • v.1 no.2
    • /
    • pp.147-152
    • /
    • 2013
  • In this paper, we surveyed the opinion of MOTIE(Ministry of Trade, Industry and Energy) R&D PDs about what are the future promising industries and their mainly associated Ppuri-technologies. According to the survey result, the future technology trends are to shift the technologies beyond their own critical performance and dominate human-centered technologies through converging technologies. In particular, the 4 industries, personalized medical technology, intelligent and emotional-based system, solar power technology and flexible technology, are expected to be good perspective industries in the near future. In order to grow these industries, we need to develop the core Ppuri-technologies that are very closely related to the future main industries. More than all, Ppuri-technology acts as a leverage for the future promising industry and is expected to be the strong supporter in manufacturing infra.

A Design of AI Cloud Platform for Safety Management on High-risk Environment (고위험 현장의 안전관리를 위한 AI 클라우드 플랫폼 설계)

  • Ki-Bong, Kim
    • Journal of Advanced Technology Convergence
    • /
    • v.1 no.2
    • /
    • pp.01-09
    • /
    • 2022
  • Recently, safety issues in companies and public institutions are no longer a task that can be postponed, and when a major safety accident occurs, not only direct financial loss, but also indirect loss of social trust in the company and public institution is greatly increased. In particular, in the case of a fatal accident, the damage is even more serious. Accordingly, as companies and public institutions expand their investments in industrial safety education and prevention, open AI learning model creation technology that enables safety management services without being affected by user behavior in industrial sites where high-risk situations exist, edge terminals System development using inter-AI collaboration technology, cloud-edge terminal linkage technology, multi-modal risk situation determination technology, and AI model learning support technology is underway. In particular, with the development and spread of artificial intelligence technology, research to apply the technology to safety issues is becoming active. Therefore, in this paper, an open cloud platform design method that can support AI model learning for high-risk site safety management is presented.

Analysis of Effect on Pesticide Drift Reduction of Prevention Plants Using Spray Drift Tunnel (비산 챔버를 활용한 차단 식물의 비산 저감 효과 분석)

  • Jinseon Park;Se-Yeon Lee;Lak-Yeong Choi;Se-woon Hong
    • Journal of Bio-Environment Control
    • /
    • v.32 no.2
    • /
    • pp.106-114
    • /
    • 2023
  • With rising concerns about pesticide spray drift by aerial application, this study attempt to evaluate aerodynamic property and collection efficiency of spray drift according to the leaf area index (LAI) of crop for preventing undesirable pesticide contamination by the spray-drift tunnel experiment. The collection efficiency of the plant with 'Low' LAI was measured at 16.13% at a wind speed of 1 m·s-1. As the wind speed increased to 2 m·s-1, the collection efficiency of plant with the same LAI level increased 1.80 times higher to 29.06%. For the 'Medium' level LAI, the collection efficiency was 24.42% and 43.06% at wind speed of 1 m·s-1 and 2 m·s-1, respectively. For the 'High' level LAI, it also increased 1.24 times higher as the wind speed increased. The measured results indicated that the collection of spray droplets by leaves were increased with LAI and wind speed. This also implied that dense leaves would have more advantages for preventing the drift of airborne spray droplets. Aerodynamic properties also tended to increase as the LAI increased, and the regression analysis of quadric equation and power law equation showed high explanatory of 0.96-0.99.

A Comparative Study of the Perceptions by Stakeholder on the Problems and Difficulties at Implementation Stages of the Agricultural Environment Conservation Program (농업환경보전프로그램 이행단계별 문제점 및 애로사항에 대한 이해당사자별 인식 비교)

  • Kim, Soo-Jin;Bae, Seung-Jong;Yoo, Seung-Hwan;Na, Ra;Son, Jeong-Woo;Hur, Seung-Oh
    • Journal of Korean Society of Rural Planning
    • /
    • v.29 no.4
    • /
    • pp.201-210
    • /
    • 2023
  • The Agricultural Environmental Conservation Program is a useful system for creating sustainable agriculture and environmentally friendly and comfortable rural areas. However, there are still many problems and difficulties, such as the establishment of necessary activities and plans by the residents themselves, and improvements are required. The degree of importance and difficulties according to the implementation stage of each stakeholder was quantified and compared with each other, and the specific difficulties recognized by on-site support organizations were structurally analyzed. It was analyzed that the importance and difficulties of the project implementation stage for local government officials and the project implementation planning stage for on-site support organizations were very high, indicating that they perceived the most need for improvement. On the other hand, 21 specific problems and difficulties were derived based on the results of the literature survey and stakeholder interviews. As a result of the structural analysis using the DEMATEL method, the most influential factor was the low understanding of the project by residents, the most influential factor was the lack of collecting and reflecting residents' opinions, the most central factor was the lack of collecting and reflecting residents' opinions, and the most causal factor was the lack of education and promotion of the project. The results indicate that a more stable system can be established if continuous promotion and education, periodic meetings and discussions, active reflection of residents' opinions in project implementation plans, and simplification of implementation inspection and project cost execution through the implementation inspection platform are promoted. Despite the limitations, considering that no institutional analysis of agricultural environmental conservation programs has been conducted so far, the results of this study are expected to serve as a basis for the establishment of relevant policies in the future.

Development of Personalized Learning Course Recommendation Model for ITS (ITS를 위한 개인화 학습코스 추천 모델 개발)

  • Han, Ji-Won;Jo, Jae-Choon;Lim, Heui-Seok
    • Journal of the Korea Convergence Society
    • /
    • v.9 no.10
    • /
    • pp.21-28
    • /
    • 2018
  • To help users who are experiencing difficulties finding the right learning course corresponding to their level of proficiency, we developed a recommendation model for personalized learning course for Intelligence Tutoring System(ITS). The Personalized Learning Course Recommendation model for ITS analyzes the learner profile and extracts the keyword by calculating the weight of each word. The similarity of vector between extracted words is measured through the cosine similarity method. Finally, the three courses of top similarity are recommended for learners. To analyze the effects of the recommendation model, we applied the recommendation model to the Women's ability development center. And mean, standard deviation, skewness, and kurtosis values of question items were calculated through the satisfaction survey. The results of the experiment showed high satisfaction levels in accuracy, novelty, self-reference and usefulness, which proved the effectiveness of the recommendation model. This study is meaningful in the sense that it suggested a learner-centered recommendation system based on machine learning, which has not been researched enough both in domestic, foreign domains.

Development of diet-based personalized nutritional supplement recommendation system (식단 기반 개인 맞춤형 영양제 추천 시스템 개발)

  • Hong, Seong-Jun;Lee, Min-Hee;Jang, Jae-Ri;Jeong, Ha-Eun;Hong, Yu-Ri;Lee, Jee-Hang;Kim, Jin
    • Proceedings of the Korea Information Processing Society Conference
    • /
    • 2022.11a
    • /
    • pp.359-361
    • /
    • 2022
  • 최근 현대인의 영양불균형이 점점 심화됨에 따라 영양결핍과 비만의 위험도가 점점 증가하고 있다. 이에 따라 건강기능식품에 대한 관심이 증가하여 일반인들의 건강기능식품 소비가 증가하고 있지만, 적정섭취량에 비해 영양소를 과도하게 섭취 중이거나 영양제를 먹지만 정작 필요한 영양소를 섭취하지 못하는 경우가 빈번히 나타나고 있다. 이러한 문제를 해소하고자 본 논문에서는 7 일간 사용자가 섭취한 식단을 기반으로 부족한 영양소를 수치상으로 계산하여 개인 맞춤 영양제를 추천하는 시스템을 제안한다.

A Hybrid Knowledge Representation Method for Pedagogical Content Knowledge (교수내용지식을 위한 하이브리드 지식 표현 기법)

  • Kim, Yong-Beom;Oh, Pill-Wo;Kim, Yung-Sik
    • Korean Journal of Cognitive Science
    • /
    • v.16 no.4
    • /
    • pp.369-386
    • /
    • 2005
  • Although Intelligent Tutoring System(ITS) offers individualized learning environment that overcome limited function of existent CAI, and consider many learners' variable, there is little development to be using at the sites of schools because of inefficiency of investment and absence of pedagogical content knowledge representation techniques. To solve these problem, we should study a method, which represents knowledge for ITS, and which reuses knowledge base. On the pedagogical content knowledge, the knowledge in education differs from knowledge in a general sense. In this paper, we shall primarily address the multi-complex structure of knowledge and explanation of learning vein using multi-complex structure. Multi-Complex, which is organized into nodes, clusters and uses by knowledge base. In addition, it grows a adaptive knowledge base by self-learning. Therefore, in this paper, we propose the 'Extended Neural Logic Network(X-Neuronet)', which is based on Neural Logic Network with logical inference and topological inflexibility in cognition structure, and includes pedagogical content knowledge and object-oriented conception, verify validity. X-Neuronet defines that a knowledge is directive combination with inertia and weights, and offers basic conceptions for expression, logic operator for operation and processing, node value and connection weight, propagation rule, learning algorithm.

  • PDF

Digital Transformation: Using D.N.A.(Data, Network, AI) Keywords Generalized DMR Analysis (디지털 전환: D.N.A.(Data, Network, AI) 키워드를 활용한 토픽 모델링)

  • An, Sehwan;Ko, Kangwook;Kim, Youngmin
    • Knowledge Management Research
    • /
    • v.23 no.3
    • /
    • pp.129-152
    • /
    • 2022
  • As a key infrastructure for digital transformation, the spread of data, network, artificial intelligence (D.N.A.) fields and the emergence of promising industries are laying the groundwork for active digital innovation throughout the economy. In this study, by applying the text mining methodology, major topics were derived by using the abstract, publication year, and research field of the study corresponding to the SCIE, SSCI, and A&HCI indexes of the WoS database as input variables. First, main keywords were identified through TF and TF-IDF analysis based on word appearance frequency, and then topic modeling was performed using g-DMR. With the advantage of the topic model that can utilize various types of variables as meta information, it was possible to properly explore the meaning beyond simply deriving a topic. According to the analysis results, topics such as business intelligence, manufacturing production systems, service value creation, telemedicine, and digital education were identified as major research topics in digital transformation. To summarize the results of topic modeling, 1) research on business intelligence has been actively conducted in all areas after COVID-19, and 2) issues such as intelligent manufacturing solutions and metaverses have emerged in the manufacturing field. It has been confirmed that the topic of production systems is receiving attention once again. Finally, 3) Although the topic itself can be viewed separately in terms of technology and service, it was found that it is undesirable to interpret it separately because a number of studies comprehensively deal with various services applied by combining the relevant technologies.