• Title/Summary/Keyword: 학습 요소

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Characteristics of Teacher Help and Student Response in Small Group Thinking Science Activities (Thinking Science의 모둠별 활동에 나타나는 교사 도움과 학생 반응의 특성)

  • Ha, Eun-Jung;Choi, Byung-Soon;Shin, Ae-Kyung;Kang, Seong-Joo
    • Journal of The Korean Association For Science Education
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    • v.26 no.2
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    • pp.212-221
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    • 2006
  • The purposes of this study were to examine the characteristics of teacher help in small group Thinking Science(TS) activities and analyze the way students respond to teacher help. For this study, twenty-four 5th grade and twenty-four 7th grade students were selected, to undertake TS activities. Out of the 8 activities students participated in, the verbal interactions in activity 4 and 6, by students in four small groups, which incorporated relatively active argumentation was analyzed. Students' cognitive level was identified through a science reasoning task and the students were grouped heterogeneously according to their cognitive level. This study showed that teachers predominately used simple confirmation questions in preference to metacognitive question. Also, teacher help varied according to one's personal traits, work experience and degree of activity recognition. It was discovered that when the teacher provided student appropriate metacognitive questions and sufficient feedback, students actively engaged in argumentation. On the other hand, when the teacher asked simple confirmation questions and interfered in the activity, students did not participate in argumentation actively.

Parents' Perceptions of Cognitive Rehabilitation for Children With Developmental Disabilities: A Mixed-Method Approach of Phenomenological Methodology and Word Cloud Analysis (발달장애 아동 부모의 인지재활 경험에 대한 질적 연구: 워드 클라우드 분석과 현상학적 연구 방법 혼합설계)

  • Ju, Yu-Mi;Kim, Young-Geun;Lee, Hee-Ryoung;Hong, Seung-Pyo;Han, Dae-Sung
    • Therapeutic Science for Rehabilitation
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    • v.13 no.1
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    • pp.49-63
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    • 2024
  • Objective : The purpose of this study was to investigate parental perspectives on cognitive rehabilitation using a combination of phenomenological research methodology and word cloud analysis. Methods : Interviews were conducted with five parents of children with developmental disabilities. Word cloud analysis was conducted using Python, and five researchers analyzed the meaning units and themes using phenomenological methods. Words with high frequency were considered as a heuristic tool. Results : A total of 43 meaning units and nine components related to the phenomenon of cognitive rehabilitation were derived, and three themes were finalized. The main themes encompassed the definition of cognitive rehabilitation, challenges associated with cognitive rehabilitation, and factors influencing the selection of a cognitive rehabilitation institute. Cognitive rehabilitation emerged as a treatment focused on improving learning, daily functioning, and cognitive abilities in children with developmental disabilities. The perceived issues with cognitive rehabilitation pertained to treatment methods, therapist expertise, and associated costs. In addition, parents highlighted the importance of therapist expertise, humane personality, and affordability of cost and schedule when choosing a cognitive rehabilitation institute. Conclusion : Parents expressed expectations for substantial improvements in their children's daily functioning through cognitive rehabilitation. However, challenges were identified in clinical practices. Going forward, we expect that cognitive rehabilitation will evolve into a better therapeutic support service addressing the concerns raised by parents.

Estimation of Frost Occurrence using Multi-Input Deep Learning (다중 입력 딥러닝을 이용한 서리 발생 추정)

  • Yongseok Kim;Jina Hur;Eung-Sup Kim;Kyo-Moon Shim;Sera Jo;Min-Gu Kang
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.26 no.1
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    • pp.53-62
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    • 2024
  • In this study, we built a model to estimate frost occurrence in South Korea using single-input deep learning and multi-input deep learning. Meteorological factors used as learning data included minimum temperature, wind speed, relative humidity, cloud cover, and precipitation. As a result of statistical analysis for each factor on days when frost occurred and days when frost did not occur, significant differences were found. When evaluating the frost occurrence models based on single-input deep learning and multi-input deep learning model, the model using both GRU and MLP was highest accuracy at 0.8774 on average. As a result, it was found that frost occurrence model adopting multi-input deep learning improved performance more than using MLP, LSTM, GRU respectively.

Automatic scoring of mathematics descriptive assessment using random forest algorithm (랜덤 포레스트 알고리즘을 활용한 수학 서술형 자동 채점)

  • Inyong Choi;Hwa Kyung Kim;In Woo Chung;Min Ho Song
    • The Mathematical Education
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    • v.63 no.2
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    • pp.165-186
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    • 2024
  • Despite the growing attention on artificial intelligence-based automated scoring technology as a support method for the introduction of descriptive items in school environments and large-scale assessments, there is a noticeable lack of foundational research in mathematics compared to other subjects. This study developed an automated scoring model for two descriptive items in first-year middle school mathematics using the Random Forest algorithm, evaluated its performance, and explored ways to enhance this performance. The accuracy of the final models for the two items was found to be between 0.95 to 1.00 and 0.73 to 0.89, respectively, which is relatively high compared to automated scoring models in other subjects. We discovered that the strategic selection of the number of evaluation categories, taking into account the amount of data, is crucial for the effective development and performance of automated scoring models. Additionally, text preprocessing by mathematics education experts proved effective in improving both the performance and interpretability of the automated scoring model. Selecting a vectorization method that matches the characteristics of the items and data was identified as one way to enhance model performance. Furthermore, we confirmed that oversampling is a useful method to supplement performance in situations where practical limitations hinder balanced data collection. To enhance educational utility, further research is needed on how to utilize feature importance derived from the Random Forest-based automated scoring model to generate useful information for teaching and learning, such as feedback. This study is significant as foundational research in the field of mathematics descriptive automatic scoring, and there is a need for various subsequent studies through close collaboration between AI experts and math education experts.

The Effect of Mathematics Classes Using AlgeoMath on Mathematical Problem-Solving Ability and Mathematical Attitude: Focusing on the 'Cuboid' Unit of the Fifth Grade in Elementary School (알지오매스 기반 수업이 수학적 문제해결력 및 태도에 미치는 효과: 초등학교 5학년 '직육면체' 단원을 중심으로)

  • Seung Dong Lee;Jong Hak Lee
    • Journal of Science Education
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    • v.48 no.1
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    • pp.47-62
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    • 2024
  • The purpose of this study is to investigate the effects of classes using AlgeoMath on fifth grade elementary students' mathematical problem-solving skills and mathematical attitudes. For this purpose, the 'cuboid' section of the 5th grade elementary textbook based on AlgeoMath was reorganized. A total of 8 experimental classes were conducted using this teaching and learning material. And the quantitative data collected before and after the experimental lesson were statistically analyzed. In addition, by presenting instances of experimental lessons using AlgeoMath, we investigated the effectiveness and reality of classes using engineering in terms of mathematical problem-solving ability and attitude. The results of this study are as follows. First, in the mathematical problem-solving ability test, there was a significant difference between the experimental group and the comparison group at the significance level. In other words, lessons using AlgeoMath were found to be effective in increasing mathematical problem-solving skills. Second, in the mathematical attitude test, there was no significant difference between the experimental group and the comparison group at the significance level. However, the average score of the experimental group was found to be higher than that of the comparison group for all sub-elements of mathematical attitude.

A Study on the Extraction of Psychological Distance Embedded in Company's SNS Messages Using Machine Learning (머신 러닝을 활용한 회사 SNS 메시지에 내포된 심리적 거리 추출 연구)

  • Seongwon Lee;Jin Hyuk Kim
    • Information Systems Review
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    • v.21 no.1
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    • pp.23-38
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    • 2019
  • The social network service (SNS) is one of the important marketing channels, so many companies actively exploit SNSs by posting SNS messages with appropriate content and style for their customers. In this paper, we focused on the psychological distances embedded in the SNS messages and developed a method to measure the psychological distance in SNS message by mixing a traditional content analysis, natural language processing (NLP), and machine learning. Through a traditional content analysis by human coding, the psychological distance was extracted from the SNS message, and these coding results were used for input data for NLP and machine learning. With NLP, word embedding was executed and Bag of Word was created. The Support Vector Machine, one of machine learning techniques was performed to train and test the psychological distance in SNS message. As a result, sensitivity and precision of SVM prediction were significantly low because of the extreme skewness of dataset. We improved the performance of SVM by balancing the ratio of data by upsampling technique and using data coded with the same value in first content analysis. All performance index was more than 70%, which showed that psychological distance can be measured well.

Study on the Expression of Sensory Visualization through AR Display Connection - Focusing on Eye Tracking (AR 디스플레이 연결을 통한 감각시각화에 대한 표현 검토)

  • Ma Xiaoyu
    • The Journal of the Convergence on Culture Technology
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    • v.10 no.2
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    • pp.357-363
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    • 2024
  • As AR display virtual technology enters public learning life extensively, the way in which reality and virtual connection are connected is also changing. The purpose of this paper is to study the expression between the 3D connection sensory information visualization experience and virtual reality enhancement through the visual direction sensory information visualization experience of the plane. It is analyzed by examining the basic setting method compared to the current application of AR display and flat visualization cases. The scope of this paper is to enable users to have a better experience through the relationship with sensory visualization, centering on eye tracking technology in the four categories of AR display connection design: gesture connection, eye tracking, voice connection, and sensor. Focusing on eye tracking technology through AR display interaction and current application and comparative analysis of flat visualization cases, the geometric consistency of visual figures, light and color consistency, combination of multi-sensory interaction methods, rational content display, and smart push presented sensory visualization in virtual reality more realistically and conveniently, providing a simple and convenient sensory visualization experience to the audience.

Trends and Issues of the Korean National Curriculum Documents' Subject-Matter Content System Table: Focusing on the Science Subject Case (우리나라 국가 교육과정 문서상 교과 내용 체계표의 변천과 쟁점 -과학과 사례를 중심으로-)

  • Gyeong-Geon, Lee
    • Journal of The Korean Association For Science Education
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    • v.44 no.1
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    • pp.87-103
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    • 2024
  • The content system table of the subject-matter curriculum is considered important in the Korean national curriculum, textbook writing, and teaching and learning in the classroom. However, studies that comprehensively organize the issues concerning the format of the subject-matter curriculum content system have been scarce. This study scrutinized the evolution of the content system from its inception in The 6th Curriculum to the most recent 2022 Revised National Curriculum, focusing on science curricular. The following issues and suggestions were derived for the format of the subject content system. First, caution should be exercised in using terms such as "domain," "field," and "category," and it should be clarified whether these terms are intended simply for logical differentiation or to serve as a content organizer with a specific emphasis. Second, the nature of components such as "core ideas," which can serve as innovative content organizers, should be strictly defined. Third, while the introduction of three-dimensional content elements such as "knowledge and understanding," "process and skill," and "value and attitude" is viewed positively, it is suggested that a further delineation be made, elaborating how each can be utilized to form core competencies. Fourth, the construction of the subject-specific content system in national curriculum needs caution because whether it will resolve or exacerbate the 'disparity between general curriculum and subject-matter curriculums' is uncertain. Finally, as an apparent pendulum motion of the subject-matter content system is observed in national curriculum documents, efforts should be made to ensure that it does not result in meaningless repetition, but instead achieves meaningful dialectical progress.

Student difficulties in constructed-response mathematics assessments: A case study of writing activities for low-performing first-year high school students (수학 서술형 평가의 어려움과 지도 방안: 고교 1학년 노력형 학생의 쓰기 활동 사례 연구)

  • Mihui Bae;Woong Lim
    • The Mathematical Education
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    • v.63 no.1
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    • pp.1-18
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    • 2024
  • This study aims to analyze low-performing high school students' difficulties in constructed response (CR) mathematics assessments and explore ways to use writing activities to support student learning. The participants took CR assessments, engaged in guided writing activities across 15 lessons, and provided responses to our interviews. The study identified 20 types of student difficulties, which were sorted into two main categories: "mathematical difficulties" and "CR difficulties." The difficult nature of mathematics as a school subject included a lack of understanding of mathematical concepts, students' difficulty with mathematical symbols and notations, and struggles with word problems. Challenges specific to CR assessments included students' difficulties arising from the testing conditions unlike those of multiple-choice items, and included issues related to constructing appropriate responses and psychological barriers. To address these challenges in CR assessments, the study conducted guided writing activities as an intervention, through which six themes were identified: (1) internalization of mathematical concepts, (2) mathematical thinking through relational understanding, (3) diverse problem-solving methods, (4) use of mathematical symbols, (5) reflective thinking, and (6) strategies to overcome psychological barriers.

Development of a Prediction Model for Personal Thermal Sensation on Logistic Regression Considering Urban Spatial Factors (도시공간적 요인을 고려한 로지스틱 회귀분석 기반 체감더위 예측 모형 개발)

  • Uk-Je SUNG;Hyeong-Min PARK;Jae-Yeon LIM;Yu-Jin SEO;Jeong-Min SON;Jin-Kyu MIN;Jeong-Hee EUM
    • Journal of the Korean Association of Geographic Information Studies
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    • v.27 no.1
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    • pp.81-98
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    • 2024
  • This study analyzed the impact of urban spatial factors on the thermal environment. The personal thermal sensation was set as the unit of thermal environment to analyze its correlation with environmental factors. To collect data on personal thermal sensation, Living Lab was applied, allowing citizens to record their thermal sensation and measure the temperature. Based on the input points of the collected personal thermal sensation, nearby urban spatial elements were collected to build a dataset for statistical analysis. Logistic regression analysis was conducted to analyze the impact of each factor on personal thermal sensation. The analysis results indicate that the temperature is influenced by the surrounding spatial environment, showing a negative correlation with building height, greenery rate, and road rate, and a positive correlation with sky view factor. Furthermore, the road rate, sky view factor, and greenery rate, in that order, had a strong impact on perceived heat. The results of this study are expected to be utilized as basic data for assessing the thermal environment to prepare local thermal environment measures in response to climate change.