Earticle

디지털 기술은 단순한 정보 전달 수단을 넘어서, 서사를 생성하고 소비하는 방식을 재정의하는 새로운 형태 의 패러다임이다. 디지털 기술의 발전과 함께, 디지털 매체는 강력한 스토리텔링 도구로서 현대 교육 분야에 자리 잡고 있으며, 이는 전통적인 교육 방식과 비교했을 때 학습자의 상호작용이 강조된다는 차이가 있다. 본 연구는 이러한 디지털 스토리텔링 환경에서 시·청각이 결합된 정보를 학습자에게 제공하고, 스토리텔링 과정에 선택지를 제공함으로써 상호작용성과 게임 요소를 더해 학습자 스스로 스토리텔링을 통해 학습하는 방법을 제안하였다. 그리고 연구의 타당성 검증을 위해 전문가 인터뷰를 실시하였다. 전문가 검증결과, 학습 자 스스로 스토리텔링을 통해 학습하는 과정은 이해도와 몰입도 측면에서 매우 효과적일 것이라는 긍정적인 답변을 얻을 수 있었다.

Digital technology is more than just a means of conveying information, it is a new form of paradigm that redefines the way we create and consume narratives. With the advancement of digital technology, digital media have found a place in modern education as a powerful storytelling tool, with the difference that it emphasizes learner interaction compared to traditional teaching methods. In this study, we proposed a method to learn through storytelling by providing learners with combined visual and auditory information in a digital storytelling environment and adding interactivity and game elements by providing choices in the storytelling process. We conducted expert interviews to validate the study. As a result of the expert validation, we received positive responses that the process of learning through storytelling by the learners themselves would be very effective in terms of comprehension and engagement

본 논문에서는 구성주의적 교수-학습 이론을 통해 학생참여 중심, 교수와 학생과의 상호작용, 최신경향 반영, 실무적용 가능성, 다양한 자료 제공 등이 강의 몰입 및 만족을 이끌어 낼 수 있음을 밝히고자 하였다. 또한 창의성의 내적 동기요인 이론을 통해 학생들의 몰입 및 만족이 창의성 개발에 중요한 요인임을 제시하였다. 연구 결과 학습방식 측면에서 학생참여 중심, 교수와 학생과의 상호작용은 강의몰입에 정(+)의 관계가 있었고 수업내용 측면에서 최신경향 반영, 실무적용 가능성, 다양한 자료제공 등이 강의몰입에 정(+)의 영향을 미쳤다. 또한 강의몰입과 강의만족에서도 유의미한 관계가 규명되었다. 본 연구는 구성주의 연구의 대부분이 질적연구임을 감안할 때 양적연구 접근을 통해 창의성 개발에 핵심 요소인 내적 동기 요인의 몰입과 만족에 긍정적인 영향을 미치는 특성 변수를 규명하였다는 데 의의가 있다. 나아가, 경영컨설팅을 진행하는데 있어 다양한 워크샵, 세미나, 설명회 등을 실시하게 되는데 본 연구의 결과는 컨설팅 과정에서 클라이언트의 적극적인 참여를 이끌어 내기 위한 방안으로 활용될 수 있을 것이다.

In this paper, Professor constructivist-learning theory says the center of student participation, interaction of faculty and students, reflect the latest trends, practical applicability, the material offers a variety of lectures, commitment and satisfaction can lead that person was. Theory of creativity, intrinsic motivation also suggest that the students' commitment and satisfaction is an important factor in the development of creativity. Study centered approach to learning in terms of student participation and interaction of faculty and students has been confirmed that the teaching commitment in the relationship between the positive (+), reflecting the latest trends in terms of course content and practical applicability, provide a variety of lectures Commitment had a positive relationship. In addition, teaching commitment and also the satisfaction of the river, a significant relationship was identified. In this paper, there are implications to identify the factors that have a positive relationship, teaching commitment and satisfaction, a quantitative approach to constructivist teaching and learning can be a key element in the development of creativity, intrinsic motivation factors. The other hand, constructivist teaching and teaching and learning about how the questionnaire for the measurement of learning theory was used as a surrogate, identify the impact of creativity, commitment and satisfaction did not point to the limitations remain. The result of this research will offer a proper way for consulting clients to participate actively in business consulting process that includes several purposed workshops, seminars, and other works. In general, the consulting process consists in several workshops, seminars, and other works. The result of this research can be used for motivating consulting clients to participate positively in process.

Machine learning models were developed to predict the degree of microbial quality of beef by a non-destructive method using a near-infrared hyperspectral imaging system. Beef was stored under aerobic conditions at different temperature scenarios (refrigerated, thawed after freezing, or left at room temperature) for a period of 15 days to induce freshness change and microbial growth. Hyperspectral data cubes were obtained from a data acquisition system in a darkroom environment. The total aerobic bacteria (TAB) experiment was performed in the established meat science manner to provide reference values for the microbial contamination level of the sample. The region of interest designated as the red meat region was selected for spectral extraction. Regression models were developed to predict the TAB value from the extracted data. Partial least squares regression, support vector machine, artificial neural network, and one-dimensional convolutional neural network methods were employed to construct TAB prediction models. Chemical maps were also created for each developed model to visualize the performance of the model. The model development process concluded with the iteration of all previous steps at completely different times and with different beef samples, generating the data for verification and applying it to the developed model to evaluate its versatility. As a result of the development, it was confirmed that the microbial quality of beef can be predicted by models generated from hyperspectral data (Best validation R2 = 0.8593, RMSE = 0.6947). Accurate quality prediction helps livestock breeders develop and apply better husbandry practices, which ultimately leads to higher quality beef production.

This paper presents a systematic review of deep learning (DL) techniques for Network-based Intrusion Detection Systems (NIDS) based on Preferred Reporting Items for Systematic Reviews and Meta-Analyses: (PRISMA2020) guidelines. It explores recent advancements in data preparation, DL architectures, and performance evaluation metrics for NIDS. The review provides insights into various datasets and tools used in the field, highlighting the effectiveness of DL in improving NIDS performance. Additionally, it discusses the applications of NIDS across different industries and identifies emerging research trends, offering a comprehensive resource for researchers and practitioners in cybersecurity.

Fake news is inaccurate information that is intentionally disseminated for a specific purpose. If allowed to spread, fake news can harm the political and social spheres, so several studies are conducted to detect fake news. This study uses a deep learning method with several architectures such as CNN, Bidirectional LSTM, and ResNet, combined with pre-trained word embedding, trained using four different datasets. Each data goes through a data augmentation process using the back-translation method to reduce data imbalances between classes. The results showed that the Bidirectional LSTM architecture outperformed CNN and ResNet on all tested datasets.

본 연구에서는 제주도 동부 지역의 지하수위 예측을 위한 머신러닝 모델로서 ANN, ELM, LSSVR, LightGBM을 적용하였으며, 모델 평가지표와 도식적 비교를 통해 적용 모델의 지하수위 예측 성능을 평가하였다. 자기상관성이 강한 지하수위 예측에 있어서 비교 모델들은 1일 예측에서 모두 매우 우수한 예측 성능을 나타낸 반면, 7일 예측에서는 예측 성능이 저하되었으며, 비교 모델들간 예측 성능은 거의 비슷하게 나타났다. 또한, 해안지역의 경우 조위변동의 영향으로 인하여 내륙지역보다 지하수위 예측 성능이 다소 저하됨을 확인할 수 있었다. 자기상관성이 강한 지하수위 예측에 있어서 예측 결과가 비슷하 게 나타날 경우 ANN, ELM 등과 같이 상대적으로 복잡한 상세 튜닝을 필요로 하지 않는 머신러닝 모델의 적용성이 상대적으로 우수할 것으로 판단된다. 따라서 머신러닝 모델을 이용한 지하수위 예측은 제주도의 지하수자원을 위한 효과적인 관리도구가 될 수 있을 것이다.

This study applies ANN, ELM, LSSVR, and LightGBM as machine learning models for groundwater level forecasting in the eastern region of Jeju Island, South Korea. The groundwater level forecasting performance of the applied models is evaluated through model evaluation indices. In forecasting the groundwater levels with strong autocorrelation, the comparative models all show excellent performance in the 1-day forecasting. In contrast, the forecasting performance deteriorates in the 7-day forecasting. The results also show that the forecasting performances among the comparative models are almost similar. In addition, it is confirmed that in coastal areas, groundwater level forecasting performance deteriorates compared to inland areas due to the influence of tidal variation. When forecasting results are similar in forecasting the groundwater levels with strong autocorrelation, models that do not require relatively complex detailed tuning, including ANN and ELM, can have excellent applicability. Therefore, groundwater level forecasting using machine learning models can be an effective tool for groundwater resources in Jeju Island.

본 논문에서는 다중 요인을 고려한 천연 가스 누출 정도 예측을 위해 관련 요인을 포함하는 기상청 자료와 천연가스 누출 자료를 통합하고, 요인 분석을 기반으로 중요 특성을 선택하는 머신러닝 기법을 제안한다. 제안된 기법은 3단계 절차로 구성되어 있다. 먼저, 통합 데이터 셋에 대해 선형 보간법을 수행하여 결측 데이터를 보완하는 전처리를 수행한다. 머신러닝 모델 학습 최적화를 위해 OrdinalEncoder(OE) 기반 정규화와 함께 요인 분석을 사용하여 필수 특징을 선택하며, 데이터 셋은 k-평균 클러스터링으로 레이블을 지정한다. 최종적으로 K-최근접 이웃, DT(Decision Tree), RF(Random Forest), NB(Naive Bayes)의 네 가지 알고리즘을 사용하여 가스 누출 수준을 예측한다. 제안된 방법은 정확도, AUC, 평균 표준 오차(MSE)로 평가되었으며, 테스트 결과 OE-F 전처리를 수행한 경우 기존 기법에 비해 성공적으로 개선되었음을 보였다. 또한 OE-F 기반 KNN(OE-F-KNN)은 95.20%의 정확도, 96.13%의 AUC, 0.031의 MSE로 비교 알고리즘 중 최고 성능을 보였다.

In this article, we proposed to predict natural gas (NG) leakage levels through feature selection based on a factor analysis (FA) of the integrating the Korean Meteorological Agency data and natural gas leakage data for considering complex factors. The paper has been divided into three modules. First, we filled missing data based on the linear interpolation method on the integrated data set, and selected essential features using FA with OrdinalEncoder (OE)-based normalization. The dataset is labeled by K-means clustering. The final module uses four algorithms, K-nearest neighbors (KNN), decision tree (DT), random forest (RF), Naive Bayes (NB), to predict gas leakage levels. The proposed method is evaluated by the accuracy, area under the ROC curve (AUC), and mean standard error (MSE). The test results indicate that the OrdinalEncoder-Factor analysis (OE-F)-based classification method has improved successfully. Moreover, OE-F-based KNN (OE-F-KNN) showed the best performance by giving 95.20% accuracy, an AUC of 96.13%, and an MSE of 0.031.

본 연구는 창의적 문제 해결을 위한 학제 간 융복합 교양교육에 관한 연구로, 이러한 교과·교육이 창의적 문제 해결에 미치는 기능과 효과를 분석하고자 하였다. 교과 운영 내용과 결과를 면밀히 검토하여 주요 특징과 관련성을 도출하였고, 향후 개선 방향과 발전적인 운영 방안을 모색하고자 하였다. 이를 위해 문헌 연구를 통해 이론적 기초를 마련하였고, 학제 간 융복합 교양 과목을 대상으로 사례 연구(Case Study)를 진행하였다. 교수법, 학습 전략, 교육(학습) 도구의 적용을 고찰하여, 수업 목표 달성과 학습자 역량 강화를 위한 적절성을 검토하였다. 연구 결과, 학제 간 융복합 교양교육은 창의적 문제 해결 역량을 배양하는 데 중요한 역할을 하였으며, 팀 기반 학습과 문제 중심 학습 방법이 실제 문제 해결 능력 강화를 위한 효과적인 접근법임을 확인하였다. 또한, 이러한 교과·교육은 학생들이 문제를 다각 도로 분석하고 최적의 해결책을 도출하도록 유도하는 데 기여하였다. 디지털 기술, 생성 형 AI 학습 도구, 경험 기반 학습의 통합은 학습자의 수업 몰입도를 높이고 학습 효과 를 증진하는 데 긍정적인 영향을 미쳤다. 나아가, 학생들은 비판적 사고, 창의적 아이디 어 도출, 협업 역량에서 뚜렷한 향상을 보였으며, 이는 학습 결과물을 통해 실증적으로 확인되었다. 본 연구를 통해 학제 간 융복합 교육이 창의적 사고와 혁신적 문제 해결 능력 함양에 효과적인 교육 방식임을 확인하였으며, 향후 융복합 교양 교과의 설계 및 운영 전략 개 선에 유용한 시사점을 제공하였다. 앞으로 다양한 교육 사례에 대한 비교연구 및 평가 체계 개선을 위한 후속 연구가 지속적으로 이루어질 필요가 있겠다.

This study examines interdisciplinary convergence-based liberal arts education for fostering creative problem-solving skills, analyzing its functions and effectiveness. By reviewing course implementation and outcomes, it identifies key characteristics and suggests strategies for improvement. A literature review established the theoretical foundation, followed by a case study of interdisciplinary liberal arts courses. The research evaluates teaching methodologies, learning strategies, and educational tools to assess their effectiveness in achieving course objectives and enhancing student competencies. Findings indicate that interdisciplinary education strengthens creative problem-solving. Team-based and problem-based learning proved effective in developing real-world problem-solving skills. Courses encouraged multifaceted analysis and optimal solutions, while digital technologies, generative AI, and experiential learning enhanced engagement and learning outcomes. Students also showed significant gains in critical thinking, creativity, and collaboration. This study confirms the effectiveness of interdisciplinary convergence education in fostering creative and innovative problem-solving. It offers insights for improving course design and implementation. Future research should explore comparative studies and refined evaluation methods to advance interdisciplinary education.

The duration of an inpatient stay affects hospital administration and improves hospital effectiveness in terms of controlling expenses and raising patient standards. It also assists in identifying the correlations among illnesses requiring hospitalization. For our study, we took 24,150 records from of the Open Data database pertaining to inpatient admissions in 2023. We used a number of methods, including Neural Networks, Deep Learning, Linear Regression, and Support Vector Machines, to predict the Length of Stay (LOS). We converted the data to numerical form for predictive purposes, dividing the dataset into 70% for training and 30% for testing. We assessed the model's performance using Root Mean Squared Error (RMSE) and split the forecast into four LOS categories: 0-2, 3-4, 5-7, and 8 days or more. The study also employed the Apriori algorithm to identify illness association rules that could impact LOS estimates. The results showed that identifying illness correlations is one element that might aid in enhancing the capacity to predict LOS.

This study explores the impact of a modified cooperative learning application on the communication skills and learning experiences of nursing students within a health statistics course. A mixed-method approach was employed, involving 39 nursing students who participated in a 10-week modified cooperative learning module integrated with both theoretical and practical sessions of the health statistics curriculum. Quantitative measures were used to assess changes in communication skills, while qualitative feedback was collected to analyze students' learning experiences. Results demonstrated a significant improvement in communication skills post-intervention (from 3.71±0.42 to 4.03±0.48, p < .001). Qualitative analysis highlighted enhanced student engagement and cooperation through active participation and interactions. The findings suggest that modified cooperative learning can effectively enhance communication skills and provide a positive learning experience, supporting its potential as an alternative teaching strategy in nursing education.

목적: 본 연구는 에스테틱 기기 관리 수업에서 사례 기반 학습(Case-Based Learning, CBL)을 경험한 학습자의 메타인지와 창의 적 문제해결력 간 관련성을 분석하고, 성찰 기록을 통해 실무 역량 형성 과정을 탐색하고자 하였다. 방법: 혼합 연구로 설계하여, 양 적 연구에서는 메타인지와 창의적 문제 해결력 하위 요인 간 상관관계를 검증하였고, 질적 분석에서는 성찰 기록에 대한 주제 분석을 실시하였다. 결과: 메타인지의 계획·조절과 모니터링은 창의적 문제 해결력과 유의한 정적 상관을 보였으나, 평가는 유의하지 않았다. 질적 분석에서는 ‘피부반응 기반 미세조절’과 ‘피부관리 장비 적용 숙련’이 핵심 주제로 도출되었으며, 실습 과정에서 전략을 즉각 수정하는 행위 중 성찰이 수행의 질에 중요한 역할을 함을 확인되었다. 결론: 에스테틱 실무 교육에서 메타인지는 실시간 상황 판단과 전략 조정을 가능하게 하는 성찰적 실천 과정으로 작동하며, 향후에는 비구조화된 사례 상황을 반영한 성찰 기반 수업 설계가 요구된다.

Purpose: This study examines the relationship between metacognition and creative problem-solving ability among learners engaged in case-based learning in an esthetic device management course. Additionally, it explores how practical competency processes develop through analysis of learners’ reflective records. Methods: A mixed-methods design was employed, integrating quantitative and qualitative approaches. Quantitative analysis assessed the correlations between metacognition and creative problem-solving ability, whereas the qualitative process used thematic analysis of learners’ reflective records. Results: The planning–regulation and monitoring components of metacognition was positively associated with creative problem-solving ability, whereas the evaluation component was not. The qualitative analysis identified two core themes: skin reaction–based micro-adjustment and proficiency in the application of skincare devices. These indicate that reflection-in-action, characterized by immediate strategy modification during practice, plays a critical role in enhancing the quality of task performance. Conclusion: In esthetic education, metacognition functions as a reflective practice that enables real-time situational judgment and strategic adjustment. These findings suggest the need to strengthen reflection-based instructional designs that incorporate ill-structured case situations in future curricula.

目的: 探讨在美学设备管理课程中，采用案例式学习方法的学习者元认知与创造性问题解决能力之间的关系。此 外，本研究还通过分析学习者的反思记录，探索其实践能力的发展过程。方法: 本研究采用混合方法设计，整合 了定量和定性方法。定量分析评估了元认知与创造性问题解决能力之间的相关性，而定性分析则采用主题分析 法分析学习者的反思记录。结果: 元认知中的计划-调节和监控成分与创造性问题解决能力呈正相关，而评估成 分则不然。定性分析确定了两个核心主题：基于皮肤反应的微调和护肤设备应用的熟练程度。这些结果表明， 以实践过程中即时调整策略为特征的行动中反思，在提升任务表现质量方面发挥着关键作用。结论: 在美学教育 中，元认知作为一种反思性实践，能够帮助学生进行实时情境判断和策略调整。这些发现表明，未来的课程需 要加强以反思为基础的教学设计，并纳入非结构化案例情境。

This study employed a mixed-methods approach to examine how international students’ AI-assisted academic and career coaching needs vary according to their levels of academic and career competencies. Quantitative and qualitative analyses revealed a three-stage pattern of coaching needs, that is to say, introductory, intermediate, and implementation, across both competencies, and identified four competency-combination types: latent-vulnerable, direction-seeking, implementation-gap, and self-development. These types differed not only in the intensity of their coaching needs but also in their attitudes toward AI use, modes of expressing needs, and levels of emotional anxiety. Notably, the same AI tool functioned as a developmental resource for some groups, while for others it appeared to heighten anxiety and avoidance. The study underscores the need to view international students as adult and lifelong learners at different developmental stages and highlights the importance of competency-based, tailored AI coaching systems for effective support.

This mixed-methods study explores perceptual learning style preferences among Korean and Uzbek EFL learners and examines teachers’ interpretations of these preferences. Quantitative data were collected from secondary-level learners in both countries (N= 208) using Reid’s PLSPQ, followed by semi-structured interviews with English teachers (n= 18) to contextualize survey patterns. The PLSPQ was selected for its modality-based structure and comparability with current EFL research, and teacher interviews were added to triangulate self-report. Independent-samples t-tests showed that Uzbek learners reported significantly higher preferences across all six modalities, with no group differences on visual. These higher scores are interpreted as context-responsive tendencies rather than indicators of superior ability, with Uzbek patterns linked to smaller classes, limited private tutoring, early instruction prior to full literacy, and movement-based activities in resource-limited schools. In contrast, narrower preference profiles among Korean learners align with exam-oriented, text-focused instruction, larger classes, and classroom norms of deference. While this study contributes a cross-context perspective on learning style preferences, its findings are limited by reliance on self-report and the absence of factor analytic validation of the PLSPQ. Future research should include psychometric testing and behavioral measures. Overall, results underscore the value of inclusive, multimodal pedagogy and learner metacognitive awareness.

본 연구는 플립러닝이 각 학습 영역에 기여하는 정도를 순위로 살펴보고, 반대로 이러한 학습방법이 플립러닝에 얼마나 효과적으로 사용되는지 양적으로 살펴보기 위해, 컴퓨터 전공자들을 대상으로 플립러닝을 받게 하였다. 기존의 플립러닝 실험은 효과성을 검증한 연구가 있는 반면 효과성에 부정적인 결과도 있어, 많은 논쟁이 되고 있다. 따라서 효과적인 실험과 수업을 위해서는 플립러닝에 대한 더 많은 연구와 정확한 이해가 필요하다. 모집된 123개의 표본을 분석한 결과 플립러닝이 학습에 기여하는 순위는 자기주도학습, 협력학습, 동영상 시청, 교수에 의한 학습 순이며, 학습 방법이 플립러닝 효과성에 영향을 주는 정도를 회귀분석한 결과 자기주도학습, 강의동영상, 협력학습이 순으로 영향을 주었다. 이는 플립러닝이 자기주도학습에 가장 큰 영향력을 줄 뿐 아니라, 자기주도학습이 플립러닝에 가장 큰 영향력을 주고 있음을 알 수 있다. 또한 협력학습과 선행학습 도구인 동영상의 역할도 중요함을 알 수 있다. 본 연구 통해 플립러 닝을 정확히 이해하고 학습방법과 성취목표를 설정하길 기대한다. 향후 본 연구의 연장으로 플립러닝과 세분화된 교실 활동의 상호작용을 분석할 예정이다.

This study ranked the degree to which flipped learning contributes to each learning area and, in contrast, to quantitatively examine how effectively these learning methods are used in flipped learning, had four-year university computer majors receive flipped learning. Existing flipped learning experiments have proven effectiveness, while there are also negative effects on effectiveness, which has led to a lot of debate. Effective experiments and classes therefore require more research and an accurate understanding of flipped learning. Analysis of the 123 samples recruited shows that flipped learning contributes to learning is in order of self-directing, collaboration, watching videos, and learning by teachers. Regression analysis of the degree to which learning method affects flipped learning effectiveness resulted in order of self-directed learning, lecture videos, and collaborative learning. This shows that flipped learning not only has the greatest influence on self-directed learning, but also self-directed learning has the greatest influence on flipped learning. It can also see that a collaborative learning and the role of video to prior learning tool is important. Through this study, we hope to understand flipped learning correctly and set learning methods and achievement goals. It is necessary to analyze the interaction between flipped learning and subdivided classroom activities.

정보통신기술의 발달과 더불어 교수 매체가 변화하고 COVID-19로 인해 비대면 교육이 늘어나고 있는 현 시점에서 모바일 러닝에 대한 관심과 수요는 계속 증가할 것으로 예상된다. 이에 본 연구는 모바일 러닝 의 주요 특성을 정리하고 이를 바탕으로 한국어 교육 콘텐츠를 직접 제작하여 교수·학습 방안을 제시하고 자 하였다. 또한 모바일을 활용한 교육을 시행한 후 수강생들을 대상으로 설문 조사를 실시하였는데 그 결과 학습자들은 모바일 러닝의 특성을 충분히 이해하며 긍정적인 반응을 보였지만 향후 모바일 러닝 교수·학습에서 고려해야 할 보완점을 제안하였다.

With the development of information and communication technology the teaching medium is changing and non-face-to-face education is increasing due to COVID-19 and it is expected that the interest and demand for mobile learning will continue to increase. Therefore, in this research we can find its significance in that the main features of mobile learning are summarized and based on this Korean language educational content is directly produced and teaching·learning methods are presented. In addition, post-learning surveys were conducted, and the results showed that learners fully understood the characteristics of mobile learning and responded positively, but also suggested considerations in future mobile learning professors and learning.

우리는 수⋅과학 영재 고등학생들의 정보과학 창의성 향상을 위한 효과적인 정보과학 교수-학습 방법을 제안 하였다. 학생들은 현실적 응용문제를 해결하는 정보과학 팀 프로젝트의 수행을 통하여 창의적 문제해결 능력과 팀워크 능력을 향상할 수 있다. 이러한 교육목표를 효과적으로 달성하기 위하여 기본과정과 응용과정으로 구성 되는 2단계 정보과학 수업 방법과 체계적 프로젝트 수행 단계를 설계하고, 소규모 협력 학습 전략과 입체적 평 가 방안을 적용하였다. 논문에서 제안한 프로젝트 기반 교수-학습 방법의 학습 효과를 분석한 결과, 정보과학 창의성의 지적⋅정의적 및 사회적 영역에서의 효과적인 교육 목표 달성을 확인할 수 있었다.

We propose an efficient information science teaching-learning method to improve information-scientific creativity of mathematically and scientifically gifted students. The students are able to improve their creative problem solving and team-work abilities through team project work to resolve a variety of application problem in real world. In the pursuit of this purpose, we designed a new two-stage information science learning method consisted of the standard stage and the application stage, and a new systemic project process. Moreover, we applied small-scale cooperation learning strategies and a multi-dimensional assessment system. The analysis on our proposed model shows that there is a remarkable achievement of educational objectives on cognitive capability, social and affective ability of information science creativity.

정보화 사회에서 필요한 능력은 정보 능력을 바탕으로 한 각 능력의 조화로운 습득이며, 이러한 핵심 역량에 대한 교육 필요성과 함께 급변하는 정보화 사회에서 새로운 기술의 발전과 사회 환경의 변화로 인하여 교육 과정을 새롭게 구성해야 할 필요가 발생하였다. 따라서 한국정보교육학회에서는 정보 교과의 내용 체계에 대한 개정안에 대하여 연구하였으며, 정보 교육 내용을 ‘컴퓨터 시스템’, ‘소프트웨어 제작’ 및 ‘융합 활동’의 세 영역으로 구분하였다. 이에 따라 본 논문에서는 ‘융합 활동’ 영역에 대하여 1학년부터 중학교 3학년까지의 교육과정을 연구하였다. 먼저 ‘융합 활동’의 교육 내용을 정보 능력과 다른 핵심 역량을 융합한 ICT 활용, 정보통신 윤리, 로봇 등의 활용으로 정의하고 이에 대한 성취 기준을 제시하였다. 그리고 이 성취 기준을 도달하기 위한 교수 학습 방법과 평가 방안을 학년군 별로 세분화하여 제시하였다. 본 연구에서 제시한 ‘융합 활동’에 대한 교육과정은 21세기 정보화 사회에 필요한 인재 양성에 기여할 것으로 기대된다.

The ability to need information-oriented society is the convergence ability based in information ability. A new curriculum is demanded by new technology and circumstance to need the core ability. Korea Association of Information Education have studied a new curriculum and suggest a new plan that content of information education classified by ‘computer system’, ‘SW production’ and ‘convergence activities.’ Therefore, we studied on convergence activities of K-9. In this paper we firstly suggested concept of convergence ability as activities to use ICT, information communication ethics and robot. We nextly suggested object to achieve, teaching-learning methods and evaluation methods of convergence activities. We expect the curriculum we suggested about convergence activities will contribute to training talented individuals.