• Journal of Internet Computing and Services
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• v.24 no.4
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• pp.117-125
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• 2023

Flipped learning is an instructional approach that reverses the traditional order of in-class and after-class activities. It entails students studying course materials before attending class, and then utilizing class time for completing homework tasks. Due to collaborative support available from teachers and peers, flipped learning has gained extensive adoption in computer science and engineering courses, enabling students to effectively engage in homework assignments. Nevertheless, students are responsible for studying class materials independently, which can limit their understanding of advanced topics. We propose an approach that combines both flipped learning and the traditional method, allowing them to mutually enhance each other. In the proposed approach, students acquire foundational concepts prior to attending class, and subsequently delve into advanced topics during classroom sessions through lectures and guidance provided by the teacher. Afterward, students collaborate with their peers to solve problems that involve the application of the concepts they have learned, and exchange a variety of solutions and perspectives. We implemented the proposed approach in four computer science and engineering classes, spanning one to four semesters and observed an enhancement in students' comprehension and satisfaction levels. We anticipate implementation of the proposed approach across various computer science and engineering courses, while enhancing their overall quality.

• Journal of the Korea Society for Simulation
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• v.32 no.4
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• pp.27-39
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• 2023

This study aimed to develop SSTPBL (Student-led Simulation with Team and Problem-Based Learning), whichcombines TBL and PBL with a student-led method to strengthen knowledge application, nursing diagnosis ability, and collaboration ability among the core competencies of nurses. Then, SSTPBL was applied to nursing students, and the results were assessed. The data was collected from September 15, 2022, to December 21, 2022, with structured questionnaires and focus group interviews with 51 fourth-year nursing students at a university in A City. The collected data were analyzed using SPSS version 25.0 and topic analysis. As a results, it was effective in simulation experience satisfaction(t = 3.51, p < .01), vSim experience satisfaction(t = 3.50, p < .01), preparation as a prospective nurse(t = 3.73, p < .01), learning self-efficacy(t = 3.87, p < .01), collaborative self-efficacy (t = 4.30, p < .01), problem-solving ability(t = 5.26, p < .01), educational satisfaction(t = 3.54, p < .01), digital health equity(t = 2.18, p < .05). Through the qualitative data's topic analysis, six main topics were derived. The main topics were 'similar to clinical practice', 'difficulty in immersion', 'learning through others', 'learning through self-reflection', 'improving confidence through new experiences' and 'new teaching methods'. Based on the results of this study, it is expected that SSTPBL can be used in various ways as a new training method for prospective nurses in the face of growing clinical practice restrictions after the pandemic.

• 대한공업교육학회지
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• v.36 no.2
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• pp.273-292
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• 2011

The Purpose of this research is to investigate how Project Based Learning(PBL) cognitive department and among the learner and instructor in the industrial highschool. Theoretical framework for the study is based on PBL, collaborative learning and module learning. The importance of the PBL has been continuously reviewed by many educational researchers. In addition, it was supported by previous research results. Based on theoretical frameworks and previous researches on the PBL provided design principles and method for learning in the industrial highschool. As a result of this study, we have developed and applied to investigate (1) differences between the types of departments(agriculture, industry, commerce) of cognition on learner's and instructor's task solving process, (2) correlation between the type of groups(learner, instructor) and type of departments(agriculture, industry, commerce) cognition on task solving process. The total of 100 learners and 50 instructors from industrial highschool in the study for the period of sixteen weeks. Based on the type of groups and departments, participants were divided into six groups such as learner and instructor of agriculture, industry, commerce department. The result of the study can be summarized as follows: First, in the study, between the types of departments(agriculture, industry, commerce) of cognition on learner's and instructor's task solving process are differences. Second, correlation between the type of groups(learner, instructor) and type of departments(agriculture, industry, commerce) of cognition on task solving process are differences. Although the differences were insignificant for cognition of PBL's help, however, four items(accomplishment, application subject, hereafter application) showed significant differences in performances. The implication of the result indicated the cognition of PBL in the industrial highschool seem significant for departments and subjects characteristic of learning. In future research it is recommended that PBL model designs should consider components of group and department types.

• Journal of Science Education
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• v.33 no.2
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• pp.207-219
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• 2009

This study aims to investigate the key common topics identified and discussed in relevant literature associated with the integrative efforts among STEM disciplines. The key methodology and pedagogy were examined and the significant benefits of using the design method for STEM education were discussed. Meta-analysis was employed and qualitative approach was mainly used to synthesize the major findings and conclusions of the 33 empirical studies. The findings of this meta-analysis revealed that the types and names describing the design methods used the various terms, but the key features have reflected the similar pedagogical benefits and key characteristics. The engineering design is an effective strategic methodology and pedagogy for STEM education. In addition, the design methods show the key benefits including (1) to improve academic achievement, (2) to promote students' affective gains, (3) to facilitate collaborative learning, and (4) to explore STEM related careers and jobs. The collaborative works among STEM professions are needed to promote the benefits of using design methods for integrating STEM subjects.

• The Journal of Korean Academic Society of Nursing Education
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• v.27 no.1
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• pp.59-67
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• 2021

Purpose: The purpose of this study is to examine the effectiveness of Problem-based Learning (PBL) in an interdisciplinary college class. This class was run under the theme of 'Nurse Social Content Creators' (NSCC) in the Korean Nurses Association (KNA)'s industry-university collaborative project designed to promote a positive image of nurses among the public. Methods: Study 1 examined changes in perception about nurses among the PBL participants before and after the program. A one-group pre-post test experimental design was applied, and the data were analyzed using a Wilcoxon signed-rank test. Study 2 identified differences of perceptions of nurses between people who had observed the PBL final presentation and people who had not. A post-test-only with nonequivalent group experimental design was used, and the data were analyzed using a Mann-Whitney U test. Results: Study 1 revealed a significant increase of positive perceptions towards nurses. Study 2 revealed a significant difference between the PBL presentation audience group and the control group. Students who had observed the PBL program showed more positive perceptions of nurses than students who had not. Conclusion: This research is an important study with high practicality in the area of media studies as well as in nursing. The PBL teaching method was proven to be effective in enhancing perceptions of nurses.

• Smart Media Journal
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• v.9 no.4
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• pp.118-125
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• 2020

This paper is conducted for automatically recommending and providing information services desired by users on websites of local governments and public institutions with vast amounts of information, In this system, we defined a method of collecting data based on the SiiRU CMS system that collects and preprocesses data, and a study that provides curation services (contents and menus) to users through a collaborative filtering algorithm based on machine learning. Also, the data used in the paper is conducted based on about 1 million data collected in 2019. The analyzed data can provide important information that cannot be easily accessed by providing a cloud tag service or recommended menu for users to conveniently view, and the environment configuration that can realize this service to local governments and public institutions is also provided.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.47 no.2
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• pp.155-167
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• 2024

Distribution and logistics industries contribute some of the biggest GDP(gross domestic product) in South Korea and the number of related companies are quarter of the total number of industries in the country. The number of retail tech companies are quickly increased due to the acceleration of the online and untact shopping trend. Furthermore, major distribution and logistics companies try to achieve integrated data management with the fulfillment process. In contrast, small and medium distribution companies still lack of the capacity and ability to develop digital innovation and smartization. Therefore, in this paper, a deep learning-based demand forecasting & recommendation model is proposed to improve business competitiveness. The proposed model is developed based on real sales transaction data to predict future demand for each product. The proposed model consists of six deep learning models, which are MLP(multi-layers perception), CNN(convolution neural network), RNN(recurrent neural network), LSTM(long short term memory), Conv1D-BiLSTM(convolution-long short term memory) for demand forecasting and collaborative filtering for the recommendation. Each model provides the best prediction result for each product and recommendation model can recommend best sales product among companies own sales list as well as competitor's item list. The proposed demand forecasting model is expected to improve the competitiveness of the small and medium-sized distribution and logistics industry.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.139-161
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• 2019

The utilization of the e-commerce market has become a common life style in today. It has become important part to know where and how to make reasonable purchases of good quality products for customers. This change in purchase psychology tends to make it difficult for customers to make purchasing decisions in vast amounts of information. In this case, the recommendation system has the effect of reducing the cost of information retrieval and improving the satisfaction by analyzing the purchasing behavior of the customer. Amazon and Netflix are considered to be the well-known examples of sales marketing using the recommendation system. In the case of Amazon, 60% of the recommendation is made by purchasing goods, and 35% of the sales increase was achieved. Netflix, on the other hand, found that 75% of movie recommendations were made using services. This personalization technique is considered to be one of the key strategies for one-to-one marketing that can be useful in online markets where salespeople do not exist. Recommendation techniques that are mainly used in recommendation systems today include collaborative filtering and content-based filtering. Furthermore, hybrid techniques and association rules that use these techniques in combination are also being used in various fields. Of these, collaborative filtering recommendation techniques are the most popular today. Collaborative filtering is a method of recommending products preferred by neighbors who have similar preferences or purchasing behavior, based on the assumption that users who have exhibited similar tendencies in purchasing or evaluating products in the past will have a similar tendency to other products. However, most of the existed systems are recommended only within the same category of products such as books and movies. This is because the recommendation system estimates the purchase satisfaction about new item which have never been bought yet using customer's purchase rating points of a similar commodity based on the transaction data. In addition, there is a problem about the reliability of purchase ratings used in the recommendation system. Reliability of customer purchase ratings is causing serious problems. In particular, 'Compensatory Review' refers to the intentional manipulation of a customer purchase rating by a company intervention. In fact, Amazon has been hard-pressed for these "compassionate reviews" since 2016 and has worked hard to reduce false information and increase credibility. The survey showed that the average rating for products with 'Compensated Review' was higher than those without 'Compensation Review'. And it turns out that 'Compensatory Review' is about 12 times less likely to give the lowest rating, and about 4 times less likely to leave a critical opinion. As such, customer purchase ratings are full of various noises. This problem is directly related to the performance of recommendation systems aimed at maximizing profits by attracting highly satisfied customers in most e-commerce transactions. In this study, we propose the possibility of using new indicators that can objectively substitute existing customer 's purchase ratings by using RFM multi-dimensional analysis technique to solve a series of problems. RFM multi-dimensional analysis technique is the most widely used analytical method in customer relationship management marketing(CRM), and is a data analysis method for selecting customers who are likely to purchase goods. As a result of verifying the actual purchase history data using the relevant index, the accuracy was as high as about 55%. This is a result of recommending a total of 4,386 different types of products that have never been bought before, thus the verification result means relatively high accuracy and utilization value. And this study suggests the possibility of general recommendation system that can be applied to various offline product data. If additional data is acquired in the future, the accuracy of the proposed recommendation system can be improved.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.926-932
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• 2009

Recently many research reports on effective use of mobile devices for museums to provide information on displayed artifacts providing individualized learning space, collaborative learning, and discovery learning, Such devices have many possibilities to support learning as a participatory media and social network. Mobile devices are used, however, limited for its usability and lack in providing expected learning experiences. It offers one-way interaction and they are often limited in providing customized services for different patrons to experience learning and entertainment. In this research, we have adopted user centered design approach to identify the needs and possible usage of PDA system in the museum. Research methods include contextual observation and inquiry with symbolic interactionism for qualitative research and its epistemology. We have developed conceptual model with scenario and storyboard method, and developed vertical prototype with Flash.

• Communications of Mathematical Education
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• v.36 no.3
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• pp.373-395
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• 2022

This study aimed to examine how prospective mathematics teachers (PMTs) perceive collaborative problem-posing (CPP) as a method to cultivate students' creativity and character in mathematics education. This is to propose the introduction of CPP at the stage of preparatory math teacher education as one of the ways to reinforce the creativity and character education capacity of PMT), and to attempt to be an opportunity to actively utilize CPP in math teaching-learning in the school field for the education of students' creativity and character. To achieve this objective, I designed PMTs taking the 'Educational Theories for Teaching Mathematics' course, required in the second year of university, to experience CPP tasks. Data were collected through questionnaires or interviews over three years on how PMTs recognized the CPP tasks as a tool to cultivate students' creativity and character in secondary schools. The results of the study are as follows. First, PMTs recognized regardless of their CPP experience that CPP might have a positive impact on improving students' ability to devise various ideas and that it positively influences students' attitudes toward building interpersonal relationships, including teamwork, respect, and consideration. Second, the experience of PMTs participating in the CPP made them more positively aware that CPP is effective in improving students' ability to elaborate on ideas. Third, the PMTs' experience of participating in CPP led to a more positive perception of the impact of CPP on the students' abilities and attitudes, namely, the students' ability to elaborate on ideas and their inner attitudes toward individuals, including honesty, fairness, and responsibility, and the attitude of students regarding logically presenting their opinions and making rational decisions. Finally, if there are downsides to the offline environment, an online environment may be more beneficial.