• Journal of Information Processing Systems
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• v.17 no.4
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• pp.721-736
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• 2021

For the mobile edge computing (MEC) system supporting dense network, a joint allocation algorithm of computing and communication resources based on reinforcement learning is proposed. The energy consumption of task execution is defined as the maximum energy consumption of each user's task execution in the system. Considering the constraints of task unloading, power allocation, transmission rate and calculation resource allocation, the problem of joint task unloading and resource allocation is modeled as a problem of maximum task execution energy consumption minimization. As a mixed integer nonlinear programming problem, it is difficult to be directly solve by traditional optimization methods. This paper uses reinforcement learning algorithm to solve this problem. Then, the Markov decision-making process and the theoretical basis of reinforcement learning are introduced to provide a theoretical basis for the algorithm simulation experiment. Based on the algorithm of reinforcement learning and joint allocation of communication resources, the joint optimization of data task unloading and power control strategy is carried out for each terminal device, and the local computing model and task unloading model are built. The simulation results show that the total task computation cost of the proposed algorithm is 5%-10% less than that of the two comparison algorithms under the same task input. At the same time, the total task computation cost of the proposed algorithm is more than 5% less than that of the two new comparison algorithms.

• Journal of Korean Elementary Science Education
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• v.26 no.2
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• pp.141-148
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• 2007

This study proposed task-based teaming strategies as a means of fulfilling the demands and goals of the 7th national science curriculum. Task-based learning is based on the use of a series of activities whereby a teacher presents students with tasks related to daily lift and the students solve the tasks by themselves using various methods and thought processes and then present and discuss their results with each other. The tasks are selected from the 6-grade science textbook, are reconstructed and are then given to the classes. The tasks include whole class activities as well as individual activities related to the interests, abilities, and concerns of the students. The purpose of this study was to verify the effects of task-based learning classes on the science process skills and the scientific attitudes of elementary school students, when applied to 6th grade students. For this, the task-based learning activities were applied to an experimental group and expository teaching was applied to the comparison group. Both groups were given a pre-post test on science process skills and scientific attitudes. The results indicate that task-based loaming is very effective in the development of science process skills and scientific attitudes.

• The Journal of Korean Academic Society of Nursing Education
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• v.20 no.4
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• pp.577-586
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• 2014

Purpose: This study investigates patterns of small group interaction and examines the influence among graduate nursing students of online collaborative learning strategies on small group interaction patterns, task performance and learning attitude in web-based team learning environments. Method: To analyze patterns of small group interaction, group discussion dialogues were reviewed by two instructors. Groups were divided into two categories depending on the type of feedback given (passive or active). For task performance, evaluation of learning processes and numbers of postings were examined. Learning attitude toward group study and coursework were measured via scales. Results: Explorative interactions were still low among graduate nursing students. Among the students given active feedback, considerable individual variability in interaction frequency was revealed and some students did not show any specific type of interaction pattern. Whether given active or passive feedback, groups exhibited no significant differences in terms of task performance and learning attitude. Also, frequent group interaction was significantly related to greater task performance. Conclusion: Active feedback strategies should be modified to improve task performance and learning attitude among graduate nursing students.

• Journal of information and communication convergence engineering
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• v.18 no.4
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• pp.239-244
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• 2020

This study analyzed the influencing factors of learning engagement and teaching presence in online programming practice classes. The subjects of this study were students enrolled in an industrial specialized high school, who practiced creating Arduino circuits and programming using a web-based virtual practice tool called Tinkercad. This research adopted a tool that can measure task value, learning flow, learning engagement, and teaching presence. Based on this analysis, learning flow had a mediating effect between task value and online learning engagement, as well as between task value and teaching presence. Increasing learning engagement in online classes requires sensitizing the learners about task value, using hands-on platforms available online, and expanding interaction with instructors to increase learning flow of students. Furthermore, using virtual hands-on tools in online programming classes is relevant in increasing learning engagement. Future research tasks include: confirming the effectiveness of online learning engagement and teaching presence through pre- and post-tests, and conducting research on various practical subjects.

• Journal of Information Processing Systems
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• v.17 no.3
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• pp.441-452
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• 2021

Federated learning provides an efficient integrated model for distributed data, allowing the local training of different data. Meanwhile, the goal of multi-task learning is to simultaneously establish models for multiple related tasks, and to obtain the underlying main structure. However, traditional federated multi-task learning models not only have strict requirements for the data distribution, but also demand large amounts of calculation and have slow convergence, which hindered their promotion in many fields. In our work, we apply the rank constraint on weight vectors of the multi-task learning model to adaptively adjust the task's similarity learning, according to the distribution of federal node data. The proposed model has a general framework for solving optimal solutions, which can be used to deal with various data types. Experiments show that our model has achieved the best results in different dataset. Notably, our model can still obtain stable results in datasets with large distribution differences. In addition, compared with traditional federated multi-task learning models, our algorithm is able to converge on a local optimal solution within limited training iterations.

• The Journal of the Korea Contents Association
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• v.22 no.6
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• pp.413-427
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• 2022

The purpose of this study was to improve and verify task value and academic self-efficacy of university students with metaverse gamification teaching method combining flipped learning and project-based learning. The subjects in this study were 16 university students majoring in counseling psychology who engaged in K university in cheong-ju. The subjects were assigned to the experimental group or the comparison group. The experimental group received the proposed metaverse gamification teaching method combining flipped learning and project-based learning while comparison group received teacher-centered learning. The dependent variables in this study were task value and academic self-efficacy. Each variable was assessed before class, after the end of the class. At the end of the class, the experimental group engaged statistically significantly higher levels of task value and academic self-efficacy than the comparison group. The findings of this study suggest that this metaverse gamification teaching method combining flipped learning and project-based learning is effective at improving task value and academic self-efficacy.

• Journal of dental hygiene science
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• v.22 no.2
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• pp.126-129
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• 2022

Background: The problem with current dental hygienist education is that it operates as an education system based on the national examination rather than on a practical basis; thus, graduates have difficulties in practice after obtaining their license. This study aimed to propose a job-oriented curriculum by analyzing the links between the task analysis of Korean dental hygienists and dental hygiene learning goals. Methods: This study performed a relationship analysis based on a second job analysis study of dental hygienists conducted by the Korea Health Personnel Licensing Examination Institute and the learning goals of the Korean Dental Hygiene Faculty Association. Results: Based on the links between the task and learning goals of the dental hygienist, they were classified into six types: 1) tasks listed in the license exam and learning goal, 2) tasks not listed in the license exam but listed in learning goals, 3) tasks not listed in learning goals, 4) learning goals not related to tasks, 5) learning goals listed in a few tasks, and 6) tasks related to several learning goals. The results showed that most of them correspond to the 5th classification, followed by the 3rd and 4th categories, which are mostly basic science learning goals. Tasks without learning goals are not included in the curriculum; thus, the curriculum needs to be supplemented. The overlapping learning goals of several subjects for one job skill must be reduced in job-oriented education. Conclusion: We suggest that the dental hygiene curriculum be developed based on task analysis and reflected in the national dental hygienist exam. The clinical practice performance of dental hygienists will take further leap forward through task-oriented education.

• English Language & Literature Teaching
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• v.11 no.4
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• pp.365-389
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• 2005

The purpose of this study is to present the task model that is the most effective in English language methodology based on the investigation of task-based performance in Korean EFL classroom practice. The subjects were 538 high school students and 126 high school teachers, each of whom had common experiences using the materials of task-based activities for more than one year. To analyze the data, the program SPSS WIN 11.0 including frequency distribution and chi-square analysis was used. The results of the questionnaire analysis showed that both teachers and students had a comparatively high level of satisfaction in task rationale, but that they had some mixed responses in the fields of input data, settings, and activity types. To conclude, a few suggestions are made to provide some meaningful considerations for the EFL teachers and material developers: a) task goals and rationale that encourage the learner's positive motivation; b) authenticity of input data based on the real-world context; c) collaborative learning environment that enhances communicative interaction; d) proportional representation of the creative problem-solving activities related to discussions and decision-making processes; e) systematic introduction of integrated language skills. It also suggests that the multi-lateral task model, which has some positive assets compared to previous task models, be newly introduced and applied to the second language learning classrooms.

• The Journal of Korea Robotics Society
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• v.16 no.1
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• pp.56-63
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• 2021

As the use of robots in service area increases, research has been conducted to replace human tasks in daily life with robots. Among them, this study focuses on the tidy-up task on a desk using a robot arm. The order in which tidy-up motions are carried out has a great impact on the success rate of the task. Therefore, in this study, a neural network-based method for determining the priority of the tidy-up motions from the input image is proposed. Reinforcement learning, which shows good performance in the sequential decision-making process, is used to train such a task planner. The training process is conducted in a virtual tidy-up environment that is configured the same as the actual tidy-up environment. To transfer the learning results in the virtual environment to the actual environment, the input image is preprocessed into a segmented image. In addition, the use of a neural network that excludes unnecessary tidy-up motions from the priority during the tidy-up operation increases the success rate of the task planner. Experiments were conducted in the real world to verify the proposed task planning method.

• Journal of Internet Computing and Services
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• v.11 no.5
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• pp.95-104
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• 2010

As the computer and the communication technology are an unity, the collaborative learning based on constructivism is emphasized more than learning by forming external representation. Especially, online has characteristics not only to facilitate collaborative activities but to make students collaborators. In online collaborative learning, learning task is an integrated element in course design and an important portion deciding learning design, learning environment and learning process. Thus this study explored collaborative learning model according to the learning task type.