• Journal of Fisheries and Marine Sciences Education
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• v.26 no.2
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• pp.296-307
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• 2014

As an educational trial for pursuit of educational excellence in the disadvantaged gifted, this study was to explore learning styles and task preferences by student's grade and gender. Furthermore, this study sought to present the practical basis to develop programs for disadvantaged gifted students. Total 153 disadvantage gifted students responded items of the Learning Styles Inventory-III and the Task Preferences Scale, which responses were analyzed by student's grade and gender in using MANOVA. As the results, the 1st grade disadvantaged gifted students preferred Direct instruction, Technology, and Learning games to the higher grade level students. There were significant differences in task preferences by students' grade level. The 4th grade disadvantaged gifted students preferred Creative tasks and Difficult tasks more than other grade level students.

• English Language & Literature Teaching
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• v.16 no.1
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• pp.123-142
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• 2009

The present study used multi-faceted Rasch measurement to explore the characteristics and bias patterns of non-native raters when they scored L2 writing tasks. Three raters scored 254 writing tasks written by Korean university students on two topics adapted from the TOEFL Test of Written English (TWE). The written products were assessed using a five-category rating scale (Content, Organization, Language in Use, Grammar, and Mechanics). The raters only showed a difference in severity with regard to rating categories but not in task types. Overall, the raters scored Grammar most harshly and Organization most leniently. The results also indicated several bias patterns of ratings with regard to the rating categories and task types. In rater-task bias interactions, each rater showed recurring bias patterns in their rating between two writing tasks. Analysis of rater-category bias interaction showed that the three raters revealed biased patterns across all the rating categories though they were relatively consistent in their rating. The study has implications for the importance of rater training and task selection in L2 writing assessment.

• The Journal of Korea Robotics Society
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• v.19 no.2
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• pp.196-202
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• 2024

The ability to understand given environments and plan a sequence of actions leading to goal state is crucial for personal service robots. With recent advancements in deep learning, numerous studies have proposed methods for state representation in planning. However, previous works lack explicit information about relationships between objects when the state observation is converted to a single visual embedding containing all state information. In this paper, we introduce graph-based state representation that incorporates both object and relationship features. To leverage these advantages in addressing the task planning problem, we propose a Graph Neural Network (GNN)-based subgoal prediction model. This model can extract rich information about object and their interconnected relationships from given state graph. Moreover, a search-based algorithm is integrated with pre-trained subgoal prediction model and state transition module to explore diverse states and find proper sequence of subgoals. The proposed method is trained with synthetic task dataset collected in simulation environment, demonstrating a higher success rate with fewer additional searches compared to baseline methods.

• The Mathematical Education
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• v.55 no.1
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• pp.107-127
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• 2016

The purpose of this study was to explore the possibility of mathematical instruction through performance task activities based on the The Backward Design, which was suggested at first by Wiggins & McTighe in 1998. The Design deals with a performance assessment task involving the whole objective and its entire content of a lesson. Based on the Backward Design, this study established the mathematical instructional materials, which deal with the concept of 'the sector' taught in middle school, with one large performance task including three small tasks. It is important that in the lesson students be guided to achieve the several learning goals by themselves through reasoning activities. For this purpose, a formal interview was carried out by the subject of three middle school mathematics teachers. As a result, in order to implement the instruction utilizing the performance tasks more efficiently in future, it is required that a large performance task should be selected or developed including the content or problem contexts to be relevant with the real-life challenging situations. In addition, to make students enhance reasoning skills, it is strongly requested that the tasks including the utilization of supplementary materials such as technological devices or manipulatives be dealt with in a lesson.

• Journal of Environmental Health Sciences
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• v.45 no.6
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• pp.569-576
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• 2019

Objectives: The main purpose of this study was to assess firefighters' daily personal noise exposure and explore noise levels related to specific tasks and their contributions to total noise exposure using 24-hour full-shift noise exposure measurements with task-based data. Methods: Noise exposure was assessed for eight firefighters (two rescuers, two drivers, and four suppressors) using time-activity diaries. We collected a total of 24 full-shift personal noise sample sets (three samples per a firefighter). The 24-hour shift-adjusted daily personal noise exposure level (L_ep,d), eight weekly personal noise exposures (L_eq,w), and 40 task-specific L_eq values (L_{eq activity}) were calculated via the ISO/NIOSH method. Results: The firefighter noise-sample datasets showed that most firefighters are exposed to noise levels above EU recommended levels at a low-action value. The highest noise exposure was for rescuers, followed by drivers and suppressors. Noise measurements with time-at-task information revealed that 82.3% of noise exposure occurred when checking equipment and responding to fire or emergency calls. Conclusions: The results indicate that firefighters are at risk of noise-induced hearing loss. Therefore, efforts at noise-control are necessary for their protection. This task-specific noise exposure assessment also shows that protective measures should be focused on certain tasks, such as checking and testing equipment.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.9
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• pp.781-790
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• 2020

This study's primary purpose is to explore the psychological capital roles and personality traits of Big-Five in predicting OCB (organizational citizenship behavior) and performance of task in Indonesia's electricity sector. The data were gathered from the employees of four major cities in Indonesia, in Southeast Sulawesi, comprising 246 employees. The data were analyzed utilizing a PLS (partial least squares) based SEM (structural equation modeling) technique. The findings indicate that the psychological capital and personality traits of Big-Five relate significantly to OCB and the performance of task. Nevertheless, against our expectations, OCB does not significantly relate to the performance of task. This study also discusses the findings' further implications. In terms of practical implications, the findings of this research stipulate that psychological capital and Big-Five personality traits aimed to improve employee performance and can be most effective if specifically targeted at OCB. Given that both variables play an important role to promote OCB, caring training initiatives that focus on mutual help can be very valuable for organizational improvement. In a managerial perspective, organizations can increase OCB by conducting open communication strategies between managers and employees to further stimulate and strengthen the ability of employees to display extra-role behaviors.

• Asia pacific journal of information systems
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• v.24 no.3
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• pp.345-370
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• 2014

The notion of technological adoption such as Radio Frequency Identification (RFID) has been examined in various domains such as supply chain management, inventory management and health care. However, there are several unanswered questions surrounding how this technology is adopted in disaster management. This study attempts to explore the potential of RFID in disaster management. The notion of Task-Technology Fit (TTF) is deemed suitable for this purpose and thus used as the theoretical framework that is further validated by employing multiple case studies. The empirical findings indicate that there are six key factors influencing the decision to adopt RFID in disaster management. Some relate to aspects of RFID when it is put into practice, namely cost, compatibility, standardisation, implementation and locatability; while the other key factor relates to privacy and security aspect of information. It is hoped that the findings of this research will inform disaster management organizations to better plan the adoption of RFID for their operations.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.400-400
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• 2000

This paper purposed that verify the validity of Petri Net method for control progressive increase of system complexity, before extend the realized single robot system to multi-robot system. An autonomous mobile robot(AMR) needs decision making, motion control, path planning, tracking a path, obstacle avoidance, and sensor fusion, to complete its task. An AMR integrates and operates these technics through a consistent command system. An error in a command hierarchy which is like duplication or omission of a control command hierarchy for each module results in serious problems. This paper minimizes the error by modeling each module and whole system using Petri Net graphical representation and applies it to the exploration task of an AMR

• Research in Mathematical Education
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• v.16 no.3
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• pp.155-176
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• 2012

It is an important issue to explore classroom environments which are conducive to developing students' mathematical performance. This study explores the effects of different classroom environments (solution-demand and corresponding-time setting) on mathematical performances. Fourteen and eighteen prospective teachers were required to prove a task under different conditions respectively: a) Cognitive demand of multiple-solution corresponding time of three hours, and b) Cognitive demand of a right solution corresponding time of 20 minutes. We used SOLO as the assessment tool for mathematical performance from quality perspective. Significant differences were found in the quantity and quality of mathematical performance. The regular environment focusing on speed and accuracy were found to be directly linked to low levels of performance. The findings above provide implications to the cognitive benefits of multiple-solution demand and corresponding time setting.

• Journal of Information Technology Applications and Management
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• v.29 no.5
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• pp.13-25
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• 2022

The purpose of this study is to explore the factors that influence the purchase of AI speakers in China. We integrate the Unified Theory of Acceptance and Use of Technology (UTAUT) and Task-technology fit (TTF) model into one model and put forward assumptions. According to the characteristics of AI speakers, we selected 6 independent variables, such as Performance Expectation, Effort Expectation, Social Influence, Facilitating Conditions, Task and Technology-characteristics. The final impact on purchase behavior is evaluated through Task-technology fit and purchase intention. After counting 478 samples, through SPSS22.0 and AMOS analysis, hypotheses have been proved by strong experimental data, except facilitating conditions. These results also imply that improving the technical level of AI speakers and enhancing consumers' purchasing intention are the central line of marketing. Based on this, we put forward several suggestions to marketers, including strengthening the research and development of AI speaker technology, and building a circle of friends of AI speakers.