Chun Fu Lin

Data mining for providing a personalized learning path in creativity: An application of decision trees

Customizing a learning environment to optimize personal learning has recently become a popular trend in e-learning. Because creativity has become an essential skill in the current e-learning epoch, this study aims to develop a personalized creativity learning system (PCLS) that is based on the data mining technique of decision trees to provide personalized learning paths for optimizing the performance of creativity. The PCLS includes a series of creativity tasks as well as a questionnaire regarding several key variables. Ninety-two college students were included in this study to examine the effectiveness of the PCLS. The experimental results show that, when the learning path suggested by a hybrid decision tree is employed, the learners have a 90% probability of obtaining an above-average creativity score, which suggests that the employed data mining technique can be a good vehicle for providing adaptive learning that is related to creativity. Moreover, the findings in this study shed light on what components should be accounted for when designing a personalized creativity learning system as well as how to integrate personalized learning and game-based learning into a creative learning program to maximize learner motivation and learning effects.

How stress influences creativity in game-based situations

This study aims to integrate neuroscientific techniques into a behavioral experimental design to investigate how stress stimuli may influence stress hormones and negative emotions, subsequently affecting working memory (WM) and creativity in game-based situations. Ninety-six college students participated in this study, in which a game-based experiment lasting 90?min was employed. The main findings were that (1) the employed stress stimuli influence creativity during gaming through two routes: enhancing creativity through cortisol concentration and WM and decreasing creativity by provoking promotion-focused negative emotions (frustration and anger); and (2) the subjective negative emotions and objective cortisol responses do not consistently predict WM and creativity in game-based situations. Accordingly, appropriate challenges or stressors that help increase the cortisol concentration to an attentional level without provoking a strong sense of promotion-focused negative emotions should be considered when designing games aimed at teaching creativity. Stress influences creativity during gaming through two routes.Working memory is a mediator of cortisol response and game-based creativity.Cortisol responses influence working memory during gaming.Highly activated and promotion-focused negative emotions decrease creativity.

Developing a Dynamic Inference Expert System to Support Individual Learning at Work.

In response to the rapid growth of information in recent decades, knowledge-based systems have become an essential tool for organizational learning. The application of electronic performance-support systems in learning activities has attracted considerable attention from researchers. Nevertheless, the vast, ever-increasing amount of information is creating management problems regarding the efficiency and accuracy of knowledge retrieval. This study aims to develop a dynamic inference expert system ( DIES) to solve these problems. DIES integrates web technology, knowledge management, Extensible Markup Language ( XML) and C Language Integrated Production System ( CLIPS) to facilitate the convenience of knowledge retrieval and the efficiency of learning at work. The advantages of XML include scalability, sharing, easy readability and the ability to enhance the efficient management of knowledge-based systems. In DIES, organizational knowledge is automatically generated as machine-readable language and knowledge description, using CLIPS as a rule-conduction tool to develop specific organizational knowledge bases. A data source consisting of 22 participants from different industries was employed to examine the effectiveness of DIES. Results indicate that participants intend to apply DIES within their industries, with a 95% probability of attaining above-average satisfaction. [ABSTRACT FROM AUTHOR]

Survey of software literacy, behavior and personal traits of freshmen accounting majors

In recent decades, the rapid growth of technology has resulted in software being widely applied in various domains. Attitudes toward using software play an important role in every industry. This study aims to explore the software literacy of accounting students along with their personal traits, such as learning styles and user behavior. This was a twofold study; we aimed to investigate the learning styles of accounting students and also discuss the correlation between learning styles and software literacy. Eighty-six freshmen, majoring in accounting, were participants in this study, and the results reveal that a sequential learning style is the variable most related to software literacy. Furthermore, we also found that most of the accounting freshmen utilize an active, sensing, visual and sequential learning style. [ABSTRACT FROM AUTHOR]

Hybrid Learning Style and Learning Preference to Explore New Learners' Feature

personalized learning can detect feature of learners to provide different assistant for individual learner. Learning style is an important feature for learners that reflect the pattern of learners in in learning situations. In this study, learning style and learning preference were be analysed to find new learning feature of learners. 94 participants were invited in this study. Analysis results show that: learning preferences and learning styles has significant differences in statistical tests. Keywords— learning style, learning preference, personalized learning.

An Evaluation Agent System for Enhancing Wikipedia Management

Wikipedia has recently become a popular platform for knowledge sharing and creation. However, the enormously increasing amount of editing has caused management problems with efficiency, accuracy, and convenience for Wikipedia administrators. This study, therefore, aimed to develop an intelligent agent system based on Web 3.0, the evaluation agent system (EAS), to solve these problems. The EAS is characterized by hybrid Web techniques, artificial intelligence, integration of management guidelines, retrieval of real-time information, and the transfer of cross-platform data and includes the following three systems: the testing agent, the wiki agent, and the rule-based expert system (RBES) agent. Because the RBES was central to the EAS, 29 university students were included in the study to examine the effectiveness of the RBES compared to the conventional approach to administration. The findings revealed that the RBES was better than the conventional approach in accuracy, efficiency, operation convenience, and fatigue strength.