Tzu-Chien Liu

Wireless and mobile technologies to enhance teaching and learning

This research aims to build a Wireless Technology Enhanced Classroom (WiTEC) that supports everyday activities unobtrusively and seamlessly in classroom contexts. This paper describes the integration of wireless LAN, wireless mobile learning devices, an electronic whiteboard, an interactive classroom server, and a resource and class management server to build the WiTEC. This contains a number of features that can support class members in various types of teaching and learning activities. Project-based learning is taken as a scenario to elaborate how teachers and students can engage in teaching and learning via WiTEC. Finally, a number of suggestions are discussed for further study.

Analysis of Learners' Navigational Behaviour and Their Learning Styles in an Online Course

Providing adaptive features and personalized support by considering students learning styles in computer-assisted learning systems has high potential in making learning easier for students in terms of reducing their efforts or increasing their performance. In this study, the navigational behaviour of students in an online course within a learning management system was investigated, looking at how students with different learning styles prefer to use and learn in such a course. As a result, several differences in the students navigation patterns were identified. These findings have several implications for improving adaptivity. First, they showed that students with different learning styles use different strategies to learn and navigate through the course, which can be seen as another argument for providing adaptivity. Second, the findings provided information for extending the adaptive functionality in typical learning management systems. Third, the information about differences in navigational behaviour can contribute towards automatic detection of learning styles, helping in making student modeling approaches more accurate.

The application of Simulation‐Assisted Learning Statistics (SALS) for correcting misconceptions and improving understanding of correlation

Simulation-based computer assisted learning (CAL) is recommended to help students understand important statistical concepts, although the current systems are still far from ideal. Simulation-Assisted Learning Statistics (SALS) is a simulation-based CAL that is developed with a learning model that is based on cognitive conflict theory to correct misconceptions and enhance understanding of correlation. In this study, a mixed method (embedded experiment model) was utilized to examine the effects of SALS-based learning compared with lecture-based learning. The sample was composed of 72 grade-12 students, who were randomly assigned to either the experimental group or the comparison group. The findings reveal that the SALS-based learning approach is significantly more effective than lecture-based learning, in terms of correcting students misconceptions and improving their understanding of correlation. The study also uses quantitative and qualitative data to examine how the learning model of the SALS-based learning approach contributes to the enhanced learning outcomes. Finally, practical suggestions were made with regard to directions for future studies.

Location-Based Adaptive Mobile Learning Research Framework and Topics

Location-based adaptive mobile learning utilizes a unique feature: location awareness of mobile devices in regards to other online learning to implement location-based functionalities or features to create adaptive and collaborative learning in mobile learning environment. There are many important research issues and technical challenges in the location-based adaptive mobile learning systems, including the assessment of learning in the mobile environment. In this paper, we present the research framework and topics related to the undergoing research project at Athabasca University towards the development of robust and effective location-based adaptive mobile learning systems. In addition, we also brief some the major research outcomes achieved so far within the project’s research framework.