A context-aware ubiquitous learning environment for conducting complex science experiments

Abstract

Context-aware ubiquitous learning (u-learning) is an innovative approach that integrates wireless, mobile, and context-awareness technologies to detect the situation of learners in the real world and provide adaptive support or guidance accordingly. In this paper, a context-aware u-learning environment is developed for guiding inexperienced researchers to practice single-crystal X-ray diffraction operations. Experimental results showed that the benefits of this innovative approach are that it is “systematic”, “authentic”, and “economical”, which implies the potential of applying it to complex science experiments, such as physics, chemistry or biotechnology experiments, for graduate and PhD students in colleges, or research workers in research institutes.

Introduction

In the past decade, the rapid advance in broadband and wireless Internet technologies has promoted the utilization of wireless applications in our daily lives. In the meantime, a variety of embedded and invisible devices, as well as the corresponding software components, have been developed and connected to the Internet wirelessly. This new Internet-ready environment has been called a ubiquitous computing environment, as it enables many people to seamlessly utilize huge amounts and various kinds of “functional objects” through network connections anytime and anywhere (Minami, Morikawa, & Aoyama, 2004). Another feature of the ubiquitous computing environment is the use of wireless communication objects with sensors, so that the system can sense user information and environmental information in the real world and then provide personalized services accordingly. Such a feature is often called “context awareness” (Khedr and Karmouch, 2004, Yang, 2006).

Recently, scholars of e-learning have noticed the progress of wireless communication and sensor technologies; therefore, the research issues have progressed from web-based learning to mobile learning (Chen, Chang, & Wang, 2008), and from mobile learning to context-aware ubiquitous learning (u-learning), in which the learning system can detect students’ behaviors and guide them to learn in the real world with personalized support from the digital world (Hwang, Tsai, & Yang, 2008).

Most of the previous studies concerning context-aware u-learning have been conducted on natural science courses (Chu et al., 2008, Rogers et al., 2005) or language training courses (Joiner et al., 2006, Ogata and Yano, 2004), and have aimed to guide the students to observe real-world objects or to experience real-world contexts. Only a few studies have attempted to apply this innovative approach to simple science experiments, such as computer hardware assembly (El-Bishouty, Ogata, & Yano, 2007). Moreover, although researchers have recognized the great potential of context-aware u-learning, few practical applications have been implemented owing to the insufficient experience in developing context-aware u-learning environments and designing learning activities.

In this paper, we attempt to develop a context-aware u-learning environment to assist novice researchers in learning a complex science experiment, that is, the single-crystal X-ray diffraction procedure; moreover, an expert system has been developed to instruct the learners based on the contexts sensed in the real world. From the feedback of several researchers who have experienced the learning environment, it is concluded that the innovative approach can improve the learning efficiency and effectiveness of the learners.