Elsevier

Computers & Education

Volume 51, Issue 2, September 2008, Pages 926-938
Computers & Education

A novel approach for assisting teachers in analyzing student web-searching behaviors

https://doi.org/10.1016/j.compedu.2007.09.011Get rights and content

Abstract

Although previous research has demonstrated the benefits of applying the Internet facilities to the learning process, problems with this strategy have also been identified. One of the major difficulties is owing to the lack of an online learning environment that can record the learning portfolio of using the Internet facilities in education, such that the teacher can analyze and evaluate the learning performance of students, and hence the teaching strategies can be adjusted accordingly. In this paper, we propose a web-search learning environment, called Meta-Analyzer, which is able to assist the teachers in analyzing student learning behaviors of using search engines for problem solving. Two-hundred and twenty students and 54 teachers contributed to the trial of the system. The results have shown that the novel approach is able to gain a better understanding about students’ learning processes and searching strategies in technology-enhanced environments, as well as to assist the teachers to acquire more about the learning status of students, and hence more constructive suggestions can be given accordingly.

Introduction

The rapid progress in information technology can help instructors to teach more efficiently and effectively by employing new strategies with appropriate software tools and environments (Fabos & Young, 1999). Several studies have demonstrated the benefits of applying information technologies to instruction, such as Computer scaffolding (Guzdial et al., 1996), Computer-Supported Collaborative Learning (CSCL, e.g., Harasim, 1999), Computer-Supported Intentional Learning Environments (CSILE, e.g., Scardamalia, Bereiter, McLean, Swallow, & Woodruff, 1989) and Computer-Integrated Classroom (CiC, e.g., Eshet, Klemes, & Henderson, 2000). Earlier studies of educational tools focused on the development of Computer-Assisted Instruction (CAI) systems. A CAI system can be perceived as a tutorial system, which is a guided system to provide well-constructed information. For example, Burks (1996) presented computer-based tutorials and a virtual classroom to teach circuit analysis; Gang, Jason, and Peter (1996) proposed a tutorial system by using artificial intelligence technology. Some researchers utilized auxiliary software to enhance their tutorial systems (Robert, 1996, William and Marion, 1996), some provided interactive tutorials for manuals with graphical user interface (Sally, 1996) or with rich multimedia formats (Pui & William, 1996). The study of Barrett and Lally (1999) showed the effectiveness of such computer-assisted instruction systems based on empirical evaluation. Davidovic, Warren, and Trichina (2003) also concluded that greater efficiency can be achieved by basing the system development on the theoretical background of cognitive knowledge acquisition.

Recently, the efficiency and popularity of the Internet has received much attention that has motivated efforts towards integrating Web-based learning activities into the curriculum (Chang, 2001, Huang and Lu, 2003, Khan, 1997, Tsai et al., 2001, Tsai and Tsai, 2003). Considerable work has been conducted on the use of Internet as a distance-learning tool (Apkarian & Dawer, 2000), and the use of Web-based simulation tools for education (Sreenivasan, Levine, & Rubloff, 2000). Moreover, some practical usages of Web-based educational systems in industrial training courses have been reported (Poindexter & Heck, 1999). In addition to their obvious use in a distance-learning scenario, those educational tools can also be used to enrich classroom experience through the use of a data projector (Ringwood & Galvin, 2002).

One of the greatest benefits of Web-based learning activities is to allow students to participate in learning as active and self-directed participants (Tsai, 2001). Web-based learning activities often involve information-searching tasks, as Web-based environments are connected with information sites worldwide. The increased access to the Web has raised many issues, including the strategies of information-seeking and use, the skill of processing Web information, the roles of teachers in educating and training, and the development of new environments that facilitate teachers to observe and analyze the information-seeking behaviors of students in Web-based learning environments (Bilal, 2000). Hess (1999) reported that users’ cognitive strategies, especially information processing skills, determine a successful search on the Internet. Graff (2005) indicated the differences in web browsing strategies not only between older and younger participants, but also between individuals displaying verbalizer and imager cognitive styles; moreover, Song and Salvendy (2003) emphasized the importance of reusing individual Web browsing experiences. Therefore, it has become an important and challenging issue to observe and analyze the information-searching behaviors of students in Web-based learning environments (Zaphiris, Shneiderman, & Norman, 2002).

In the past decade, several studies (e.g., Bilal, 2000, Poindexter and Heck, 1999, Tsai and Tsai, 2003) have been conducted to analyze the learning behaviors of students in using search engines to collect information for problem solving. Research has indicated that children are more persistent and motivated in seeking information over the Web than in using traditional and online sources (Bilal, 2000). However, it appears to be difficult for Internet novice users to search information effectively and efficiently through the web (Marchionini, 1995). Researchers found that, disorientation is one of the problems that novice explorers tend to have while navigating within a hyperspace (Dias, Gomes, & Correia, 1999); therefore, training novice users, especially children, to use search engines to collect information for problem solving in elementary schools has become an important and challenging issue. Nevertheless, recent studies also indicated that teacher anxiety can often reduce the success of such technological and pedagogical innovations (Chou, 2003, Todman and Day, 2006). The anxiety is owing to the lack of sufficient knowledge to apply those computer systems to their classes, which has become a barrier to conduct information technology-applied instructions (Namlu & Ceyhan, 2003). As most of those online educational tools focus on the student-centered design, necessary supports to assist the teachers in designing learning activities and analyzing student learning performance are often ignored.

Bilal (2000) indicated several limitations in analyzing student learning behaviors of using search engines by an exit interview, including the reliability of the students’ affective states gathered from it. Owing to the lack of technical supports, most researchers adopted the qualitative method using an exit interview relied on students’ perceptions of and feelings about their experiences with the search engines; therefore, the reliability of the studies may be threatened unless a careful check can be made on the videotapes of traversal activities or the verbalization during traversal, which is known to be time-consuming. Consequently, to allow the researchers and the teachers to make precise quantitative analysis on student learning behaviors, the development of a web-search learning environment, which can record students’ problem-solving behaviors of using search engines, is needed. To cope with this problem, in this paper, we propose a web-search analytic environment, called Meta-Analyzer, to assist teachers in observing and analyzing student learning behaviors.

Section snippets

Method

To assist the teachers in tracing and analyzing the information-searching behaviors of students, a Web-based learning environment, Meta-Analyzer, has been developed. Moreover, a series of investigations have been conducted to demonstrate the usefulness of the innovative approach.

Results and discussion

A series of investigations has been conducted to evaluate the usefulness of Meta-Analyzer. It should be noted that development of Meta-Analyzer aims to record and represent online behaviors, rather than measure the actual quality of the information obtained by the students.

Conclusions

Although the study of web-search behaviors is known to be an important issue, previous reports also depict its challenges (Bilal, 2000, Bilal and Kirby, 2002, Tsai and Tsai, 2003). Without any technical assistance, researchers had to use some screen capture software or video camera to record the student online activities. That is, they had to spend a very long time on browsing the web-search portfolio and take notes manually. In this paper, a Web-based environment, Meta-Analyzer, for recording

Acknowledgement

This study is supported in part by the National Science Council of the Republic of China under contract numbers NSC 95-2524-S-024-002 and NSC 95-2520-S-024-003.

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