Using Concept Map to Evaluate Learning by Searching

Using Concept Map to Evaluate Learning by Searching Hitomi Saito (hsaito@auecc.aichi-edu.ac.jp) Aichi University of Education, 1 Hirosawa, Igaya, Kariya, Aichi, 448-8542, Japan Yuka Egusa (yuka@nier.go.jp) National Institute for Educational Policy Research, 3-2-2 Kasumigaseki, Chiyoda-ku, Tokyo, 100-8951, Japan Masao Takaku (TAKAKU.Masao@nims.go.jp) National Institute for Materials Science, 1-2-1 Sengen, Tsukuba, Ibaraki, 305-0047, Japan Makiko Miwa (miwamaki@ouj.ac.jp) The Open University of Japan, 2-11 Wakaba, Mihama, Chiba, 261-8586, Japan Noriko Kando (kando@nii.ac.jp) National Institute of Informatics, 2-1-2 Hitotsubashi Chiyoda-ku, Tokyo, 101-8430, Japan contexts, and investigate how people acquire knowledge dur- ing their search and what influence search topics and situa- tions have on their knowledge. We used concept maps to evaluate the knowledge acquired by the users and how their knowledge structure changed as a result of their searching for information on the Web. The concept map is a graphical representation that allows peo- ple to explicitly represent their knowledge (Novak & Gowin, 1984). The concept map consists of concept words, arrows that connect the concept words, and linking words (link la- bels on the arrows.) Concept maps have been used as measures to assess learn- ers’ knowledge and understanding. Meagher (2009) reported that the graph structures of concept maps became more com- plex from the first class in a course through the final exam. Rebich and Gautier (2005) also showed that the total number of useful items on post-course maps increased, while the total number of weak items and misconceptions decreased. Con- cept maps are also used to compare expert knowledge struc- tures with novice knowledge structures. Chi, Feltovich, and Glaser (1981) compared the categories used by experts and novices and their explanations about the problems to examine the relationship between categorization and representation of physics problems. They drew concept maps to compare ex- pert explanations with novice explanations. Some research on information seeking behaviors has used concept maps as a means of measuring the change in a learner’s knowledge. Vakkari and Pennanen (2003) explored how a student’s conceptual structure is related to search tac- tics and search success. They reported that, between the beginning and end of the overall task, different features of the student’s conceptual structures were connected to search success in terms of the useful documents they found. Cole, Lin, Leide, Large, and Beheshti (2007) focused on how stu- dents’ mental model diagrams for a topic were represented in an early exploration stage of the information-seeking process and they suggested a 12-category classification schema of the mental models. Our previous researches also have studied Abstract We defined learning while searching and browsing on the Web as ”learning by searching. ” We used concept map to evaluate how users’ knowledge structure changed as a result of their learning by searching. The influence of different topics and different scenarios was also investigated. In the experiment, participants were divided into divergent and convergent sce- nario groups. They were asked to assume the role of a journal editor and search for information to be presented at an editorial meeting. They performed two tasks within the topics of envi- ronment and travel. We compared the two concept maps drawn by the participants before and after the search and analyzed the web pages browsed by the participants during the tasks. The results showed that the participants’ knowledge representation dynamically changed through learning as a result of search- ing, and the topics and scenarios influenced their processes and changed their conceptual structures before and after searching. Keywords: Concept Map; Knowledge Structure; Information Seeking on the Web; Learning by Searching Introduction Searching on the Web is more than just a tool for information retrieval; it has used a tool for investigating, learning, and de- cision making. For instance, when people buy a new digital camera, they often search and browse many digital camera sites. During these activities, they learn and acquire knowl- edge about digital cameras (i.e., function, structure, price, de- sign, and size). We define this learning through searching and browsing on the Web as ”Learning by Searching. ” Learning by searching is considered a type of discovery learning. Discovery learning is inquiry-based, constructivist learning. The learner discover facts and relationships and new truths on their own (Bruner, 1967). Discovery learning fa- cilitates the learner’s spontaneous motivation and encourages discovery, as compared with learning by teacher instruction only. However, discovery learning is difficult for learners and research suggests that the effects of discovery learning are influenced by learning processes and the learner’s skill or motivation. Learning by searching is considered to have the same benefits and problems as the discovery learning, but the factors that affect learning by searching have not been inves- tigated. In this study, we focus on search topics and problem