Web-based undergraduate chemistry problem-solving: The interplay of task performance, domain knowledge and web-searching strategies Hsiao-Ching She a, * , Meng-Tzu Cheng c , Ta-Wei Li b , Chia-Yu Wang a , Hsin-Tien Chiu b , Pei-Zon Lee a , Wen-Chi Chou a , Ming-Hua Chuang a a Institute of Education, National Chiao Tung University, Taiwan, ROC b Department of Applied Chemistry, National Chiao Tung University, Taiwan, ROC c Department of Biology, National Changhua University of Education, Taiwan, ROC article info Article history: Received 12 November 2010 Received in revised form 15 February 2012 Accepted 16 February 2012 Keywords: Applications in subject areas Post-secondary education Teaching/learning strategies abstract This study investigates the effect of Web-based Chemistry Problem-Solving, with the attributes of Web- searching and problem-solving scaffolds, on undergraduate students’ problem-solving task performance. In addition, the nature and extent of Web-searching strategies students used and its correlation with task performance and domain knowledge also were examined. We recruited a total of 183 undergraduate students, all of whom are taking the freshman chemistry course, to participate in the study to solve three chemistry tasks across a semester. Mandated screen-capture software captured participants’ on-screen Web-searching processes were recorded every five seconds. Results demonstrated that students’ problem-solving performance was significantly improved from task 1 to 3, and students with more domain knowledge outperformed students with less domain knowledge. Students with higher problem- solving performance employed more existing knowledge and metacognitive Web-searching strategies; and students with lower problem-solving performance employed more cognitive Web-searching strat- egies. In addition, students’ problem-solving performance was correlated with their domain knowledge, use of existing knowledge, and metacognitive Web-searching strategies. Moreover, students’ use of existing knowledge was the major factor for predicting their problem-solving performance according to the regression model. Ó 2012 Elsevier Ltd. All rights reserved. 1. Introduction For more than two decades, problem-solving has been considered a pivotal ability for students (American Association for the Advancement of Science [AAAS], 1993; Bransford, Brown, & Cocking, 2000; Watts, 1994).Watts (1994) suggested that problem-solving could foster students’ ability to think, and even more to promote their creativity and motivation in learning science. Other researchers addressed the idea that problem-solving offers the potential to help students develop flexible knowledge and effective problem-solving skills (Hmelo-Silver, 2004). Problem-solving ability is important, therefore, we are specifically interested in examining undergraduate students’ chemistry problem-solving in the study. Thompson, Martin, Richards, and Branson (2003) reported that using a Web-based learning context can facilitate problem-solving instruction. However, many studies indicated that students’ failure to construct meaning from the problem statements, their inability to link the meaning of the problem with their prior knowledge, and a lack of the appropriate knowledge for specific content areas were possible reasons why problem-solving remains so difficult for students (Gabel, Sherwood, & Enochs, 1984; Lee, 1985). The question is how to structure a potential Web-based learning environment to overcome the obstacles reported above. We believe that there is a need to revisit theories of problem-solving to offer a more feasible and effective pathway to promote undergraduate students’ chemistry problem-solving. Researchers have proposed a number of problem-solving models over the last three decades. Garrison (1991) decomposed the process as problem identification, problem description, problem exploration, applicability, and integration. Other researchers divided the problem- solving process into four steps, which are problem representation, searching for solutions, and implementing solutions (Bransford, 1994; * Corresponding author. E-mail address: hcshe@mail.nctu.edu.tw (H.-C. She). Contents lists available at SciVerse ScienceDirect Computers & Education journal homepage: www.elsevier.com/locate/compedu 0360-1315/$ – see front matter Ó 2012 Elsevier Ltd. All rights reserved. doi:10.1016/j.compedu.2012.02.005 Computers & Education 59 (2012) 750–761