Enhancing Example-Based Learning in Hypertext Environments

Enhancing Example-Based Learning in Hypertext Environments Julia Schuh (j.schuh@iwm-kmrc.de ) Virtual Ph.D. Program: Knowledge Acquisition and Knowledge Exchange with New Media Konrad-Adenauer-Strasse 40, 72072 Tuebingen Germany Peter Gerjets (p.gerjets@iwm-kmrc.de) Multimedia and Hypermedia Research Unit, Knowledge Media Research Center Konrad-Adenauer-Strasse 40, 72072 Tuebingen, Germany Katharina Scheiter (k.scheiter@iwm-kmrc.de) Department of Applied Cognitive Psychology and Media Psychology, University of Tuebingen Konrad-Adenauer-Strasse 40, 72072 Tuebingen, Germany Abstract In previous research, Gerjets, Scheiter, and Tack (2000) demonstrated that learners experience serious difficulties in utilizing instructional examples according to their profitability when interacting with a hypertext-based learning environment. In this paper we focus on possible causes of these difficulties and on different instructional methods for improving learners' utilization of worked-out examples in hypertext environments. The results of two experimental studies are reported. Learning from Worked-Out Examples: The Role of Example Processing Strategies and Example Design Research over the last 15 years in the domain of learning and problem solving has demonstrated that instructional examples play an important role for knowledge acquisition in domains like mathematics, physics, or programming (Chi, Bassok, Lewis, Reimann, & Glaser, 1989). In particular for initial skill acquisition, learning from worked-out examples seems to be superior to actively solving training problems (Sweller, van Merrienboer, & Paas, 1998). However, numerous findings also indicate major drawbacks of example-based learning. In particular, poor learners tend to overuse examples during problem solving without reflecting on their appropriateness (VanLehn & Jones, 1993). In addition, learners have difficulties identifying relevant information in worked-out examples and are often distracted by examples' surface features (Ross, 1989). Furthermore, Renkl (1999) assumes that students often suffer from illusions of understanding when learning from worked-out examples. I.e., they may have the false impression of having grasped the solution rationale of an example problem. Finally, learners have difficulties generalizing solutions from examples to novel problems (Catrambone & Holyoak, 1989; Reed, Dempster, & Ettinger, 1985). A number of empirical studies have identified features of example processing strategies and example design that are efficient for successful knowledge acquisition (cf. Atkinson, Derry, Renkl, & Wortham, 2000). •Important strategical aspects mainly concern the adequate selection and elaboration of instructional examples. Reed, Ackinclose, and Voss (1990) showed that learners failed to select sufficiently complex instructional examples for learning although the profitability of these examples for subsequently solving test problems could be demonstrated. However, Reed, Willis, and Guarino (1994) found that learners who were allowed to select worked-out examples while solving test problems were able to select suitable examples. Additionally, it has been shown that self- explanations are an important aspect of good learners’ example processing (Chi et al., 1989; Pirolli & Recker, 1994; Renkl, 1997). In particular, anticipations of solution steps and inferences with regard to the relations between solution steps, goals, and abstract principles have been proven useful for knowledge acquisition. •With respect to design issues it could be shown that multiple examples can support schema induction which helps learners to solve novel problems (Cummins, 1992). Providing multiple examples with different surface features might further improve this process of abstraction (Quilici & Mayer, 1996). Additionally, it has been proposed that the provision of completion problems - where learners have to fill in some details of worked-out examples’ solution steps - is a helpful instructional device as it fosters self-explanations (Van Merrienboer, 1990). In particular, presenting completion problems along with evaluative feedback on subjects’ gap-filling performance seems to improve learning outcomes. For instance, Stark (1999) showed that learners benefit from such a combination of completion problems and feedback and stresses the point that completion problems foster example elaboration whereas giving feedback on the learning success might prevent learners from illusions of understanding. From these findings on learning from examples it can be argued that strategies of example selection and processing as well as features of example design have to be taken into account to improve learning outcomes. The aspect of adopting suitable strategies gains increasing importance the more the control of the learning process is left up to the learner. In learning situations where the learner can select instructional material as well as determine the sequence and the pace of presentation, the importance of strategies increases (Gerjets, Scheiter, & Tack, 2000). Therefore, an identification of suitable strategies of information utilization and an examination of whether learners can adopt these strategies is highly relevant when more focus is put on self-regulated learning in the field of instruction.