Matching presentational tools' ontology to part-task demands to foster problem-solving in business economics

Collaborative problem-solving is often regarded as an effective pedagogical method beneficial for both group and individual learning. The premise underlying this approach is that through a dynamic process of eliciting one’s own knowledge, discussing this with peers, and establishing and refining the group’s shared understanding of the knowledge domain, students acquire new knowledge and skills and process them more deeply (e.g., O'Donnell, Hmelo-Silver, & Erkens, 2006). However, due to its complexity (i.e., diversity in concepts, principles and procedures, see Miller & VanFossen, 2008) students in business economics encounter difficulties with acquiring a well-developed understanding of the knowledge domain (e.g., Marangos & Alleys, 2007). When solving problems, students, therefore, rely primarily on surface features such as using objects referred to in the problem instead of the underlying principles of the knowledge domain, and employ weak problem-solving strategies such as working via a means-ends strategy towards a solution (e.g., Jonassen & Ionas, 2008). This hinders students in effectively and efficiently coping with their problem-solving task because the ease with which a problem can be solved often depends on the quality of the available problem representations (e.g., Ploetzner, Fehse, Kneser, & Spada, 1999). To this end, it would be beneficial if students are supported in acquiring and applying suitable representations (e.g., Ainsworth, 2006). Research on concept mapping (Nesbit & Adesope, 2006; Roth & Roychoudhury, 1993) has shown that the collaborative construction of external representations (i.e., concept maps) can guide students’ collaborative cognitive activities and beneficially affect learning. Due to its ontology (i.e., objects, relations, and rules for combining them, see Van Bruggen, Boshuizen, & Kirschner, 2003) a representational tool enables students to co-construct a domainspecific content scheme fostering students’ understanding of the knowledge domain in question. Problemsolving tasks, however, are usually composed of fundamentally different part-tasks (i.e., problem orientation, problem solution, solution evaluation), that each requires a different perspective on the knowledge domain and, thus, another representational tool with a different ontology. To be supportive for problem-solving, the ontology provided in a representational tool must be matched to the part-task demands and activities of a specific problem phase. Otherwise, effective problem-solving may be hindered (e.g., Van Bruggen et al.). The goal of the study presented in this paper is to determine whether an instructional design aimed at providing ontologically part-task congruent support in the representational tools leads to more successful problem-solving performance in the field of business economics.