Determining the Effectiveness of Prompts for Self-Regulated Learning in Problem-Solving Scenarios

By Ifenthaler, Dirk | Educational Technology & Society, January 2012 | Go to article overview

Determining the Effectiveness of Prompts for Self-Regulated Learning in Problem-Solving Scenarios


Ifenthaler, Dirk, Educational Technology & Society


Introduction

Self-regulated learning is regarded as one of the most important skills needed for life-long learning. Zimmerman (1989, p. 4) describes self-regulated learning as a process in which learners "are metacognitively, motivationally, and behaviorally active participants in their own learning process." Hence, self- regulated learning is a complex process which involves numerous dimensions of human information processing (Azevedo, 2008, 2009; Pintrich, 2000; Schraw, 2007; Veenman, van Hout-Wolters, & Afflerbach, 2006; Zimmerman, 2008). Accordingly, in order to solve challenging tasks in problem situations, learners not only have to perform cognitive activities, e.g., activating existing knowledge structures or organizing new information (Seel, Ifenthaler, & Pirnay-Dummer, 2009), they also have to set specific goals, plan their activities, monitor their performance during the problem-solving process, and evaluate the efficiency of their actions (Wirth & Leutner, 2008).

Moreover, the facilitation of self-regulated learning is a balancing act between necessary external support and desired internal regulation (Koedinger & Aleven, 2007; Simons, 1992). From an instructional point of view, there are two vital ways to externally support self-regulated learning within problem- solving processes. Direct external support, in terms of direct instruction, aims at facilitating explicit problem- solving strategies and skills as well as their application and transfer to different domains. Hence, direct instruction could include detailed scaffolds (step-by-step instruction) on how to solve a specific phenomenon in question (Collins, Brown, & Newman, 1989). Indirect external support provides learning aids which induce and facilitate already existing problem-solving strategies and skills. Accordingly, if learners already possess comprehensive problem-solving strategies but fail to use this knowledge in a specific situation, it seems reasonable to motivate them to apply their existing strategic knowledge effectively (Lin & Lehmann, 1999). A possible instructional method for indirectly guiding and supporting the regulation of learners' problem-solving processes is prompting (Wirth, 2009). In general, prompts are presented as simple questions (e.g., "What will be your first step when solving the problem?"), incomplete sentences (e.g., "To approach the solution to the problem step by step, I have to ..."), explicit execution instructions (e.g., "First, draw the most important concepts and link them."), or pictures and graphics for a specific learning situation (Bannert, 2009). Accordingly, well-designed and embedded prompts direct learners to perform a specific desired activity which is contextualized within a particular problem-solving situation (see Davis, 2003; Davis & Linn, 2000; Lin & Lehmann, 1999). According to Davis (2003), prompts can be categorized into generic and directed prompts. While the generic prompt only asks learners to stop and reflect about their current problem- solving activities, the directed prompt also provides them with an expert model of reflective thinking in the problem-solving process.

From a methodological point of view, we argue that it is essential to identify economic, fast, reliable, and valid techniques to assess and analyze these complex problem-solving processes. Especially within experimental setting where huge sets of data need to be processed, standard methodologies (e.g., paper and pencil tests) may have disadvantages with regard to analysis economy. Therefore, we developed an automated assessment and analysis technology, HIMATT (Highly Integrated Model Assessment Technology and Tools; Pirnay-Dummer, Ifenthaler, & Spector, 2010), which combines qualitative and quantitative research methods and provides bridges between them.

In our current research we are investigating effective instructional interventions for self-regulated learning within problem-solving processes (e. …

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