Why Prompting Metacognition in Computer-Based Learning Environments

ABSTRACTSelf-regulated learning (SRL) is a central construct in education, especially in the context of the widespread use of instructional technologies. According to metacognition models (e.g., Nelson & Narens, 1994), the accuracy of monitoring plays a crucial role for effective regulation of one's cognition, behavior, and motivation as s/he strives to achieve academic performance. In other words, being able to make accurate metacognitive judgments during learning (e.g., judge if the information was sufficiently learned) is assumed to positively affect subsequent effort and strategic behaviors (Hadwin & Webster, 2013). From this perspective, calibration between students' judgments and their actual performance represents a metacognitive indicator for the need to regulate and adapt studying behavior (e.g., allocation of studying time; Metcalfe, 2009). Given the empirical evidence that many students have poor calibration skills (Graesser & McNamara, 2010), there is a need to prompt them to accurately monitor their metacognitive processes, which is expected to foster SRL and performance. Therefore, the purpose of this paper is to provide an overview of research on metacognitive judgments accuracy and, in particular, on how this accuracy impacts students' self-regulation as they learn using CBLEs.KEYWORDS: self-regulated learning, metacognitive judgments, academic performanceSelf-regulated learning (SRL) is a central construct in education, especially in the context of the widespread use of learning technologies (Bannert & Reimann, 2012; Winters, Greene, & Costich, 2008). SRL is defined as an active process in which students plan, monitor, and control their cognitive, metacognitive, and motivational processes as they pursue their own learning goals (Winne & Hadwin, 1998; Zimmerman, 1990). For SRL to be effective, students need to make accurate judgments about whether they understand what they are learning (i.e., to accurately monitor their understanding or knowledge), and whether they need to change their plans, goals or strategies (Azevedo, 2008; Winne & Jamieson-Noels, 2002). Research has shown that these SRL processes are especially important in computerbased learning environments (CBLEs), because they present challenges that can hinder learning, even for the best students, such as the need to decide on their own whether, when, and how to use the multiple information resources (e.g., texts, graphics) provided by CBLEs. Students cannot use effectively the resources provided by CBLEs if they are not able to accurately monitor and evaluate their own performance, as well as regulate their learning processes in order to reach the desired goals (Azevedo & Witherspoon, 2009). Within this context, understanding how students use SRL processes in CBLEs and which of these regulatory processes are the most important for improving learning may provide a better perspective on how to support students' self-regulation (Vrugt & Oort, 2008). Therefore, the goal of this paper is to provide a short overview of research on metacognitive processes, detailing the role of monitoring accuracy in SRL. A complete review of research on metacognition is beyond the goal of this paper. Rather than doing this, we will provide some insight that have originated from research in metacognition and are particularly relevant for SRL while using CBLEs. More specifically, we will focus on two questions that can arise regarding self-regulation in CBLEs: (i) what are the problems associated with metacognitive judgments during SRL; (it) why (and how) prompting metacognitive judgments of students while using CBLEs?1. SRL and metacognitionAlthough a number of SRL models have been proposed (e.g., Boekaerts, 1997; Pintrich, 2000; Winne & Perry, 2000; Zimmerman, 2000) employing different perspectives on self-regulation, all of them agree that SRL involves three main processes: goal setting or planning, monitoring and the use of meta(cognitive) strategies. …