| The emphasis on metacognition exists in several corners of education research. In collaborative learning research, it constitutes a component of collective learning of content (Khosa and Volet 2014; Vauras et al. 2003). In motivation research, it constitutes a component of successful learning strategies (e.g., Duncan and McKeachie 2005). In the critical thinking literature, it is often considered a foundation to critical thinking (Halpern 1998; Ku and Ho 2010; Kuhn and Dean 2004; Magno 2010; Schön 1983). Though an agreed-upon definition of metacognition has been elusive (Dinsmore et al. 2008), a longstanding view is that it comprises two components: knowledge of cognition and regulation of cognition (Brown 1987), where the former involves our awareness of our thought processes, particularly our declarative knowledge about our memory (Flavell 1979), and the latter involves our planning and control of these processes (Brown 1987; Jacobs and Paris 1987). Being able to control our cognition, and therefore apply metacognitive skills, requires knowledge of various strategies and awareness about when to best apply them (Ambrose et al. 2010; Schraw et al. 2006). An individual’s regulation of cognition involves a continuous evaluation of what is known and what still needs to be learned (Brown 1987; Flavell 1976; Jacobs and Paris 1987). Research on metacognition has increased in frequency since the 1970s. Practitioner oriented studies have investigated correlations between metacognitive awareness and achievement (e.g., RincónGallardo 2009; Young and Fry 2008), with some studies presenting evidence or cogent arguments that students who regulate their cognition tend to perform well in problembased learning (Hmelo-Silver 2004; Rozencwajg 2003), expert learning (Bransford et al. 2000; Sternberg 1998), and overall academic achievement (Peverly et al. 2003; Vrugt and Oort 2008; Winston et al. 2010). There have been concerns, however, that these positive correlations between general metacognitive skills and academic achievement have not been as strong as would be expected (Cromley and Azevedo 2006; Jacobse and Harskamp 2012; Schunk 2008; Sperling et al. 2004; Veenman 2011). Part of this weak correlation may be because individuals who report infrequent use of metacognition place at either end of an achievement scale; that is, in addition to lower achievers who infrequently engage in metacognitive thinking, there are higher achievers who have already automatized their metacognitive scripts and therefore report less frequent use (Brown 1987; Veenman et al. 2005). Correlations may also be moderated by unrelated variables such as stereotype threat or test anxiety (Dent and Koenka 2015). Another plausible source of weak correlations may be a lack of quality instruments used to measure metacognition. |