Metamotivational Monitoring in the Context of Self-Regulated Learning

• In Event: 25.021 - Advances in Self-Regulated Learning: Considering Personal Epistemology, Metamotivational Monitoring, Intentional Conceptual Change, and Time Management

Abstract

According to Pintrich (2004), students regulate at least four different aspects of their learning: cognition, motivation/affect, behavior, and context. Regulation of motivation, like the regulation of cognition, behavior, and context, involves two reciprocal processes: monitoring and control. In the context of motivation, we refer to these processes as “metamotivational” because (like metacognitive processes) they are introspective in nature. Metamotivational monitoring involves assessing both the quantity and quality (e.g., autonomous vs. controlled) of one’s motivation to pursue a task goal, whereas metamotivational control involves using the output of one’s monitoring in order to select and implement strategies aimed at bolstering a particular motivational state (Miele & Scholer, 2018; Scholer & Miele, 2016). Although researchers have long acknowledged the importance of metamotivational monitoring for successful regulation (e.g., Sansone & Thoman, 2005; Wolters, 2003, 2011), most of the work in this area has focused on the strategies students use to increase or maintain their task motivation (i.e., on their metamotivational control).

To address this gap in the literature, we developed a model of metamotivational monitoring that attempts to explain how students become aware of the need to implement particular motivation regulation strategies (Miele & Scholer, 2018). The model distinguishes between students’ monitoring of motivation quantity (i.e., “Am I motivated enough?”) and motivation quality (i.e., “Am I motivated in the right way?”). In explaining how students’ monitor the quality of their motivational states, we draw on several prominent theories of motivation that distinguish between different types of motivation, such as regulatory focus theory (Higgins, 1997), self-determination theory (Deci & Ryan, 2000), and construal level theory (Trope & Liberman, 2010). Because specific types of motivation (e.g., promotion vs. prevention) are thought to be associated with particular modes of information processing (e.g., divergent vs. convergent), we propose that metamotivational monitoring involves assessing the fit between the processing demands of a given task and one’s current motivational state (referred to as task-motivation fit). If a mismatch is detected, then one must identify strategies that can be used to shift oneself into a more appropriate motivational state (see also Scholer, Miele, Murayama, & Fujita, in press).

In this presentation, we will outline what we believe to be the key monitoring processes involved in the creation and maintenance of task-motivation fit, with a focus on the different types of metamotivational knowledge on which these processes rely. Specifically, we will distinguish between (a) students’ understanding of how particular types of motivation affect performance on different kinds of task (task knowledge), (b) their understanding of what it is like to experience these different types of motivation (self knowledge), and (c) their understanding of the strategies they can use to induce these motivations in themselves (strategy knowledge). We will then present evidence from several different studies suggesting that college students possess the kinds of task and strategy knowledge that may be necessary for regulating the quality of their motivation in different performance contexts (Edwards, Scholer, & Miele, in preparation; Scholer & Miele, 2016).
 

Authors

• David B. Miele, Boston College

• Abigail A. Scholer, University of Waterloo

• Jessica Edwards