A Learning Theory You Can’t Afford Not to Know: Self-Regulated Learning (Part 2)

Pintrich’s Model of Self-Regulated Learning

Unlike Zimmerman’s model, Pintrich’s (1999, 2004) model examines self-regulatory strategies using a well-known questionnaire (i.e., Motivated Strategies for Learning Questionnaire, MSLQ) that was developed by Pintrich and his colleagues (Pintrich, Smith, Garcia, & Mckeachie, 1993). MSLQ is very well received by the scholars in the field of self-regulation, and it has also been one of the most widely used measures of self-regulated learning in technologically enhanced environments. Pintrich’s model was designed to examine self-regulated learning using four phases, namely the forethought phase, monitoring phase, control phase, and reflection phase. As illustrated in the Table, each of these phases are placed under four domains of self-regulation: cognition, motivation/affect, behavior, and context.

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The components of Pintrich’s model of self-regulation in phase one include goal setting,activation of prior content and metacognitive knowledge (cognitive domain), adaptation of goal orientation and efficacy judgments (motivation/affect domain), effort planning (behavioral domain), and perception of task and context (context domain). Phase two (monitoring) refers to student’s ability to make adaptive changes (when needed) while progressing towards a particular goal. As seen in phase one, phase two also includes metacognitive awareness and monitoring of cognition, affect, motivation, effort, time use, and context conditions. Phase three (control) refers to selection and adaptation of cognitive strategies for learning, thinking, managing, motivation, and affect. Similarly phase four (reflection) includes cognitive judgments, affective reaction, choice behavior, and task evaluation. As access to online education has increased, researchers have moved quickly to identify the underlying factors that may influence one’s performance in technologically enhanced settings. In my next post, I will discuss the important role of self-regulation in technologically enhanced learning environments.

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