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Section I: Definitions, forms, and levels of strategies

Strategic processing within and across domains of learning

Introduction

Educational psychologists observe various aspects of learning and education—whether it be large-scale educational data collected across many schools (e.g., Cameron, Grimm, Steele, Castro-Schilo, & Grissmer, 2015), or more finely grained data collected in a laboratory setting (e.g., Xie, Mayer, Wang, & Zhou, 2019)—and pose a fundamental question: why do students differ so substantially in their academic outcomes? (Alexander, 2018). Since the 1890s (James, 1890; Mayer, 2018), educational psychologists have identified and investigated many explanatory factors for the observed student variance in learning outcomes, including but not limited to: intelligence and other cognitive functions (Canivez, Watkins, Marley, Good, & James, 2017), motivation and goals (Linnenbrink-Garcia et al., 2018), self-regulatory abilities (Winne, 2018), and socio-emotional support and development (Wentzel, Muenks, McNeish, & Russell, 2018).

This body of educationally relevant psychological constructs can generally account for hundreds of published educational psychology research studies, but, beginning in the latter part of the 1980s (Alexander & Judy, 1988; Pressley, 1986), educational psychologists began to understand that none of these constructs is the most proximal influence on student performance in school. Instead, the actual procedures that students enact while learning—the specific cognitive actions that students engage in during the learning process—are a much more readily useful predictor of student learning outcomes than are students pre-existing individual differences or abilities (Alexander, Graham, & Harris, 1998; Dinsmore, 2017). Here, these cognitive procedures are referred to as the strategies or skills that students employ in order to solve a problem, independently study from text, or regulate their academic activities.

After the identification of strategic or skillful processing as the most proximal influence on student achievement in schools, a number of further patterns emerged in educational psychology data that have complicated this picture. For instance, it had long been understood (e.g., Thorndike, 1913) that student variance existed not only inter-individually in educational outcomes but also intra-individually, meaning that an individual student may be more or less effective at problem solving, studying, or learning in a particular domain of knowledge (e.g., mathematics) than they are in another domain (e.g., reading). But, explaining these intra-individual differences in terms of procedural strategy differences within a student offered some conundrums. For example, some strategic processes used for learning (e.g., self-questioning; King, 1989) appeared to be effective at supporting educational outcomes across a variety of domains, while others were more specific to a single domain (e.g., counting-all in early mathematics; Baroody, 1987). As such, students who more readily use domain-general strategies, or cognitive procedures that are useful across a variety of domains of learning, may have stronger outcomes across a range of academic domains, while those who struggle to use domain-general strategies may have more pronounced intra-individual differences in their learning outcomes across domains because they rely more on strategic processes that are domain-specific, or are only useful in one particular domain of learning.

However, even for those strategies that have been identified as domain-general, some students are more capable of flexibly utilizing these general procedures across different learning contexts than are other students (Campione & Brown, 1984; Cushen & Wiley, 2018), limiting the degree to which domain-general strategic processes are actually transferred across domains of learning in real-world educational settings. For this reason, being capable of utilizing a strategic process that is theoretically domain-general (e.g., outlining) within one particular domain (e.g., history) does not necessarily mean that a student will be effective at using the exact same strategy within another domain (e.g., biology). This highly limited degree of strategy transfer across domains of learning has complicated the degree to which the true domain-generality or domain-specificity of any given cognitive procedure can be identified by researchers. The observed uncommonness of strategic transfer also creates instructional difficulties in that, in some cases, it remains unclear whether the teaching of strategies specific to a given domain or more general strategic procedures is a more effective instructional choice. This is because domain-general strategies may appear to be more widely effective for students to learn, but without the capability of identifying wider learning contexts in which that strategy is useful, students may never actually transfer the strategy across domains. If this occurs more often than not, it may be more prudent for educators to focus on domain-specific strategies with the pre-supposition that strategy transfer will not occur anyway. In this chapter, issues such as this, that center on the degree to which cognitive procedures used for learning and problem solving can be considered transferable across domains of learning (i.e., domain-general), are reviewed and discussed.

 
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