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The Need to Define Strategic Processing

The previous section established why key terms in our field need to be defined. In short, terms serve as an epistemological shorthand (Alexander et al., 1991) that undergirds communication across a scholarly community. When these definitions are unclear and evolving over time, the potential for miscommunication is great and can undermine scientific progress. The previous section also established that the potential for miscommunication is present for the terms strategy and strategic processing because their definitions have been both unclear and evolving over time. These points alone, however, are not sufficient to answer the question, “Why are strategies and strategic processing particularly important to define?” Of course, one obvious answer is to point out that strategic processing is consistently tied to learning outcomes, e.g., students’ self-reported strategy use predicts learning outcomes (Braten & Stromso, 2011; Cantrell, Almasi, Carter, Rintamaa, & Madden, 2010; Crede & Phillips, 2011). These relationships are not sufficient to justify special attention to strategic processing, however, because there are many other variables that show similar, predictive relationships to academic performance (e.g., motivation, Pintrich & Schunk, 2002; spatial ability, Carter, Larussa, & Bodner, 1987; intellectual ability, Sternberg & Kaufman, 1998). Given that other factors are relevant to learning, what is it about strategic processing that warrants special attention? To answer this question, we turn to two characteristics of strategic processing, namely the proximity to learning outcomes and the responsiveness to instruction.

First, with respect to proximity, we agree with Dumas’ (this volume) argument that strategic processing is centrally important to the study of learning because how a student processes some learning materials, strategically or otherwise, is immediately and directly tied to what is learned. This has been demonstrated many times in the research literature, but we will share just two examples from our own work. In a study by Firetto and Van Meter (2018), college biology students read to learn about two different physiological systems and the goal of the study was to test instructional conditions that would promote students’ integration across the two systems. In the integration instruction condition, students were prompted to directly compare the two systems while the comprehension instruction condition prompted comprehension of each system. These two experimental conditions were compared to a control condition and all participants completed a self-report measure of strategy use and an essay posttest that was scored for both accuracy and cross-system integration. Participants in the integration condition did achieve higher post-test scores, which demonstrates that the instructional intervention was effective. Responses to the strategy measure, however, revealed that these intervention effects were mediated by participants’ strategic processing. In a second study, Van Meter et al. (2016) had college engineering students complete an intervention exercise designed to support understanding the First Law of Thermodynamics. An experimental test showed that intervention condition participants had higher conceptual reasoning scores than did control condition participants.

Most relevant to the current point are the findings obtained from a small group of students who thought aloud while completing the intervention exercises. Analysis of these protocols revealed significant relationships between conceptual reasoning scores at post-test and the frequency of strategic processes (e.g., elaboration) while completing the exercise.

A conclusion that can be drawn across these two studies is that, although instructional interventions can and do improve learning, these improvements are tied to the influence of the intervention on students’ strategic processing. In both studies, despite the benefit of the intervention overall, participants in experimental conditions who were less strategically engaged in the task benefitted less from the intervention than their more strategic peers. These findings are consistent with other research demonstrating that strategic processing has a direct influence on performance across diverse tasks such as learning from multiple documents (e.g., Braten & Stromso, 2011), worked examples (e.g., Chi, Bassok, Lewis, Reimann, & Glaser, 1989), and multimedia (e.g., Cromley, Snyder-Hogan, & Luciw-Dubas, 2010). In sum, students’ strategic processing is a proximal cause of learning outcomes.

A second reason that strategies and strategic processing warrant attention is because they are amenable to instruction. While studies of students’ independent, naturally occurring use of strategies has shown significant relationships between strategy use and learning (e.g., Chi et al., 1989; Cromley et al., 2010), the evidence also shows that students can be taught to use strategies effectively. One example is McNamara and colleagues’ research on training students to use self-explanation. In this training, students learn to generate explanations through the use of five strategies (e.g., bridging, paraphrasing) and practice applying these strategies to expository text. Whether learning through face-to-face tutoring (i.e., SERT; McNamara, 2004, 2017) or via an online strategy trainer (i.e., iSTART; McNamara, Levinstein, & Boonthum, 2004; McNamara, O’Reilly, Best, & Ozuru, 2006), comparisons between trained and untrained students reveals a benefit for self-explanation instruction. In the context of multimedia learning, Mason and colleagues (Mason, Pluchino, & Tornatora, 2015; Mason, Scheffer, & Tornatora, 2017) have trained students to process text and diagrams by having them watch a video replay of a successful student’s eye movements. This eye movement modeling example (EMME) shows the model using effective strategic processing such as attending to the diagram and transitioning between corresponding parts of the text and diagram. These EMME studies show that students who were exposed to the model not only score higher on learning outcome measures but also demonstrate more effective multimedia learning patterns in their own eye movements.

Altogether then, there is ample evidence that strategic processing is both a proximal cause of individual variations in learning and addressable through instruction. Moreover, the causal relations between strategies and learning outcomes is robust. This robustness is evidenced, on the one hand, by the range of domains, tasks, and learners that are discussed just within the four chapters of this Handbook section. Dumas, for example, draws attention to the role of strategic processing across domains while Rogier et al. point out that strategy use influences learning and performance across all developmental levels. The robustness of the causal relations is also evidenced by a number of empirical demonstrations that there is a direct andsignificant path between the application of strategic processing to some material and what is learned from that material (e.g. Berthold, Nuckles, & Renkl, 2007; Braten, Anmarkrud, Brandmo, & Stromso, 2014; Firetto & Van Meter, 2018; Murphy & Alexander, 2002). Furthermore, although variations in methodologies used makes it difficult to quantify these effects across studies, meta-analytic reviews have concluded that strategy training programs have a positive effect on students’ learning (de Boer, Donker, Kostons, & van der Werf, 2018; Dignath & Biittner, 2008; Donker, De Boer, Kostons, Van Ewijk, & van der Werf, 2014).

On these grounds, we argue that the efforts to define strategies and strategic processing are not only justified, they are necessary. Although the chapters in this section advance our understanding of these important learning processes, there are differences in how each conceptualizes strategies and strategic processing. Consequently, these chapters do not present a single agreed upon definition, but rather a call to consider a broad range of related issues. These differences present an opportunity to synthesize across perspectives to generate definitions of strategies and strategic processing that capture not only the essence of this Handbook section but also the direction of this field of study as a whole.

 
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