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Encountering Complementary Routes

Another pleasant excursion that I had when delving into this volume came in the informative section surveying the measurement of strategies and strategic processing. It was not just the richness of the individual contributions that I found appealing, but the alternative and complementary pathways the authors laid out for chronicling and evaluating students’ strategic journeys. I have long been frustrated by the limited avenues available for measuring strategies and strategic processing (Alexander, 2018b; Alexander et al., 1998; Alexander, Grossnickle Peterson, Dumas, & Hattan, 2018). However, while the contributing authors in the section did not present me with any wholly new paths for uncovering what remains largely in the minds of individuals or groups, they did expand and extend those paths. Consequently, I was afforded fresh vistas onto the nature and effects of strategic processing. For example, it was delightful to read an entire chapter devoted to person-centered analyses (Fryer & Shum, this volume), accompanied with an up-to-date examination of variable-centered analytic approaches (Freed, Greene, & Plumley, this volume).

The Freed et al. exploration of variable-centered analyses offered a nice synopsis of statistical procedures useful in strategy research; from correlational analyses and structural equation modeling to case studies and mixed methods designs. I certainly concur with these authors that variable-centered approaches hold an important position within the field of strategy research—and will continue to do so well into the future. Further, the number of techniques that can be utilized in person-centered analysis are far fewer in number than exists for variable-centered analyses. Yet, these alternative approaches allow researchers to examine the complex and often intricate interplay between learner characteristics and strategic performance for a given problem within a specific context (Fryer & Shum, this volume). In effect, person-centered approaches provide insights into what, strategically, is working for whom and under what conditions.

However, whether the approach that researchers take in strategy research is variable-or person-centered, the fact remains that the outcomes are only as good as the data analyzed. There is both good news and bad news on this front for strategy researchers. The good news is that new and improved tools for unearthing markers of strategic processing and for making sense of the resulting data have made an appearance since the 1970s. The new tools include more portable and sophisticated eye-tracking devices, and advancements in neuroimaging techniques (e.g., fMRI, functional near-infrared spectroscopy) and biophysiological monitoring (e.g., skin galvanic or electrodermal responses). The proliferation of digital devices also permits researchers to record relevant information (e.g., time stamps, navigation paths) as students engage in academic tasks (Braten, Magliano, & Salmeron, this volume; Cho, Woodward, & Afflerbach, this volume; List, this volume).

Contributors to this volume expand on these new and improved tools and what they can reveal about strategies and strategic processing. For example, Catrysse, Gij-bels, and Donche (this volume) illustrate how eye tracking and fMRI data can offer invaluable clues as to the level of students’ strategic engagement. As Catrysse et al. rightly acknowledge, there are still challenges in reaching conclusions from such data sources, including the degree of inferencing and interpretation involved. There is also the concern for ecological validity, since these data are gathered under conditions far different from what students typically experience. Also, Taboada Barber, Cartwright, and Klauda (this volume) detail how data on executive function derived from neuroimaging techniques can contribute to a richer understanding of what is occurring in the minds of students confronting cognitive or linguistical challenges in the classroom, and the concomitant motivational, emotional, and social issues that co-exist. What this chapter reinforced for me is that strategic processing is not solely a cognitive enterprise, but is intertwined with motivational, emotional, and social factors that must be considered when devising interventions. As with Taboada Barber et al., my colleagues and I have found the literature on executive function invaluable in our investigations of relational reasoning. Relational reasoning is a higher-order executive function that involves the extraction of meaningful patterns from seemingly unrelated information through the perception of similarities and dissimilarities (Alexander, 2017; Alexander, Jablansky, Singer, & Dumas, 2016).

Despite the progress in measurement tools and data-analytic procedures (Freed et al., this volume; Fryer & Shum, this volume), far too many strategy researchers continue to rely on survey and self-report data without corroborating information. The shortcomings of this practice have been discussed at length (Mayer et al., 2007). For one thing, humans are not the most reliable information source when it comes to their internal operations and the conditions that may have prompted those actions (Alexander, 2013). Interestingly, Vermunt (this volume) presents a more positive, contrasting view of survey and self-report data. Beginning in the 1970s and running to the present day, he frames his discussion in a historical context, describing several generations of survey and retrospective self-report instruments. Whether I accept this more optimistic view of survey and self-report data, especially in the absence of any direct measures, I found several aspects of Vermunt’s discussion intriguing.

For one, the concept of learning styles, which was a focus of the early generations of survey instruments, was explicated. Specifically, learning styles, which are now referred to as approaches to learning, are conceived as learners’ disposition to adopt a learning or studying routine regardless of the specific context or task demands (Schmeck, 1983). From my perspective, and that of other contributors to this volume (Afflerbach et al„ this volume), this conception has more in common with the definition of skills than strategies; more habituated than intentional and more rigid than flexible. That being said, Vermunt offers three rationales for the continued use of surveys and retrospective self-reports. First, the decades of research using these measures has led to a rich literature on college students’ learning and study practices. Second, these tools have served as a catalyst for students’ reflections on their actions when studying. Third, rather than serving as a self-evaluation tool for students, Vermunt considered the later generations of these survey and self-report measures to be viable for assessing the instructional environment.

Finally, in their chapter, Cho, Woodward, and Afflerbach (this volume) delve into another form of self-reporting, verbal protocols, but they do so through what they classify as a qualitative lens. Consistent with Vermunt’s rationale, these authors see merits to employing verbal protocol analyses as a mechanism for probing the thinking and reasoning of students engaged in online reading tasks. I found other aspects of this chapter thought provoking. For one, I was struck by the authors’ claim that qualitative research is primarily inductive and informed by the data, “rather than deductive or beholden to theory.” This claim was puzzling to me because much of the chapter established how the authors’ analysis was, in fact, driven by theories of epistemic beliefs, text comprehension, argument, and more.

Perhaps Cho et al.’s choice of word, beholden, was intended to signal a strict top-down process that allowed for no variability or flexibility based on trends emerging from the data, task, or situation. As a counterargument, I would contend that the distinction between inductive and deductive in strategy research that the authors pose represents a false dichotomy. The complexity of the phenomena being explored almost inevitably forces researchers to move rhythmically between induction and deduction. Otherwise, studies of strategies and strategic processing would either be atheoretical and, thus, uninterpretable, or led wholly by the data, in which case, there would be no sense of what might be relevant or whether inferences seemed reasonable or realistic.

Braten et al. (this volume) also explore verbal protocols in their chapter on concurrent and task-specific self-reports. Addressing the concern that thinking aloud while engaged in a cognitive task alters normal strategic processing by directing students to share what otherwise would be tacit, habituated actions, these authors describe alternative approaches to gathering verbal protocol data. In addition, they discuss the coding of these verbal protocols and consider what steps are required to ensure the validity of those data. One recommendation they offer is to look for correspondence between the strategies identified from the verbal protocol data and what would be expected based on individual differences data. Similarly, there should be a reasonable relation between what individuals verbalize about their processing and the quality of their performance. In effect, more knowledgeable or more competent learners should be more likely to describe deeper-processing and regulatory strategies than those for whom the task at hand is unfamiliar and cognitive demanding. Likewise, the students who verbalize more instances of deeper, regulatory processing should tend to have higher outcomes than those whose strategic processing is limited and surface-level. Another approach to validation could involve corroborating what students report with some objective markers such as logfiles, eye tracking patterns, or neuro-imaging data.

Collectively, what these chapters on methodology revealed is that there are multiple paths that can be traversed in the study of strategies and strategic processing and that researchers should be able to follow one or more of these paths in pursuit of their goals. What I also came to realize is that these paths may diverge as certain junctures in the journey, but they are also apt to cross or even overlap at other times. The bigger question that lingers for me is whether these complementary routes reach similar points in the end. My guess is that they will ultimately afford different vistas onto the strategy landscape, but the topography will be recognizable, nonetheless.

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