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2008A15Ewing

Cognitive Science and Scientific Research for Composition Studies
Reviewed by Patrick M. Ewing
pewing@education.ucsb.edu

Chaired by Scott Gage of Florida State University, “Cognitive Science and Scientific Research for Composition Studies”—one of the few sessions with any kind of cognition-and-research emphasis—was held in a room with few open seats. Moreover, given that signage in the hallways of the Hilton was lacking early that first morning, and given that many could not find the room’s delegated entrance (myself one of those, initially), this session was, despite its being of a rare kind, attractive to many. This session, with its focus on cognition and research, certainly calls for more of its fashion in the future.

The session began with a clear presentation by Olivia Walling from UC Santa Barbara on the need for scientific research in writing studies. Walling, presenting from her conference paper, “Writing in a Technological System,” began by addressing a decline in quantitative writing research methods starting with the slowing of cognitivist studies in the 1980s, resulting in a manifest dominance of qualitative and ethnographic methods in writing research today. Citing authors like Charney and Haswell on the one side, and Blyler, Dombrowski, and Flynn on the other, Walling engaged a brief literature review to outline the methodological camps. The first camp are those who favor data-driven, replicable and aggregable studies, and those in the other camp who, amidst claims of disempowerment and positivism (the latter of which, according to Walling, is misunderstood and unfairly burdened with a connotation of condemnation), call for ethnographic studies of writing. In her presentation, Walling sought to bridge the impasse between these two camps.

Citing authors like Ong, Goody, and Bazerman, Walling began by looking at writing as a historically developed technology. She did so to point out false assumptions held by many involved with the teaching of writing: 1) we have a naïve view of technology in writing, and 2) “we assume that knowledge is created and exists outside of texts and that texts express or represent knowledge” (Walling, 2008, para. 5). The research report, for Walling, is technology itself: “If text is a technology, then it shares qualities with underground storage tanks, microscopes, accelerators, and more” (Walling, 2008, para. 7). Without reducing writing to an ephemeral, romantic vision of muse and inspiration, writing for Walling, as a technology, is viewed in context as a tool to accomplish specific goals. Written research reports create knowledge for specific purposes. The activity or genre system in which these texts operate includes “peer review, publications, university personnel committees” and other dynamic relations (Walling, 2008). Walling’s ultimate claim is that research reports do not uncover knowledge found through the methods; rather, that report is knowledge itself (para. 12), and we use it for our own aims, to help people with predictions and interventions.

Walling, in defending scientific research methods for writing, explained, “those opposed to the use of quantitative methods suggest that the written product of qualitative research provides us with a more ‘realistic’ view of the research subject. However, this view fails to recognize how research products function” (para. 13). This is so because we need to construct, for Walling, cause-and-effect views of human behavior so as to make predictions and interventions possible. Therefore, those who claim that qualitative work helps disenfranchised groups whereas quantitative work could not, are actually counter-productive if they do not see the value of scientific research.

Walling continued to outline problems with privileging culture in ethnographic educational research, saying “there is no logical relationship between the means by which an activity comes into being and the appropriate tools for examining it” (para. 18). She also argued that mentioning writing as a “social construction” is not necessary—as all technological constructions are social. Walling also claims that using this tenet to form various assumptions or premises is faulty. She makes this point to say that ethnographic accounts are not “closer to reality” than scientific research reports, and, again, she made the case that by not quantifying certain data we fail to help those we intend to (Walling, 2008).

Interestingly, Walling’s cogent presentation lauding empirical research for writing studies and education coalesced nicely with the next presenter’s interest in cognition and emotion. The presenter, Liberty Kohn, cited, among others, David Miall (2006). Miall, while working in a humanities environment, uses empirical methods to study literary reading. Kohn’s presentation, “Beyond Reason: How Students Use Emotion and Narrative Problem-Solving for Context and Reading Strategy in Non-narrative Texts”, positioned students as novice readers whose emotions may explain misreadings, whose rhetorical reading strategies may be thrown off by “literary-esque” language (testimonies, narratives, passages of purple prose, et al.), and these jarring misreadings are, according to Kohn, due to emotional activation.

Kohn, of University of Louisiana, Lafayette, began by citing Damasio and ‘the loss of duality’ resultant from his research and writings—the theoretical blending of emotion on the one hand and reason on the other as posited in Descartes’ Error: Emotion, Reason, and the Human Brain (1994). Emotion is a “heuristic” and a “frame” for Kohn that prompts and informs reason. Emotion can ultimately trump logic, and that is anticipatory, yet at the same time emotion can be unpredictable.

In his section on cognitive models, Kohn cited Hayes (1996, p.4) and his updated model which includes a box titled “Motivation/Affect” inclusive of goals, predispositions, beliefs and attitudes, and cost/benefit estimates. Kohn, however, suggested that “a box” not be added to the model as “emotion is complicit in many, if not all, of the architectures.” Kohn said that affect is “global” for Hayes; that it has “no bearing on text-based decisions.” In regards to the latter, Hayes’ 1996 work does link the “motivation/affect” box with the “cognitive processes” box that contains actions like text interpretation and production—but Kohn called for further exploration of these connections. He may also be suggesting a soft spot in the model as “motivation/affect” has no direct arrow linking it to “the physical environment” (p.4) (i.e., the text produced so far)—but this is my speculation.

Kohn finished by reinforcing the idea that emotion needs to be discussed as part of the reasoning process on the part of the individual. Even while social conventions also regulate affect, those like semantics and diction as well as genre conventions also inflame certain emotions; personal memory (i.e., episodic memory) “stokes emotion” (Kohn). Reading is, therefore, highly personal. He also suggested that teachers can benefit by recognizing the source or “frame” of misreading in novice students—and that recognition of these potential “unwanted propositions” that cloud a “reasoned reading” will allow teachers to respond more efficaciously.

Kohn’s work sought to revitalize cognitive studies in writing research and theory. While citing empirical researchers (Miall) and neuroscientists (Damasio) that use an array of quantitative methods to study the brain and its function, Kohn’s presentation, like that of Walling’s, was very forward-looking, and his calls for attention to be paid to emotion in the reasoning process are an attempt to help students be understood in class settings.

Stephen Adkison of Idaho State University, like Kohn, used studies from cognitive science and neuroscience in his presentation to address cognition and writing. Adkison glossed the work of Paul Grobstein, a neurobiologist, in his presentation title, “Why our Brains Need to Be ‘Wide as the Sky’,” the latter being a reference to Emily Dickenson’s “The Brain is Wider than the Sky” which is a poem Grobstein uses in his own work. Grobstein posited that the brain is an explorer (Grobstein), that learning is a search for meaning, and—this is key to Adkison’s thesis—that brain studies (studying learning as a brain function) can compliment our developed shared ideas about best teaching practices and learning in the classroom.

In regards to this metaphor of brain as explorer, the process of learning is active, not receptive. Adkison cited child psychologist Margaret Donaldson, renowned psychologist Jerome Bruner, and James Britton to suggest that story-telling is intentional process of “filling in gaps” (Adkison) in various patterns (genre variations). Adkison explained that all inputs into the neural circuitry are ambiguous (they are symbols), and he suggested our consciousness, our production of knowledge, is a continuous loop, a “reafferent loop” (Adkison) which aims at filling in gaps and getting it less wrong.

Adkison went on to talk about Vygotsky’s ZPD and the importance of a rich social environment of language-based social interactions for child development. More inputs and stories, according to Adkison, help a child “organize and represent” (Britton) the world. Thus, the potential development zone is a range of trajectory-probability; making stories with other kids and getting it “less wrong” in richer social interactions will increase trajectory potential. In other words, we make knowledge with others; we don’t receive it. As Adkison put it, “learning is not something we do; it is who we are.”

This idea of a ‘loop’—interestingly—was also especially important for understanding the last speaker’s presentation, Brian J. McNely’s “Theorizing Recursion: A Multidisciplinary Approach.” McNely, of the University of Texas at El Paso, started by citing a resurgence in revision research by the Europeans (cf. van Waes & Leijten, Mark Torrance, David Galbraith, Åsa Wengelin, Eva Lindgren, and others). He also discussed recursion as a theoretical term with a narrow definition; for McNely, there is something about the recursive loop that is uniquely human, of ultimate importance and worth further research.

McNely created a foundation for his talk by citing Faigley’s (1986) assertion that Emig’s (1971) appropriation of the term recursion from mathematics for writing is a misapplication. But, he asks, if it is a misapplication, why do we still use it? McNely called for a deeper appreciation of the term and concept, suggesting that recursion is “the fuel of rhetorical invention” and “perhaps the central component of writing research, a concept integral to all thinking, writing, and doing…” (McNely).

McNely, to this end, called for a multi-disciplinary understanding of the concept. In a short lit review, he cited rhetoric/composition theorists (Bazerman and Russell 2003, Emig 1971, et al.), physics and applied math scholars (Kyburz 2004, Gleick 1988, et al.), and cognitive scientists (focusing on Hofstadter and Hawkins). From these sources, McNely pulled key concepts and definitions: recursion is a way by which “things are repeated in a self-similar way” (McNely); humans think recursively, using “complex patterns of previous thought to produce new thought” (McNely); and humans think in a “strange” (Hofstadter) dialectic loop, phenomenologically, between self and other. The strangeness, for Adkison and Grobstein as well as McNely, comes from raw stimuli as input: “In any strange loop that gives rise to human [subjectivity]…the level-shifting acts of perception, abstraction, and categorization are central, indispensable elements. It is the upward leap from raw stimuli to symbols that imbues a loop with ‘strangeness’” (McNealy citing Hofstadter). The symbolic and referential loop of language makes for a continual testing of ideas, building thoughts upon thoughts, recursively.

McNely concluded that recursive hermeneutics is a single, key step to formation of new knowledge. He cited Jeff Hawkins (2004) to discuss how ‘prediction’ is a key component of this looping process: “prediction is not just one of the things your brain does. It is the primary function of the neocortex, and the foundation of intelligence” (McNely). Read another way, as McGaugh (2003) would say for dreams and memories, these predictions are used to practice potential situations, to produce schemas that can be used later (to create genres or actions) for particular purposes. Our cycle of prediction and testing is, for McNely, a key aspect of our consciousness, and it is recursive.

McNely finished suggesting that by re-contextualizing recursion in light of this multidisciplinary approach as part of rhetorical invention, we can start to theorize recursivity as robustly as we ought to. He also discussed benefits for students, and he cited Miles et al. (2008) to do so: “In the best sense of recursion, students revisit and re-see what they have previously learned. In a vertical curriculum, such moments of recursion should be intentionally designed to foster students’ growing complexity with each learning outcome” (Miles et al.). By understanding how students think, according to McNely, we can adjust our curricula to fit this fresh understanding.

And fresh understanding is exactly what this panel called for. Whether challenging notions about writing and research itself or by energizing writing studies with the fruits of cognitive labors in psychology, cognitive science, neuroscience, and other related fields, the panel presentations were inspiring and rejuvenating. Should my optimism prove true, the popularity of this session might represent an American resurgence, albeit a slow and small one, in cognitive approaches to writing. My hope is that this may become manifest in the future by more like sessions like this one; that the 4Cs might see more replicable, aggregable, data-driven research on cognition and writing being presented.

References