In “How People Learn,” Bransford et al. (1999) provide a compelling overview of the history and recent landmarks in the study of cognition and learning. In particular, the author notes the developments in the understanding of knowledge organization, infant cognition, knowledge transfer, and situated learning. Noting the relevance across multiple fields of social science, the authors commend the contributions from a wide range of disciplines including social psychology, anthropology, and neuroscience. Advanced research methodologies have also greatly impacted cognitive science research, and in terms of scientific credibility, seem a great improvement from the initial introspective self-report labs from which scientific psychological and cognitive inquiry first emerged.
In previous readings about the science of learning, I have often found it to be an area that is difficult to discretely define. Not only does the science of learning extend throughout the course of human lifespan development, but it also aims to describe a personal process in a generalizable manner, to be multidisciplinary, and to be readily applicable. Seemingly inconsistent in its conclusions, with both Behaviorism and schema theory representing viable aspects of learning, the theories of learning area constantly evolving from their mechanistic origins. Today we recognize that the learning of facts and concepts are both of great importance, as the active integration of the former into the later, supports the construction of a foundational knowledge base. Yet, defining the basics of “how” learning occurs in education, it is surprisingly complex.
The current dilemmas in cognitive science research are also in some ways the most intriguing. In particular, the challenge of equitably evaluating learning make it greatly important to define related concepts such as pre-existing knowledge, understanding, comprehension, analysis, and other critical thinking skills.
The first chapter of the book highlights the significance of building a linkage between home and school-based learning environments. Among the principles, the authors recommend creating environments that are learner-centered, knowledge-centered by providing a justification for what, why, and how content is taught, afford opportunities for formative assessments and feedback, and pay appropriate consideration to the context in which learning occurs. The chapter ends with recommendations for constructing effective learning environments.
The second chapter presents the paradigm of the expert-novice. In this chapter, we learn that a unique mental characteristic that separates experts from novices is their ability to meaningfully chunk and organize relevant domain-specific conceptual information. Adaptive experts can also learn to apply original solutions to problems within their domain of expertise, while novices may require more direct support and lengthier time to produce solutions to problems. The authors suggest that to make this transition from novice to expert, the novice learner must undergo hours of meaningful practice before knowledge becomes conditionalized and can be retrieved with fluency when necessary.
The seventh chapter deals with the importance of pedagogical content knowledge, which in addition to expert knowledge, can lead to more effective instructional practices. According to Bransford et al. (1999, p. 155), “Expert teachers know the structure of their disciplines, and this knowledge provides them with cognitive roadmaps that guide the assignments they give students, the assessments they use to gauge students’ progress, and the questions they ask in the give and take of classroom life.” That is to say, that the experienced teacher with good pedagogical content knowledge also possesses a model of how the prototypical student would learn the content. Included in this chapter, are examples of teaching across multiple disciplines, including history, mathematics, and science.
Provocation:
- In “How People Learn,” we are given the sense that all learning is context-dependent. Do you agree or disagree and why? Is it possible that learning can occur across contexts such that information that you learn in one context can be readily applied to another? How could the context-dependency of learning affect how we interact online vs. in offline environments? Is this knowledge transferrable?
- In chapter 2, the authors suggest that instruction that is “a mile wide and an inch deep” is generally not a constructive form of learning and results in a superficial level of knowledge. In your own experience as a student and/or a teacher, how do you view this breadth vs. depth trade-off? Is there ever a risk in covering one topic “too in-depth”? In an ideal world, how should instructional time be allocated for sufficient coverage?
- The authors suggest that expertise in a domain does not necessarily result in good teaching ability. In fact, the automatization of expert knowledge can make it difficult to verbalize the information and to effectively communicate it to novices. What do you think this means about the nature of teaching? How does one revert to an earlier stage of expertise in order to communicate knowledge to a novice learner? Is this merely a process of deconstructing implicit knowledge into an explicit, readily verbalized form?
- In chapter 7, the authors cover some effective teaching strategies in multiple content-areas. If you were to provide instruction to novice students in your area, what strategies would you consider using? Would the strategies be similar or substantially different than those used in the content-areas described?
References
Bransford, J., Brown, A., & Cocking, R. (Eds.) (1999). How people learn: Brain, mind, experience, and school. Washington, DC: National Academy Press.
Teresa,
Thanks for your thorough post!
I was particularly interested in your second question, which asks whether it can in fact be meaningful to engage modes of instruction that are “a mile wide and an inch deep,” in contrast to the claims in “How People Learn.” I feel this question is informed by the same logic of dividing learners into “expert/novice” categories, and of distinguishing good teachers as those who can hold the whole scope of their instruction in their head and chunk accordingly. It strikes me that in order to group categories, we need to have a sense of the whole picture (both as teachers and students)–how else do you know what fits where, and which patterns relate?
Admittedly, this perspective is informed through recent experience: this week, I taught a workshop called “The Lexicon of DH” as part of the GC Digital Fellows offerings, and first things first: have to give a shout-out to this course for providing such good material to think through pedagogy, and also to my colleagues in this course who have modeled excellent teaching in their ITP workshops! Y’all are AWESOME!
The nature of the “Lexicon” workshop was that it was meant to provide an entire overview of the field of Digital Humanities, so students would be better able to start determining which areas appealed to their interests, which types of tools and critical methods can be well matched, and generally where they wanted to position themselves in a wide and unwieldy discipline. We didn’t go in depth on anything, but instead sketched the whole field at a speedy clip. We used Zotero to build our own bibliographies, followed along on a hyperlinked Powerpoint, took breaks to research tools that looked particularly relevant, and had group work to get ideas flowing. Of course, participants expressed frustration at certain elements of how brief the overview was, but still seemed glad to have a link between the usual theory-heavy DH classes and the highly specialized tool-type workshops. Having a sense of scope that we can share with our students–even as we acknowledge the superficiality of only large-scale survey learning–can be a valuable initial step that allows us to begin the process of information chunking and develop toeholds into complex topics and domains.