why we learn

Classroom instruction is complex but do we treat it as such? Is “sensing” a priority of teacher education? How would an instructor who waits for “patterns to emerge” be viewed by their supervisor? As laid back? Aloof? And does outcome-based education (unintentionally) result in educators treating complex situations as complicated, or worse yet, simple in nature? These questions find their origins in the work of David Snowden and Mary Boone, as they apply the principles of Snowden’s Cynefin Framework to leadership in the 2007 Harvard Business Review article A Leader’s Framework for Decision Making.

Rather than summarize Snowden & Boone’s application textually, I’ve generated a graphical representation. Clicking on this smaller image will produce the full-sized document.

Initially, my interest in this article was peaked by a blog posting of David Clark in his series of writings aimed at describing how the tenets of Agile software development can be applied as a system of instructional design. The HBR article had the added advantage of using this framework as a lens from which to view leadership, a topic of focus for me now as I begin supervising staff at my school. However, its application to the classroom teacher is intriguing.

Aren’t teachers really classroom leaders, or leaders within a complex educational / instructional setting? David Williamson Shaffer, in his 2004 TCR article Pedagogical Praxis: The Professions as Models for Postindustrial Education states the following.

We know a great deal about some of the epistemological and pedagogical underpinnings of compelling learning environments. However, orchestrating these elements into a coherent whole remains a challenge (p. 1417).

Shaffer suggests that professions have unique epistemologies, or “ways of knowing”, and thus have the potential to be used as models for instruction. Daniel Willingham, in his new book Why Don’t Students Like School?, alludes to the complexity of the educational setting as well as he explains the disconnect between controlled experimental studies and the classroom.

But mental processes are not isolated in the classroom. They all operate simultaneously, and they often interact in difficult-to-predict ways (Kindle edition, Location 126).

Marzano et al., in their work Classroom Instruction that Works: Research-Based Strategies for Increasing Student Achievement discuss nine categories of instructional strategies.

• Identifying Similarities and Differences
• Summarizing and Note Taking
• Reinforcing Effort and Providing Recognition
• Homework and Practice
• Nonlinguistic Representations
• Cooperative Learning
• Setting Objectives and Providing Feedback
• Generating and Testing Hypotheses
• Cues, Questions, and Advance Organizers

Throughout this work, the presented strategies are also (necessarily) related to content and instructional situation. Doesn’t this make instructional choices more complex? If we agree with Willingham, who differs from Marzana et al. in this regard, there’s another layer of complexity that must be superimposed onto the extant relationships between content and strategy, topic specific ability. He contends that we must present problems to learners that fall within a specific range, not too tough (which causes despair), or too easy (no satisfaction, nor release of dopamine), but just right. (Goldilocks analogies are welcome.)

Thus, we will seek out opportunities to think, but we are selective in doing so; we choose problems that pose some challenge but that seem likely to be solvable, because these are the problems that lead to feelings of pleasure and satisfaction (Kindle edition, Location 400).

At this point, I’ve identified several variables that must be considered by a teacher as they teach.

• What needs to be taught
• What has been taught
• What is to be taught in the future
• Individual abilities of students with regards to content
• Individual abilities / preferences of students related to instructional strategies
• Situation / relation between content and potential strategies (what “fits” best)

But there is another, most important factor, life outside of the classroom. What happens beyond the classroom walls, in other classes, and more significantly outside of school, affects each learner. The combination of these variables supports the idea that classrooms should be classified as “complex” with the Cynefin Framework. If we review the traits of “Complex” systems, it is clear that often times there is “no right answer” in terms of instructional choices, that classrooms are “systems in constant flux”, and that the “ability to understand” (from the teacher’s perspective) comes after class has been dismissed.

The ability to work within this complex system (the classroom) is typically part of the teacher observation process. For example, Domain 3e in Charlotte Danielson’s Framework for Teaching is entitled Demonstrating Flexibility and Responsiveness, and includes the elements Lesson adjustment, Response to students, and Persistence. However, outcomes are the focus of this work, not the manner in which those outcomes are reached. Admittedly, factors such as rapport and teacher-student interactions are also part of these assessments, and these might be considered constituents of “probing”. However, the emergence / identification of patterns is not addressed in any meaningful way.

Is there a need, then, to construct a formalized framework / structure for “probing” and “sensing (for emergent patterns)” specific to the classroom? Is this something teachers need to know how to do? Would familiarity with the tenets of the Cynefin framework lead to more effective instruction through appropriate responses to the different categories of complexity manifest within that setting?

Comments and/or critiques are welcomed.

Benjamin S. Bloom has two works from which to draw when interpreting the results of a new study by Carnegie Mellon. The key finding, related to the efficiency of this design, is summarized in the following quotation.

By combining the open-learning software with two weekly 50-minute class sessions in an intro-level statistics course, they found that they could get students to learn the same amount of material in half the time.

Essentially, the inclusion of this intelligent tutoring system allows the professor to discuss more nuanced and/or complex aspects of the content, and do so in one less class period. Bloom might infer that the observed improvements were due to an increase in the amount of time spent analyzing, synthesizing, and/or evaluating, i.e., at the higher levels of “his” taxonomy, while in class. Alternatively, he could point to his work on tutoring, and its corresponding “2 Sigma Problem”, which suggests that one can expect to observe a difference of +2 standard deviations when students work with a teacher in a one-to-one setting.

I’m inclined to agree with both of these hypothetical conclusions. I’m also reminded of Ewan McIntosh’s recent response to Will Richardson’s post commenting on an image of a lecture hall filled with (mostly Apple) computers. McIntosh’s critique, in he differentiates between curriculum and pedagogy, noting that teachers can control pedagogy but not curriculum, culminates with the following assertion.

The reason the picture presents a dubious message is that neither curriculum nor pedagogy have changed an iota in this learning space: it’s about the same layout – with as many apples on laps – as a Victorian classroom would have appeared.

I wonder how instructional design fits, as Carnegie Mellon’s design offloads the mundane, didactic portions of instruction to technological entities, thus freeing up space and time for the instructor/professor to do the sorts of things that are much harder for computers, even “intelligent” systems, to replicate. This is a good start, but can we go further?

The program’s efforts to maximize the contributions of technology are impressive. They’ve applied adaptive algorithms similar to those that are used in the GRE, which monitor and subsequently respond to students understanding. This is one of the first times this technology has been used outside of the assessment arena. (The article refers to its use as “novel”.) What needs to be considered, however, is a design that manufactures or generates time for face-to-face. That is to say that although the tutoring aspect of Bloom’s research is (partially) present in the form of the intelligent tutoring system, the potential of human tutoring is greater.

This is not the first time that I’ve considered using technology to offload the sort of lower level tasks of instruction. My presentation, entitled “A Shift in Focus: Designing for Face-to-Face” can be found here. Comments/critiques are welcome.

What was the research question(s) in the article?

This researcher’s work focuses on uncovering ways in which online instructors can successfully scaffold their students. The early part of the paper reviews learning theories, specifically Behaviorism, Cognitive Theory, Constructivism, and Social Constructivism. One senses from the placement and because of the words used to introduce each succeeding theory that the author views each theory as an evolution. Social Constructivism and it’s tenants that learners are active participants in their learning, that learning is socially constructed form the basis for the researcher’s study.

Is the literature review relevant to the research questions(s)?

The reviewed literature was used in three ways. Early in the paper, the author uses recent work to frame the existing ideas and concerns surrounding online (distance) education. The focus quickly shifts then to the previously described review of learning theories. Additionally, the author takes some time to review literature related to scaffolding, a large component of Vygotsky’s Zone of Proximal Development. Finally, Bryceson reviews knowledge-management literature as a way of further contextualizing the review, and of segueing into looking at the work of Nonaka and Konno (1998) related to ‘Ba’.

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What was the research question(s) in the article?

The reviewed article looked at how educators might embed thinking frames or ways of faming and thinking about problems, into their existing curriculum. The author’s premise is that good thinking is unnatural, that is, that although the purist may have an instinctively negative reaction to the idea of teaching “ways of thought”, the reality is that high-quality thought processes are, in many ways and for many individuals, unnatural and need to be learned.

Is the literature review relevant to the research questions(s)?

The reviewed literature was appropriate. Perkins begins by examining research related to the various ways in which intelligence is defined. He divided this body of work into three camps, those that perceive intelligence to be a fixed entity (which he refers to as “power”), those who subscribe to the idea that intelligence is derived from domain specific knowledge or expertise (which he refers to as “content”), and lastly, those researchers who believe that intelligence is related to the “tactical repertoire” of the individual, which he simplifies to “tactics”. Perkins concedes that each must be considered, and from this body of work he generates a elementary mathematical formula.

Intelligence = Power + Tactics + Content

The remainder of the article is based on the premise that “power” is, for all intents and purposes, a fixed entity, that “content” is already the focus of traditional schooling and something which takes painfully long to expand, and that “tactics” have long been ignored as a piece of the curricular puzzle. Thinking frames, defined by the author as a representation intended to guide the process of though, supporting, organizing, and catalyzing that process (p. 7). Literature is used to support the use of different types of thinking frames and to give examples of current programs which fall within the author’s definition of frames.

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