11
Jan
2016

MOOC MOOC: Instructional Design

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Join Digital Pedagogy Lab and Hybrid Pedagogy from January 25 – February 12, 2016 for a meta-MOOC about instructional design.


“Didn’t we have bigger dreams for instructional technology?” ~ Phil Hill

By the end of this post, you will:

  1. Know the theme of the next MOOC MOOC
  2. Be able to articulate when MOOC MOOC will begin
  3. Be prepared to participate in #moocmooc discussions
  4. Have your ideas about instructional design challenged or affirmed, or both

(To know more about the birth and evolution of MOOC MOOC, you’ll need to do your homework.)

I have written that: “today most students of online courses are more users than learners … the majority of online learning basically asks humans to behave like machines.” This comes out of the fact that most online courses today are written around instructional design principles, which in turn were written around research in computer-aided instruction (CAI). The relationship fostered by instructional design is not one of learner to learning, it’s one of learner (or, more to the point, student) to mechanized instruction.

I say this now, on the eve of donning the mantle of Instructional Designer for the Office of the Associate Provost of Digital Learning at Middlebury College. A very long time ago, I wore that mantle for a small start-up firm in Colorado whose nearly sole client was Skillsoft, and whose primary foundation for instruction was Bloom’s Taxonomy. Quite literally, software for corporate training was designed around the cognitive domain of the Taxonomy of Educational Objectives. All learning, in this case, boiled down to five component objectives:

  • Remembering
  • Understanding
  • Applying
  • Analyzing
  • Evaluating

And every course we wrote scaffolded learning along the ladder of these objectives, almost always resting at application-level work… because that’s all workers were expected to do, really, to be considered knowledgeable. Bloom and his team defined knowledge as involving “the recall of specifics and universals, the recall of methods and processes, or the recall of a pattern, structure, or setting.” Which means that, to this kind of instructional design, knowledge is the same as recall.

New experiments in digital learning — personalized learning, adaptive learning, competency-based learning — raise the banners of education revolution (as did the MOOC), but what principles are they founded on? What relationship do they encourage between learner and learning, or learner and computer? In many cases, the methodology hasn’t evolved from a critical pedagogy, but rather from the same CAI principles of traditional instructional design. Monkey see, monkey do, monkey hit submit. Students in adaptive learning or competency-based learning environments may seem to have more “say” in how their learning happens, but knowledge still equates, and is inevitably assessed according to recall.

But of course, knowledge isn’t the same as recall. It’s more than that. For starters, we know that learners can create knowledge, that they can be their own best resources outside of a teacher or content. If we look at complexity theory, for example, we discover that knowledge is the result of inquiry, experimentation, feedback, and emergence. As well, the relationship of the learner to the computer can be more nuanced than the kind of “banking education” CAI demands.

Ladies, gentlemen, and everyone in between, Seymour Papert:

Most honest Schoolers are locked into the assumption that School’s way is the only way because they have never seen or imagined convincing alternatives to impart certain kinds of knowledge … almost all experiments in purporting to implement progressive education have been disappointing because they simply did not go far enough in making the student the subject of the process rather than the object.

The hard truth is that instructional design needs to start imagining convincing alternatives, needs to go “far enough”.

Do CAI, and its stepchild instructional design, really demand “banking education”? Matthew Kruger-Ross writes that “CAI redefined learning as driven by clear and concise objectives that could be easily quantified and measured.” Quantifying learning depends on right answers, and right answers are based on recall of content. This is learning reduced to a game of Simon. As Amy Collier has observed, this sort of teaching

has had the effect of 1) narrowing our views of what learning is, thus ignoring more humanistic, holistic, critical, and speculative approaches to learning; and 2) narrowing our views of what learning looks like and what counts as valid research on learning, thus ignoring more humanistic, holistic, critical, and speculative approaches.

When the computer becomes the teacher, it preempts any real potential for student agency, knowledge production, or creativity.

Student agency arrives in the form of open inquiry, which relies on learner autonomy at a foundational level. This is not just the teacher constructing opportunities or scaffolding for agency, leading the students to discover that they have certain, limited ownership of their learning. Student agency is an assumption built into the pedagogy, and comes from an integral trust of learners’ capabilities. Quite the opposite, In banking education:

  • the teacher teaches and the students are taught;
  • the teacher knows everything and the students know nothing;
  • the teacher thinks and the students are thought about;
  • the teacher talks and the students listen — meekly;
  • the teacher disciplines and the students are disciplined;
  • the teacher chooses and enforces his choice, and the students comply;
  • the teacher acts and the students have the illusion of acting through the action of the teacher;
  • the teacher chooses the program content, and the students (who were not consulted) adapt to it;
  • the teacher confuses the authority of knowledge with his or her own professional authority, which she and he sets in opposition to the freedom of the students;
  • the teacher is the Subject of the learning process, while the pupils are mere objects.

With CAI, and with so much of instructional design, you can replace “teacher” with “computer” or “content” in the phrases above. The computer teaches. The content knows everything. The computer chooses, disciplines, acts. The content is the subject of the learning process.

Perhaps above all, instructional design depends upon the notion that outcomes both determine learning and can be conceived ahead of time — sometimes so far ahead of their delivery that we can’t know who the students are, how many there are, what their backgrounds or level of preparation are, or how their intersectionality might affect their approach to the subject matter. The learner becomes a generic factor in the planning of mechanized, scheduled knowledge brokering. The instructor, through design, becomes nothing more than a recording, a megaphone, her only nuance the occasional typo. The lecture — which next to assessment is at the core of such a course — becomes stultifying, common, bad.

Ira Shor writes, “At the heart of my lecture was my search for a presentation that could unveil a compelling reality to the students.” We must ask, is today’s instructional design bent on this same unveiling? Can a course whose content circles around objectives, assessments, and recall pull back the curtain on anything? Can it, as Paulo Freire suggests, invite learners into an epistemological relationship to reality?

At the bottom of this discussion lies the question, “What is learning?” And any critical course design must focus on how we answer that question. Is learning a matter of recall? Is learning emergent? Is learning the development of critical faculties? Or is it some combination of these things… or something altogether different?

Enter MOOC MOOC: Instructional Design

Beginning on January 25, 2016, Digital Pedagogy Lab will be hosting MOOC MOOC Instructional Design (MMID). We will be aiming to unveil instructional design for both its strengths and weaknesses, and we will ask about its future — in light of the revelations of the MOOC movement, complexity theory, and the quest for more and better buzzwords for variations on the CAI theme.

This year, we’ve chosen to jump down the throat of instructional design for a few different reasons. First and foremost, as more learning goes digital, instructional design is no longer a peripheral preoccupation in education: it is a force to be reckoned with, discussed, and understood. Additionally, more and more learning is being turned over to instructional designers, who sometimes must push the round peg of teachers’ content into the square hole of the learning management system. Teaching is rapidly becoming an effort between experts in the field and experts in design, with only the rare conversation about pedagogy. Efficiency has become the modus operandi of the educational institution, which leaves inquiry, agency, and emergence to find other arenas for expression.

MMID will be distributed. Each week, we’ll hold a discussion on Twitter using #moocmooc; and the questions for the discussion — along with readings, prompts, and instructional challenges — will appear here on the Digital Pedagogy Lab site. All participants will be encouraged to write on their own blogs, Facebook pages, or up and down all over Twitter to record their own observations, invite their own networks into the discussion, and to produce, rather than recall, knowledge.

Here’s a quick look at the schedule for MMID (some of the readings may change as we go):

Week 1 (1/25 – 31): Foundations of Instructional Design

Week 2 (2/1 – 2/7): Critical Instructional Design

Week 3 (2/8 – 2/12): Emerging Instructional Design

There’s no need to register, and the MOOC is free to join, but if you want to keep up on news and information about MOOC MOOC and other Digital Pedagogy Lab offerings, sign up for our occasional e-mails.

Sign up now for updates

 

[Photo “Convergence (Explored!)” by Moe Moosa]

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