Interdisciplinary Courseware to the Rescue?

In the midst of all the bling of media-rich, adaptive, personalized, [insert-buzzword-here] digital products, there is a lurking underlying problem:

The general education curriculum in higher education has barely changed. Today’s world is cross-disciplinary, culturally diverse, and team-oriented. There is almost no problem that can be solved in a silo content area with a team of one.

Map showing the interconnected nodes between a variety of subject areas in research.

Interdisciplinary Thinking, from New Scientist’s article “Open your Mind to Interdisciplinary Research”

We need new cross-disciplinary curriculum. We need courses that are more engaging and reflective of today’s real issues. We need courses like these (referenced from my 2009 post on Hacking Higher Education):

  • Trend Analysis (Math + History)
  • Biology and Human Enhancement (Biology + Philosophy)
  • Science of Exercise (Science + Health & PE)
  • Exploring Water Issues (Science + Politics)
  • Design and Digital Presentations (Graphic Design + Communication)
  • Data Analysis and Information Presentation (Statistics, Graphic Design, and Communication)
  • Exploring Recycling and Refuse (Science, Government, and Humanities)
  • Chemistry of Nutrition (Chemistry + Health & PE)
  • Poverty and World Culture (Humanities, Government, and Sociology)
  • Sociology and Psychology of the Web (Sociology + Psychology)
  • How Computers Think (CIS + Philosophy)
  • Art, Media, and Copyright (Fine Arts + Law)
  • Writing for the Digital Age (CIS + Communication + English)
  • Energy (Physics, Chemistry, and Government)
  • Information, Query, and Synthesis (Literacy, Logic, English)

The problem is that very few faculty can teach courses like this without extensive learning or teamwork, and very few authors that could write such a curriculum from scratch.

This is exactly the moment when “digital courseware” should rise to the occasion. Digital courseware could be built to support these kinds of inter-disciplinary courses with a well-designed learning experience (not just text, but formative assessment and designed interactions with students and faculty). It could be multimedia rich, adaptive, personalized, and all that good buzzword stuff.

With a solid digital courseware backbone to support the learning, faculty could be tapped from different disciplines to evaluate work, answer questions, and coach students in their learning. No one faculty member would have to learn all the nuances of the course immediately.

So why aren’t we getting that? Why are we just getting more Algebra, English Comp, and Freshman Biology courses? Because that’s what we keep asking for. We keep saying, “give us better pass rates for these courses we currently teach.” We keep funding the rebuild (and rebuild) of those courses that create retention and graduation pressure in higher education. What if the problem is not the delivery of the course, but in the course itself? What if students are never going to do better in these courses because deep at the heart of the issue, the student knows the course isn’t applicable to the world they live in?

The Big History course (funded by Bill Gates) is an admirable step towards creating a more modern and more interdisciplinary curriculum. MOOCs do not have to pay attention to credit counts, what “department” the course lives in, or how it will or will not count as an elective towards multiple degrees. Consequently, MOOC providers have the freedom to build interesting, modern, and cross-disciplinary courses like The Science of Everyday Thinking (from EdX) or Politics and Economics of International Energy (from Coursera).

But why is it outsiders to education that have to lead these efforts? Educators should begin asking for the “right” curriculum from courseware providers (looking at traditional publishers, digital platforms, and MOOCs). We need to ask for the curriculum we want to teach instead of that which we have always taught.

Of course, courseware providers aren’t going to build something they don’t think has a market yet – and so we have a classic “chicken and egg” problem. This seems like exactly the kind of problem that needs a funding push. If a beautiful digital course on “How Computers Think” or “Poverty and World Culture” became available nationally at a low cost, I’d like to think that institutions and faculty would be able to step up to the challenge of figuring out the rest of the logistics to offer these courses.

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Why prototype a digital course?

Very few of us would buy an unbuilt home without at least viewing a model home that conveys the look and feel of the interior and exterior of the rest of the community. We should be unwilling to build (or buy) an entire course (a “row” of units, modules, chapters, or weeks of content) without seeing at least one “model unit” first.



In the software world, a low-fidelity prototype is used to give the look and feel of a future product. With this prototype there is some hand-waving (mockups) to explain away missing functionality and potential users are asked how they would navigate and use the product. This happens long before the product build, and is iterative.

In the learning world, we should consider that course builds (especially large-scale digital courseware) need the same kind of prototype.  Before the time and money is invested to build the a full course, consider building one unit as completely as possible, and make sure your stakeholders (students, faculty, instructional designers, deans, customers) actually want to learn in this course.  Choose a prototype unit that is most representative of the majority of the learning in course; this is usually not the first or last unit.

When the model unit is being designed and built, this is the ideal time to collaborate iteratively with students, faculty, IT, assessment, and instructional designers. While it will take some time to change the model unit as opinions shift, it will not take as much time as remodeling every unit in the course.

After you’ve got stakeholder approval for the model unit design, make sure to carefully document what features this prototype contains, since your team will need to apply it consistently across the full development. Here are just a few of the learning features you might want to apply across your multi-unit build:

  • content: where did it come from? what quantity per learning objective?
  • examples: how often, how relevant?
  • interaction: how much, what kind, and how often?
  • assessment: what kind? how often? authentic? purely for practice? for learning scaffolding?
  • images: for what purpose, how often?
  • videos: how long are they, what stylistic elements are there, how often do they occur?
  • simulations or games: for what purpose? how often?

As digital learning becomes more accepted (thanks MOOCs) and blended learning becomes a more standard model at traditional institutions, I hope we’ll see much more collaborative prototyping, followed by intentional design, in these courses.

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Instructional Design for Vocabulary in Higher Ed (Part 1)

Part I: Tiers of Vocabulary and General Education

In many courses in higher education, we have a need for the students to learn a new set of vocabulary. Vocabulary words can be broken into three tiers (the following are the definitions from Bringing Words to Life, Beck, McKeown, and Kucan, 2013):

Tier One: Words typically found in oral language.

Tier Two: Wide-ranging words of high utility for literate language users.

Tier Three: Words limited to a specific domain.

While there are three (simple) tiers of vocabulary, and these are often depicted in a pyramid or a cake with three levels, I think the learning of vocabulary is much more complex than that, especially as a student acquires the very domain-specific vocabulary of their future career. I prefer to think of the tiers as a more complicated structure of garden tiers, where the plants from one tier might intermingle with other tiers as priorities shift for the learner.

Landscaped tiers containing a variety of garden plants.

Let’s assume that Tier 1 words are what a college student picks up in K-12 education. For solid instructional design of assessments (both formative and summative) in higher education, first consider whether the vocabulary should be learned at the level of Tier 2 or Tier 3.  You might think of this as the difference between teaching to recognize a word and identifying some general connections to it or teaching to recall a word with specifics of function/definition.

As an example of this critical design thinking, let’s do a brief analysis for a set of biology vocabulary for a general education biology course:

  • cytoplasm
  • mitochondrion
  • cell
  • nucleus
  • nucleolus
  • vacuole
  • virus
  • chlorophyll
  • chromosome
  • chloroplast

Pay attention, because in this context of general education, the highest cognitive-level learning objectives do not occur at the highest vocabulary tier.

Tier 1 (words typically found in oral language): cell, virus

Most likely, college students already have common knowledge of how these two Tier 1 words are used in context, but they may lack specific details on how we differentiate between the words. For example, a student may understand both a cell and a virus to be very small structures in the body that carry genetic material but not understand the differences between them. In a college course, you may want to focus learning objectives for already-acquired Tier One vocabulary on differentiation of these words from other common language words, a deeper dive into the understanding of the word, or on how these words relate to other newly acquired higher-tiered vocabulary.

Example Learning Objectives:

  • Compare the structures in a virus and a cell.
  • List the types of cells.
  • Identify the organelles that are often found in a cell.

Tier 2 (wide-ranging words of high utility for literate language users): nucleus, chromosome, chlorophyll

Even if this is a general education biology course, it is likely that students will hear, read, and use these Tier 2 words again during their lives. High-utility means we should try to help the student learn the words at a permanent recall/mastery level (understanding both definition and context).  Learning objectives should be focused on definition (with relevance, like function), characteristics, and comprehension in context.

Example Learning Objectives:

  • Describe the function of the nucleus.
  • Describe the function of chlorophyll.
  • Locate the nucleus, nucleolus, and mitochondrion in a cell.
  • Explain how a plant cell benefits from its chlorophyll.
  • Describe the structure of chromosomes in the human body.
  • Explain the function of chromosomes during human reproduction.

Tier 3 (words limited to a specific domain): cytoplasm, mitochondrion, nucleolus, vacuole, chloroplast

In a general education biology class, it might be important to recognize Tier 3 words and their functions, but it may not be necessary to recall specific definitions of the word or store it in long-term memory past the end of the course. Remember that biology majors that take this general education course will take more biology courses. Each subsequent biology course will provide opportunities for repeated vocabulary retrieval and in-depth learning. A general education course is not the time to drill in every property.  The learning objectives for Tier 3 words in a general education course should focus on the recognition-level with enough comprehension to make sense of the context in which the vocabulary words appear. These learning objectives should also focus on how the Tier Three words relate to lower-tiered words, since that is what will help the learning do sense-making around context.

Example Learning Objectives:

  • Identify the function of the mitochondrion, nucleus, and nucleolus.
  • Label the chlorophyll, chloroplast, and vacuole in a plant cell.
  • Select the organelles that might appear in a plant or animal cell.

As the student moves from general education to a majors-oriented biology course, the learning objectives should also shift and scaffold to support the deeper learning requirements. In this example, Tier 2 vocabulary should be treated as known by the student, but needing further differentiation. Tier 3 vocabulary should be learned to the recall level (instead of recognition). In addition, we ask students to do more sense-making with higher-order concepts while using the acquired vocabulary (even though we no longer mention the vocabulary by name).

Stay tuned for Part II of this series on Instructional Design for Vocabulary in Higher Ed, where we will start to focus on designing digital interaction to teach vocabulary.

Note: I’m not 100% sure that cell and virus would be considered Tier 1 vocabulary words, but it seems to me that these are the most obvious candidates from the example list provided.  Both words appear in the Merriam-Webster Learners Dictionary (which provides definitions in simple English). If you know of a definitive source for Tier 1 vocabulary words online, please let me know.

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The 1-9-90 Rule and Observations of a Classroom Experience

I’ve referenced Vilma Mesa‘s Classroom Mapping for a while now, and want to give this some more thoughtful due diligence.

You can see examples of Vilma’s Classroom mapping in this Slideshow (the images are shared with her permission and you may reshare them by sharing the slideshow).

The 1-9-90 rule is a rule of thumb governing interaction in collaborative environment: 1% of the participants are creators, 9% are contributors (they comment, like and share things), and 90% lurk. While it is applied mostly to collaboration and networking in digital environments, I was struck by how it also plays out in classrooms. If you click through the slides, you’ll see the same ratio play out over and over.
The instructor (one person) creates the content. Roughly 3-4 students ask and answer questions. The rest of the class? They lurk, probably hoping to just watch it all play out without having to participate.
If this is the natural norm of collaborative environments, this gave me a couple questions to ponder. First, should we even try to shift the norm by mandating more participation by the lurkers? I think that classroom environments are a good place to try to engage students in more active learning. Even if a students’ natural tendency is to lurk, she/he has to learn to participate actively even when it is not desirable (they will have to face an employer eventually that will require this of them). So I think that we should try to increase the participation by the 90%, but just be mindful of this natural social breakdown in collaborative settings (translation: there will be pushback).
The second point to ponder is this: typically online instructors do “force” the lurkers to participate in activities like discussion boards. But often the same instructor will have no such type of participation requirement for a face-to-face classroom. Clearly one reason is the time that would take too much time to let everyone in the class have a say in every discussion, not to mention that the discussion would quite quickly become a lot of rephrasing of what other people said. Oh wait … that is what required online discussions are like. If you teach both online and face-to-face, give this some good thought – I think it is our goal to create the most high-value learning experience we can, and while the environment should impact the design of the experience, be mindful of creating dull experiences just because everyone “has to” participate.

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Surviving (and Thriving) in the Age of Technology-Enhanced Teaching

I’ve been giving versions of this presentation at several events lately: AlaMATYC, SXSWEdu, STEAM3, and Elgin CC’s Distance Learning Conference. I said I would post the slides, and so here they are in one version.

To see the video of students in the math classroom, here are some links to the YouTube videos:

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