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.


From http://www.houzz.com/photos/36213135

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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Video Code Easter Eggs

I have this sneaky trick I use to tell which students watch online videos and which don’t.  I hide “secret codes” in the videos (like the programmer’s Easter Eggs).  When a student finds one of my “Easter Egg codes” they can submit it for 1 point towards participation.  Sometimes the codes are numbers I generate at random (Ex: 40234) and sometimes it’s a word, phrase, or story (my cat is chasing a fly in front of my computer).

I don’t tell the students where the codes are. I don’t tell them HOW I’ve shared the code or what kind of code it is.  Some videos have codes, and many don’t.  Because of the random distribution of codes in videos, and my “loose” way of collecting them for points, I can always add or remove videos with codes, and it won’t affect the overall point system.

Here's an example of a video code inserted as a callout bubble. Click on image to enlarge.

Let me explain. Students are not required to watch particular videos and there are two other ways to earn participation points.  Participation for each unit is counted out of 10 points, but 5 extra credit points may also be earned.  Thus, there is a cap on the total number of points I will count.

Participation points can be earned by:

  1. Participating in a live online chat. (2 points)
  2. Posting something substantive in a Discussion. (1 point)
  3. Turning in a video code. (1 point)

Here are various ways that I hide the codes in videos:

  • In callout bubbles I add post-recording and pre-production
  • On calculator screens (sneaky, huh?)
  • In something I say out loud
  • In something I write on the journaling screen
  • In something I say and write on the journaling screen
  • In the text of a math equation
  • Underlining a particular word or phrase on the screen from a lesson
  • An action to take (call my office phone and sing the quotient rule to me)

Collecting the codes is the real trick.  Some years I’ve used a Google Spreadsheet or Doc for the collection.  This year, I’m using the comment field of the Canvas Graded Discussions.  I set up one Discussion for each unit, worth 10 points.  When a student participates in an online chat, I go to the gradebook for this Discussion and add a comment “Chat 7/9/12 = 2 points” for that student.  When the student submits a video code, I go to the gradebook for this Discussion and add the comment “Video Code 40234 = 1 point”.  Then when I go to grade the assignment, I see not only all the students’ discussion posts, but also all their collected codes and chat points (see image).

Canvas Discussions grading screen with comments. Click on image to enlarge.

It’s really interesting to see which students find and submit the codes and which students never submit a single code. This helps me to track the progression of students through a particular unit.  Pessimistically, it helps me to “catch” those students who claim they are watching videos when, in fact they aren’t.  But optimistically, I can also tell who consistently watches all the videos by seeing their collected codes pile up.  While I haven’t always enjoyed keeping lists of students and codes, the “Easter Egg” method has worked well over the years to keep track of video-watching as a way to participate in online courses.

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