In this month’s guest post, Erin Czerwinski shares how we can look at the process of instructional design through a scientific lens. This approach encourages faculty to embrace iterative development and feel empowered by their course design.
Erin Czerwinski is an experienced curriculum developer and learning engineer. Erin currently works as the Manager, Learning Engineering and TEL Product for Carnegie Mellon University’s Simon Initiative and Open Learning Initiative.
As Erin’s motto goes, “Every course you build is a hypothesis of how you think the students will learn it.” This approach aligns with the features and design of CourseTune. The tools can help you apply the scientific method to the curriculum design and see the opportunities for improvement.
We thank Erin for sharing her perspective and for getting nerdy with us. You can watch her recent webinar with us on Foundational Knowledge Course Design here. Thanks, Erin!
I believe that every course that you design is a hypothesis essentially. You’re putting your idea of what learning is out into the world. How will the students learn it? How will they work through the materials? It’s all in the course design. And you’re really collecting ideas all the time. Whether you’re collecting feedback from the students in the form of data or just notional things you observe. All of it informs how you can better your design. It also exposes where students are still struggling, where they might need more scaffolding, and where they might need things broken down a little further. The idea is that this data drives feedback loops — feedback loops to the instructor, to the student, and the course designers. Hopefully, these feedback loops inform overall learning science in the aggregate.
The way students organize knowledge determines how they use it. All that means is that students bring a lot of prior experience with them that could be full of misconceptions.
Find your evidence in student objectives and learning outcomes.
Scientists know that they can’t make assumptions and accept them as fact. They need proof to support their theories. The same approach should be applied to how we look at students. We can’t assume we know what they know. We can’t guess that they already have a certain level of experience. As educators, we have to keep an open and curious mind, particularly when it comes to our students. Students from K-12 to Higher-ed will keep changing. The only way to ensure a course design stays relevant to their needs is to remain in a continuous improvement mindset.
It comes down to what do you want your students to be able to do. To make sure that you’re giving practice and assessments that align with those outcomes. Then making sure that the instructional content and everything else falls together. You want to think about, “How will I know when or how will I know it when I see it? How will I know when my students have achieved mastery or whatever you call mastery?” The answers to those questions should be your learning outcomes.
Learning outcomes, at any level, are the evidence you are looking for. How do you know your course is working? The outcome has to be written in a way that is clear to the student. They have to know what they’ll be able to walk away with and do.
Give yourself permission to question everything.
To help people who are new to this domain, I share research with them from this list of articles, videos, and books. This information helps explain the WHY behind intentional course design. It’s handy for educators who have been doing things the same way for a long time. Even the existence of so much research is enough to get them excited about the possibilities of designing a well-aligned course that clearly communicates their goals. I want to get them thinking and questioning. Questioning is a good thing!
Scientists also give themselves the permission to question themselves. Their methods are open to examination. They challenge themselves and their peers to find ways to improve the delivery and consistency of their work.
Educators can benefit from taking time to reflect and discuss their learning design. If you have a learning objective and you start to think, “Okay, what are the steps my students would take to learn to reach that learning objective?” And then end up with 15 skills underneath that learning objective. That’s probably too much, right?
I usually look at something like that and say, “Are all of these really necessary?” Maybe there are actually two learning objectives here. You’re putting them all under one topic area. Conversely, if you have only one skill you can think of under a learning objective, maybe that learning objective isn’t as meaty as you thought. Perhaps it’s a skill that belongs to a different learning objective.
A dynamic course never says die.
Why isn’t a course design ever done? Once it’s being taught and students are passing, isn’t that enough? Thinking like a scientist means continuously thinking about “what-if” and “what about.” Learning is a lifelong experiment that is dynamic and active. Binders on a shelf aren’t living, changing curriculum documents.
By looking at your course in a visual tool like CourseTune, you can see opportunities and gaps that were never apparent. You can iterate on the delivery design as easily as moving Lego pieces around. With a click of a button, you can see whether all learning objectives are covered in the activity and assessment panel.
Students aren’t static and dusty binders full of spreadsheets won’t help them meet their ever-evolving goals. Course design has to continuously improve and iterate to be student-centered.
Ask questions about your data.
The research-collection, the analysis and synthesis of data, and the ability to draw conclusions from patterns are skills shared by curriculum designers and scientists. It’s a lot to take in and make sense of. Consider what you know about the behind-the-scenes lives of learning engineers, instructional designers, or learning experience designers. How many documents would you guess are created in a typical course design process? Here are 54 possible documents you can use across the different stages of the design process.
You’ll have to meet the challenge of knowing what data is essential versus learning how to get the correct data. Then you’ll need to figure out what to do with it. Don’t know where to begin? This document can get you going in the right direction.
If you have CourseTune (and you should), you’ll want to learn how CourseTune talks about reports and data. For example, the Course (Level 4) Outcomes Report will generate a list of outcomes the course meets. This report can help you answer questions like, where can I pull a summary report of the course alignment to an outcome set (PLO, Standard, etc.), or what documentation can I include in a body of evidence for a course review or an accreditation audit? The goal of all reports in CourseTune is to help you make sense of your data. The end result? You can use your data in meaningful ways to improve your courses.
How to get started with instructional design experimentation.
What might some of these learning experiments look like in your course? It depends mainly on the phase of work you might be in and what you want to evaluate. Here’s a document that shows the time, tasks, resources, and considerations across the phase of design and development. This will help you gauge the duration of your experiments.
Go where your strengths are. Some instructors are really great with activity design.
Some are great with assessment design. You don’t have to be the expert in everything.
If you want advice or support, find a community like ICICLE.
And remember the motto: “Every course you build is a hypothesis of how you think the students will learn it.”
While thinking like a scientist won’t add any additional letters to your title, it can provide you with an approach that will improve your course design understanding. Hopefully, it will spark a little bit of playful curiosity to find new ways to engage your learners.
Here are some more resources to take back to the lab.
Ready to take a deeper dive into a scientific approach to instructional design? Here are a few resources to take a look at:
- A Course Archetypes video showcase from CourseTune
- Open Learning Initiative
- OpenSimon Toolkit
- LearnSphere (can do lightweight analysis without much instrumentation)
- Eberly Center
- Learning Engineering Bibliography (including KLI Framework)
- A guide to some questions CourseTune’s reports will help you answer.
CourseTune can help you look at your instructional design scientifically.
In the classroom, educators watch for head nods, drifting eyelids, and raised hands to evaluate engagement and learning in action. When they give an assessment, they look at the scores and analyze their assessment design for possible changes. Naturally, the process of teaching involves making guesses, collecting data, and shifting instruction with new insights– just like a scientist.
Every time educators interact with students, they make a well-educated guess that they are helping a student. Wouldn’t it be great if they KNEW that they made the correct guess? With transparent tools and an aligned course, you can start to gather evidence of your student’s success.
CourseTune’s patented visualization gives educators a chance to see their course as a hypothesis.
You can learn more about CourseTune here.
You can also schedule a free call to talk with the CourseTune team.