Intermediate level
No prior experience required
Designing for Transfer of Learning
Flexible schedule
1 week, 6 to 8 hours per week
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*Proof of full-time student enrollment required. Acceptable forms of ID include a letter from your university’s registrar office or an unofficial transcript. Email your documents to learnlab-help@lists.andrew.cmu.edu.
What you will learn
- Explain major theories of transfer, including general and specific transfer, meaningful and rote transfer, and lateral and vertical transfer.
- Describe analogical transfer, including its stages and the difference between deep and shallow features.
- Evaluate classic studies of transfer and explain what they imply for instructional design.
- Use ACT-R concepts such as chunks and production rules to reason about when transfer is likely to occur.
- Identify how target knowledge and source knowledge shape different types of transfer and their instructional implications.
Course description
Transfer is one of the most important goals of instruction, but also one of the most misunderstood. Learners do not automatically apply what they studied in one lesson to a new problem, context, or representation. This course introduces major theories of transfer, including general and specific transfer, meaningful and rote transfer, lateral and vertical transfer, and analogical transfer, and connects them to practical decisions in course design.
In this course, you will examine classic research on transfer, including work by Thorndike, Judd, Wertheimer, Katona, and Wason, and explore how cognitive models such as ACT-R explain when transfer is likely to occur. The course is designed to help you move beyond the vague goal of “teaching for transfer” and instead make more precise design choices about the kinds of knowledge, practice, and representations that support application in new situations.
Syllabus
Module 1: Theories of Transfer and Their Design Implications
- Compare general and specific transfer, including Thorndike’s theory of identical elements and the limits of that view.
- Distinguish meaningful and rote transfer as well as lateral and vertical transfer, and connect classic studies by Judd, Wertheimer, and Katona to instructional design decisions.
- Explain analogical transfer, including its stages and the difference between deep and shallow features.
- Use Wason’s selection task to reason about the specificity of transfer and how concrete versus abstract representations affect application.
- Apply ACT-R ideas such as chunks and production rules to explain when transfer is likely to occur.
- Evaluate evidence for and against broad general transfer and identify how target knowledge and source knowledge shape transfer outcomes.
Meet the instructor
Dr. Vincent Aleven
Vincent Aleven’s research aims to advance the science of how people interact and learn with adaptive, AI-based learning technologies, and to advance the design and engineering of these technologies. Practically, he aims to help realize the smart classroom through strong synergy among learners, those who facilitate learning such as teachers, instructors, peers, tutors, and parents, and novel AI applications. In this context, he is excited to help a new generation of scientists and professionals develop interest and skill in research and development.
Where to go next
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Evidence-Based Backward Design for Online Learning
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Introduction to Learning Engineering
Apply learning engineering principles to design effective e-learning and use the KLI framework to match instructional strategies to the right knowledge components and learning processes.