Practicing Connections: A Framework to Guide Instructional Design for Developing Understanding in Complex Domains.
Saved in:
| Title: | Practicing Connections: A Framework to Guide Instructional Design for Developing Understanding in Complex Domains. |
|---|---|
| Authors: | Fries, Laura (AUTHOR), Son, Ji Y. (AUTHOR), Givvin, Karen B. (AUTHOR), Stigler, James W. (AUTHOR) |
| Source: | Educational Psychology Review. Jun2021, Vol. 33 Issue 2, p739-762. 24p. 5 Diagrams. |
| Subjects: | Instructional systems design, Mental representation, Comprehension, Education statistics |
| Abstract: | Research suggests that expert understanding is characterized by coherent mental representations featuring a high level of connectedness. This paper advances the idea that educators can facilitate this level of understanding in students through the practicing connections framework: a practical framework to guide instructional design for developing deep understanding and transferable knowledge in complex academic domains. We start by reviewing what we know from learning sciences about the nature and development of transferable knowledge, arguing that connectedness is key to the coherent mental schemas that underlie deep understanding and transferable skills. We then propose features of instruction that might uniquely facilitate deep understanding and suggest that the connections between a domain's core concepts, key representations, and contexts and practices of the world must be made explicit and practiced, over time, in order for students to develop coherent understanding. We illustrate the practicing connections approach to instructional design in the context of a new online interactive introductory statistics textbook developed by the authors. [ABSTRACT FROM AUTHOR] |
| Copyright of Educational Psychology Review is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Psychology and Behavioral Sciences Collection |
Be the first to leave a comment!
