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How Theory, Research and Instruction Come Together in Active Learning

Tomorrow's Teaching and Learning

Message Number: 
1784

So simply telling the faculty that “active learning” produces better learning is not convincing; they might be more impressed if they understood why we think that’s true.

Folks: 

The posting below “shows how cognitive researchers brings bring together theory, research and instruction to help faculty target the ‘active’ part of active learning.” It is by Marilla Svinicki, Ph.D., (msvinicki@utexas.edu), professor emeritus Educational Psychology, The University of Texas at Austin, Austin, Texas  and is from the National Teaching and Learning Forum, Volume 29, Number 3, March 2020It is from a series of selected excerpts from the NT&LF reproduced here as part of our "Shared Mission Partnership." NT&LF has a wealth of information on all aspects of teaching and learning. If you are not already a subscriber, you can check it out at: http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)2166-3327  The online edition of the Forum - like the printed version - offers subscribers insight from colleagues eager to share new ways of helping students reach the highest levels of learning. ©2020 Wiley Periodicals, Inc. Published by Wiley Subscription Services Inc., a Wiley Company, 111 River St., Hoboken, NJ 07030-5774.  Reprinted with permission.

Regards,

Rick Reis

reis@stanford.edu

UP NEXT: Global Engagement of Colleges and Universities 

 

Tomorrow’s Teaching and Learning

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How Theory, Research and Instruction Come Together in Active Learning

 

One of the most productive ideas championed by educational psychologists in recent times is active learning. But what is “active” learning and how does it work? Some instructors have tried to get students to be more active in class with varying degrees of success. Others have had very active class sessions involving lots of participation and creativity, but not much improved learning when the test comes around. So simply telling the faculty that “active learning” produces better learning is not convincing; they might be more impressed if they understood why we think that’s true. Let me show how cognitive researchers bring together theory, research and instruction to help faculty target the “active” part of active learning more accurately.

We’ll start with just one thread of the work Michelene Chi developed with her colleague, Ruth Wylie, the ICAP (interactive, constructive, active, and passive) framework, focusing on why active learning matters in instructional design. Let me try to do justice to their thinking and actions. (If you’d like to go straight to their own explanation of the ICAP framework, here is the link: https://www.tandfonline.com/doi/abs/10.1080/00461520.2014.965823 . If you really want to become a wonk on this, see Chi et al., 2018.)

Theory

The cognitive psychology behind the value of active learning asserts that it is not the behavioral processes (i.e., just “doing something,” like reading or highlighting a sentence in the text) that are the foundation of “active” learning. It is the cognitive processes (i.e., “doing something constructively that gives individual meaning to what is learned,” like thinking about how the new stuff fits with other things that you’ve learned or, even better, if it doesn’t fit with other things you’ve learned) that psychologists are referring to when we say “active learning.” It’s an intentional, effortful attempt to make connections with what you already know or summarize an idea in your own words, or explain your thinking to someone, not just tell them what you think. So “active learning” involves cognitive activity of engaging with the situation so that you can learn from it.

Being theorists themselves, Chi and Wylie (2014) laid out four modes of cognitive activity that would be indicative of cognitive processes they think are happening. Here’s how I interpret them:

• Interactive mode is the most intense form of cognition, because it involves the give-and-take of discussion that usually stimulates the deepest level of analysis of an idea (the constructive controversy effect). It’s a comparative type of thinking.

• Constructive mode is the first glimmer of the cognitive process that is focused on generating an individual explanation clearer to the learner (the self-explaining effect). It’s a generative type of thinking.

• Active mode is some attempt to do something with the information, without changing it substantially—just repeat it, as one does in rote memory. It is a replication type of thinking.

Passive mode doesn’t really do anything beyond orienting toward a lecturer that may leave a short memory trace that’s gone as soon as the next idea is presented. It’s not much of a type of thinking, I’m afraid. Perhaps it’s a hopeful type of thinking (“I hope I remember this for the test”).

Chi and Wylie (2014) offer the mnemonic of ICAP to remind us of what might produce different types of thinking and learning according to cognitive theory.

Research

What I’ve described above is what some psychologists propose happens during learning. If these are the cognitive processes happening during each mode, then putting a problem to the learner in a way that will reveal how they were cognitively active during the process can lead to suggestions about how to design “active learning.”

And that’s what happened when the ICAP model was researched. Chi and several other of her colleagues showed that when the four types of mode are compared with regard to pre- and post-test performance, the interaction mode produced the best results, and the other three fell in line as predicted.

Confirmation

In other studies, researchers tested the value of self-explaining described earlier. The results consistently show better performance in comparison to active or passive modes alone. Then, Hausmann, van de Sande and VanLehn (2008) compared the constructive mode (self-explaining individually) with the interactive mode (explaining done with a peer). They found that combining the modes produced better performance on a whole bunch of measures. I take this to show that the combination of constructive and interactive modes is the set of cognitive processes that would work to produce the best learning.

Research shows that the constructive mode requires each learner to make a personal explanation (the self-explanation effect). We know that works. Then combining constructive and interactive modes to coordinate with another person’s explanation (the constructive controversy effect) challenges both to clarify, solidify and verify a joint explanation. We know that works too.

Instruction

So, designing activities that push students to the constructive mode in a way that also activates the interactive mode would have the best track record of producing deep learning. And that’s what we mean by “active learning.”

The implications of the ICAP model offer strong support to the value of group work. But a common problem that sometimes interferes with learning in groups is that one or two members dominate the discussion. If group work started with short quiet time for each member to construct their own idea about the question or topic, all the students would have something to contribute to the interaction. A single member would be less likely to do all the talking, especially if there is a structure on the interactions that gives each person a short time to present their response without interruption before everyone is done. This is the structure of the “constructive controversy” method mentioned earlier. At that point, groups working together offer the best learning opportunities—dynamic combinations of interactive and constructive. ❖

References

Chi, M. T. H. Chi, M., Adams, J., Bogusch, E., Bruchok, C., Kang, S., Lancaster, M., … Yaghnourian, D. (2018). Translating the ICAP theory of cognitive engagement into practice. Cognitive Science, 42, 1777–1832. Retrieved from https:// www.ncbi.nlm.nih.gov/pubmed/29954048

Chi, M. T. H., & Wylie, R. (2014). The ICAP framework: Linking cognitive engagement to active learning outcomes. Educational Psychologist, 49, 219–243. Retrieved from . https://www.tandfonline.com/doi/abs/10.1080/00461520.2014.965823

Hausmann, R. G. M.,  van de Sande, B., & VanLehn, K. (2008). Shall we explain? Augmenting learning from intelligent tutoring systems and peer collaboration. In B. P. Woolf, E. Aimeur, R. Nkambou, & S. Lajoie (Eds.), Intelligent tutoring systems (pp. 636–645). Amsterdam, The Netherlands: IOS.

CONTACT: 

Marilla Svinicki, Ph.D.

Email: msvinicki@utexas.edu

Professor Emeritus Educational Psychology,The University of Texas at Austin, One University Station D5800 Austin, TX 78712