Learning, Motivation, and Theory.

Based on the three types of learning that were discussed in the reading on behaviorism, cognitivism and constructivism (Ertmer & Newby, 2013), it is clear how each of these different learning theories can be specifically beneficial depending on the situation and the intended learning outcomes. There is overlap in the three theories, and perhaps the “best” form of instructional design consists of extracting different aspects from each theory. However, based on other students’ blog posts, it seems that each individual typically has one theory they personally favour for overall instruction. When receiving information in a school based context, I find the behaviorist theory to be most successful in allowing me to retain information and understand the subject. A behaviorist perspective aims for learners to react to conditions, and “no attempt is made to determine the structure of a student’s knowledge nor to assess which mental processes it is necessary for them to use” (Ertmer & Newby, 2013). I would choose to use this instruction style because it allows for different interpretations of knowledge, as it focuses less on the mental process, as opposed to cognitivism. To me, the behaviorist design allows for learners to get to the same answer, through their own unique process. 

One of my best learning experiences occurred in a psychology class last semester. To assess students on tests, we were given prompts and could write about what we know on this subject, and are encouraged to incorporate information learned from other classes, personal experience, or various other sources. I relate this to behavioral instruction, as I learned and expressed my knowledge through reacting to a prompt. I finished this class feeling like I had learnt and understood much more than I did in my other classes that use multiple choice, or more standardized testing for evaluation. I think this is because my motivation was coming from learning, rather than memorizing information for a test (“Why is learning hard?”, 2023).

This week’s content also allowed me to reflect on how people do not often talk about how learning itself is hard. Although you may hear about specific skills or tasks being difficult, the process of learning in general can be difficult, even when the information or skills seem simple (“Why is learning hard?”, 2023). The backwards brain bicycle video allowed me to reflect on the work and repetition it takes to obtain knowledge. I interpreted this video as a demonstration of using your knowledge, or you will lose it (“The Backwards Brain Bicycle”, 2015). Finally, I enjoyed how a bicycle was used in this video to demonstrate how difficult a task can be when a person tries to do it backwards, because typically, biking is viewed as a skill that you learn and never forget. You hear “It’s like riding a bike”!, as if it is something you can pick up after years of not doing it and still be able to, so it was fascinating to see a different perspective demonstrated through this video.

References

YouTube. (2015). The Backwards Brain Bicycle – Smarter Every Day 133. YouTube. Retrieved January 27, 2023, from https://www.youtube.com/watch?v=MFzDaBzBlL0&t=472s. 

Ertmer, P. A., & Newby, T. J. (2013). Behaviorism, cognitivism, constructivism: Comparing critical features from an instructional design perspective. Performance Improvement Quarterly, 26(2), 43–71. https://doi.org/10.1002/piq.21143 

Why is learning hard? EDCI 335. (n.d.). Retrieved January 25, 2023, from https://edtechuvic.ca/edci335/why-is-learning-hard/

1 Comment

  1. Anastassiya

    Thank you for sharing your ideas on learning theories in relation to your best learning experience. Interestingly, you mentioned that some prefer one theory over the other. In learning design, we should always think about the learning outcomes we want our learners to reach and the nature of our subject matter (e.g., do we teach facts, concepts, procedures, processes, etc.), as these factors determine the most effective strategies we may want to use in each particular context.

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