Why Educational Technology needs the Learning Sciences

I very much enjoyed myself at the EdTech Forum organised by Founders Factory and at Bett. On both occasions I spoke about the Learning Sciences and we had some great discussions. BUT what are the Learning Sciences and why are they so important for EdTech?

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The Learning Sciences is an interdisciplinary research field that aims to increase our understanding of the learning process and to engage in the design and implementation of learning innovations, such as those enabled by technology. The disciplines encompassed include cognitive science, educational psychology, computer science, anthropology, sociology, information sciences, neurosciences, education, design studies, and instructional design.

This increased understanding about how people learn ought to  underpin the design of all EdTech, but sadly it does not. A couple of examples might help here.

The Self-Explanation Effect

Micheline Chi now at Arizona State University has done some fascinating work on what she calls: The Self-explanation effect and cognitive engagement. Simply put, students learn better when they explain to themselves the material they are working on. The self-explanation effect has been studied across age groups, subjects, and educational contexts. Evidence shows that a learner explaining an idea to themselves will learn more, because the process of self-explaining is a constructive learning activity.

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(Table from http://serc.carleton.edu/details/images/26492.html)

Constructive learning is a form of active learning. Evidence suggest that it is useful to consider 4 types of engagement:

  • Passive engagement: e.g. hearing an explanation
  • Active engagement: e.g. summarising an explanation
  • Constructive engagement: e.g. explaining to oneself
  • Interactive engagement: e.g. explaining to another

Studies have shown that students gain the most knowledge and improve their understanding during interactive engagement, followed by constructive engagement and active engagement, the least learning gains were achieved after passive engagement.

For EdTech this is relevant and has for example been used to inform the design of prompts and scaffolds within EdTech applications to encourage self-explanation in learners.

The Acts of Learning

The self-explanation effect is a very specific example of ways that the Learning Sciences are producing findings that are relevant for EdTech developers and users. A more general example can be found in that of Learning Acts: a product of the CAPITAL project. The table below illustrates the 19 Learning Acts that have been observed to occur when learning occurs with digital media, these are grouped into four meta-categories.

For example, a standard video would promote and support Exposition as a Learning Act. This Act is characterised as a private interaction with an author or speaker who is presenting a narrative account of knowledge to a learner. Knowledge is thereby “exposed”. This practice is well suited to situations where expertise can be transmitted in structured narrative form. The success of this form of learning depends on the depth of the private interaction elicited from the (otherwise passive) learner. Thus technology may support such depth of interaction by making material vivid or representationally rich. Interactive video is likely to also promote Learning Acts such as Browsing, Ludic, Simulation and Problem Focussed. The effectiveness with which the range of different Learning Acts is supported through the design of interactive EdTech will impact upon its Learning effectiveness.

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For more information about the self-explanation effect see for example, http://chilab.asu.edu/papers/Wylie_Chi_SelfExplanation.pdf

For more information about the Learning Acts see – Manches, A., Phillips, B., Crook, C., Chowcat, I., & Sharples, M. (2010). CAPITAL-Curriculum and Pedagogy in Technology Assisted Learning. http://www.icde.org/filestore/Resources/Reports/CAPITALfinalreport.pdf

 

 

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