Teachable Machines anyone?

Colleagues, I am delighted to be piloting an early workshop in the next stage of the ARU/BU augmented reality work for STEM students.

This is at the ALDinHE National Conference, please do follow/ support us at #aldcon

Design, Create, Evaluate: can a ‘teachable machine’ help learners learn? Mike Hobbs and Elaine Brown, Anglia Ruskin University; Debbie Holley, Bournemouth University

Abstract

This workshop will explore the affordances of Google’s ‘Teachable Machine’ to illustrate how a simple technological tool can be used to engage students with their studies.

Drawing upon the evidence of three years of an action research study, our curriculum design for first year computing students has transformed their learning of the softer skills with an activity that engages these hard to reach STEM students. They work in small groups to create a demonstration of technology, which they research, design, and peer evaluate.

Underpinned by Vygotskyian principles of the more capable peer we use technology as the mediating factor to support students while they develop their artefacts. The ‘design create evaluate’ cycle scaffold’s the peer groups as they reflect on their choice of tool and their role within the team; offering a unique blend of peer-to-peer and ‘flipped classroom’ learning.

In their future careers students will increasingly encounter machine-learning systems, so it is appropriate to develop a deeper understanding to demystify this technology within a digital literacy context. The novelty of the application provides an interesting context for group work and by providing instant feedback helps to develop skills in design, problem solving, evaluation and critical analysis.

The workshop offers a ‘hands on’ practical experience of the framework for technology mediated learning that is applicable to any disciplinary context. The session will start with an overview of the current study and then participants will replicate the student experience by working in small groups to design, create, set criteria and peer review their applications before a final reflective discussion. Each group will need one laptop or similar between them to access the Google Teaching Machine website.

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