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Author Archives: galst64p

Finding multimedia resources to support learning

As teachers, having video and images that help convey clinical material is invaluable. It’s not possible for every student to see every procedure, or to provide one-on-one tutorials every time someone needs a refresher. There are multiple sources of these resources online, but the most easily found (e.g., YouTube or Google image search) sometimes have terms of use placed around them that limit their use, or worse have been placed their without the copyright holder’s permission. When dealing with video and images that show patients, we must be particularly careful to make sure that the appropriate consent has been given before using that video. Continue reading

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Design for eLearning

Our good friend Gala Hesson developed some excellent resources on design for elearning when she worked for HEDC, which are sadly no longer available online. However, she has graciously allowed us to share the handout from her Communication Design for eLearning workshop. If you’re wondering about some good principles for elearning design, this handout is a great place to get an overview that can shape your further investigation.

The handout draws on the work of a number of researchers, particularly Clark and Mayer’s text eLearning and the Science of Instruction. In particular, it explores the principles of

1: multimedia
2: contiguity
3: modality
4: redundancy
5: coherence
6: personalisation

There are some good, clear illustrations of these principles in this handout, and advice on design aspects for your eLearning projects. Take a look! e-learning_handout

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Learning Analytics

Technology Enhanced Learning. eLearning. Educational Technology – this is a field that is so filled with buzzwords we have trouble deciding what to call ourselves.

One emerging field that some might consider a buzzword is Learning Analytics. Simply put, learning analytics is the practice of analysing data from student interactions with online learning material in order to infer information about student learning. A simple example might be looking at the number of times students click on a link to a particular learning activity as a measure of student engagement. Another example might be looking at proportion of students in a cohort who engage in a series of weekly activities – a decrease over time might be inferred to be a decrease in engagement with learning. Continue reading

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