A Smattering of Plenary Lessons from #GlobalSummit18 #onlinelearning2018 #I4PL2018

The opening session of Online Learning 2018 covered a variety of topics. Here are a few take-aways mixed with my refelctions.

When selecting a vendor there are a lot of things to consider such as who will change, what is the role, and who will interact with them.Selecting the right vendor is very important.

A passion for learning is an important driver of our actions that needs to come from the top and go throughout the organization. It is important that we, particularly in higher education, remember to keep that passion alive.

Free-Photos / Pixabay

Students like short, relevant, flexible content – and like to learn from YouTube. This statement is so true. As several sessions said yesterday – learning needs to be delivered in manageable chunks that students can explore. No one is going to watch an hour long lecture capture – well, maybe someone but not very many people will.

Great closing quote shared by @MikeMooreD2L from #D2L. "In over 300 years of economic history, the principal and the most enduring mechanism for distribution of wealth and reduction of inequality is the diffusion of skills and knowledge." #ThomasPiketty. #GlobalSummit18 pic.twitter.com/i6bSeVGW1a

— Dr. Rick Kralevich (@rickkralevich) October 17, 2018

Dynamic testing helps students and educators know where they are in their learning. Yes, that is true. It is very hard to build dynamic testing. We need to do that to replace things like the HESSI and make learning more open and freely available.

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Learning analytics involves measuring, collecting and analysis of data to make the learning environment better. the ability of the analytics to make predictions is getting better and better. I find this interesting and question how this technology can be use for good or evil. I was at a presentation about data privacy that outlined how some predictions, depending how they are used, can actually impede student success. Yes, they can be helpful and we need to understand them but we also need to be careful not to use them to create barriers to learning.

Artificial intelligence is evolving and being used in a variety of interesting ways. Things like automatic captioning, read text, and much more can enhance student learning. It can even be used to assess student work. Reflecting on this is a topic for a different blog post. Click here for a post about Jill Watson.

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Blockchain (not bitcoin) for higher education can be used for digital badges. It enables the collection of time-stamped portfolio development. Bitcoin is being used to pay tuition or get donations to universities. Blockchain can be used to connect students and tutors. There is an entire university – Wolf U – being build around blockchain.

Technology is not without it’s challenges. Reflection is needed in terms of accountability for predictions, how AI is used and privacy. Where is the evidence that learning has improved? That all learners can take advantage of the learning?

We can now begin to measure results of what is happening in our classes. Measurement can lead to improvement. I think that only works if you use the data appropriately. How do we use the data? The panel agreed that data needs to be used well. We need research about learning efficiently, which takes time. Realistic expectations about the output is also needed. Blended learning is supported by research.

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What is the return on investment (ROI)? What is the cost if you don’t do it? Someone on the panel suggests that you have to do it – invest in technology. While I agree that there is a cost if you don’t do it I believe we need to spend wisely. The cost is in the transition. Making content that improves education takes time and money but if it results in more effective education the return can be incredible. What does the ROI look like for your organization? It will be organizational specific. Retention, engagement, are some key metrics that can be measured and examined. Basically – to me – it sounds like the ROI is unknown but worth investigating.

Grateful for the insightful question re: risk of colonialism posed by predictive analytics. Is our strategy to simply learn from our mistakes as we go? #globalsummit18

— Jessica O'Reilly (@Cambrian_Jess) October 17, 2018

There is a danger of a new colonialism from the use of data. WOW – what a statement from the audience. There is a danger in predictive analytics when considering how minority groups of students learn. The panel says we need research and hopefully can learn how to use the data well. Artificial intelligence is a growth area. We need to keep data contextualized. There is a lot of data – too much. The long game is to identify the type of learners not just the type of content that works.