For my upcoming presentation at Learning Solutions 2016, I am going to be exploring how data is altering the way that content is being developed for the higher education content market, and examining how this generally relates to content generation for any learning population. In this article, I want to give a little bit of background information on the approach that I am using and some of the ways that I am applying what I am learning to my projects.
As a science educator and STEM author, I have always had an interest in building better, and more relevant, content for my students. I have conducted countless workshops, webinars and seminars for instructors at community colleges, universities and for-profit educational organizations.
The problem of course is that instructors do not use textbooks… they assign them.
That doesn’t mean that I haven’t tried to get student input as well. Students in my classes frequently served as test subjects for a variety of new technologies and approaches to teaching. Like all students today, they have been surveyed, quizzed and queried as to their preparedness for class, engagement with the content, study habits – you get the idea.
The problem, of course, is that students don’t know what they don’t know. And if you are a content developer, that presents a host of problems.
Over time, I have explored a number of ed tech platforms, I have realized that by analyzing data derived from adaptive learning technologies, it is possible to get a better understanding of how students are engaging with content.
The video below examines how I first started using the data from an adaptive learning platform (McGraw-Hill’s SmartBook system) . This data, which is displayed as a heat map, was initially very useful in identifying which areas of the text were in need of revision from the user’s perspective.
Over time, I recognized that the data not only had the ability to help with revising content, but provided a insight into what learning resources needed to be developed. Specifically, I was interested in building microlearning resources that targeted the specific knowledge deficiencies.
The video below, developed for the 2015 DevLearn Hyperdrive competition, explains this process.
Although this presentation won that competition, I recognized that the heat map data was just a step in the process. Once you have this data, and start to develop microlearning resources, you need to continue the process of data analytics. We have been posting a number of our microlearning resources on our Ricochet Science YouTube Channel, and now we are beginning to analyze how learners are interacting with this content.
In this session I will describing some of our efforts to refine the development of microlearning resources using analytics from sites, such as YouTube.
The conference information is below – and I hope to see you there.
Conference Information:
Session Time: Wednesday March 16th at 230pm
Session Abstract:
Students don’t know what they don’t know. This concept applies not only to academics, but to learners in any environment. This means that educators and developers are constantly developing resources that focus on what they anticipate the learner needs. Adaptive learning technologies are now providing the data that allows us to understand specific knowledge deficiencies. This is not only changing the learning environment, but also the process by which content is generated.
In this session, using data obtained from a large-lecture university science education class, you will be shown how an understanding of knowledge deficiencies is being used by the individual to personalize the learning experience and in the classroom to flip the learning environment. You will learn how the analysis of this data is leading to revisions of content within the textbook, and allowing for the development of continuously updated information. Ultimately, you will experience how data from a single learning experience may be utilized across the entire learning ecosystem.
In this session, you will learn:
- How user data may be used to revise content
- How user data may be used to personalize learning
- How user data may be used to generating micro-learning resources
- How adaptive learning platforms provide data on knowledge deficiencies
Audience:
Novice to advanced designers, developers, project managers, managers, and directors.
Technology discussed in this session:
N/A
More information on the Learning Solutions 2016 Conference:
