I’m reflecting on the question about how AI-supported sentiment analysis changes how decisions are made about curriculum, activities, assessments or other educational aspects in my organization. In the company I’m contracting for, as well as in the broader customer education community, no one is talking about sentiment analysis in an educational context (yet).
I did find one mention of an off-the-shelf tool that uses sentiment analysis. This is a case where I could see that people may already be using sentiment analysis without necessarily calling it that. The tool is SurveyMonkey. I see SurveyMonkey as already being a popular tool, but in the context of things like product feedback, employee engagement, and market research. For organizations that consider their curriculum, learning activities, and assessments products (as my current organization does), it’s not a far leap to see using a survey tool like this to get further insights into learners’ sentiment. We already use surveys to collect feedback on learning experiences. We usually have a small amount of data to work with, so the value of having some of that analysis automated by AI is limited. It would very much depend on asking the right kinds of open-ended questions in the survey itself. In this context, sentiment analysis would mostly benefit the Product Owner and Instructional Designer (as well as other stakeholders). This would be during the early testing for the purpose of knowing the most important ways to improve a learning experience. That would presumably benefit learners as well, as we work to make the most effective learning experiences. Why would I trust SurveyMonkey? For me it wouldn’t take much. A quick glance through their site leads me to believe they have done their due diligence in regards to privacy and compliance with existing regulations. For me personally, this would probably be enough, because the impact of decisions would be more about company success than anything with long-term consequences for learners. However, the cost of the tool would have to be justified for the organization. And as I mentioned earlier, that would only be true if we needed to analyze a large amount of data.
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AuthorMichele Wiedemer has worked in software as an "accidental instructional designer" for many years. She is currently completing the MS in Learning Technologies at The University of North Texas. This blog represents reflections on specific assignments in the coursework. Archives
February 2024
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