Students write candid answers to six questions about the institute’s academic rigour, newly launched online portal and facilities.
Traditional methods of analysing open-ended responses suffer from multiple human biases and are intensive in terms of effort as well as time. Knowing this, they decided to outsource this project to ParallelDots. The goal was to understand key themes in student feedback consistently and without bias. Ideally, they wanted to find a solution that they could use continuously, to measure the effect of actions taken over time. ParallelDots employed their in-house tools to perform these tasks. Their standard text classification product is SmartReader.
Our team built a user-friendly and efficient SaaS solution to analyze students’ responses. Our strategy involved identifying key themes of concern that emerge from their voice and discovering how the institute is faring in these areas. We wanted to understand the general sentiment of the students and pinpoint areas for improvement.
By leveraging responses to open-ended comment questions together with
AI-based predicted satisfaction
from student comment data, the ParallelDots analysis provides much
deeper and more
actionable insights than are
obtainable with conventional analytics. In contrast to typical tracking
which are limited to just measuring
satisfaction levels, ParallelDots yields not only intelligence about the
factors driving satisfaction (the
“Why's”), but also quantifies the extent to which each factor actually
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