Supercharging your data analysis with AI
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Surveys are a great way to gain insights to help answer questions. But to get to making a decision, we first need to analyse the data. At StudentPulse, we're taking a significant leap forward with our latest AI innovations, that will help you level up your data analysis process, and make understanding and addressing student needs easier than ever.
In the past year, an invaluable resource has been at our fingertips – thousands of authentic student comments, rich in insights and experiences. Educators, have been playing a pivotal role in this process by actively engaging with our platform. They’ve been 'liking' and ‘disliking’ students’ comments, and this way identifying the most valuable comments and comments that seemed rushed.
This interaction has not only captured genuine student sentiments but has also been crucial in training our AI model. By analysing these likes and the associated comments, we've been able to refine our AI's understanding of what constitutes impactful student feedback. This process exemplifies a perfect synergy of human expertise and machine learning, where each '(dis)like' contributes to the AI's evolving intelligence.
We are thrilled to announce the imminent release of a pivotal feature in our suite of AI tools - a multi-lingual, natural language processing model that marks a significant advance in AI-driven education technology. Drawing from a diverse linguistic pool, including languages like Spanish, Finnish, Norwegian, and English, our model is designed to do more than just understand words; it comprehends context and quality across ALL languages.
This deep learning-driven approach allows us to assign a predictive score to each student comment, gauging its relevance and actionability based on the extensive user interactions. It’s important to keep in mind that the confidence score refers to the comment’s relevance probability. Therefore it does not guarantee the comment to be more relevant, but rather to be more likely to be relevant. As this feature rolls out, we continue to encourage our users to interact with the platform by 'liking' comments they find particularly relevant and actionable, whilst ‘disliking’ those they don’t. Each interaction not only refines the model's accuracy but also enhances its ability to identify and prioritise the most impactful student feedback, regardless of language. This feature represents a significant stride in making our platform a truly inclusive, global educational tool.
With StudentPulse's AI, the future of understanding and enhancing student well-being is clearer than ever. We're not just analyzing feedback; we're creating pathways for real change, ensuring every student's voice leads to meaningful action.
