Abstract
This paper describes the design and implementation of automated techniques for grading students’ PowerPoint slides. Preparing PowerPoint slides for seminars, workshops, and conferences is one of the crucial activity of graduate and undergraduate students. Educational institutes use rubrics to assess the PowerPoint slides’ quality on different grounds, such as the use of diagrams, text highlighting techniques, and animations. The proposed system describes a method and dataset designed to automate the task of grading students’ PowerPoint slides. The system aims to evaluate students’ knowledge about various functionalities provided by presentation software. Multiple machine learning techniques are used to grade presentations. Decision Tree classifiers gives 100% accuracy while predicting grade of PowerPoint presentation.
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Borade, J.G., Netak, L.D. (2022). Machine Learning Techniques for Grading of PowerPoint Slides. In: Kim, JH., Singh, M., Khan, J., Tiwary, U.S., Sur, M., Singh, D. (eds) Intelligent Human Computer Interaction. IHCI 2021. Lecture Notes in Computer Science, vol 13184. Springer, Cham. https://doi.org/10.1007/978-3-030-98404-5_1
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