Katherine Smith, Jessica Johnson, Gul Ayaz, Charis Horner

Proceedings of the 13th International Conference on Society and Information Technologies: ICSIT 2022, pp. 114-120 (2022); https://doi.org/10.54808/ICSIT2022.01.114

Katherine Smith
Virginia Modeling, Analysis, and Simulation Center, Old Dominion University, Suffolk, Virginia, United States

Jessica Johnson
Virginia Modeling, Analysis, and Simulation Center, Old Dominion University, Suffolk, Virginia, United States

Gul Ayaz
Virginia Modeling, Analysis, and Simulation Center, Old Dominion University, Suffolk, Virginia, United States

Charis Horner
Design Interactive, Inc., Orlando, Florida, United States

Cite this paper as:
Smith, K., Johnson, J., Ayaz, G., Horner, C. (2022). Phased Framework for Automated Educational Content Curation. In N. Callaos, S. Lunsford, B. Sánchez, A. Tremante (Eds.), Proceedings of the 13th International Conference on Society and Information Technologies: ICSIT 2022, pp. 114-120. International Institute of Informatics and Cybernetics. https://doi.org/10.54808/ICSIT2022.01.114

This paper applies modern, data-driven techniques to the traditionally manual, time consuming process of educational content curation. Specifically, educational content produced through a peer-to-peer knowledge sharing process is considered. After an overall introduction, an overview of previous work in the application of machine learning to education is provided. Then, a three-phase framework is developed to support implementation of an educational content curation process designed to inspire and enable learning. This process involves evaluation of individual content items, situation of content items in a repository of existing content, and correlation of content items to a learner and their needs. An initial example implementation of this framework is conceptualized. Finally, directions for future work are described.