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Data-Driven Learning Support

Data-Driven Learning Support

contact: Andreas Paepcke

Data-driven Learning Support

Students learning online leave data trails that we can explore to improve teaching. Yet exploring a billion footsteps requires compute algorithms that have only recently matured . The Data-Driven Learning Support project brings technologies such as machine learning and natural language processing to the task. We include in our studies MOOC learning, residential instruction, and international expert advice sites, such as Stack Exchange.

Publications:

  • Ankita Bihani and Andreas Paepcke. Faqtor: Automatic faq generation using online forums. In Proceedings of the 11th International Conference on Educational Data Mining, Buffalo, NY. USA, 2018.
  • Aashna Garg and Andreas Paepcke. Supporting the encouragement of forum participation. In Proceedings of the 10th International Conference on Educational Data Mining, Wuhan, China, 2017.
  • David Lang, Ben Domingue, Alex Kindel, and Andreas Paepcke. Making the grade: How learner engagement changes after passing a course. In Proceedings of the 10th International Conference on Educational Data Mining, Wuhan, China, 2017.
  • Andrew Lamb, Jose Hernandez, Jeffrey Ullman, and Andreas Paepcke. Portrait of an indexer—computing pointers into instructional videos. In Proceedings of the 9th International Conference on Educational Data Mining, Raleigh, NC. USA, 2016.
  • Akshay Agrawal, Jagadish Venkatraman, Shane Leonard, and Andreas Paepcke. Youedu: Addressing confusion in mooc discussion forums by recommending instructional video clips. In Proceedings of the 8th International Conference on Educational Data Mining, Madrid, Spain, 2015.