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Fingerprint Fingerprint is based on mining the text of the expert's scholarly documents to create an index of weighted terms, which defines the key subjects of each individual researcher.

  • 17 Similar Profiles
Students Engineering & Materials Science
Authoring Mathematics
Tracing Mathematics
Gaming Mathematics
Learning Environment Mathematics
student Social Sciences
Well-defined Mathematics
Model Mathematics

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Research Output 2009 2019

Affect sequences and learning in Betty's brain

Andres, J. M. A. L., Paquette, L., Ocumpaugh, J., Jiang, Y., Baker, R. S., Karumbaiah, S., Slater, S., Bosch, N., Munshi, A., Moore, A. & Biswas, G., Mar 4 2019, Proceedings of the 9th International Conference on Learning Analytics and Knowledge: Learning Analytics to Promote Inclusion and Success, LAK 2019. Association for Computing Machinery, p. 383-390 8 p. (ACM International Conference Proceeding Series).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Brain
Students
Learning systems
Education
Systems analysis

Comparing machine learning to knowledge engineering for student behavior modeling: a case study in gaming the system

Paquette, L. & Baker, R. S., Aug 18 2019, In : Interactive Learning Environments. 27, 5-6, p. 585-597 13 p.

Research output: Contribution to journalArticle

Knowledge engineering
Learning systems
Students
engineering
learning

A system-general model for the detection of gaming the system behavior in CTAT and LearnSphere

Paquette, L., Baker, R. S. & Moskal, M., Jan 1 2018, Artificial Intelligence in Education - 19th International Conference, AIED 2018, Proceedings. Luckin, R., Porayska-Pomsta, K., du Boulay, B., Mavrikis, M., Penstein Rosé, C., McLaren, B., Martinez-Maldonado, R. & Hoppe, H. U. (eds.). Springer-Verlag, p. 257-260 4 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 10948 LNAI).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Authoring Tools
Gaming
Detector
Students
Detectors

Detecting and Addressing Frustration in a Serious Game for Military Training

DeFalco, J. A., Rowe, J. P., Paquette, L., Georgoulas-Sherry, V., Brawner, K., Mott, B. W., Baker, R. S. & Lester, J. C., Jun 1 2018, In : International Journal of Artificial Intelligence in Education. 28, 2, p. 152-193 42 p.

Research output: Contribution to journalArticle

frustration
Military
Students
Detectors
student

Expert feature-engineering vs. Deep neural networks: Which is better for sensor-free affect detection?

Jiang, Y., Bosch, N., Baker, R. S., Paquette, L., Ocumpaugh, J., Andres, J. M. A. L., Moore, A. L. & Biswas, G., Jan 1 2018, Artificial Intelligence in Education: 19th International Conference, AIED 2018, London, UK, June 27–30, 2018, Proceedings, Part I. Penstein Rosé, C., Martínez-Maldonado, R., Hoppe, H. U., Luckin, R., Mavrikis, M., Porayska-Pomsta, K., McLaren, B. & du Boulay, B. (eds.). Springer-Verlag, p. 198-211 14 p. (Lecture Notes in Computer Science; vol. 10947).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Neural Networks
Engineering
Sensor
Sensors
Students