Janice Gobert, Ph.D., Professor of Educational Psychology develops technology for learning that makes use of AI, including data mining and eye tracking. With seven patents for her technology, her cutting edge work focuses on personalized learning of science and assessment to replace traditional tests, which are unable to assess students’ competencies at authentic science tasks. In essence, the technology makes use of students performing a complex task and tracking metrics on how well they perform science as opposed to reciting rote facts on multiple choice tests. In working on virtual experiments, students can be evaluated in what is called real-time performance assessment. The results and metrics obtained from this technology is then compared to what students write and used to provide each student with the personalized help they need to succeed in the science classroom. By using AI-based, big data techniques, Gobert is able to obtain personalized learning metrics to learn exactly what and how students are learning, which can then trigger the system to provide personalized help via a digital agent named Rex, as well as alert the teacher in real-time so that they can offer support on the spot. Gobert is a strong believer in tailoring content to the student so as to maximize understanding, especially if a student, and one who is underrepresented, is falling behind. This technology is currently in 50 states, with some being research sites and others trial sites.
Gobert studied psychology during her undergraduate years with a deep focus on experimental and cognitive psychology. Propelled by her interest in learning how people understand visually rich diagrams, she went on to pursue her master’s and Doctorate in Cognitive Science. Gobert believes that education has the potential to be a great equalizer and aims to further her goal of deeply investing in future citizens. She currently teaches Psychology of Learning and Inquiry II and constantly looks to bring her students to the cutting edge of what technology can offer them for their research and future career goals. Gobert considers teachers’ love and implementation of her technology to be one of her most significant professional achievements.
• B.A. in Psychology, Laurentian University (1985)
• M.A. in Cognitive Science, McGill University (1989)
• Ph.D. in Cognitive Science, University of Toronto (1994)
• American Association for Adult and Continuing Education
• American Educational Research Association
• Cognitive Science Society
• International Society for the Learning Sciences
• National Association for research in Science Teaching
• Educational Data Mining Society
• AI in Education Society
Expertise & Research Interest
Intelligent Tutoring Systems for Science
Performance Assessment for Science
Inq-Blotter: Designing Supports for Teachers’ Real Time Instruction (NSF-IIS- 1902647). Gobert, J. (Principal Investigator), Awarded July 17, 2019 from the National Science Foundation, $299,999.00
Inq-Blotter – A Real Time Alerting Tool to Transform Teachers’ Assessment of Science Inquiry Practices, (NSF-IIS-1629045). Gobert, J. (Principal Investigator), M. Sao Pedro (Co-Principal Investigator). Awarded August 2016 from the National Science Foundation, $550,000.00
Testing the Effects of Real-time Scaffolding of Science Inquiry Driven by Automated Performance Assessment, (NSF-DRL-1252477), Gobert, J., Principal Investigator, Awarded September 2013 from the National Science Foundation, $1,499,346.00
The Development of an Intelligent Pedagogical Agent for Physical Science Inquiry Driven by Educational Data Mining. Gobert, J. & Baker, R. Proposal (R305A120778) Awarded May, 2012 by the U.S. Dept. of Education, $1,499,588.00
Empirical Research: Emerging Research: Using Automated Detectors to Examine the Relationships Between Learner Attributes and Behaviors During Inquiry in Science (NSF-DRL# 1008649). Janice Gobert, Principal Investigator, Ryan Baker, Co-Principal Investigator. Awarded July 1, 2010 from the National Science Foundation; $986,111.00
Recent & Selected Publications
Gobert, J. D., Sao Pedro, M.A., Betts, C.G. (in press). An AI-Based Teacher Dashboard to Support Students’ Inquiry: Design Principles, Features, and Technological Specifications. To appear in N. Lederman, D. Zeidler, & J. Lederman (Eds). Handbook of Research on Science Education, Volume III, ELSEVIER.
Gobert, J., Sao Pedro, M., Li, H., & Lott, C. & the Inq-ITS Development Team (in press). Intelligent Tutoring Systems: A History and an example of an ITS for science Inquiry Science Inquiry ITS. To appear in Tierney, R., Rizvi, F., Ercikan, K., and Smith, G. (Eds.), International Encyclopaedia of Education (4th VOLUME), ELSEVIER.
Dickler, R., Gobert, J., & Sao Pedro, M. (2021). Using Innovative Methods to Explore the Potential of an Alerting Dashboard for Science Inquiry. Journal of Learning Analytics, 8(2), 105-122. https://doi.org/10.18608/jla.2021.7153
Nicolay, B., Krieger, F., Stadler, M., Gobert, J., & Grieff, S. (2021). Lost in transition – Learning analytics on the transfer from knowledge acquisition to knowledge application in complex problem solving. Computers in Human Behavior, 115.
Mislevy, R., Yan, D., Gobert, J., & Sao Pedro, M. (2020). Automated Scoring with Intelligent Tutoring Systems. In Yan, D., Rupp, A. & Foltz, P. (Eds.), Handbook of Automated Scoring: Theory into Practice. Chapman and Hall, London, UK.
Luan, Hui, Geczy Peter, Lai Hollis, Gobert, Janice, Yang Stephen J. H., Ogata Hiroaki, Baltes, Jacky, Guerra Rodrigo, Li Ping, Tsai Chin-Chung. (2020). Challenges and Future Directions of Big Data and Artificial Intelligence in Education. Frontiers in Psychology, 11, 1-11.
Gobert, J., Moussavi, R., Li, H., Sao Pedro, M., & Dickler, R. (2018). Real-time scaffolding of students’ online data interpretation during inquiry with inq-its using educational data mining. Invited book chapter in Abul K.M. Azad, Michael Auer, Arthur Edwards, and Ton de Jong (Eds), Cyber-Physical Laboratories in Engineering and Science Education. Springer.
Li, H., Graesser, A. C., & Gobert, J. (2017). 具身在人工智能导师系统中隐身何处？[Where is embodiment hidden in the intelligent tutoring system?]. 华南师范大学学报（社会科学版）[Journal of South China Normal University (Social Science Edition)], 第二期, 79–91.
Gobert, J.D. & Sao Pedro, M. (2017). Inq-ITS: Design decisions used for an inquiry intelligent system that both assesses and scaffolds students as they learn. In Rupp, A. A., & Leighton, J. (Co-Eds). Handbook of cognition and assessment. New York: Wiley/Blackwell.
Gobert, J.D., Kim, Y.J, Sao Pedro, M.A., Kennedy, M., & Betts, C.G. (2015). Using educational data mining to assess students’ skills at designing and conducting experiments within a complex systems microworld. Thinking Skills and Creativity, 18, 81-90. doi:10.1016/j.tsc.2015.04.008
Kim, B., Pathak, S., Jacobson, M., Zhang, B., & Gobert, J.D. (2015). Cycles of Exploration, Reflection, and Consolidation in Model-Based Learning of Genetics. Journal of Science Education and Technology. Journal of Science Education and Technology, 24(6), 789-802. DOI 10.1007/s10956-015-9564-6
Gobert, J.D., Baker, R., & Wixon, M. (2015). Operationalizing and Detecting Disengagement Within On-Line Science Microworlds. Educational Psychologist, 50(1), 43-57. DOI:10.1080/00461520.2014.999919
Honors & Awards
Gobert, J.D. (2022, August 4). Panelist for the White House Office of Science and Technology Policy and the U.S. Department of Education to advise on the future of Artificial Intelligence in Education.
Gobert, J.D. (2022). Expert panelist, AI and the Future of Skills, OECD.
Gobert, J.D. 2021 Nominee, Grawemeyer Award in Education. http://grawemeyer.org/education/ (competition postponed due to COVID-19)
Honorable Mention, AERA Cognition and Assessment SIG, 2015
James Chen Best Student Paper Award, Michael Sao Pedro (advisee), 20th Conference on User Modeling, Adaptation, and Personalization, 2012
Best Student Paper Award, Michael Sao Pedro (advisee), AERA SIG on Advanced Learning Technologies, 2012
Best Interactive Event, 10th International Conference on Intelligent Tutoring Systems, 2010
Young Researchers’ Award, Michael Sao Pedro (advisee), 10th International Conference on Intelligent Tutoring Systems, 2010
Research Development Award, Western Michigan University, 1997
Dean’s Appreciation Award, Western Michigan University, 1996
Developing & Testing Real-time Assessment & Scaffolding for Mathematics Use & Modeling During Science Inquiry (R305A210432). Gobert, J. (Principal Investigator) & Sao Pedro, M. (Co- Investigator). Awarded May, 2021 by the U.S. Dept. of Education, $1,905,787.00