Selected Publications Behind Inq-ITS Performance Based Assessment

Gobert, J., Moussavi, R., Li, H., Sao Pedro, M., & Dickler, R. (under revision).

Scaffolding students’ on-line data interpretation during inquiry withInq-ITS. Invited book chapter for Cyber-Physical Laboratories in Engineering and Science Education, Abul K.M. Azad, Michael Auer, Arthur Edwards, and Ton de Jong (Eds). Springer.


Gobert, J.D., & Sao Pedro, M.A. (2017). Digital Assessment Environments for Scientific Inquiry Practices. In Rupp, A.A. & Leighton, J.P (Eds.) The Wiley Handbook of Cognition and Assessment: Frameworks, Methodologies, and Applications​​​​​​​. West Sussex, UK. 508-534.


Li, H., Gobert, J., & Dickler, R. (2017).

Dusting Off the Messy Middle: Assessing Students’ Inquiry Skills Through Doing and Writing. In Proceedings of the 18th International Conference on Artificial Intelligence in Education. Wuhan, China (pp. 175-187).


Li, H., Gobert, J., & Dickler, R. (2017).

Automated Assessment for Scientific Explanations in On-line Science Inquiry. In Proceedings of the 10th International Conference on Educational Data Mining. Wuhan, China (pp. 214-219).


Li, H., Graesser, A. C., & Gobert, J. (2016).

Where is embodiment hidden in the intelligent tutoring system? Journal of South China Normal University.


Moussavi, R., Gobert, J., and Sao Pedro, M. (2016).

The Effect of Scaffolding on the Immediate Transfer of Students' Data Interpretation Skills within Science Topics. In Proceedings of the 12th International Conference of the Learning Sciences. Singapore. (pp. 1002-1006)


Moussavi, R. and Gobert, J. (2016).

Iterative Design, Development, and Evaluation of Scaffolds for Data Interpretation Practices during Inquiry. Presented as part of the Doctoral Consortium. In Proceedings of the 12th International Conference of the Learning Sciences. Singapore. (p. 1404)


Gobert, J.D., Kim, Y.J, Sao Pedro, M.A.,Kennedy, M., and 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, 1-10. doi:10.1016/j.tsc.2015.04.008


Gobert, J. D., Baker, R. S., and Wixon, M. (2015).
Operationalizing and Detecting Disengagement During On-Line Science Inquiry.
In Educational Psychologist, 50:1, 43-57.


Sao Pedro, M., Gobert, J., Toto, E., & Paquette, L. (April, 2015).

Assessing Transfer of Students’ Data Analysis Skills across Physical Science Simulations. Paper presented as part of Bejar, I. et al.’s symposium on The State of the Art in Automated Scoring of Science Inquiry Tasks at the Annual Meeting of the American Education Research Association. Chicago, IL.


Moussavi, R., Kennedy, M., Sao Pedro, M.A., Gobert, J.D. (April, 2015).

​​​​​​​Evaluating a Scaffolding Design to Automatically Support Students’ Data Interpretation within a Simulation-Based Inquiry Environment. Presented at the Annual Meeting of the American Educational Research Association, April 2015, Chicago, IL


Sao Pedro, M., Jiang, Y., Paquette, L., Baker, R.S. & Gobert, J. (2014).

​​​​​​​Identifying Transfer of Inquiry Skills across Physical Science Simulations using Educational Data Mining. In Proceedings of the 11th International Conference of the Learning Sciences. Boulder, CO (pp. 222-229).


Sao Pedro, M.A., Gobert, J.D., & Betts, C.G. (2014).

​​​​​​​Towards Scalable Assessment of Performance-Based Skills: Generalizing a Detector of Systematic Science Inquiry to a Simulation with a Complex Structure. In Proceedings of the 12th International Conference on Intelligent Tutoring Systems. Honolulu, HI (pp. 591-600).


Paquette, L., Baker, R.S., Sao Pedro, M.A., Gobert, J.D., Rossi, L., Nakama, A., Kauffman-Rogoff, Z. (2014). 
Sensor-Free Affect Detection for a Simulation-Based Science Inquiry Learning Environment. In Proceedings of the 12th International Conference on Intelligent Tutoring Systems. Honolulu, HI (pp. 1-10).


Sao Pedro, M.A., Gobert, J.D., & Baker, R.S. (2014). 

Impacts of Automatic Scaffolding on Students’ Acquisition of Data Collection Inquiry Skills. Paper presented at the Annual Meeting of the American Education Research Association. Philadelphia, PA.


Gobert, J., Sao Pedro, M., & Betts, C. (April, 2014).

Using Educational Data Mining to Assess Students’ Experimentation Skills During Inquiry Within Complex Systems. Poster presented at The Annual Meeting of the American Educational Research Association, Philadelphia, PA, April, 2014.


Gobert, J. D., Sao Pedro, M., Raziuddin, J., and Baker, R. S. (2013).
From log files to assessment metrics: Measuring students' science inquiry skills using Educational Data Mining.
In Journal of the Learning Sciences, 22(4), 521-563.


Sao Pedro, M.A., Baker, R.S.J.d., Gobert, J., Montalvo, and O. Nakama, A. (2013). 

​​​​​​​Leveraging Machine-Learned Detectors of Systematic Inquiry Behavior to Estimate and Predict Transfer of Inquiry Skill. User Modeling and User-Adapted Interaction, 23, 1-39.


Sao Pedro, M., Baker, R., & Gobert, J. (2013).

Incorporating Scaffolding and Tutor Context into Bayesian Knowledge Tracing to Predict Inquiry Skill Acquisition. In S.K. D'Mello, R.A. Calvo, & A. Olney (Eds.) Proceedings of the 6th International Conference on Educational Data Mining, (pp. 185-192). Memphis, TN.


Gobert, J., Sao Pedro, M., Raziuddin, J., & Baker, R. (2013).

Developing and Validating EDM (Educational Data Mining)-Based Assessment Measures for Measuring Science Inquiry Skill Acquisition and Transfer Across Science Topics. Paper presented at The Annual Meeting of the American Educational Research Association. San Francisco, CA.


Sao Pedro, M., Baker, R., & Gobert, J. (2013).

What Different Kinds of Stratification Can Reveal about the Generalizability of Data-Mined Skill Assessment Models. In Proceedings of the 3rd Conference on Learning Analytics and Knowledge. Leuven, Belgium.


Gobert, J., Toto, E., Brigham, M., & Sao Pedro, M. (2013).

​​​​​​​Searching for Predictors of Learning Outcomes in Non Abstract Eye Movement Logs. In H.C. Lane, K. Yacef, J. Mostow, & P. Pavlik (Eds.) Proceedings of the 16th International Conference on Artificial Intelligence in Education, (pp. 799-802). Memphis, TN.


Gobert, J., Sao Pedro, M., Baker, R.S., Toto, E., and Montalvo, O. (2012). 
Leveraging Educational Data Mining for real time performance assessment of scientific inquiry skills within microworlds, 
Journal of Educational Data Mining, Article 15, Volume 4, 153-185.


Sao Pedro, M., Baker, R., & Gobert, J. (2012).

Improving Construct Validity Yields Better Models of Systematic Inquiry, Even with Less Information. In Proceedings of the 20th Conference on User Modeling, Adaptation, and Personalization (UMAP 2012). Montreal, QC, Canada (pp. 249-260). James Chen Best Student Paper Award


Sao Pedro, M., Gobert, J., & Baker, R. (2012, April 15).

​​​​​​​Assessing the Learning and Transfer of Data Collection Inquiry Skills Using Educational Data Mining on Students' Log Files. Paper presented at The Annual Meeting of the American Educational Research Association. Vancouver, BC, CA: Retrieved April 15, 2012, from the AERA Online Paper Repository. Best Student Paper Award - AERA SIG Advanced Technologies for Learning/Learning Sciences


Gobert, J., Raziuddin, J., and Sao Pedro, M. (2011). 
The Influence of Learner Characteristics on Conducting Scientific Inquiry Within Microworlds. 
To appear in L. Carlson, C. Hoelscher, & T. Shipley (Eds.), Proceedings of the 33rd Annual Conference of the Cognitive Science Society. Austin, TX: Cognitive Science Society.


Sao Pedro, M., Gobert, J., and Sebuwufu, P. (2011, April 10). 
The Effects of Quality Self-Explanations on Robust Understanding of the Control of Variables Strategy. 
Paper presented at The Annual Meeting of the American Educational Research Association. New Orleans, LA: Retrieved April 18, 2011, from the AERA Online Paper Repository.


Gobert, J., Sao Pedro, M., Toto, E., Montalvo, O., and Baker, R. (2011).
Science ASSISTments: Assessing and scaffolding students' inquiry skills in real time. 
Paper presented at The Annual Meeting of the American Educational Research Association, April, 2011, New Orleans, LA.


Gobert, J., Baker, R.,Sao Pedro,M.,Toto, E., and Montalvo, O. (2011).
Science ASSISTments: Using student logs, machine learning, and Data Mining to determine when & how to scaffold students' science inquiry. 
Paper presented at The Annual Meeting of the American Educational Research Association, April, 2011, New Orleans, LA


Bachmann, M., Gobert, J.D., and Beck, J. (2010).
Tracking Students’ Inquiry Paths through Student Transition Analysis. 
Proceedings of the 3rd International Conference on Educational Data Mining (Pages 269-270).


Montalvo, O., Baker, R.S.J.d., Sao Pedro, M.A., Nakama, A. and Gobert, J.D. (2010). 
Identifying Students’ Inquiry Planning Using Machine Learning. 
Proceedings of the 3rd International Conference on Educational Data Mining (Pages 141-150).


Sao Pedro, M.A., Baker, R.S.J.d, Montalvo, O., Nakama, A. and Gobert, J.D. (2010).
Using Text Replay Tagging to Produce Detectors of Systematic Experimentation Behavior Pattern. 
Proceedings of the 3rd International Conference on Educational Data Mining (Pages 181-190).


Sao Pedro, M., Gobert, J., and Raziuddin, J. (2010). 
Comparing Pedagogical Approaches for the Acquisition and Long-Term Robustness of the Control of Variables Strategy. 
To appear in the Proceedings of the International Conference of the Learning Sciences, Chicago, IL, June, 2010.