Nigel Bosch

in press

Constructing categories: Moving beyond protected classes in algorithmic fairness C. Belitz, J. Ocumpaugh, S. Ritter, R. S. Baker, S. E. Fancsali, N. Bosch Journal of the Association for Information Science and Technology [DOI]

Automated video interview personality assessments: Reliability, validity, and generalizability investigations L. Hickman, N. Bosch, V. Ng, R. Saef, L. Tay, S. E. Woo Journal of Applied Psychology [DOI]

How are feelings of difficulty and familiarity linked to learning behaviors and gains in a complex science learning task? Y. Zhang, L. Paquette, R. S. Baker, N. Bosch, J. Ocumpaugh, G. Biswas European Journal of Psychology of Education

The evolution of metacognitive strategy use in an open-ended learning environment: Do prior domain knowledge and motivation play a role? Y. Zhang, L. Paquette, N. Bosch, J. Ocumpaugh, G. Biswas, S. Hutt, R. S. Baker Contemporary Educational Psychology [DOI]

2022

Can computers outperform humans in detecting user zone-outs? Implications for intelligent interfaces N. Bosch, S. K. D'Mello ACM Transactions on Computer-Human Interaction (TOCHI), 29(2), 1-33 [DOI]

Novice reflections during the transition to a new programming language P. Denny, B. A. Becker, N. Bosch, J. Prather, B. Reeves, J. Whalley Proceedings of the 53rd ACM Technical Symposium on Computer Science Education (SIGCSE), pp. 948-954 [DOI]

Tracking individuals in classroom videos via post-processing OpenPose data P. Hur, N. Bosch Proceedings of the 12th International Conference on Learning Analytics & Knowledge (LAK '22), pp. 465-471 [DOI]

2021

Automating procedurally fair feature selection in machine learning C. Belitz, L. Jiang, N. Bosch Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society (AIES '21), pp. 379-389 [DOI] [code]

Automatic detection of mind wandering from video in the lab and in the classroom N. Bosch, S. K. D'Mello IEEE Transactions on Affective Computing, 12(4), 974-988 [DOI]

AutoML feature engineering for student modeling yields high accuracy, but limited interpretability N. Bosch Journal of Educational Data Mining, 13(2), 55-79 [DOI]

What's next? Sequence length and impossible loops in state transition measurement N. Bosch, L. Paquette Journal of Educational Data Mining, 13(1), 1-23 [DOI]

Students' verbalized metacognition during computerized learning N. Bosch, Y. Zhang, L. Paquette, R. S. Baker, J. Ocumpaugh, G. Biswas Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems (CHI '21), pp. 680:1-680:12 [DOI]

Identifying supportive student factors for mindset interventions: A two-model machine learning approach N. Bosch Computers & Education, 167, 104190:1-15 [DOI]

A new generation of transdermal alcohol biosensing technology: Practical applications, machine learning analytics, and questions for future research C. E. Fairbairn, N. Bosch Addiction, 116(10), 2912-2920 [DOI]

Alcohol narrows physical distance between strangers L. Gurrieri, C. E. Fairbairn, M. A. Sayette, N. Bosch Proceedings of the National Academy of Sciences, 118(20), e2101937118:1-3 [DOI]

Developing and evaluating language-based machine learning algorithms for inferring applicant personality in video interviews L. Hickman, R. Saef, V. Ng, S. E. Woo, L. Tay, N. Bosch Human Resource Management Journal [DOI]

Who's stopping you? Using microanalysis to explore the impact of science anxiety on self-regulated learning operations S. Hutt, J. Ocumpaugh, J. M. A. L. Andres, A. Munshi, N. Bosch, R. S. Baker, Y. Zhang, L. Paquette, S. Slater, G. Biswas Proceedings of the Annual Meeting of the Cognitive Science Society, pp. 1409-1415

Investigating SMART models of self-regulation and their impact on learning S. Hutt, J. Ocumpaugh, J. M. A. L. Andres, N. Bosch, L. Paquette, G. Biswas, R. S. Baker Proceedings of the 14th International Conference on Educational Data Mining (EDM 2021), pp. 580-587

Predictive sequential pattern mining via interpretable convolutional neural networks L. Jiang, N. Bosch Proceedings of the 14th International Conference on Educational Data Mining (EDM 2021), pp. 761-766 [poster]

Promoting self-regulated learning in online learning by triggering tailored interventions H. Lee, P. Hur, S. Bhat, N. Bosch CEUR Workshop Proceedings: Joint Workshops at the International Conference on Educational Data Mining, 3051, 1-8

Ask for help: Online help-seeking and help-giving as indicators of cognitive and social presence for students underrepresented in chemistry D. Williams-Dobosz, A. Jeng, R. F. L. Azevedo, N. Bosch, C. Ray, M. Perry Journal of Chemical Education, 98(12), 3693-3703 [DOI]

A social network analysis of online engagement for college students traditionally underrepresented in STEM D. Williams-Dobosz, R. F. L. Azevedo, A. Jeng, V. Thakkar, S. Bhat, N. Bosch, M. Perry Proceedings of the 11th International Conference on Learning Analytics & Knowledge (LAK '21), pp. 207-215 [DOI]

Can strategic behavior facilitate confusion resolution? The interplay between confusion and metacognitive strategies in Betty’s Brain Y. Zhang, L. Paquette, R. S. Baker, J. Ocumpaugh, N. Bosch, G. Biswas, A. Munshi Journal of Learning Analytics, 8(3), 28-44 [DOI]

2020

"Hello, [REDACTED]": Protecting student privacy in analyses of online discussion forums N. Bosch, R. W. Crues, N. Shaik, L. Paquette Proceedings of the 13th International Conference on Educational Data Mining (EDM 2020), pp. 39-49 [code] [Best paper nominee]

Advancing computational grounded theory for audiovisual data from mathematics classrooms C. D'Angelo, E. Dyer, S. Krist, J. Rosenberg, N. Bosch Proceedings of the 14th International Conference on Learning Sciences (ICLS 2020), pp. 2393-2394 [poster]

Analyzing learning with speech analytics and computer vision methods: Technologies, principles, and ethics E. Dyer, C. D'Angelo, N. Bosch, S. Krist, J. Rosenberg Proceedings of the 14th International Conference on Learning Sciences (ICLS 2020), pp. 2651-2653 [workshop]

Using machine learning for real-time BAC estimation from a new-generation transdermal biosensor in the laboratory C. E. Fairbairn, D. Kang, N. Bosch Drug and Alcohol Dependence, 216, 108205:1-108205:8 [DOI]

The sound of inattention: Predicting mind wandering with automatically derived features of instructor speech I. Gliser, C. Mills, N. Bosch, S. Smith, D. Smilek, J. D. Wammes Proceedings of the 21st International Conference on Artificial Intelligence in Education (AIED 2020), pp. 204-215 [DOI]

Automatically classifying the evidence type of drug-drug interaction research papers as a step toward computer supported evidence curation L. Hoang, R. D. Boyce, N. Bosch, B. A. Stottlemyer, M. Brochhausen, J. Schneider Proceedings of the American Medical Informatics Association (AMIA) Annual Meeting, pp. 554-562

Harbingers of collaboration? The role of early-class behaviors in predicting collaborative problem solving P. Hur, N. Bosch, L. Paquette, E. Mercier Proceedings of the 13th International Conference on Educational Data Mining (EDM 2020), pp. 104-114

Online discussion forum help-seeking behaviors of students underrepresented in STEM V. Jay, G. M. Henricks, C. J. Anderson, L. Angrave, N. Bosch, D. Williams-Dobosz, N. Shaik, S. Bhat, M. Perry Proceedings of the 14th International Conference on Learning Sciences (ICLS 2020), pp. 809-810 [poster]

The invisible breadcrumbs of digital learning: How learner actions inform us of their experience L. Paquette, N. Bosch Handbook of Research on Digital Learning, pp. 302-316 [DOI] [book chapter]

Feature selection metrics: Similarities, differences, and characteristics of the selected models D. Sanyal, N. Bosch, L. Paquette Proceedings of the 13th International Conference on Educational Data Mining (EDM 2020), pp. 212-223

Using association rule mining to uncover rarely occurring relationships in two university online STEM courses: A comparative analysis H. Valdiviejas, N. Bosch Proceedings of the 13th International Conference on Educational Data Mining (EDM 2020), pp. 686-690 [poster]

The relationship between confusion and metacognitive strategies in Betty’s Brain Y. Zhang, L. Paquette, R. S. Baker, J. Ocumpaugh, N. Bosch, A. Munshi, G. Biswas Proceedings of the 10th International Conference on Learning Analytics and Knowledge (LAK20), pp. 276-284 [DOI]

2019

Affect sequences and learning in Betty's Brain A. Andres, J. Ocumpaugh, R. S. Baker, S. Slater, L. Paquette, Y. Jiang, N. Bosch, A. Munshi, A. L. Moore, G. Biswas Proceedings of the 9th International Conference on Learning Analytics & Knowledge (LAK19), pp. 383-390 [DOI]

Modeling improvement for underrepresented minorities in online STEM education N. Bosch, E. Huang, L. Angrave, M. Perry Proceedings of the 27th Conference on User Modeling, Adaptation and Personalization (UMAP 2019), pp. 327-335 [DOI]

I'm sure! Automatic detection of metacognition in online course discussion forums E. Huang, H. Valdiviejas, N. Bosch Proceedings of the 8th International Conference on Affective Computing and Intelligent Interaction (ACII 2019), pp. 241-247 [DOI]

Automated gaze-based mind wandering detection during computerized learning in classrooms S. Hutt, K. Krasich, C. Mills, N. Bosch, S. White, J. R. Brockmole, S. K. D'Mello User Modeling and User-Adapted Interaction, 29(4), 821-867 [DOI]

Reducing mind wandering during vicarious learning from an intelligent tutoring system C. Mills, N. Bosch, K. Krasich, S. K. D'Mello Proceedings of the 20th International Conference on Artificial Intelligence in Education (AIED 2019), pp. 296-307 [DOI]

Disengagement during lectures: Media multitasking and mind wandering in university classrooms J. D. Wammes, B. C. W. Ralph, C. Mills, N. Bosch, T. L. Duncan, D. Smilek Computers & Education, 132, 76-89 [DOI]

2018

Modeling key differences in underrepresented students' interactions with an online STEM course N. Bosch, R. W. Crues, G. M. Henricks, M. Perry, L. Angrave, N. Shaik, S. Bhat, C. J. Anderson Proceedings of TechMindSociety '18, pp. 6:1-6:6 [DOI]

Metrics for discrete student models: Chance levels, comparisons, and use cases N. Bosch, L. Paquette Journal of Learning Analytics, 5(2), 86-104 [DOI]

Diverse learners, diverse motivations: Exploring the sentiment of learning objectives N. Bosch, R. W. Crues, N. Shaik Proceedings of the 11th International Conference on Educational Data Mining (EDM 2018), pp. 553-556 [poster]

Quantifying classroom instructor dynamics with computer vision N. Bosch, C. Mills, J. D. Wammes, D. Smilek Proceedings of the 19th International Conference on Artificial Intelligence in Education (AIED 2018), pp. 30-42 [DOI] [code]

Refocusing the lens on engagement in MOOCs R. W. Crues, N. Bosch, M. Perry, L. Angrave, N. Shaik, S. Bhat Proceedings of the 5th ACM Conference on Learning@Scale (L@S 2018), pp. 11:1-11:10 [DOI]

Who they are and what they want: Understanding the reasons for MOOC enrollment R. W. Crues, N. Bosch, C. J. Anderson, M. Perry, S. Bhat, N. Shaik Proceedings of the 11th International Conference on Educational Data Mining (EDM 2018), pp. 177-186

Multimodal-multisensor affect detection S. K. D'Mello, N. Bosch, H. Chen The Handbook of Multimodal-Multisensor Interfaces, Volume 2: Signal Processing, Architectures, and Detection of Emotion and Cognition, pp. 167-202 [DOI] [book chapter]

Expert feature-engineering vs. deep neural networks: Which is better for sensor-free affect detection? Y. Jiang, N. Bosch, R. S. Baker, L. Paquette, J. Ocumpaugh, J. M. A. L. Andres, A. L. Moore, G. Biswas Proceedings of the 19th International Conference on Artificial Intelligence in Education (AIED 2018), pp. 198-211 [DOI] [Best student paper award]

Matching data-driven models of group interactions to video analysis of collaborative problem solving on tablet computers L. Paquette, N. Bosch, E. Mercier, J. Jung, S. Shehab, Y. Tong Proceedings of the 13th International Conference of the Learning Sciences (ICLS) 2018, Volume 1, pp. 312-319

2017

The affective experience of novice computer programmers N. Bosch, S. K. D'Mello International Journal of Artificial Intelligence in Education, 27(1), 181-206 [DOI]

Unsupervised deep autoencoders for feature extraction with educational data N. Bosch, L. Paquette Deep Learning with Educational Data Workshop at the 10th International Conference on Educational Data Mining [code]

Zone out no more: Mitigating mind wandering during computerized reading S. K. D'Mello, C. Mills, R. Bixler, N. Bosch Proceedings of the 10th International Conference on Educational Data Mining (EDM 2017), pp. 8-15 [Best paper nominee]

Out of the fr-"eye"-ing pan: Towards gaze-based models of attention during learning with technology in the classroom S. Hutt, C. Mills, N. Bosch, K. Krasich, J. Brockmole, S. K. D'Mello Proceedings of the 2017 Conference on User Modeling, Adaptation, and Personalization (UMAP 2017), pp. 94-103 [DOI] [Best student paper award]

MAP: Multimodal assessment platform for interactive communication competency S. Khan, D. Suendermann-Oeft, K. Evanini, D. M. Williamson, S. Paris, Y. Qian, Y. Huang, N. Bosch, S. K. D'Mello, A. Loukina, L. Davis Practitioner Track Proceedings of the 7th International Conference on Learning Analytics & Knowledge (LAK17), pp. 6-12

Automated detection of engagement using video-based estimation of facial expressions and heart rate H. Monkaresi, N. Bosch, R. A. Calvo, S. K. D'Mello IEEE Transactions on Affective Computing, 8(1), 15-28 [DOI]

Face forward: Detecting mind wandering from video during narrative film comprehension A. Stewart, N. Bosch, H. Chen, P. J. Donnelly, S. K. D'Mello Proceedings of the 18th International Conference on Artificial Intelligence in Education (AIED 2017), pp. 359-370 [DOI]

Generalizability of face-based mind wandering detection across task contexts A. Stewart, N. Bosch, S. K. D'Mello Proceedings of the 10th International Conference on Educational Data Mining (EDM 2017), pp. 88-95 [Best student paper award]

2016

Detecting student engagement: Human versus machine N. Bosch Proceedings of the 2016 Conference on User Modeling, Adaptation, and Personalization (UMAP 2016), pp. 317-320 [DOI]

Using video to automatically detect learner affect in computer-enabled classrooms N. Bosch, S. K. D'Mello, J. Ocumpaugh, R. S. Baker, V. Shute ACM Transactions on Interactive Intelligent Systems (TiiS), 6(2), 17:1-17:26 [DOI]

Detecting student emotions in computer-enabled classrooms N. Bosch, S. K. D'Mello, R. S. Baker, J. Ocumpaugh, V. J. Shute, M. Ventura, L. Wang, W. Zhao Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI 2016), pp. 4125-4129

Attending to attention: Detecting and combating mind wandering during computerized reading S. K. D'Mello, K. Kopp, R. Bixler, N. Bosch Proceedings of the 2016 CHI Conference Extended Abstracts on Human Factors in Computing Systems, pp. 1661-1669 [DOI] [poster]

Student emotion, co-occurrence, and dropout in a MOOC context J. Dillon, N. Bosch, M. Chetlur, N. Wanigasekara, G. A. Ambrose, B. Sengupta, S. K. D'Mello Proceedings of the 9th International Conference on Educational Data Mining (EDM 2016), pp. 353-357

Where’s your mind at? Video-based mind wandering detection during film viewing A. Stewart, N. Bosch, H. Chen, P. J. Donnelly, S. K. D'Mello Proceedings of the 2016 Conference on User Modeling, Adaptation, and Personalization (UMAP 2016), pp. 295-296 [DOI] [poster]

2015

Automatic detection of learning-centered affective states in the wild N. Bosch, S. K. D'Mello, R. S. Baker, J. Ocumpaugh, V. J. Shute, M. Ventura, L. Wang, W. Zhao Proceedings of the 2015 International Conference on Intelligent User Interfaces (IUI 2015), pp. 379-388 [DOI] [Honorable mention for the best paper award]

Accuracy vs. availability heuristic in multimodal affect detection in the wild N. Bosch, H. Chen, R. Baker, V. Shute, S. K. D'Mello Proceedings of the 17th International Conference on Multimodal Interaction (ICMI 2015), pp. 267-274 [DOI] [poster]

Temporal generalizability of face-based affect detection in noisy classroom environments N. Bosch, S. K. D'Mello, R. S. Baker, J. Ocumpaugh, V. J. Shute Proceedings of the 17th International Conference on Artificial Intelligence in Education (AIED 2015), pp. 44-53 [DOI] [Best paper award]

Multimodal affect detection in the wild: Accuracy, availability, and generalizability N. Bosch Proceedings of the 17th International Conference on Multimodal Interaction (ICMI 2015 doctoral consortium), pp. 645-649 [DOI]

Video-based affect detection in noninteractive learning environments Y. Chen, N. Bosch, S. K. D'Mello Proceedings of the 8th International Conference on Educational Data Mining (EDM 2015), pp. 440-443

A comparison of face-based and interaction-based affect detectors in Physics Playground S. Kai, L. Paquette, R. Baker, N. Bosch, S. K. D'Mello, J. Ocumpaugh, V. J. Shute, M. Ventura Proceedings of the 8th International Conference on Educational Data Mining (EDM 2015), pp. 77-84 [Best student paper award]

Mind wandering during learning with an intelligent tutoring system C. Mills, S. K. D'Mello, N. Bosch, A. Olney Proceedings of the 17th International Conference on Artificial Intelligence in Education (AIED 2015), pp. 267-276 [DOI]

Modeling how incoming knowledge, persistence, affective states, and in-game progress influence student learning from an educational game V. J. Shute, S. K. D'Mello, R. Baker, K. Cho, N. Bosch, J. Ocumpaugh, M. Ventura, V. Almeda Computers & Education, 86, 224-235 [DOI]

2014

It’s written on your face: Detecting affective states from facial expressions while learning computer programming N. Bosch, Y. Chen, S. K. D'Mello Proceedings of the 12th International Conference on Intelligent Tutoring Systems (ITS 2014), pp. 39-44 [DOI]

It takes two: Momentary co-occurrence of affective states during computerized learning N. Bosch, S. K. D'Mello Proceedings of the 12th International Conference on Intelligent Tutoring Systems (ITS 2014), pp. 638-639 [DOI] [poster]

Co-occurring affective states in automated computer programming education N. Bosch, S. K. D'Mello Proceedings of the Workshop on AI-supported Education for Computer Science (AIEDCS) at the 12th International Conference on Intelligent Tutoring Systems, pp. 21-30

To quit or not to quit: Predicting future behavioral disengagement from reading patterns C. Mills, N. Bosch, A. Graesser, S. K. D'Mello Proceedings of the 12th International Conference on Intelligent Tutoring Systems (ITS 2014), pp. 19-28 [DOI]

Improving automated source code summarization via an eye-tracking study of programmers P. Rodeghero, C. McMillan, P. W. McBurney, N. Bosch, S. K. D'Mello Proceedings of the 36th International Conference on Software Engineering (ICSE 2014), pp. 390–401 [DOI] [ACM distinguished paper award]

2013

What emotions do novices experience during their first computer programming learning session? N. Bosch, S. K. D'Mello, C. Mills Proceedings of the 16th International Conference on Artificial Intelligence in Education (AIED 2013), pp. 11-20 [DOI]

Programming with your heart on your sleeve: Analyzing the affective states of computer programming students N. Bosch, S. K. D'Mello Proceedings of the 16th International Conference on Artificial Intelligence in Education (AIED 2013), pp. 908-911 [DOI]

Sequential patterns of affective states of novice programmers N. Bosch, S. K. D'Mello Proceedings of the First Workshop on AI-supported Education for Computer Science (AIEDCS 2013), pp. 1-10

What makes learning fun? Exploring the influence of choice and difficulty on mind wandering and engagement during learning C. Mills, S. K. D'Mello, B. Lehman, N. Bosch, A. Strain, A. Graesser Proceedings of the 16th International Conference on Artificial Intelligence in Education (AIED 2013), pp. 71-80 [DOI]