Jaclyn L Ocumpaugh

Teachers College, Columbia University, Human Development, Post-Doc

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Papers by Jaclyn L Ocumpaugh

Baker Rodrigo Ocumpaugh Monitoring Protocol (BROMP) 2.0 Technical and Training Manual.

Training manual and technical report on the BROMP method for field observations of student engage... more

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Population validity for Educational Data Mining models: A case study in affect detection.

British Journal of Educational Technology.

Automatic Detection of Learning-Centered Affective States in the Wild.

Also With: Bosch, N., D'Mello, S., Shute, V., Ventura, M., Wang, L., Zhao, W.

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Temporal Generalizability of Face-Based Affect Detection in Noisy Classroom Environments

Also with P. Bosch, S. D'Mello, and V. Shute

Modifying Field Observation Methods on the Fly: Metanarrative and Disgust in an Environmental MUVE

Interaction-Based Affect Detection in Educational Software. In R.A. Calvo, S.K. D'Mello, J. Gratch, A. Kappas (Eds.), Handbook of Affective Computing. Oxford, UK: Oxford University Press.

Towards General Models of Effective Science Inquiry in Virtual Performance Assessments.

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Improving Engagement in an E-Learning Environment

by Jaclyn L Ocumpaugh and Kevin Mulqueeny

Baker-Rodrigo Observation Method Protocol (BROMP) 1.0 (Training Manual version 1.0)

Download

Towards Sensor-Free Affect Detection in Cognitive Tutor Algebra

Download

Reengineering the Feature Distillation Process: A Case Study in the Detection of Gaming the System.

Towards Detection of Engagement and Affect in a Simulation-based Combat Medic Training Environment.

Ensuring Reliability of Educational Data Mining Detectors for Diverse Populations of Learners.

Predicting STEM and Non-STEM College Major Enrollment from Middle School Interaction with Mathematics Educational Software.

I Feel Your Pain: A Selective Review of Affect-Sensitive Instructional Strategies.

Sequences of Frustration and Confusion, and Learning

Extending Log-Based Affect Detection to a Multi-User Virtual Environment for Science.

Interaction-Based Affect Detection in Educational Software. In R.A. Calvo, S.K. D'Mello, J. Gratch, A. Kappas (Eds.), Handbook of Affective Computing. Oxford, UK: Oxford University Press.

Field Observations of Engagement in Reasoning Mind.

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Towards Automatically Detecting Whether Student Learning is Shallow

Baker Rodrigo Ocumpaugh Monitoring Protocol (BROMP) 2.0 Technical and Training Manual.

Training manual and technical report on the BROMP method for field observations of student engage... more

Download

Population validity for Educational Data Mining models: A case study in affect detection.

British Journal of Educational Technology.

Automatic Detection of Learning-Centered Affective States in the Wild.

Also With: Bosch, N., D'Mello, S., Shute, V., Ventura, M., Wang, L., Zhao, W.

Download

Temporal Generalizability of Face-Based Affect Detection in Noisy Classroom Environments

Also with P. Bosch, S. D'Mello, and V. Shute

Modifying Field Observation Methods on the Fly: Metanarrative and Disgust in an Environmental MUVE

Interaction-Based Affect Detection in Educational Software. In R.A. Calvo, S.K. D'Mello, J. Gratch, A. Kappas (Eds.), Handbook of Affective Computing. Oxford, UK: Oxford University Press.

Towards General Models of Effective Science Inquiry in Virtual Performance Assessments.

Download

Improving Engagement in an E-Learning Environment

by Jaclyn L Ocumpaugh and Kevin Mulqueeny

Baker-Rodrigo Observation Method Protocol (BROMP) 1.0 (Training Manual version 1.0)

Download

Towards Sensor-Free Affect Detection in Cognitive Tutor Algebra

Download

Reengineering the Feature Distillation Process: A Case Study in the Detection of Gaming the System.

Towards Detection of Engagement and Affect in a Simulation-based Combat Medic Training Environment.

Ensuring Reliability of Educational Data Mining Detectors for Diverse Populations of Learners.

Predicting STEM and Non-STEM College Major Enrollment from Middle School Interaction with Mathematics Educational Software.

I Feel Your Pain: A Selective Review of Affect-Sensitive Instructional Strategies.

Sequences of Frustration and Confusion, and Learning

Extending Log-Based Affect Detection to a Multi-User Virtual Environment for Science.

Interaction-Based Affect Detection in Educational Software. In R.A. Calvo, S.K. D'Mello, J. Gratch, A. Kappas (Eds.), Handbook of Affective Computing. Oxford, UK: Oxford University Press.

Field Observations of Engagement in Reasoning Mind.

Download

Towards Automatically Detecting Whether Student Learning is Shallow

Jaclyn L Ocumpaugh

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