Works (39)

Updated: July 5th, 2023 15:39

2023 journal article

Early prediction of student knowledge in game-based learning with distributed representations of assessment questions

BRITISH JOURNAL OF EDUCATIONAL TECHNOLOGY, 54(1), 40–57.

By: A. Emerson n, W. Min n, R. Azevedo* & J. Lester n

author keywords: game-based learning; natural language processing; predictive student modelling
Sources: Web Of Science, ORCID
Added: March 6, 2023

2023 conference paper

Leveraging Game Design Activities for Middle Grades AI Education in Rural Communities

Vandenberg, J., Min, W., Catete, V., Boulden, D., & Mott, B. (2023, April 12).

Source: ORCID
Added: April 11, 2023

2023 conference paper

Multimodal Predictive Student Modeling with Multi-Task Transfer Learning

Emerson, A., Min, W., Rowe, J., Azevedo, R., & Lester, J. (2023, March 13).

Source: ORCID
Added: February 22, 2023

2023 conference paper

Toward AI-infused Game Design Activities for Rural Middle Grades Students

Vandenberg, J., Min, W., Gupta, A., Catete, V., Boulden, D., & Mott, B. (2023, June 29).

Source: ORCID
Added: June 30, 2023

2022 conference paper

Promoting AI Education for Rural Middle Grades Students with Digital Game Design

Vandenberg, J., Min, W., Cateté, V., Boulden, D., & Mott, B. (2022, March).

Source: ORCID
Added: March 7, 2023

2021 article

Detecting Disruptive Talk in Student Chat-Based Discussion within Collaborative Game-Based Learning Environments

LAK21 CONFERENCE PROCEEDINGS: THE ELEVENTH INTERNATIONAL CONFERENCE ON LEARNING ANALYTICS & KNOWLEDGE, pp. 405–415.

author keywords: Collaborative Game-Based Learning; Disruptive Talk Detection; Text Analytics
Sources: Web Of Science, ORCID
Added: November 28, 2022

2021 article

Enhancing Multimodal Affect Recognition with Multi-Task Affective Dynamics Modeling

2021 9TH INTERNATIONAL CONFERENCE ON AFFECTIVE COMPUTING AND INTELLIGENT INTERACTION (ACII).

By: N. Henderson n, W. Min n, J. Rowe n & J. Lester n

author keywords: multitask learning; affect recognition; multimodal interaction; game-based learning environments
Sources: Web Of Science, ORCID
Added: June 6, 2022

2021 article

Multidimensional Team Communication Modeling for Adaptive Team Training: A Hybrid Deep Learning and Graphical Modeling Framework

ARTIFICIAL INTELLIGENCE IN EDUCATION (AIED 2021), PT I, Vol. 12748, pp. 293–305.

By: W. Min n, R. Spain n, J. Saville n, B. Mott n, K. Brawner*, J. Johnston*, J. Lester n

author keywords: Team communication analytics; Probabilistic graphical models; Deep learning; Distributed language representations; Natural language processing
Sources: Web Of Science, ORCID
Added: November 28, 2022

2021 article

Multimodal Trajectory Analysis of Visitor Engagement with Interactive Science Museum Exhibits

ARTIFICIAL INTELLIGENCE IN EDUCATION (AIED 2021), PT II, Vol. 12749, pp. 151–155.

By: A. Emerson n, N. Henderson n, W. Min n, J. Rowe n, J. Minogue n & J. Lester n

author keywords: Museum learning; Visitor engagement; Multimodal trajectory; analytics
Sources: Web Of Science, ORCID
Added: November 28, 2022

2020 conference paper

A conceptual assessment framework for k-12 computer science rubric design

Annual Conference on Innovation and Technology in Computer Science Education, ITiCSE, 1328.

author keywords: CS Assessment; Evidence Centered Design; K-12 CS Instruction
Source: ORCID
Added: May 20, 2020

2019 journal article

DeepStealth: Game-Based Learning Stealth Assessment with Deep Neural Networks

IEEE Transactions on Learning Technologies, 13(2), 1–1.

By: W. Min n, M. Frankosky, B. Mott n, J. Rowe n, P. Smith n, E. Wiebe n, K. Boyer*, J. Lester n

author keywords: Hidden Markov models; Computational modeling; Games; Predictive models; Task analysis; Adaptation models; Computer science; Computational thinking; deep learning; educational games; game-based learning; stealth assessment
Sources: ORCID, Crossref
Added: February 20, 2020

2019 conference paper

Generating educational game levels with multistep deep convolutional generative adversarial networks

IEEE Conference on Computatonal Intelligence and Games, CIG, 2019-August.

Source: ORCID
Added: May 20, 2020

2019 conference paper

Position: IntelliBlox: A Toolkit for Integrating Block-Based Programming into Game-Based Learning Environments

Proceedings - 2019 IEEE Blocks and Beyond Workshop, B and B 2019, 55–58.

By: S. Taylor n, W. Min n, B. Mott n, A. Emerson n, A. Smith n, E. Wiebe n, J. Lester n

Source: ORCID
Added: February 19, 2020

2019 article

Predicting Dialogue Breakdown in Conversational Pedagogical Agents with Multimodal LSTMs

ARTIFICIAL INTELLIGENCE IN EDUCATION, AIED 2019, PT II, Vol. 11626, pp. 195–200.

By: W. Min n, K. Park n, J. Wiggins*, B. Mott n, E. Wiebe n, K. Boyer*, J. Lester n

author keywords: Conversational pedagogical agent; Multimodal; Dialogue breakdown detection; Natural language processing; Gaze
Sources: Web Of Science, ORCID
Added: December 2, 2019

2019 article

Take the Initiative: Mixed Initiative Dialogue Policies for Pedagogical Agents in Game-Based Learning Environments

ARTIFICIAL INTELLIGENCE IN EDUCATION, AIED 2019, PT II, Vol. 11626, pp. 314–318.

By: J. Wiggins*, M. Kulkarni*, W. Min n, K. Boyer*, B. Mott n, E. Wiebe n, J. Lester n

author keywords: Pedagogical agents; Game-based learning; Initiative
Sources: Web Of Science, ORCID
Added: December 2, 2019

2019 conference paper

Toward computational models of team effectiveness with natural language processing

CEUR Workshop Proceedings, 2501, 30–39. http://www.scopus.com/inward/record.url?eid=2-s2.0-85075911853&partnerID=MN8TOARS

By: R. Spain, M. Geden, W. Min, B. Mott & J. Lester

Source: ORCID
Added: May 20, 2020

2018 conference paper

Affect-based early prediction of player mental demand and engagement for educational games

Proceedings of the 14th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, AIIDE 2018, 243–249. http://www.scopus.com/inward/record.url?eid=2-s2.0-85070822616&partnerID=MN8TOARS

By: J. Wiggins, M. Kulkarni, W. Min, B. Mott, K. Boyer, E. Wiebe, J. Lester

Source: ORCID
Added: May 20, 2020

2018 conference paper

High-fidelity simulated players for interactive narrative planning

IJCAI International Joint Conference on Artificial Intelligence, 2018-July, 3884–3890. http://www.scopus.com/inward/record.url?eid=2-s2.0-85055720882&partnerID=MN8TOARS

By: P. Wang, J. Rowe, W. Min, B. Mott & J. Lester

Source: ORCID
Added: May 20, 2020

2018 conference paper

Improving stealth assessment in game-based learning with LSTM-based analytics

Proceedings of the 11th International Conference on Educational Data Mining, EDM 2018. http://www.scopus.com/inward/record.url?eid=2-s2.0-85080493724&partnerID=MN8TOARS

By: B. Akram, W. Min, E. Wiebe, B. Mott, K. Boyer & J. Lester

Source: ORCID
Added: May 20, 2020

2018 conference paper

User Affect and No-Match Dialogue Scenarios: An Analysis of Facial Expression

Proceedings of the 4th International Workshop on Multimodal Analyses Enabling Artificial Agents in Human-Machine Interaction - MA3HMI'18, 6–14.

By: J. Wiggins*, M. Kulkarni*, W. Min n, K. Boyer*, B. Mott n, E. Wiebe n, J. Lester n

Event: the 4th International Workshop

author keywords: Dialogue agents; facial expression; no-match dialogue policy
Sources: ORCID, Crossref
Added: February 24, 2020

2017 article

"Thanks Alisha, Keep in Touch": Gender Effects and Engagement with Virtual Learning Companions

ARTIFICIAL INTELLIGENCE IN EDUCATION, AIED 2017, Vol. 10331, pp. 299–310.

By: L. Pezzullo*, J. Wiggins*, M. Frankosky n, W. Min n, K. Boyer*, B. Mott n, E. Wiebe n, J. Lester n

author keywords: Learning companions; Pedagogical agents; Gender; Engagement; Game-based learning
Sources: Web Of Science, ORCID
Added: August 6, 2018

2017 conference paper

Deep LSTM-based goal recognition models for open-world digital games

AAAI Workshop - Technical Report, WS-17-01 - WS-17-15, 851–858. http://www.scopus.com/inward/record.url?eid=2-s2.0-85046086839&partnerID=MN8TOARS

By: W. Min, B. Mott, J. Rowe & J. Lester

Source: ORCID
Added: May 20, 2020

2017 article

Inducing Stealth Assessors from Game Interaction Data

ARTIFICIAL INTELLIGENCE IN EDUCATION, AIED 2017, Vol. 10331, pp. 212–223.

By: W. Min n, M. Frankosky n, B. Mott n, E. Wiebe n, K. Boyer* & J. Lester n

author keywords: Game-based learning environments; Stealth assessment; Deep learning; Computational thinking; Educational games
Sources: Web Of Science, ORCID
Added: August 6, 2018

2017 conference paper

Interactive narrative personalization with deep reinforcement learning

IJCAI International Joint Conference on Artificial Intelligence, 3852–3858. http://www.scopus.com/inward/record.url?eid=2-s2.0-85031928990&partnerID=MN8TOARS

By: P. Wang, J. Rowe, W. Min, B. Mott & J. Lester

Source: ORCID
Added: May 20, 2020

2017 conference paper

Multimodal goal recognition in open-world digital games

Proceedings of the 13th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, AIIDE 2017, 80–86. http://www.scopus.com/inward/record.url?eid=2-s2.0-85051737443&partnerID=MN8TOARS

By: W. Min, B. Mott, J. Rowe, R. Taylor, E. Wiebe, K. Boyer, J. Lester

Source: ORCID
Added: May 20, 2020

2017 conference paper

Simulating player behavior for data-driven interactive narrative personalization

Proceedings of the 13th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, AIIDE 2017, 255–261. http://www.scopus.com/inward/record.url?eid=2-s2.0-85055706729&partnerID=MN8TOARS

By: P. Wang, J. Rowe, W. Min, B. Mott & J. Lester

Source: ORCID
Added: May 20, 2020

2016 chapter

Integrating Real-Time Drawing and Writing Diagnostic Models: An Evidence-Centered Design Framework for Multimodal Science Assessment

In A. Micarelli, J. Stamper, & K. Panourgia (Eds.), Intelligent Tutoring Systems (Vol. 9684, pp. 165–175).

By: A. Smith n, O. Aksit n, W. Min n, E. Wiebe n, B. Mott n & J. Lester n

Ed(s): A. Micarelli, J. Stamper & K. Panourgia

author keywords: Assessment; Multimodalilty; Evidence-centered design
Sources: Web Of Science, ORCID, Crossref
Added: August 6, 2018

2016 conference paper

Integrating real-time drawing and writing diagnostic models: An evidence-centered design framework for multimodal science assessment

Intelligent tutoring systems, its 2016, 0684, 165–175.

By: A. Smith, O. Aksit, W. Min, E. Wiebe, B. Mott & J. Lester

Source: NC State University Libraries
Added: August 6, 2018

2016 conference paper

Player goal recognition in open-world digital games with long short-term memory networks

IJCAI International Joint Conference on Artificial Intelligence, 2016-January, 2590–2596. http://www.scopus.com/inward/record.url?eid=2-s2.0-85006136250&partnerID=MN8TOARS

By: W. Min, B. Mott, J. Rowe, B. Liu & J. Lester

Source: ORCID
Added: May 20, 2020

2016 conference paper

Predicting dialogue acts for intelligent virtual agents with multimodal student interaction data

Proceedings of the 9th International Conference on Educational Data Mining, EDM 2016, 454–459. http://www.scopus.com/inward/record.url?eid=2-s2.0-85072280923&partnerID=MN8TOARS

By: W. Min, A. Vail, M. Frankosky, J. Wiggins, K. Boyer, E. Wiebe, L. Pezzullo, B. Mott, J. Lester

Source: ORCID
Added: May 20, 2020

2015 article

DeepStealth: Leveraging Deep Learning Models for Stealth Assessment in Game-Based Learning Environments

ARTIFICIAL INTELLIGENCE IN EDUCATION, AIED 2015, Vol. 9112, pp. 277–286.

By: W. Min n, M. Frankosky n, B. Mott n, J. Rowe n, E. Wiebe n, K. Boyer n, J. Lester n

author keywords: Game-based learning environments; Stealth assessment; Deep learning; Computational thinking; Educational games
Sources: Web Of Science, ORCID
Added: August 6, 2018

2015 chapter

Diagrammatic Student Models: Modeling Student Drawing Performance with Deep Learning

In Lecture Notes in Computer Science (Vol. 9146, pp. 216–227).

By: A. Smith n, W. Min n, B. Mott n & J. Lester n

author keywords: Student modeling; Intelligent tutoring systems; Deep learning
Sources: ORCID, Crossref
Added: February 19, 2020

2014 conference paper

Deep learning-based goal recognition in open-ended digital games

Proceedings of the 10th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, AIIDE 2014, 37–43. http://www.scopus.com/inward/record.url?eid=2-s2.0-84916877257&partnerID=MN8TOARS

By: W. Min, E. Ha, J. Rowe, B. Mott & J. Lester

Source: ORCID
Added: May 20, 2020

2014 book

Leveraging semi-supervised learning to predict student problem-solving performance in narrative-centered learning environments

In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 664–665).

By: W. Min n, B. Mott n, J. Rowe n & J. Lester n

Sources: NC State University Libraries, ORCID
Added: August 6, 2018

2013 book

Personalizing embedded assessment sequences in narrative-centered learning environments: A collaborative filtering approach

In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 369–378).

By: W. Min, J. Rowe, B. Mott & J. Lester

Source: ORCID
Added: May 20, 2020

2009 book

An interactive-content technique based approach to generating personalized advertisement for privacy protection

In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 185–191).

By: W. Min* & Y. Cheong*

author keywords: Privacy; Interactive content; Personalized advertising
Source: ORCID
Added: May 20, 2020

2008 book

PRISM: A framework for authoring interactive narratives

In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 297–308).

By: Y. Cheong*, Y. Kim*, W. Min*, E. Shim* & J. Kim*

Source: ORCID
Added: May 20, 2020

2008 conference paper

Planning-integrated story graph for interactive narratives

MM'08 - Proceedings of the 2008 ACM International Conference on Multimedia, with co-located Symposium and Workshops, 27–32.

By: W. Min*, E. Shim*, Y. Kim* & Y. Cheong*

Source: ORCID
Added: May 20, 2020

conference paper

Diagrammatic student models: Modeling student drawing performance with deep learning

Smith, A., Min, W., Mott, B. W., & Lester, J. C. User modeling, adaptation and personalization, 9146, 216–227.

By: A. Smith, W. Min, B. Mott & J. Lester

Source: NC State University Libraries
Added: August 6, 2018