Works (39)

Updated: April 5th, 2024 05:45

2024 journal article

Engagement of adolescents with ADHD in a narrative-centered game-based behavior change environment to reduce alcohol use

FRONTIERS IN EDUCATION, 8.

By: M. Pugatch*, N. Blum*, W. Barbaresi*, J. Rowe n, M. Berna*, S. Hennigan*, A. Giovanelli*, C. Penilla* ...

author keywords: prevention; technology; adolescent; alcohol-related disorders; parenting; attention deficit hyperactivity disorder; ADHD; life course
TL;DR: It is suggested that INSPIRE may support facilitating youth with ADHD to learn the developmental competencies needed to mitigate risk and thrive and warrants further testing to explore its impact on alcohol use in youth with ADHD. (via Semantic Scholar)
UN Sustainable Development Goal Categories
3. Good Health and Well-being (OpenAlex)
Source: Web Of Science
Added: January 29, 2024

2024 article

The AI Institute for Engaged Learning

Lester, J., Bansal, M., Biswas, G., Hmelo-Silver, C., Roschelle, J., & Rowe, J. (2024, February 14). AI MAGAZINE.

By: J. Lester n, M. Bansal*, G. Biswas*, C. Hmelo-Silver*, J. Roschelle* & J. Rowe n

TL;DR: The EngageAI Institute focuses on AI‐driven narrative‐centered learning environments that create engaging story‐based problem‐solving experiences to support collaborative learning and emphasizes broad participation and diverse perspectives to ensure that advances in AI‐augmented learning address inequities in STEM. (via Semantic Scholar)
Source: Web Of Science
Added: February 26, 2024

2023 journal article

Supporting Adolescent Engagement with Artificial Intelligence-Driven Digital Health Behavior Change Interventions

JOURNAL OF MEDICAL INTERNET RESEARCH, 25.

author keywords: digital health behavior change; adolescent; adolescence; behavior change; BCT; behavioral intervention; artificial intelligence; machine learning; model; AI ethics; trace log data; ethics; ethical; youth; risky behavior; engagement; privacy; security; optimization; operationalization
MeSH headings : Adolescent; Humans; Artificial Intelligence; Health Behavior; Software; Adolescent Behavior; Risk-Taking
TL;DR: A framework for harnessing AI to accomplish 4 goals that are pertinent to health care providers and software developers alike: measurement of adolescent engagement, modeling of adolescents engagement, optimization of current interventions, and generation of novel interventions is proposed. (via Semantic Scholar)
Source: Web Of Science
Added: July 3, 2023

2022 article

Investigating Student Interest and Engagement in Game-Based Learning Environments

ARTIFICIAL INTELLIGENCE IN EDUCATION, PT I, Vol. 13355, pp. 711–716.

author keywords: Interest; Science learning; Learning technology
TL;DR: It is found that interest is significantly related to performance (both knowledge assessment and game completion), suggesting that students with high interest are likely to perform better academically, but also be more engaged in the in-game objectives. (via Semantic Scholar)
UN Sustainable Development Goal Categories
4. Quality Education (Web of Science)
Sources: Web Of Science, ORCID
Added: November 21, 2022

2022 article

Leveraging Student Goal Setting for Real-Time Plan Recognition in Game-Based Learning

ARTIFICIAL INTELLIGENCE IN EDUCATION, PT I, Vol. 13355, pp. 78–89.

author keywords: Plan recognition; Game-based Learning; Self-regulated learning
TL;DR: A novel plan recognition framework is introduced that leverages trace log data from student interactions within a game-based learning environment called C RYSTAL I SLAND, in which students use a drag-and-drop planning support tool that enables them to externalize their science problem-solving goals and plans prior to enacting them in the learning environment. (via Semantic Scholar)
UN Sustainable Development Goal Categories
4. Quality Education (Web of Science)
Sources: Web Of Science, ORCID
Added: November 21, 2022

2022 article

Robust Adaptive Scaffolding with Inverse Reinforcement Learning-Based Reward Design

ARTIFICIAL INTELLIGENCE IN EDUCATION: POSTERS AND LATE BREAKING RESULTS, WORKSHOPS AND TUTORIALS, INDUSTRY AND INNOVATION TRACKS, PRACTITIONERS AND DOCTORAL CONSORTIUM, PT II, Vol. 13356, pp. 204–207.

By: F. Fahid n, J. Rowe n, R. Spain n, B. Goldberg*, R. Pokorny* & J. Lester n

author keywords: Inverse reinforcement learning; Reward modeling; Adaptive learning environments; Adaptive scaffolding; ICAP
Source: Web Of Science
Added: November 14, 2022

2021 article

A reinforcement learning approach to adaptive remediation in online training

Spain, R., Rowe, J., Smith, A., Goldberg, B., Pokorny, R., Mott, B., & Lester, J. (2021, July 23). JOURNAL OF DEFENSE MODELING AND SIMULATION-APPLICATIONS METHODOLOGY TECHNOLOGY-JDMS, Vol. 7.

By: R. Spain n, J. Rowe n, A. Smith n, B. Goldberg*, R. Pokorny*, B. Mott n, J. Lester n

author keywords: Tutorial planning; adaptive remediation; reinforcement learning; adaptive instructional systems
TL;DR: This study induces data-driven policies for tutorial planning using reinforcement learning (RL) to provide adaptive scaffolding based on the Interactive, Constructive, Active, Passive framework for cognitive engagement to demonstrate how AI-based training can be leveraged to enhance training effectiveness. (via Semantic Scholar)
UN Sustainable Development Goal Categories
4. Quality Education (Web of Science; OpenAlex)
Sources: Web Of Science, ORCID
Added: August 2, 2021

2021 article

Adaptively Scaffolding Cognitive Engagement with Batch Constrained Deep Q-Networks

ARTIFICIAL INTELLIGENCE IN EDUCATION (AIED 2021), PT I, Vol. 12748, pp. 113–124.

By: F. Fahid n, J. Rowe n, R. Spain n, B. Goldberg*, R. Pokorny* & J. Lester n

author keywords: Deep reinforcement learning; Cognitive engagement; ICAP; Adaptive learning environments
Source: Web Of Science
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
TL;DR: A multimodal, multitask affect recognition framework that predicts students’ future affective states as auxiliary training tasks and uses prior affectiveStates as input features to capture bi-directional affective dynamics and enhance the training of affect recognition models is presented. (via Semantic Scholar)
UN Sustainable Development Goal Categories
4. Quality Education (Web of Science)
Sources: Web Of Science, ORCID
Added: June 6, 2022

2021 article

Investigating Student Reflection during Game-Based Learning in Middle Grades Science

LAK21 CONFERENCE PROCEEDINGS: THE ELEVENTH INTERNATIONAL CONFERENCE ON LEARNING ANALYTICS & KNOWLEDGE, pp. 280–291.

author keywords: Self-Regulated Learning; Game-Based Learning; Reflection
TL;DR: This paper uses embedded reflection prompts to elicit written reflections during students’ interactions with Crystal Island, a game-based learning environment for middle-school microbiology, and identifies key features in students�’ problem-solving actions and reflections that are predictive of reflection depth. (via Semantic Scholar)
UN Sustainable Development Goal Categories
4. Quality Education (OpenAlex)
Source: Web Of Science
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

2021 journal article

Predictive Student Modeling in Game-Based Learning Environments with Word Embedding Representations of Reflection

INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE IN EDUCATION, 31(1), 1–23.

By: M. Geden n, A. Emerson n, D. Carpenter n, J. Rowe n, R. Azevedo* & J. Lester n

author keywords: Student modeling; Early prediction; Game-based learning environments; Self-regulated learning; Reflection
TL;DR: A predictive student modeling framework that leverages natural language responses to in-game reflection prompts to predict student learning outcomes in a game-based learning environment for middle school microbiology, CRYSTAL ISLAND is presented. (via Semantic Scholar)
UN Sustainable Development Goal Categories
4. Quality Education (Web of Science; OpenAlex)
Source: Web Of Science
Added: November 9, 2020

2020 review

Artificial Intelligence for Personalized Preventive Adolescent Healthcare

[Review of ]. JOURNAL OF ADOLESCENT HEALTH, 67(2), 552–558.

By: J. Rowe n & J. Lester n

author keywords: Artificial intelligence; Prevention; Health information technology; Adaptive learning technologies; User modeling; Interactive narrative generation; Adolescents
MeSH headings : Adolescent; Adolescent Health Services; Artificial Intelligence; Deep Learning; Delivery of Health Care; Forecasting; Humans; Narration; Preventive Health Services
TL;DR: A computer science perspective on how emerging AI technologies-intelligent learning environments, interactive narrative generation, user modeling, and adaptive coaching-can be utilized to model adolescent learning and engagement and deliver personalized support in adaptive health technologies is provided. (via Semantic Scholar)
Source: Web Of Science
Added: August 10, 2020

2020 journal article

Fostering Engagement in Health Behavior Change: Iterative Development of an Interactive Narrative Environment to Enhance Adolescent Preventive Health Services

JOURNAL OF ADOLESCENT HEALTH, 67(2), S34–S44.

author keywords: Health behavior change; Prevention; Interactive narrative technologies; Adolescent risk behavior; Alcohol use; Games for health; Narrative-centered behavior change environments; Health information technology; Self-efficacy; Social-cognitive theory
MeSH headings : Adolescent; Adolescent Behavior / psychology; Adolescent Health Services; Health Behavior; Humans; Narration; Preventive Health Services; Video Games / psychology
TL;DR: In this article, the iterative design and development of Interactive Narrative System for Patient-Individualized Reflective Exploration (INSPIRE), a narrative-centered behavior change environment for adolescents focused on reducing alcohol use is described. (via Semantic Scholar)
Source: Web Of Science
Added: August 10, 2020

2019 article

4D Affect Detection: Improving Frustration Detection in Game-Based Learning with Posture-Based Temporal Data Fusion

ARTIFICIAL INTELLIGENCE IN EDUCATION (AIED 2019), PT I, Vol. 11625, pp. 144–156.

By: N. Henderson n, J. Rowe n, B. Mott n, K. Brawner*, R. Baker* & J. Lester n

author keywords: Affect detection; Data fusion; Posture; Frustration; Deep learning
TL;DR: A data-driven framework that leverages spatial and temporal posture data to detect learner frustration using deep neural network-based data fusion techniques and shows significant improvements to frustration detection relative to baseline models. (via Semantic Scholar)
UN Sustainable Development Goal Categories
4. Quality Education (Web of Science)
Source: Web Of Science
Added: December 2, 2019

2019 journal article

Collaborative inquiry play A design case to frame integration of collaborative problem solving with story-centric games

INFORMATION AND LEARNING SCIENCES, 120(9/10), 547–566.

author keywords: Play; Socially shared regulated learning; Problem-based learning; Collaborative inquiry; Game-based learning; Complex systems
UN Sustainable Development Goal Categories
4. Quality Education (Web of Science)
Source: Web Of Science
Added: December 30, 2019

2019 article

Designing and Developing Interactive Narratives for Collaborative Problem-Based Learning

INTERACTIVE STORYTELLING, ICIDS 2019, Vol. 11869, pp. 86–100.

By: B. Mott n, R. Taylor n, S. Lee n, J. Rowe n, A. Saleh*, K. Glazewski*, C. Hmelo-Silver*, J. Lester n

author keywords: Narrative-centered learning; Collaborative learning
TL;DR: Results from pilot testing the learning environment with 45 students suggest it supports the creation of engaging and effective collaborative narrative-centered learning experiences, and a novel framework for designing and developing these environments is proposed. (via Semantic Scholar)
UN Sustainable Development Goal Categories
4. Quality Education (Web of Science)
Source: Web Of Science
Added: December 11, 2020

2019 journal article

ENGAGING ADOLESCENTS IN A SELF-ADAPTIVE PERSONALIZED BEHAVIOR CHANGE SYSTEM FOR ADOLESCENT PREVENTIVE HEALTHCARE

JOURNAL OF ADOLESCENT HEALTH, 64(2), S60–61.

By: E. Ozer*, J. Rowe n, K. Tebb*, M. Berna*, C. Jasik*, C. Penilla*, A. Giovanelli*, M. Ozer-Staton*, A. Kellenberger*, J. Lester n

Source: NC State University Libraries
Added: February 4, 2019

2018 journal article

Detecting and Addressing Frustration in a Serious Game for Military Training

INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE IN EDUCATION, 28(2), 152–193.

By: J. DeFalco*, J. Rowe n, L. Paquette*, V. Georgoulas-Sherry*, K. Brawner*, B. Mott n, R. Baker*, J. Lester n

author keywords: Affect detection; Motivational feedback; Game-based learning; Gift
TL;DR: The results are mixed, finding that self-efficacy enhancing interventions based on interaction-based affect detectors enhance outcomes in one of two experiments investigating affective interventions. (via Semantic Scholar)
Source: Web Of Science
Added: August 6, 2018

2017 journal article

Play in the Museum: Design and Development of a Game-Based Learning Exhibit for Informal Science Education

INTERNATIONAL JOURNAL OF GAMING AND COMPUTER-MEDIATED SIMULATIONS, 9(3), 96–113.

By: J. Rowe n, E. Lobene, B. Mott n & J. Lester n

author keywords: Educational Game Design; Game-Based Learning; Museum Education; Pedagogical Agents; Surface Computing Tables; Visitor Studies
TL;DR: Results indicate that visitors showed significant gains in sustainability knowledge as well as high levels of engagement in a free-choice learning environment with F UTURE W ORLDS, pointing toward the importance of designing game-based learning exhibits that address the distinctive design challenges presented by museum settings. (via Semantic Scholar)
UN Sustainable Development Goal Categories
4. Quality Education (Web of Science)
Source: Web Of Science
Added: August 6, 2018

2017 conference paper

Toward affect-sensitive virtual human tutors: The influence of facial expressions on learning and emotion

International conference on affective computing and intelligent, 184–189.

By: N. Mudrick n, M. Taub n, R. Azevedo n, J. Rowe n & J. Lester n

TL;DR: Results from the study suggest that learners' performance is significantly better when a human tutor agent facially expresses emotions that are congruent with the content relevancy and that learners facially express significantly more confusion when the human tutorAgent provides incongruent facial expressions. (via Semantic Scholar)
UN Sustainable Development Goal Categories
4. Quality Education (OpenAlex)
Source: NC State University Libraries
Added: August 6, 2018

2017 journal article

Using multi-channel data with multi-level modeling to assess in-game performance during gameplay with CRYSTAL ISLAND

COMPUTERS IN HUMAN BEHAVIOR, 76, 641–655.

By: M. Taub n, N. Mudrick n, R. Azevedo n, G. Millar n, J. Rowe n & J. Lester n

author keywords: Cognitive strategies; Metacognitive monitoring; Game-based learning environments; Eye tracking; Log files; Self-regulated learning
TL;DR: This study uses multi-level modeling with data from eye movements and log files to examine the cognitive and metacognitive self-regulatory processes used by 50 college students as they read books and completed the associated in-game assessments (concept matrices) while playing the Crystal Island game-based learning environment. (via Semantic Scholar)
UN Sustainable Development Goal Categories
4. Quality Education (Web of Science; OpenAlex)
Source: Web Of Science
Added: August 6, 2018

2016 journal article

The AIIDE 2015 Workshop Program

AI MAGAZINE, 37(2), 91–94.

By: C. Barot n, M. Buro*, M. Cook*, M. Eladhari*, M. Johansson*, B. Li*, A. Liapis*, J. McCoy* ...

TL;DR: The workshop program at the Eleventh Annual AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment was held November 14-15, 2015 at the University of California, Santa Cruz, USA and included 4 workshops: Artificial Intelligence in Adversarial Real-Time Games, Experimental AI in Games, Intelligent Narrative Technologies and Social Believability in games, and Player Modeling. (via Semantic Scholar)
Source: Web Of Science
Added: August 6, 2018

2016 article

Using Multi-level Modeling with Eye-Tracking Data to Predict Metacognitive Monitoring and Self-regulated Learning with CRYSTAL ISLAND

INTELLIGENT TUTORING SYSTEMS, ITS 2016, Vol. 9684, pp. 240–246.

By: M. Taub n, N. Mudrick n, R. Azevedo n, G. Millar n, J. Rowe n & J. Lester n

author keywords: Metacognition; Self-regulated learning; Game-based learning; Eye tracking; Process data; Scientific reasoning
TL;DR: A study that investigated how college students' eye tracking behavior predicted performance on embedded assessments within the Crystal Island GBLE found that participants strategized when reading book and article content and completing assessments, which led to better performance. (via Semantic Scholar)
UN Sustainable Development Goal Categories
4. Quality Education (Web of Science)
Source: Web Of Science
Added: August 6, 2018

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

Contributors: 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
TL;DR: A framework for stealth assessment that leverages deep learning, a family of machine learning methods that utilize deep artificial neural networks, to infer student competencies in a game-based learning environment for middle grade computational thinking, Engage is presented. (via Semantic Scholar)
UN Sustainable Development Goal Categories
4. Quality Education (Web of Science; OpenAlex)
Sources: Web Of Science, ORCID
Added: August 6, 2018

2014 journal article

A Supervised Learning Framework for Modeling Director Agent Strategies in Educational Interactive Narrative

IEEE TRANSACTIONS ON COMPUTATIONAL INTELLIGENCE AND AI IN GAMES, 6(2), 203–215.

By: S. Lee n, J. Rowe n, B. Mott n & J. Lester n

author keywords: Bayesian networks; interactive drama; machine learning; narrative; serious games
TL;DR: Results indicate that machine-learning director agent strategies from human demonstrations yield models that positively shape players' narrative-centered learning and problem-solving experiences. (via Semantic Scholar)
UN Sustainable Development Goal Categories
4. Quality Education (OpenAlex)
Source: Web Of Science
Added: August 6, 2018

2014 conference paper

Generalizability of goal recognition models in narrative-centered learning environments

User modeling, adaptation, and personalization, umap 2014, 8538, 278–289.

By: A. Baikadi n, J. Rowe n, B. Mott n & J. Lester n

TL;DR: An approach to goal recognition that leverages Markov Logic Networks (MLNs)—a machine learning framework that combines probabilistic inference with first-order logical reasoning—to encode relations between problem-solving goals and discovery events, domain-specific representations of user progress in narrative-centered learning environments is described. (via Semantic Scholar)
UN Sustainable Development Goal Categories
4. Quality Education (OpenAlex)
Source: NC State University Libraries
Added: August 6, 2018

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

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

TL;DR: Results suggest the semi-supervised machine-learning approach to predicting whether students will be successful in solving problem-solving tasks within narrative-centered learning environments often outperforms standard supervised learning methods. (via Semantic Scholar)
UN Sustainable Development Goal Categories
4. Quality Education (OpenAlex)
Sources: NC State University Libraries, ORCID
Added: August 6, 2018

2014 conference paper

Serious games go informal: a museum-centric perspective on intelligent game-based learning

Intelligent tutoring systems, its 2014, 8474, 410–415.

By: J. Rowe n, E. Lobene n, B. Mott n & J. Lester n

TL;DR: Findings from a study investigating the influence of individual differences on learning and engagement in Future Worlds support the promise of intelligent game-based learning environments that dynamically recognize and adapt to learners’ individual differences during museum learning. (via Semantic Scholar)
Source: NC State University Libraries
Added: August 6, 2018

2012 journal article

Reports on the 2011 AAAI Fourth Artificial Intelligence for Interactive Digital Entertainment Conference Workshops

AI MAGAZINE, 33(1), 55–56.

By: D. Elson*, J. Rowe n, A. Smith*, G. Smith* & E. Tomai

TL;DR: The Seventh Artificial Intelligence for Interactive Digital Entertainment Conference (AIIDE-11) was held October 11–14, 2011 at Stanford University, Stanford, California and the highlights of each workshop are presented. (via Semantic Scholar)
Source: Web Of Science
Added: August 6, 2018

conference paper

Affect dynamics in military trainees using vMedic: From engaged concentration to boredom to confusion

Ocumpaugh, J., Andres, J. M., Baker, R., DeFalco, J., Paquette, L., Rowe, J., … Sottilare, R. Artificial intelligence in education, aied 2017, 10331, 238–249.

By: J. Ocumpaugh, J. Andres, R. Baker, J. DeFalco, L. Paquette, J. Rowe, B. Mott, J. Lester ...

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

conference paper

Archetype-driven character dialogue generation for interactive narrative

Rowe, J. P., Ha, E. Y., & Lester, J. C. Intelligent virtual agents, proceedings, 5208, 45–58.

By: J. Rowe, E. Ha & J. Lester

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

conference paper

Balancing learning and engagement in game-based learning environments with multi-objective reinforcement learning

Sawyer, R., Rowe, J., & Lester, J. Artificial intelligence in education, aied 2017, 10331, 323–334.

By: R. Sawyer, J. Rowe & J. Lester

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

conference paper

Improving student problem solving in narrative-centered learning environments: A modular reinforcement learning framework

Rowe, J. P., & Lester, J. C. Artificial intelligence in education, aied 2015, 9112, 419–428.

By: J. Rowe & J. Lester

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

conference paper

Is more agency better? The impact of student agency on game-based learning

Sawyer, R., Smith, A., Rowe, J., Azevedo, R., & Lester, J. Artificial intelligence in education, aied 2017, 10331, 335–346.

By: R. Sawyer, A. Smith, J. Rowe, R. Azevedo & J. Lester

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

conference paper

Off-task behavior in narrative-centered learning environments

Rowe, J. P., McQuiggan, S. W., Robison, J. L., & Lester, J. C. Artificial intelligence in education - building learnning systems that care: from knowledge representation to affective modelling , 200, 99–106.

By: J. Rowe, S. McQuiggan, J. Robison & J. Lester

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

conference paper

Toward affect-sensitive virtual human tutors: The influence of facial expressions on learning and emotion

Mudrick, N. V., Taub, M., Azevedo, R., Rowe, J., & Lester, J. International conference on affective computing and intelligent, 184–189.

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

conference paper

Using multi-level modeling with eye-tracking data to predict metacognitive monitoring and self-regulated learning with CRYSTAL ISLAND

Taub, M., Mudrick, N. V., Azevedo, R., Millar, G. C., Rowe, J., & Lester, J. Intelligent tutoring systems, its 2016, 0684, 240–246.

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

conference paper

Using multi-level modeling with eye-tracking data to predict metacognitive monitoring and self-regulated learning with crystal island

Taub, M., Mudrick, N. V., Azevedo, R., Millar, G. C., Rowe, J., & Lester, J. Intelligent tutoring systems, its 2016, 9684, 240–246.

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

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