Works (29)

Updated: April 4th, 2024 10:28

2023 article

Multimodal CS Education Using a Scaffolded CSCL Environment

PROCEEDINGS OF THE 2023 CONFERENCE ON INNOVATION AND TECHNOLOGY IN COMPUTER SCIENCE EDUCATION, ITICSE 2023, VOL. 2, pp. 645–645.

By: R. Monahan n, J. Vandenberg n, A. Gupta n, A. Smith n, R. Elsayed*, K. Fox*, A. Cheuoua*, C. Ringstaff* ...

TL;DR: The approach to integrating virtual and physical learning modalities into InfuseCS, a CSCL environment for upper elementary school students to foster their computational thinking and science knowledge construction as they collaborate to create digital narratives is presented. (via Semantic Scholar)
UN Sustainable Development Goal Categories
4. Quality Education (Web of Science; OpenAlex)
Sources: Web Of Science, NC State University Libraries, ORCID
Added: June 30, 2023

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, NC State University Libraries
Added: August 2, 2021

2021 article

Modeling Frustration Trajectories and Problem-Solving Behaviors in Adaptive Learning Environments for Introductory Computer Science

ARTIFICIAL INTELLIGENCE IN EDUCATION (AIED 2021), PT II, Vol. 12749, pp. 355–360.

author keywords: Frustration trajectory; Adaptive learning environments; Problem-solving behavior; Computer science education; Block-based programming
Sources: Web Of Science, NC State University Libraries
Added: November 28, 2022

2021 conference paper

Progression Trajectory-Based Student Modeling for Novice Block-Based Programming

Proceedings of the 29th ACM Conference on User Modeling, Adaptation and Personalization.

TL;DR: It is suggested that progression trajectory-based student models can accurately model students’ block-based programming problem solving and hold potential for informing adaptive support in block- based programming environments. (via Semantic Scholar)
UN Sustainable Development Goal Categories
4. Quality Education (OpenAlex)
Source: ORCID
Added: October 5, 2021

2020 conference paper

Cluster-Based Analysis of Novice Coding Misconceptions in Block-Based Programming

Proceedings of the 51st ACM Technical Symposium on Computer Science Education.

Andy Smith

author keywords: Block-based programming; introductory programming education; cluster analysis
TL;DR: This paper identifies three families of student misconceptions and discusses their implications for refinement of the activities as well as design of future activities in a block-based programming environment for introductory computer science education. (via Semantic Scholar)
UN Sustainable Development Goal Categories
4. Quality Education (Web of Science; OpenAlex)
Source: ORCID
Added: April 17, 2020

2020 conference paper

Designing Block-Based Programming Language Features to Support Upper Elementary Students in Creating Interactive Science Narratives

Proceedings of the 51st ACM Technical Symposium on Computer Science Education.

Andy Smith

author keywords: Digital storytelling; Block-based programming
TL;DR: This work proposes the design of block-based programming language features to enable the creation of rich, interactive science narratives by upper elementary students in order to enable effective and engaging storytelling. (via Semantic Scholar)
UN Sustainable Development Goal Categories
4. Quality Education (Web of Science; OpenAlex)
Source: ORCID
Added: April 17, 2020

2020 conference paper

Predictive Student Modeling in Block-Based Programming Environments with Bayesian Hierarchical Models

Proceedings of the 28th ACM Conference on User Modeling, Adaptation and Personalization.

Andy Smith

TL;DR: Evaluation results reveal that predictive student models that account for both the distributional and hierarchical factors outperform baseline models and suggest that Bayesian hierarchical modeling and representing individual differences in students can substantially improve models' accuracy for predicting student performance on post-tests. (via Semantic Scholar)
UN Sustainable Development Goal Categories
4. Quality Education (OpenAlex)
Source: ORCID
Added: September 8, 2020

2020 journal article

The agency effect: The impact of student agency on learning, emotions, and problem-solving behaviors in a game-based learning environment

Computers and Education, 147.

By: M. Taub*, R. Sawyer n, A. Smith n, J. Rowe n, R. Azevedo* & J. Lester n

Contributors: M. Taub*, R. Sawyer n, A. Smith n, J. Rowe n, R. Azevedo* & J. Lester n

author keywords: Agency in learning; Game-based learning; Learner-centered emotions; Self-regulated learning
TL;DR: A moderate degree of agency provided to students in game- based learning environments leads to better learning outcomes without sacrificing interest and without yielding a negative emotional experience, demonstrating how even low levels of agency can positively impact learning, problem solving, and affect during game-based learning. (via Semantic Scholar)
UN Sustainable Development Goal Categories
4. Quality Education (Web of Science; OpenAlex)
Source: ORCID
Added: February 19, 2020

2020 conference paper

Toward a Block-Based Programming Approach to Interactive Storytelling for Upper Elementary Students

Interactive Storytelling, 111–119.

UN Sustainable Development Goal Categories
4. Quality Education (OpenAlex)
Source: ORCID
Added: October 27, 2020

2019 journal article

A Multimodal Assessment Framework for Integrating Student Writing and Drawing in Elementary Science Learning

IEEE Transactions on Learning Technologies, 12(1), 3–15.

By: A. Smith n, S. Leeman-Munk*, A. Shelton n, B. Mott n, E. Wiebe n & J. Lester n

Contributors: A. Smith n, S. Leeman-Munk*, A. Shelton n, B. Mott n, E. Wiebe n & J. Lester n

author keywords: Intelligent tutoring systems; formative assessment; multimodal assessment; student writing analysis; student drawing analysis
TL;DR: A framework for the multimodal automated assessment of students’ writing and drawing to leverage the synergies inherent across modalities and create a more complete and accurate picture of a student's knowledge is proposed. (via Semantic Scholar)
UN Sustainable Development Goal Categories
4. Quality Education (Web of Science; OpenAlex)
Sources: Web Of Science, NC State University Libraries, ORCID, Crossref
Added: May 6, 2019

2019 journal article

Construction and Validation of an Anticipatory Thinking Assessment

FRONTIERS IN PSYCHOLOGY, 10.

By: M. Geden n, A. Smith n, J. Campbell n, R. Spain n, A. Amos-Binks*, B. Mott n, J. Feng n, J. Lester n

Contributors: M. Geden n, A. Smith n, J. Campbell n, R. Spain n, A. Amos-Binks*, B. Mott n, J. Feng n, J. Lester n

author keywords: anticipatory thinking; prospective cognition; divergent thinking; assessment development; validation
TL;DR: The findings suggest that the ANTA is a psychometrically valid instrument that may help researchers investigate anticipatory thinking in new contexts and explore the relationship between theANTA scores and certain psychological traits and cognitive measures (need for cognition, need for closure, and mindfulness). (via Semantic Scholar)
UN Sustainable Development Goal Categories
4. Quality Education (Web of Science)
10. Reduced Inequalities (OpenAlex)
Sources: Web Of Science, NC State University Libraries, ORCID
Added: January 13, 2020

2019 journal article

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

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

Contributors: 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
TL;DR: DeepStealth is presented, a deep learning-based stealth assessment framework that yields significant reductions in the feature engineering labor that has previously been required to create stealth assessments and uses end-to-end trainable deep neural network-based evidence models. (via Semantic Scholar)
Sources: ORCID, Crossref, NC State University Libraries
Added: February 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.

TL;DR: IntelliBlox is presented, a Blockly-inspired toolkit for the Unity cross-platform game engine that enables learners to create block-based programs within immersive game-based learning environments. (via Semantic Scholar)
Source: ORCID
Added: February 19, 2020

2019 conference paper

Prime: Engaging STEM undergraduates in computer science with intelligent tutoring systems

ASEE Annual Conference and Exposition, Conference Proceedings. http://www.scopus.com/inward/record.url?eid=2-s2.0-85078800967&partnerID=MN8TOARS

By: J. Lester, K. Boyer, E. Wiebe, B. Mott & A. Smith

Contributors: J. Lester, K. Boyer, E. Wiebe, B. Mott & A. Smith

Source: ORCID
Added: February 19, 2020

2019 conference paper

Toward a Responsive Interface to Support Novices in Block-Based Programming

Proceedings - 2019 IEEE Blocks and Beyond Workshop, B and B 2019, 9–13.

By: F. Rodriguez*, C. Smith n, A. Smith n, K. Boyer*, E. Wiebe n, B. Mott n, J. Lester n

Contributors: F. Rodriguez*, C. Smith n, A. Smith n, K. Boyer*, E. Wiebe n, B. Mott n, J. Lester n

TL;DR: The early design and piloting of Prime, a learning environment under development that provides scaffolded support for novices in block-based programming, and analysis of students’ code quality showed that students in the responsive condition achieved higher quality code in later programming tasks. (via Semantic Scholar)
UN Sustainable Development Goal Categories
4. Quality Education (Web of Science; OpenAlex)
Source: ORCID
Added: February 19, 2020

2018 conference paper

Enhancing complex mathematics problem solving through learning by teaching with a teachable agent

IMSCI 2018 - 12th International Multi-Conference on Society, Cybernetics and Informatics, Proceedings, 2, 31–36. http://www.scopus.com/inward/record.url?eid=2-s2.0-85056509594&partnerID=MN8TOARS

By: C. Psaradellis, K. Muis, A. Smith & S. Lajoie

Contributors: C. Psaradellis, K. Muis, A. Smith & S. Lajoie

Source: ORCID
Added: February 19, 2020

2018 article

Towards Adaptive Support for Anticipatory Thinking

PROCEEDINGS OF THE TECHNOLOGY, MIND, AND SOCIETY CONFERENCE (TECHMINDSOCIETY'18).

By: M. Geden n, A. Smith n, J. Campbell n, A. Amos-Binks n, B. Mott n, J. Feng n, J. Lester n

author keywords: Anticipatory thinking; cognitive process; assessment; training; adaptive technology
TL;DR: A task to measure anticipatory thinking is developed in which participants explore uncertainties and the impacts on the future given a particular topic and design principles for supporting training, application, and assessment of anticipateatory thinking are introduced. (via Semantic Scholar)
UN Sustainable Development Goal Categories
16. Peace, Justice and Strong Institutions (OpenAlex)
Sources: Web Of Science, NC State University Libraries
Added: November 18, 2019

2017 conference paper

Enhancing student models in game-based learning with facial expression recognition

UMAP 2017 - Proceedings of the 25th Conference on User Modeling, Adaptation and Personalization, 192–201.

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

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

author keywords: Student Modeling; Affect; Game-based Learning
TL;DR: The study found that models based on individual facial action coding units are more effective than composite emotion models, and suggests that introducing facial expression tracking can improve the accuracy of student models, both for predicting student learning gains and also for predictingStudent engagement. (via Semantic Scholar)
UN Sustainable Development Goal Categories
4. Quality Education (OpenAlex)
Source: ORCID
Added: February 19, 2020

2017 chapter

Is More Agency Better? The Impact of Student Agency on Game-Based Learning

In Lecture Notes in Computer Science: Vol. 10331 LNAI (pp. 335–346).

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

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

author keywords: Game-based learning; Student agency; Problem-solving behavior
TL;DR: Results indicate that students in the Low Agency condition achieved greater learning gains than students in both the High Agency and No Agency conditions, but exhibited more unproductive behaviors, suggesting that artfully striking a balance between high and low agency best supports learning. (via Semantic Scholar)
Sources: ORCID, Crossref
Added: February 19, 2020

2016 journal article

Drawing and Writing in Digital Science Notebooks: Sources of Formative Assessment Data

Journal of Science Education and Technology, 25(3), 474–488.

By: A. Shelton n, A. Smith n, E. Wiebe n, C. Behrle n, R. Sirkin n & J. Lester n

Contributors: A. Shelton n, A. Smith n, E. Wiebe n, C. Behrle n, R. Sirkin n & J. Lester n

author keywords: Science education; Elementary grades; Digital science notebooks; Drawing; Writing; Magnetism
UN Sustainable Development Goal Categories
4. Quality Education (Web of Science; OpenAlex)
Sources: ORCID, Crossref, NC State University Libraries
Added: February 19, 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

Contributors: 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
TL;DR: This work utilizes ECD to analyze a corpus of elementary student writings and drawings collected with a digital science notebook and reveals that ECD provides an expressive unified framework for multimodal assessment of science learning with accurate predictions of student learning. (via Semantic Scholar)
UN Sustainable Development Goal Categories
4. Quality Education (Web of Science; OpenAlex)
Sources: Web Of Science, NC State University Libraries, 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

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

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

author keywords: Student modeling; Intelligent tutoring systems; Deep learning
TL;DR: The diagrammatic student modeling framework utilizes deep learning, a family of machine learning methods based on a deep neural network architecture, to reason about sequences of student drawing actions encoded with temporal and topological features. (via Semantic Scholar)
Sources: ORCID, Crossref
Added: February 19, 2020

2015 article

Two Modes Are Better Than One: A Multimodal Assessment Framework Integrating Student Writing and Drawing

ARTIFICIAL INTELLIGENCE IN EDUCATION, AIED 2015, Vol. 9112, pp. 205–215.

By: S. Leeman-Munk n, A. Smith n, B. Mott n, E. Wiebe n & J. Lester n

Contributors: S. Leeman-Munk n, A. Smith n, B. Mott n, E. Wiebe n & J. Lester n

author keywords: Formative assessment; Multimodal assessment; Student writing analysis; Student sketch analysis
TL;DR: This paper introduces a novel multimodal assessment framework that integrates two techniques for automatically analyzing student artifacts: a deep learning-based model for assessing student writing, and a topology-based models for assessingStudent drawing. (via Semantic Scholar)
UN Sustainable Development Goal Categories
4. Quality Education (Web of Science; OpenAlex)
Sources: Web Of Science, NC State University Libraries, ORCID
Added: August 6, 2018

2012 conference paper

A glove for tapping and discrete 1D/2D input

International Conference on Intelligent User Interfaces, Proceedings IUI, 101–104.

By: S. Miller*, A. Smith n, S. Bahram n & R. St. Amant n

Contributors: S. Miller*, A. Smith n, S. Bahram n & R. St. Amant n

TL;DR: A glove with which users enter input by tapping fingertips with the thumb or by rubbing the thumb over the palmar surfaces of the middle and index fingers is described. (via Semantic Scholar)
Source: ORCID
Added: February 19, 2020

1999 journal article

P-methylstyrene

Polymer Data Handbook, 688–695.

By: A. Smith & R. Spontak

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

1998 journal article

Statistical properties of fitted estimates of apparent in vivo metabolic constants obtained from gas uptake data. I. Lipophilic and slowly metabolized VOCs

Inhalation Toxicology, 10(5), 383–409.

By: A. Smith, M. Evans & M. Davidian

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

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

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

Employment

Updated: September 7th, 2020 16:17

2017 - present

North Carolina State University Raleigh, NC, US
Research Scholar Computer Science

2009 - 2009

Alcatel-Lucent Raleigh, NC, US
Firmware Engineer

2005 - 2009

Space and Naval Warfare Systems Center Pacific San Diego, CA, US
Robotics Engineer Unmanned Maritime Vehicle Laboratory

Education

Updated: September 7th, 2020 16:17

2016 - 2020

North Caolina State University Raleigh, NC, US
PhD Computer Science

2010 - 2016

North Carolina State University Raleigh, NC, US
MS Computer Science

2001 - 2005

Duke University Durham, NC, US
BSE Electrical Engineering and Computer Science

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