Works (24)
Updated: April 15th, 2024 08:54
2022 article
"I remember how to do it": exploring upper elementary students' collaborative regulation while pair programming using epistemic network analysis
Vandenberg, J., Lynch, C., Boyer, K. E., & Wiebe, E. (2022, March 11). COMPUTER SCIENCE EDUCATION, Vol. 3.
author keywords: Elementary school; pair programming; attitudes; self-efficacy; academic regulation
TL;DR:
It is suggested that upper elementary students learn about productive disagreement and how to peer model and a range of ways the dyads’ self-efficacy and CS conceptual understanding affected their collaborative and regulated discourse.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
4. Quality Education
(Web of Science)
Sources: Web Of Science, ORCID, NC State University Libraries
Added: March 11, 2022
2022 article
It's Challenging but Doable: Lessons Learned from a Remote Collaborative Coding Camp for Elementary Students
PROCEEDINGS OF THE 53RD ACM TECHNICAL SYMPOSIUM ON COMPUTER SCIENCE EDUCATION (SIGCSE 2022), VOL 1, pp. 342–348.
author keywords: Elementary CS; Remote Learning; Collaborative Learning
UN Sustainable Development Goal Categories
4. Quality Education
(Web of Science)
Sources: Web Of Science, NC State University Libraries
Added: December 12, 2022
2022 journal article
Two-Computer Pair Programming: Exploring a Feedback Intervention to improve Collaborative Talk in Elementary Students.
COMPUTER SCIENCE EDUCATION, 32(1), 3–29.
author keywords: Pair programming; collaboration; elementary school; feedback; intervention
TL;DR:
This study employs an intervention to explore the role instructor-directed feedback plays on elementary students’ dyadic collaboration during 2-computer pair programming and highlights ways to support students in pair programming contexts so that they can maximize the benefits afforded through these experiences.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
4. Quality Education
(Web of Science)
Sources: Web Of Science, ORCID, NC State University Libraries
Added: February 5, 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 article
Prompting collaborative and exploratory discourse: An epistemic network analysis study
Vandenberg, J., Zakaria, Z., Tsan, J., Iwanski, A., Lynch, C., Boyer, K. E., & Wiebe, E. (2021, August 7). INTERNATIONAL JOURNAL OF COMPUTER-SUPPORTED COLLABORATIVE LEARNING, Vol. 8.
author keywords: Epistemic network analysis; Primary grades; Discourse; Pair programming; Collaboration
TL;DR:
An easy-to-implement prompting intervention in the context of collaborative (pair) programming with upper elementary students to demonstrate the potential of ENA was found that intervention students—those given empirically-derived prompts in support of collaborative and exploratory talk—asked questions, justified their thinking, and offered alternative ideas in ways that were both qualitatively and quantitatively different from control students.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
4. Quality Education
(Web of Science)
Sources: Web Of Science, NC State University Libraries
Added: August 16, 2021
2021 article
The Challenge of Noisy Classrooms: Speaker Detection During Elementary Students' Collaborative Dialogue
ARTIFICIAL INTELLIGENCE IN EDUCATION (AIED 2021), PT I, Vol. 12748, pp. 268–281.
author keywords: Adaptive and intelligent collaborative learning support; Classroom environment; Speaker detection; Multimodal learning
TL;DR:
A multimodal method to identify speakers by using visual and acoustic features from ten video recordings of children pairs collaborating in an elementary school classroom indicates that the visual modality was better for identifying the speaker when in-group speech was detected, while the acoustic modality was better for differentiating in-group speech from background speech.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
4. Quality Education
(OpenAlex)
Sources: Web Of Science, NC State University Libraries
Added: November 28, 2022
2020 journal article
Elementary Students' Understanding of CS Terms
ACM TRANSACTIONS ON COMPUTING EDUCATION, 20(3).
author keywords: Cognitive interviewing; elementary; computer science; instrument development
TL;DR:
The refinement of a validated survey to measure upper elementary students’ attitudes and perspectives about computer science (CS) indicated that students could not explain the terms computer programs nor computer science as expected, and struggled to understand how coding may support their learning in other domains.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
4. Quality Education
(Web of Science; OpenAlex)
Sources: Web Of Science, NC State University Libraries
Added: October 26, 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.
author keywords: Conversational pedagogical agent; Multimodal; Dialogue breakdown detection; Natural language processing; Gaze
TL;DR:
Results from a study with 92 middle school students demonstrate that multimodal long short-term memory network (LSTM)-based dialogue breakdown detectors incorporating eye gaze features achieve high predictive accuracies and recall rates, suggesting that multi-modal detectors can play an important role in designing conversational pedagogical agents that effectively engage students in dialogue.
(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: 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.
Contributors: J. Wiggins*, M. Kulkarni*, W. Min n , *, B. Mott n, E. Wiebe n , J. Lester n
author keywords: Pedagogical agents; Game-based learning; Initiative
TL;DR:
A study to investigate two different agent dialogue policies with regard to conversational initiative, a core consideration in dialogue system design found the Mixed Initiative policy better supported the goals of the game-based learning environment by fostering exploration, yielding better performance on in-game assessments, and creating higher student engagement.
(via Semantic Scholar)
Sources: Web Of Science, NC State University Libraries, ORCID
Added: December 2, 2019
2018 article
"I Think We Should...": Analyzing Elementary Students' Collaborative Processes for Giving and Taking Suggestions
SIGCSE'18: PROCEEDINGS OF THE 49TH ACM TECHNICAL SYMPOSIUM ON COMPUTER SCIENCE EDUCATION, pp. 622–627.
author keywords: Elementary school; pair programming; collaboration; dialogue
TL;DR:
It is found that students regularly accept or reject suggestions without explanation or explicit acknowledgement and that it is often unclear whether they understand the substance of the suggestion, which may inhibit the development of a shared understanding between the partners and limit the value of the collaborative process.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
4. Quality Education
(Web of Science)
Source: Web Of Science
Added: September 16, 2019
2018 article
Infusing Computational Thinking into Middle Grade Science Classrooms: Lessons Learned
WIPSCE'18: PROCEEDINGS OF THE 13TH WORKSHOP IN PRIMARY AND SECONDARY COMPUTING EDUCATION, pp. 109–114.
Contributors: V. Cateté n , N. Lytle n, Y. Dong n, D. Boulden n , B. Akram n, J. Houchins n, T. Barnes n, E. Wiebe n
author keywords: Professional Development; STEM plus C; Computational Thinking
TL;DR:
Initial lessons learned while conducting design-based implementation research on integrating computational thinking into middle school science classes are presented and case studies suggest that several factors including teacher engagement, teacher attitudes, student prior experience with CS/CT, and curriculum design can all impact student engagement in integrated science-CT lessons.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
4. Quality Education
(Web of Science)
Sources: Web Of Science, NC State University Libraries, ORCID
Added: January 28, 2019
2018 conference paper
Introducing the Computer Science Concept of Variables in Middle School Science Classrooms
Proceedings of the 49th ACM Technical Symposium on Computer Science Education - SIGCSE '18, 906–911.
Event: the 49th ACM Technical Symposium
author keywords: Middle school; Computational Thinking; Science classrooms
TL;DR:
This position paper makes a case for introducing the concept of variables in the context of middle school science in a way that can benefit students' learning of both computer science and core science content.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
4. Quality Education
(Web of Science; OpenAlex)
Sources: Web Of Science, NC State University Libraries, Crossref
Added: September 16, 2019
2017 journal article
Preface for the Special Issue on AI-Supported Education in Computer Science
INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE IN EDUCATION, 27(1), 1–4.
TL;DR:
Computer science has gone beyond an important skill required for a wide range of modern professions, to become an essential competence for everyday life and a very dynamic domain, where technologies, skills and even subfields are constantly emerging and evolving, challenging CS education researchers to find ways to promote effective education.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
4. Quality Education
(Web of Science; OpenAlex)
Source: Web Of Science
Added: August 6, 2018
2015 conference paper
A Tutorial dialogue system for real-time evaluation of unsupervised dialogue act classifiers: Exploring system outcomes
Artificial intelligence in education, aied 2015, 9112, 105–114.
Source: NC State University Libraries
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.
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, NC State University Libraries, ORCID
Added: August 6, 2018
2015 conference paper
Discovering individual and collaborative problem-solving modes with hidden Markov models
Artificial intelligence in education, aied 2015, 9112, 408–418.
Source: NC State University Libraries
Added: August 6, 2018
2015 conference paper
Leveraging collaboration to improve gender equity in a game-based learning environment for middle school computer science
2015 Research in Equity and Sustained Participation in Engineering, Computing, and Technology (RESPECT).
TL;DR:
Evidence is presented that a collaborative gameplay approach may, over time, compensate for gender differences in experience and lead to equitable learning experiences within game-based learning environments for computer science education.
(via Semantic Scholar)
Sources: NC State University Libraries, NC State University Libraries
Added: August 6, 2018
2015 article
Mind the Gap: Improving Gender Equity in Game-Based Learning Environments with Learning Companions
ARTIFICIAL INTELLIGENCE IN EDUCATION, AIED 2015, Vol. 9112, pp. 64–73.
author keywords: Learning companions; Game-based learning; Gender
TL;DR:
A prototype learning companion designed specifically to reduce frustration through the telling of autobiographical stories is developed, suggesting that introducing learning companions can directly contribute to making the benefits of game-based learning equitable for all learners.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
4. Quality Education
(Web of Science)
Sources: Web Of Science, NC State University Libraries
Added: August 6, 2018
2015 conference paper
Supporting K-5 learners with dialogue systems
Artificial intelligence in education, aied 2015, 9112, 873–876.
Source: NC State University Libraries
Added: August 6, 2018
2015 conference paper
The Mars and Venus effect: The influence of user gender on the effectiveness of adaptive task support
User modeling, adaptation and personalization, 9146, 265–276.
Source: NC State University Libraries
Added: August 6, 2018
2014 conference paper
Identifying effective moves in tutoring: On the refinement of dialogue act annotation schemes
Intelligent tutoring systems, its 2014, 8474, 199–209.
Source: NC State University Libraries
Added: August 6, 2018
2013 article
Automatically Recognizing Facial Indicators of Frustration: A Learning-Centric Analysis
2013 HUMAINE ASSOCIATION CONFERENCE ON AFFECTIVE COMPUTING AND INTELLIGENT INTERACTION (ACII), pp. 159–165.
author keywords: affect; frustration; learning; computer-mediated tutoring; facial expression recognition; facial action units; intensity
TL;DR:
A study to analyze a video corpus of computer-mediated human tutoring using an automated facial expression recognition tool that detects fine-grained facial movements reveals three significant relationships between facial expression, frustration, and learning.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
4. Quality Education
(OpenAlex)
Sources: Web Of Science, NC State University Libraries
Added: August 6, 2018
2012 conference paper
Multimodal analysis of the implicit affective channel in computer-mediated textual communication
ICMI '12: Proceedings of the ACM International Conference on Multimodal Interaction, 145–152.
TL;DR:
Computer-mediated tutoring sessions were recorded with Kinect video and depth images and processed with novel tracking techniques for posture and hand-to-face gestures and it was demonstrated that tutors implicitly perceived students' focused attention, physical demand, and frustration.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
4. Quality Education
(OpenAlex)
Source: NC State University Libraries
Added: August 6, 2018
conference paper
Modeling self-efficacy across age groups with automatically tracked facial expression
Grafsgaard, J. F., Lee, S. Y., Mott, B. W., Boyer, K. E., & Lester, J. C. Artificial intelligence in education, aied 2015, 9112, 582–585.
Source: NC State University Libraries
Added: August 6, 2018
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