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Using AI Chat Assistants to Enhance Online Discussions Boards

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Roundtable presentation
Research Paper
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Session description

This presentation examines the integration of AI chat assistants in online discussions. Using mixed-methods data from 30 students at The Citadel, findings reveal how AI supports clarity, engagement, and critical reflection while raising questions about authenticity, over-reliance, and the balance between human and machine presence in learning.

Framework

This research is grounded in Vygotsky’s Social Constructivism and the Community of Inquiry (CoI) framework. Social Constructivism emphasizes learning through interaction and scaffolding, while CoI highlights cognitive, social, and teaching presence in online environments. Together, they frame AI as a mediational tool that supports collaboration, reflection, and deeper learning.

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Methods

This mixed-methods study examined how AI chat assistants influenced engagement, clarity, and critical thinking in graduate-level online discussions. Participants included 30 graduate students enrolled in The Citadel’s principal preparation program. Selection was based on full course enrollment during the term in which AI-supported discussion boards were implemented.

Design and Instruments:
Data were collected through a 29-item Likert-scale survey and open-ended interview questions. The survey measured perceptions of engagement, motivation, writing clarity, critical thinking, collaboration, and concerns about over-reliance on AI. Items used a five-point scale (1 = Strongly Disagree to 5 = Strongly Agree). The qualitative component invited participants to describe their experiences, perceived benefits, and challenges using AI in discussion forums.

Data Collection and Procedure:
Students used AI chat assistants (e.g., ChatGPT) to brainstorm ideas, refine writing, and generate questions during online discussions. Faculty clarified that AI was to supplement—not replace—authentic participation. Surveys were administered at the end of the term, followed by optional written interviews.

Analysis:
Quantitative data were analyzed using descriptive statistics (means, standard deviations, and frequency distributions). Qualitative data underwent **inductive thematic coding**, with two researchers independently identifying themes such as enhanced confidence, improved clarity, critical reflection, and concerns about authenticity. Triangulation across data sources strengthened validity and ensured alignment between quantitative trends and qualitative insights.

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Results

Here’s a concise, proposal-ready response describing your study’s results:

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Results indicate that graduate students viewed AI chat assistants as valuable tools for improving clarity, organization, and engagement in online discussions. Quantitative data showed high agreement in writing support and motivation, while qualitative findings revealed increased confidence and reflection. However, students also expressed concerns about authenticity, over-reliance, and diminished peer interaction—highlighting the need for balanced, ethical integration of AI in graduate learning.

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Importance

This study addresses a critical gap in understanding how AI influences teaching and learning in graduate education. By examining real student experiences, it offers evidence-based insights into how AI can enhance engagement and reflection while preserving authenticity. Conference audiences will gain practical strategies for responsibly integrating AI into meaningful, equity-driven learning environments.

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References

Baidoo-Anu, D., & Owusu Ansah, L. (2023). Education in the era of generative artificial intelligence: Understanding the potential benefits of ChatGPT in promoting teaching and learning. Learning: Research and Practice, 9(1), 1–13. https://doi.org/10.1080/23735082.2023.2200144
Darabi, A., Arrastia, M. C., Nelson, D. W., Cornille,

T., & Liang, X. (2013). Cognitive presence in asynchronous online learning: A comparison of four discussion strategies. Journal of Computer Assisted Learning, 29(4), 314–329. https://doi.org/10.1111/jcal.12005

Garrison, D. R., Anderson, T., & Archer, W. (2000). Critical inquiry in a text-based environment: Computer conferencing in higher education. The Internet and Higher Education, 2(2–3), 87–105. https://doi.org/10.1016/S1096-7516(00)00016-6

Holmes, W., Porayska-Pomsta, K., Holstein, K., Sutherland, E., Baker, T., & Russell, S. (2022). Ethics of AI in education: Towards a community-wide framework. British Journal of Educational Technology, 53(3), 331–348. https://doi.org/10.1111/bjet.13141

Hou, H. T., & Wu, S. Y. (2011). Analyzing the social knowledge construction process of computer gaming for learning. Computers & Education, 57(1), 224–238. https://doi.org/10.1016/j.compedu.2010.11.005

Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., & Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103, 102274. https://doi.org/10.1016/j.lindif.2023.102274
Luckin, R. (2021). AI for school teachers. Routledge. https://doi.org/10.4324/9781003002581

Selwyn, N. (2023). Generative AI in education: What are the opportunities and risks? Learning, Media and Technology, 48(3), 295–301. https://doi.org/10.1080/17439884.2023.2203149

Thomas, M. J. W. (2013). Learning within incoherent structures: The space of online discussion forums. Journal of Computer Assisted Learning, 19(3), 351–366. https://doi.org/10.1046/j.0266-4909.2003.00036.x

Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. Harvard University Press. https://doi.org/10.2307/j.ctvjf9vz4

Zawacki-Richter, O., Marín, V. I., Bond, M., &
Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education – where are the educators? International Journal of Educational Technology in Higher Education, 16(1), 39. https://doi.org/10.1186/s41239-019-0171-0

Zhang, D., & Aslan, B. (2023). Exploring the potential of ChatGPT in supporting higher education learning and teaching: A preliminary study. Smart Learning Environments, 10(1), 1–14. https://doi.org/10.1186/s40561-023-00237-4

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Presenters

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Assistant Professor
The Citadel
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Associate Professor
The Citadel

Session specifications

Topic:

Leadership

Grade level:

Community College/University

Audience:

District-Level Leadership, School Level Leadership

Attendee devices:

Devices not needed

ISTE Standards:

For Education Leaders: Empowering Leader
For Students: Empowered Learner, Creative Communicator

Transformational Learning Principles:

Connect Learning to Learner, Elevate Reflection