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Death to Online Discussion Boards: How AI Is Making Discussion Boards Obsolete
- The Scholarly Teacher
- Aug 15
- 4 min read
Oren Hertz, Florida International University; Scholarly Teacher Editorial Board
Key Statement: Academic institutions must reconsider the use of discussion boards as a form of assessment and adopt more authentic, AI-resilient methods that reflect the realities of modern technological capabilities.
Keywords: Digital Pedagogy, Artificial Intelligence, Resilient Assessment
Introduction
Online discussion boards were once heralded as a breakthrough in digital learning— spaces where students could engage in thoughtful dialogue, reflect on course content, and build community asynchronously. However, the educational landscape has shifted dramatically with the advent of generative AI tools like ChatGPT, Claude, and others. These tools can produce high-quality, contextually appropriate discussion posts in seconds, undermining the original intent of fostering critical thinking and authentic student engagement.
The Rise of AI and the Fall of Authenticity
Generative AI has democratized access to sophisticated writing assistance. Although inexpensive or free advanced writing assistance can be empowering, it also introduces significant challenges to academic integrity. Students can now generate entire discussion posts and peer responses with minimal effort, often bypassing the cognitive processes that these assignments were designed to stimulate (Cotton et al., 2023). Research shows that AI-generated content is increasingly indistinguishable from human writing, making detection difficult and unreliable.
Across a variety of writing assignments completed by students, AI detection tools have proven to be inconsistent and biased, particularly against non-native English speakers. This has led some institutions, such as Vanderbilt University, to disable AI detectors altogether due to concerns about false positives and
ethical implications (EDUCAUSE, 2023). In this context, relying on discussion boards as a measure of student learning becomes not only ineffective but potentially unjust.
The Pedagogical Problem
The core issue is not that students are using AI, but that the format of discussion boards is ill-suited to an AI-saturated environment. These boards were designed for a different era—one in which students were expected to write reflectively and engage with peers in a meaningful way. Today, many students view them as perfunctory tasks, easily outsourced to AI tools. This shift erodes the pedagogical value of the exercise and reduces it to a box-checking activity.
Furthermore, the asynchronous nature of discussion boards often leads to superficial engagement. Students post once to meet a deadline and respond to peers out of obligation rather than genuine interest. The result is a diluted learning experience that fails to foster deep understanding or critical discourse (Hew & Cheung, 2012).
Institutional Inertia and the Need for Change
Despite these challenges, many institutions continue to mandate discussion boards, often as a default component of Learning Management Systems (LMSs). This persistence reflects institutional inertia rather than pedagogical efficacy. As AI continues to evolve, clinging to outdated assessment methods risks compromising the credibility and relevance of higher education (Selwyn, 2023).
Institutions must recognize that the landscape of student learning has changed. Just as we no longer rely on overhead projectors or dial-up internet, we must also retire the discussion board as a primary tool for learning assessment. This is not a call to abandon online learning, but to innovate within it.
Toward AI-Resilient Assessment
The solution lies in reimagining assessment strategies to prioritize authenticity, creativity, and critical thinking—skills that students must still possess, and that AI, however convincing, cannot transfer to students. Some promising alternatives include:
Oral assessments: Live or recorded presentations and interviews that require students to articulate their understanding in real time.
Project-based learning: Collaborative, real-world tasks that emphasize process over product.
Reflective journals: Personal reflections that connect course content to individual experiences.
Peer teaching: Assignments where students explain concepts to others, demonstrating mastery through instruction.
These methods not only reduce the likelihood of AI misuse but also align more closely with the skills students need in the workforce (Zawacki-Richter et al., 2019).
Ethical and Cultural Considerations
The integration of AI into education is not merely a technical issue—it is a cultural and ethical one. As EDUCAUSE notes, institutions must lead with clear principles that align AI use with academic values. This includes fostering transparency, promoting equity, and ensuring that assessments reflect genuine learning rather than technological savvy.
By continuing to rely on discussion boards, institutions risk sending the message that surface-level engagement is sufficient. In contrast, embracing new forms of assessment signals a commitment to meaningful education in a rapidly changing world.
Conclusion
The time has come to declare the death of the online discussion board. In an era where AI can generate thoughtful posts in seconds, the format no longer serves its intended purpose. Academic institutions must evolve, adopting assessment methods that are resistant to automation and rooted in authentic learning. Only then can we ensure that education remains a space for genuine intellectual growth.
References
Cotton, D. R. E., Cotton, P. A., & Shipway, J. R. (2023). Chatting and cheating? Exploring the potential impact of ChatGPT on higher education assessment. Assessment & Evaluation in Higher Education, 48(2), 292–304.
EDUCAUSE. (2023). 7 things you should know about generative AI. https://library.educause.edu/resources/2023/12/7-things-you-should-know-about generative-ai
Hew, K. F., & Cheung, W. S. (2012). Student participation in online discussions: Challenges, solutions, and future research. Educational Research Review, 7(1), 1–15. https://doi.org/10.1016/j.edurev.2011.11.001
Selwyn, N. (2023). Should robots replace teachers? AI and the future of education. Polity Press.
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), 1–27. https://doi.org/10.1186/s41239-019-0171-0
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