Embracing AI in Distance Learning: Challenges, Leadership, and Solutions
by Dr. Anton Gates
November 09, 2024
(OpenAI, 2024)
As artificial intelligence continues to evolve and permeate various sectors, its impact on education, particularly online learning, is profound. While AI offers tremendous potential to personalize learning and enhance educational experiences, it also introduces challenges around leadership, academic integrity, and institutional adaptability. Online universities must embrace the technological capabilities of AI while also overcoming leadership deficits and policy gaps that hinder effective integration. This article explores how AI can reshape distance learning, the leadership required to navigate these transformations, and practical strategies to ensure institutions thrive in an AI-driven educational landscape.
AI-Enhanced Personalized Learning: Unlocking Individualized Student Potential
One of the most promising uses of AI in distance learning is its potential for personalization. AI-driven adaptive learning platforms can tailor educational content to meet each student's specific needs, identifying areas of weakness and focusing on those while allowing more proficient learners to advance at their own pace (Shear et al., 2023). This individualized approach can make distance learning feel more interactive and engaging, addressing one of the long-standing challenges of traditional online education: a lack of real-time, responsive support for learners. By integrating AI to offer personalized learning paths, institutions can create a dynamic educational environment where students feel more connected to the curriculum and are better supported in their learning journey. These insights were made abundantly clear in a webinar I attended called "ChatGPT Strategies You Can Implement Today to Enhance Your Class Sessions." In this webinar, Dr. Dan Levy, Senior Lecturer in Public Policy at the Harvard Kennedy School and co-author of the book Teaching Effectively with ChatGPT, discussed and demonstrated practical approaches to integrate ChatGPT into courses to enhance and personalize the learning experiences of college learners (Levy, 2024).
AI and Academic Integrity: The Cheating Dilemma
Recent observations in my classes align with Beth McMurtrie's (2024) insights on students' increasing use of AI for completing assignments (Shear et al., 2023). Additionally, the Digital Education Council Global AI Student Survey (2024) found that 86% of students surveyed reported using AI in their studies. This widespread use of AI tools like ChatGPT signifies a significant shift in student behavior towards embracing AI for academic support, highlighting the need for institutions to adapt their teaching methods accordingly. Specifically, 66% of 3,839 respondents from bachelor, master's, and doctoral programs in 16 countries used ChatGPT, with 69% using it to search for information, 42% to check grammar, 33% to summarize documents, 28% to paraphrase documents, and 24% to create a first draft (Digital Education Council Global AI Student Survey, 2024). In her article, Cheating Has Become Normal, McMurtrie describes how 50-75% of students have adopted AI tools like ChatGPT to complete their coursework, which mirrors my findings. McMurtrie highlights the widespread cultural shift towards accepting cheating in academic environments, emphasizing the urgent need for new approaches to academic integrity (McMurtrie, 2024). This aligns with my experiences where students openly admit to relying on AI, often citing workload pressures and the perception that their peers are doing the same.
Case Studies of Effective AI Integration in Higher Education
Several educational institutions have already embraced AI to revolutionize their teaching models. For example, Arizona State University has implemented AI chatbots to assist with administrative tasks and student inquiries, freeing up faculty time to focus on teaching and providing additional student support (Smith & Johnson, 2023). Similarly, the University of Essex has launched an AI-based system that helps predict students' academic performance and offers targeted interventions to keep learners on track (Brown, 2023). These success stories highlight how AI can enhance the administrative and educational aspects of distance learning, ultimately driving better student outcomes (Smith & Johnson, 2023; Brown, 2023). These practical applications of AI provide strong evidence that AI can be an effective tool for universities and distance learning institutions to transform online and distance learning (Shear et al., 2023).
The Leadership Deficit: Can Academia Keep Up?
Like the digital transformation challenges businesses face, many online universities have a leadership deficit. The academic leaders who have overseen distance learning programs lack the necessary digital transformation expertise to guide their institutions through the AI revolution. After struggling with AI-driven digital change, often due to a lack of a cohesive strategy, insufficient expertise, fragmented leadership, or underestimating the scope of necessary organizational change, online universities and distance learning institutions frequently find themselves unable to keep pace with the rapid rate of AI technological advancements. Challenges such as aligning digital initiatives with institutional goals, outdated governance structures, and a lack of internal champions who understand and have led successful digital change have compounded these issues. Consequently, these institutions either sustain failing digital transformations or become financially burdened by hiring expensive consulting companies to craft digital transformation roadmaps. Instead of relying on costly external consultants, institutions should invest in cultivating internal leaders with the strategic vision and technical expertise to guide these transformations effectively. Building internal leadership capabilities ensures institutions can independently navigate future technological changes and proactively adapt their strategies. Without fostering such internal leaders, online universities risk becoming dependent on external firms, leading to prolonged, costly engagements and an inability to respond swiftly to the rapid evolution of AI technologies.
The leadership deficit is not unique to education, as Paula Rooney (2024) highlights similar challenges CIOs face in the business sector. I discuss similar insights in my research poster session (Gates, 2024b), which provides an overview of digital transformation strategies and emphasizes the role of leadership in navigating technological disruptions. My research findings reveal institutions must cultivate adaptive leadership capable of aligning digital transformation initiatives with institutional values, long-term goals, and decision-making agility. This adaptability is crucial to overcoming the common obstacles faced in academic settings, such as resistance to change, lack of framework for managing digital change, and rapid technological evolution. Successful digital transformation requires technological innovation and robust and adaptive leadership capable of aligning organizational goals with evolving technological trends. Without visionary leaders who understand and have experience with digital strategies, online universities risk falling behind in the AI-driven educational landscape.
Furthermore, institutions that create policies that passively address the use of AI are allowing AI tools like ChatGPT, CoPilot, and others that they will ultimately rule as unethical for learners. Many institutions are taking this passive approach because they are unsure how to lead in this transformation. Institutions must take a proactive stance on AI policy to avoid falling into the same pitfalls and ensure they lead rather than react to changes.
Call to Action: Embracing AI and Overhauling Leadership
The future of distance learning hinges on universities fully embracing AI, not as a threat but as an integral part of the learning process. To close the digital transformation experience gap, universities should focus on hiring leaders from corporations that have successfully led organizations through digital change (Gates, 2024a). These leaders bring practical, firsthand experience in managing the complexities of digital transformation, which can be invaluable in bridging the experience gap within academic institutions. These leaders bring invaluable experience from successes and failures, which can help academic institutions avoid common pitfalls and learn best practices. Hiring experienced leaders rather than relying on external consultants ensures institutions develop the internal capabilities and resilience needed for sustainable transformation.
Academic leaders often lack direct experience in navigating evolutionary technological disruptions, so collaboration with those who have already faced similar challenges in the corporate world is essential. Bringing in corporate leaders with insight can help bridge the experience deficit at the leadership level, ensuring that academic institutions are reactive and proactive in harnessing AI's potential. This can help create an environment where AI policies are thoughtfully designed, anticipating ethical challenges and incorporating practical, scalable solutions. This means restructuring assessment models to move beyond written assignments and adopting AI-enhanced learning strategies, all while using various methods to maintain integrity. While proctored exams are one effective tool, I also believe that live presentations for exams and final projects can provide an excellent way for instructors to assess a learner's understanding and comprehension of course concepts. These presentations allow instructors to ask direct questions and challenge students in real time, ensuring they truly grasp the material. This approach not only tests knowledge but also enhances students' communication skills.
Other approaches can be employed in an AI-rich environment to assess learner comprehension effectively. For instance:
-
Oral Examinations: One-on-one or small-group oral exams where learners are asked to explain core concepts, solve problems verbally, or demonstrate practical applications. This allows instructors to probe deeper into student understanding and address gaps in real time.
-
Project-Based Assessments: Assigning practical projects that require students to apply concepts to real-world scenarios. Projects can be designed to require critical thinking, collaboration, and creativity—skills that are more challenging for AI to replicate autonomously.
-
Reflective Journals: Requiring students to maintain reflective journals throughout the course can provide insights into their thought processes, engagement with the material, and personal learning journey. These journals should be supplemented by periodic live discussions with the instructor to verify authenticity.
-
Flipped Classroom and In-Class Problem Solving: Utilizing a flipped classroom model where students study the material independently and use class time for problem-solving sessions. Instructors can directly observe how students tackle challenges, providing an opportunity to assess comprehension through active participation.
By incorporating these more engaging approaches to testing learner comprehension, instructors can now encourage learners to use AI to explore diverse perspectives beyond those of the instructor or course developer. This helps students develop a broader understanding of the material, fosters critical thinking, and makes learning a more enriching experience overall.
As highlighted by Stanford HAI (2023), by February 15, 2023, ChatGPT had gained over 100 million unique users, with approximately 30% of college students using it for assignments. This rapid adoption has made ChatGPT one of the fastest applications to be integrated into education settings. As a result, educators and school districts are actively grappling with how best to respond to the widespread use of this emerging technology (Stanford HAI, 2023). This rapid adoption of AI underscores the urgency for institutions to create thoughtful, effective policies that embrace AI’s potential while addressing ethical concerns.
By incorporating a mix of these methods, online universities and distance learning institutions can better ensure that students are learning the material and developing the skills necessary for future success. Institutions like WGU, which already use proctored exams, are uniquely positioned to develop aggressive policies to foster the use of AI in distance learning and can expand these approaches to create more comprehensive, integrity-driven learning assessment systems.
Conclusion: Will Distance Learning Institutions Survive the AI Revolution?
As AI continues to evolve, online universities face a stark choice: adapt or risk becoming irrelevant. Universities that fail to integrate AI into their curricula while maintaining rigorous knowledge checks through diverse assessment strategies will see their credibility deteriorate. The time to act is now. Institutions can turn this technological challenge into an opportunity by embracing AI and cultivating agile, tech-savvy leadership. The question is no longer whether AI will reshape education but whether universities can evolve fast enough to lead the charge.
References
Brown, L. (2023). Predictive analytics in education: The University of Essex experience. Education Technology Insights. https://www.edtechinsights.com/university-essex-predictive-analytics
Digital Education Council Global AI Student Survey 2024. (n.d.). https://www.digitaleducationcouncil.com/post/digital-education-council-global-ai-student-survey-2024
ForbesBLK. (2024). AI and agile methodologies for future leaders. Forbes. https://www.forbes.com/sites/forbesblk/2024/03/01/ai-and-agile-future-leaders/
Gates, A. (2024a). Digital Transformation: Strategic Planning with Generative AI. Executive Insight Solutions. https://www.executiveinsightsolutions.com/articles-publications/strategic-planning-with-generative-ai
Gates, A. (2024b). Poster Overview of Dr. Anton Gates' Research on Digital Transformation Strategy. Executive Insight Solutions. https://www.executiveinsightsolutions.com/articles-publications/poster-overview-of-research
Gates, A. (2024c). The AI-Driven Agile Revolution: A New Era in Project Management. Executive Insight Solutions. https://www.executiveinsightsolutions.com/articles-publications/ai-driven-agile-revolution
Levy, D. (2024). Teaching effectively with ChatGPT. Harvard Kennedy School. https://www.hks.harvard.edu/publications/teaching-effectively-chatgpt-practical-guide-creating-better-learning-experiences-your
McMurtrie, B. (2024, November 4). Cheating has become normal. The Chronicle of Higher Education. https://www.chronicle.com/article/cheating-has-become-normal?utm_source=Iterable&utm_medium=email&utm_campaign=campaign_11635705_nl_Academe-Today_date_20241108
OpenAI. (2024). Image depicting an African American woman using generative AI in a distance learning environment [DALL-E generated image]. OpenAI.
Rooney, P. (2024). CIOs under pressure to deliver AI outcomes faster. CIO. https://www.cio.com/article/3568799/cios-under-pressure-to-deliver-ai-outcomes-faster.html
Shear, H. E., Britton, L. L., Schaefer, K. A., Thapa, B., & Bergtold, J. S. (2023). Artificial intelligence and the future of learning and assessment in agricultural and applied economics. Journal of the Agricultural and Applied Economics Association, 2(4), 838–850. https://doi.org/10.1002/jaa2.98
Smith, J., & Johnson, A. (2023). AI chatbots in higher education: The case of Arizona State University. Journal of Educational Technology. https://www.journalofedtech.com/ai-chatbots-asu
Stanford HAI. (2023). AI will transform teaching and learning. Let’s get it right. Stanford University. https://hai.stanford.edu/news/ai-will-transform-teaching-and-learning-lets-get-it-right
Tyton Partners. (2024). Challenges in adopting AI policies in higher education. Tyton Partners. https://www.tytonpartners.com/reports/ai-challenges-higher-education/