Leveraging AI-driven edtech for continuous improvement in higher ed

Key points:

• The exploration phase of generative AI is a defining moment in academia
• What does higher ed think about AI?
• Addressing data use and AI for student affairs staff
• For more news on AI in higher ed, visit eCN’s Teaching & Learning hub

Today’s higher education institutions grapple with escalating expenses, unpredictable student enrollments, and a changing digital landscape. Navigating these complexities, generative AI emerges as both an opportunity and a challenge. While perceptions about its integration into academia are shifting positively, concerns around plagiarism and academic integrity persist. Yet, there’s an undeniable consensus: Faculty and administration recognize the transformative potential of generative AI tools.

In a recent Educause QuickPoll, 67 percent of respondents expressed optimism regarding the capabilities of generative AI. When questioned about whether they believed generative AI would profoundly influence higher education in the next few years, 83 percent said yes, with more believing generative AI would simplify their tasks and provide more advantages than disadvantages. Conversely, some respondents expressed a sense of unease, possibly reflecting their awareness of the potential risks associated with these technologies despite their potential benefits.

The prominence of generative AI is coming at higher education institutions from all angles–faculty are using it to help build their syllabi and reflect on assessment effectiveness, administrators are embracing it to generate self-studies ahead of accreditation season, and students are relying on it for help with research and writer’s block. Every stakeholder across every campus is impacted by the latest AI technologies, so the best way around it is through it. This starts by taking a holistic approach to how institutions utilize AI to their advantage, monitoring it for misuse, and embracing it as the newest addition to their tech stack. An approach to generative AI tailored to an institution’s individual needs can potentially unleash new levels of productivity across the board.

AI and assessment culture

The importance of assessment in education has always been evident. However, the term itself has come to encompass a much broader and more detailed process in recent years. Aside from the traditional focus on what students can remember, assessment has taken on additional meaning thanks to innovative technology. Institutions can use assessment data to inform strategic decision-making, upgrade curricula, and elevate the student learning experience.

In the shifting landscape of educational assessment, AI is a pivotal tool for real-time feedback and practice, benefiting both students and faculty. Students can engage with platforms like ChatGPT to simulate assessment scenarios, receiving immediate, formative feedback that guides their learning and preparation. This interaction fosters self-reflection and targeted improvement before official evaluations. Similarly, faculty can utilize AI to refine and test the efficacy of their assessments, ensuring questions are clear, concise, and accurately measure learning outcomes. By acting as a rehearsal space, AI facilitates a feedback loop that enhances the quality of assessments, tailors the learning process, and ultimately bridges the gap between teaching strategies and student understanding.

Evolving assessment trends prove AI can help institutions embrace a new era of measuring institutional effectiveness. This includes different types of assessment and a focus on processes and experiences. Embracing technological innovations such as AI can also create a more detailed and accurate picture of how institutions are meeting their objectives and supporting student success.

Getting ahead of accreditation season

Reporting on assessment effectiveness becomes crucial ahead of accreditation season. Today, many institutions harness the capabilities of AI to expedite this process. The contention lies not in AI’s efficacy, but in the balance it strikes between efficiency and the narrative richness of reports. While some might argue that AI could compromise the depth of these reports, others see it differently. Many administrators view AI as not a replacement but an enhancement tool—bolstering efficiency while maintaining the report’s core integrity.

Integrating AI into the assessment and accreditation process alleviates the challenges traditionally associated with this exercise. As more higher education AI tools are embraced, it becomes evident that their application ensures optimal resource utilization. Colleges and universities should brace for a balanced approach that recognizes the benefits of AI while preserving the essence of the accreditation process.

Enhancing faculty success with AI

Faculty success is another component intrinsically tied to an institution’s academic reputation. Documenting these achievements, which span research, teaching milestones, and community outreach, often presents logistical challenges. With the rise of AI, there’s a paradigm shift in how academic data management is approached.

The incorporation of AI in faculty data management was born out of a pressing need: the simplification of manual data entry processes for faculty. Traditional digital tools, though helpful, lacked the precision and efficiency required, and AI is proving to be a game-changing solution for higher education. Modern AI tools can seamlessly sift through a faculty’s publication records, capturing essential data such as titles, authors, journal names, and publication dates. This ensures data accuracy while significantly reducing manual entry efforts.

By intertwining AI with faculty data management, institutions are paving the way for a more streamlined and efficient academic environment. Lifting administrative burdens and optimizing data processing lets faculty members focus more on their primary academic pursuits, propelling institutions to greater heights.

Everything must begin and end with responsible AI

As institutions and their edtech partners collaborate closely, the primary focus must be on responsible AI, emphasizing ethical, private, fair, and transparent solutions through developing and deploying this advanced technology. However, adopting new technological advancements can often be met with reluctance, mainly when staff or faculty members are unfamiliar with the solutions. Therefore, adopting an ethical and thoughtful approach to utilizing such technology is imperative. Here are several ways edtech companies and institutions can collaborate to ensure responsible AI utilization:

1. Prioritize transparency: Promoting ethical product development and maintaining trust hinges on transparency regarding the technologies, partners, and data employed in AI solutions. Edtech companies should offer client institutions the choice to participate or not and disclose the nature of the data involved, especially when integrating third-party systems to enhance existing processes or introduce new features.
   
2. Uphold fairness: It’s crucial to prioritize accessibility and inclusivity while mitigating potential biases. This entails careful consideration of the data fed into AI systems, ongoing monitoring of AI-generated results, and conscientious avoidance of domains where AI may not be the optimal solution. Respecting each institution’s principles, policies, and legal requirements fosters fairness and prevents adverse outcomes.

3. Ensure data privacy and security: Aligning an institution’s data privacy policies with its technology partner is essential for responsible AI activity. Edtech providers should follow a transparent approach, offering insights into the data used and shared during AI operations, thus safeguarding privacy and security.

4. Guarantee reliability and oversight: Incorporate mechanisms to ensure the reliability of AI-generated results and maintain human oversight throughout the AI processes. Any outputs, suggestions, or decisions originating from AI should be identified as such, with options for overriding or modification as necessary. The use of generative AI should require informed consent, with explicit explanations of its purpose and expected outcomes.

5. Remain dedicated to access: Edtech companies must prioritize accessibility when integrating AI into their solutions. Recognizing that these capabilities are essential, there’s a commitment to making them accessible and affordable for all clients. This approach aims to assist the entire higher education sector, ensuring no institution or student is left behind in the rapidly evolving technological landscape.

Building a culture of assessment with the help of AI

The exploration phase of generative AI represents a defining moment in academia. By integrating AI at the administrative level, institutions can unlock new opportunities to enhance student outcomes, improve organizational efficiency, and make data-driven decisions. While challenges exist, the potential benefits are too significant to ignore. It is increasingly clear that generative AI will play a pivotal role in shaping the future of higher education by improving personalized learning and streamlining administrative functions.