The Role of AI-Enhanced Educational Technology in Advancing Higher Education

Sizing up a promising asset—and a complex hurdle. 

GUEST COLUMN | by Darren Bauer Kahan


Contemporary colleges and universities face increasing costs, unpredictable student enrollment, and evolving digital environments. In this context, generative AI is both a promising asset and a complex hurdle. The sentiment toward adopting this technology in educational settings is becoming more favorable, though issues such as plagiarism and maintaining academic standards remain of great concern. Nonetheless, educators and administrators have a shared agreement about the revolutionary impact of generative AI tools.

A recent Educause QuickPoll revealed that 67% of participants are hopeful about the capabilities of generative AI, with 83% anticipating it will significantly influence higher education. Many believe these tools will ease their workload and offer more benefits than drawbacks. However, some participants also reported apprehension, likely due to an understanding of the risks that come with such technology despite its advantages.

‘A recent Educause QuickPoll revealed that 67% of participants are hopeful about the capabilities of generative AI, with 83% anticipating it will significantly influence higher education.’

Generative AI influences all facets of academic institutions, including faculty members who use it to develop syllabuses and evaluate assessment efficacy, administrators who employ it for generating reports during accreditation periods, and students who utilize it to assist with research and overcoming writer’s block. The widespread impact of AI technology means that embracing and understanding it is essential. Institutions are encouraged to adopt a comprehensive strategy that leverages AI for their benefit, ensures its proper use, and integrates it as a key component of their technological resources. Tailoring generative AI use to an institution’s specific needs can unlock unprecedented levels of efficiency and create new opportunities to enhance student outcomes. 

Preparing for Accreditation Season with AI 

When the accreditation period approaches, reporting on assessment effectiveness becomes paramount. Many institutions are now using AI to quicken the process of accreditation reporting. The debate isn’t about AI’s efficiency, but about how it balances time-saving with the depth of reporting. While there are concerns that AI may reduce the complexity of reports, many administrators regard AI as a tool that enhances, rather than replaces, human effort, preserving the essence of the report while improving productivity.

Incorporating AI into assessment and accreditation processes can relieve the traditional difficulties associated with these tasks. It’s clear that doing so facilitates the best use of resources. As AI tools become more widespread, institutions must adopt a balanced approach that taps into the advantages of AI while upholding fundamental values of the accreditation process.

AI and Academic Assessment 

The concept of assessment in education is not new, but its scope has broadened significantly, going beyond merely evaluating what students remember. Thanks to technological advancements, assessment now also includes using data to shape strategic decisions, improve curricula, and enhance student learning experiences.

AI has become a crucial instrument for providing instantaneous feedback and practice, to the benefit of students and teachers alike. Platforms like ChatGPT can offer students simulated assessment scenarios with immediate feedback that helps them prepare for actual evaluations. This immediate feedback encourages self-assessment and focused improvement. Likewise, faculty can refine their assessment methods using AI, ensuring that their questions are effective and accurately measure learning outcomes. AI acts as a practice space, creating a feedback loop that improves the quality of assessments and aligns teaching methods with student comprehension.

The advancement in assessment trends indicates that AI can aid institutions in adopting new methods of evaluating their effectiveness. This includes varying assessment types, focusing on processes and experiences, and utilizing technological innovations like AI to provide a comprehensive and precise understanding of institutional goals and student support.

Advancing Faculty Success through AI

Faculty achievements are closely linked to an institution’s academic standing. Recording these successes, which include research, teaching, and community engagement, often poses logistical hurdles. However, the emergence of AI is changing the way academic data management is approached.

AI’s role in faculty data management stems from the need to simplify the process of manual data entry. While existing digital tools are helpful, they often lack the precision and speed required. AI is becoming a game-changing solution in this area. Advanced AI tools can meticulously parse through a faculty member’s publication records, accurately capturing key data and reducing the burden of manual entry.

By integrating AI with faculty data management, institutions are streamlining academic operations. This allows faculty to concentrate on their scholarly work, thereby propelling institutions forward.

Commitment to Responsible AI Use 

As educational institutions and edtech providers work together, the main priority should be responsible AI use, focusing on ethical, private, fair, and transparent practices. However, integrating new technology can be met with hesitation, particularly if staff or faculty are not familiar with it. Therefore, adopting an ethical and thoughtful approach to technology deployment is crucial. Here’s how edtech companies and institutions can ensure the responsible use of AI:

Emphasize Transparency: Trust and ethical product development depend on being transparent about the technology, partners, and data used in AI solutions. Edtech companies should allow institutions to choose whether to engage with AI and be open about the data being used, especially when integrating third-party systems.

Maintain Fairness: Ensuring accessibility and inclusivity while avoiding biases is vital. This involves careful consideration of data input into AI, continuous monitoring of AI outputs, and the deliberate avoidance of areas where AI may not be suitable. Upholding each institution’s values and legal standards is key to fairness and preventing negative consequences.

Protect Data Privacy and Security: It is critical for institutions to align their data privacy policies with those of their technology partners for responsible AI operations. Edtech providers must be transparent about the data they use and share, ensuring privacy and security.

Ensure Reliability and Oversight: It is important to have mechanisms that guarantee the reliability of AI outputs and human oversight in AI processes. Outputs and suggestions from AI should be clearly identified, with options for human intervention and informed consent for use.

Stay Committed to Access: It’s imperative for edtech companies to focus on making AI features in their offerings both reachable and economical for everyone. Understanding the importance of these advancements, edtech companies must pledge to ensure widespread accessibility to their clients. Their AI strategy must support the entire higher education field, guaranteeing that no educational body or learner gets excluded in the rapidly changing tech landscape.

Cultivating a Culture of Assessment with AI 

The current exploration of generative AI marks a significant moment in the academic world. By incorporating AI at the administrative level, institutions can discover new ways to enhance student outcomes, increase organizational efficiency, and make informed decisions. Despite the challenges, the potential rewards are too significant to overlook. It is becoming increasingly apparent that generative AI will have a central role in the future of higher education, improving personalized learning and administrative processes.

Darren Bauer Kahan serves as the Chief Product and Technology Officer for Watermark, a leading provider of software solutions for higher education. A tenured technology professional, Darren previously served as Chief Technical Product Officer at SAP Concur and has played significant roles in shaping various enterprise software and consumer-focused solutions. Darren holds a B.A. in Computer Science from the University of California, Berkeley. Connect with Darren on LinkedIn.


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