When it comes to specific AI adoption, the highest percentage of existing, planned, or considered use is for detecting AI-generated content/plagiarism (56 percent), with editing (52 percent) close behind. Content creation (44 percent), assessment & feedback (37 percent), accessibility (34 percent), and research (32 percent) were next.
Other key findings around AI adoption in higher ed
When it comes to AI utilization:
- Using AI to support instruction and learning is in its infancy on many campuses,
although some have been using it for this and other purposes for years. - Concerns about AI and academic honesty (preventing cheating) are a
focus for many institutions and the top reason given for not using AI. - At the majority of institutions, AI adoption and use to support instruction and learning is on the radar or scattered but there is no systemic action yet. The highest percentage of existing, planned, or considered use is for detecting AI-generated content, plagiarism, with editing and content creation close behind.
- In terms of discipline-specific use, AI is being most utilized, perhaps unsurprisingly, in computer and information science, but a number of respondents also indicated use in English and business administration, among other fields. However, the arts and humanities may see a renaissance as critical
and creative skills become crucial in ensuring responsible and ethical use of AI.
Support, incentives, and training:
- Online and distance education administrators and staff, including instructional
designers, are the primary roles leading this work on their campuses, with
faculty and chief academic officers and provosts (as well as associate and
assistant CAO/provosts) close behind. Additionally, on some campuses, leaders
at the highest level are engaging in work around AI–and some are including
students in AI policy development and practice as well. - The overwhelming majority of institutions do not offer incentives to encourage
faculty in AI adoption and use, and a majority also reported no faculty development or training around AI.
Strategy, planning, and policy around AI adoption in higher ed:
- The majority of institutions lack official strategy around the use of AI but have or
will be developing policies, primarily around academic integrity and instructional
use. - Some institutions are adapting existing policies to include the use of AI.
- Respondents identified empowering educators with new technologies as the top
reason for adopting or considering AI adoption.
Challenges and benefits of AI adoption and use:
- The primary challenge to using AI was lack of expertise among faculty and
administrators, followed closely by lack of policies and guidelines and concerns
about protecting academic integrity. - Given the lack of incentives or training previously mentioned, there seems to be a disconnect between perceived challenges, like lack of expertise among
faculty, and strategies – such as comprehensive professional development and
training – to mitigate the challenges and support the practices. - A majority of respondents identified both teaching critical digital skills and
learner engagement as the top benefits to using AI to support instruction and
learning. Interviews confirmed a need for a new, “digital literacy 2.0” – for both
students and faculty – as well as an imperative to include industry in
conversations and planning to prepare students for a workforce already using AI. But a new version of the “digital divide” may result from lack of access to training and skills acquisition around AI.
Related: How to redefine learning in the digital age
Laura Ascione is the Editorial Director at eSchool Media. She is a graduate of the University of Maryland's prestigious Philip Merrill College of Journalism.
Latest posts by Laura Ascione (see all)
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