AI adoption introduces a wealth of potential benefits to higher-ed instruction and learning--but many are wary of persistent challenges

Despite hype, AI adoption lags in higher ed


AI adoption introduces a wealth of potential benefits to higher-ed instruction and learning--but many are wary of persistent challenges

Key points:

  • Although AI has soared in popularity, higher education is cautious in its rate of AI adoption
  • Many in higher ed cite concerns around cheating as their biggest reason for not adopting AI
  • See related article: Education in the age of AI and smart technology

Artificial intelligence (AI) has certainly made its presence known in higher education, bringing with it opportunities and challenges. AI adoption in higher ed could help support equity initiatives and increase digital skills and workforce readiness, but it also has introduced a number of concerns in areas such as academic integrity and bias.

Supporting Instruction & Learning Through Artificial Intelligence: A Survey of Institutional Practices & Policies, a July 2023 report from WCET (the WICHE Cooperative for Educational Technologies) based on a national April 2023 survey, outlines how and why higher-ed institutions are using AI in their efforts to support instruction and learning, what policies they have put in place, and what barriers and benefits exist around AI adoption.

When survey participants were asked what stage they are in regarding AI adoption and implementation to support instruction and learning, nearly 60 percent said the use of AI to support instruction and learning at their institution “is on the radar or
scattered but there is no systemic action yet,” and 22 percent said they are in the planning stage.

For those who indicated any level of AI adoption or use, more than half (53 percent) first deployed AI to support instruction and learning less than one year ago, 19 percent one to two years ago, 20 percent three to five years ago, and only 8 percent deployed more than five years ago.

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

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Laura Ascione

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