Generative AI in the Curriculum: A Call for Coordinated Integration

As artificial intelligence becomes increasingly embedded in our personal and professional lives, higher education must take a strategic, coordinated approach to help students develop essential AI literacies. In this timely post, Gloria Niles, WCET Steering Committee Vice Chair, and the Director of Online Learning with the University of Hawai’i System, reflects on the 2025 EDUCAUSE Horizon Report and offers practical strategies for integrating AI into institutional, programmatic, and course-level learning outcomes. For more resources and insights on this important topic, visit WCET’s Artificial Intelligence resource page. Thank you to Gloria for this excellent article!

Enjoy the read,
Lindsey Downs, WCET

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 The 2025 EDUCAUSE Horizon Report (Teaching and Learning Edition) offers valuable insights into the key technologies and practices shaping the future of higher education. The rise of generative AI tools is transformative, potentially revolutionizing teaching and learning. Reflecting on the report’s findings, one thing is clear: higher education institutions must adopt a coordinated, strategic approach to integrate AI literacies into the curriculum.

The report emphasizes that AI will continue to evolve and integrate into nearly every profession rapidly. Three of the six key technologies and practices highlighted in the report center on AI:

• AI Tools for Teaching and Learning
• Faculty Development for Generative AI
• AI Governance

This makes it imperative for faculty to develop their AI fluency and teach students how to use these tools responsibly and ethically. Neglecting this could lead to graduates who are ill-prepared for the AI-integrated workforce.

Addressing AI Literacies Through Learning Outcomes

One effective way to ensure students develop essential AI skills and knowledge is to address AI literacies through clearly defined learning outcomes at the institutional, program, and course levels.

• Institutional Learning Outcomes (ILOs): These high-level outcomes define the knowledge, skills, and values that all graduates should possess, regardless of their specific program of study.
• Program Learning Outcomes (PLOs): These outcomes specify what students should know and be able to do upon completing a degree program.
• Course Learning Outcomes (CLOs): outline the specific knowledge and skills students are expected to acquire in a given course.

By mapping AI literacies into this curricular structure, institutions can ensure that students systematically develop the necessary competencies throughout their academic journey.

In their work on Dimensions of AI Literacies, Opened Culture offers a helpful framework that can inform the development of these learning outcomes. They identify several key areas of AI literacies, including:

• Cultural AI Literacies
• Cognitive AI Literacies
• Constructive AI Literacies
• Communicative AI Literacies

Institutions can draw upon these dimensions to create learning outcomes that are comprehensive and relevant.

Examples of Learning Outcomes

With assistance from ChatGPT 4o and Gemini Advanced, here are some examples of how these AI literacy dimensions could be incorporated into ILOs, PLOs, and CLOs:

Institutional Learning Outcomes (ILOs)

• Cultural AI Literacies
  Graduates will analyze and evaluate the social and cultural contexts in which AI tools are developed and applied to address complex problems within their field of study.
• Cognitive AI Literacies
  Graduates will critically engage with AI environments to acquire knowledge, assess information accuracy, and identify the strengths and limitations of AI tools in academic and professional contexts.
• Constructive AI Literacies
  Graduates will ethically create, remix, and generate content using AI tools, demonstrating responsible use and proper attribution in alignment with academic and professional standards.
• Communicative AI Literacies
  Graduates will use AI technologies to enhance communication, adapting messages for diverse audiences while acknowledging the sociocultural influences AI may reinforce or obscure.

Program Learning Outcomes (PLOs)

• Example – Business Program
  • Graduates will apply AI tools to analyze market trends, optimize business operations, and inform data-driven decision-making.
  • Graduates will evaluate AI’s ethical and legal implications in marketing, finance, human resources, and customer analytics.
  • Graduates will develop strategic communication plans incorporating AI-driven insights to engage stakeholders and consumers.
• Example – Communication Program
  • Graduates will analyze the role of AI in shaping media narratives, public opinion, and information dissemination across platforms.
  • Graduates will ethically use AI-powered tools (e.g., chatbots, content generators, analytics platforms) to produce and evaluate multimedia communication.
  • Graduates will demonstrate fluency in adapting messaging strategies in response to AI-driven audience insights and media environments.

• Example – Health Sciences
  • Graduates will apply AI tools to support evidence-based clinical decision-making, patient education, and healthcare delivery.
  • Graduates will critically evaluate AI’s implications for health equity, data privacy, and algorithmic bias in patient care.
  • Graduates will communicate AI-generated health data clearly and compassionately to diverse patient populations and interdisciplinary teams.

Course Learning Outcomes (CLOs)

• Conceptual knowledge of AI
  • Students will define and explain core concepts in artificial intelligence, including machine learning, natural language processing, and computer vision.
• Ethical analysis of AI
  • Students will analyze the ethical implications of AI technologies, including algorithmic bias, privacy, transparency, and accountability.
• Societal Impact of AI
  • Students will use evidence-based analysis to evaluate AI’s impact on key sectors of society, such as healthcare, education, and the economy.
• Communication about AI
  • Students will communicate clearly and effectively about AI concepts and issues to various audiences through written, oral, and visual formats.
• Ethical use of AI tools
  • Students will apply AI tools ethically and responsibly to support original work in course assignments and projects, with appropriate attribution. 

The Importance of a Coordinated Approach

There are differing views on how institutions should integrate AI literacies. Some argue for a top-down approach, starting with the development of ILOs, which would then inform PLOs and CLOs. While time-consuming due to the shared governance process, this process ensures a coordinated and cohesive approach. This also facilitates the development of learning activities and assessments that effectively support the identified outcomes.

Others suggest that faculty should be encouraged to integrate AI into course assignments without waiting for a coordinated mapping of ILOs, PLOs, and CLOs. While this approach may seem more expedient, it could lead to a fragmented and siloed approach to AI literacy education. Teaching AI literacies may lack consistency, depth, and coherence without a clear connection to broader institutional and program goals.

Striking a Balance

In my view, a balanced approach is needed. While developing ILOs, PLOs, and CLOs provides a crucial framework for integrating AI literacies, faculty should also be empowered to experiment with AI tools in their courses. Institutions could provide faculty with resources and support to help them integrate AI into their teaching while aligning their efforts with broader institutional goals.

Ultimately, the goal is to equip students with the AI skills and knowledge they need to thrive in an increasingly complex and interconnected world. By adopting a coordinated and strategic approach, higher education institutions can ensure that graduates are proficient in their chosen fields and adept at navigating artificial intelligence’s ethical, social, and technological dimensions.

This post was written by Gloria Niles.

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