In looking at the future of teaching and learning in higher ed, AI has a place--but more research is needed to define its role.

How does higher ed use AI for teaching and learning?


In looking at the future of teaching and learning, AI has a place--but more research is needed to define its role

Key points:

As AI cements its place in education and the workforce, and as AI tools evolve, questions abound around how educators are using AI for teaching and learning, along with how they’re helping prepare students for a future that will require AI know-how.

During an ISTELive 24 session, a team of researchers from National College of Education at National Louis University delved into higher-ed AI use as they explored the first phase of a two-phase project.

The National College of Education at National Louis University team includes:

  • Dr. Angela Elkordy, Associate Professor, Educational Leadership Studies
  • Dr. Jack Denny, Secondary Education Teacher Preparation Program, Advanced Professional Programs
  • Dr. Ayn Keneman, Professor, Early Childhood Education Teacher Preparation Program
  • Dr. Stuart Carrier, Associate Professor, Educational Leadership Studies
  • Dr. Donna Wakefield, Associate Professor, Special Education Teacher Preparation Program

In the project’s first phase, researchers sought to explore emerging practices and implementation of generative AI in higher education. A second phase will build upon findings to gather additional information and data on educators’ practice to elicit and extrapolate design principles.

Research questions included:

1. How are faculty in higher education using generative AI for instruction?
2. What are the perspectives and experiential insights of educators in higher education concerning the adoption and use of AI digital tools?
3. In what ways do educators learn about AI digital tools, teaching, and learning?

Data sources for the research questions included focus groups, surveys, and Facebook group posts.

How are faculty in higher ed using generative AI for instruction?

Results indicate great interest among faculty, but also a desire for professional development. Faculty use generative AI to enhance, differentiate, and innovate instruction. They also use it as a cognitive tool or thought partner, along with using it to create text.

Among the greatest advantages of using generative AI for teaching and learning: As a thought partner to offer ideas, reclaiming time, creating instructional materials, leveraging creativity in instruction, individualizing learning, for research on instructional strategies, and for research on best practices.

Focus group results for this research question center on teaching prompt engineering. Users typically provide the AI tool with a prompt, often written in normal conversational language. The user can craft the prompt with more details to customize and improve output. Writing an effective prompt usually requires more specific and detailed information than, say, writing a successful search query. General guidelines would be helpful in aiding users as they improve their prompting skills.

“I specifically teach AI in my courses. To have successful use of AI, you need to know how to use it and need to know how to write prompts the right way, and exactly what goes into a prompt and what prompt engineering is. It’s a skill I teach–all the different parts of a prompt,” said Wakefield.

Wakefield also uses MagicSchool.ai to ensure her assignments are AI-resistant.

One general theme that quickly emerged: Faculty are able to establish effective AI use with students in which students co-create.

What are the perspectives and experiential insights of educators in higher education concerning the adoption and use of AI digital tools?

In exploring their second question, the researchers found a primarily positive sentiment in their sample group. There are conflicting ideas of plagiarism, and some educators are hesitant to use AI tools due to low confidence, a lack of policies and guidance around such tools, and varying expectations from leadership.

General themes include:

  • Ethics and policy in AI
  • Maintaining reports to organize research papers
  • The line of plagiarism is blurred
  • GenAI has significantly raised the stakes for all, particularly marginalized groups

In what ways do educators learn about AI digital tools, teaching, and learning?

Focus group responses around this third question offered a number of takeaways: AI apps are evolving daily, and higher-ed faculty would benefit from regular ISTE professional development, along with checking in on the “state of AI art.”

When it comes to different AI tools, the researchers noted that Claude, mentioned a number of times, emerged as useful in helping faculty generate meaningful feedback to graduate students’ expository writing–the tools returns nuanced feedback on the writings’ content quality, relevance to standards and objectives, and grammar, rhetoric, and syntax.

“We recommend constant vigilance by higher-ed faculty over the development of AI platforms because it’s changing all the time. As a practitioner using AI in doctoral-level courses, I’ve recently discovered Claude, an AI platform by Anthropic, and after I started using it to evaluate student expository writing, Claude started introducing itself to me as my AI teaching assistant and started giving me very nuanced feedback to give to the students. It was very, very helpful,” Carrier noted.

These findings led to several implications for practice. Successful graduate students will use AI with transparency and evidence of human engagement. Successful higher-ed faculty will use AI with differentiated human responses reinforcing students’ human engagement. Successful AI use in teaching involves student engagement with AI paired with teacher engagement with AI. Evidence that the student is present is a critical success factor, as is evidence of faculty engagement, Carrier added.

In looking at how higher-ed faculty learn about AI tools, sources include online searches, from faculty and teacher colleagues, educational journals or articles, webinars, their institutions or in their work context, professional organizations, Facebook, and college trainings or communications.

Findings from surveys pertaining to this question include:

  • AI can enhance their own voice
  • Digital literacy has become a mindset
  • There’s a need to learn about the digital world

A future with AI

“We really want to look at how the practices of using generative AI are aligned with constructivist theories of learning to engage the students in their own learning,” Elkordy said.

Research also will explore policy development and will examine educators’ learning needs and effective PD models.

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Laura Ascione