Exploring artificial intelligence and its role and impact on education, the world, and at Lehigh.

Introduction

Faculty, students, and staff at Lehigh are focused on artificial intelligence (AI) and its place in university classrooms. Areas of interest include AI as a teammate, AI as an aid to productivity, AI as a teaching consultant, and AI for shared humor and productive play. Early adopters and critics also ask: Is the use of AI incongruent to academic integrity?

This guide to AI from Lehigh’s Center for Innovation in Teaching and Learning (CITL) will:

help faculty talk with students and set policies regarding the use of AI; and
aid faculty in the design of assignments and assessments related to AI.

What is Generative AI?

Generative AI is a subfield of AI. In a few words, “AI can be defined as ‘automation based on associations’” (Cardona 2023). In longer form: “AI is a branch of computer science. AI systems use hardware, algorithms, and data to create ‘intelligence’ to do things like make decisions, discover patterns, and perform some sort of action” (Ruiz and Fusco 2023). Generative AI refers to AI systems that produce text, images, code, audio, and video, among other possibilities.

How do apps like ChatGPT or Gemini work?

ChatGPT and Gemini are AI-powered content creators. They are also chatbots and applications on the Internet. Both are powered by large language models, or LLMs. At their inception, LLMs depend on text mining and web scraping to build a corpus for study by a computer. An LLM then learns based on rules, or algorithms, set by developers, as well as training by humans. LLMs “learn a probability distribution of the next word/pixel/value in a sequence” (Thompson 2023). This means that they do not output whole sentences from a text-mined foundation based on a user's prompt(s). Instead, LLMs and their chatbot intermediaries build outputs in strings, based on probability and machine learning. This is one reason why proper citation becomes an issue for people who rely on generative AI. Outputs from an app like ChatGPT are probable, plausible, but they do not draw from specific, reliable sources. This is also why text generators make up references, or hallucinate, even when a user asks for citations within a prompt (Edwards 2023).

Learn more: On demand LTS Seminar entitled “Understanding AI” (recorded session, PDF of slide deck, and AI-assisted meeting summary).

The impact of AI

In a critical literature review, researchers identified a discourse of imperative change surrounding AI in higher education (Bearman, et al. 2023). But that imperative should be critiqued and analyzed in specific scenarios of teaching and learning. Faculty bandwidth is wide and limited. Take time to consider the impact of AI on your course and field of study. Know that there will be many opportunities for change in semesters and years to come.

Top Seven Recommendations

Address AI

Directly address the prevalence of generative AI in your classroom, in your syllabi, in each assignment prompt, and in course materials.

Whether or how

Provide students with explicit guidance about whether or how they may use AI-powered tools in your class. The LU Syllabus Template contains sample statements for professors that embrace, permit limited uses, or prohibit the use of AI.

Guidance on any use

If you permit or encourage the use of generative AI, offer guidance to students on how they can best use it to enhance their learning, which uses they should avoid, and why. Teach students to critically assess AI tools and recognize their limitations. Have your students review Undergraduate and Graduate Student Senate Statements on Academic Integrity, Article III of Lehigh's Code of Conduct, and the detailed policies and expectations and best practices at ai.lehigh.edu.

Engage, explore, question

Engage your students in thinking together about AI by inviting them to share their perspectives, experiences, questions, and concerns. Hands-on AI experimentation (e.g., comparing student work with AI-generated versions) helps demystify AI and build confidence.

The next generation

Show students how generative AI does or will impact your discipline. Then teach students in ways that prepare them for that future.

Foreground equity

Address important questions about AI related to biases, inaccuracies/hallucinations, inequities in access to emerging technologies, ethical and legal concerns regarding texts scraped from the web, the complexities of using and citing AI-generated texts and images, and the need to avoid any inputs of institutional data, restricted data, or critical data into available tools.

Revise and redesign assignments

Create personalized assessments such as brief in-class writing or coding exercises, writing on topics unique to each student, in-person presentations, oral exams, and one-on-one discussions of paper topics.

When a professor adapts to technological change without losing their core student learning objectives they create an AI-resilient assignment! An AI-resilient assignment emphasizes process, student ownership, creativity, critical thinking, and the motivation of a readership and public for student work, among other possibilities. To redesign assignments you might:

Break down assignments into scaffolded, multi-step tasks to emphasize process and reduce opportunities for improper use.
Include personalized and reflective writing, such as autobiographical or student-designed assignments.
Craft assignments that are inquiry- or problem-based and involve applications to real world problems. These projects lend themselves to meaning-making and are harder for AI to replicate.
Feature peer-reviewed work during the semester and presentations for a public at the end of the semester. Accountability to others incentivizes students to invest effort and originality.

Learn more: On demand LTS Seminar entitled “Creating AI-Resilient Assignments” (recorded session, PDFs of slide deck, and AI-assisted meeting summary) and the CITL guide “7 Step Process for Deterring AI Misuse.”

Questions?

Request a consultation with LTS staff to discuss use cases, explore tools, or get help navigating best practices for your academic and/or administrative work.

CITL Guidance for Faculty on Generative AI in the Classroom