AI for Teaching, Learning, and Student Research: Helping educators and students use AI while preserving independent judgment

Session Submission Type: AI Peer Learning Lab

Abstract

Using AI Tools to Support the Research Process
Facilitator: Subhasankar Bhattacharya - National Louis University
Training Category: Writing, Editing & Research Communication
AI Tool: Claude
Participant Type: Students
Skill level recommended: No_Experience
Recommended preparation or pre-work before session: No prior experience with AI tools is required. I will also provide you with practical “cheat "codes"—ready-to-use prompts, tips, and resources that you can take with you and use in your own research.

In this conference session, I want to show students how AI can be used as a research assistant, not as a replacement for their own thinking or writing. We will walk through a complete research workflow together, using a real or sample research question. First, students will learn how to use AI tools such as Consensus to find relevant research papers and quickly understand what previous studies have found. We will practice searching for a research topic, identifying important papers, and comparing findings across studies. Next, we will use Claude to organize and work with research materials. Students will learn how to upload documents, ask questions about papers, summarize key themes, compare studies, and identify possible research gaps. We can also demonstrate how AI can help organize qualitative or quantitative data and support basic data analysis. Then, students will learn how to use AI during the research-writing process. We will demonstrate how to develop a research question, create an outline, improve clarity and organization, and critically review a draft. We can also show students how to create an AI “peer reviewer” prompt that provides feedback on their manuscript. Most importantly, the session will emphasize responsible AI use: verifying information, checking citations, protecting confidential data, and making sure the researcher—not AI—makes the final decisions.


Using AI to Design Public-Service Cases That Require Student Judgment
Facilitator: Marcela Nava - Tarleton State University, Assistant Professor
AI Tool : ChatGPT
Participant Type: Faculty
Skill level recommended: Beginner
Recommended preparation or pre-work before session: No required pre-work. Participants are encouraged to bring a laptop or tablet and have access to a ChatGPT account; a paid subscription is not required. Participants may also bring a learning objective or assignment they would like to revise. A sample assignment excerpt will be provided, and attendees can complete the review activity without logging into an AI tool. Please exclude identifiable student information from any materials brought to the session.
Training Category: Teaching & Curriculum Development

Public administration instructors need cases that connect with students’ experience and require them to apply concepts, weigh competing public values, and defend consequential choices. This interactive lab demonstrates how instructors can use generative AI to develop such cases while retaining responsibility for disciplinary accuracy and assessment design. Drawing on an undergraduate leadership assignment at Tarleton State University, the workflow begins with learning objectives and the reasoning students must demonstrate. An instructor-reviewed, anonymous summary of students’ backgrounds and interests—including summaries informed by Canvas’s AI discussion-summary feature where available—helps identify a relevant setting. Participants will see how instructors can guide and revise AI-generated scenarios to establish realistic constraints, plausible alternatives, and meaningful tradeoffs. The example asks students to choose how a county agency should implement a new service system under a fixed deadline. Informed by team-based learning, the live activity asks students to make an individual provisional choice, deliberate in small teams on the same problem, commit to a collective decision, and compare reasoning across teams. Students apply leadership concepts, examine the strongest alternative, identify an unresolved consequence, and reflect on their leadership tendencies. An asynchronous “Path B” assesses these core analytical skills through an individual decision video, followed by a debrief presenting competing arguments. Common rubric criteria connect the pathways while recognizing the distinct learning opportunities offered by team deliberation. The session distinguishes instructor AI use for assignment design from permitted student assistance with brainstorming and organizing their own analysis. Participants will consider how instructions, disclosure requirements, and rubric criteria support accountable AI use without treating a polished response as proof of independent reasoning. The 20-minute lab includes three minutes of framing, seven minutes of demonstration, six minutes of participant revision and peer comparison, and four minutes of discussion. Participants will revise a weak AI-generated case option and explain how their revision strengthens the judgment students must exercise. Participants will practice specifying pedagogical constraints in an AI prompt, evaluating the resulting alternatives, and connecting assessment requirements to learning objectives. They will receive an adaptable prompt sequence, assessment example, and review checklist for use in their own courses. No coding or prior AI expertise is required.

Building Transferable AI Training for Education and Workforce Development

Training Category: Teaching & Curriculum Development
AI Tool : Generative AI platforms; the training emphasizes transferable concepts and materials rather than a single tool.
Participant Type: Faculty and government
Skill level recommended: No_Experience Recommended preparation or pre-work before session: No prior preparation is required. Participants are encouraged to bring a course, program, training module, or workplace-learning need they would like to adapt during the guided activity. If possible, participants should have access to a generative AI tool of their choice.
Training Category: Teaching & Curriculum Development

This interactive training session provides educators and workforce-development professionals tools to build adaptable introductory learning experiences on generative AI. Drawing on the facilitator’s experience teaching a master's level course called "AI use in the public sector" and delivering trainings for state-level organizations, the session introduces a transferable training framework designed for adult learners with varied professional backgrounds. It emphasizes the benefits, limitations, risks, and barriers associated with AI use. Participants will examine sample materials and identify elements that can be customized for their own discipline, student population, or workplace context.In a guided activity, participants will select a course, program, or training need and outline one AI-related learning objective, a practical use case, and a strategy for discussing responsible use. The session will conclude with small-group reflection on how to keep materials current as AI tools change. By the end of the training, participants will be able to adapt an introductory AI-training structure, incorporate responsible-use considerations, and identify a practical next step for integrating generative AI into teaching or workforce development.

Policy Area

• AI Peer Learning Lab

Facilitators

• Subhasankar Bhattacharya, National Louis University

• Marcela Nava, Tarleton State University

• Ashlee Frandell, University of Nevada - Las Vegas

Individual Presentations

• Using AI Tools to Support the Research Process - Facilitator: Subhasankar Bhattacharya, National Louis University

• Using AI to Design Public-Service Cases That Require Student Judgment - Facilitator: Marcela Nava, Tarleton State University

• Building Transferable AI Training for Education and Workforce Development - Facilitator: Ashlee Frandell, University of Nevada - Las Vegas