About Research Fellows

The following overviews outline the research areas our fellows will explore and publish.

Victoria Abramenka
Clinical Assistant Professor, College of Education

Using the IDea Chatbot to Support Professional Reasoning and Autonomy in Graduate Instructional Design Students

This study explores how interaction with a domain-specific generative AI tool (IDea chatbot) influences graduate instructional design students’ professional reasoning, reflective depth, autonomy, and decision-making during authentic client-based projects. The research also compares AI-supported learning to traditional peer discussion and role-play approaches.

Darci McCall
Instructor, School of Nursing

Student Perceptions of AI-Based VR Simulations in Asynchronous Online Nursing Courses

This study investigates how nursing students experience AI-based VR simulations in asynchronous online learning environments, particularly in relation to communication skills, emotional conversations, engagement, and usability.

Serena Morales
Clinical Associate Professor, College of Education and Public Service

Developing Assessment Literacy and AI Literacy Through AI-Integrated Pedagogy

This study examines how AI-integrated pedagogy, modeling, and deliberate instructional design influence graduate students’ development of assessment literacy and AI literacy as professional competencies.

Jayne Josephsen
Tenured Professor, College of Health Sciences

AI-Generated Avatar Simulations and Empathy Development in Nursing Education

This continuation of a prior fellowship study explores the effectiveness of AI-generated avatar simulations, virtual role-play, and reflective debriefing in supporting empathy development and reflective practice among nursing students.

Gemma Morawski
Instructor, College of Arts and Sciences

Evaluating H5P Activities for Language Learning Retention and Practice

This study examines which H5P activities are most and least effective for language retention and practice in accelerated online Spanish courses.

Brittney Gehrig
Lecturer, College of Arts and Sciences

AI Chatbot Conversation Assistants and Student Retention in Online Spanish Courses

This study explores how AI chatbot conversation assistants influence student retention, engagement, language learning outcomes, and persistence in fully online Spanish courses.

Andy Hyer
Lecturer, College of Health Sciences

Student Confidence and Self-Efficacy in Generative AI-Supported Assignments

This study examines how structured, scaffolded AI-based assignments affect student confidence, self-efficacy, and perceptions of AI-supported assessment strategies.

Todd Norton
Associate Professor, College of Arts and Sciences

Structuring AI-Supported Discussion Activities to Increase Student Engagement

This exploratory study investigates how discussion prompts and AI-supported activities can encourage more meaningful, applicable student engagement in undergraduate and graduate courses.

Karen Nicholas
Associate Professor, College of Business and Economics

Integrating AI Into Teaching and Learning in Business Education

This project explores how instructors can effectively integrate AI into business education both to teach disciplinary content and to develop students’ AI literacy and professional competencies.

Anthony Saba
Assistant Professor, College of Education

Persona-Informed AI Assistants to Support Engagement and Persistence in Accelerated Online Courses

This study investigates how AI assistants designed from learning analytics and student feedback can support engagement, persistence, and success in accelerated asynchronous online courses.

The following overviews outline the research areas our fellows will explore and publish.

Dr. Jayne Josephsen 
Tenured Professor, College of Health Sciences

Immersive AI Simulations 

This research uses digital simulations such as the Wonda platform to create immersive learning experiences grounded in simulation-based pedagogy. Wonda allows educators to create interactive, scenario-based learning experiences without coding skills or VR hardware. The research deployed in NURS 422 to develop AI-generated experiential learning interventions. The study focuses on the efficacy and student experience with these interventions, exploring how AI-generated impact learning outcomes.

Leslie Atkins (Professor, Curriculum, Instruction and Foundational Studies) and ShaKayla Moran (Secondary STEM Education Specialist)
College of Arts and Sciences

Cultivating Empathy and Perspective Through AI Personas in Federal Science Funding

This research explores how cultivating and conversing with AI-generated scientific personas over time impacts students’ awareness of and empathy towards key members of the scientific workforce. In STEM-ED 220, students will assume particular personas (such as a recent immigrant graduate student working on carbon capture, a Manhattan Project member who escaped fascism, or a Chief Information Security Officer) and craft plausible biographies for those characters. These personas, built on student input and enhanced by AI, will engage students in meaningful dialog about research goals, challenges, economic implications, and political considerations. This longitudinal assignment threads together various components of the course throughout the semester, compelling student interest in unique perspectives and deepening their understanding of the scientific ecosystem and diverse career pathways.

Yu-Hui Ching and Yu-Chang Hsu
Professors, Educational Leadership, Research, and Technology

Preparing Pre-Service Teachers for AI-Enhanced Instruction: Building Critical Thinking Skills

In collaboration with Dr. Yu-Chang Hsu, this follow-up study aims to help pre-service teachers develop the critical thinking skills required to effectively use AI in their future teaching careers. The research will place pre-service teachers in authentic educator scenarios where they use Amplify AI to generate initial drafts of lesson plans. They will then critically evaluate the AI-generated content using a detailed rubric designed to scaffold the process. This activity helps pre-service teachers understand that while AI can be a powerful tool for content creation, its outputs require thoughtful evaluation and intentional refinement to ensure instructional soundness, contextual appropriateness, and responsiveness to diverse student populations. Data collection will include participant-AI interaction logs, interviews, and reflections, providing insight into how pre-service teachers engage with AI tools and develop their critical thinking skills related to instructional design.

Brett Shelton
Professor, Educational Technology Department

This research works with OER and H5P to assess learning acquisition among students. eSports students will provide their perspectives and experiences using these tools. Using a survey design to gain student perspectives, Shelton will evaluate which H5P might contribute to positive learning experiences and knowledge acquisition among students. 

Darci McCall
Instructor, School of Nursing

Video-Enhanced AI Patient Simulations for Remote Nursing Students

Darci has been developing an interactive patient encounter experience for online nursing students using AI tools. In NURS-RN 402: Vulnerable Populations – Critical Issues in Obstetrics, she has built a custom GPT that simulates patient interactions, allowing students to practice clinical decision-making in a virtual setting. With this fellowship, Darci will integrate a digital video component to make the encounters more realistic, engaging, and immersive—bringing elements of the on-ground nursing simulation lab into the online environment. Because her students are all remote and never come to campus, this enhancement is particularly important. Darci will gather student feedback and examine whether digital and AI-driven simulations enhance engagement and overall learning in online nursing education.

Gemma Morawski
Instructor, College of Arts and Sciences

Integrating H5P Activities into Canvas for OER Adoption

Gemma wants to study H5P integration with Canvas to expand the use of Open Educational Resources in her department. She has an OER textbook with several H5P activities currently assigned as homework, but students must navigate outside of Canvas to complete them. By integrating these activities directly into Canvas, she aims to ease the student workflow, improve assignment completion tracking, and reduce instructor reluctance to adopt OER materials in the World Language Department.

Hetal Vig
Adjunct, College of Health Sciences

AI-Driven Standardized Patient Simulations for Genetic Counseling

Genetic counseling requires nuanced communication skills, empathy, and technical expertise that traditional training methods often fail to develop comprehensively. Hetal is developing an AI-powered standardized patient simulation platform to supplement genetic counseling graduate student training in GENCOUN 549. The project will develop AI-driven standardized patient profiles representing varied genetic conditions, clinical indications, and emotional states, providing students with focused practice sessions on communication skills, clinical reasoning, and empathetic engagement before traditional standardized patient experiences.

Margaret Sass
School for the Digital Future

Generative AI and Effective Digital Teamwork: A Quasi-Experimental Study

How does the use of generative AI tools influence students’ development as effective team players in a digitally connected and remote environment? This research question will be examined in TEAM 302: Teamwork in the Digital Age, a 7-week online course exploring how digital tools and remote collaboration have reshaped teamwork. Using a pre/post quasi-experimental design, the study will assess whether generative AI tools enhance students’ development in essential teamwork skills, including communication, coordination, and managing remote work dynamics in virtual environments.

The following overviews outline the AI research areas our fellows will explore and publish.

Yu-Hui Ching and Yu-Chang Hsu
Professors, Educational Leadership, Research, and Technology

Pre-service Teachers’ Perceptions of Using GenAI Tools as Critical Peers in Online Learning

This study will promote AI literacy modules for future teachers in EdTech 202, Teaching and Learning in a Digital Age. Through a learning community and rapid iteration process, Ching and Hsu aim to enhance students’ self-improvement and critical thinking skills by using GenAI tools as critical peers in assignments, improving their ability to receive, evaluate, and reflect on AI feedback. The study seeks to deepen pre-service teachers’ understanding of AI and demonstrate how AI tools can be used to develop critical thinking about their work.

Tiffany Hitesman (Lecturer, Professional & Public Writing) with Ti Macklin (Program Director, Department of Writing Studies)
What has age got to do with it?: Nontraditional Student Perceptions and Use of Artificial Intelligence

Nontraditional student experiences with AI systems in online writing courses have not been sufficiently researched, especially in comparison to their more traditional student counterparts. By focusing on this overlooked demographic, this study seeks to give voice to nontraditional students and understand their perceptions, concerns, and prior knowledge about AI in the context of online writing courses.

Andy Hung and Brett Shelton
Professors, Educational Leadership, Research, and Technology

Fostering Doctoral Success: Multi-Agent System Feedback for Dissertation Proposals

Doctoral students need help completing dissertations which is sometimes due to timely feedback and challenges faced by faculty members. The solution in this research is to design a multi-agent system that provides the feedback to students on their dissertation proposals. Using AI tools to build a domain expert, a methodology expert, and a writing expert, these agents collaborate to provide student feedback. Success will be measured by the quality of student work through rubrics and surveys.

Steven Hyde (Assistant Professor, Management) and Gundy Kaupins (Professor, Management)

Martin-Gale: AI-Powered Case Generation and Grading

Case studies are often outdated, lacking diversity, and ineffective at simulating real-world processes. Using AI case generators and providing feedback from an AI grader can improve student performance. By using open-source language models, case studies will become AI chatbots. This research will be assessed through quantitative and qualitative methods of learner perceptions.

Karen Krier (Online Course Technologist, Department of Management) with Karen Nicholas (Clinical Associate Professor, Management) and Yu-Hui Ching (Professor, Educational Leadership)
Students’ Perspectives on Utilizing Poe for Research in an Online International Business Management Course

Non-traditional learners in online courses need community, engagement, and research skill development. By customizing the learning experience through an AI chat tool, students in this course will learn research skills and gain asynchronous support. This research will be an exploratory case study and will use semi-structured interviews and document analysis of chat scripts to measure outcomes.

Ross Perkins
Associate Professor, Educational Leadership, Research, and Technology

An Investigation of Artificial Intelligence Tools in the Teaching and Learning Research Methods

Research methods faculty have concerns about using AI tools due to both data security and student reliance on AI. Through a mixed-methods study, this research will explore how faculty are currently thinking about this dilemma and learn what practices they use to integrate AI into their research methods courses.

Margaret Sass
Lecturer, College of Arts and Sciences

Community-Centric AI Project Development
The focus of this research project is for students to design a community-based project that leverages ChatGPT and other AI tools to solve specific challenges faced by small and/or local communities. Students will be required to critically assess the ethical considerations involved in applying AI to these community projects. My research delves deeper into AI education—how to teach students to use AI tools both effectively and ethically, particularly within smaller, localized communities. By engaging in this fully online course, students will not only develop essential AI skills but also contribute meaningfully to community development through the thoughtful application of AI technology. Online students will first identify challenges within local communities and then provide the necessary AI education and tools to meet those needs.

Brian Stone
Associate Professor, Department of Psychological Science

AI as artificial person, statistical model, or copilot: How mental models of AI affect use of the technology

Mental models of what generative AI is and how it works can alter how students use AI in their learning, in ways that may enhance or hinder learning, especially in online environments. This research will involve experimental and survey research to see how manipulating mental models of AI may affect how AI is used by online students, as well as identifying individual differences in how students use AI.

Baker Lawley
Clinical Associate Professor, Interdisciplinary Professional Studies and Bachelor of Applied Science

Lawley is exploring student learning and sentiment after completing their ePortfolios and how this high-impact strategy contributes to a transformative experience. This research focuses on credit for prior learning students, particularly those who are more nontraditional.

Patrick Lowenthal
Professor in Educational Technology and Innovation Faculty Associate, eCampus Center

Lowenthal’s innovative study focuses on faculty perceptions of accessibility tools like Ally. By combining analytics with qualitative data, he seeks to understand faculty needs, provide professional development, and enhance online course accessibility at Boise State. This research may pave the way for a more inclusive online educational environment.

Andy Hung and Kerry Rice
Professors in Educational Technology

Hung and Rice will leverage analytics, machine learning, and AI to obtain profound insights into online student engagement trends. By pinpointing when online students disengage, they plan to design personalized interventions for positive outcomes. Their research stands to bring about transformative changes in identifying and responding to online student needs and learning patterns.

Brian Stone
Associate Professor, Department of Psychology

Stone seeks to innovate instructional practices across disciplines by exploring the frontier of AI-supported student learning in online courses. Aligning with Bloom’s taxonomy, he will create pedagogical strategies that instructors can apply at various levels. Stone’s research promises to culminate in an open educational resource, offering an invaluable asset to educators everywhere.