The eCampus Center announced their selection of faculty members who will pioneer the AI Research Fellowship in online education. Each research project studies an aspect of artificial intelligence and its impact on online learning.
These individuals will explore effective strategies to support learning about AI, including AI literacy, AI in research methods and designing machine learning products to support learning.
The following overviews outline the AI research areas the fellows will explore and publish.
Yu-Hui Ching and Yu-Chang Hsu
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 with Ti Macklin
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
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 and Gundy Kaupins
Martin-gale: AI-powered case generation and grading – Case studies are often outdated, lacking diversity, and ineffective at simulating real-world processes.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 with Karen Nicholas and Yu-Hui Ching
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
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
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
AI as an 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.
Learn More About the Faculty Research Fellowship on the eCampus Center website.