Artificial Intelligence (AI) plays an increasingly important role in many aspects of society, including education. One of the most beneficial contributions of AI is the personalization of learning with tools such as intelligent tutoring systems, providing students with personalized instruction based on the student's performance. Educational data mining (EDM) allows educators and researchers to leverage student performance data to discover patterns in learning outcomes and determine appropriate interventions to promote improved academic achievements. Online education enables more opportunities for AI to facilitate instruction and keep students engaged in learning, even when remote. From learning management systems to video conferencing to online forums, teachers and students are using AI to improve teaching and learning practices.
However, concerns surround the use of AI-based applications in education and the potential misuse by students and faculty. The rising popularity and use of the large language model application ChatGPT has resulted in greater attention to the concern of its exploitation to generate content for research papers, exam answers, and other products in which students may leverage this technology in a dishonest way. Additionally, teachers' widespread adoption of AI-based applications may depend on their knowledge, proficiency, and understanding of its potential benefits and their trust in the AI’s decision-making capabilities.
This project will explore the perceptions and attitudes of instructors in higher education toward the use of AI-based applications in education. This research aims to gain a deeper understanding of instructors' knowledge of, attitudes toward, perceived benefits, and perceived harm of such applications.
You will either need to have been enrolled for 12 hours in the spring semester (Spring 2023), or will need to be enrolled for 3 hours over the summer.
Identify as a UT undergraduate student
Have a passion for research
Have strong writing, organizational, and communication skills
Able to meet bi-weekly with project supervisors (in person or remotely)
Start date: June 1, 2023
End date: August 31, 2023*
*Although the position ends on 8/31, there will be opportunities to continue the research if desired and based on performance during the appointment.
Assist with steps of data collection and analysis, including, but not limited to, the following
- Scheduling interviews,
- Managing audio files,
- Generating and correcting transcripts
- Analysis of transcripts
- Drafting memos to supplement the data analysis led by the PI
