Introduction: Recent advancements in generative AI (GAI) platforms appear to mark an abrupt shift in higher education. Statement of the Problem: Instructors have a responsibility to teach students to use GAI, which is a promising tool for promoting personalized, student-centered, process-focused learning environments. Literature Review: Drawing on…

Background: Generative artificial intelligence (AI) represents a potentially powerful, time-saving tool for grading student essays. However, little is known about how AI-generated essay scores compare to human instructor scores. Objective: The purpose of this study was to compare the essay grading scores produced by AI with those of human…

Introduction: The proliferation and accessibility of generative artificial intelligence (AI) have led to strong reactions across the academia. Statement of the Problem: Teachers can adapt to the availability of AI by integrating disclosure statements about its use into courses, which may promote student learning. Literature Review: Suggestions to…

Introduction: The integration of artificial intelligence (AI) into higher education ushers in a new era of teaching and learning possibilities for both educators and students. Statement of the Problem: These technologies not only offer unparalleled opportunities for personalized learning and instructional support, but also introduce challenges…

Background: Psychology instructors frequently assign writing-to-learn exercises that include personal reflection. Generative Artificial Intelligence (GenAI) can write text that passes for humans in other domains. Objective: Do students and faculty rate a reflection written by GenAI differently than reflections written by students? Do students and…

Background: Multiple-choice item (MCI) assessments are burdensome for instructors to develop. Artificial intelligence (AI, e.g., ChatGPT) can streamline the process without sacrificing quality. The quality of AI-generated MCIs and human experts is comparable. However, whether the quality of AI-generated MCIs is equally good across various domain-…

We describe 3 computer-based neuroscience laboratories. In the first 2 labs, we used commercially available interactive software to enhance the study of functional and comparative neuroanatomy and neurophysiology. In the remaining lab, we used customized software and hardware in 2 psychophysiological experiments. With the use of the computer-based…