Feedback is a cornerstone of academic development, particularly in marketing education, where skill development often requires iteration and applied practice. While instructors spend considerable time providing effective feedback, artificial intelligence (AI) tools can significantly reduce this burden by generating timely, tailored responses. For example, AI-based chatbots can supplement instruction, providing students with timely feedback and reducing instructors’ workload. This study examines how marketing students perceive feedback quality based on its source, specifically whether it is delivered by an AI system or a human instructor. Through a scenario-based experiment, we investigate student perceptions of feedback quality and effectiveness based on the source (AI vs. Instructor) or valence (positive vs. negative). Our findings provide guidance for professors who want to incorporate AI tools into their teaching practices. Understanding student perceptions of feedback source is crucial for marketing educators who want to leverage AI systems to enhance the educational experience without compromising the human component that students value.
Russell et al. (Sat,) studied this question.