Artificial Intelligence (AI) presents transformative potential for human-centered design education by enabling personalized learning, enhancing collaboration, and expanding access to tailored resources. This study aimed at exploring AI technologies support for instruction in design education, especially their application in personalization, online collaborative learning, and equitable access, along with their ethical considerations. A mixed-methods approach was utilized in this study that included surveys combined with semi-structured interviews and classroom observations. The purposive sample of 60 participants was made up of 25 instructors, 30 students, and 5 design professionals at Stephen F. Austin State University. Quantitative data were analyzed using descriptive statistics and Pearson correlation, toward identifying correlations between learner performance and the usage of AI, while qualitative data was thematically analyzed using NVivo. Results showed how AI significantly facilitates individualized learning through real-time feedback and personalized content (Demszky et al., 2023; Woolf, 2010), facilitates collaboration through intelligent platforms (Suthers, 2006), and opens access to relevant resources (Ferguson, 2012; Chiu et al., 2023). Data privacy issues, bias (Luckin et al., 2016; O’Neil, 2016), and the ability to augment educational inequity (Warschauer, 2004) issues were raised, however. The study concludes on the premise that AI can support effective learning and inclusion if complemented by ethical surveillance and access parity interventions
Wanakuta et al. (Wed,) studied this question.