Abstract:

Many university instructors report using active learning methodologies in their classrooms; however, they employ them occasionally in theoretical contexts. This paper examines this issue and seeks to understand which training formats are most suitable for learning these methodologies, while also considering the barriers that currently hinder such learning. Survey responses from 99 instructors at a Spanish business university (Barcelona) were analyzed and data were collected through open-ended questions and Likert scales to understand current practices, perceived barriers, and preferred training formats across profile variables, including academic category, gender, age, and teaching experience. The analysis is structured through a cross-sectional descriptive methodology, which describes the data and characteristics of the study population or phenomenon. Methods include descriptive statistics, logistic models predicting format preferences from profile variables, and cluster analysis to derive actionable personas. Results show a clear preference for web-based resources, followed by video, with virtual assistants gaining traction in specific segments. These results are segmented by the different profiles studied and the combination of these.

The variable of experience details that younger professionals prefer assistant mediated by AI, hands-on formats (often with interactive elements). A similar pattern emerges among less experienced instructors, industry-based faculty, and female academics, who demonstrate a more favorable disposition toward AI technologies. The remaining groups, which include the largest sample of participants and the most experienced instructors, gravitate toward structured web/video materials that emphasize reliability and time efficiency. All the participants strongly value personalized training and “step-by-step” guidance. Reported barriers cluster around limited time, difficulty adapting methods to theory heavy or technical subjects and large cohorts. In relation to generative AI, respondents recognize its potential but express concerns about accuracy and sources, calling for transparent citations and “safe” usage modes within training.

The value of this study lies in providing empirical evidence on instructors limited use of active learning. By identifying barriers, it contributes guidance for more effective faculty development.

Keywords:

Active learning, faculty development, teacher segmentation, AI, higher education, active learning pedagogies.