Dr. Abelardo Pardo
Dr. Pardo is Associate Head of Teaching and Learning and Lecturer at the School of Electrical and Information Engineering, The University of Sydney. He has a PhD in Computer Science from the University of Colorado at Boulder applied to formal verification of digital circuits. As co-director of the Software Engineering group, his research interest is in the application of technology to explore, understand and influence human behavior. He has experience in the use of technology in learning and behavioral analytics, social networks, computer supported collaboration, personalization, and technology enhanced learning. The national and international projects in which he has participated have been funded by the Office for Teaching and Learning (Australia), the National Science Foundation (USA), and the European Union. He serves as member of the steering committee of the Society for Learning Analytics Research (www.solaresearch.org), and as a member of the editorial board of the IEEE Transactions on Learning Technology and the Journal of Social Media and Interactive Learning Environments.
On October 1, from Noon until 1 pm (Central Time), in the Rady Room (Rm 601 in Nedderman Hall)
Dr. Pardo delivered the following public presentation:
Title: Connecting Pedagogical Intent with Analytics in a Flipped Classroom
Student engagement is one of the topics that is typically addressed to increase academic performance. Active learning is a pedagogical strategy that has been shown to increase student performance in areas such as science, engineering and mathematics. At the same time, technology increasingly mediates the interaction between students, instructors, and resources. The idea of students preparing in advance for a face-to-face lecture session has been re-branded as the flipped classroom. In this paradigm, students participate in various outside of class activities while the higher cognitive elements can be tackled in class.
This approach requires a significant redesign of the pedagogical strategy which now relies on students using technology (videos, animations, simulations, multiple choice questions, etc.) to prepare for a lecture. New activities need to be designed to take into account these two phases because the face-to-face part of a course is now very vulnerable to low student engagement. Learning analytics techniques can provide the required insight on how students are preparing for the lecture and can offer instructors the possibility of adapting the content. But how can that data collection be integrated in the design process?
In this talk, I will explore the implications derived from the need for this integration in the design stages and possible solutions based on markup languages.