Patrick Tran

Background

About Patrick Tran

I am a data scientist by training, instructional designer by choice, and educator at heart! I specialize in learning analytics, instructional design, and educational technology, applying my expertise to develop impactful solutions for learners and educators alike. With a comprehensive understanding of the data development stack, from data engineering and machine learning to visualization and interpretation, I bridge the gap between data and actionable insights. At the University of New South Wales (UNSW), I am leading the data science aspects of the Learning Analytics and Intelligence (LAI) project. Our flagship product, the Academic Success Monitor (ASM), utilizes advanced machine learning and generative AI to proactively identify students at risk of academic difficulty. By analyzing diverse student data, we provide timely, personalized interventions, significantly enhancing their chances of success. This pioneering project exemplifies the transformative potential of data-driven personalized learning in higher education. My research interests span a broad spectrum, including learning analytics, educational data mining, gamification, learning theories, inventive problem-solving, and foresight. As a regular contributor to the EdTechPosium conference and a published author in online courses and international journals, I actively share my knowledge and insights with the wider educational community. With a proven track record in both teaching and management roles at leading Australian universities, I have extensive experience in technology-enabled learning initiatives, including analyzing learner data and developing early intervention strategies. I am a certified PRINCE2 project manager with an MBA in Accounting and Finance, bringing a unique blend of technical and business acumen to my work. I am a lifelong learner committed to pushing the boundaries of educational innovation through data-driven insights and cutting-edge technology. When I'm not working, you can find me cycling, watching movies, or enjoying quality time with loved ones.