The transition to tertiary education is typically characterised by fewer structured classes per week and greater reliance on self-regulated learning (SLR). SRL involves a student’s effort to plan and set goals and engage in strategies to achieve those goals (Zimmerman & Schunk, 2011). With the development and integration of online learning technologies, blended learning is quickly growing in popularity in higher education. The blended method adopts a web-based technology for online learning which is used in combination with face-to-face instruction. Technology have brought new opportunities to modern education but also poses many challenges for the student. In particular, deciding what, when, how, and for how long to learn. In this context, self-regulation gains importance. In this study we focus on one aspect of SLR – procrastination. Therefore, the purpose of this study is to evaluate procrastination behaviour in a blended learning property course in relation to student performance through educational data mining. We investigate work intensity to explore temporal patterns of students’ behaviour among low, medium and high performing students. We include a discussion of implications and insights on procrastination in the context of blended learning.