Alignment of Learning Design with Learning Analytics: Case of MOODLE Blended Learning Course in Higher Education

This paper studies the effects of the design for an Engineering Education introductory course in a brick-and-mortar university through the alignment of learning design with learning analytics. It looks at how an analysis of students' data (logs in the Learning Management System (LMS) and assessment grades) can be interpreted in the context of educators' pedagogical intentions and the influence in students' performance. The findings show that even in this case of blended learning it is possible to align learning analytics with learning design, leading to interesting conclusions nurturing course redesign. Learning analytics, which is the way data about students can be represented and analyzed can be used to understand the impact of learning design. In blended learning settings, it is possible to collect data about students' interactions with the LMS which are configured, at least partially, according to educators' designs. This study assumed a censors approach with a cross sectional design. Learner actions in the Moodle LMS for a course offered in a blended learning mode for engineering first-year students in a Spanish university were analyzed. The learning design employed in the course had a mix of collaborative task and individual tasks. The result indicates that; there is an alignment of learning design and learning analytics, there are observed behavior patterns in learners, there is a relationship between observed patterns and performance, and there is significant difference between the students in different clusters in individual tasks as opposed to group tasks.