Learning analytics allow instructors and researchers to discover important learning episodes and phenomena (e.g., moment of learning/misconception), get better understanding of learner characteristics/needs; and understand the features that make the learning material effective. In Future Learning we will leverage learning analytics capabilities to formulate a conceptual framework for assisting researchers and instructors in improving the orchestration of e-learning tools and practices as well as harmonizing heterogeneous learning analytics streams.

During the last years within the Information Systems and Software Engineering (ISSE) group has long record of innovative technologies for learning. This record, includes but it is not limited to, video learning analytics system, educational games, the multiple awards winner Kahoot! game-based learning system with more than 50 million monthly users and adaptive learning systems to support programming. Our systems allow instructors to create their own assignments, quizzes and interact with as well as assess their students.

Collecting and managing integrated learning analytics from different resources like video lectures, wikis, quizzes, LMSs and so forth, will allow us to better understand students’ progress, experience and usage behavior. Exploring important issues like, the dynamics between different e-learning tools, students prioritization of e-learning tools, the association of different orchestrations with students’ learning experience and the combination of different learning practises with different set of e-learning tools, will allow us to construct novel principles and technical knowledge in order to increase benefits arising from the efficient orchestration.

About the Future Learning project.