Motivation has been considered as a significant factor in student's academic journey. As discussed by Schweinle, Meyer and Turner (2006), student motivation and emotions are crucial for their attitudes, behaviours and achievement. In general, many learning theories such as Self-Regulated Learning (SRL) emphasis on motivation for achievement and learning (Boekaerts 1999; Pintrich 2000; Zimmerman 2002). In fact, nowadays, the availability of the big data in the educational domain, and analysis of this through learning analytics, is leading to changes in learning and the learning environment (Long and Siemens, 2011). In learning analytics, information about students is used for assessing, eliciting, and analysing to optimise students' learning experience and to help in decision making Miltiadou and Savenye (2003) reported that motivation has not received attention in online learning and in their study, they recommended that in order to increase student success rate and engagement, more studies are required to test motivation theories and their effect on student learning. Therefore, further studies are needed to identify the role of learning analytics in enhancing learning processes, especially for supporting student learning motivation. To add evidence to this gap in research, this research aims to investigate student's motivational factors with the support of using learning analytics techniques.

Motivation has been considered as a significant factor in student's academic journey. As discussed by Schweinle, Meyer and Turner (2006), student motivation and emotions are crucial for their attitudes, behaviours and achievement. In general, many learning theories such as Self-Regulated Lear...