Supporting higher education students through analytics systems

wide implementation are still scare (Ifenthaler, 2017).Research on student retention has been conducted predominantly in English-speaking countries such as Australia, UK or USA (e.g.Bean, 1982;Krause et al., 2005;Mah et al., 2019;Tinto, 1993).Findings highlight that students may benefit from analytics systems through personalised and adaptive support during their learning journey (Ifenthaler, Yau and Mah, 2019).For example, students often enter higher education academically unprepared and with unrealistic perceptions and expectations of academic competencies for their studies.Both, the inability to cope with academic requirements as well as unrealistic perceptions and expectations of university life, in particular with regard to academic competencies, are important factors for leaving the institution prior to degree completion (Mah and Ifenthaler, 2018).Analytics systems for supporting learning and teaching in higher education are slowly moving towards a mature field of research and development (Ifenthaler, Mah and Yau, 2019; Schumacher and Ifenthaler, 2018a, b;Schumacher et al., 2019).This broader (and system wide) adoption of analytics system provides new testbeds for empirical research and areas of new discoveries for the learning as well as data sciences (Mah et al., 2019).This special issue brings together the scholarly research and theory focusing on contemporary issues related to analytics system and how they support students' at higher education institutions.The contributions provide insights into how educational data, analytics systems and advanced digital technologies contribute towards successful learning and teaching scenarios at higher education institutions.