Academic analytics: Anatomy of an exploratory essay

A systematic literature review on student performance predictions

“…Although not many studies emphasize on using the school design features, however this review has able to identify two studies that has discovered that the best attributes in their research is school size [3] and the percentage of lecturer attendance [10]. Therefore, it is important for other researchers to look beyond the common attributes such as academic performance as the educators and school facilities also tend to impacted students' performance.…”

Εκπαιδευτικά Συστήματα Υποστήριξης Αποφάσεων Βασισμένα Σε Ψηφιακές Ικανότητες Σχολικών Μονάδων Και Εκπαιδευτικών

“…Academic Analytics are addressed at providing HEI leaders with support for managing the processes of the macro institutional layer, namely the "Business Intelligence" Elias, 2011;Chatti et al, 2012;Siemens, 2013). These processes primarily refer to operational and financial decision making (van Barneveld et al, 2012;Ferreira & Andrade, 2014). A similar term used in the literature is that of Action Analytics which considers similar data and decisions at a macrolayer towards the generation of informed insights (Norris et al, 2009).…”

“…Main Purpose. Apart from the evident rationale of internal HEI management and improvement (including, faculty professional development and hiring), exploitation of the aforementioned data can be crucial for the HEI in terms of meeting external accountability goals (Ferreira & Andrade, 2014;Gašević et al, 2015). Therefore, HEI leadership can utilize the insights generated towards remedying actions, such as targeted curriculum (or course) improvements (Bichsel, 2012).…”

“…The analysis of key objectives of Academic Analytics supports the initial statement that, apart from its explicit focus on HEI, existing Academic Analytics approaches have focused on orchestrating the Business Intelligence of the macro organizational layer. This can be (at least partly) attributed to the common mandates regarding external accountability, which mainly include (a) reporting the level of quality of operations to policy makers and funders (Norris et al, 2009;Ferreira & Andrade, 2014;Gašević et al, 2015) and (b) achieving high rankings in inter-HEI benchmarks which are largely based on a diverse set of data (e.g., staff-to-student ratio, research quality/quantity, resource allocation per student, alumni professional success) (Siemens, 2013;Daniel, 2015). On the other hand, explicit orchestration of the teaching and learning processes of the micro/meso-layers of the HEI is not robustly addressed and supported by Academic Analytics approaches.…”

“…Towards addressing the aforementioned goal in an educational context, the concept of Analytics has spawned two core strands, namely Learning Analytics (LA) and Academic Analytics (AA) (Long & Siemens, 2011;Norris & Baer, 2013;Ferreira & Andrade, 2014). Learning Analytics are addressed to all types of educational institutions (e.g., K-12 schools and Higher Education Institutions -HEI), as well as online education (e.g., Massive Open Online Courses -MOOCs), and mainly aim at providing data-driven decision support for the micro/meso-layers (Long & Siemens, 2011).…”