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The research aims at examining educators’ perceptions, attitudes and behavioral intentions toward learning analytics (LA) and the role of self-instruction within the proposed model for LA adoption.

A quantitative approach is utilized in which a questionnaire is designed as a tool for data collection and partial least squares structural equation modeling (PLS-SEM) is used for data analysis and model testing.

Results show that performance expectancy and effort expectancy have a significant effect on educators’ attitudes, which in turn significantly affect educators’ behavioral intentions. Self-instruction mediates the relationship between educators’ attitudes and behavioral intentions. The attitude towards LA mediates the relationship between LA performance expectancy and educators’ self-instruction. The research model explains 54% of the variance in learning analysis adoption.

Findings open a path for research on pedagogical factors affecting LA adoption and guide education managers toward facilitating LA adoption. The tested model contributes to LA and teaching and learning literature by highlighting the role of educators’ self-instruction in LA adoption.

The potential capabilities and benefits that learning analytics can provide are not fully utilized. A current stream of research suggests that learning analytics has more to offer for continuous improvement of higher education institutions. This study aims to explore the opportunities that data analytics stand to offer higher education and the challenges that plays down its role, adoption and usage in different areas of higher education institutions.

This study adopts a systematic literature review approach in answering the research questions. The critical role of learning analytics and the exploratory nature of research questions justify the use of systematic literature review. The current study used systematic research process adapted and presented by Hallinger (2013) to be used in social sciences in general and in educational leadership and management in particular. A standard process of finding relevant articles and examining reference lists is followed using articles from higher education which is the research context.

An examination of the literature showed that the majority of studies within the sample of articles are empirical representing 53 per cent, 32 per cent are conceptual, while only 15 per cent of the articles are a systematic literature review. Results also show that 58 per cent of the articles are teaching and learning related, 34 per cent are management related, while only 8 per cent are research related. Several challenges and opportunities of learning analytics in the three areas highlighted are presented and discussed.

The benefits and challenges of learning analytics are numerous and scattered in the literature. In this study, a typology related to different educational domains is developed to shed light on the benefits and challenges of learning analytics within particular higher education areas that are relevant to specific stakeholders. Benefits and challenges of learning analytics are classified into being management related, teaching and learning related and research related.