Alzahrani, AsmaTsai, Yi-ShanKovanovic, VitomirMoreno-Marcos, Pedro ManuelJivet, IoanaAljohani, NaifGasevic, Dragan2024-06-032024-06-032022Alzahrani, A., Tsai, Y.-S., Kovanovic, V., Moreno Marcos, P. M., Jivet, I., Aljohani, N., Gasevic, D. (2022). Success-Enablers of Learning Analytics Adoption in Higher Education: A Quantitative Ethnographic Study. In: Wasson, B., Zörgő, S. (eds). Advances in Quantitative Ethnography : Springer Nature Limited. Pp. 395-409978-3-030-93859-8https://hdl.handle.net/10016/43928Proceedings of: Third International Conference on Quantitative Ethnography 2021, (ICQE 2021). Virtual conference, Nov. 6-11, 2021This paper focuses on the area of success-enablers in learning analytics (LA) adoption from the perspective of senior managers in higher education institutions (HEIs). A significant body of academic literature exists about challenges in LA. However, to date, the success-enablers from the perspectives of institutional senior managers have received limited attention. This research aims to address this gap reporting on the findings of a study that conducted a series of semi-structure interviews with senior managers at 44 European HEIs. A detailed thematic analysis was conducted on the interviews to tease out the main success-enablers. Then, connections of different success-enablers were analyzed using epistemic network analysis (ENA). The analysis showed that the success-enablers in HEIs that had fully adopted LA depended on the involvement of high-level stakeholders, setting an embedded strategy, getting a technology support from the external partnership, or having a strategic analytical culture. The HEIs that were preparing or only partly adopted LA depended on success-enablers such as having a developing analytical culture or a delegation of expertise in LA-related activity. The findings of this study can help HEIs create strategies that can support successful adoption of LA.15engEpistemic Network AnalysisHigher EducationLearning Analytics, Success-Enablers, Adoption Scopeconference paperInformáticaIngeniería Industrialhttps://doi.org/10.1007/978-3-030-93859-8_26395409Advances in Quantitative Ethnography1522CC/0000033253