Perceptions and expectations about learning analytics from a brazilian higher education institution

Taciana Pontual Falcão, Rafael Ferreira Mello, Rodrigo Lins Rodrigues, Juliana Regueira Basto Diniz, Yi-Shan Tsai, Dragan Gaševic

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

3 Citations (Scopus)


Several tools to support learning processes based on educational data have emerged from research on Learning Analytics (LA) in the last few years. These tools aim to support students and instructors in daily activities, and academic managers in making institutional decisions. Although the adoption of LA tools is spreading, the field still needs to deepen the understanding of the contexts where learning takes place, and of the views of the stakeholders involved in implementing and using these tools. In this sense, the SHEILA framework proposes a set of instruments to perform a detailed analysis of the expectations and needs of different stakeholders in higher education institutions, regarding the adoption of LA. Moreover, there is a lacuna in research on stakeholders' expectations from LA outside the Global North. Therefore, this paper reports on the findings of the application of interviews and focus groups, based on the SHEILA framework, with students and teaching staff from a Brazilian public university, to investigate their perceptions of the potential benefits and risks of using LA in higher education in the country. Findings indicate that there is a high interest in using LA for improving the learning experience, in particular, being able to provide personalized feedback, to adapt teaching practices to students' needs, and to make evidence-based pedagogical decisions. From the analysis of these perspectives, we point to opportunities for using LA in Brazilian higher education.

Original languageEnglish
Title of host publicationLAK 2020 Conference Proceedings
EditorsVitomir Kovanović, Maren Scheffel, Niels Pinkwart, Katrien Verbert
Place of PublicationNew York NY USA
PublisherAssociation for Computing Machinery (ACM)
Number of pages10
ISBN (Electronic)9781450377126
Publication statusPublished - 2020
EventInternational Conference on Learning Analytics and Knowledge 2020 - Frankfurt, Germany
Duration: 23 Mar 202027 Mar 2020
Conference number: 10th


ConferenceInternational Conference on Learning Analytics and Knowledge 2020
Abbreviated titleLAK 2020
Internet address


  • Higher education institutions
  • Human factors
  • Learning analytics
  • Qualitative research

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