Hakami, EyadHernández Leo, Davinia2021-04-302021-04-302020Hakami E, Hernández-Leo D. How are learning analytics considering the societal values of fairness, accountability, transparency and human well-being?: a literature review. In: Martínez-Monés A, Álvarez A, Caeiro-Rodríguez M, Dimitriadis Y, editors. LASI-SPAIN 2020: Learning Analytics Summer Institute Spain 2020: Learning Analytics. Time for Adoption?; 2020 Jun 15-16; Valladolid, Spain. Aachen: CEUR; 2020. p. 121-41.http://hdl.handle.net/10230/47267Comunicació presentada al LASI-SPAIN 2020: Learning Analytics Summer Institute Spain 2020, celebrat del 15 al 16 de juny de 2020 a Valladolid, Espanya.The scientific community is currently engaged in global efforts towards a movement that promotes positive human values in the ways we formulate and apply Artificial Intelligence (AI) solutions. As the use of intelligent algorithms and analytics are becoming more involved in how decisions are made in public and private life, the societal values of Fairness, Accountability and Transparency (FAT) and the multidimensional value of human Well-being are being discussed in the context of addressing potential negative and positive impacts of AI. This research paper reviews these four values and their implications in algorithms and investigates their empirical existence in the interdisciplinary field of Learning Analytics (LA). We present and highlight results of a literature review that was conducted across all the editions of the Learning Analytics & Knowledge (LAK) ACM conference proceedings. The findings provide different insights on how these societal and human values are being considered in LA research, tools, applications and ethical frameworks.application/pdfengCopyright © 2020 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0)info:eu-repo/semantics/conferenceObjectLearning analyticsFairnessTransparencyAccountabilityWellbeing/well-beinginfo:eu-repo/semantics/openAccess