About the workshop

Research about Learning Analytics has increasingly gained attention, as demonstrated by the geographic and substantive scope of the International Learning Analytics and Knowledge (LAK) Conference. However, as the domain of LA is maturing, the connection of research to long-term applicability is relatively underdeveloped. This may hinder further investment of policy makers and administrators.

SASLAS19 (Scalability and Sustainability of Learning Analytics Solutions) will be organized as part of LAK19 on 4 or 5 March in Tempe, Arizona (US). The goal of our half-day workshop is to explore and discuss the scalability and sustainability of existing and proposed solutions, and to initiate the creation of a framework of strategies available to researchers and practitioners.

While Learning Analytics (LA) is still a relatively young discipline, it is quickly expanding, both in substantive scope and geographic interest. At each edition of the LAK conference, several promising results are being shared. However, in many cases LA tools demonstrate difficulties in making the transition from research artefacts into scalable solutions in real-life educational contexts. Research papers generally do not address the issues of scalability and sustainability of proposed solutions extensively, if at all, leaving practitioners with unclear guidelines to apply them in non-experimental settings.

Important dates

  • December 3, 2018: Paper submission deadline extended to December 10.
  • January 4, 2018: Notification of acceptance
  • January 8, 2018: Last day for early-bird registration
  • January 25, 2019: Submission of camera-ready version
  • March 4 or 5, 2019: Workshop in Tempe, Arizona


The first target group of the workshop are researchers that are actively publishing about LA solutions. The workshop invites them to assess their own or other’s work from a scalability and sustainability perspective and provides them with a contribution channel to extend previous studies. For this purpose, participants are invited to submit a paper (see below).

The second target group are policy makers, practitioners, student representatives, managers, and other stakeholders that either have hands-on experience with successful or unsuccessful implementations of LA at scale, or are exploring the opportunities. They will be invited to participate in the workshop discussions with a critical but constructive view.

Call for papers

Authors are invited to submit original unpublished work addressing one or more of the following topics.

  • Generalizability: not uncommonly, LA research takes place in favorable settings, e.g. involving a researcher-teacher with detailed knowledge of the specific course, or other highly motivated stakeholders. While an experiment-friendly context may be a valuable incubator for innovative LA solutions, it does not test or harden them for real-life applicability at scale. We would like to invite researchers to address this issue when presenting their own work, or to start from existing work to explore its reproducibility in challenging contexts.
  • Return on investment: several authors have raised questions about the impact of LA applications on learning (e.g. Dyckhoff et al. 2013Dawson et al. 2017), something that may be difficult to measure. However, it has recently been argued that impact is only part of the equation when making a business case (Broos et al. 2018). As LA projects are likely to end up competing for resources with other proposals, LA researchers need to include return-on-investment (ROI) in their reasoning. LA solutions that require only limited effort can be attractive, even if the expected impact is relatively low or even uncertain. Vice versa, LA projects that would require significant investment will be challenged with higher expectations. The workshop aims at creating awareness in the LA community to this consideration.
  • Change management and trust: even if issues of generalizability and ROI are addressed by LA projects, chances of sustainable and scalable implementations are limited without acceptance of learners, teachers and other stakeholders. Even the best models and feedback tools are of little use if they are not acted upon due to a lack of trust or willingness. Therefore, LA needs to address transparency, openness and understanding of user acceptance. Underestimation of the importance of institutional culture, resistance to innovation and the role of change management poses a big treat for success of LA within institutions (Macfadyen & Dawson 2012). Many lessons learned in general change management should not be ignored by the LA community and several change management frameworks are available for reuse. The ADKAR model, for instance, provides insight into five stages: awareness, desire, knowledge, ability and reinforcement (Hiat 2006). Similarly, several maturity assessment models have been developed in management science and information systems literature. It has been argued that institutions should build their LA maturity layer by layer, starting with modest implementations (Broos 2017).

Contributions of researchers, as well as practitioners, are welcomed. Submissions should have 3 pages at least and 12 at most and follow the Companion Proceedings, using the Companion Proceedings Template. Authors are strongly recommended to add an interactive demo or mockup of solutions where applicable. All submissions are handled by the EasyChair submission system. Please click the logo below to start your session.


  • Tom Broos is doctoral researcher specializing in Learning Analytics at KU Leuven (more).
  • Dragan Gašević is Professor of Learning Analytics in the Faculty of Education and Adjunct Professor in the Faculty of Information Technology at Monash University, Melbourne, Australia (more).
  • Abelardo Pardo is Professor and Dean Academic at the Division of Information Technology, Engineering and the Environment at the University of South Australia (more).
  • Hendrik Drachsler is Professor for Educational Technologies at Goethe University Frankfurt am Main and DIPF, Germany (more).
  • Rafael Ferreira works at Universidade Federal Rural de Pernambuco Department of Statistics and Informatics.
  • Katrien Verbert is an Associate Professor at the HCI research group of KU Leuven (more).
  • Tinne De Laet is tenure track professor at the Faculty of Engineering Science, KU Leuven (more).