Pre-conference Schedule
Please note, due to the virtual format of LAK21, organizers have decided that pre-conference sessions will only be 3 hours per synchronous workshop or session. The only exception to this schedule is the LAKathon which may have multiple synchronous sessions throughout the two days - a detailed schedule for the LAKathon will be available soon.
April 12 & April 13, 2021 - Two Day Event (Hackathon)
Interactive Workshop Session
Welcome to the seventh Learning Analytics Hackathon (LAKathon). The LAKhathon 2021 will become an online laboratory to envisage future Learning Analytics (LA) applications with an emphasis on supporting Learning and mental health through online strategies. Do you have a research question, a dataset or online support orientated idea you would like to explore? Bring it to the LAKathon! We encourage joining this inclusive online workshop no matter what your background or skills, everyone is welcome. We aim to address the science-practice divide by having practitioners and researchers from diverse fields working in multidisciplinary teams towards common objectives.
Organizers:
Daniele Di Mitri, DIPF | Leibniz Institute for Research and Information in Education
Alan Berg, University of Amsterdam
Gábor Kismihók, Leibniz Information Centre for Science and Technology
José Ruipérez-Valiente, University of Murcia
Kirsty Kitto, University of Technology Sydney
Jan Schneider, DIPF | Leibniz Institute for Research and Information in Education
Atezaz Ahmad, DIPF | Leibniz Institute for Research and Information in Education
Stefan Mol, Amsterdam Business School, University of Amsterdam
Website:
April 12, 2021 - Day 1, 6 AM to 9 AM PST
Interactive Workshop Session
The workshop aims to explore how learning analytics can effectively capture students' learning experiences across diverse learning, including practice-based activities (medical simulations, sports, field-based science, vocational trades). Currently, under the current global pandemic, the notion of cross physical and virtual spaces plays a substantial factor and challenge for MMLA, which has been focused on collaborative learning in physical spaces. The workshop will serve as a forum to exchange ideas on how we, as a community, can use our knowledge and experiences from CrossMMLA to design new tools to analyse evidence from multimodal and multisystem data.
Organizers:
Daniel Spikol CET Copenhagen
Xavier Ochoa EST New York
Marcelo Worsley CST Chicago
Daniele Di Mitri CET Frankfurt
Mutlu Cukurova GMT London
Roberto Martinez-Maldonado AEDT Melbourne
Jan Schnieder CET Frankfurt
Website:
April 12, 2021 - Day 1, 9 AM to 12 PM PST
Mini-track/symposium
This workshop aims to gather researchers from both the Gamification and Learning analytics domains. These two complementary approaches have a common goal: to improve learner motivation and engagement. While the gamification approach tends to integrate motivational mechanisms relevant for learners into learning environments, learning analytics aim at identifying and predicting learner motivation and engagement during a course. Researchers will be invited to present their ongoing projects at the intersection of these two areas, in order to identify the future agenda for the research field.
Organizers:
Élise Lavoué, Université Jean Moulin Lyon 3, Lyon, France
Audrey Serna, INSA Lyon, Lyon, France
Davinia Hernández-Leo, Universitat Pompeu Fabra, Barcelona, Spain
Katrien Verbert, KU Leuven, Leuven, Belgium
Vero Vanden Abeele, KU Leuven, Leuven, Belgium
Website:
Mini-track/symposium
Initiated in 2020, the purpose of the symposium is to bring together a community of researchers and practitioners who work on data-driven analytics for detecting students at-risk and on strategic institutional initiatives for addressing dropouts in Higher Education.
The activities will include group discussions about the accepted submissions, a plenary discussion on shaping best practices and building a knowledge base as well as a planning of the dissemination of the results & future joint actions.
Organizers:
Juan I. Asensio-Pérez, Universidad de Valladolid, Spain
Yannis Dimitriadis, Universidad de Valladolid, Spain
François Bouchet, Sorbonne Université, France
Vanda Luengo, Sorbonne Université, France
Geoffray Bonnin, Université de Lorraine, France
Anne Boyer, Université de Lorraine, France
Armelle Brun, Université de Lorraine, France
Mohamed Amine Chatti, University of Duisburg-Essen, Germany
Irene-Angelica Chounta, University of Tartu, Estonia
María Jesús Rodríguez-Triana, Tallinn University, Estonia
Kairit Tammet, Tallinn University, Estonia
Agathe Merceron, Beuth University of Applied Sciences
Petra Sauer, Beuth University of Applied Sciences
Website:
Mini-track/symposium
Given the diversity of the applications of network science to learning analytics, this workshop aims to identify common challenges experienced through the use of network science methodologies. The workshop will invite researchers working in the area to share their work and reflect on common challenges. We envision themes of causality, linkage between micro- and macro-processes, use of time and space, elements of generalizability and validity to surface in the group discussions. The workshop aims to gather LA scholars to build a foundation for network modelling of learning data and shape strategies of future work in this important sub-field of LA.
Organizers:
Oleksandra Poquet, C3L, University of South Australia
Bodong Chen, University of Minnesota
Mohammed Saqr, University of Eastern Finland
Tobias Hecking, German Aerospace Center
Website:
April 12, 2021 - Day 1, 1 PM to 4 PM PST
Interactive Workshop Session
Ethical considerations and the values embedded in the design and use of Learning Analytics (LA) systems have received considerable attention. However, little is known about how conceptual understandings of ethics work in practice and what tensions practitioners (e.g., researchers, teachers, learners) experience when designing or using LA with care. This interactive workshop will provide participants with a space for dialogue around Responsible LA. We invite participants to bring edge cases to discuss ethical considerations covered and not covered in LA practices. The outcomes will help inform LA practitioners on ethical tensions that need to be addressed with care and researched.
Organizers:
Teresa Cerratto Pargman, Stockholm University, Sweden.
Cormac McGrath, Stockholm University, Sweden.
Olga Viberg, Royal institute of technology, Sweden.
Kirsty Kitto, University of Technology Sydney, Australia
Simon Knight, University of Technology Sydney, Australia
Rebecca Ferguson, The Open University, UK.
Website:
https://sites.google.com/dsv.su.se/responsible-la/home?authuser=0
April 12, 2021 - Day 1, 4 PM to 7 PM PST
Interactive Workshop Session
In this workshop we’ll work together to make explicit connections between theory and learning at any stage of research – from conceptualisation right through to analysis and interpretation. The organisers will set the scene by giving an overview of theory use in learning analytics, followed by short talk from Sarah Howard and Karl Maton on ‘Theory that Works with Big Data’. The remainder of the time will be given over to roundtable discussions. Participants will be invited to nominate a current research project that would benefit from a roundtable-style discussion with colleagues, along with a theoretical framework of interest. We’ll close with some tech-mediated birds of a feather activities, and consider gathering this community of practice together again.
Organizers:
Kathryn Bartimote, University of Sydney
Sarah K. Howard, University of Wollongong
Dragan Gašević, Monash University
Website:
https://sites.google.com/view/lak21-theoryworkshop/home?authuser=0
Interactive Workshop Session
This workshop seeks to build on the momentum from recent years within the LAK community, around the contributions that Human-Centred Design theory and practice should make to Learning Analytics system conception, design, implementation and evaluation. The term human-centred learning analytics (HCLA) was recently coined to refer to the subcommunity of LA researchers and practitioners interested in utilising the body of knowledge and practice from design communities, such as participatory design and co-design, into data-intensive educational contexts. Although there is a growing interest in designing LA systems with students and teachers, several questions still remain regarding how the LA community can appropriate design approaches from other communities and identify best practices that can be more suitable for LA developments. This workshop intends to address some of these questions.
Organizers:
Roberto Martinez-Maldonado, Monash University, Australia
Yannis Dimitriadis, University of Valladolid, Spain
Kenneth Holstein, Carnegie Mellon University, United States
Alyssa Wise, New York University, United States
Carlos Prieto-Alvarez, The University of Sydney, Australia
Fabio Campos, New York University, United States
Juan Pablo Sarmiento, New York University, United States
June Ahn, University of California, Irvine, United States
Lu Lawrence, Carnegie Mellon University, United States
Simon Buckingham Shum, University of Technology, Sydney, Australia
Website:
Interactive Workshop Session
The Annual 6th DesignLAK Workshop addresses a need to be able to rapidly prototype learning analytics visualisations with educators based on their needs relating to the learning designs used in their teaching context. In this interactive, 3-hour workshop we explore an alternative approach to this prototyping process which helps educators to design learning analytics visualisations in a less time- and expertise-intensive way. Workshop participants will use the DIVE tool to create visualisations useful for their teaching contexts and provide feedback on the process to inform further work on how this tool could be adapted to support learning analytics application development.
Organizers:
Linda Corrin, Swinburne University of Technology
Aneesha Bakharia, University of Queensland
Nancy Law, University of Hong Kong
Ulla Ringtved, University College of Northern Denmark
Sandra Milligan, University of Melbourne
Website:
Website coming soon
Mini-track/symposium
As the adoption of digital learning materials in modern education systems is increasing, the analysis of reading behavior and their effect on student performance gains attention. This workshop seeks to foster research into the analysis of students’ interaction with ebooks, and find new ways in which it can be used to inform and provide meaningful feedback to teachers, students and researchers. Building on previous years workshops at LAK19/LAK20 which focused on reading behavior in higher education, this year we will offer participants a new challenge that focuses on secondary school reading behavior using a synthetic dataset trained from actual data.
Organizers:
Brendan Flanagan (Kyoto University, Japan)
Atsushi Shimada (Kyushu University, Japan)
Rwitajit Majumdar (Kyoto University, Japan)
Hiroaki Ogata (Kyoto University, Japan)
Website:
April 13, 2021 - Day 2, 9 AM to 12 PM PST
Interactive Workshop Session
Learner accessibility is often linked to physical infrastructure or, in online learning contexts, guidelines for web design. Learning analytics offer new possibilities for identifying and removing barriers to accessibility in learning environments. This workshop is a step towards developing solutions. It will take the form of an evidence café, a structured event in which participants will discuss technical and pedagogic approaches to accessibility, barriers faced by disabled students and educators, challenges faced by those who design and research learning analytics. The intended outcomes are to raise awareness of accessible learning and analytics, and to build a community of researchers.
Organizers:
Tina Papathoma, The Open University, UK
Rebecca Ferguson, The Open University, UK
Dimitrios Vogiatzis, The Open University, UK
Website:
https://sites.google.com/view/accessible-analytics-learning/
Interactive Workshop Session
The workshop focuses on the affordances and challenges of collaborating with educators to make games and game data useful and meaningful for classroom use. The organizers will introduce a process that can lead collaborative development of learning analytics and kickoff the workshop with an overview of their games. Next, participants will deep dive with one game of their choosing. The workshop will then showcase participant presentations selected from an open call for contributions. Participants will get to present, discuss, and receive feedback from one another. We anticipate a Special Interest Group emerging from the workshop as well as potential publications.
Organizers:
Yoon Jeon (YJ) Kim, University of Wisconsin-Madison
José A. Ruipérez-Valiente, University of Murcia
Grace C. Lin, Massachusetts Institute of Technology
Nathan Holbert, Teachers College, Columbia University
Matthew Berland, University of Wisconsin-Madison
Baltasar Fernández Manjón, Complutense University of Madrid
David Gagnon, University of Wisconsin-Madison
Website:
Interactive Workshop Session
Bayesian Knowledge Tracing (BKT) is a common statistical model used in intelligent tutoring systems to help adapt material by estimating when a student has mastered a skill. While the research community around BKT has been active, there has been a high barrier to entry given the lack of accessible software libraries. This tutorial will introduce participants to the first BKT library for Python, a computationally efficient implementation that allows for easy replication of many model variants from the literature. The tutorial will consist of 30 minutes of lecture and 2 hours of notebook-based, hands-on tutorial activities and group work.
Organizers:
Zachary Pardos, UC Berkeley
Frederic Wang, UC Berkeley
Anirudhan Badrinath, UC Berkeley
Website:
April 13, 2021 - Day 2, 4 PM to 7 PM PST
Interactive Workshop Session
This workshop aims to bring members of the LA community together to share and discuss ideas around the philosophical foundations of the field. The hope is to begin construction of a philosophical framework to provide a strong foundation to help strengthen learning analytics as a relevant and impactful field. The workshop is the first step towards the development of a philosophical approach to help practitioners collaborate, interrogate, and develop this foundation. It is a sharing and collaborative workshop targeted at (a) those that have an a priori contribution to make towards a philosophical framework of learning analytics; and (b) those who have a more general interest in the topic, and would like to engage with the ideas proposed by others.
Organizers:
Pablo Munguia, Flinders University, Australia
Andrew Gibson, Queensland University of Technology, Australia
Website:
Interactive Workshop Session
The Learning Analytics Learning Network (LALN) was established to build capacity for the field of learning analytics. It does so by leveraging efforts that are currently taking place in existing communities and sharing with a worldwide network as a scalable way to develop requisite expertise in cyberinfrastructure, data science methods, and educational data, research, and practice. This workshop will include an introductory presentation on LALN, a panel discussion by local/regional learning analytics community leaders, and a brainstorming activity to explore the needs that LALN can support going forward, including relevant strategies, types and frequency of events, and facilitating networking opportunities.
Organizers:
Justin T. Dellinger, University of Texas at Arlington (USA)
Florence Gabriel, University of South Australia (Australia)
George Siemens, University of Texas at Arlington (USA) and University of South Australia (Australia)
Ryan Baker, University of Pennsylvania (USA)
Shane Dawson, University of South Australia (Australia)
Website:
Tutorial
This tutorial aims to bring researchers, practitioners, and other educational stakeholders into the design space of learning visualizations and provide tools/methods for handcrafting visualizations relevant to the context by guiding the user's attention to critical insights (i.e., derived from the learning design/expected outcomes, etc.). This tutorial will introduce data storytelling techniques and how to apply them when designing learning visualizations.
The main activities of this tutorial will include: (1) an introduction to data storytelling tools and methods, (2) a hands-on activity for designing a low-fidelity prototype that includes storytelling elements, and (3) networking opportunities to build a community on educational data storytelling research.
Organizers:
Vanessa Echeverria, Escuela Superior Politécnica del Litoral, ESPOL, Guayaquil, Ecuador
Lu Lawrence, Carnegie Mellon University, CMU, Pittsburgh, United States
Yi-Shan Tsai, Monash University, Melbourne, Australia
Shaveen Singh, Monash University, Melbourne, Australia
Gloria Fernandez-Nieto, University of Technology Sydney, UTS, Sydney, Australia
Roberto Martinez-Maldonado, Monash University, Melbourne, Australia
Website:
Interactive Workshop Session
The workshop focuses on the connections between learning analytics and assessment. The workshop will address key open challenges in learning analytics that are related to reliability and validity of data collection and analysis, use of learning analytics in formative and summative assessment, measurement of learning progression, and assurance of assessment trustworthiness. The workshop will outline links between learning analytics and assessment. An open call for contributions is distributed to solicit brief descriptions of current research and practice projects for roundtable-style discussions with workshop participants. Expected outcomes are the formation of a community and a possible follow-up publication.
Organizers:
Dragan Gašević, Monash University, Australia
Mladen Raković, Monash University, Australia
Naif Aljohani, King Abudlaziz University, Saudi Arabia
José A. Ruipérez Valiente, University of Murcia, Spain
Sandra Milligan, University of Melbourne, Australia
Saeed Ul Hassan, Information Technology University, Pakistan
Website:
Interactive Workshop Session
Learning analytics (LA) researchers often fail to collect the necessary data to answer research questions due to a lack of understanding of what types of data they need. This workshop aims to advance understanding of the necessities of iterative processes in data collection and analysis to address the issue. The workshop includes panel talks by the organizers, who have experience in data collection tool design, and discussion to sketch out designs of potential Evidence-Based Iterative (EBI) processes. which can help LA community update the design of the data collection system in consideration of research contexts and findings from previous iterations.
Organizers:
Heeryung Choi, University of Michigan
Christopher Brooks, University of Michigan
Caitlin Hayward, University of Michigan
Neil Heffernan, Worcester Polytechnic Institute
Dragan Gasevic, Monash University.
Kirsty Kitto, University of Technology Sydney
Abelardo Pardo, University of South Australia
Phil Winne, Simon Fraser University
Website: