There are a great variety of half- and full-day workshops and tutorials available at LAK’17 as well as a two-day hackathon. Find out the details of each below, including when they will take place and if they are open sign-up or require an application to participate. Colors indicate mini-track themes of interests and are explained below the table.
Registration for pre-conference events takes place in the conference registration tool which is now open.
Themed Mini-Tracks for Pre-Conference Events
This year we have organised the LAK workshops into thematic groupings, or mini-tracks. These were conceived to provide a clear overview of the kinds of event taking place in the pre-conference workshops and tutorials, and to encourage participants and organisers to build on synergies identified for maximum impact. The workshop chairs have encouraged workshop organisers to engage with each other, to provide continuity and share resources and perspectives. These mini-tracks are:
- Data from Many Places and Spaces [SPACES/PLACES]: The workshops in this mini-track focus on learning across modalities and spaces, building on previous workshops at LAK and elsewhere to bring into focus learning beyond computer-interaction based log files.
- Applying Learning Analytics in MOOCs [MOOCs]: The workshops in this mini-track focus on the application of learning analytics to learning in MOOCs.
- Using Policy to Drive the Adoption of LA: Community, Institutional and International Perspectives: [POLICY]: The workshops in this mini-track focus on policy considerations in the development and application of learning analytics.
- Practical Methods in Learning Analytics and Evaluation [METHODS]: The workshops in this mini-track focus on development of particular methods in learning analytics, and the evaluation of applied learning analytics.
- Learning About and From Learning Analytics [LEARNING]:– The workshops in this mini-track focus on developing learning around learning analytics, including how we develop learning resources for a range of stakeholders to better understand the application of learning analytics to practical contexts.
LAK17 Hackathon (Full Days Mon & Tues) – Getting the Right Information to the Right People So They Can Take the Right Action
Website: https://lakhackathon.wordpress.com/
Organisers: Adam Cooper, Alan Berg, Niall Sclater, Tanya Dorey-Elias, Kirsty Kitto
How to join: Open signup
Mini-track: Learning about and from learning analytics [LEARNING]
Abstract: The hackathon is intended to be a practical hands-on workshop involving participants from academia and commercial organizations with both technical and practitioner expertise. It will consider the outstanding challenge of visualizations which are effective for the intended audience: informing action, not likely to be misinterpreted, and embodying contextual appropriacy, etc. It will surface particular issues as workshop challenges and explore responses to these challenges as visualizations resting upon interoperability standards and API-oriented open architectures.
Monday Full Day Workshops/Tutorials
Beyond Failure: The 2nd LAK Failathon
Website: https://lakfailathon.wordpress.com
Organisers: Doug Clow, Rebecca Ferguson, Kirsty Kitto, Yong-Sang Cho
How to join: Open signup
Mini-track: Learning about and from learning analytics [LEARNING]
Abstract: The 2nd LAK Failathon will build on the successful event in 2016 and extend the workshop beyond discussing individual experiences of failure to exploring how the field can improve, particularly regarding the creation and use of evidence.
Failure in research is an increasingly hot topic, with high-profile crises of confidence in the published research literature in medicine and psychology. Among the major factors in this research crisis are the many incentives to report and publish only positive findings. These incentives prevent the field in general from learning from negative findings, and almost entirely preclude the publication of mistakes and errors. Thus providing an alternative forum for practitioners and researchers to learn from each other’s failures can be very productive. The first LAK Failathon, held in 2016, provided just such an opportunity for researchers and practitioners to share their failures and negative findings in a lower-stakes environment, to help participants learn from each other’s mistakes. It was very successful, and there was strong support for running it as an annual event. This workshop will build on that success, with twin objectives to provide an environment for individuals to learn from each other’s failures, and also to co-develop plans for how we as a field can better build and deploy our evidence base.
DesignLAK17: Quality metrics and indicators for analytics of assessment design at scale
Website: https://sites.google.com/site/designlak17
Organisers: Ulla Ringtved, Sandra Milligan, Linda Corrin, Allison Littlejohn, Nancy Law
How to join: See workshop website for call for participation
Mini-track: Practical methods in learning analytics and evaluation [METHODS]
Abstract: Notions of what constitutes quality in design in traditional on-campus or online teaching and learning may not always translate into scaled digital environments. The DesignLAK17 workshop builds on the DesignLAK16 workshop to explore one aspect of this theme, namely the opportunities arising from the use of analytics in scaled assessment design. New paradigms for learning design are exploiting the distinctive characteristics and potentials of analytics, trace data and newer kinds of sensory data useable on digital platforms to transform assessment. But, characteristics of quality assessment design need to be reconsidered, and new metrics for capturing quality are required. This symposium and workshop focuses on what might be appropriate quality metrics and indicators for assessment design in scaled learning. It aims to build a community of interest round the topic, to share perspectives, and to generate design and research ideas.
2nd Cross-LAK: Learning Analytics Across Physical and Digital Spaces
Website: http://crosslak.utscic.edu.au
Organisers: Roberto Martinez-Maldonado, Davinia Hernandez-Leo, Abelardo Pardo, Hiroaki Ogata
How to join: See workshop website for call for participation
Mini-track: Data from many places and spaces [SPACES/PLACES]
Abstract: Student’s learning happens where the learner is, rather than being constrained to a single physical or digital environment. It is of high relevance for the LAK community to provide analytics support in blended learning scenarios where students can interact at diverse learning spaces and with a variety of educational tools. This workshop aims to gather the sub-community of LAK researchers, learning scientists and researchers in other areas, interested in the intersection between ubiquitous, mobile and/or classroom learning analytics. The underlying concern is how to integrate and coordinate learning analytics seeking to understand the particular pedagogical needs and context constraints to provide learning analytics support across digital and physical spaces. The goals of the workshop are to consolidate the Cross-LAK sub-community and provide a forum for idea generation that can build up further collaborations. The workshop will also serve to disseminate current work in the area by both producing proceedings of research papers and working towards a journal special issue.
Half Day: Monday Morning
Learning Analytics and Policy (LAP) – international aspirations, achievements and constraints
Website: http://www.laceproject.eu/blog/lapolicy
Organisers: Megan Bowe, Weiqin Chen, Dai Griffiths, Tore Hoel, Jaeho Lee, Hiroaki Ogata, Griff Richards, Li Yuan, Jingjing Zhang
How to join: See workshop website for call for participation
Mini-track: Using policy to drive the adoption of LA: community, institutional and international perspectives [POLICY]
Abstract: The Learning Analytics and Policy (LAP) workshop explores and documents the ways in which policies at national and regional level are shaping the development of learning analytics. It promises to bring together representatives from around the world who will report in a standard format on the circumstances in their own country. The workshop will be preceded by an information gathering phase, and followed by the authoring of a report. The aspirations, achievements and constraints in the different countries will be contrasted and documented, providing a valuable resource for the future development of learning analytics.
Building the Learning Analytics Curriculum
Website: http://blogs.cuit.columbia.edu/cl3584
Organisers: Charles Lang, Stephanie Teasley, John Stamper
How to join: See workshop website for call for participation
Mini-track: Learning about and from learning analytics [LEARNING]
Abstract: Learning Analytics courses and degree programs both on-and offline have begun to proliferate over the last three years. As a result of this growth in interest from students, university administrators, researchers and instructors we believe it is a good time to review how these educational efforts are impacting the field, how synergy between instructors might be developed to greater serve the field and what kinds of best practices could be developed.
FutureLearn data: what we currently have, what we are learning and how it is demonstrating learning in MOOCs
Website: https://sites.google.com/site/lak17flworkshop
Organisers: Lorenzo Vigentini, Manuel León Urrutia, Ben Fields
How to join: See workshop website for call for participation
Mini-track: Applying Learning Analytics in MOOCs [MOOCs]
Abstract: Compared to other MOOC platforms, FutureLearn is a relatively new player and received limited coverage in the Learning Analytics and Educational Data Mining research. Founded by a partnership between the Open University in the UK, the BBC, The British Library and (originally) 12 universities in the UK, it recently surpassed 5 million learners worldwide.
FutureLearn has two distinctive features: 1) it was designed with a specific educational philosophy in mind, which focuses on the social dimension of learning; and 2) every learning activity provides opportunities for formal discussion and commenting. Furthermore, simple, stable datasets are made available for those involved in the course in near real-time opening up exceptional opportunities to use LA in practice while the courses are running and after they close informing course re-development.
This workshop invites contributions from researchers and practitioners aiming to showcase their most recent work and connect both individual and groups to share their research and evaluation activities on an international stage. All papers submitted will be included in a CEUR Proceedings volume.
As the first of its kind, this workshop will bring together a number of scholars, practitioners, educational developers, data scientists and analyst involved in the development, delivery, reporting and researching in and with the platform.
Half Day: Monday Afternoon
Workshop on Integrated Learning Analytics of MOOC Post-Course Development
Website: http://bit.ly/moocpcd
Organisers: Yuan Wang, Dan Davis, Guanliang Chen, Luc Paquette
How to join: See workshop website for call for participation
Mini-track: Applying Learning Analytics in MOOCs [MOOCs]
Abstract: MOOC research is typically limited to evaluations of learner behavior in the context of the learning environment. However, some research has begun to recognize that the impact of MOOCs may extend beyond the confines of the course platform or conclusion of the course time limit. This workshop aims to encourage our community of learning analytics researchers to examine the relationship between performance and engagement within the course and learner behavior and development beyond the course. This workshop intends to build awareness in the community regarding the importance of research measuring multi-platform activity and long-term success after taking a MOOC. We hope to build the community’s understanding of what it takes to operationalize MOOC learner success in a novel context by employing data traces across the social web.
LA Policy: Developing an Institutional Policy for Learning Analytics using the RAPID Outcome Mapping Approach
Website: http://sheilaproject.eu/2016/11/11/the-sheila-project-team-will-be-holding-a-workshop-at-the-7th-international-learning-analytics-knowledge-conference
Organisers: Yi-Shan Tsai, Dragan Gašević, Pedro Muñoz-Merino
How to join: Open signup
Mini-track:Using policy to drive the adoption of LA: community, institutional and international perspectives [POLICY]
Abstract: This workshop aims to promote strategic planning for learning analytics in higher education through the development of institutional policies. While the adoption of learning analytics is predominantly observed in a small-scale and bottom-up manner, it is believed that a systemic implementation can bring the greatest impact to the education system and lasting benefits to learners. To achieve this, a policy that is relevant to contexts and stakeholders at various levels can effectively aid the success of learning analytics.
The workshop involves two components. The first component includes a set of presentations about the state of learning analytics in higher education, drawing on results from an Australian and a European project examining institutional learning analytics policy and adoption processes. The second component is an interactive session where participants are encouraged to share their motivations for adopting learning analytics and challenges that have emerged in their institutions. Thereafter, participants will use the RAPID Outcome Mapping Approach (ROMA) to create a draft policy that articulates how the various challenges identified can be addressed. The workshop will develop an understanding of organisational operation for learning analytics and provide an opportunity for stakeholders to engage in a strategic planning process for this.
Quasi-Experimental Design for Causal Inference Using Python and Apache Spark: A Hands-on Tutorial
Website: http://www.mheducation.com/lak2017.html
Organisers: Shirin Mojarad, Nicholas Lewkow, Alfred Essa, Jie Zhang
How to join: Open signup (some knowledge of Python is required)
Mini-track: Practical methods in learning analytics and evaluation [METHODS]
Abstract: Educational practitioners and policy makers require evidence supporting claims about educational efficacy. Evidence is often found using causal relationships between education inputs and student learning outcomes. Causal inference covers a wide range of topics in education research, including efficacy studies to prove if a new policy, software, curriculum or intervention is effective in improving student learning outcomes. Randomized controlled trials (RCT) are considered a gold standard method to demonstrate causality. However, these studies are expensive, timely and costly, as well as not being ethical to conduct in many educational contexts. Causality can also be deducted purely from observational data. In this tutorial, we will review methodologies for estimating the causal effects of education inputs on student learning outcomes using observational data. This is an inherently complex task due to many hidden variables and their inter-relationships in educational research. In this tutorial, we discuss causal inference in the context of educational research with big data. This is the first tutorial of its kind at Learning Analytics and Knowledge Conference (LAK) that provides a hands-on experience with Python and Apache Spark as a practical tool for educational researchers to conduct causal inference.
Tuesday Full Day Workshops/Tutorials
Writing Analytics Literacy – Bridging from Research to Practice
Website: wa.utscic.edu.au/events/lak17wa
Organisers: Simon Knight, Laura Allen, Andrew Gibson, Danielle McNamara, Simon Buckingham Shum
How to join: See workshop website for call for participation
Mini-track: Learning about and from learning analytics [LEARNING]
Abstract: Broadly defined, writing analytics involves the measurement and analysis of written texts for the purpose of understanding writing processes and products, in their educational contexts. Writing analytics are ultimately aimed at improving the educational contexts in which writing is most prominent. The principal goal of writing analytics is to move beyond assessment of texts divorced from contexts, transitioning instead to a more nuanced investigation of how analytics may be effectively deployed in different writing contexts. Writing analytics thus aims to employ learning analytics to develop a deeper understanding of writing skills.
There is untapped potential in achieving the full impact of learning analytics through the integration of tools into practical pedagogic contexts. To meet this potential, more work must be conducted to support educators in developing learning analytics literacy. The proposed workshop addresses this need by building capacity in the learning analytics community and developing an approach to resourcing for building ‘writing analytics literacy’.
The workshop will be targeted at:
- Providing a tutorial regarding key tools for writing analytics research and practice, highlighting existing tools, resources, and practices
- Building a resource bank of sample datasets from which learning vignettes might be developed
- Creating a ‘wish list’ of resources to support practitioners in their learning analytics literacy around writing, including developing a framework describing the kinds of pedagogic contexts in which particular tools might be integrated.
The workshop thus proposes to provide both hands-on tutorial elements, and resource-creation.
Current and Future Multimodal Learning Analytics Data Challenges
Website: http://sigmla.org/mmla2017/
Organisers: Daniel Spikol, Luis Prieto, Multu Cukurova, Marcelo Worsley, Xavier Ochoa, M.J. Rodriguez-Triana
How to join: See workshop website for call for participation
Mini-track: Data from many places and spaces [SPACES/PLACES]
Abstract: Multimodal Learning Analytics (MMLA) captures, integrates and analyzes learning traces from different sources in order to obtain a more holistic understanding of the learning process, wherever it happens. MMLA leverages the increasingly widespread availability of diverse sensors, high-frequency data collection technologies and sophisticated machine learning and artificial intelligence techniques. The aim of this workshop is twofold: first, to provide participants hands-on experience with different multimodal datasets that reflect how MMLA can bring new insights and opportunities to investigate complex learning processes and environments; second, to collaboratively identify a set of grand challenges for further MMLA research, built upon the foundations of previous workshops on the topic.
Community Based Educational Data Repositories and Analysis Tools
Website: https://pslcdatashop.web.cmu.edu/LAK2017/
Organisers: Ken Koedinger, Ran Liu, John Stamper, Candace Thille, Phil Pavlik
How to join: Open signup
Mini-track: Using policy to drive the adoption of LA: community, institutional and international perspectives [LEARNING]
Abstract: This workshop will explore community based repositories for educational data and analytic tools that are used to connect researchers and reduce the barriers to data sharing. Leading innovators in the field, as well as attendees, will identify and report on bottlenecks that remain toward our goal of a unified repository. We will discuss these as well as possible solutions. We will present LearnSphere, an NSF funded system that supports that supports collaborating on and sharing a wide variety of educational data, learning analytics methods, and visualizations while maintaining confidentiality. We will then have hands-on sessions in which attendees have the opportunity to apply existing learning analytics workflows to their choice of educational datasets in the repository (using LearnShere’s simple drag-and-drop interface), add their own learning analytics workflows (requires very basic coding experience), or both. Leaders and attendees will then jointly discuss the unique benefits as well as the limitations of these solutions. Our goal is to create building blocks to allow researchers to integrate their data and analysis methods with others, in order to advance the future of learning science.
Half Day: Tuesday Morning
Developing Institutional Learning Analytics ‘Communities of Transformation’ to Support Student Success
Website: http://bayviewalliance.org/what-we-do/research-action-clusters-racs/rac3-using-academic-analytics-to-support-and-catalyze-transformation/2017-lak-workshop/
Organisers: Leah Macfadyen, Dennis Groth, George Rehrey, Linda Shepard, Jim Greer, Douglas Ward, Caroline Bennett, Jake Kaupp, Marco Molinaro, Matt Steinwachs
How to join: Open signup
Mini-track: Using policy to drive the adoption of LA: community, institutional and international perspectives [POLICY]
Abstract: Institutional implementation of learning analytics calls for thoughtful management of cultural change. This interactive half-day workshop responds to the LA literature describing the benefits and challenges of institutional LA implementation by offering participants an opportunity to learn about and begin planning for a program to actively engage their faculty as leaders of data exploration around the topics of student success. This session will share experiences from five institutions actively engaged in fostering Learning Analytics Communities (LAC) by identifying key issues, sharing lessons learned, and considering structural frameworks that are transferable to other institutional contexts. Structured discussion and activities will engage participants in developing an action plan for exploring the establishment of a LAC on their own campus.
Connecting Data with Student Support Actions in a Course: A Hands-on Tutorial
Website: https://latte.ee.usyd.edu.au/lak17tutorial/index.html
Organisers: Abelardo Pardo, Roberto Martinez-Maldonado, Simon Buckingham Shum, Simon McIntyre, Dragan Gašević, George Siemens
How to join: Open signup
Mini-track: Learning about and from learning analytics [LEARNING]
Abstract: The amount of data extracted from learning experiences has grown at an astonishing pace both in depth due to the increasing variety of data sources, and in breath with courses now being offered to massive student cohorts. However, in this emerging scenario instructors are now facing the challenge of connecting the knowledge emerging from data analysis with the provision of meaningful support actions to students within the context of an instructional design. The objective of this tutorial is to give attendees a set of hypothetical scenarios in which the knowledge extracted from a learning experience needs to be used to provide frequent personalized feedback to students.
Half Day: Tuesday Afternoon
Workshop of the Methodology in Learning Analytics Bloc
Website: https://sites.google.com/a/nyu.edu/lakmla2017/
Organisers: Yoav Bergner, Charles Lang, Geraldine Gray
How to join: See workshop website for call for participation
Mini-track: Practical methods in learning analytics and evaluation [METHODS]
Abstract: Learning analytics is an interdisciplinary and inclusive field, a fact which makes the establishment of methodological norms the challenging and important. This community-building workshop intends to convene methodology-focused researchers to discuss new and established approaches, comment on the state of current practice, author pedagogical manuscripts, and co-develop guidelines to help move the field forward with quality and rigor.