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Workshops and Tutorials

Workshops

The following AIED and EDM workshops and events are taking place on the 27th and 31st of July and are available to all AIED registrants.

AIED – Intelligent Textbooks (full-day, hybrid)

Textbooks have evolved over the last several decades in many aspects. Most textbooks can be accessed online, many of them freely. They often come with libraries of supplementary educational resources or online educational services built on top of them. As a result of these enrichments, new research challenges and opportunities emerge that call for the application of AIED methods to enhance digital textbooks and learners’ interaction with them. Therefore, we ask: How to facilitate the access to textbooks and improve the reading process? What can be extracted from textbook content and data-mined from the logs of students interacting with it? This workshop seeks research contributions addressing these and other research questions related to the idea of intelligent textbooks. It aims at bringing together researchers working on different aspects of learning technologies to establish intelligent textbooks as a new, interdisciplinary research field.
https://intextbooks.science.uu.nl/workshop2022/

Organisers
  • Sergey Sosnovsky
  • Peter Brusilovsky
  • Andrew S. Lan
  • Richard G. Baraniuk
Time & Location
  • Date: July 27
  • Time: 10:00-12:30 and 13:30-16:00
  • Room: TLC113, first floor

AIED – Advances and Opportunities in Team Tutoring (half-day, virtual/Zoom)

The workshop covers the topic areas of approaches and challenges during team tutoring and collaborative learning in intelligent tutoring systems (ITSs). The development of team ITSs is a time-intensive and difficult task that includes technological, instructional, and design based challenges.
https://easychair.org/cfp/TeamTutoringWorkshopAIED2022

Organisers
  • Anne Sinatra
  • Benjamin Goldberg
Time & Location
  • Date: July 31
  • Time: 15:00-18:00
  • Room: Fully online

AIED – Interdisciplinary Approaches to Getting AI Experts and Education Stakeholders Talking (half-day, hybrid)

The present workshop aims to facilitate conversations within the Artificial Intelligence in Education (AIED) community around bridging the gap between AI efforts and educational stakeholders’ (teachers, students, parents, administrators, etc.) needs. In particular, the workshop will address existing barriers to collaboration between researchers and stakeholders, approaches envisioned and taken to address these challenges, and corresponding insights to help move the field forward in this area.
https://sites.google.com/colorado.edu/aied2022/home

Organisers
  • Rachel Dickler
  • Shiran Dudy
  • Areej Mawasi
  • Jacob Whitehill
  • Alayne Benson
  • Amy Corbitt
Time & Location
  • Date: July 31
  • Time: 13:00-16:00
  • Room: TLC113, first floor

Tutorials

AIED – Design, Build, Evaluate, and Implement Conversation-based Adaptive Instructional Systems (CbAIS)

Presenters: Xiangen Hu and Art Graesser

https://sites.autotutor.org/course/view.php?id=35

  • Date: July 31
  • Time: 10:00-12:30 and 13:30-16:00
  • Room: TLC116, first floor

AIED – ETS® AI Labs™ ways of working demonstration: How to build evidence-based, user-obsessed, AI-enabled learning solutions in an Agile framework

Presenters: Larisa Nachman, Kinta D. Montilus, Kristen Smith Herrick, K. Rebecca Marsh Runyon and Lisa Ferrara

https://www.ets.org/research/ai-labs

  • Date: July 31
  • Time: 10:00-12:30 and 13:30-16:00
  • Room: TLC123, first floor

AIED/EDM Alan Turing ATI@Durham Networking Event

Durham@ATI will build upon and expand existing regional networks, such as the N8 Digital Humanities and N8 Digital Health networks. It will also enable engagement in the potential opportunities and initiatives available across the Turing network – to deliver research collaborations with a range of partners. Durham@ATI will organise workshops on Data Science, AI and the Epistemological Engine, AI and Data in Education, Digital Humanities, AI and Data Science in Health, boosting and promoting Durham research in these important areas.

https://aihs.webspace.durham.ac.uk/durhamati/

EDM workshops

EDM – The Third Workshop of the Learner Data Institute: Big Data, Research Challenges, & Science Convergence in Educational Data Science (half-day, hybrid)

The Third Workshop of the Learner Data Institute (LDI) builds on the success of two previous, virtual workshops (at EDM 2020 & EDM 2021) and seeks to bring together researchers working across disciplines on data-intensive research of interest to the educational data science and educational data mining communities. In addition to welcoming work describing mature, data-intensive or “big data” research and emerging work-in-progress that spans traditional academic disciplines, the workshop organizers welcome case studies of interdisciplinary research programs and projects, including case studies of learning engineering efforts pursued by universities, learning technology providers, and others (both successful and unsuccessful), as well as position papers on important challenges for researchers harnessing “big data” and crossing disciplinary boundaries as they do so.
https://sites.google.com/view/learnerdatainstitute/ldiedm

Organisers
  • Vasile Rus, Ph.D., University of Memphis (Co-Chair)
  • Stephen E. Fancsali, Ph.D., Carnegie Learning, Inc. (Co-Chair)
  • Dale Bowman, Ph.D., University of Memphis
  • Jody Cockroft, AA, BS, CCRP, University of Memphis
  • Art Graesser, Ph.D., University of Memphis
  • Andrew Hampton, Ph.D., Christian Brothers University
  • Philip I. Pavlik Jr., Ph.D., University of Memphis
  • Steven Ritter, Ph.D., Carnegie Learning, Inc.
  • Deepak Venugopal, Ph.D., University of Memphis
Time & Location
  • Date: July 27
  • Time:  13:30 – 16:00 BST
  • Room: TLC124

EDM – FATED 2022: Fairness, Accountability, and Transparency in Educational Data (full-day, hybrid)

The increasing impact of machine learning and algorithmic decision making on education has brought about growing opportunities and concerns. Evidence has shown that these technologies can perpetuate and even magnify existing educational and social inequities. Research on fair machine learning has aimed to develop algorithms that can detect and, in some cases correct, bias, but this effort within the educational data mining community is still limited. In this workshop, we hope to spur discussion around algorithmic fairness and bias detection as specifically applied in an educational context. Submissions and panels will be invited to discuss (a) collection and preparation of benchmark datasets for bias detection and correction tasks, (b) evaluation protocol definition and metric formulation appropriate for bias and fairness in educational tasks, and (c) countermeasure design and development for biased and unfair circumstances. These specific topics will be complemented by a more general discussion of the education-specific challenges for fair machine learning in education, bringing together perspectives from both industry and academia. This workshop builds on the FATED workshop held at EDM 2020, and we expect the workshop to make connections among already interested researchers and provide a foundation for those who want to engage in this area.
http://fated2022.github.io

Organisers
  • Collin Lynch, North Carolina State University
  • Mirko Marras, University of Cagliari
  • Mykola Pechenizkiy, Eindhoven University of Technology
  • Anna N. Rafferty, Carleton College,
  • Steve Ritter, Carnegie Learning
  • Vinitra Swamy, EPFL
  • Renzhe Yu, University of California, Irvine
Time & Location
  • Date: July 27
  • Time: 10:00 – 12:30 & 13:30 – 16:00 BST
  • Room: TLC129

EDM – 6th Educational Data Mining in Computer Science Education (CSEDM) Workshop (half-day, virtual)

The objective of this workshop is to facilitate a discussion among our research community around Educational Data Mining (EDM) and AI in Computer Science Education. The workshop is meant to be an interdisciplinary event. Researchers, faculty and students are encouraged to share their data mining approaches, methodologies and experiences where AI is transforming the way students learn Computer Science (CS) skills.
https://sites.google.com/ncsu.edu/csedm-workshop-edm22/home

Organisers
  • Bita Akram, NC State University
  • Thomas Price, NC State University
  • Yang Shi, NC State University
  • Peter Brusilovsky, University of Pittsburgh
  • Sharon Hsiao, Santa Clara University
Time & Location
  • Date: July 27
  • Time: 15:30 – 18:00 BST (10:30 – 13:00 EST)

EDM – Causal Inference in Educational Data Mining (half-day, hybrid)

Causal questions–what works, for whom, when, and why–are central to learning sciences and policy, and the interface between causal inference and the data and methods of EDM and AIED is an exciting, crucial, under-explored area of research. This workshop is intended to spur discussion of some of the exciting methods available to address those questions, and of some of the open problems. It will include invited discussions of ongoing projects addressing causal questions, short talks about relevant work in progress, including work in any stage of development, and very short open-ended talks about unsolved problems. The workshop will be organized with the goal of stimulating and engendering critical, constructive, and cross-disciplinary discussions related to the presented work.
https://sites.google.com/umich.edu/causaledm22/home

Organisers
  • Adam Sales, Worcester Polytechnic Institute
  • Neil Heffernan, Worcester Polytechnic Institute
Time & Location
  • Date: July 27
  • Time: 13:30 – 16:00 BST
  • Room: TLC116

EDM – Using the Open Science Framework to promote Open Science in Education Research (half-day, hybrid)

Within the past 10 years there has been increasing momentum of the open science movement to make research more open, transparent, and reproducible. However, the adoption of open science practices in education lags behind other fields. In this hybrid tutorial, we will begin by providing a brief overview of open science practices, benefits and workarounds, as well as how the statistical foundations of open science, including the benefits for inference and hypothesis testing. In the second part of the workshop, we will provide a hands-on tutorial of how to use the Open Science Framework to make projects, invite collaborators, preregister studies, share data, code, and materials. Participants in this workshop will gain a better understanding of open science practices, the reasons motivating their adoption, and how to use the Open Science Framework to make their research more open.
https://osf.io/m7cnr/

Organisers
  • Stacy T. Shaw, Worcester Polytechnic Institute, Center for Open Science Ambassador
  • Adam Sales, Worcester Polytechnic Institute
Time & Location
  • Date: July 27
  • Time: 13:30 – 16:00 BST
  • Room: TLC123