Learning @ Scale 2020 will have workshops surrounding the planned conference times.
Designing Inclusive Learning Environments
Large-scale online learning environments present new opportunities to address the need for greater inclusivity in education. Unlike residential environments, which have physical and logistic constraints (e.g., classroom configurations, sizes, and scheduling) that impede our ability to enact more inclusive pedagogy, online learning environments can be personalized and adapted to individual learner needs. As these environments are completely technology mediated, they offer an almost infinite design space for innovation. Social-scientific research on inclusivity in residential settings provides insight into how we might design for online learning environments, however evidence of efficacious digital implementations of these insights is limited. This workshop aims to advance our understanding of the ways in which adaptivity can be leveraged to buttress inclusivity in STEM learning. Through brief paper presentations and collaborative activities we intend to outline design opportunities in the scaled learning space for creating more inclusive environments.
Artificial Intelligence for Video-based Learning at Scale
Video-based Learning (VBL) is pervasive in education. However, there are several challenges. Instructors are hesitant to use video because it takes a lot of time and effort to make videos. For students, watching a video can be a passive activity, and thus, limit learning. Artificial Intelligence (AI) approaches, such as machine learning, natural language processing, and computer vision, have a potential to help VBL be mutable (easily record and edit), bidirectional (provide personalized feedback), and interoperable (link to other information), just to name a few supported advanced characteristics. This one-day, multi-disciplinary workshop will bring together researchers and practitioners to collaboratively explore future VBL when embraced by AI. A series of activities, including poster/demo session, prototyping, exhibitions, and discussion, will facilitate the crosspollination and development of new ideas. In so doing, workshop participants will engage in critical reviews of emerging AI approaches and develop a joint research agenda to use them in future VBL.
Supporting Learners’ Self-regulation in LMOOCs: What Have We Done and How Far We Can Go?
This half-day workshop aims at collecting experiences of MOOC designers and MOOC educators to discuss what has been done to support SRL and what can be done to scaffold learners in MOOCs, particularly MOOCs for language learning purposes (LMOOCs). For this purpose, it is planned to come together with academicians and researchers working on related subjects within the scope of this workshop to develop a student support framework in large-scale learning environments.
In this workshop, the participants should actively participate and take part in both the face-to-face session and the discussions that may emerge on social media (via Twitter). In line with this process, the main problems faced by individuals learning a foreign language with the help of LMOOCs will be examined following the experiences of the participants and the organizers.
Building an Infrastructure for Computer Science Education Research and Practice at Scale
The goal of this workshop is to bring together the existing community of researchers working on the Infrastructure Design for Data-Intensive Research in Computer Science Education and a community of L@S researchers focused on CS Education. While both communities share many similar goals and could greatly benefit from each other work, the interaction between the communities is small. We hope that the proposed workshop will be instrumental in bringing together like-minded researchers from different communities, establishing collaboration, and expanding the scope of infrastructure project to address critical scaling issues.
Global Learning @ Scale
This workshop proposes specifically soliciting contributions and presentations from initiatives, programs, and platforms around the world. While many of these may already be presented at the full conference, we are also interested in more casual experience reports, case studies, and background presentations from individuals more closely acquainted with how learning at scale initiatives—including MOOCs, for-credit degree programs, informal learning environments, government initiatives, and so on—have unique needs and opportunities based on their local context. We refer to this as Global Learning @ Scale.
Educational A/B Testing at Scale
The emerging discipline of Learning Engineering is focused on putting into place tools and processes that use the science of learning as a basis for improving educational outcomes. An important part of Learning Engineering focuses on improving the effectiveness of educational software. In many software domains, A/B testing has become a prominent technique to achieve the software’s goals. Many large companies (Amazon, Google, Facebook, etc.) run thousands of AB tests and present at the Annual Conference on Digital Experimentation (CODE), but that venue is too broad to address AB testing issues specific to EdTech platforms. We see a need to address issues with running large-scale A/B tests within the educational context, where the use of A/B testing lags other industries. This workshop will explore ways in which A/B testing in educational contexts differs from other domains and proposals to overcome current challenges so that this approach can become a more useful tool in the learning engineer’s toolbox.
Learning Engineering @ Scale
Scaled learning requires a novel set of practices on the part of professionals developing and delivering systems of scaled learning. IEEE’s Industry Connections Industry Consortium for Learning Engineering (ICICLE) defines learning engineering as “a process and practice that applies the learning sciences, using human-centered engineering design methodologies, and data-informed decision-making to support learners and their development.” This event will bring together learning engineering experts and other interested
conference participants to further define the discipline and strategies to establish learning engineering at scale. It will also serve as a gathering place for attendees with shared interests in learning engineering to build community around the advancement of learning engineering as a professional practice and academic field of study.
Interdisciplinary research in the learning, computer and data sciences fields continue to discover techniques for developing increasingly effective technology-mediated learning solutions. However, these applied sciences discoveries have been slow to translate into wide-scale practice. This workshop will bring together conference participants to give input into models for scaling the profession of learning engineering and wide-scale use of learning engineering process and practice models.
Code Free Chatbot Development: An Easy Way to Jumpstart Your Chatbot!
Advancement in technology and innovation in teaching such as chatbot and extended reality can be daunting for teachers but as an educator, we need to leverage on these advancements to respond to the changes and challenges in the teaching and learning landscape. There are a number of tools available for teachers to use to overcome the challenges, and one of them is the application of artificial intelligence (AI) but creating a chatbot requires complex computer programming skills, and it is usually built from scratch to fit the intended educational purpose. This practice makes it difficult for teachers to adapt existing systems or to attempt in creating a similar version. In this workshop, we will be sharing our experiences gained from developing various chatbots for higher education using a commercial platform that can jumpstart your chatbot.