Working Groups

Artificial Intelligence Working Group (AIWG)

This working group aims to explore the role of artificial intelligence (AI) in education though a research-creation based lens. Accepting a baseline premise that AI, including generative AI, is already prolific and here to stay, the goal is not to debate whether AI should or should not be used in education but to investigate possibilities for how AI is used. As a group we will discuss a variety of multimedia use cases, focused on matters of concern to the working group members, whether that be information searching, learning assessment, curriculum design, privacy and copyright, algorithmic literacy, relationality and digital equities, and so on. Our aim is to create case examples and collect these AI experiments in a volume and seek an appropriate form of publication / knowledge sharing. Through creative engagement with AI, we will host a dialogue with the future of education in an age of artificial intelligence and awareness. These experimental propositions can be fully realized or purely conceptual. We aim to engage in fruitful discussion and critique of various examples and products derived using generative AI that address a broadly construed understanding of human (and machine) learning, knowledge, and education.

Facilitators

Kedrick James (LLED)

Members

Susan Curtis (ELI)
Bryan Lee (OPL)
Leah Macfadyen (MET)
Kelvin Mok (OPL)

 
Interested in joining this working group? Email us to learn more and submit your request to join.
 
 
 
 
 
 
 
 

Accessibility Working Group (AWG)

The Accessibility Working Group (AWG) is a group of community members in the Faculty of Education. Its intended role is to provide an avenue for its members to discuss, explore and share on topics related to accessibility, and how this can impact our work, research, and practice of teaching and learning. The group is interested in delving into topics such as Universal Design for Learning (UDL) and web accessibility. As this group begins meeting in the 2024-2025 academic year, more specific goals will emerge based on the needs and interests of its members and the Faculty of Education. Through this work, AWG plans to broaden awareness of accessibility across the Faculty and build capacity to implement accessible practices in our work at UBC. LDDI provides any support needed to facilitate this work.

Facilitators

Alison Li (LDDI)
Surita Jhangiani (ECPS)
Hazel Ryan-Sheehan (ECPS)
Melodie Corbett (LDDI)
Maryam Danaei Ababin (LDDI)

Members

Shruti Asokan (DNSO)
Amy Caesar (EDCP)
Joanna Cannon (ECPS)
Andreea Cervatiuc (LLED)
Erika Fundelius (ECPS)
Nasrin Kowkabi (LLED)
Marcus Lau (ECPS)
Melanie Leeming (RRED)
Carl Ruest (LLED)
Terry Taylor (RRED)
Sonya Woloshen (TEO)

Sustainability Working Group (SWG)

The role of the Sustainability Working Group (SWG) is to weave together a complex view of environmental education and research across the Faculty of Education. The goal is to reflect on and engage with different articulations of climate justice advocacy and action by sharing our own beliefs, hopes, philosophies, curriculum theories, and stories of nature. The aim is to enhance teaching and learning for climate justice and to enrich professional, academic, and environmental places and practices.

Facilitators

Sandra Scott (EDCP)

Members

Kshamta Hunter (EDCP)
Iris Berger (ECED)
Shannon Leddy (EDCP)
Balraj Rathod (EDCP)
Danielle Tan (EDST)

Learning Analytics Working Group (LAWG) | 2023–2025

The Learning Analytics Working Group has concluded its work. Thank you to all the members for your valuable contributions, thoughtful insights, active engagement in discussions, and for co-organizing the 2025 LDDI Summer Institute. We are grateful to everyone who supported the group and shaped our Faculty’s understanding of learning analytics.

The Learning Analytics Working Group (LAWG) was a space for Faculty of Education community members to discuss, share and ask questions about Learning Analytics and how it relates to the practice of teaching and learning and to the existing educational theories and research. The goal of this work was to gain inward-facing knowledge about Learning Analytics methods, research, theories, goals, and tools at UBC and beyond, decipher meaningful and reliable LMS data, understand bias and ethical dilemmas of Learning Analytics, and apply and interpret data to support teaching and learning.

Facilitators

Leah Macfadyen (MET)
Eduardo Rebagliati (LDDI)

Members

Halimat Alabi (MET)
Susan Curtis (ELI)
Keri Ewart (MET)
Surita Jhangiani (ECPS)
Nasrin Kowkabi (LLED)
Kapil Regmi (EDST)
Fatemeh Salehian Kia (iSchool)
Sonya Woloshen (TEO)