First International Workshop on
Generative AI for Learning Analytics (GenAI-LA):
Exploring Practical Tools and Methodologies
to be held at the 14th International Learning Analytics and Knowledge Conference (LAK'24)
Tuesday, March 19, 2024 | Half Day | 9:00 AM to 12:30 PM JST
In-person Event: Kyoto, Japan
WORKSHOP MATERIALS
Early Access to VizChat (Empower your LADs with a contextualized Chatbot): https://forms.gle/zxHMQNnP455o9k3fA
Workshop Resources (incl. workshop papers, presentation slides, and virtual presentations): https://shorturl.at/koFO0
Collaborative Design Instructions: https://shorturl.at/oNPTW
Accessing Miro Board: https://shorturl.at/bis06
Welcome to the first annual workshop on Generative AI for Learning Analytics (GenAI-LA) to be held during the LAK'24 conference!
The aim of this in-person workshop is to ignite discussions and collaboration around the potential of GenAI in LA by bringing together a sub-community of LA researchers and practitioners with a range of expertise in learning sciences, software engineering, and artificial intelligence. Researchers and practitioners are encouraged to share their perspectives, methodologies, and experiences where GenAI-based practical tools and methodologies can benefit learning analytics research.
Registration: To register for the workshop, please visit the registration website for the LAK' conference by clicking on the register button.
CALL FOR WORKSHOP PAPERS
Empirical work to showcase work in progress, tools, or successful experiences of utilising GenAI techniques to advance the field of LA.
Discussion piece to provoke the audience to think about key issues and problems related to utilising GenAI in LA study or tool design.
Accepted workshop papers will be published in the CEUR Workshop Proceedings (CEUR-WS.org). Please note that accepted workshop papers will not be published in the LAK proceedings this year.
Suggested topics
The following can guide the selection of topics for submitted papers:
What are the different GenAI tools that can support the research and development of LA solutions?
How can GenAI tools be embedded into the different stages of the LA cycle, specifically from researching theoretical knowledge and developing prototype products to implementing practical solutions and evaluating intervention effectiveness?
What are the opportunities of GenAI in supporting both self-regulated and collaborative learning?
How can GenAI be utilized to create personalised learning experiences, content, and feedback for students?
How do we ensure that the application of GenAI in LA respects student privacy and ethical considerations?
How can educators and learners interact with GenAI tools to co-create learning experiences and materials?
How can GenAI aid in creating dynamic and interactive visualisations to represent learning analytics data?
In what ways can GenAI assist educators in making informed decisions based on learning analytics data?
How can GenAI techniques be employed to automatically generate constructive feedback for learners based on their performance?
How can GenAI be used to combine and analyse data from different educational platforms, tools, and mediums to provide holistic insights?
IMPORTANT DATES (GMT-12/AOE Timezone)
26 Oct 2023 Open Call for Submissions
16 Dec 2023 Deadline for Workshop Papers
13 Jan 2024 Notification of Acceptance for Papers
29 Jan 2024 Camera-Ready Deadline for Papers
March, 2024 1st GenAI-LA Workshop at LAK'24
AGENDA
9:00 - 9:15: Opening Remarks
A brief overview of GenAI in learning analytics and welcoming remarks to set the stage for the workshop activities.
9:15 - 10:00: Keynote Presentation - Prof. Ryan Baker
Featuring insights from Prof. Ryan Baker's latest research on the intersection of GenAI and learning analytics. This session will explore the transformative potential of GenAI in the educational landscape, followed by an interactive Q&A segment for attendees to engage directly with Prof. Baker.
10:00 - 10:30: Flash Presentation
Authors of selected workshop papers will present brief overviews of their research in a series of flash presentations, each lasting 2-3 minutes. An invited expert in LA and GenAI will provide constructive feedback and facilitate a discussion, encouraging interactive dialogue among presenters and participants.
10:30 - 11:00: Coffee Break
11:00 - 12:30: Collaborative Design Sessions
Participants will be organized into small, diverse groups for collaborative design sessions. Focusing on one of the essential research questions that aim to synergize learning analytics and GenAI. The session concludes with groups sharing their insights and proposed innovations with all workshop attendees.
Contact: lixiang.yan@monash.edu
ACCEPTED PAPERS
TamilCo-Writer: Towards inclusive use of generative AI for writing support (by Antonette Shibani, Faerie Mattins, Srivarshan Selvaraj, Ratnavel Rajalakshmi, Gnana Bharathy) [Presentation Video]
An AI Agent Facilitating Help-Seeking: Producing Data on Students’ Support Needs and Well-Being (by Joonas Merikko, Anni Silvola)
Enhancing Trust in Generative AI: Investigating Explainability of LLMs to Analyse Confusion in MOOC Discussions (by Yuanyuan Hu, Nasser Giacaman, Claire Donald) [Presentation Video]
3DG: A Framework for Using Generative AI for Handling Sparse Learner Performance Data from Intelligent Tutoring Systems (by Liang Zhang, Jionghao Lin, Conrad Borchers, Meng Cao, Xiangen Hu)
GPT-3.5, GPT-4, Bard, and Claude’s Performance on the Chinese Reading Comprehension Test (by Bor-Chen Kuo, Pei-Chen Wu, Chen-Huei Liao)
Supporting Self-Regulated Learning with Generative AI: A Case of Two Empirical Studies (by Jacqueline Wong, Olga Viberg)
Generative Multimodal Analysis (GMA) for Learning Process Data Analytics (by Ridwan Whitehead, Andy Nguyen, Sanna Järvelä)
Generative AI for Critical Analysis: Practical Tools, Cognitive Offloading and Human Agency (by Simon Buckingham Shum)
Supporting Student Decisions on Learning Recommendations: An LLM-Based Chatbot with Knowledge Graph Contextualization for Conversational Explainability and Mentoring (by Hasan Abu-Rasheed, Mohamad Hussam Abdulsalam, Christian Weber, Madjid Fathi)
ORGANISERS
Lixiang Yan (Monash University)
Andy Nguyen (University of Oulu)
Lele Sha (Monash University)
Jionghao Lin (Carnegie Mellon University)
Mutlu Cukurova (University College London)
Kshitij Sharma (Norwegian University of Science and Technology)
Roberto Martinez-Maldonado (Monash University)
Linxuan Zhao (Monash University)
Yuheng Li (Monash University)
Yueqiao Jin (Monash University)
Dragan Gašević (Monash University)