LAK-WS 2024
Joint Proceedings of LAK 2024 Workshops

Table of Contents

The 6th Workshop on Predicting Performance Based on the Analysis of Reading and Learning Behavior (DC-LAK24)

• Preface1-2
  Summary: There were 11 papers submitted for peer-review to this workshop. Out of these, 11 papers were accepted for this volume, 9 as regular papers and 2 as short paper.
• Trustworthy and Explainable AI for Learning Analytics 3-12
  Min-Jia Li, Shun-Ting Li, Albert C. M. Yang, Anna Y.Q. Huang, Stephen J.H. Yang
• Using a Hierarchical Clustering Algorithm to Explore the Relationship Between Students' Program Debugging and Learning Performance 13-22
  Chao-Hung Liu, Ting-Chia Hsu
• Predicting Learning Achievement through Self-Regulated Learning Strategies, Motivation, and Programming Behaviors 23-31
  Pei-Xuan Wang, Ting-Chia Hsu
• Personalized Navigation Recommendation for E-book Page Jump 32-41
  Boxuan Ma, Li Chen, Min Lu
• Enhancing Personalized Learning with MBTI Forecasts and ChatGPT's Tailored Study Advice 42-46
  Yi-Chun Hsieh, Albert C.M. Yang
• Educational Data Analysis using Generative AI 47-55
  Abdul Berr, Sukrit Leelaluk, Cheng Tang, Li Chen, Fumiya Okubo, Atsushi Shimada
• The Feasibility of Utilizing ChatGPT in Learning Analytics for the Identification of At-Risk Students 56-63
  Zhi Qi Liu, Owen H.T. Lu, Hsiao-Ting Tseng
• Explore the Explanation and Consistency of Explainable AI in the LBLS Data Set 64-72
  Tiffany T.Y. Hsu, Owen H.T. Lu
• Educational Data Analysis using Generative AI 73-82
  Shuaileng Yuan, Sukrit Leelaluk, Cheng Tang, Li Chen, Fumiya Okubo, Atsushi Shimada
• Classroom Monitoring using Emotional Data 83-88
  Mohammad Nehal Hasnine, Ho Tan Nguyen, Gökhan Akçapınar, Ryugo Morita, Hiroshi Ueda
• Chatbots and English as a Foreign Language Learning: A Systematic Review 89-98
  Steve Woollaston, Brendan Flanagan, Hiroaki Ogata

Data Storytelling and Learning Analytics Workshop (DS-LAK24)

• Preface 99
  Summary: There were 7 papers submitted for peer-review to this workshop. Out of these, 6 papers were accepted for this volume, 4 as regular papers and 2 as short papers.
• Data Storytelling on Multi-Modal Knowledge Graph via Data Comics: a Case Study in Yanyuwa Language 100-117
  Zhiping Liang, Zijie Zeng, Gloria Fernandez Nieto, Yuheng Li, Yi-Shan Tsai, Guanliang Chen, Zachari Swiecki, Dragan Gašević, John Bradley, Lele Sha
• Data Storytelling for Feedback Analytics 118-123
  Bhagya Maheshi, Mikaela Elizabeth Milesi, Hiruni Palihena, Aaron Zheng, Roberto Martinez-Maldonado, Yi-Shan Tsai
• YarnSense: Automated Data Storytelling for Multimodal Learning Analytics 124-138
  Gloria Milena Fernández-Nieto, Vanessa Echeverria, Roberto Martinez-Maldonado, Simon Buckingham Shum
• Use of SHAP Values for Identifying Differences in Behaviors for Subpopulations Under Intervention 139-149
  Juan A. Talamás-Carvajal, Hector G. Ceballos-Cancinob, Roberto Martinez-Maldonado, Yi-Shan Tsai
• Automating Data Narratives in Learning Analytics Dashboards using GenAI 150-161
  Adriano Pinargote, Eddy Calderón, Kevin Cevallos, Gladys Carrillo, Katherine Chiluiza, Vanessa Echeverria
• From Visualizing to Narrativizing: Powerful Data Storytelling through Non-Player Characters 162-170
  Maurice A. Boothe Jr, Jeffrey S. Brenneman

Generative AI for Learning Analytics (GenAI-LA)

• Preface 171-172
  Summary: There were 12 papers submitted for peer-review to this workshop. Out of these, 9 papers were accepted for this volume, 7 as regular papers and 2 as short papers.
• 3DG: A Framework for Using Generative AI for Handling Sparse Learner Performance Data From Intelligent Tutoring Systems 173-184
  Liang Zhang, Jionghao Lin, Conrad Borchers, Meng Cao, Xiangen Hu
• An AI Agent Facilitating Student Help-Seeking: Producing Data on Student Support Needs 185-194
  Joonas Merikko, Anni Silvola
• Enhancing Trust in Generative AI: Investigating Explainability of LLMs to Analyse Confusion in MOOC Discussions 195-204
  Yuanyuan Hu, Nasser Giacaman, Claire Donald
• Generative AI for Critical Analysis: Practical Tools, Cognitive Offloading and Human Agency 205-213
  Simon Buckingham Shum
• Generative Multimodal Analysis (GMA) for Learning Process Data Analytics 214-218
  Ridwan Whitehead, Andy Nguyen, Sanna Järvelä
• GPT-3.5, GPT-4, Bard, and Claude’s Performance on the Chinese Reading Comprehension Test 219-222
  Bor-Chen Kuo, Pei-Chen Wu, Chen-Huei Liao
• Supporting Self-Regulated Learning with Generative AI: A Case of Two Empirical Studies 223-229
  Jacqueline Wong, Olga Viberg
• Supporting Student Decisions on Learning Recommendations: An LLM-Based Chatbot with Knowledge Graph Contextualization for Conversational Explainability and Mentoring 230-239
  Hasan Abu-Rasheed, Mohamad Hussam Abdulsalam, Cristian Weber, Madjid Fathi
• Tamil Co-Writer: Towards Inclusive Use of Generative AI for Writing Support 240-248
  Antonette Shibani, Faerie Mattins, Srivarshan Selvaraj, Ratnavel Rajalakshmi, Gnana Bharathy

Learning Analytics from Virtual Reality (LAVR)

• Preface 249-250
  Summary: There were 4 papers submitted for peer-review to this workshop. Out of these, 4 papers were accepted for this volume, 2 as regular papers and 2 as short papers.
• A Learning Analytics Dashboard to Investigate the Influence of Interaction in a VR Learning Application 251-259
  Birte Heinemann, Sergej Görzen, Ana Dragoljić, Lars Meiendresch, Marc Troll, Ulrik Schroeder
• Towards using the xAPI specification for Learning Analytics in Virtual Reality 260-271
  Sergej Görzen, Birte Heinemann, Ulrik Schroeder
• Approximating eye gaze with head pose in a virtual reality microteaching scenario for pre-service teachers 272-283
  Ivan Moser, Martin Hlosta, Per Bergamin, Umesh Ramnarain, Christo Van Der Westhuizen, Mafor Penn, Noluthando Mdlalose, Koketso Pila, Ogegbo Ayodele
• Towards Learning Analytics for Student Evaluation in the Metaversity 284-291
  Amir Winer, Nitza Geri

Marrying Asset- and Deficit-Based Approaches: A Data Feminist Perspective in Learning Analytics

• Preface 292-294
  Summary: There was 1 paper submitted for peer-review to this workshop. 1 paper was accepted for this volume.
• Exploring Strength- and Growth-Based Learning Analytics: Possibilities and Challenges for New Data, Models and Tools 295-301
  Alyssa Wise, Fanjie Li