Doctoral Consortium – Tuesday, July 22nd
The AEID’2025 Doctoral Consortium will take place on 22 July, in parallel with conference workshops. It will run as a full-day event.
It will be divided into two thematic sessions. Each session will begin with a round of brief presentations, where each participant will have approximately (5-10) minutes to introduce their research project to the group in a “carousel”-style format.
After the presentations, we will continue with a poster and discussion session, where students can engage more deeply with mentors and attendees about their research.
Schedule
| 9:00-10:30 | Session 1: Presentations |
| 10:30-11:00 | Coffee Break 1 |
| 11:00-13:00 | Session 1: Posters and Discussions |
| 13:00-14:00 | Lunch Break |
| 14:00-15:30 | Session 2: Presentations |
| 15:30-16:00 | Coffee Break 2 |
| 16:00-18:00 | Session 2: Posters and Discussions |
Detailed Program
| SESSION 1 | ||
| Authors | Title | |
| 1 | Wen Chiang Lim and Neil Heffernan | Evaluating the Impact of LLM-Generated Assignment Report Summaries in Intelligent Tutoring Systems |
| 2 | Clara Belitz | Fair for whom? Investigating school identity, algorithmic fairness, and educational technologies |
| 3 | Amani Alrobai and Alexandra Cristea | Personality-Aware Conversational Intelligent Tutoring System with GenAI: Studying the effect on Learners in Introductory Programming |
| 4 | Betsy Araujo Grando | Perceptions of Secondary School Students Solving Math Word Problems in a Foreign Language with GenAI Support |
| 5 | Lachlan McGinness | AI Grading of Australian High School Physics Exams |
| 6 | Thumesha Jayatilake | Designing An Ethical Framework for the Integration of Generative AI in Higher Education: Balancing Stake-holder Interests and Enhancing Learning Outcomes |
| 7 | Eamon Worden and Neil Heffernan | Few-shot is All you Need, A Framework for RAG-Based LLM Feedback |
| 8 | Conrad Borchers, Kenneth R. Koedinger and Vincent Aleven | Intelligent Support for Practice Goal Setting to Enhance Learning |
| 9 | William Lee and Ivon Arroyo | Toward Extracting Computational Thinking Artifacts with Large Language Models: Empowering K-12 Educators |
| 10 | Sonika Pal, Prajish Prasad and Sridhar Iyer | Understanding Human-GenAI Collaboration for Complex Open-ended Problem-Solving Tasks in Online Settings |
| 11 | Aditya Rajmane, Ramkumar Rajendran and Kshitij Sharma | Identifying and Fostering Self-Regulated Learning Among Computer Programmers Using Artificial Intelligence Systems |
| 12 | Aysu Ismayilova | Integrating Learner Models: The mAIchart Project |
| 13 | Deliang Wang, Gaowei Chen and Yu Lu | Fine-tuning Large Language Models for Knowledge Tracing Harnessing Insights from Explainable AI |
| SESSION 2 | ||
| 14 | Duaa Baig, Diana Nurbakova, Sylvie Calabretto and Baba Mbaye | Enhancing Knowledge Tracing with Large Language Models (LLMs): A Proposal for PhD Consortium |
| 15 | Morgan Lee and Neil Heffernan | Improving Student Support Personalization with Historical Data and Theoretically Informed Feature Choice |
| 16 | Mario Adkins | Assessing the Effectiveness of AI Tutoring for Tertiary Academic Probation Students: A Repeated Measures Study using ChatGPT |
| 17 | Daniel Flood, Matthew England and Beate Grawemeyer | Predicting At-Risk Programming Students in Small Imbalanced Datasets using Synthetic Data |
| 18 | Vihanga Wijayasekara, Kyle Martin and Nirmalie Wiratunga | Towards Ordinal Few-Shot Learning for Automated Essay Grading |
| 19 | Ajanie Karunanayake, Antonette Shibani and Simon Knight | Supporting Information Problem Solving in the Age of Misinformation and Generative AI: A Socio-technical Approach |
| 20 | Liqun He, Manolis Mavrikis and Mutlu Cukurova | Towards Mining Effective Pedagogical Strategies from Learner–LLM Educational Dialogues |
| 21 | Aditi Haiman, Ivon Arroyo and Bruce McLaren | Comparing the Effectiveness of Digital Game-Based Learning and Embodied Learning |
| 22 | Yuri Noviello | Designing and Evaluating AI-generated Multimodal Analogy-Based Explanations |
| 23 | Kejia Zhang, Charaka Palansuriya and Aurora Constantin | Multimodal Story Generation Using Generative AI for Contextualised Mathematics Education |
| 24 | Alessio Ferrato | Large Language Models to Enhance Learning In Cultural Heritage |
| 25 | Chang Cai, Minyang Chow, Ruth Choe and Xiuyi Fan | AI-Powered Classification of Medical Students’ Professionalism Profiles: Early Detection and Personalised Intervention |
| 26 | Ivan Chepikov and Ilia Karpov | Rewriting the Rules: LLMs vs. Traditional ML in University Admissions |
| 27 | Yi Shang, Jingyun Wang and Xiaofei Qi | A Learner-AI-Parent Collaboration Framework for Home Learning Environment |
All accepted posters must follow the guidelines below to ensure consistency and quality during the conference.
Poster Format
- Size: A0 format (33.1″ × 46.8″), portrait orientation only
- File format for printing: PDF, high resolution (300 DPI recommended)
Poster Content
Each poster must include:
- Paper title (exactly as submitted)
- Name of the student and supervisor(s)
- University affiliation
Poster Printing Service (Optional)
Servizitalia, the company supporting the local organization of AIED 2025, offers a poster printing service at a cost of 30 euros. To use the service, send your final poster (PDF format) to: aied2025@servizitalia.it CC: Davide Taibi – davide.taibi@itd.cnr.it, Giosuè Lo Bosco – giosue.lobosco@unipa.it