{"id":872,"date":"2025-06-22T08:56:44","date_gmt":"2025-06-22T08:56:44","guid":{"rendered":"https:\/\/aied2025.itd.cnr.it\/?page_id=872"},"modified":"2025-07-17T15:44:36","modified_gmt":"2025-07-17T15:44:36","slug":"doctoral-consortium","status":"publish","type":"page","link":"https:\/\/aied2025.itd.cnr.it\/index.php\/program\/doctoral-consortium\/","title":{"rendered":"Doctoral Consortium"},"content":{"rendered":"\n

Doctoral Consortium \u2013 Tuesday, July 22nd<\/strong><\/h2>\n\n\n\n

The AEID\u20192025 Doctoral Consortium will take place on 22 July, in parallel with conference workshops. It will run as a full-day event.<\/p>\n\n\n\n

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  \u201ccarousel\u201d-style format.<\/p>\n\n\n\n

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.<\/p>\n\n\n\n

Schedule<\/strong><\/h2>\n\n\n\n
9:00-10:30 <\/strong><\/td>Session 1: Presentations<\/strong><\/td><\/tr>
10:30-11:00<\/td>Coffee Break 1<\/td><\/tr>
11:00-13:00<\/strong><\/td>Session 1: Posters and Discussions<\/strong><\/td><\/tr>
13:00-14:00<\/td>Lunch Break<\/td><\/tr>
14:00-15:30 <\/strong><\/td>Session 2: Presentations<\/strong><\/td><\/tr>
15:30-16:00 <\/td>Coffee Break 2<\/td><\/tr>
16:00-18:00<\/strong><\/td>Session 2: Posters and Discussions<\/strong><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n
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Detailed Program<\/strong><\/h2>\n\n\n\n

SESSION 1 (9:00-13:00)<\/strong><\/p>\n\n\n\n

<\/th>Authors<\/th>Title<\/th>Mentor<\/th><\/tr><\/thead>
1<\/td>Wen Chiang Lim and Neil Heffernan<\/td>Evaluating the Impact of LLM-Generated Assignment Report Summaries in Intelligent Tutoring Systems<\/td>Mingyu Feng<\/td><\/tr>
2<\/td>Clara Belitz<\/td>Fair for whom? Investigating school identity, algorithmic fairness, and educational technologies<\/td>Valery Psych\u00e9<\/td><\/tr>
3<\/td>Amani Alrobai and Alexandra Cristea<\/td>Personality-Aware Conversational Intelligent Tutoring System with GenAI: Studying the effect on Learners in Introductory Programming<\/td>Jionghao Lin<\/td><\/tr>
4<\/td>Betsy Araujo Grando<\/td>Perceptions of Secondary School Students Solving Math Word Problems in a Foreign Language with GenAI Support<\/td>Noboru Matsuda<\/td><\/tr>
5<\/td>Lachlan McGinness<\/td>AI Grading of Australian High School Physics Exams<\/td>Arthur Graesser<\/td><\/tr>
6<\/td>Thumesha Jayatilake<\/td>Designing An Ethical Framework for the Integration of Generative AI in Higher Education: Balancing Stake-holder Interests and Enhancing Learning Outcomes<\/td>Sergey Sosnovsky<\/td><\/tr>
7<\/td>Eamon Worden and Neil Heffernan<\/td>Few-shot is All you Need, A Framework for RAG-Based LLM Feedback<\/td>Andrew Lan<\/td><\/tr>
8<\/td>Conrad Borchers, Kenneth R. Koedinger and Vincent Aleven<\/td>Intelligent Support for Practice Goal Setting to Enhance Learning<\/td>Roger Azevedo<\/td><\/tr>
9<\/td>William Lee and Ivon Arroyo<\/td>Toward Extracting Computational Thinking Artifacts with Large Language Models: Empowering K-12 Educators<\/td>Kasia Muldner<\/td><\/tr>
10<\/td>Sonika Pal, Prajish Prasad and Sridhar Iyer<\/td>Understanding Human-GenAI Collaboration for Complex Open-ended Problem-Solving Tasks in Online Settings<\/td>Peter Brusilovsky<\/td><\/tr>
11<\/td>Aditya Rajmane, Ramkumar Rajendran and Kshitij Sharma<\/td>Identifying and Fostering Self-Regulated Learning Among Computer Programmers Using Artificial Intelligence Systems<\/td>Maria Mercedes Rodrigo<\/td><\/tr>
12<\/td>Aysu Ismayilova<\/td>Integrating Learner Models: The mAIchart Project<\/td>Nikol Rumel<\/td><\/tr>
13<\/td>Deliang Wang, Gaowei Chen and Yu Lu<\/td>Fine-tuning Large Language Models for Knowledge Tracing Harnessing Insights from Explainable AI<\/td>Neil Heffernan<\/td><\/tr>
Session 2 (14:00-18:00)<\/strong><\/strong><\/td><\/td><\/tr>
14<\/td>Duaa Baig, Diana Nurbakova, Sylvie Calabretto and Baba Mbaye<\/td>Enhancing Knowledge Tracing with Large Language Models (LLMs): A Proposal for PhD Consortium<\/td>John Stamper<\/td><\/tr>
15<\/td>Morgan Lee and Neil Heffernan<\/td>Improving Student Support Personalization with Historical Data and Theoretically Informed Feature Choice<\/td>Roger Azevedo<\/td><\/tr>
16<\/td>Mario Adkins<\/td>Assessing the Effectiveness of AI Tutoring for Tertiary Academic Probation Students: A Repeated Measures Study using ChatGPT<\/td>Rene Kizilcec<\/td><\/tr>
17<\/td>Daniel Flood, Matthew England and Beate Grawemeyer<\/td>Predicting At-Risk Programming Students in Small Imbalanced Datasets using Synthetic Data<\/td>Filippo Sciarrone<\/td><\/tr>
18<\/td>Vihanga Wijayasekara, Kyle Martin and Nirmalie Wiratunga<\/td>Towards Ordinal Few-Shot Learning for Automated Essay Grading<\/td>Gautam Biswas<\/td><\/tr>
19<\/td>Ajanie Karunanayake, Antonette Shibani and Simon Knight<\/td>Supporting Information Problem Solving in the Age of Misinformation and Generative AI: A Socio-technical Approach<\/td>Tanja K\u00e4ser<\/td><\/tr>
20<\/td>Liqun He, Manolis Mavrikis and Mutlu Cukurova<\/td>Towards Mining Effective Pedagogical Strategies from Learner\u2013LLM Educational Dialogues<\/td>Jionghao Lin<\/td><\/tr>
21<\/td>Aditi Haiman, Ivon Arroyo and Bruce McLaren<\/td>Comparing the Effectiveness of Digital Game-Based Learning and Embodied Learning<\/td>Arthur Graesser<\/td><\/tr>
22<\/td>Yuri Noviello<\/td>Designing and Evaluating AI-generated Multimodal Analogy-Based Explanations<\/td>Maria Mercedes Rodrigo<\/td><\/tr>
23<\/td>Kejia Zhang, Charaka Palansuriya and Aurora Constantin<\/td>Multimodal Story Generation Using Generative AI for Contextualised Mathematics Education<\/td>Penghe Chen<\/td><\/tr>
24<\/td>Alessio Ferrato<\/td>Large Language Models to Enhance Learning In Cultural Heritage<\/td>Olga Viberg<\/td><\/tr>
25<\/td>Chang Cai, Minyang Chow, Ruth Choe and Xiuyi Fan<\/td>AI-Powered Classification of Medical Students’ Professionalism Profiles: Early Detection and Personalised Intervention<\/td>Carla Limongelli<\/td><\/tr>
26<\/td>Ivan Chepikov and Ilia Karpov<\/td>Rewriting the Rules: LLMs vs. Traditional ML in University Admissions<\/td>Ryan Baker<\/td><\/tr>
27<\/td>Yi Shang, Jingyun Wang and Xiaofei Qi<\/td>A Learner-AI-Parent Collaboration Framework for Home Learning Environment<\/td>Bruce M. McLaren<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n
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All accepted posters must follow the guidelines below to ensure consistency and quality during the conference.<\/p>\n\n\n\n

Poster Format<\/strong><\/h4>\n\n\n\n