Interested in exploring the impact of AI in Education? Join us at AAAI-24 for a 2-day workshop: AI for Education - Bridging Innovation and Responsibility. The workshop will examine the transformative potential of Generative AI and Responsible AI on education, exploring new research opportunities, technological advances, and the crucial ethical implications for equity in education.
For the full Call for Papers and workshop details, please see: https://ai4ed.cc/workshops/aaai2024.
]]>We would like to share a job advertisement: Tenure-Stream Assistant Professor of Artificial Intelligence and Learning Science at University of Pittsburgh, Pittsburgh, PA USA.
The School of Computing and Information (SCI) and Learning Research and Development Center (LRDC) at University of Pittsburgh seek to hire a faculty member at the rank of Assistant Professor (SCI) and Research Scientist (LRDC) at the confluence of Artificial Intelligence and Learning Science. The position builds on SCI’s ongoing initiative and faculty hiring that prioritizes scholarship on the use of learning technology to further social justice outcomes. This role requires experience in advancing technology-oriented educational approaches and outcomes through the development and application of AI methods including large language models, generative AI, and other foundational AI approaches. The ideal candidate will also have an interest in learning sciences, including but not limited to the study of student and teacher learning, broadly construed, and in scholarship on social justice, including but not limited to learning processes, practices, and outcomes for minoritized populations, principles for responsible and equitable AI in education, and community-engaged scholarship. In sum, the individual filling this position is expected to engage in research that considers, improves, or creates state-of-the-art AI-centric learning science to address societal problems, including supporting learning for all, deepening social impact, and improving lives.
We seek candidates who are interested in exploring how AI and learning science can analyze and affect mechanisms within the social structure, such as cultural symbols, rules of behavior, social organizations, or value systems that influence learning. We seek transdisciplinary researchers who have a strong interest in working across other areas such as Africana Studies, Natural and Physical Sciences, Communications, Education, Psychology, Health Sciences, Gender Studies, Law, Medicine, Social Science, or Social Work. Additionally, we seek researchers with a strong background in engaging historically excluded communities in the development, application, and evaluation of AI technologies in learning spaces.
SCI and LRDC strongly encourage applications from women, underrepresented, and minoritized candidates. We are especially interested in candidates with a demonstrated commitment to working with students from diverse backgrounds, as well as those whose research, teaching, and service align with our diversity values and aim to address societal issues.
Candidates must have earned a Ph.D. or equivalent degree (e.g., Doctor of Law) prior to the appointment, in an area relevant to Artificial Intelligence and Learning Science
Candidates must possess at least three years of relevant experience in research, teaching, community work, technology innovation, or equivalent areas
Candidates must have a commitment to advancing diversity, equity, and inclusion
Interest in interdisciplinary, impactful work, and collaboration in AI and learning science
A relevant scholarly record including but not limited to publication quality, teaching portfolio, technology products, and/or history of community advocacy
Interest in supporting a learning and social change agenda
More information can be found on Careers at Pitt.
Sincerely,
SIGEDU Member
]]>We would like to share with you an update on the shared task that was held at the BEA workshop this year.
The BEA 2023 Shared Task on Generating AI Teacher Responses in Educational Dialogues ran from March 24 to May 6. The goal of the task was to benchmark the ability of generative language models to act as AI teachers, replying to a student in a teacher-student dialogue. Eight teams participated in the competition hosted on CodaLab. They experimented with a wide variety of state-of-the-art models, including Alpaca, Bloom, DialoGPT, DistilGPT-2, Flan-T5, GPT-2, GPT-3, GPT-4, LLaMA, OPT-2.7B, and T5-base. Their submissions were automatically scored using BERTScore and DialogRPT metrics, and the top three among them were further manually evaluated in terms of pedagogical ability. The NAISTeacher system, which ranked first in both automated and human evaluation, generated responses with GPT-3.5 Turbo using an ensemble of prompts and DialogRPT-based ranking of responses for given dialogue contexts. These results were presented at the 18th edition of the BEA workshop in Toronto on July 13, 2023. More information can be found on the shared task website, in the shared task overview paper, and in the corresponding system papers that can be found in the workshop proceedings on ACL Anthology.
If you are interested in following up on this task: because the CodaLab competition is no longer open to submissions, the shared task data can no longer be downloaded from the platform and the scoring program can no longer be used to run the evaluation metrics. To obtain the shared task data, you must now register for the shared task via this Google Form. In this form, you must sign and comply with the terms and conditions of the task and the TSCC data. After a successful registration, you will receive a confirmation email with the data. To run the shared task metrics, you should now download the anaistack/bea-2023-shared-task-metrics Docker image that is available on Docker Hub and run it locally on your computer. See https://github.com/anaistack/bea-2023-shared-task for more information.
If you encounter any problems, do not hesitate to submit an issue on the GitHub repository.
We hope the shared task will be of interest to you.
Sincerely,
The BEA 2023 Shared Task Organizers
]]>This is the final call for papers for the 2023 AIED Workshop on Intelligent Textbooks (Notice: the deadlines have been extended)
Fifth Workshop on Intelligent Textbooks @ The 24th International Conference on Artificial Intelligence in Education (AIED’2023)
We are happy to announce that we will be organizing a full-day workshop at AIED 2023. The date of the workshop is July 3, 2023. AIED 2023 will be held in Tokio, Japan during July 3-7, 2023. See here: https://www.aied2023.org/
Textbooks have evolved over the last several decades in many aspects. Most textbooks can be accessed online, many of them freely. They often come with libraries of supplementary educational resources or online educational services built on top of them. As a result of these enrichments, new research challenges and opportunities emerge that call for the application of AIED methods to enhance digital textbooks and learners’ interaction with them. Therefore, we ask: How to facilitate access to textbooks and improve the reading process? What can be extracted from textbook content and data-mined from the logs of students interacting with it? How can we use large language models to support the development and usage of textbooks? This workshop seeks research contributions addressing these and other research questions related to the idea of intelligent textbooks. It aims at bringing together researchers working on different aspects of learning technologies to establish intelligent textbooks as a new, interdisciplinary research field. More information is available on the workshop website: https://intextbooks.science.uu.nl/workshop2023/
This workshop builds on the success of the four previous events:
The workshop themes include but are not limited to:
Paper submission: May 19, 2023 Notification of acceptance: June 09, 2023 Final version of accepted papers: June 23, 2023
Accepted papers will be presented orally and included in the workshop proceedings. At this point, we invite full (up to 12 pages) and short (up to 6 pages) paper submissions. Submissions should follow the 1-column CEUR-ART style. The docx template can be downloaded from: https://ceur-ws.org/Vol-XXX/CEUR-Template-1col.docx The general Overleaf page for LaTeX users is available at: https://www.overleaf.com/read/gwhxnqcghhdt Submission should be made in pdf format through the EasyChair system (https://easychair.org/my/conference?conf=itextbooks2023). Submissions will be reviewed by members of the workshop program committee.
Isaac Alpizar Chacon (Utrecht University & Instituto Tecnológico de Costa Rica) Debshila Basu Mallick (OpenStax, Rice University) Peter Brusilovsky (University of Pittsburgh) Paulo Carvalho (Carnegie Mellon University) Vinay Chaudhri Brendan Flanagan (Kyoto University) Reva Freedman (Northern Illinois University) Benny Johnson (VitalSource Technologies) Andrew Lan (University of Massachusetts Amherst) Noboru Matsuda (North Carolina State University) Roger Nkambou (Université du Québec à Montréal) Andrew Olney (University of Memphis) Philip Pavlik (University of Memphis) Cliff Shaffer (Virginia Tech) Sergey Sosnovsky (Utrecht University) Khushboo Thaker (University of Pittsburgh) Ilaria Torre (University of Genoa)