Artificial Intelligence in Measurement and Education

Introductions

Executive Board

  • Co-Chair: Chris Ormerod

  • Co-chair: John Whitmer

  • Secretary: Maggie Beiting-Parrish

Outline

  • Overview & Updates
  • Today’s Speaker: Rene Kizilcec, Cornell University’s Future of Learning Lab
  • Additional SIG Updates & Calls for Participation

Quick Updates

The website is up and running

www.ncme-aime.org

Contains

  • Past events with recordings

  • Calls for Participation

  • Datasets and literature

Today’s Research Presentation

Speaker: Rene Kizilcec, Cornell University’s Future of Learning Lab

Title: Bias in Large Language Models in Education: Sources, Measures, and Mitigation Strategies

Additional SIG Updates & Calls for Participation

The ethical use of AI in educational measurement

We are looking for researchers to contribute to a white paper on the Ethical use of AI in educational measurement. Examples of topics include the following:

  • Accountability when AI is used for measurement

  • Detection and mitigation of algorithmic bias when using AI for measurement

  • Transparency in the use of AI for measurement

  • Toxicity in Generative AI

  • Regulations on the ethical use of AI for measurement

If you are interested, please email Okan Bulut at bulut@ualberta.ca.

Collaboration with SALAL

The State & Local Assessment Leaders SIGIMIE. Talk series on

How can AI benefit State & Local Assessment Leaders:

  • Improved Scoring, Accommodations, Lessons, and Results.

  • Customized translation, reporting, lesson plans.

  • Time, cost, and effort efficiencies.

Addressing the concerns of State & Local Assessment Leaders:

  • Cost, comprimised learning, decrease human interactions

  • Threat to Jobs, security, PII concerns, Bias.

If you are interested in working with SALAL towards a series that promotes the widespread adoption of AI in Education, contact christopher.ormerod@cambiumassessment.com.

Assistant Professor of Artificial Intelligence in Learning and Education @ Harvard University

The Harvard Graduate School of Education (HGSE) invites applications for a full-time, tenure track faculty position at the rank of Assistant Professor focused on artificial intelligence (AI) in learning and education.

We seek scholars whose research, teaching, and impact in the field will advance one or more dimensions of AI in learning and education, including but not limited to:

  • Theoretical and Empirical Foundations: Investigating the foundational theoretical principles of various learning processes in relation to AI, and/or examining these through empirical studies to understand their impact on learning and cognition.

  • Design: Conceptualizing, creating, and evaluating AI-based designs, such as tools or curricula used in classrooms, online platforms, and out-of-school-time settings.

  • Practice: Analyzing the pedagogical potentials and complexities of AI, attending to learners’ present needs and preparation for future needs in life and work.

  • Ethical and Societal Implications: Interrogating the ethical, historical, and cultural impacts of AI in learning and education, such as privacy and bias.

Strong applicants will be distinguished by the quality of their research, their use of rigorous methods, and the significance of their work for policy and practice.

Postdoc Research Association - AI Learning Technologies @ USC

The Learning Sciences group would like to share a position opening for a postdoctoral researcher. If you have any questions, please contact Dr. Ben Nye (nye@ict.usc.edu).

Additional details are below.

Postdoctoral Research Associate - AI Learning Technologies University of Southern California, Institute for Creative Technologies

Apply at: https://usccareers.usc.edu/job/los-angeles/postdoctoral-research-associate-ai-learning-technologies/1209/53758066992