Co-Chair: Chris Ormerod
Co-chair: John Whitmer
Secretary: Maggie Beiting-Parrish
Andrew Lan, Assistant Professor at The University of Massachusetts Amherst
Exploring Automated Distractor and Feedback Generation for Math Multiple-choice Questions via In-context Learning
We have been approved by the NCME board. Two more immediate concerns are:
Meet with NCME board Liasons.
NCME Proposal.
Generative AI has exploded upon our culture and is having widespread impacts in many industries. In this presentation, members of the NCME Generative AI SIGIME will discuss examples of prototyping, piloting, and/or deploying education solutions using these new technologies. While this specific technology is new, measurement experts have significant experience applying innovative technologies in our work and many of our conventional measures of efficacy - namely validity, reliability, and fairness - are more relevant than ever in determining whether these innovations are ready for widescale use.
Paragraph-length abstract describing your application, which includes:
Specific problem/use case seeking to address
Technology / algorithmic approaches used (high level summary)
Any custom datasets used to tune/train/refine the approach
Evidence of impact
Advertising GAIME on NCME
Suggestions for future speakers
Links with AI companies (Future speakers)
Advancement of Fair, Accountable, Transparent, and Ethical use of AI
Zoom account (webinar?)
Github Organization
Zotero w/shared space
Paid website domain name
Datasets for fine-tuning
Other Suggestions? What are we missing?
Note: Use of funds requires some board approval.
Journal: Harvard Data Science Review
Published: 11 Jul 2023
Deadline: 25 August 2023
URL: Call for papers
Articles clarifying the nature and limitations of foundation models, large language models (LLMs), and generative AI applications. Articles exploring the wider societal risks and impacts of foundation models, LLMs, and generative AI applications.
Journal: Computers and Education: Artificial Intelligence (Open Access)
Published: 28 June 2023
Deadline: 30 October 2023
Contact: Prof. Rafael Ferreira Mello at rflm@cesar.org.br
URL: Call for Papers
This special issue focuses on exploring the implications of utilizing large language models (LLMs) for educational assessment, with particular emphasis on leveraging LLMs for formative feedback provision and mitigating challenges related to academic integrity. To this end, we invite researchers from diverse fields to submit papers investigating the use of LLMs to support the assessment process.