R&D Hub

EdSurvey 4.0.7 was recently released and is now available on CRAN-R. This update enables EdSurvey to support the analysis of main NAEP data up to 2022, NAEP long-term trend data up to 2023, the 2022 Monthly School Survey (MSS) Linking Study, and the 2021 School and Teacher Questionnaire Special Study. In addition, the package now supports two international large-scale assessments: PISA 2022 and ICILS 2023. A new rounding feature has also been introduced to facilitate rounding results according to NCES statistical standards or user-defined criteria. For details, users can refer to “?es_round” within package 4.0.7. For more information on minor changes and bug fixes in this update, visit the EdSurvey news page on CRAN-R.  

The 2024 NAEP Doctoral Student Internship Program is now in its final weeks, so interns are hard at work applying all the technical skills and knowledge they’ve gained since the beginning of June to their collaborative projects. Get some insight on the program before it ends by checking out our interview with the remaining three 2024 cohort interns: Adalin Ni, Maggie Perkoff, and Winnie Wilberforce.

With the 2024 NAEP Doctoral Student Internship Program well underway, our interns are now developing their technical skills and knowledge in the field of large-scale assessment by working collaboratively with NAEP experts on client-based projects. Recently, two more interns, Paulina Grekov and Dekyi Suolang, participated in our ongoing interviews to introduce the newest cohort to the NAEP R&D community.

Summer is in full swing, and so is the 2024 NAEP Doctoral Student Internship! Our new interns are busy analyzing NAEP data alongside researchers from the National Center for Education Statistics and the American Institutes for Research. Naomi Duran and Saugat Pandey, two members of this newest intern cohort, have taken the time to answer a few questions and introduce themselves to the NAEP R&D community.

This month, we are excited to share the latest research from the NAEP R&D community, focusing on the evaluation of large language models (LLMs). “The Challenges of Evaluating LLM Applications: An Analysis of Automated, Human, and LLM-Based Approaches” will be presented at the LLM4Eval workshop at the 2024 Association for Computer Machinery Special Interest Group on Information Retrieval (ACM SIGIR) conference on July 18, 2024. This paper from AIR researchers Bhashithe Abeysinghe and Ruhan Circi explores innovative approaches to evaluating custom AI applications, addressing a crucial barrier to faster progress in generative AI.