2 citations · 2 across the 4 of their papers we have counts for
7 papers
Interpretable Humans, Alien LLMs: Expert Analysis of Latent Structures in Assessment Responses
Alona Strugatski, Licol Zeinfeld, Jason Cooper +3
The evaluation of large language models (LLMs) relies heavily on human-designed assessments, implicitly assuming that AI and humans employ similar underlying cognitive constructs.…
Do Assessment Instruments Measure the Same Thing for Humans and LLMs? A Latent Structure Analysis
Alona Strugatski, Licol Zeinfeld, Giora Alexandron
The rapid development and growing deployment of large language models (LLMs) have made it increasingly important to understand their capabilities. A common approach is to evaluate…
Assessment Design in the AI Era: A Method for Identifying Items Functioning Differentially for Humans and Chatbots
Licol Zeinfeld, Alona Strugatski, Ziva Bar-Dov +3
The rapid adoption of large language models (LLMs) in education raises profound challenges for assessment design. To adapt assessments to the presence of LLM-based tools, it is cru…
SciTextures: Collecting and Connecting Visual Patterns, Models, and Code Across Science and Art
Sagi Eppel, Alona Strugatski
The ability to connect visual patterns with the processes that form them represents one of the deepest forms of visual understanding. Textures of clouds and waves, the growth of ci…
Applying IRT to Distinguish Between Human and Generative AI Responses to Multiple-Choice Assessments
Alona Strugatski, Giora Alexandron
Generative AI is transforming the educational landscape, raising significant concerns about cheating. Despite the widespread use of multiple-choice questions in assessments, the de…
Image interpretation by iterative bottom-up top-down processing
Shimon Ullman, Liav Assif, Alona Strugatski +4
Scene understanding requires the extraction and representation of scene components together with their properties and inter-relations. We describe a model in which meaningful scene…