15 citations · 20 across the 7 of their papers we have counts for
8 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…
Quality-Conditioned Agreement in Automated Short Answer Scoring: Mid-Range Degradation and the Impact of Task-Specific Adaptation
Abigail Victoria Gurin Schleifer, Moriah Ariely, Beata Beigman Klebanov +2
Automated short answer scoring (ASAS) is shifting from discriminative, fine-tuned models to large language models (LLMs) used in few-shot settings. This paradigm leverages LLMs bro…
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…
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…
Anna Karenina Strikes Again: Pre-Trained LLM Embeddings May Favor High-Performing Learners
Abigail Gurin Schleifer, Beata Beigman Klebanov, Moriah Ariely +1
Unsupervised clustering of student responses to open-ended questions into behavioral and cognitive profiles using pre-trained LLM embeddings is an emerging technique, but little is…
What Explains Teachers' Trust of AI in Education across Six Countries?
Olga Viberg, Mutlu Cukurova, Yael Feldman-Maggor +9
With growing expectations to use AI-based educational technology (AI-EdTech) to improve students' learning outcomes and enrich teaching practice, teachers play a central role in th…
Kappa Learning: A New Method for Measuring Similarity Between Educational Items Using Performance Data
Tanya Nazaretsky, Sara Hershkovitz, Giora Alexandron
Sequencing items in adaptive learning systems typically relies on a large pool of interactive assessment items (questions) that are analyzed into a hierarchy of skills or Knowledge…