8 citations · 13 across the 6 of their papers we have counts for
7 papers
Seeing the Big Picture: Evaluating Multimodal LLMs' Ability to Interpret and Grade Handwritten Student Work
Owen Henkel, Bill Roberts, Doug Jaffe +1
Recent advances in multimodal large language models (MLLMs) raise the question of their potential for grading, analyzing, and offering feedback on handwritten student classwork. Th…
Learning to Love Edge Cases in Formative Math Assessment: Using the AMMORE Dataset and Chain-of-Thought Prompting to Improve Grading Accuracy
Owen Henkel, Hannah Horne-Robinson, Maria Dyshel +3
This paper introduces AMMORE, a new dataset of 53,000 math open-response question-answer pairs from Rori, a learning platform used by students in several African countries and cond…
Can Large Language Models Make the Grade? An Empirical Study Evaluating LLMs Ability to Mark Short Answer Questions in K-12 Education
Owen Henkel, Adam Boxer, Libby Hills +1
This paper presents reports on a series of experiments with a novel dataset evaluating how well Large Language Models (LLMs) can mark (i.e. grade) open text responses to short answ…
Effective and Scalable Math Support: Evidence on the Impact of an AI- Tutor on Math Achievement in Ghana
Owen Henkel, Hannah Horne-Robinson, Nessie Kozhakhmetova +1
This study evaluates the impact of Rori, an AI powered conversational math tutor accessible via WhatsApp, on the math performance of approximately 1,000 students in grades 3-9 acro…
Using State-of-the-Art Speech Models to Evaluate Oral Reading Fluency in Ghana
Owen Henkel, Hannah Horne-Robinson, Libby Hills +2
This paper reports on a set of three recent experiments utilizing large-scale speech models to evaluate the oral reading fluency (ORF) of students in Ghana. While ORF is a well-est…
Can LLMs Grade Short-Answer Reading Comprehension Questions : An Empirical Study with a Novel Dataset
Owen Henkel, Libby Hills, Bill Roberts +1
Open-ended questions, which require students to produce multi-word, nontrivial responses, are a popular tool for formative assessment as they provide more specific insights into wh…
Leveraging Human Feedback to Scale Educational Datasets: Combining Crowdworkers and Comparative Judgement
Owen Henkel, Libby Hills
Machine Learning models have many potentially beneficial applications in education settings, but a key barrier to their development is securing enough data to train these models. L…