2 citations · 3 across the 8 of their papers we have counts for
8 papers
A Case Study Reexamining the Cold-Start Problem in Knowledge Tracing Models and Implications for SafeInsights, an Education Research Infrastructure
Jiayi Zhang, Ryan S. Baker, Debshila Basu Mallick +2
Knowledge tracing (KT) models are widely used to predict students' evolving knowledge states from their learning history. However, many KT models are evaluated using specific datas…
Stable and Privacy-Preserving Synthetic Educational Data with Empirical Marginals: A Copula-Based Approach
Gabriel Diaz Ramos, Lorenzo Luzi, Debshila Basu Mallick +1
To advance Educational Data Mining (EDM) within strict privacy-protecting regulatory frameworks, researchers must develop methods that enable data-driven analysis while protecting…
Learning Context Matters: Measuring and Diagnosing Personalization Gaps in LLM-Based Instructional Design
Johaun Hatchett, Debshila Basu Mallick, Brittany C. Bradford +1
The adoption of generative AI in education has accelerated dramatically in recent years, with Large Language Models (LLMs) increasingly integrated into learning environments in the…
Learning Context: A Unified Framework and Roadmap for Context-Aware AI in Education
Naiming Liu, Brittany Bradford, Johaun Hatchett +5
We introduce a unified Learning Context (LC) framework designed to transition AI-based education from context-blind mimicry to a principled, holistic understanding of the learner.…
Atomic Learning Objectives Labeling: A High-Resolution Approach for Physics Education
Naiming Liu, Shashank Sonkar, Debshila Basu Mallick +2
This paper introduces a novel approach to create a high-resolution "map" for physics learning: an "atomic" learning objectives (LOs) system designed to capture detailed cognitive p…
Marking: Visual Grading with Highlighting Errors and Annotating Missing Bits
Shashank Sonkar, Naiming Liu, Debshila B. Mallick +1
In this paper, we introduce "Marking", a novel grading task that enhances automated grading systems by performing an in-depth analysis of student responses and providing students w…
Code Soliloquies for Accurate Calculations in Large Language Models
Shashank Sonkar, MyCo Le, Xinghe Chen +3
High-quality conversational datasets are crucial for the successful development of Intelligent Tutoring Systems (ITS) that utilize a Large Language Model (LLM) backend. Synthetic s…
CLASS: A Design Framework for building Intelligent Tutoring Systems based on Learning Science principles
Shashank Sonkar, Naiming Liu, Debshila Basu Mallick +1
We present a design framework called Conversational Learning with Analytical Step-by-Step Strategies (CLASS) for building advanced Intelligent Tutoring Systems (ITS) powered by hig…