8 citations · 12 across the 11 of their papers we have counts for
11 papers
Who Decides in AI-Mediated Learning? The Agency Allocation Framework
Conrad Borchers, Olga Viberg, René F. Kizilcec
As AI-mediated learning systems increasingly shape how learners plan, make decisions, and progress through education, learner agency is becoming both more consequential and harder…
Physiological and Semantic Patterns in Medical Teams Using an Intelligent Tutoring System
Xiaoshan Huang, Conrad Borchers, Jiayi Zhang +1
Effective collaboration requires teams to manage complex cognitive and emotional states through Socially Shared Regulation of Learning (SSRL). Physiological synchrony (i.e., longit…
Understanding Teacher Revisions of Large Language Model-Generated Feedback
Conrad Borchers, Luiz Rodrigues, Newarney Torrezão da Costa +2
Large language models (LLMs) increasingly generate formative feedback for students, yet little is known about how teachers revise this feedback before it reaches learners. Teachers…
Representation Learning to Study Temporal Dynamics in Tutorial Scaffolding
Conrad Borchers, Jiayi Zhang, Ashish Gurung
Adaptive scaffolding enhances learning, yet the field lacks robust methods for measuring it within authentic tutoring dialogue. This gap has become more pressing with the rise of r…
Multimodal Analytics of Cybersecurity Crisis Preparation Exercises: What Predicts Success?
Conrad Borchers, Valdemar Švábenský, Sandesh K. Kafle +2
Instructional alignment, the match between intended cognition and enacted activity, is central to effective instruction but hard to operationalize at scale. We examine alignment in…
The Digital Divide in Generative AI: Evidence from Large Language Model Use in College Admissions Essays
Jinsook Lee, Conrad Borchers, AJ Alvero +2
Large language models (LLMs) have become popular writing tools among students and may expand access to high-quality feedback for students with less access to traditional writing su…
Large Language Models as Students Who Think Aloud: Overly Coherent, Verbose, and Confident
Conrad Borchers, Jill-Jênn Vie, Roger Azevedo
Large language models (LLMs) are increasingly embedded in AI-based tutoring systems. Can they faithfully model novice reasoning and metacognitive judgments? Existing evaluations em…
Fifteen Years of Learning Analytics Research: Topics, Trends, and Challenges
Valdemar Švábenský, Conrad Borchers, Elvin Fortuna +2
The learning analytics (LA) community has recently reached two important milestones: celebrating the 15th LAK conference and updating the 2011 definition of LA to reflect the 15 ye…
Measuring the Impact of Student Gaming Behaviors on Learner Modeling
Qinyi Liu, Lin Li, Valdemar Švábenský +2
The expansion of large-scale online education platforms has made vast amounts of student interaction data available for knowledge tracing (KT). KT models estimate students' concept…
Does the Doer Effect Exist Beyond WEIRD Populations? Toward Analytics in Radio and Phone-Based Learning
Darren Butler, Conrad Borchers, Michael W. Asher +7
The Doer Effect states that completing more active learning activities, like practice questions, is more strongly related to positive learning outcomes than passive learning activi…
Evaluating the Impact of Data Augmentation on Predictive Model Performance
Valdemar Švábenský, Conrad Borchers, Elizabeth B. Cloude +1
In supervised machine learning (SML) research, large training datasets are essential for valid results. However, obtaining primary data in learning analytics (LA) is challenging. D…