40 citations · 59 across the 10 of their papers we have counts for
12 papers
HealthCAT: An Interpretable Encoder-only Transformer Framework for Health Indicator Prediction and Temporal Interpretation of Wearable Sensor Data
Xiaotong Yu, Joshua Y. Kim, HaeJin Lee +1
Wearable sensors continuously capture fine-grained multivariate time-series data, providing opportunities to model behavioural patterns associated with health outcomes. However, ex…
AI Expert Twin: Capturing Expert Cognition for Human-Centred, Practice-Based Learning
Annie Yuan, Xiaohua Chen, Kalina Yacef +1
Tacit knowledge embedded in expert practice remains difficult to capture, formalise, and scale. While AI-driven educational systems have advanced personalisation, learner modelling…
An empirical user-study of text-based nonverbal annotation systems for human-human conversations
Joshua Y. Kim, Kalina Yacef
the substantial increase in the number of online human-human conversations and the usefulness of multimodal transcripts, there is a rising need for automated multimodal transcripti…
Transfer Learning in Conversational Analysis through Reusing Preprocessing Data as Supervisors
Joshua Yee Kim, Tongliang Liu, Kalina Yacef
Conversational analysis systems are trained using noisy human labels and often require heavy preprocessing during multi-modal feature extraction. Using noisy labels in single-task…
ast2vec: Utilizing Recursive Neural Encodings of Python Programs
Benjamin Paaßen, Jessica McBroom, Bryn Jeffries +2
Educational datamining involves the application of datamining techniques to student activity. However, in the context of computer programming, many datamining techniques can not be…
MONAH: Multi-Modal Narratives for Humans to analyze conversations
Joshua Y. Kim, Greyson Y. Kim, Chunfeng Liu +3
In conversational analyses, humans manually weave multimodal information into the transcripts, which is significantly time-consuming. We introduce a system that automatically expan…
Recursive Tree Grammar Autoencoders
Benjamin Paassen, Irena Koprinska, Kalina Yacef
Machine learning on trees has been mostly focused on trees as input to algorithms. Much less research has investigated trees as output, which has many applications, such as molecul…
DETECT: A Hierarchical Clustering Algorithm for Behavioural Trends in Temporal Educational Data
Jessica McBroom, Kalina Yacef, Irena Koprinska
Techniques for clustering student behaviour offer many opportunities to improve educational outcomes by providing insight into student learning. However, one important aspect of st…
Tree Echo State Autoencoders with Grammars
Benjamin Paassen, Irena Koprinska, Kalina Yacef
Tree data occurs in many forms, such as computer programs, chemical molecules, or natural language. Unfortunately, the non-vectorial and discrete nature of trees makes it challengi…
Detecting depression in dyadic conversations with multimodal narratives and visualizations
Joshua Y. Kim, Greyson Y. Kim, Kalina Yacef
Conversations contain a wide spectrum of multimodal information that gives us hints about the emotions and moods of the speaker. In this paper, we developed a system that supports…
A Survey of Automated Programming Hint Generation -- The HINTS Framework
Jessica McBroom, Irena Koprinska, Kalina Yacef
Automated tutoring systems offer the flexibility and scalability necessary to facilitate the provision of high quality and universally accessible programming education. In order to…
A Review on Dyadic Conversation Visualizations - Purposes, Data, Lens of Analysis
Joshua Y. Kim, Rafael A. Calvo, Kalina Yacef +1
Many professional services are provided through text and voice systems, from voice calls over the internet to messaging and emails. There is a growing need for both individuals and…