no code implementations • NAACL 2022 • Zijie Zeng, Xinyu Li, Dragan Gasevic, Guanliang Chen
Deep Learning (DL) techniques have been increasingly adopted for Automatic Text Scoring in education.
1 code implementation • COLING 2022 • Lele Sha, Yuheng Li, Dragan Gasevic, Guanliang Chen
Pretrained Language Models (PLMs), though popular, have been diagnosed to encode bias against protected groups in the representations they learn, which may harm the prediction fairness of downstream models.
1 code implementation • 6 Mar 2024 • Zijie Zeng, Shiqi Liu, Lele Sha, Zhuang Li, Kaixun Yang, Sannyuya Liu, Dragan Gašević, Guanliang Chen
Our empirical findings highlight (1) detecting AI-generated sentences in hybrid texts is overall a challenging task because (1. 1) human writers' selecting and even editing AI-generated sentences based on personal preferences adds difficulty in identifying the authorship of segments; (1. 2) the frequent change of authorship between neighboring sentences within the hybrid text creates difficulties for segment detectors in identifying authorship-consistent segments; (1. 3) the short length of text segments within hybrid texts provides limited stylistic cues for reliable authorship determination; (2) before embarking on the detection process, it is beneficial to assess the average length of segments within the hybrid text.
1 code implementation • 11 Jan 2024 • Kaixun Yang, Mladen Raković, Yuyang Li, Quanlong Guan, Dragan Gašević, Guanliang Chen
Automatic Essay Scoring (AES) is a well-established educational pursuit that employs machine learning to evaluate student-authored essays.
2 code implementations • 23 Jul 2023 • Zijie Zeng, Lele Sha, Yuheng Li, Kaixun Yang, Dragan Gašević, Guanliang Chen
Then we proposed a two-step approach where we (1) separated AI-generated content from human-written content during the encoder training process; and (2) calculated the distances between every two adjacent prototypes and assumed that the boundaries exist between the two adjacent prototypes that have the furthest distance from each other.
no code implementations • 15 Apr 2023 • Jionghao Lin, Wei Tan, Ngoc Dang Nguyen, David Lang, Lan Du, Wray Buntine, Richard Beare, Guanliang Chen, Dragan Gasevic
We note that many prior studies on classifying educational DAs employ cross entropy (CE) loss to optimize DA classifiers on low-resource data with imbalanced DA distribution.
no code implementations • 12 Apr 2023 • Wei Tan, Jionghao Lin, David Lang, Guanliang Chen, Dragan Gasevic, Lan Du, Wray Buntine
Then, the study investigates how the AL methods can select informative samples to support DA classifiers in the AL sampling process.
no code implementations • 17 Mar 2023 • Lixiang Yan, Lele Sha, Linxuan Zhao, Yuheng Li, Roberto Martinez-Maldonado, Guanliang Chen, Xinyu Li, Yueqiao Jin, Dragan Gašević
Educational technology innovations leveraging large language models (LLMs) have shown the potential to automate the laborious process of generating and analysing textual content.
no code implementations • WS 2018 • Guanliang Chen, Claudia Hauff, Geert-Jan Houben
Knowledge tracing serves as a keystone in delivering personalized education.