Search Results for author: Zachary A. Pardos

Found 10 papers, 4 papers with code

Survey of Computerized Adaptive Testing: A Machine Learning Perspective

1 code implementation31 Mar 2024 Qi Liu, Yan Zhuang, Haoyang Bi, Zhenya Huang, Weizhe Huang, Jiatong Li, Junhao Yu, Zirui Liu, Zirui Hu, Yuting Hong, Zachary A. Pardos, Haiping Ma, Mengxiao Zhu, Shijin Wang, Enhong Chen

Computerized Adaptive Testing (CAT) provides an efficient and tailored method for assessing the proficiency of examinees, by dynamically adjusting test questions based on their performance.

cognitive diagnosis Question Selection +1

Learning gain differences between ChatGPT and human tutor generated algebra hints

no code implementations14 Feb 2023 Zachary A. Pardos, Shreya Bhandari

Learning gains from human-created hints were substantially and statistically significantly higher than ChatGPT hints in both topic areas, though ChatGPT participants in the Intermediate Algebra experiment were near ceiling and not even with the control at pre-test.

Insights into undergraduate pathways using course load analytics

1 code implementation20 Dec 2022 Conrad Borchers, Zachary A. Pardos

Course load analytics (CLA) inferred from LMS and enrollment features can offer a more accurate representation of course workload to students than credit hours and potentially aid in their course selection decisions.

Towards Equity and Algorithmic Fairness in Student Grade Prediction

no code implementations14 May 2021 Weijie Jiang, Zachary A. Pardos

With equity of educational outcome as the aim, we trial strategies for boosting predictive performance on historically underserved groups and find success in sampling those groups in inverse proportion to their historic outcomes.


Learning Skill Equivalencies Across Platform Taxonomies

1 code implementation10 Feb 2021 Zhi Li, Cheng Ren, Xianyou Li, Zachary A. Pardos

Assessment and reporting of skills is a central feature of many digital learning platforms.

Machine Translation Translation

Combating the Filter Bubble: Designing for Serendipity in a University Course Recommendation System

no code implementations2 Jul 2019 Zachary A. Pardos, Weijie Jiang

Collaborative filtering based algorithms, including Recurrent Neural Networks (RNN), tend towards predicting a perpetuation of past observed behavior.

Collaborative Filtering

Goal-based Course Recommendation

1 code implementation25 Dec 2018 Weijie Jiang, Zachary A. Pardos, Qiang Wei

With cross-disciplinary academic interests increasing and academic advising resources over capacity, the importance of exploring data-assisted methods to support student decision making has never been higher.

Decision Making

Connectionist Recommendation in the Wild: On the utility and scrutability of neural networks for personalized course guidance

no code implementations26 Mar 2018 Zachary A. Pardos, Zihao Fan, Weijie Jiang

The aggregate behaviors of users can collectively encode deep semantic information about the objects with which they interact.

Decision Making

Modelling Student Behavior using Granular Large Scale Action Data from a MOOC

no code implementations16 Aug 2016 Steven Tang, Joshua C. Peterson, Zachary A. Pardos

This research lays the ground work for recommendation in a MOOC and other digital learning environments where high volumes of sequential data exist.

Language Modelling Sentence +1

The Utility of Clustering in Prediction Tasks

no code implementations21 Sep 2015 Shubhendu Trivedi, Zachary A. Pardos, Neil T. Heffernan

Previous work has hinted at the improvement in prediction accuracy attributed to clustering algorithms if used to pre-process the data.

Clustering Data Compression

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