Saved in:
| Main Authors: | Zhao, Yan, Otteson, Amy |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2408.02598 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
A Practice in Enrollment Prediction with Markov Chain Models
by: Zhao, Yan, et al.
Published: (2024)
by: Zhao, Yan, et al.
Published: (2024)
Machine Learning-Driven Student Performance Prediction for Enhancing Tiered Instruction
by: Chen, Yawen, et al.
Published: (2025)
by: Chen, Yawen, et al.
Published: (2025)
Improvement of Applicability in Student Performance Prediction Based on Transfer Learning
by: Zhao, Yan
Published: (2024)
by: Zhao, Yan
Published: (2024)
Student Answer Forecasting: Transformer-Driven Answer Choice Prediction for Language Learning
by: Gado, Elena Grazia, et al.
Published: (2024)
by: Gado, Elena Grazia, et al.
Published: (2024)
Predicting and Understanding College Student Mental Health with Interpretable Machine Learning
by: Chowdhury, Meghna Roy, et al.
Published: (2025)
by: Chowdhury, Meghna Roy, et al.
Published: (2025)
A Frugal Model for Accurate Early Student Failure Prediction
by: Gagaoua, Ikram, et al.
Published: (2025)
by: Gagaoua, Ikram, et al.
Published: (2025)
Centralized vs. Federated Learning for Educational Data Mining: A Comparative Study on Student Performance Prediction with SAEB Microdata
by: Tertulino, Rodrigo
Published: (2025)
by: Tertulino, Rodrigo
Published: (2025)
Towards An Online Incremental Approach to Predict Students Performance
by: Labba, Chahrazed, et al.
Published: (2024)
by: Labba, Chahrazed, et al.
Published: (2024)
Detecting Struggling Student Programmers using Proficiency Taxonomies
by: Schwartz, Noga, et al.
Published: (2025)
by: Schwartz, Noga, et al.
Published: (2025)
Machine Learning Algorithms for Detecting Mental Stress in College Students
by: Singh, Ashutosh, et al.
Published: (2024)
by: Singh, Ashutosh, et al.
Published: (2024)
Feature Engineering on LMS Data to Optimize Student Performance Prediction
by: Hubbard, Keith, et al.
Published: (2025)
by: Hubbard, Keith, et al.
Published: (2025)
Interpreting Latent Student Knowledge Representations in Programming Assignments
by: Fernandez, Nigel, et al.
Published: (2024)
by: Fernandez, Nigel, et al.
Published: (2024)
Substance Beats Style: Why Beginning Students Fail to Code with LLMs
by: Lucchetti, Francesca, et al.
Published: (2024)
by: Lucchetti, Francesca, et al.
Published: (2024)
Differentiating Student Feedbacks for Knowledge Tracing
by: Cui, Jiajun, et al.
Published: (2022)
by: Cui, Jiajun, et al.
Published: (2022)
Exploring Student Expectations and Confidence in Learning Analytics
by: Asatryan, Hayk, et al.
Published: (2026)
by: Asatryan, Hayk, et al.
Published: (2026)
Exploring Knowledge Tracing in Tutor-Student Dialogues using LLMs
by: Scarlatos, Alexander, et al.
Published: (2024)
by: Scarlatos, Alexander, et al.
Published: (2024)
Research on Education Big Data for Students Academic Performance Analysis based on Machine Learning
by: Wang, Chun, et al.
Published: (2024)
by: Wang, Chun, et al.
Published: (2024)
Ordinal Behavior Classification of Student Online Course Interactions
by: Trask, Thomas
Published: (2024)
by: Trask, Thomas
Published: (2024)
Ontology-driven Reinforcement Learning for Personalized Student Support
by: Hare, Ryan, et al.
Published: (2024)
by: Hare, Ryan, et al.
Published: (2024)
SMART: Simulated Students Aligned with Item Response Theory for Question Difficulty Prediction
by: Scarlatos, Alexander, et al.
Published: (2025)
by: Scarlatos, Alexander, et al.
Published: (2025)
Revolutionising Distance Learning: A Comparative Study of Learning Progress with AI-Driven Tutoring
by: Möller, Moritz, et al.
Published: (2024)
by: Möller, Moritz, et al.
Published: (2024)
Australian Bushfire Intelligence with AI-Driven Environmental Analytics
by: Jois, Tanvi, et al.
Published: (2026)
by: Jois, Tanvi, et al.
Published: (2026)
Accurate Multi-Category Student Performance Forecasting at Early Stages of Online Education Using Neural Networks
by: Junejo, Naveed Ur Rehman, et al.
Published: (2024)
by: Junejo, Naveed Ur Rehman, et al.
Published: (2024)
LLM-based Cognitive Models of Students with Misconceptions
by: Sonkar, Shashank, et al.
Published: (2024)
by: Sonkar, Shashank, et al.
Published: (2024)
Embracing Imperfection: Simulating Students with Diverse Cognitive Levels Using LLM-based Agents
by: Wu, Tao, et al.
Published: (2025)
by: Wu, Tao, et al.
Published: (2025)
Evaluation of Machine Learning Models in Student Academic Performance Prediction
by: Sandeepa, A. G. R., et al.
Published: (2025)
by: Sandeepa, A. G. R., et al.
Published: (2025)
Unlocking Mental Health: Exploring College Students' Well-being through Smartphone Behaviors
by: Xuan, Wei, et al.
Published: (2025)
by: Xuan, Wei, et al.
Published: (2025)
Predicting Student Dropout Risk With A Dual-Modal Abrupt Behavioral Changes Approach
by: Cheng, Jiabei, et al.
Published: (2025)
by: Cheng, Jiabei, et al.
Published: (2025)
Cluster Model for parsimonious selection of variables and enhancing Students Employability Prediction
by: Thakar, Pooja, et al.
Published: (2024)
by: Thakar, Pooja, et al.
Published: (2024)
Evaluating Algorithmic Bias in Models for Predicting Academic Performance of Filipino Students
by: Švábenský, Valdemar, et al.
Published: (2024)
by: Švábenský, Valdemar, et al.
Published: (2024)
End-to-end Graph Learning Approach for Cognitive Diagnosis of Student Tutorial
by: Yang, Fulai, et al.
Published: (2024)
by: Yang, Fulai, et al.
Published: (2024)
Single-Agent vs. Multi-Agent LLM Strategies for Automated Student Reflection Assessment
by: Li, Gen, et al.
Published: (2025)
by: Li, Gen, et al.
Published: (2025)
Interpret3C: Interpretable Student Clustering Through Individualized Feature Selection
by: Salles, Isadora, et al.
Published: (2024)
by: Salles, Isadora, et al.
Published: (2024)
Benchmark-Driven Selection of AI: Evidence from DeepSeek-R1
by: Spelda, Petr, et al.
Published: (2025)
by: Spelda, Petr, et al.
Published: (2025)
A Comparative Analysis of Student Performance Predictions in Online Courses using Heterogeneous Knowledge Graphs
by: Trask, Thomas, et al.
Published: (2024)
by: Trask, Thomas, et al.
Published: (2024)
Transformative Influence of LLM and AI Tools in Student Social Media Engagement: Analyzing Personalization, Communication Efficiency, and Collaborative Learning
by: Bashiri, Masoud, et al.
Published: (2024)
by: Bashiri, Masoud, et al.
Published: (2024)
Personalized Knowledge Tracing through Student Representation Reconstruction and Class Imbalance Mitigation
by: Chen, Zhiyu, et al.
Published: (2024)
by: Chen, Zhiyu, et al.
Published: (2024)
Multi-Layer Personalized Federated Learning for Mitigating Biases in Student Predictive Analytics
by: Chu, Yun-Wei, et al.
Published: (2022)
by: Chu, Yun-Wei, et al.
Published: (2022)
Semantic Risk Scoring of Aggregated Metrics: An AI-Driven Approach for Healthcare Data Governance
by: Ahmed, Mohammed Omer Shakeel
Published: (2026)
by: Ahmed, Mohammed Omer Shakeel
Published: (2026)
Simulating Students or Sycophantic Problem Solving? On Misconception Faithfulness of LLM Simulators
by: Do, Heejin, et al.
Published: (2026)
by: Do, Heejin, et al.
Published: (2026)
Similar Items
-
A Practice in Enrollment Prediction with Markov Chain Models
by: Zhao, Yan, et al.
Published: (2024) -
Machine Learning-Driven Student Performance Prediction for Enhancing Tiered Instruction
by: Chen, Yawen, et al.
Published: (2025) -
Improvement of Applicability in Student Performance Prediction Based on Transfer Learning
by: Zhao, Yan
Published: (2024) -
Student Answer Forecasting: Transformer-Driven Answer Choice Prediction for Language Learning
by: Gado, Elena Grazia, et al.
Published: (2024) -
Predicting and Understanding College Student Mental Health with Interpretable Machine Learning
by: Chowdhury, Meghna Roy, et al.
Published: (2025)