Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance | Paper Citation Record

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Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance Unresolved cited work

Reference 1

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Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance Unresolved cited work

Reference 2

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Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance Unresolved cited work

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This paper cites Neural Machine Translation by Jointly Learning to Align and Translate.

Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance Neural Machine Translation by Jointly Learning to Align and Translate

Reference 4

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Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance Constrained-degree percolation in random environment

Reference 5

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This paper cites Simard, and Paolo Frasconi.

Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance Simard, and Paolo Frasconi

Reference 6

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Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance Unresolved cited work

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Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance Unresolved cited work

Reference 8

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Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance Unresolved cited work

Reference 9

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Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance Unresolved cited work

Reference 10

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Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance Unresolved cited work

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Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance Unresolved cited work

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Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance Unresolved cited work

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Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance Unresolved cited work

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Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance Unresolved cited work

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This paper cites Maybank, and Dacheng Tao.

Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance Maybank, and Dacheng Tao

Reference 16

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Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance Alamri, Ranim S

Reference 17

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Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance Unresolved cited work

Reference 18

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This paper cites Ajanovski, Mirela Gutica, Timo Hynninen, Antti Knutas, Juho Leinonen, Chris Messom, and Soohyun Nam Liao.

Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance Ajanovski, Mirela Gutica, Timo Hynninen, Antti Knutas, Juho Leinonen, Chris Messom, and Soohyun Nam Liao

Reference 19

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This paper cites Distilling the Knowledge in a Neural Network.

Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance Distilling the Knowledge in a Neural Network

Reference 20

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Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance Unresolved cited work

Reference 21

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Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance Unresolved cited work

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Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance Unresolved cited work

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Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance Unresolved cited work

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This paper cites GritNet: Student Performance Prediction with Deep Learning.

Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance GritNet: Student Performance Prediction with Deep Learning

Reference 25

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Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance Unresolved cited work

Reference 26

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Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance Unresolved cited work

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This paper cites Lopez Z, Tsubasa Minematsu, Yuta Taniguchi, Fumiya Okubo, and Atsushi Shimada.

Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance Lopez Z, Tsubasa Minematsu, Yuta Taniguchi, Fumiya Okubo, and Atsushi Shimada

Reference 28

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Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance Effective Approaches to Attention-based Neural Machine Translation

Reference 29

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Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance Unresolved cited work

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Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance Unresolved cited work

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Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance Unresolved cited work

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Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance Unresolved cited work

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Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance Unresolved cited work

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Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance Unresolved cited work

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Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance Unresolved cited work

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Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance Unresolved cited work

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This paper cites In Proceedings of the 25th International Con- ference on Computers in Education, ICCE 2017 - Main Conference Pro- ceedings.

Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance In Proceedings of the 25th International Con- ference on Computers in Education, ICCE 2017 - Main Conference Pro- ceedings

Reference 38

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Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance Unresolved cited work

Reference 39

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This paper cites Teaching Where to Look: Attention Similarity Knowledge Distillation for Low Resolution Face Recognition.

Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance Teaching Where to Look: Attention Similarity Knowledge Distillation for Low Resolution Face Recognition

Reference 40

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Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance Sequence to Sequence Learning with Neural Networks

Reference 41

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Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance Francisco Segura Altamirano

Reference 42

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This paper cites Detecting Unsuccessful Students in Cybersecurity Exercises in Two Different Learning Environments.

Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance Detecting Unsuccessful Students in Cybersecurity Exercises in Two Different Learning Environments

Reference 43

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Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance FitNets: Hints for Thin Deep Nets

Reference 44

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Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance Attention Distillation: self-supervised vision transformer students need more guidance

Reference 45

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Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance Unresolved cited work

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Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance Unresolved cited work

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Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance Unresolved cited work

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Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance Unresolved cited work

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Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance Unresolved cited work

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Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance Aljohani, Guanliang Chen, and Dragan Gasevic

Reference 51

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Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance Unresolved cited work

Reference 52

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This paper cites Delving Deeper into MOOC Student Dropout Prediction.

Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance Delving Deeper into MOOC Student Dropout Prediction

Reference 56

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Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance Unresolved cited work

Reference 59

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Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance Unresolved cited work

Reference 444

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Observation 6af119a1-e40e-444e-a64e-d7be6135cd1e · outbound

This paper cites Wallach, Rob Fergus, S.

Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance Wallach, Rob Fergus, S

Reference 2017

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Observation 8dbd83b8-fe24-447e-b388-5492f1a795de · outbound

This paper cites Computational Intelligence and Neuro- science 2018, 1 (10 2018), 6347186.

Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance Computational Intelligence and Neuro- science 2018, 1 (10 2018), 6347186

Reference 2018

Resolution: verified exact; doi, observed 2026-08-11T12:13:37.576071Z

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Observation 3c495ad1-5d81-42ef-b976-2991995f8e7a · outbound

This paper cites Applied Soft Computing 106 (7 2021), 107355.

Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance Applied Soft Computing 106 (7 2021), 107355

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-11T12:13:35.814569Z

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Observation 60a8705f-a3f8-4d67-b613-86c9e3e49864 · outbound

This paper cites In Proceed- ings of the 24th Australasian Computing Education Conference (ACE ’22) , Judy Sheard and Paul Denny (Eds.).

Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance In Proceed- ings of the 24th Australasian Computing Education Conference (ACE ’22) , Judy Sheard and Paul Denny (Eds.)

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-11T12:13:36.179233Z

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Observation 8a3117be-86fe-4836-92a3-e8fc8d8372b8 · outbound

This paper cites an unresolved cited work.

Knowledge Distillation in RNN-Attention Models for Early Prediction of Student Performance Unresolved cited work

Reference 5898

Resolution: unresolved; no resolver link, observed 2026-08-11T12:13:36.614754Z

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