A Systematic Review of Deep Learning Approaches to Educational Data Mining
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Borja Navarro-Colorado | David Tomás | Antonio Hernández-Blanco | Boris Herrera-Flores | Borja Navarro-Colorado | D. Tomás | Antonio Hernández-Blanco | Boris Herrera-Flores
[1] Roger Nkambou,et al. Convolutional Neural Network for Automatic Detection of Sociomoral Reasoning Level , 2017, EDM.
[2] Neil T. Heffernan,et al. The ASSISTments Ecosystem: Building a Platform that Brings Scientists and Teachers Together for Minimally Invasive Research on Human Learning and Teaching , 2014, International Journal of Artificial Intelligence in Education.
[3] Trevor Darrell,et al. Sequence to Sequence -- Video to Text , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[4] Jürgen Schmidhuber,et al. Long Short-Term Memory , 1997, Neural Computation.
[5] Mykola Pechenizkiy,et al. Handbook of Educational Data Mining , 2010 .
[6] Sebastián Ventura,et al. Data mining in education , 2013, WIREs Data Mining Knowl. Discov..
[7] Chen Lin,et al. A Comparisons of BKT, RNN and LSTM for Learning Gain Prediction , 2017, AIED.
[8] Yoshua Bengio,et al. Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation , 2014, EMNLP.
[9] Geoffrey E. Hinton. Deep belief networks , 2009, Scholarpedia.
[10] Arjun Sharma,et al. LIVELINET: A Multimodal Deep Recurrent Neural Network to Predict Liveliness in Educational Videos , 2016, EDM.
[11] Hugo Larochelle,et al. An Autoencoder Approach to Learning Bilingual Word Representations , 2014, NIPS.
[12] Di Wang,et al. A Long Short-Term Memory Model for Answer Sentence Selection in Question Answering , 2015, ACL.
[13] Osmar R. Zaïane,et al. Educational data mining applications and tasks: A survey of the last 10 years , 2017, Education and Information Technologies.
[14] Pedro M. Domingos. A few useful things to know about machine learning , 2012, Commun. ACM.
[15] Chunyan Miao,et al. Deep Model for Dropout Prediction in MOOCs , 2017, ICCSE'17.
[16] Tianqi Chen,et al. Net2Net: Accelerating Learning via Knowledge Transfer , 2015, ICLR.
[17] Cheng-Yuan Liou,et al. Autoencoder for words , 2014, Neurocomputing.
[18] Neil T. Heffernan,et al. Using Big Data to Sharpen Design-Based Inference in A/B Tests , 2018, EDM.
[19] Phil Blunsom,et al. A Convolutional Neural Network for Modelling Sentences , 2014, ACL.
[20] Jürgen Schmidhuber,et al. Framewise phoneme classification with bidirectional LSTM and other neural network architectures , 2005, Neural Networks.
[21] Hosam Al-Samarraie,et al. Educational data mining and learning analytics for 21st century higher education: A review and synthesis , 2019, Telematics Informatics.
[22] Varun Ganapathi,et al. GritNet 2: Real-Time Student Performance Prediction with Domain Adaptation , 2018, ArXiv.
[23] Yuan Zhang,et al. Deep Learning + Student Modeling + Clustering: a Recipe for Effective Automatic Short Answer Grading , 2016, EDM.
[24] Sebastián Ventura,et al. Educational Data Mining: A Review of the State of the Art , 2010, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).
[25] Yoshua Bengio,et al. Algorithms for Hyper-Parameter Optimization , 2011, NIPS.
[26] Michael C. Mozer,et al. A Focused Backpropagation Algorithm for Temporal Pattern Recognition , 1989, Complex Syst..
[27] Chris Piech,et al. Deep Knowledge Tracing On Programming Exercises , 2017, L@S.
[28] Kristy Elizabeth Boyer,et al. Predicting Dialogue Acts for Intelligent Virtual Agents with Multimodal Student Interaction Data , 2016, EDM.
[29] Dit-Yan Yeung,et al. Temporal Models for Predicting Student Dropout in Massive Open Online Courses , 2015, 2015 IEEE International Conference on Data Mining Workshop (ICDMW).
[30] Jürgen Schmidhuber,et al. Deep learning in neural networks: An overview , 2014, Neural Networks.
[31] Wei Xu,et al. Deep Captioning with Multimodal Recurrent Neural Networks (m-RNN) , 2014, ICLR.
[32] John J. Hopfield,et al. Neural networks and physical systems with emergent collective computational abilities , 1999 .
[33] Joseph E. Beck,et al. Going Deeper with Deep Knowledge Tracing , 2016, EDM.
[34] Qiang Yang,et al. A Survey on Transfer Learning , 2010, IEEE Transactions on Knowledge and Data Engineering.
[35] Alex Graves,et al. Generating Sequences With Recurrent Neural Networks , 2013, ArXiv.
[36] Min Chi,et al. Deep Learning vs. Bayesian Knowledge Tracing: Student Models for Interventions , 2018 .
[37] Peter Glöckner,et al. Why Does Unsupervised Pre-training Help Deep Learning? , 2013 .
[38] Sung Wook Baik,et al. Action Recognition in Video Sequences using Deep Bi-Directional LSTM With CNN Features , 2018, IEEE Access.
[39] Neil T. Heffernan,et al. Addressing the assessment challenge with an online system that tutors as it assesses , 2009, User Modeling and User-Adapted Interaction.
[40] Jacob Whitehill,et al. Who are they looking at? Automatic Eye Gaze Following for Classroom Observation Video Analysis , 2018, EDM.
[41] Yoshua Bengio,et al. On the Properties of Neural Machine Translation: Encoder–Decoder Approaches , 2014, SSST@EMNLP.
[42] Leonidas J. Guibas,et al. Deep Knowledge Tracing , 2015, NIPS.
[43] James C. Lester,et al. Improving Stealth Assessment in Game-based Learning with LSTM-based Analytics , 2018, EDM.
[44] Sebastián Ventura,et al. Educational data mining: A survey from 1995 to 2005 , 2007, Expert Syst. Appl..
[45] Geoffrey E. Hinton,et al. On the importance of initialization and momentum in deep learning , 2013, ICML.
[46] Paul Smolensky,et al. Information processing in dynamical systems: foundations of harmony theory , 1986 .
[47] Jason Weston,et al. Natural Language Processing (Almost) from Scratch , 2011, J. Mach. Learn. Res..
[48] Sweety Agrawal,et al. Few hundred parameters outperform few hundred thousand? , 2017, EDM.
[49] Cristina L. Abad,et al. An Undergraduate Project combining Computer Science and the Arts: An Experience Report of a Multidisciplinary Capstone Design , 2018, CSERC '18.
[50] Ming Yang,et al. 3D Convolutional Neural Networks for Human Action Recognition , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[51] Kai Wang,et al. Deep Recurrent Multi-instance Learning with Spatio-temporal Features for Engagement Intensity Prediction , 2018, ICMI.
[52] Varun Ganapathi,et al. GritNet: Student Performance Prediction with Deep Learning , 2018, EDM.
[53] Chris Wong,et al. Sequence Based Course Recommender for Personalized Curriculum Planning , 2018, AIED.
[54] Alejandro Peña-Ayala. Review: Educational data mining: A survey and a data mining-based analysis of recent works , 2014 .
[55] Christopher Brooks,et al. Social work in the classroom? A tool to evaluate topical relevance in student writing , 2017, EDM.
[56] Ryan S. Baker,et al. The State of Educational Data Mining in 2009: A Review and Future Visions. , 2009, EDM 2009.
[57] Andrew Zisserman,et al. Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.
[58] Hwee Tou Ng,et al. A Neural Approach to Automated Essay Scoring , 2016, EMNLP.
[59] Yoshua Bengio,et al. Practical Recommendations for Gradient-Based Training of Deep Architectures , 2012, Neural Networks: Tricks of the Trade.
[60] Alpana Dubey,et al. LeCoRe: A Framework for Modeling Learner's preference , 2018, EDM.
[61] Chris Piech,et al. Learning to Represent Student Knowledge on Programming Exercises Using Deep Learning , 2017, EDM.
[62] Thomas Jackson,et al. Neural Computing - An Introduction , 1990 .
[63] Dit-Yan Yeung,et al. Addressing two problems in deep knowledge tracing via prediction-consistent regularization , 2018, L@S.
[64] Mirza Mohtashim Alam,et al. A Reduced feature based neural network approach to classify the category of students , 2018, ICIAI '18.
[65] Demis Hassabis,et al. Mastering the game of Go with deep neural networks and tree search , 2016, Nature.
[66] Alejandro Peña Ayala,et al. Educational data mining: A survey and a data mining-based analysis of recent works , 2014, Expert Syst. Appl..
[67] Xiaolu Xiong,et al. Submission to the NIPS 2016 Workshop on Machine Learning for Education Estimating student proficiency : Deep learning is not the panacea , 2016 .
[68] Junyu Dong,et al. An Overview on Data Representation Learning: From Traditional Feature Learning to Recent Deep Learning , 2016, ArXiv.
[69] F ROSENBLATT,et al. The perceptron: a probabilistic model for information storage and organization in the brain. , 1958, Psychological review.
[70] Luca Maria Gambardella,et al. Max-pooling convolutional neural networks for vision-based hand gesture recognition , 2011, 2011 IEEE International Conference on Signal and Image Processing Applications (ICSIPA).
[71] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[72] Yoshua Bengio,et al. Gradient-based learning applied to document recognition , 1998, Proc. IEEE.
[73] Jacob Whitehill,et al. Delving Deeper into MOOC Student Dropout Prediction , 2017, ArXiv.
[74] Neil T. Heffernan,et al. Incorporating Rich Features into Deep Knowledge Tracing , 2017, L@S.
[75] Chaitanya Ekanadham,et al. Back to the basics: Bayesian extensions of IRT outperform neural networks for proficiency estimation , 2016, EDM.
[76] Zachary A. Pardos,et al. Deep Neural Networks and How They Apply to Sequential Education Data , 2016, L@S.
[77] Amal Zouaq,et al. A Comparison of Features for the Automatic Labeling of Student answers to Open-ended Questions , 2018, EDM.
[78] Wanli Xing,et al. Dropout Prediction in MOOCs: Using Deep Learning for Personalized Intervention , 2019 .
[79] Michael C. Mozer,et al. Does Deep Knowledge Tracing Model Interactions Among Skills? , 2018, EDM.
[80] Kenneth R. Koedinger,et al. A Data Repository for the EDM Community: The PSLC DataShop , 2010 .
[81] Wei Yu,et al. A Survey of Deep Learning: Platforms, Applications and Emerging Research Trends , 2018, IEEE Access.
[82] Neil T. Heffernan,et al. A Memory-Augmented Neural Model for Automated Grading , 2017, L@S.
[83] Hiroaki Ogata,et al. A neural network approach for students' performance prediction , 2017, LAK.
[84] Shiv Kumar Saini,et al. Modeling Hint-Taking Behavior and Knowledge State of Students with Multi-Task Learning , 2018, EDM.
[85] Jeffrey Dean,et al. Distributed Representations of Words and Phrases and their Compositionality , 2013, NIPS.
[86] Li Yang,et al. Predicting Students Performance in Educational Data Mining , 2015, 2015 International Symposium on Educational Technology (ISET).
[87] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[88] Nitish Srivastava,et al. Dropout: a simple way to prevent neural networks from overfitting , 2014, J. Mach. Learn. Res..
[89] Geoffrey E. Hinton,et al. Speech recognition with deep recurrent neural networks , 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.
[90] Laura Alonso Alemany,et al. Co-embeddings for Student Modeling in Virtual Learning Environments , 2018, UMAP.
[91] G. Lewicki,et al. Approximation by Superpositions of a Sigmoidal Function , 2003 .
[92] Quoc V. Le,et al. On optimization methods for deep learning , 2011, ICML.
[93] Jason Weston,et al. Memory Networks , 2014, ICLR.
[94] Bendangnuksung,et al. Students ' Performance Prediction Using Deep Neural Network , 2018 .