Computer Science ›› 2022, Vol. 49 ›› Issue (10): 83-95.doi: 10.11896/jsjkx.211000119
• Database & Big Data & Data Science • Previous Articles Next Articles
CHEN Zhi-yu1, SHAN Zhi-long1,2
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| [1]LIU H Y,ZHANG T C,WU P W,et al.A review of knowledge tracking [J].Journal of East China Normal University:Natural Sciences,2019(5):1-15. [2]SAPOUNTZI A,BHULAI S,CORNELISZ I,et al.DynamicKnowledge Tracing Models for Large-Scale Adaptive Learning Environments[J].International Journalon Advances in Intelligent Systems,2019,12(3):93-110. [3]LI F M,YE Y W,LI X F,et al.The application of knowledge tracking model in education:A Review of Relevant Research from 2008 to 2017 [J].China Distance Education,2019(7):86-91. [4]GERVET T,KOEDINGER K.When is Deep Learning the Best Approach to Knowledge Tracing- [J].Journal of Educational Data Mining,2020,12(3):31-54. [5]HU X G,LIU F,BU C Y.Research progress of cognitive tra-cking model in education big data[J].Computer Research and Development,2020,57(12):47-70. [6]CASALINO G,GRILLI L,LIMONE P,et al.Deep learning for knowledge tracing in learning analytics:an overview [C]//Technology Enhanced Learning Environments for Blended Education(teleXbe).2021,2817:1-10. [7]LIU T Y,CHEN W,CHANG L,et al.Based on deep learning knowledge to track progress [J/OL].[2021-10-10].http://kns.cnki.net/kcms/detail/11.1777.TP.20210609.0938.002.html. [8]LIANG K,REN Y M,SHANG Y H,et al.A Review of deep Learner-driven Knowledge tracking [J/OL].[2021-10-10].http://kns.cnki.net/kcms/detail/11.2127.tp.20210729.1649.012.html. [9]LIU Q,SHEN S,HUANG Z,et al.A Survey of Knowledge Tra-cing[J].arXiv:2105.15106,2021. [10]PANDEY S,KARYPIS G,SRIVASTAVA J.An EmpiricalComparison of Deep Learning Models for Knowledge Tracing on Large-Scale Dataset[J].arXiv:2101.06373,2021. [11]ZHANG N,JIANG B.Review on The Research Progress ofStudent Knowledge Tracking [J].Computer Science,2021,48(4):213-222. [12]CORBETT A T,ANDERSON J R.Knowledge tracing:Mode-ling the acquisition of procedural knowledge [J].User Modeling and User-adapted Interaction,1994,4(4):253-78. [13]PIECH C,SPENCER J,HUANG J,et al.Deep knowledge tra-cing [J].arXiv:1506.05908,2015. [14]SHEN S,LIU Q,CHEN E,et al.Convolutional knowledge tra-cing:Modeling individualization in student learning process[C]//Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval.2020:1857-1860. [15]PANDEY S,KARYPIS G.A self-attentive model for knowledge tracing [J].arXiv:1907.06837,2019. [16]BAKER R S J D,CORBETT A T,ALEVEN V.More accurate student modeling through contextual estimation of slip and guess probabilities in bayesian knowledge tracing[C]//International Conference on Intelligent Tutoring Systems.Berlin:Springer,2008:406-415. [17]PARDOS Z A,HEFFERNAN N T.Modeling individualization in a bayesian networks implementation of knowledge tracing [C]//International Conference on User Modeling,Adaptation,and Personalization.Berlin:Springer,2010:255-266. [18]LEE J I,BRUNSKILL E.The Impact on Individualizing Student Models on Necessary Practice Opportunities [J].British Journal of Dermatology,2012,169(4):910-915. [19]QIU Y,QI Y,LU H,et al.Does Time Matter-Modeling theEffect of Time with Bayesian Knowledge Tracing[C]//EDM.2011:139-148. [20]GONZÁLEZ-BRENES J,HUANG Y,BRUSILOVSKY P.Gene-ral features in knowledge tracing to model multiple subskills,temporal item response theory,and expert knowledge[C]//The 7th International Conference on Educational Data Mining.University of Pittsburgh,2014:84-91. [21]WANG Y,HEFFERNAN N T.Leveraging First ResponseTime into the Knowledge Tracing Model[C]//International Conference on Educational Data Mining(EDM).2016:176-179. [22]VIE J J,KASHIMA H.Knowledge tracing machines:Factorization machines for knowledge tracing[C]//Proceedings of the AAAI Conference on Artificial Intelligence.2019:750-757. [23]WU R,LIU Q,LIU Y,et al.Cognitive modelling for predicting examinee performance [C]//Proceedings of the 24th International Conference on Artificial Intelligence.Buenos Aires,Argentina:AAAI Press,2015:1017-1024. [24]GHOSH A,RASPAT J,LAN A.Option Tracing:Beyond Correctness Analysis in Knowledge Tracing [C]//International Conference on Artificial Intelligence in Education.Cham:Sprin-ger,2021:137-149. [25]WANG Y,HEFFERNAN N.Extending knowledge tracing toallow partial credit:Using continuous versus binary nodes[C]//International Conference on Artificial Intelligence in Education.Berlin:Springer,2013:181-188. [26]CEN H,KOEDINGER K,JUNKER B.Learning factors analysis-a general method for cognitive model evaluation and improvement[C]//International Conference on Intelligent Tutoring Systems.Berlin:Springer,2006:164-175. [27]PAVLIK JR P I,CEN H,KOEDINGER K R.Performance Factors Analysis--A New Alternative to Knowledge Tracing[C]//14th International Conference on Artificial Intelligence in Education.2009:531-538. [28]XU Y,MOSTOW J.Using Logistic Regression to Trace Multiple Sub-skills in a Dynamic Bayes Net[C]//EDM.2011:241-246. [29]KÄSER T,KLINGLER S,SCHWING A G,et al.DynamicBayesian networks for student modeling [J].IEEE Transactions on Learning Technologies,2017,10(4):450-462. [30]ZHANG J,SHI X,KING I,et al.Dynamic key-value memorynetworks for knowledge tracing[C]//Proceedings of the 26th International Conference on World Wide Web.2017:765-774. [31]YANG Y,SHEN J,QU Y,et al.GIKT:a graph-based interaction model for knowledge tracing[C]//Joint European Confe-rence on Machine Learning and Knowledge Discovery in Databa-ses.Cham:Springer,2020:299-315. [32]GHOSH A,HEFFERNAN N,LAN A S.Context-aware attentive knowledge tracing [C]//Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining.2020:2330-2339. [33]ZHANG L,XIONG X,ZHAO S,et al.Incorporating rich fea-tures into deep knowledge tracing[C]//Proceedings of the fourth(2017) ACM Conference on Learning@ Scale.2017:169-172. [34]CHEN P,LU Y,ZHENG V W,et al.Prerequisite-driven deepknowledge tracing[C]//2018 IEEE International Conference on Data Mining(ICDM).IEEE,2018:39-48. [35]SU Y,LIU Q,LIU Q,et al.Exercise-enhanced sequential mode-ling for student performance prediction[C]//Proceedings of the AAAI Conference on Artificial Intelligence.2018:2435-2443. [36]LIU Q,HUANG Z,YIN Y,et al.Ekt:Exercise-aware know-ledge tracing for student performance prediction[J].IEEE Transactions on Knowledge and Data Engineering,2019,33(1):100-115. [37]MONGKHONVANIT K,KANOPKA K,LANG D.Deepknowledge tracing and engagement with moocs [C]//Procee-dings of the 9th International Conference on Learning Analytics &Knowledge.2019:340-342. [38]WANG Z,FENG X,TANG J,et al.Deep knowledge tracingwith side information [C]//International Conference on Artificial Intelligence in Education.Cham:Springer,2019:303-308. [39]NAGATANI K,ZHANG Q,SATO M,et al.Augmentingknowledge tracing by considering forgetting behavior[C]//The World Wide Web Conference.2019:3101-3107. [40]LI X G,WEI S Q,ZHANG X,et al.LFKT:Deep KnowledgeTracking Model for Learning and Forgetting Fusion [J].Journal of Software,2021,32(3):818-830. [41]ABDELRAHMAN G,WANG Q.Knowledge tracing with se-quential key-value memory networks[C]//Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval.2019:175-184. [42]SUN X, ZHAO X, LI B,et al.Dynamic Key-Value MemoryNetworks With Rich Features for Knowledge Tracing[EB/OL].https://www.researchgate.net/publication/349001411_Dynamic_Key-Value_Memory_Networks_With_Rich_Features_for_Knowledge_Tracing. [43]MINN S,YU Y,DESMARAIS M C,et al.Deep knowledge tra-cing and dynamic student classification for knowledge tracing[C]//2018 IEEE International Conference on Data Mining(ICDM).IEEE,2018:1182-1187. [44]MINN S, DESMARAIS M C, ZHU F,et al.Dynamic Student Classification on Memory Networks for Knowledge Tracing[C]//Pacific-Asia Conference on Knowledge Discovery and Data Mining.2019:163-174. [45]AI F,CHEN Y,GUO Y,et al.Concept-Aware Deep Knowledge Tracing and Exercise Recommendation in an Online Learning System[C]//International Educational Data Mining Society.2019:2-5. [46]NAKAGAWA H,IWASAWA Y,MATSUO Y.Graph-basedknowledge tracing:modeling student proficiency using graph neural network[C]//2019 IEEE/WIC/ACM International Conference on Web Intelligence(WI).IEEE,2019:156-163. [47]YEUNG C K,YEUNG D Y.Addressing two problems in deep knowledge tracing via prediction-consistent regularization[C]//Proceedings of the Fifth Annual ACM Conference on Learning atScale.2018:1-10. [48]ZHU J,YU W,ZHENG Z,et al.Learning from InterpretableAnalysis:Attention-Based Knowledge Tracing[C]//International Conference on Artificial Intelligence in Education.Cham:Springer,2020:364-368. [49]PU S,YUDELSON M,OU L,et al.Deep knowledge tracingwith transformers [C]//International Conference on Artificial Intelligence in Education.Cham:Springer,2020:252-256. [50]CHOI Y,LEE Y,CHO J,et al.Towards an Appropriate Query,Key,and Value Computation for Knowledge Tracing [C]//Proceedings of the Seventh ACM Conference on Learning @ Scale.Virtual Event,USA,Association for Computing Machinery.2020:341-344. [51]PANDEY S,SRIVASTAVA J.Rkt:Relation-aware self-attention for knowledge tracing[C]//Proceedings of the 29th ACM International Conference on Information & Knowledge Management.2020:1205-1214. [52]TANG J,QU M,WANG M,et al.Line:Large-scale information network embedding [C]//Proceedings of the 24th International Conference on World Wide Web.2015:1067-1077. [53]GROVER A,LESKOVEC J.node2vec:Scalable feature learning for networks[C]//Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mi-ning.2016:855-864. [54] LEWIS P M.R63-33 Introduction to the Theory of Finite State Machines[J].IEEE Transactions on Electronic Computers,1963,EC-12(2):155-156. [55]VASWANI A,SHAZEER N,PARMAR N,et al.Attention isall you need[C]//Advances in Neural Information Processing Systems.2017:5998-6008. [56]DEVLIN J,CHANG M W,LEE K,et al.Bert:Pre-training of deep bidirectional transformers for language understanding[J].arXiv:1810.04805,2018. [57]DELAVENAY E,DELAVENAY K M.An introduction to machine translation[M].London:Thames and Hudson,1960. [58]ROBERTS C W.Text Analysis[M].Blackwell PublishersInc.,2015. [59]KOEDINGER K R.Toward evidence for instructional designprinciples:Examples from Cognitive Tutor Math 6[C]//Proceedings of PME-NA XXXIII(the North American Chapter of the International Group for the Psychology of Mathematics Education).2002:20-49. [60]KASURINEN J,NIKULA U.Estimating programming know-ledge with Bayesian knowledge tracing[J].ACM SIGCSE Bulletin,2009,41(3):313-317. [61]PARDOS Z,BERGNER Y,SEATON D,et al.Adapting baye-sian knowledge tracing to a massive open online course in edx[C]//Educational Data Mining.2013:137-144. [62]WANG Z,ZHANG M.Evaluation of MOOC Students Based on Bayesian Knowledge Tracking Model[J].China Science and Technology Papers,2015,10(2):241-246. [63]SPAULDING S,GORDON G,BREAZEAL C L.Affect-aware student models for robot tutors[C]//Proceedings of the 2016 International Conference on Autonomous Agents & Multiagent Systems.2016:864-872. [64]SCHODDE T,BERGMANN K,KOPP S.Adaptive robot lan-guage tutoring based on Bayesian knowledge tracing and predictive decision-making[C]//Proceedings of the 2017 ACM/IEEE International Conference on Human-Robot Interaction.2017:128-136. [65]ZHU T Y,HUANG Z Y,CHEN E H,et al.Personalized Question Recommendation Method Based on Cognitive Diagnosis [J].Chinese Journal of Computers,2017,40(1):176-191. [66]MONGKHONVANIT K,KANOPKA K,LANG D.Deepknowledge tracing and engagement with moocs[C]//Procee-dings of the 9th International Conference on Learning Analytics &Knowledge.2019:340-342. [67]YEUNG C K,YEUNG D Y.Incorporating features learned by an enhanced deep knowledge tracing model for stem/non-stem job prediction[J].International Journal of Artificial Intelligence in Education,2019,29(3):317-341. [68]WANG S,XU Y,LI Q,et al.Learning Path Planning Algorithm Based on Learner Behavior Analysis[C]//2021 4th International Conference on Big Data and Education.2021:26-33. [69]RUAN S,WEI W,LANDAY J.Variational Deep KnowledgeTracing for Language Learning[C]//LAK21:11th International Learning Analytics and Knowledge Conference.2021:323-332. [70]WANG C,SAHEBI S,ZHAO S,et al.Knowledge Tracing for Complex Problem Solving:Granular Rank-Based Tensor Factori-zation[C]//Proceedings of the 29th ACM Conference on User Modeling,Adaptation and Personalization.2021:179-188. |
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