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Security and Privacy Implications of Pervasive Memory Augmentation

Nigel Davies, Adrian Friday, Sarah Clinch, Corina Sas, Marc Langheinrich, Geoff Ward, Albrecht Schmidt
2015 IEEE pervasive computing  
could have a transformational impact on the lives of citizens by improving the acquisition of new knowledge, retention of existing knowledge, and loss of unwanted knowledge.  ...  (For evidence that timely prompts through technology can increase the effectiveness of behavior change, see work by Andrew Prestwich, Marco Perugini, and Robert Hurling. 6 ) Learning Pervasive memory-augmentation  ... 
doi:10.1109/mprv.2015.13 fatcat:6iq4opl4tvdhbdiuduqucxtib4

Multiple Features Fusion Attention Mechanism Enhanced Deep Knowledge Tracing for Student Performance Prediction

Dong Liu, Yunping Zhang, Jun Zhang, Qinpeng Li, Congpin Zhang, Yu Yin
2020 IEEE Access  
the knowledge tracing model.  ...  Generally, student performance prediction is achieved by tracing the evolution of each student's knowledge states via a series of learning activities.  ...  Students can recognize their poor knowledge points and make individual learning schemes by tracing the knowledge state.  ... 
doi:10.1109/access.2020.3033200 fatcat:oyov7avxjnaktksdc36bg2cgxy

Deep Trustworthy Knowledge Tracing [article]

Heonseok Ha, Uiwon Hwang, Yongjun Hong, Jahee Jang, Sungroh Yoon
2019 arXiv   pre-print
Knowledge tracing (KT), a key component of an intelligent tutoring system, is a machine learning technique that estimates the mastery level of a student based on his/her past performance.  ...  To substantiate the claim, we show limitations of DLKT from various perspectives such as knowledge state update failure, catastrophic forgetting, and non-interpretability.  ...  Nagatani et al. address the forgetting pattern of the student by using auxiliary time information. This method is similar to our method in terms of considering the forgetting pattern in DLKT.  ... 
arXiv:1805.10768v3 fatcat:xq75fsfwi5gplmqoujswo6lrsi

Deep Graph Memory Networks for Forgetting-Robust Knowledge Tracing [article]

Ghodai Abdelrahman, Qing Wang
2021 arXiv   pre-print
Recent knowledge tracing methods tend to respond to these challenges by modelling knowledge state dynamics across learning concepts.  ...  Particularly, this forget gating mechanism is built upon attention forgetting features over latent concepts considering their mutual dependencies.  ...  Knowledge Tracing Methods.  ... 
arXiv:2108.08105v1 fatcat:a6wj7dkifnhwxprismlqsea464

How deep is knowledge tracing? [article]

Mohammad Khajah and Robert V. Lindsey and Michael C. Mozer
2016 arXiv   pre-print
tracing or DKT---has demonstrated a stunning performance advantage over the mainstay of the field, Bayesian knowledge tracing or BKT.  ...  In this article, we attempt to understand the basis for DKT's advantage by considering the sources of statistical regularity in the data that DKT can leverage but which BKT cannot.  ...  ACKNOWLEDGMENTS This research was supported by NSF grants SES-1461535, SBE-0542013, and SMA-1041755.  ... 
arXiv:1604.02416v2 fatcat:wsl4oujmszfgbmfedqndihurlm

A Dynamic Knowledge Diagnosis Approach Integrating Cognitive Features

Tao Huang, Huali Yang, Zhi Li, Hekun Xie, Jing Geng, Hao Zhang
2021 IEEE Access  
However, existing approaches to diagnosis either exploit data from a one-time assessment for the cognitive diagnosis (ignoring the previous historical interactions) or trace the knowledge state using recurrent  ...  Specifically, given the characteristics of assessment data in China, our approach mainly aims to model sequence data with cognitive features, including forgetting and learning.  ...  DKT+F [10] is an extension of the DKT model by considering forgetting behavior to predict performance. Our proposed model is CF-DKD in this study. C.  ... 
doi:10.1109/access.2021.3105830 fatcat:3xujfazwxfhgle3xv4ssqdm6nu

Deep Knowledge Tracing with Learning Curves [article]

Shanghui Yang, Mengxia Zhu, Xuesong Lu
2021 arXiv   pre-print
Based on this theory, we propose a Convolution-Augmented Knowledge Tracing (CAKT) model in this paper.  ...  Knowledge tracing (KT) has recently been an active research area of computational pedagogy.  ...  The mechanism down-weights the importance of questions in the distant past to mimic the forgetting behavior. Nakagawa et al.  ... 
arXiv:2008.01169v2 fatcat:ogcrwrc26nahrjfguxawxlapki

Dynamic Key-Value Memory Networks With Rich Features for Knowledge Tracing

Xia Sun, Xu Zhao, Bo Li, Yuan Ma, Richard Sutcliffe, Jun Feng
2021 IEEE Transactions on Cybernetics  
The dynamic key-value memory network (DKVMN) proposed for processing knowledge tracing tasks is considered to be superior to other methods.  ...  Knowledge tracing is an important research topic in student modeling. The aim is to model a student's knowledge state by mining a large number of exercise records.  ...  By modeling student's learning behavior through their past exercise records, knowledge tracing can assess their mastery of knowledge skills.  ... 
doi:10.1109/tcyb.2021.3051028 pmid:33531331 fatcat:65pvoorio5bdzeoe25nwwlz6pm

The Role of Inhibition in Learning [chapter]

Justin C. Hulbert, Michael C. Anderson
2008 Advances in Psychology  
Consider professors and experts, who routinely retrieve and present only a subset of their wealth of knowledge.  ...  Concluding remarks On one hand, learning, by definition, involves the acquisition of knowledge. Inhibition, on the other hand, involves the reduction in accessibility of a memory trace.  ... 
doi:10.1016/s0166-4115(08)10002-4 fatcat:ne6n3atfcng4dbpqx5ya6bp7gy

Intentional Forgetting [article]

Deborah Shands, Carolyn Talcott
2021 arXiv   pre-print
Intentional forgetting enables software and hardware system designers at every level of abstraction to clearly specify and rigorously reason about the forgetting capabilities required of and provided by  ...  We discuss approaches to modeling intentional forgetting and then modeling the strength of a system's forgetting capability by its resistance to disclosing information to different types of detectors.  ...  Acknowledgements This work was funded by the U.S. Department of Homeland Security (DHS) Science and Technology (S&T) Directorate under Contract No. HSHQDC-16-C-00034.  ... 
arXiv:2106.09802v1 fatcat:smdza2cdabhpjih23raocoryzi

Spatio-Temporal Guidance for Ambient Agents

Ahmed-Chawki Chaouche, Amal El Fallah Seghrouchni, Jean-Michel Ilie, Djamel Eddine Saidouni
2015 2015 20th International Conference on Control Systems and Computer Science  
Our objective is to improve the CPS mechanism by the use of reinforcement learning strategy.  ...  Consider that the set of elementary plan's names is ranged over by P 1 , P 2 , ... and that the set of all the possible behavior expressions is denoted E, ranged over by E 1 , E 2 , ....  ...  Contextual Planning System with Learning (CPS-L) The structure CPS-L inherits from the maximum traces Σ M AX of the CPS, augmented by the different values EP a ( ) and ED a ( ) whatever the action a to  ... 
doi:10.1109/cscs.2015.79 dblp:conf/cscs/ChaoucheFIS15 fatcat:yu6x257lifdy5jrshx7rab4ac4

Remembering to Forget: A Dual Role for Sleep Oscillations in Memory Consolidation and Forgetting

Jesse J. Langille
2019 Frontiers in Cellular Neuroscience  
I go on to speculatively consider several sleep stage specific forgetting mechanisms and conclude by discussing a notional function of NREM-rapid eye movement sleep (REMS) cycling.  ...  memory consolidation and adaptive forgetting.  ...  In brief, non-theta REMS activity may possess a seldom considered forgetting function.  ... 
doi:10.3389/fncel.2019.00071 pmid:30930746 pmcid:PMC6425990 fatcat:3k3gwvgwzjfrxg7fnilnezgsji

Improving the Contextual Selection of BDI Plans by Incorporating Situated Experiments [chapter]

Ahmed-Chawki Chaouche, Amal El Fallah Seghrouchni, Jean-Michel Ilié, Djamel Eddine Saïdouni
2015 IFIP Advances in Information and Communication Technology  
Adopting the idea that "location" and "time" are key stones information in the activity of the agent, we show how to enforce guidance by ordering the different possible plans.  ...  Spatio-Temporal Guidance from Past-Experiences Contextual Planning System with Learning (CPS-L) The structure CPS-L inherits from the maximum traces Σ M AX of the CPS, augmented by the different values  ...  To select an optimal trace, the set Σ M AX of maximum traces is ordered regarding the assigned values from QP and N QD, considered separately.  ... 
doi:10.1007/978-3-319-23868-5_19 fatcat:5uwknj5axzajnpukli6asr2sba

GIKT: A Graph-based Interaction Model for Knowledge Tracing [article]

Yang Yang, Jian Shen, Yanru Qu, Yunfei Liu, Kerong Wang, Yaoming Zhu, Weinan Zhang, Yong Yu
2020 arXiv   pre-print
With the rapid development in online education, knowledge tracing (KT) has become a fundamental problem which traces students' knowledge status and predicts their performance on new questions.  ...  In this paper, we propose a Graph-based Interaction model for Knowledge Tracing (GIKT) to tackle the above probems.  ...  Based on these two models, several methods have been proposed by considering more information, such as the forgetting behavior of students [16] , multi-skill information and prerequisite skill relation  ... 
arXiv:2009.05991v1 fatcat:b3afj23hj5aedmvyesyx77o7ve

Social Networks through the Prism of Cognition

Radosław Michalski, Boleslaw K. Szymanski, Przemysław Kazienko, Christian Lebiere, Omar Lizardo, Marcin Kulisiewicz, Fei Xiong
2021 Complexity  
Human relations are driven by social events—people interact, exchange information, share knowledge and emotions, and gather news from mass media.  ...  Each trace continuously weakens over time unless another related event activity strengthens it.  ...  Memory is considered to be one of the most important components of human cognition. is is especially the case given the necessity to efficiently retrieve large amounts of knowledge and to select information  ... 
doi:10.1155/2021/4963903 fatcat:sbbu3dknqngajcepohcmqki6tu
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