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Security and Privacy Implications of Pervasive Memory Augmentation
2015
IEEE pervasive computing
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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
2020
IEEE Access
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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]
2019
arXiv
pre-print
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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]
2021
arXiv
pre-print
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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]
2016
arXiv
pre-print
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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
2021
IEEE Access
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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]
2021
arXiv
pre-print
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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
2021
IEEE Transactions on Cybernetics
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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]
2008
Advances in Psychology
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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]
2021
arXiv
pre-print
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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
2015
2015 20th International Conference on Control Systems and Computer Science
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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
2019
Frontiers in Cellular Neuroscience
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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]
2015
IFIP Advances in Information and Communication Technology
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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]
2020
arXiv
pre-print
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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
2021
Complexity
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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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