Filters








4,006 Hits in 15.9 sec

Applying Learning Analytics to Detect Sequences of Actions and Common Errors in a Geometry Game

Manuel J. Gomez, José A. Ruipérez-Valiente, Pedro A. Martínez, Yoon Jeon Kim
2021 Sensors  
The final objective is to facilitate that teachers can understand the sequence of actions and common errors of students using Shadowspect so they can better understand the process, make proper assessment  ...  More specifically, we build our work on top of Shadowspect, a three-dimensional geometry game that has been developed to measure geometry skills as well other cognitive and noncognitive skills.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/s21041025 pmid:33546167 fatcat:3zfv66ai3zcwtbwifzxbhmt65m

Ideating and Developing a Visualization Dashboard to Support Teachers Using Educational Games in the Classroom

Jose A Ruiperez-Valiente, Manuel J. Gomez, Pedro A. Martinez, Yoon Jeon Kim
2021 IEEE Access  
For this work, we build upon Shadowspect, a 3D geometry puzzle game that has been used by teachers in a group of schools in the US.  ...  To support teachers, educational games should incorporate learning analytics to transform data generated by students when playing useful information in a friendly and understandable way.  ...  ACKNOWLEDGMENT The authors would like to recognize Shadowspect design and development team at the MIT Playful Journey Lab, along with the folks at Firehose, for their collaborative work bringing the game  ... 
doi:10.1109/access.2021.3086703 fatcat:veuqh5iexjhrnok5y62dew5m4m

Developing a generalizable detector of when students game the system

Ryan S. J. d. Baker, Albert T. Corbett, Ido Roll, Kenneth R. Koedinger
2008 User modeling and user-adapted interaction  
Some students, when working in interactive learning environments, attempt to "game the system", attempting to succeed in the environment by exploiting properties of the system rather than by learning the  ...  In this paper, we present a system that can accurately detect whether a student is gaming the system, within a Cognitive Tutor mathematics curricula.  ...  Nottingham, and by IERI grant number REC-043779 to "Learning-Oriented Dialogue in Cognitive Tutors: Towards a Scalable Solution to Performance Orientation".  ... 
doi:10.1007/s11257-007-9045-6 fatcat:m5l3hpijgfc4ba3jmf25i2kiua

EventAnchor: Reducing Human Interactions in Event Annotation of Racket Sports Videos [article]

Dazhen Deng, Jiang Wu, Jiachen Wang, Yihong Wu, Xiao Xie, Zheng Zhou, Hui Zhang, Xiaolong Zhang, Yingcai Wu
2021 arXiv   pre-print
Our approach uses machine learning models in computer vision to help users acquire essential events from videos (e.g., serve, the ball bouncing on the court) and offers users a set of interactive tools  ...  In this paper, we propose EventAnchor, a data analysis framework to facilitate interactive annotation of racket sports video with the support of computer vision algorithms.  ...  The work was supported by National Key R&D Program of China (2018YFB1004300), NSFC (62072400), Zhejiang Provincial Natural Science Foundation (LR18F020001), and the 100 Talents Program of Zhejiang University  ... 
arXiv:2101.04954v2 fatcat:t2ty6bcpsnczzdqxxdjx5gby6a

Exploring the Assistance Dilemma in Experiments with Cognitive Tutors

Kenneth R. Koedinger, Vincent Aleven
2007 Educational Psychology Review  
Cognitive Tutors provide a rich problem-solving environment with tutorial guidance in the form of step-by-step feedback, specific messages in response to common errors, and ondemand instructional hints  ...  As Cognitive Tutors have matured and are being applied in new subject-matter areas, they have been used as a research platform and, particularly, to explore interactive methods to support metacognition  ...  In contrast to the goal of producing error-free experts, one might want to produce "intelligent novices" who may make initial errors, but are able to detect them and correct them.  ... 
doi:10.1007/s10648-007-9049-0 fatcat:2smamx25ije7vpkysql57uoixi

Playing Atari Ball Games with Hierarchical Reinforcement Learning [article]

Hua Huang, Adrian Barbu
2019 arXiv   pre-print
We argue that these instructions have tremendous value in designing a reinforcement learning system which can learn in human fashion, and we test the idea by playing the Atari games Tennis and Pong.  ...  In this paper, we test the idea of speeding up machine learning through social learning.  ...  The action effect can be pre-trained offline, and in this game design, the movement of one step of action is fixed, so the subpolicy π(s, o) can be derived analytically here.  ... 
arXiv:1909.12465v1 fatcat:lungjcxzfjhz3ell3gpuenk3sq

Hierarchical Policy Design for Sample-Efficient Learning of Robot Table Tennis Through Self-Play [article]

Reza Mahjourian, Risto Miikkulainen, Nevena Lazic, Sergey Levine, Navdeep Jaitly
2019 arXiv   pre-print
Training robots with physical bodies requires developing new methods and action representations that allow the learning agents to explore the space of policies efficiently.  ...  After only about 24,000 strikes in self-play the agent learns to best exploit the human dynamics models for longer cooperative games.  ...  Acknowledgments Special thanks to Erwin Coumans for help with PyBullet and VR integration, Torsten Kröger and Kurt Konolige for help and discussions on the Reflexxes library, and the Google Brain team  ... 
arXiv:1811.12927v2 fatcat:zzyl67addrc77h4vm3fmhtlt5m

Keep It Simple and Sparse: Real-Time Action Recognition [chapter]

Sean Ryan Fanello, Ilaria Gori, Giorgio Metta, Francesca Odone
2017 Gesture Recognition  
In this paper we show that sparse representation plays a fundamental role in achieving one-shot learning and real-time recognition of actions.  ...  We then apply a sparse coding stage, which allows us to take care of noise and redundant information and produces a compact and stable representation of the image content.  ...  Acknowledgments This work was supported by the European FP7 ICT projects N. 270490 (EFAA) and N. 270273 (Xperience).  ... 
doi:10.1007/978-3-319-57021-1_10 fatcat:yxitbm4nsnhhjlef3azje4j2zi

Locally time-invariant models of human activities using trajectories on the grassmannian

Pavan Turaga, Rama Chellappa
2009 2009 IEEE Conference on Computer Vision and Pattern Recognition  
Human activity analysis is an important problem in computer vision with applications in surveillance and summarization and indexing of consumer content.  ...  To this end, we describe activities as outputs of linear dynamic systems (LDS) whose parameters vary with time, or a Time-Varying Linear Dynamic System (TV-LDS).  ...  This requires one to have analytical expressions for the intra-cluster pdfs and the gradient of the likelihood of a sequence in terms of these parameters.  ... 
doi:10.1109/cvpr.2009.5206710 dblp:conf/cvpr/TuragaC09 fatcat:nmho4ic4m5gxxkme2tayehm3yq

Locally time-invariant models of human activities using trajectories on the grassmannian

P. Turaga, R. Chellappa
2009 2009 IEEE Conference on Computer Vision and Pattern Recognition  
Human activity analysis is an important problem in computer vision with applications in surveillance and summarization and indexing of consumer content.  ...  To this end, we describe activities as outputs of linear dynamic systems (LDS) whose parameters vary with time, or a Time-Varying Linear Dynamic System (TV-LDS).  ...  This requires one to have analytical expressions for the intra-cluster pdfs and the gradient of the likelihood of a sequence in terms of these parameters.  ... 
doi:10.1109/cvprw.2009.5206710 fatcat:nj2vsmmxkvhs3oerben3dg3whe

D4.4 Implementation of R8: Digital Learning Materials

Jon Arambarri, Maria Madarieta
2019 Zenodo  
The main objective of this task is O4.2. Design innovative learning methods to foster the empowerment of citizen and stakeholder (Result R8).  ...  This document describes the work done under Task 4.2 Learning materials within WP4 CREATION OF INNOVATIVE SOCIAL ACTIONS which main responsible is Virtualware with the contribution and help of Fundación  ...  or DP: A sequence of teaching units and activities with the aim of acquiring a series of specific skills and knowledge based on using technology as a learning facilitation tool, contents and online references  ... 
doi:10.5281/zenodo.3234019 fatcat:d6qujrxzhfaqhcgq6bwz2tvgfu

GTDM-CSAT: an LTE-U self Coexistence Solution based on Game Theory and Reinforcement Learning

Pedro Santana, José Neto, Fuad Abinader Jr., Vicente Sousa Jr.
2019 Journal of Communication and Information Systems  
The solution for the best ON-OFF time ratio is defined by applying a modified Minimax Q-learning algorithm for finding the game equilibrium.  ...  There is substantial literature covering both problems and solutions related to the operation of Long Term Evolution (LTE) networks in unlicensed spectrum (LTE-U) while in coexistence with other technologies  ...  In [22] , the authors use stochastic geometry to model and analyze the coexistence performance of Wi-Fi/LTE-U in a multi-RAT network.  ... 
doi:10.14209/jcis.2019.17 fatcat:iroq76jvcnc65gfxjywb4wssra

Use the Force, Luke! Learning to Predict Physical Forces by Simulating Effects [article]

Kiana Ehsani, Shubham Tulsiani, Saurabh Gupta, Ali Farhadi, Abhinav Gupta
2020 arXiv   pre-print
point and force prediction, we can improve the performance on both tasks in comparison to independent training, and (c) we can learn a representation from this model that generalizes to novel objects  ...  On the other hand, current recognition or geometric approaches lack the physicality of action representation. In this paper, we take a step towards a more physical understanding of actions.  ...  We would like to thank Dhiraj Gandhi for his help with the hardware setup.  ... 
arXiv:2003.12045v1 fatcat:h7idofmhvfclbiv46fg5oasumy

State-of-the-art in artificial neural network applications: A survey

Oludare Isaac Abiodun, Aman Jantan, Abiodun Esther Omolara, Kemi Victoria Dada, Nachaat AbdElatif Mohamed, Humaira Arshad
2018 Heliyon  
It provides a taxonomy of artificial neural networks (ANNs) and furnish the reader with knowledge of current and emerging trends in ANN applications research and area of focus for researchers.  ...  This is a survey of neural network applications in the real-world scenario.  ...  Acknowledgements The authors express appreciation to the staff and students of Security & Forensic Research Group (SFRG) Laboratory, School of Computer Sciences, Universiti Sains Malaysia, Penang Malaysia  ... 
doi:10.1016/j.heliyon.2018.e00938 pmid:30519653 pmcid:PMC6260436 fatcat:vqddhirom5e3fft2punuo4yrh4

Reinforcement Learning with Neural Networks for Quantum Feedback

Thomas Fösel, Petru Tighineanu, Talitha Weiss, Florian Marquardt
2018 Physical Review X  
To solve this, we develop two ideas: two-stage learning with teacher/student networks and a reward quantifying the capability to recover the quantum information stored in a multi-qubit system.  ...  This is the domain of reinforcement learning, where control strategies are improved according to a reward function.  ...  With a suitable encoding, this remains true even after some errors have happened, if a suitable error-detection and decoding sequence is applied ("recovery").  ... 
doi:10.1103/physrevx.8.031084 fatcat:2bxnq2x52banhhlnlz7pe5jhq4
« Previous Showing results 1 — 15 out of 4,006 results