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Control structures in hypothesis spaces: The influence on learning [chapter]

John Case, Sanjay Jain, Mandayam Suraj
1997 Lecture Notes in Computer Science  
Studied herein are the e ects on learnability of the presence or absence of certain control structures in the hypothesis space.  ...  Each of these characterizes the invariance of a learning class over hypothesis space V (and a little more about V ) as: V has suitable instances of all denotational control structures.  ...  Acknowledgements We would like to thank Ganesh Baliga for helpful discussions, encouragement, and for suggesting some lines of research that, in part, led to the present paper.  ... 
doi:10.1007/3-540-62685-9_24 fatcat:b6nb3pl5orhtznstfytwolughi

Control structures in hypothesis spaces: the influence on learning

John Case, Sanjay Jain, Mandayam Suraj
2002 Theoretical Computer Science  
Studied herein are the in uence on learnability of the presence or absence of certain control structures in the hypothesis space.  ...  Each of these non-trivially characterizes the invariance of a learning class over hypothesis space V and the presence of a particular projection control structure, called proj, in V as: V has suitable  ...  Acknowledgements We would like to thank Ganesh Baliga for helpful discussions, encouragement, and for suggesting some lines of research that, in part, led to the present paper.  ... 
doi:10.1016/s0304-3975(00)00385-6 fatcat:a7eouvmezvesnfpjyvy7b46wfa

The Influence of Visual Motion on Motor Learning

Z. Danziger, F. A. Mussa-Ivaldi
2012 Journal of Neuroscience  
Consistent with our hypothesis, subjects learned to move the simulated linkage along geodesic lines corresponding to the geometrical structure of the observed motion.  ...  We present an alternative hypothesis in which movement trajectories also result from acquired knowledge about the geometrical properties of the object that the brain is controlling.  ...  ., July 18, 2012 • 32(29):9859 -9869 Danziger and Mussa-Ivaldi • The Influence of Visual Motion on Motor Learning  ... 
doi:10.1523/jneurosci.5528-11.2012 pmid:22815501 pmcid:PMC3437549 fatcat:5yd5skg2jbg2dmvrxywf7pfqmi

Simulation models of the influence of learning mode and training variance on category learning

R Elio
1994 Cognitive Science  
This article uses simulation as an empirical method for identifying process models of strategy effects in a category-learning task.  ...  A general set of learning LEARNING MODE AND VARIANCE EFFECTS 203 LEARNING MODE AND VARIANCE EFFECTS 205  ...  More simply, the space of patterns is not controlled in any deliberate sense.  ... 
doi:10.1016/0364-0213(94)90001-9 fatcat:jv7jiqxezbfhpjmru4j4ipzfnu

The Influence of Training in Argumentation on Students' Individual Learning Outcomes

Julia Gressick, Sharon J. Derry
2013 International Conference on Computer Supported Collaborative Learning  
We conducted an in vivo experiment (Aleven & Koedinger, 2002) to investigate the impact of Adventures in Argument, a week-long online unit in argumentation, on subsequent science learning from an online  ...  The context of the study was HAL Online, an undergraduate course in The Learning Sciences that enrolled 44 students.  ...  Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.  ... 
dblp:conf/cscl/GressickD13 fatcat:m3f2kf3o3bgohdkgzhmtzey6ui

Simulation Models of the Influence of Learning Mode and Training Variance on Category Learning

Renée Elio, Kui Lin
1994 Cognitive Science  
This article uses simulation as an empirical method for identifying process models of strategy effects in a category-learning task.  ...  A general set of learning LEARNING MODE AND VARIANCE EFFECTS 203 LEARNING MODE AND VARIANCE EFFECTS 205  ...  More simply, the space of patterns is not controlled in any deliberate sense.  ... 
doi:10.1207/s15516709cog1802_1 fatcat:4oq5k7iwznhytm3lnxaipjkcxe

Modelling the influence of data structure on learning in neural networks: the hidden manifold model [article]

Sebastian Goldt, Marc Mézard, Florent Krzakala, Lenka Zdeborová
2020 arXiv   pre-print
These approaches are thus by construction blind to the correlation structure of real-world data sets and their impact on learning in neural networks.  ...  the learning rate or the dimension of the hidden manifold.  ...  We thus provide a rich test bed for exploring the influence of data structure on learning in neural networks.  ... 
arXiv:1909.11500v3 fatcat:drqmbio5xbh6bk3haulmmv6e7i

Some Experiments on the influence of Problem Hardness in Morphological Development based Learning of Neural Controllers [article]

M.Naya-Varela Universidade da Coruna
2020 arXiv   pre-print
To this end, we present the results of some initial experiments on the application of morpho-logical development to learning to walk in three cases, that of a quadruped, a hexapod and that of an octopod  ...  In fact, this is the period where the most important learning pro-cesses, those that will support learning as adults, will take place.  ...  Naya-Varela is very grateful for the support of the UDC-Inditex 2019 grant for international mobility.  ... 
arXiv:2003.05817v1 fatcat:dk7cjss5abbslnpntju6c6wmc4

The Influence of Biology Learning Using Concept Attainment Model on Student's Cognitive Learning Achievement

Yuliati Yuliati, Maridi Maridi, Mohammad Masykuri
2018 Journal of Education and Learning (EduLearn)  
The population of research was the 12 th Science graders of SMAN 1 Karas of Magetan Regency in school year of 2016/2017.  ...  as the second experiment class using Discovery Learning model.  ...  ACKNOWLEDGEMENTS The author would like to thank all of those participating in this study for their help, particularly Headmaster and students of SMA Negeri 1 Karas Magetan.  ... 
doi:10.11591/edulearn.v12i4.9296 fatcat:cvf5oxjvp5dy5kelbpmxmdsm64

The Influence of E-learning Behavior on Students' Learning Performance of Disaster Emergency Knowledge

Yixuan Zou, Laijin Shen, Shabnam Dadparvar
2022 International Journal of Emerging Technologies in Learning (iJET)  
Based on the theory of deconstruction program behavior and task technology fit model, four assumptions of e-learning behavior's influence on learning performance of students' disaster emergency knowledge  ...  E-learning has advantages of huge learning resources, enthusiastic learners, friendly interaction and flexible space-time, especially, the large-scale application of many new educational technologies makes  ...  Influence of E-learning Behavior on Students' Learning Performance of Disaster Emergency… http://www.i-jet.org Paper-The Influence of E-learning Behavior on Students' Learning Performance of Disaster  ... 
doi:10.3991/ijet.v17i01.28475 fatcat:owxzsm7r3zgdhg6ga7xx6puitu

The influence of task outcome on implicit motor learning

Hyosub E Kim, Darius E Parvin, Richard B Ivry
2019 eLife  
Here, we examine the influence of task outcome on implicit adaptation, using a reaching task in which adaptation is induced by feedback that is not contingent on actual performance.  ...  In this way, the cursor either hit or missed the target, with the former producing a marked attenuation of implicit motor learning.  ...  The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication. Additional information Competing interests  ... 
doi:10.7554/elife.39882 pmid:31033439 pmcid:PMC6488295 fatcat:fdmkxyeawzeutpah6f3kv6yyte

The influence of types of collaborative learning models jigsaw vs discovery learning model and learning discipline on learning results

2022 Pegem Journal of Education and Instruction  
The data in testing this hypothesis used Descriptive Statistical Analysis and ANOVA (analysis of variance) based on a 2X2 or two-way factorial design.  ...  Thus the jigsaw type collaborative learning model has advantages over the discovery learning model in achieving learning disciplines on learning outcomes message design course.  ...  Thus, learning outcomes will be influenced by one's competence and intellectual structure.  ... 
doi:10.47750/pegegog.12.02.17 fatcat:34wfziyefvdc3b7revo6z4hx2m

The Influence of Learning Style on Learning Attitude with Multimedia Teaching Materials

Fumei Weng, Hann-Jang Ho, Rong-Jou Yang, Chin-Hui Weng
2018 Eurasia Journal of Mathematics, Science and Technology Education  
The aim of this study is to discover the influence of multimedia materials of Taekwondo Aerobic on students' learning attitude with diverse learning styles.  ...  Not every student handles the material well and their learning styles also influence their learning achievement. Participants were students on grade seventh and eighth.  ...  Therefore, the learning attitude of students in the experimental group was better than in the controlled group.  ... 
doi:10.29333/ejmste/100389 fatcat:h277wdlh6rdarbo3srjjywrqiq

The influence of the openness of an e-learning situation on adult students' self-regulation

Annie Jézégou
2013 International Review of Research in Open and Distance Learning  
Their training took place mainly in e-learning.  ...  The goal of this research was to identify and explain the processes of influence existing between two specific dimensions: the degree of openness of the components of the e-learning situation and students  ...  The Influence of the Openness of an E-Learning Situation on Adult Students' Self-Regulation Jézégou Vol 14 | No 3 July/13  ... 
doi:10.19173/irrodl.v14i3.1450 fatcat:xxdi6voajnb4zip7er7vvh454q

Support of the collaborative inquiry learning process: influence of support on task and team regulation

Nadira Saab, Wouter van Joolingen, Bernadette van Hout-Wolters
2011 Metacognition and Learning  
In this study, we investigate how support of collaborative inquiry learning can influence the use of regulative activities of students.  ...  Students in the first condition did not receive any support at all (Control condition).  ...  This article focuses on the following questions: 1) What is the influence of support of collaborative inquiry learning on task and team regulation of students?  ... 
doi:10.1007/s11409-011-9068-6 fatcat:5ue6n2pxqvdjzh5vwg7yvv55hy
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