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Готові списки джерел за темами / Theory of applied learning of competencivism / Статті в журналах

Статті в журналах з теми "Theory of applied learning of competencivism"

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Автор: Grafiati

Опубліковано: 10 грудня 2022

Оновлено: 28 січня 2023

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1

Zhou, Ding-Xuan, Qiang Wu, and Yiming Ying. "Learning Theory." Abstract and Applied Analysis 2014 (2014): 1–2. http://dx.doi.org/10.1155/2014/138960.

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2

Costa, Roberto D., Gustavo F. Souza, Ricardo A. M. Valentim, and Thales B. Castro. "The theory of learning styles applied to distance learning." Cognitive Systems Research 64 (December 2020): 134–45. http://dx.doi.org/10.1016/j.cogsys.2020.08.004.

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3

van der Molen, Popko. "Reversal theory, learning and psychotherapy." British Journal of Guidance and Counselling 14, no. 2 (May 1, 1986): 125–39. http://dx.doi.org/10.1080/03069888600760141.

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4

van der Molen, Popko P. "Reversal Theory, Learning and Psychotherapy." British Journal of Guidance & Counselling 14, no. 2 (May 1986): 125–39. http://dx.doi.org/10.1080/03069888608253504.

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5

Jacobs, Robert A., and John K. Kruschke. "Bayesian learning theory applied to human cognition." Wiley Interdisciplinary Reviews: Cognitive Science 2, no. 1 (May 17, 2010): 8–21. http://dx.doi.org/10.1002/wcs.80.

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6

Lee, Jaemu, and Du-Gyu Kim. "Adaptive Learning System Applied Bruner’ EIS Theory." IERI Procedia 2 (2012): 794–801. http://dx.doi.org/10.1016/j.ieri.2012.06.173.

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7

RAKHLIN, ALEXANDER, SAYAN MUKHERJEE, and TOMASO POGGIO. "STABILITY RESULTS IN LEARNING THEORY." Analysis and Applications 03, no. 04 (October 2005): 397–417. http://dx.doi.org/10.1142/s0219530505000650.

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Анотація:

The problem of proving generalization bounds for the performance of learning algorithms can be formulated as a problem of bounding the bias and variance of estimators of the expected error. We show how various stability assumptions can be employed for this purpose. We provide a necessary and sufficient stability condition for bounding the bias and variance for the Empirical Risk Minimization algorithm, and various sufficient conditions for bounding bias and variance of estimators for general algorithms. We discuss settings in which it is possible to obtain exponential bounds, and we prove an extension of the bounded-difference inequality for "almost always" stable algorithms.

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8

Cornwell, John M., and Pamela A. Manfredo. "Kolb'S Learning Style Theory Revisited." Educational and Psychological Measurement 54, no. 2 (June 1994): 317–27. http://dx.doi.org/10.1177/0013164494054002006.

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9

Freitas, Elias J. R., Leonardo S. Prado, Marcos V. F. Silva, Vinícius A. Alvarenga, and Adrielle C. Santana. "Active Learning Strategy Applied to Control Theory Teaching." International Journal of Advanced Engineering Research and Science 9, no. 9 (2022): 001–8. http://dx.doi.org/10.22161/ijaers.99.1.

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10

Knouse, Stephen B. "Brand loyalty and sequential learning theory." Psychology and Marketing 3, no. 2 (1986): 87–98. http://dx.doi.org/10.1002/mar.4220030205.

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11

Smale, Steve, and Ding-Xuan Zhou. "Shannon sampling II: Connections to learning theory." Applied and Computational Harmonic Analysis 19, no. 3 (November 2005): 285–302. http://dx.doi.org/10.1016/j.acha.2005.03.001.

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12

Kim, Mi Hey. "Effects of Cooperative Learning Applied to Nursing Theory Subjects." Korean Health & Fundamental Medical Science Society 14, no. 2 (December 31, 2021): 47–53. http://dx.doi.org/10.37152/kmhs.2021.14.2.47.

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13

Braess, Dietrich, and Thomas Sauer. "Bernstein polynomials and learning theory." Journal of Approximation Theory 128, no. 2 (June 2004): 187–206. http://dx.doi.org/10.1016/j.jat.2004.04.010.

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14

Morett, Laura M., Benjamin A. Clegg, Lisa D. Blalock, and Heather M. Mong. "Applying multimedia learning theory to map learning and driving navigation." Transportation Research Part F: Traffic Psychology and Behaviour 12, no. 1 (January 2009): 40–49. http://dx.doi.org/10.1016/j.trf.2008.07.001.

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15

Sheng, Bao-Huai, and Jian-Li Wang. "On the K-functional in learning theory." Analysis and Applications 18, no. 03 (November 12, 2019): 423–46. http://dx.doi.org/10.1142/s0219530519500192.

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Анотація:

[Formula: see text]-functionals are used in learning theory literature to study approximation errors in kernel-based regularization schemes. In this paper, we study the approximation error and [Formula: see text]-functionals in [Formula: see text] spaces with [Formula: see text]. To this end, we give a new viewpoint for a reproducing kernel Hilbert space (RKHS) from a fractional derivative and treat powers of the induced integral operator as fractional derivatives of various orders. Then a generalized translation operator is defined by Fourier multipliers, with which a generalized modulus of smoothness is defined. Some general strong equivalent relations between the moduli of smoothness and the [Formula: see text]-functionals are established. As applications, some strong equivalent relations between these two families of quantities on the unit sphere and the unit ball are provided explicitly.

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16

Kluge, Annette, and Jan Schilling. "Organizational learning and learning organizations: Theory and empirical findings." Psychologist-Manager Journal 6, no. 1 (2003): 31–50. http://dx.doi.org/10.1037/h0095917.

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17

Forrester, John P., and Charles J. Spindler. "BUDGETING THEORY THROUGH “RELATIONAL LEARNING”." International Journal Organization Theory and Behavior 4, no. 1-2 (February 28, 2001): 107–31. http://dx.doi.org/10.1081/otb-100103039.

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18

Forrester, John P., and Charles J. Spindler. "Budgeting theory through “relational learning”." International Journal of Organization Theory & Behavior 4, no. 1/2 (March 2001): 107–31. http://dx.doi.org/10.1108/ijotb-04-01-02-2001-b008.

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19

Scott, Carol Jack. "Applied adult learning theory: Broadening traditional CME programs with self-guided, computer-assisted learning." Journal of Continuing Education in the Health Professions 14, no. 2 (1994): 91–99. http://dx.doi.org/10.1002/chp.4750140205.

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20

Iwaniec, Dorota, Roger McAuley, and Karola Dillenburger. "Multi-disciplinary diploma applied social-learning theory in child care." Child Care in Practice 3, no. 1 (September 1996): 30–37. http://dx.doi.org/10.1080/13575279608410455.

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21

Nieto, J. "The (kinetic) theory of active particles applied to learning dynamics." Physics of Life Reviews 16 (March 2016): 152–53. http://dx.doi.org/10.1016/j.plrev.2016.01.017.

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22

Hamade, Ramsey F., Hassan A. Artail, and Mohamad Y. Jaber. "Learning Theory as Applied to Mechanical CAD Training of Novices." International Journal of Human-Computer Interaction 19, no. 3 (November 2005): 305–22. http://dx.doi.org/10.1207/s15327590ijhc1903_2.

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23

FIORI, SIMONE. "RELATIVE UNCERTAINTY LEARNING THEORY: AN ESSAY." International Journal of Neural Systems 14, no. 05 (October 2004): 293–311. http://dx.doi.org/10.1142/s0129065704002042.

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Анотація:

The aim of this manuscript is to present a detailed analysis of the algebraic and geometric properties of relative uncertainty theory (RUT) applied to neural networks learning. Through the algebraic analysis of the original learning criterion, it is shown that RUT gives rise to principal-subspace-analysis-type learning equations. Through an algebraic-geometric analysis, the behavior of such matrix-type learning equations is illustrated, with particular emphasis to the existence of certain invariant manifolds.

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24

Goldman, Sally. "Special Issue: Learning Theory 2003." Journal of Computer and System Sciences 71, no. 3 (October 2005): 249. http://dx.doi.org/10.1016/j.jcss.2004.10.017.

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25

Dasgupta, Sanjoy. "Special issue on learning theory." Journal of Computer and System Sciences 74, no. 1 (February 2008): 1. http://dx.doi.org/10.1016/j.jcss.2007.04.018.

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26

Hellerstein, Lisa, and Hans U. Simon. "Special Issue: Learning Theory 2006." Journal of Computer and System Sciences 75, no. 1 (January 2009): 1. http://dx.doi.org/10.1016/j.jcss.2008.07.002.

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27

Lange, Fredrik, Sara Rosengren, Jonas Colliander, Mikael Hernant, and Karina T. Liljedal. "Bridging Theory and Practice in an Applied Retail Track." Journal of Marketing Education 40, no. 1 (February 4, 2018): 6–16. http://dx.doi.org/10.1177/0273475318755837.

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Анотація:

In this article, we present an educational approach that bridges theory and practice: an applied retail track. The track has been co-created by faculty and 10 partnering retail companies and runs in parallel with traditional courses during a 3-year bachelor’s degree program in retail management. The underlying pedagogical concept is to move retail education from simple dissemination of knowledge toward the production of learning by way of experiential, situated, and skill-based learning. Overall, we believe that this learning approach has helped to create a win-win-win situation for students, retailers, and faculty. Students gain unique insights from retail practice to complement their topically oriented course-based learning, thus enhancing their attractiveness to employers after graduation. Retailers gain in-depth knowledge about the competencies of young prospective employees, and faculty and retailers jointly benefit from exchanging ideas about contemporary challenges in retailing. This article describes the program’s main features and successes and offers recommendations for others seeking to implement all or some of its components.

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28

Lu, Fangyan, and Hongwei Sun. "Positive definite dot product kernels in learning theory." Advances in Computational Mathematics 22, no. 2 (February 2005): 181–98. http://dx.doi.org/10.1007/s10444-004-3140-6.

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29

DeCaporale-Ryan, Lauren N., Rita Dadiz, and Sarah E. Peyre. "Simulation-based learning: From theory to practice." Families, Systems, & Health 34, no. 2 (June 2016): 159–62. http://dx.doi.org/10.1037/fsh0000203.

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30

Furaida, Laily. "Implementation of Cybernetic Learning Theory on Scientific Philosophy Learning." Epistema 2, no. 1 (June 4, 2021): 23–32. http://dx.doi.org/10.21831/ep.v2i1.40383.

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Анотація:

The topic is focused on cybernetic learning theory and its implementation to scientific philoshophy learning. Theoretical approach and scientific learning can be connected each other with the same purposes on learning process. Cybernetic learning theory attent to information processing substance and organize its connection to be come an information system which is creating a new idea or a new invention of science. Due to this, the main purpose of scientific philosophy learning is a critical thinking process which construct a new idea that is engaging a kognitive aspect.This research is a literature review. Literature review is a research which compare previous research then connected with a topic that be come a main review (Efron & Ravid, 2019). The research design is narrative review. Narrative review well known as traditional literature review which is a literature review with an analysis as a whole in order to construct a theory and context of a research main focus (Stratton, 2019).The implementation of cybernetic learning theory are suitable for scientific philosophy learning for the same goal in order to find out and proceed new information. Information processing theory which is include kognitive aspect has an important role of cybernetic approach. Cybernetic learning theory can be applied on every learning method which is connecting kognitive aspect in its process.

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31

Sheng, Baohuai, and Haizhang Zhang. "Performance analysis of the LapRSSLG algorithm in learning theory." Analysis and Applications 18, no. 01 (December 16, 2019): 79–108. http://dx.doi.org/10.1142/s0219530519410033.

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It is known that one aim of semi-supervised learning is to improve the prediction performance using a few labeled data with a large set of unlabeled data. Recently, a Laplacian regularized semi-supervised learning gradient (LapRSSLG) algorithm associated with data adjacency graph edge weights is proposed in the literature. The algorithm receives success in applications, but there is no theory on the performance analysis. In this paper, an explicit learning rate estimate for the algorithm is provided, which shows that the convergence is indeed controlled by the unlabeled data.

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32

Falmagne, Keam-Claude. "A latent trait theory via a stochastic learning theory for a knowledge space." Psychometrika 54, no. 2 (June 1989): 283–303. http://dx.doi.org/10.1007/bf02294521.

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33

Sun, Hongwei, and Qiang Wu. "A note on application of integral operator in learning theory." Applied and Computational Harmonic Analysis 26, no. 3 (May 2009): 416–21. http://dx.doi.org/10.1016/j.acha.2008.10.002.

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34

Keyes, Laura M., and Abraham David Benavides. "Chaos theory, uncertainty, and organizational learning." International Journal of Organization Theory & Behavior 21, no. 4 (November 12, 2018): 226–41. http://dx.doi.org/10.1108/ijotb-04-2018-0050.

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Purpose The purpose of this paper is to juxtapose chaos theory with organizational learning theory to examine whether public organizations co-evolve into a new order or rather institutionalize newly gained knowledge in times of a highly complex public health crisis. Design/methodology/approach The research design utilizes the results from a survey administered to 200 emergency management and public health officials in the Dallas–Fort Worth metroplex. Findings The findings of this paper suggest that public entities were more likely to represent organizational learning through the coordination of professionals, access to quality information, and participation in daily communication. Leadership was associated with the dissemination of knowledge through the system rather than the development of new standard operating procedures (as suggested by chaos theory and co-evolution). Research limitations/implications There are limitations to this study given the purposive sample of emergency management and public health officials employed in the Dallas–Fort Worth metroplex. Practical implications The authors find that public organizations that learn how to respond to unprecedented events through reliance on structure, leadership, and culture connect decision makers to credible information resulting in organizational learning. Social implications As a result, public administrators need to focus and rely on their organization’s capacity to receive and retain information in a crisis. Originality/value This research contributes to our understanding of organizational learning in public organizations under highly complex public health situations finding decisions makers rely on both organizational structure and culture to support the flow of credible information.

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35

Eteläpelto, Anneli. "Learning Processes in the Control Theory." Applied Psychology 43, no. 3 (July 1994): 370–76. http://dx.doi.org/10.1111/j.1464-0597.1994.tb00830.x.

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36

Simon, Martin A., Melike Kara, Nicora Placa, and Arnon Avitzur. "Towards an integrated theory of mathematics conceptual learning and instructional design: The Learning Through Activity theoretical framework." Journal of Mathematical Behavior 52 (December 2018): 95–112. http://dx.doi.org/10.1016/j.jmathb.2018.04.002.

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37

Alt, Dorit. "Students’ Perceived Constructivist Learning Environment." European Journal of Psychological Assessment 34, no. 6 (November 2018): 432–43. http://dx.doi.org/10.1027/1015-5759/a000358.

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Abstract. Theoretical classifications suggest three key tenets of the constructivist learning environment: constructivist task, teacher-student interaction, and social activity. This study assessed two scales, measuring the perceptions of high school and college students of their constructivist learning environment. Facet theory (FT) approach with smallest space analysis (SSA) as well as confirmatory factor analysis (CFA) were used to confirm the structure of the constructivist learning theory and to test the structural validity of scores on two scales. In the first study, data were gathered by using the Constructivist Learning Environment Survey (CLES). In this study, compared with the CFA result, the SSA gave additional information showing the existence of the three theoretical key tenets which were absent from the factor analysis. This facet was derived from the constructivist learning theory, framed in the mapping sentence, purposely designed as part of the FT research strategy. In the second study, students’ perceptions of the occurrence of constructivist practices in higher education learning environments were assessed. The comparison between SSA and CFA showed that the CFA was limited to capture merely one facet at a time and failed to illustrate the correspondence between the content facets of the mapping sentence.

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38

Wang, Hong-Yan, Dao-Hong Xiang, and Ding-Xuan Zhou. "Moving least-square method in learning theory." Journal of Approximation Theory 162, no. 3 (March 2010): 599–614. http://dx.doi.org/10.1016/j.jat.2009.12.002.

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39

Lai, Florence, Frédéric Magoulès, and Fred Lherminier. "Vapnik's learning theory applied to energy consumption forecasts in residential buildings." International Journal of Computer Mathematics 85, no. 10 (October 2008): 1563–88. http://dx.doi.org/10.1080/00207160802033582.

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40

Haehl, Victoria, Vassilios Vardaxis, and Beverly Ulrich. "Learning to cruise: Bernstein's theory applied to skill acquisition during infancy." Human Movement Science 19, no. 5 (November 2000): 685–715. http://dx.doi.org/10.1016/s0167-9457(00)00034-8.

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41

GILBERT, DAVID. "INTEGRATING THEORY AND PRACTICE FOR STUDENT ENTREPRENEURS: AN APPLIED LEARNING MODEL." Journal of Enterprising Culture 18, no. 01 (March 2010): 83–106. http://dx.doi.org/10.1142/s0218495810000495.

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Анотація:

This paper reports on an innovative pilot project embedded in a capstone unit of Australia's leading undergraduate degree program in Entrepreneurship. The project was developed as part of an industry linkage pilot agreement between the Entrepreneurship program and one of the 'Big Four' consultancy companies, Deloitte Touche Tohmatsu. A pedagogically innovative model of applied learning is proposed that enabled Higher Education students enrolled in a Bachelor of Business (Entrepreneurship) degree to apply in a dynamic (and sometimes chaotic) environment skill and capabilities they already possessed (as opposed to work-based learning about a particular job). Results presented in this paper indicate that educating young entrepreneurs in a Higher Educational setting needs to be like the practice itself; creative, risky, exciting and above all highly satisfying.

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42

FIORI, SIMONE, and ROBERTO ROSSI. "STIEFEL-MANIFOLD LEARNING BY IMPROVED RIGID-BODY THEORY APPLIED TO ICA." International Journal of Neural Systems 13, no. 05 (October 2003): 273–90. http://dx.doi.org/10.1142/s0129065703001625.

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Анотація:

In previous contributions we presented a new class of algorithms for orthonormal learning of a linear neural network with p inputs and m outputs, based on the equations describing the dynamics of a massive rigid frame in a submanifold of ℛp. While exhibiting interesting features, such as intrinsic numerical stability, strongly binding to the orthonormal submanifolds, and good controllability of the learning dynamics, tested on principal/independent component analysis, the proposed algorithms were not completely satisfactory from a computational-complexity point of view. The main drawback was the need to repeatedly evaluate a matrix exponential map. With the aim to lessen the computational efforts pertaining to these algorithms, we propose here an improvement based on the closed-form Rodriguez formula for the exponential map. Such formula is available in the p=3 and m=3 case, which is discussed with details here. In particular, experimental results on independent component analysis (ICA), carried out with both synthetic and real-world data, help confirming the computational gain due to the proposed improvement.

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43

Cheung, Y. L. "Learning number theory with a computer algebra system." International Journal of Mathematical Education in Science and Technology 27, no. 3 (May 1996): 379–85. http://dx.doi.org/10.1080/0020739960270308.

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44

Boucheron, St�phane, and Dani�le Gardy. "An urn model from learning theory." Random Structures and Algorithms 10, no. 1-2 (January 1997): 43–67. http://dx.doi.org/10.1002/(sici)1098-2418(199701/03)10:1/2<43::aid-rsa3>3.0.co;2-x.

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45

Lordo, Robert A. "Learning from Data: Concepts, Theory, and Methods." Technometrics 43, no. 1 (February 2001): 105–6. http://dx.doi.org/10.1198/tech.2001.s558.

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46

Guo, Zheng-Chu, Shao-Bo Lin, and Ding-Xuan Zhou. "Learning theory of distributed spectral algorithms." Inverse Problems 33, no. 7 (June 21, 2017): 074009. http://dx.doi.org/10.1088/1361-6420/aa72b2.

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47

Thorwart, Anna, and Harald Lachnit. "Inhibited Elements Model — Implementation of an associative learning theory." Journal of Mathematical Psychology 94 (February 2020): 102310. http://dx.doi.org/10.1016/j.jmp.2019.102310.

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48

Zhou, Ding-Xuan. "Derivative reproducing properties for kernel methods in learning theory." Journal of Computational and Applied Mathematics 220, no. 1-2 (October 2008): 456–63. http://dx.doi.org/10.1016/j.cam.2007.08.023.

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49

Sherron, Todd, Catherine A. Cherrstrom, Carrie Boden, and Lindsey Wilson. "Block Credit Prior Learning Assessment Theory to Practice." Measurement: Interdisciplinary Research and Perspectives 19, no. 1 (January 2, 2021): 1–14. http://dx.doi.org/10.1080/15366367.2020.1832812.

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50

Sloan, Robert. "Special issue on computational learning theory." Journal of Computer and System Sciences 70, no. 4 (June 2005): 433–34. http://dx.doi.org/10.1016/j.jcss.2004.10.011.

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