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Journal articles on the topic 'Flexible Learning'

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Published: 4 June 2021
Last updated: 21 February 2023

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1

Evans, David W., and Penelope J. Hood. "Flexible Learning." Management in Education 11, no. 4 (September 1997): 24–25. http://dx.doi.org/10.1177/089202069701100412.

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2

Irvine, Jan, and Amanda Cossham. "Flexible learning." Library Review 60, no. 8 (September 6, 2011): 712–22. http://dx.doi.org/10.1108/00242531111166728.

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3

Bhoite, Dr Sudhakar D. "E-Learning: the Technology Enhanced Learning (TEL) Makes Learning Easier And Flexible." International Journal of Scientific Research 2, no. 9 (June 1, 2012): 84–85. http://dx.doi.org/10.15373/22778179/sep2013/29.

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4

Hill, Janette R. "Flexible Learning Environments: Leveraging the Affordances of Flexible Delivery and Flexible Learning." Innovative Higher Education 31, no. 3 (September 1, 2006): 187–97. http://dx.doi.org/10.1007/s10755-006-9016-6.

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5

Talosa, Arlene D., Billy S. Javier, and Estela L. Dirain. "flexible-learning journey." Linguistics and Culture Review 5, S3 (October 23, 2021): 422–34. http://dx.doi.org/10.21744/lingcure.v5ns3.1590.

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Philippine higher education has been driven by the urgency of alternative learning modalities from traditional to flexible teaching and learning. Much research has already been embarked on flexible learning. New to the platform, this study purports to document and describe the learning opportunities and influencing factors on the self-efficacy of students in a flexible learning set-up. Using In-depth individual interviews as its method, the qualitative study was administered to higher education students who consented to take part in the study. Findings revealed that self-regulated learning and digital or technological self-efficacy are the two themes found as a learning opportunity with the current learning modality. Personal, Technological, Communication, Home Environment, and Teacher-related are the overarching themes that emerged as influencing factors. The findings of this study have generated several implications for teaching practice, technology experts, and other stakeholders that must be considered very seriously as they represent the opinion of the users of flexible learning.
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6

Richmond, Terry. "Making Learning Flexible." British Journal of Special Education 20, no. 1 (May 31, 2007): 20–23. http://dx.doi.org/10.1111/j.1467-8578.1993.tb00023.x.

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7

Nicoll, Katherine. "‘Flexible learning'—unsettling practices." Studies in Continuing Education 19, no. 2 (January 1997): 100–111. http://dx.doi.org/10.1080/0158037970190202.

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8

Lewis, R. "Flexible and Distance Learning." Journal of Computer Assisted Learning 9, no. 2 (June 1993): 127–28. http://dx.doi.org/10.1111/j.1365-2729.1993.tb00166.x.

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9

Harry, Keith. "Flexible and distance learning." Computers & Education 22, no. 4 (May 1994): 364–65. http://dx.doi.org/10.1016/0360-1315(94)90059-0.

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10

Murphy, David, Kym Fraser, and Len Webster. "'Wrestling with blancmange': A flexible flexible learning workshop." International Journal for Academic Development 5, no. 1 (January 2000): 54–60. http://dx.doi.org/10.1080/136014400410105.

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11

Martín-SanJosé, Juan-Fernando, M. Carmen Juan, José-A. Gil-Gómez, and Noemí Rando. "Flexible learning itinerary vs. linear learning itinerary." Science of Computer Programming 88 (August 2014): 3–21. http://dx.doi.org/10.1016/j.scico.2013.12.009.

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12

Moodie, Erica E. M., Nema Dean, and Yue Ru Sun. "Q-Learning: Flexible Learning About Useful Utilities." Statistics in Biosciences 6, no. 2 (September 12, 2013): 223–43. http://dx.doi.org/10.1007/s12561-013-9103-z.

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13

Bridgland, Angela, and Patrick Blanchard. "Flexible Delivery/Flexible Learning…Does it Make a Difference?" Australian Academic & Research Libraries 32, no. 3 (January 2001): 177–91. http://dx.doi.org/10.1080/00048623.2001.10755158.

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14

Saul, Rosemary, Winnie Wade, Keith Hodgkinson, Alison Smith, and John Arfield. "Flexible Learning in Higher Education." British Journal of Educational Studies 44, no. 1 (March 1996): 129. http://dx.doi.org/10.2307/3121722.

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15

Cook, Kerry. "Your flexible friend: e-learning." Nursing Standard 22, no. 39 (June 4, 2008): 62–63. http://dx.doi.org/10.7748/ns.22.39.62.s48.

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16

Edwards, Richard, and Julia Clarke. "Flexible Learning, Spatiality and Identity." Studies in Continuing Education 24, no. 2 (November 2002): 153–65. http://dx.doi.org/10.1080/0158037022000020965.

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17

Kirkpatrick, Denise. "Staff development for flexible learning." International Journal for Academic Development 6, no. 2 (January 2001): 168–76. http://dx.doi.org/10.1080/713769268.

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18

Baggaley, Jon. "Flexible learning: a Luddite view." Distance Education 32, no. 3 (November 2011): 457–62. http://dx.doi.org/10.1080/01587919.2011.610294.

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19

Smith, Peter J. "Workplace Learning and Flexible Delivery." Review of Educational Research 73, no. 1 (March 2003): 53–88. http://dx.doi.org/10.3102/00346543073001053.

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20

Petrie, Moira. "Flexible Learning and Mathematics Support." MSOR Connections 11, no. 1 (March 2011): 46–47. http://dx.doi.org/10.11120/msor.2011.11010046.

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21

Brooks, Christopher, and Gord McCalla. "Towards flexible learning object metadata." International Journal of Continuing Engineering Education and Life-Long Learning 16, no. 1/2 (2006): 50. http://dx.doi.org/10.1504/ijceell.2006.008917.

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22

McCain, Roger A. "Flexible Learning of Optimal Strategies." IFAC Proceedings Volumes 34, no. 20 (September 2001): 413–18. http://dx.doi.org/10.1016/s1474-6670(17)33100-2.

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23

Sutton, Alan. "NTETs, GNVQs and flexible learning." Curriculum Journal 5, no. 3 (September 1994): 337–53. http://dx.doi.org/10.1080/0958517940050306.

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24

O'Hagan, Chris. "Custom Videos for Flexible Learning." Innovations in Education and Training International 32, no. 2 (May 1995): 131–38. http://dx.doi.org/10.1080/1355800950320207.

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25

Riele, Kitty Te, Vicky Plows, and Dorothy Bottrell. "Interest, learning, and belonging in flexible learning programmes." International Journal on School Disaffection 12, no. 1 (May 23, 2016): 45–63. http://dx.doi.org/10.18546/ijsd.12.1.03.

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26

Siemens, George. "Learning analytics and open, flexible, and distance learning." Distance Education 40, no. 3 (July 3, 2019): 414–18. http://dx.doi.org/10.1080/01587919.2019.1656153.

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27

Parnell, Rosie, and Lisa Procter. "Flexibility and placemaking for autonomy in learning." Educational and Child Psychology 28, no. 1 (2011): 77–88. http://dx.doi.org/10.53841/bpsecp.2011.28.1.77.

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Flexibility is a key aspiration of contemporary government guidance on school design. Used liberally, the term provides a convenient site for the meeting of educational approach (think flexible, personalised learning, timetabling, groupings) and spatial design (non-bounded, open space, moveable elements, independent structure and services). However, this meeting seems to pose a challenge. As Building Bulletin 95 puts it: ‘…the most flexibly designed spaces can only work if building users have a flexible attitude.’ Framing flexibility in the discourse of autonomy, this paper contends that it can be understood as a ‘tool’ to enable children to experience authorship of their own learning. The paper draws on participatory action research with primary and secondary schools in England in which the built environment and placemaking were explored as a means to support learning. Through examples, it is argued that once children are enabled to experience their learning environment as ‘flexible’, by changing it themselves, they are better able to self-direct their learning. Findings show that flexible learning space is encouraged when children and teachers experience together how their environment can support their learning needs. Once established, it is an environment that is constantly changing according to the needs of individuals and groups. The paper concludes that flexibility, at the congruence of spatial design and learning, can only be attained once children feel trusted to shape their environment within an enabling school culture.
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28

Šimonová, Ivana, Petra Poulová, and Kateřina Kostolányová. "Flexible Hybrid Learning: Comparison of Two Approaches and Learning Results." International Journal of Information and Communication Technologies in Education 5, no. 2 (October 1, 2016): 29–50. http://dx.doi.org/10.1515/ijicte-2016-0007.

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Abstract Hybrid learning has become a widely exploited approach within the ICT-enhanced instruction. Making it flexible to students’ individual needs and preferences was the problem solved in various ways at Czech higher education institutions. In the paper two approaches to adapting the learning process to learner’s individual preferences are described comparing two different models of flexible hybrid learning. These models were exploited in educational practice and pedagogical experiments comparing learners’ knowledge in flexible and non-flexible learning were conducted. The results did not proved clearly visible differences in the two approaches, as neither numerous world-recognized researches did. Despite this, authors are persuaded that research activities in this field should go on, paying deeper attention to learners’ personal characteristics and other activities within the learning process.
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29

Agudelo, Olga Lucía, and Jesus Salinas Ibáñez. "Flexible Learning Itineraries Based on Conceptual Maps." Journal of New Approaches in Educational Research 4, no. 2 (July 15, 2015): 70–76. http://dx.doi.org/10.7821/naer.2015.7.130.

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30

Zhou, Qiang, and Qi Zhao. "Flexible Clustered Multi-Task Learning by Learning Representative Tasks." IEEE Transactions on Pattern Analysis and Machine Intelligence 38, no. 2 (February 1, 2016): 266–78. http://dx.doi.org/10.1109/tpami.2015.2452911.

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31

Zhang, Jingjing, Daniel Burgos, and Shane Dawson. "Advancing open, flexible and distance learning through learning analytics." Distance Education 40, no. 3 (July 3, 2019): 303–8. http://dx.doi.org/10.1080/01587919.2019.1656151.

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32

Charypar, David, and Kai Nagel. "Q-Learning for Flexible Learning of Daily Activity Plans." Transportation Research Record: Journal of the Transportation Research Board 1935, no. 1 (January 2005): 163–69. http://dx.doi.org/10.1177/0361198105193500119.

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Q-learning is a method from artificial intelligence to solve the reinforcement learning problem (RLP), defined as follows. An agent is faced with a set of states, S. For each state s there is a set of actions, A( s), that the agent can take and that takes the agent (deterministically or stochastically) to another state. For each state the agent receives a (possibly stochastic) reward. The task is to select actions such that the reward is maximized. Activity generation is for demand generation in the context of transportation simulation. For each member of a synthetic population, a daily activity plan stating a sequence of activities (e.g., home-work-shop-home), including locations and times, needs to be found. Activities at different locations generate demand for transportation. Activity generation can be modeled as an RLP with the states given by the triple (type of activity, starting time of activity, time already spent at activity). The possible actions are either to stay at a given activity or to move to another activity. Rewards are given as “utility per time slice,” which corresponds to a coarse version of marginal utility. Q-learning has the property that, by repeating similar experiences over and over again, the agent looks forward in time; that is, the agent can also go on paths through state space in which high rewards are given only at the end. This paper presents computational results with such an algorithm for daily activity planning.
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33

Forer, Pip, Margaret Goldstone, and Felix B. Tan. "Implementing Flexible Learning in GIS Education." Journal of Global Information Management 6, no. 1 (January 1998): 33–40. http://dx.doi.org/10.4018/jgim.1998010104.

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34

Burgess, Marion, and Matthew Stead. "Flexible learning program for acoustic consultants." Journal of the Acoustical Society of America 151, no. 3 (March 2022): 1672–75. http://dx.doi.org/10.1121/10.0009782.

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There is a demand around the world for professional staff to join acoustic consulting companies, and in Australasia this demand is increasing. The extent of acoustics covered in undergraduate programs varies greatly, and there is usually the need to provide additional learning opportunities for new employees. While larger companies may provide training in-house, there are times when they are not in a position to release the senior members to provide such training. By contrast, smaller companies generally do not have this option. Short courses or similar programs can provide the necessary upskilling of new staff, but such courses may not be offered at times or locations that suit the company recruitment program. To overcome the demonstrated need for supplementary education programs in acoustics, the Australasian Association for Acoustical Consultants worked with the University of New South Wales to develop a fully flexible distance learning program, loosely based on the United Kingdom Institute of Acoustics Diploma program. The development, implementation, and experiences from over a decade of offering this program are discussed in this paper.
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35

Osborn, Jon. "Lifelong Learning: Flexible Delivery and CPD." Australian Surveyor 45, no. 2 (December 2000): 16–22. http://dx.doi.org/10.1080/00050354.2000.10558811.

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36

Latchem, Colin, and Donald E. Hanna. "Leadership for Open and Flexible Learning." Open Learning: The Journal of Open, Distance and e-Learning 17, no. 3 (September 2002): 203–15. http://dx.doi.org/10.1080/0268051022000048219.

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37

Collis, Betty, and Jef Moonen. "Flexible Learning in a Digital World." Open Learning: The Journal of Open, Distance and e-Learning 17, no. 3 (September 2002): 217–30. http://dx.doi.org/10.1080/0268051022000048228.

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38

Evans, Michael. "Flexible learning and modern language teaching." Language Learning Journal 8, no. 1 (September 1993): 17–21. http://dx.doi.org/10.1080/09571739385200301.

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39

Moss, Dennis. "School pupils' reactions to flexible learning." British Journal of Educational Technology 23, no. 1 (January 1992): 28–38. http://dx.doi.org/10.1111/j.1467-8535.1992.tb00307.x.

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40

Mirhoseini, Azalia, Ebrahim M. Songhori, Bita Darvish Rouhani, and Farinaz Koushanfar. "Flexible Transformations For Learning Big Data." ACM SIGMETRICS Performance Evaluation Review 43, no. 1 (June 24, 2015): 453–54. http://dx.doi.org/10.1145/2796314.2745889.

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41

Guest, Ross. "Will Flexible Learning Raise Student Achievement?" Education Economics 13, no. 3 (September 2005): 287–97. http://dx.doi.org/10.1080/09645290500073761.

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42

Challis, Neil. "Flexible learning in mathematics: the future." MSOR Connections, no. 4 (November 2000): 9–12. http://dx.doi.org/10.11120/msor.2000.00040009.

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43

Fratus, Greig, and Pam Bishop. "Electronic Mathematics Resources and Flexible Learning." MSOR Connections, no. 4 (November 2000): 13–15. http://dx.doi.org/10.11120/msor.2000.00040013.

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44

Nikolova, Iliana, and Betty Collis. "Flexible learning and design of instruction." British Journal of Educational Technology 29, no. 1 (January 1998): 59–72. http://dx.doi.org/10.1111/1467-8535.00046.

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45

Bell, Jane. "E‐learning: your flexible development friend?" Development and Learning in Organizations: An International Journal 21, no. 6 (October 9, 2007): 7–9. http://dx.doi.org/10.1108/14777280710828558.

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46

Taylor, Jordan A., and Richard B. Ivry. "Flexible Cognitive Strategies during Motor Learning." PLoS Computational Biology 7, no. 3 (March 3, 2011): e1001096. http://dx.doi.org/10.1371/journal.pcbi.1001096.

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47

Lambourne, R. J. A., and M. H. Tinker. "The Flexible Learning Approach to Physics:FLAP." Physics Education 28, no. 5 (September 1993): 311–16. http://dx.doi.org/10.1088/0031-9120/28/5/012.

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48

Willmot, Mike, and Monica McLean. "Evaluating Flexible Learning: A Case Study." Journal of Further and Higher Education 18, no. 3 (September 1994): 99–108. http://dx.doi.org/10.1080/0309877940180309.

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49

Abdelghani, M. N., T. P. Lillicrap, and D. B. Tweed. "Sensitivity Derivatives for Flexible Sensorimotor Learning." Neural Computation 20, no. 8 (August 2008): 2085–111. http://dx.doi.org/10.1162/neco.2008.04-07-507.

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To learn effectively, an adaptive controller needs to know its sensitivity derivatives—the variables that quantify how system performance depends on the commands from the controller. In the case of biological sensorimotor control, no one has explained how those derivatives themselves might be learned, and some authors suggest they are not learned at all but are known innately. Here we show that this knowledge cannot be solely innate, given the adaptive flexibility of neural systems. And we show how it could be learned using forms of information transport that are available in the brain. The mechanism, which we call implicit supervision, helps explain the flexibility and speed of sensorimotor learning and our ability to cope with high-dimensional work spaces and tools.
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50

Deed, Craig, Damian Blake, Joanne Henriksen, Amanda Mooney, Vaughan Prain, Russell Tytler, Tina Zitzlaff, et al. "Teacher adaptation to flexible learning environments." Learning Environments Research 23, no. 2 (November 15, 2019): 153–65. http://dx.doi.org/10.1007/s10984-019-09302-0.

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