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Journal articles on the topic 'Self-paced'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

Yu, Tingzhao, Chaoxu Guo, Lingfeng Wang, Shiming Xiang, and Chunhong Pan. "Self-Paced AutoEncoder." IEEE Signal Processing Letters 25, no. 7 (July 2018): 1054–58. http://dx.doi.org/10.1109/lsp.2018.2843295.

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2

Stowers, Michael P., and Martin Tessmer. "Self-paced instruction." New Directions for Higher Education 1986, no. 56 (1986): 17–26. http://dx.doi.org/10.1002/he.36919865604.

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3

Wessel, Karl, Thomas Zeffiro, Camilo Toro, and Mark Hallett. "Self-Paced Versus Metronome-Paced 7 Finger Movements." Journal of Neuroimaging 7, no. 3 (July 1997): 145–51. http://dx.doi.org/10.1111/jon199773145.

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4

Edwards, Clayton M. "Self-Paced Mathematical Instruction." Mathematics Teaching in the Middle School 19, no. 4 (November 2013): 230–36. http://dx.doi.org/10.5951/mathteacmiddscho.19.4.0230.

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5

MENG, Deyu, Zongben XU, and Jun SHU. "Meta self-paced learning." SCIENTIA SINICA Informationis 50, no. 6 (June 1, 2020): 781–93. http://dx.doi.org/10.1360/ssi-2020-0005.

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6

Holroyd, Tom, Matt Nielsen, S. Miyauchi, and T. Yanagida. "2P219MEG during self-paced and externally paced rhythmic tapping." Seibutsu Butsuri 41, supplement (2001): S150. http://dx.doi.org/10.2142/biophys.41.s150_3.

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7

Schlegel, Betina, and Margarita Beneke. "A Study of Self-Paced and Machine-Paced Inspection." Proceedings of the Human Factors Society Annual Meeting 30, no. 5 (September 1986): 471–75. http://dx.doi.org/10.1177/154193128603000514.

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A study was conducted to investigate the performance of inspectors under different conditions using computer generated visual test items. The purpose of the study was to compare performance for self-paced vs. machine-paced inspection tasks. The factors considered were searching for a single type of flaw vs. three types of flaws, the viewing time for machine-paced inspection, and the type of instruction for self-paced inspection. The results showed that performance was better when subjects searched for only one type of flaw. Performance improved with increased viewing time, but was not affected by the type of instruction. There was no difference between self-paced and machine-paced inspection provided the viewing time was sufficient. Overall, performance in self-paced inspection was better.

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8

Ren, Yazhou, Xiaofan Que, Dezhong Yao, and Zenglin Xu. "Self-paced multi-task clustering." Neurocomputing 350 (July 2019): 212–20. http://dx.doi.org/10.1016/j.neucom.2019.03.062.

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9

Klenk, Virginia. "Self-Paced Logic Without Computers." Teaching Philosophy 9, no. 3 (1986): 239–46. http://dx.doi.org/10.5840/teachphil19869338.

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10

Rhode, Jason, and Murali Krishnamurthi. "Preparing Faculty to Teach Online: Recommendations for Developing Self-Paced Training." International Journal of Information and Education Technology 6, no. 5 (2016): 376–82. http://dx.doi.org/10.7763/ijiet.2016.v6.717.

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11

Gill, Grandon, and Carolyn F. Holton. "A Self-Paced Introductory Programming Course." Journal of Information Technology Education: Research 5 (2006): 095–105. http://dx.doi.org/10.28945/236.

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12

Xu, Wei, Wei Liu, Haoyuan Chi, Song Qiu, and Yu Jin. "Self-paced learning with privileged information." Neurocomputing 362 (October 2019): 147–55. http://dx.doi.org/10.1016/j.neucom.2019.06.072.

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13

Huh, Dongsung, and Terrence J. Sejnowski. "Conservation law for self-paced movements." Proceedings of the National Academy of Sciences 113, no. 31 (July 14, 2016): 8831–36. http://dx.doi.org/10.1073/pnas.1608724113.

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Optimal control models of biological movements introduce external task factors to specify the pace of movements. Here, we present the dual to the principle of optimality based on a conserved quantity, called “drive,” that represents the influence of internal motivation level on movement pace. Optimal control and drive conservation provide equivalent descriptions for the regularities observed within individual movements. For regularities across movements, drive conservation predicts a previously unidentified scaling law between the overall size and speed of various self-paced hand movements in the absence of any external tasks, which we confirmed with psychophysical experiments. Drive can be interpreted as a high-level control variable that sets the overall pace of movements and may be represented in the brain as the tonic levels of neuromodulators that control the level of internal motivation, thus providing insights into how internal states affect biological motor control.

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14

Wehlander, Terri. "Performance Improvement Through Self-Paced Learning." Journal For Healthcare Quality 19, no. 4 (July 1997): 26–28. http://dx.doi.org/10.1111/j.1945-1474.1997.tb00897.x.

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15

Nixon, Philip D., and Richard E. Passingham. "The striatum and self-paced movements." Behavioral Neuroscience 112, no. 3 (1998): 719–24. http://dx.doi.org/10.1037/0735-7044.112.3.719.

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16

Wallot, Sebastian, and Guy Van Orden. "Nonlinear analyses of self-paced reading." Mental Lexicon 6, no. 2 (August 3, 2011): 245–74. http://dx.doi.org/10.1075/ml.6.2.02wal.

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Nonlinear methods of fractal analysis and recurrence quantification analysis are becoming more commonplace in the cognitive and behavioral sciences. These methods are illustrated here in a tutorial style using self-paced reading data. Self-paced reading was performed in which each spacebar press revealed a story word-by-word or else sentence-by-sentence. Participant readers were either Ph.D. candidates in English literature or undergraduates from an introductory psychology course and the same story was read by all, either one time only or reread another time on another occasion. The nonlinear analyses revealed crucial differences between the word unit and sentence unit conditions. Performance in the word unit condition was dominated by a task specific strategy, yielding data patterns more like those observed in tapping tasks. Nonlinear analyses of the sentence unit condition, however, discriminated between graduate and undergraduate readers, and first readings of the story from re-reading. From these analyses, the repeated reading of the same story reveals a kind of über-fluency, in a manner of speaking, of the Ph.D. candidates in English literature, whose performance stayed at or closer to a performance ceiling in both readings.

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17

Weng, Pangyen. "Developmental Math, Flipped and Self-Paced." PRIMUS 25, no. 9-10 (October 27, 2015): 768–81. http://dx.doi.org/10.1080/10511970.2015.1031297.

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18

Inkson, Donna, and Erica Smith. "Self paced learning: A student perspective." Australian Educational Researcher 28, no. 1 (April 2001): 107–28. http://dx.doi.org/10.1007/bf03219746.

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19

Inkson, Donna, and Erica Smith. "Self paced learning: A student perspective." Australian Educational Researcher 28, no. 2 (August 2001): 107–28. http://dx.doi.org/10.1007/bf03219755.

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20

Al-taezi, Mohammed, Pengfei Zhu, Qinghua Hu, Yu Wang, and Abdulrahman Al-badwi. "Self-paced hierarchical metric learning (SPHML)." International Journal of Machine Learning and Cybernetics 12, no. 9 (June 10, 2021): 2529–41. http://dx.doi.org/10.1007/s13042-021-01336-2.

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21

Huang, Zongmo, Yazhou Ren, Xiaorong Pu, Lili Pan, Dezhong Yao, and Guoxian Yu. "Dual self-paced multi-view clustering." Neural Networks 140 (August 2021): 184–92. http://dx.doi.org/10.1016/j.neunet.2021.02.022.

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22

Scheiber, Peter, John G. Seifert, and Erich Müller. "Instructor-Paced vs. Self-Paced Skiing Modes in Older Recreational Alpine Skiers." Journal of Strength and Conditioning Research 25, no. 4 (April 2011): 988–96. http://dx.doi.org/10.1519/jsc.0b013e3181d4eb2d.

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23

Rooks, Daniel S., Bernard J. Ransil, and Wilson C. Hayes. "Self-Paced Exercise and Neuromotor Performance in Community-Dwelling Older Adults." Journal of Aging and Physical Activity 5, no. 2 (April 1997): 135–49. http://dx.doi.org/10.1123/japa.5.2.135.

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The aim of this study was to determine the efficacy and safety of 16 weeks of self-paced resistance training or walking protocols on neuromotor and functional parameters in active, community-dwelling older adults. Twenty-two sequentially recruited older adults were randomly assigned to one of two exercise groups: self-paced resistance training and self-paced walking. Static and dynamic balance, upper and lower extremity reaction times, muscle strength, and stairclimbing speed were measured before and immediately after 16 weeks of exercise. Preliminary data showed that 16 weeks of self-paced. progressive, lower body resistance training improved balance (one-legged stance with eyes open, 68%). reaction time (10%), muscle strength (160%), and stair climbing speed (28%), while a self-paced walking program improved balance (one-legged stance with eyes open, 51%), stair climbing speed (16%), and in certain circumstances muscle strength (25%), in active, community-dwelling older adults.

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24

Mauger, Alexis R., Alan J. Metcalfe, Lee Taylor, and Paul C. Castle. "The efficacy of the self-paced V̇O2max test to measure maximal oxygen uptake in treadmill running." Applied Physiology, Nutrition, and Metabolism 38, no. 12 (December 2013): 1211–16. http://dx.doi.org/10.1139/apnm-2012-0384.

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The novel self-paced, cycle-based maximal oxygen uptake (V̇O2max) test (SPV) has been shown to produce higher V̇O2max values than standard graded exercise test (GXT) protocols. This study sought to ascertain whether these observations would also be apparent in a self-paced, treadmill-based test design. Fourteen trained male runners performed a standard GXT on a motorised treadmill and a self-paced V̇O2max test on a nonmotorised treadmill in a counter-balanced design. The GXT included a plateau verification and was designed to last between 8 and 12 min. The self-paced test included 5 × 2 min stages and allowed participants to set their own running speed based on fixed increments in rating of perceived exertion. Significantly higher V̇O2max values (t[13] = 3.71, p = 0.003) were achieved in the self-paced test (64.4 ± 7.3 mL·kg−1·min−1) compared with the GXT (61.3 ± 7.3 mL·kg−1·min−1), and 13 of the 14 participants achieved the same or higher V̇O2max values in the self-paced test. Higher (p = 0.01) maximum heart rates were observed in the GXT (191 ± 10 beats·min−1 vs. 187 ± 7 beats·min−1), but no differences were observed in any other recorded variables. The self-paced V̇O2max test may provide a more valid means of measuring V̇O2max than the GXT and suggests that a V̇O2 plateau during a GXT does not always signify achievement of a definitive V̇O2max. These results provide further support that self-paced V̇O2max testing produces higher values for maximal oxygen uptake.

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25

Freeman, Mark J., and Duane I. Miller. "Effects of Locus of Control and Pacing on Performance of and Satisfaction with a Simulated Inspection Task." Perceptual and Motor Skills 69, no. 3-1 (December 1989): 779–85. http://dx.doi.org/10.1177/00315125890693-113.

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Subjects performed a simulated-inspection task where they searched 200 printed circuits for defects. Self-paced subjects were allowed to control the amount of time spent on each circuit, while the machine-paced subjects were allowed 10 sec. per circuit. Each subject completed Rotter's (1966) Locus of Control Scale (I-E). Variance was maximized by excluding the middle scores of the I-E scale. Self-paced subjects performed significantly better on correct decisions and on the number of misses. Internal scorers performed significantly better than external scorers on the number of misses. The personality variable interacted with the pacing variable when false alarms were considered. in the self-paced condition, external subjects had fewer false alarms than internal scorers. There were no differences in locus of control, pacing, or the interaction for these variables when satisfaction was the dependent variable. Evidence suggests locus of control may be useful in selecting inspectors for self-paced and machine-paced tasks.

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26

Astorino, Todd Anthony, David William McMillan, Ross Montgomery Edmunds, and Eduardo Sanchez. "Increased cardiac output elicits higher V̇O2max in response to self-paced exercise." Applied Physiology, Nutrition, and Metabolism 40, no. 3 (March 2015): 223–29. http://dx.doi.org/10.1139/apnm-2014-0305.

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Recently, a self-paced protocol demonstrated higher maximal oxygen uptake versus the traditional ramp protocol. The primary aim of the current study was to further explore potential differences in maximal oxygen uptake between the ramp and self-paced protocols using simultaneous measurement of cardiac output. Active men and women of various fitness levels (N = 30, mean age = 26.0 ± 5.0 years) completed 3 graded exercise tests separated by a minimum of 48 h. Participants initially completed progressive ramp exercise to exhaustion to determine maximal oxygen uptake followed by a verification test to confirm maximal oxygen uptake attainment. Over the next 2 sessions, they performed a self-paced and an additional ramp protocol. During exercise, gas exchange data were obtained using indirect calorimetry, and thoracic impedance was utilized to estimate hemodynamic function (stroke volume and cardiac output). One-way ANOVA with repeated measures was used to determine differences in maximal oxygen uptake and cardiac output between ramp and self-paced testing. Results demonstrated lower (p < 0.001) maximal oxygen uptake via the ramp (47.2 ± 10.2 mL·kg–1·min–1) versus the self-paced (50.2 ± 9.6 mL·kg–1·min–1) protocol, with no interaction (p = 0.06) seen for fitness level. Maximal heart rate and cardiac output (p = 0.02) were higher in the self-paced protocol versus ramp exercise. In conclusion, data show that the traditional ramp protocol may underestimate maximal oxygen uptake compared with a newly developed self-paced protocol, with a greater cardiac output potentially responsible for this outcome.

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27

Holroyd, T., M. Nielsen, S. Miyauchi, T. Yanagida, R. Turner, and Q. Deeley. "An MEG investigation of rhythmic tapping comparing self-paced and externally paced modes." NeuroImage 13, no. 6 (June 2001): 1188. http://dx.doi.org/10.1016/s1053-8119(01)92506-6.

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28

Hildebrandt, Gary H., and Michael A. Belmont. "Self-Paced Versus Instructor-Paced Preclinical Training in Operative Dentistry: A Case Study." Journal of Dental Education 82, no. 11 (November 2018): 1178–84. http://dx.doi.org/10.21815/jde.018.122.

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29

GUO, Lihua. "Self-Paced Learning with Statistics Uncertainty Prior." IEICE Transactions on Information and Systems E101.D, no. 3 (2018): 812–16. http://dx.doi.org/10.1587/transinf.2017edl8169.

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30

Travlos, Antonios K. "Kr-Withdrawal and Self-Paced Motor Performance." Perceptual and Motor Skills 89, no. 3_suppl (December 1999): 1111–26. http://dx.doi.org/10.2466/pms.1999.89.3f.1111.

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31

Terboven, Christian, Julian Miller, Sandra Wienke, and Matthias S. Müller. "Self-paced Learning in HPC Lab Courses." Journal of Computational Science Education 11, no. 1 (January 2020): 61–67. http://dx.doi.org/10.22369/issn.2153-4136/11/1/10.

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32

Protter, Murray H. "The Self-Paced Calculus Program at Berkeley." American Mathematical Monthly 98, no. 3 (March 1991): 245. http://dx.doi.org/10.2307/2325030.

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33

Maccotta, Luigi, Jeffrey M. Zacks, and Randy L. Buckner. "Rapid self-paced event-related functional MRI." NeuroImage 13, no. 6 (June 2001): 192. http://dx.doi.org/10.1016/s1053-8119(01)91535-6.

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34

Tullis, Jonathan G., and Aaron S. Benjamin. "On the effectiveness of self-paced learning." Journal of Memory and Language 64, no. 2 (February 2011): 109–18. http://dx.doi.org/10.1016/j.jml.2010.11.002.

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35

Protter, Murray H. "The Self-Paced Calculus Program at Berkeley." American Mathematical Monthly 98, no. 3 (March 1991): 245–49. http://dx.doi.org/10.1080/00029890.1991.11995736.

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36

Low, David, Martha Gramlich, and Barbara Wright Engram. "Self-Paced Exercise Program for Office Workers." AAOHN Journal 55, no. 3 (March 2007): 99–105. http://dx.doi.org/10.1177/216507990705500302.

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37

Wittmann, Marc, Nicole von Steinbüchel, and Elzbieta Szelag. "Hemispheric specialisation for self-paced motor sequences." Cognitive Brain Research 10, no. 3 (January 2001): 341–44. http://dx.doi.org/10.1016/s0926-6410(00)00052-5.

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38

Trojbicz, Lucas Rosiello, Mayara Vieira Damasceno, Leonardo Alves Pasqua, Arthur Fernandes Gáspari, Adriano Eduardo Lima-Silva, and Rômulo Bertuzzi. "Parasympathetic activity delayed after self-paced exercise." European Journal of Sport Science 18, no. 6 (April 18, 2018): 842–50. http://dx.doi.org/10.1080/17461391.2018.1462855.

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39

Sparkman, O. David. "MS fundamentals self-paced training, version B." Journal of the American Society for Mass Spectrometry 6, no. 6 (June 1995): 536–37. http://dx.doi.org/10.1016/s1044-0305(95)80071-9.

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40

Sun, Lijian, and Yun Zhou. "FSPMTL: Flexible Self-Paced Multi-Task Learning." IEEE Access 8 (2020): 132012–20. http://dx.doi.org/10.1109/access.2020.3009988.

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41

MYLES, W. S., and T. T. ROMET. "Self-paced work in sleep deprived subjects." Ergonomics 30, no. 8 (August 1987): 1175–84. http://dx.doi.org/10.1080/00140138708966006.

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42

Feldstein, Michael, and Lisa Neal. "Designing usable, self-paced e-learning courses." eLearn 2006, no. 8 (August 2006): 1. http://dx.doi.org/10.1145/1165342.1165344.

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43

Larsson, Jonas, Balázs Gulyás, and Per E. Roland. "Cortical representation of self-paced finger movement." NeuroReport 7, no. 2 (January 1996): 463–68. http://dx.doi.org/10.1097/00001756-199601310-00021.

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44

Rinchen, Paden, and Udit Kumar Chakraborty. "Open Ended Tool for Self Paced Learning." International Journal of Hybrid Information Technology 8, no. 8 (August 31, 2015): 201–8. http://dx.doi.org/10.14257/ijhit.2015.8.8.20.

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45

Meng, Deyu, Qian Zhao, and Lu Jiang. "A theoretical understanding of self-paced learning." Information Sciences 414 (November 2017): 319–28. http://dx.doi.org/10.1016/j.ins.2017.05.043.

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46

Sloot, L. H., M. M. van der Krogt, and J. Harlaar. "Self-paced versus fixed speed treadmill walking." Gait & Posture 39, no. 1 (January 2014): 478–84. http://dx.doi.org/10.1016/j.gaitpost.2013.08.022.

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47

DeFazio, K., D. Wittman, and C. G. Drury. "Effective vehicle width in self-paced tracking." Applied Ergonomics 23, no. 6 (December 1992): 382–86. http://dx.doi.org/10.1016/0003-6870(92)90369-7.

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48

Koć-Januchta, Marta M., Tim N. Höffler, Helmut Prechtl, and Detlev Leutner. "Is too much help an obstacle? Effects of interactivity and cognitive style on learning with dynamic versus non-dynamic visualizations with narrative explanations." Educational Technology Research and Development 68, no. 6 (September 17, 2020): 2971–90. http://dx.doi.org/10.1007/s11423-020-09822-0.

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AbstractThe aim of this study was to investigate the role of visual/verbal cognitive style and interactivity level in dynamic and non-dynamic multimedia learning environments. A group of 235 biology students learned about photosynthesis either from a computer-based animation or a series of static pictures with spoken explanatory text. Participants were randomly assigned to one of two conditions: with or without the possibility to pause, to play, or to fast-forward/rewind the learning environment (self-paced versus system-paced condition). Participants obtained better results when learning with the system-paced environment than with the self-paced one. A significant triple interaction between cognitive style, type of pacing, and type of visualization showed that highly developed visualizers learned poorer with self-paced static pictures than with system-paced static pictures. There were no significant effects regarding verbal cognitive style. Results shed more light on the relation between different levels of interactivity and visual cognitive style, when learning from static pictures.

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49

Lee, Harold H., Shira Dunsiger, Lauren Connell Bohlen, Holly K. Boyle, Jessica A. Emerson, and David M. Williams. "Age Moderates the Effect of Self-Paced Exercise on Exercise Adherence among Overweight Adults." Journal of Aging and Health 32, no. 3-4 (November 23, 2018): 154–61. http://dx.doi.org/10.1177/0898264318812139.

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Objective: The present study tested the hypothesis that the effect of self-paced exercise on adherence to exercise programs is more pronounced with increasing age. Method: Fifty-nine low-active overweight adults (18-65 years) were encouraged to walk 30 to 60 min/day and randomized to either self-paced ( n = 30) or prescribed moderate-intensity ( n = 29) conditions. Results: The effect of study condition was moderated by age (main effect: b = 6.14, SE = 2.54, p = .02; Condition × Age: b = −11.55, SE = 3.77, p < .01), such that among participants >50 years, those in the self-paced condition exercised 6 more min/day than participants in the prescribed moderate-intensity condition ( p = .02), whereas among participants <50 years, those in the self-paced condition exercised 5.4 fewer min/day compared with those in the moderate-intensity condition ( p = .05). Affective response to physical activity did not mediate the moderating effect of age. Discussion: As age increases, adults may be more likely to adhere to self-paced versus prescribed moderate-intensity exercise.

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50

Faulkner, James, Johannes Gerhard, Lee Stoner, and Danielle Lambrick. "Self-Paced Walking within a Diverse Topographical Environment Elicits an Appropriate Training Stimulus for Cardiac Rehabilitation Patients." Rehabilitation Research and Practice 2012 (2012): 1–5. http://dx.doi.org/10.1155/2012/140871.

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Purpose. To assess the effect of a self-paced walking intervention within a topographically varied outdoor environment on physiological and perceptual markers in cardiac rehabilitation (CR) patients.Methods. Sixteen phase II CR patients completed twelve self-paced one-mile walking sessions over a four-week period within a community-based CR programme. Walking velocity, heart rate (HR), and ratings of perceived exertion (RPE) were reported at eight stages throughout the self-paced walks.Results. The study showed a significant increase in walking velocity from week 1 (~4.5 km/h) to week 4 (~5.1 km/h) of the self-paced walking programme (P<.05). A significantly higher HR was also observed in week 4 (111±13 b·min−1;~69% of maximal HR) compared to week 1 (106±14 b·min−1;~65% of maximal HR,P<.001). There were no changes in the average RPE across the course of the 4-week self-paced walking programme (P>.05).Conclusion. A self-paced walking programme may elicit an appropriate training stimulus for CR patients when exercising within a diverse topographical environment. Participants completed a one-mile walk within a shorter period of time and at a higher physiological intensity than that elicited at the onset of the programme, despite no observed changes in participants' subjective perception of exertion.

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