3,419
Views
41
CrossRef citations to date
0
Altmetric
Articles

Measuring cognitive load and cognition: metrics for technology-enhanced learning

References

  • Afergan, D., Peck, E. M., Solovey, E. T., Jenkins, A., Hincks, S. W., Brown, E. T., … Jacob, R. J. K. (2014). Dynamic difficulty using brain metrics of workload. In CHI'14 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 3797–3806). New York, NY: ACM Press.
  • Anderson, E. W., Potter, K. C., Matzen, L. E., Shepherd, J. F., Preston, G. A., & Silva, C. T. (2011). A user study of visualisation effectiveness using EEG and cognitive load. Computer Graphics Forum, 30, 791–800. doi: 10.1111/j.1467-8659.2011.01928.x
  • Anderson, J. R. (1983). The architecture of cognition. Cambridge, MA: University Press.
  • Antonenko, P. D., & Neiderhauser, D. S. (2010). The influence of leads on cognitive load and learning in a hypertext environment. Computers in Human Behavior, 26, 140–150. doi: 10.1016/j.chb.2009.10.014
  • Argyris, C. (1976). Theories of action that inhibit individual learning. American Psychologist, 31, 636–654. doi: 10.1037/0003-066X.31.9.638
  • Ayaz, H., Cakir, M. P., Izzetoglu, K., Curtin, A., Shewokis, P. A., Bunce, S., & Onaral, B. (2012, April). Monitoring expertise development during simulated UAV piloting tasks using optical brain imaging. Paper presented at the IEEE Aerospace conference, BigSky, MN.
  • Ayaz, H., Shewokis, P. A., Bunce, S., Izzetoglu, K., Willems, B., & Onaral, B. (2012). Optical brain monitoring for operator training and mental workload assessment. NeuroImage, 59, 36–47. doi: 10.1016/j.neuroimage.2011.06.023
  • Ayres, P. (2006). Using subjective measures to detect variations of intrinsic cognitive load within problems. Learning and Instruction, 16, 389–400. doi: 10.1016/j.learninstruc.2006.09.001
  • Ayres, P., & Paas, F. (2012). Cognitive load theory: New directions and challenges. Applied Cognitive Psychology, 26, 827–832. doi: 10.1002/acp.2882
  • Ayres, P., & Van Gog, T. (2009). State of the art research into cognitive load theory. Computers in Human Behavior, 25, 253–257. doi: 10.1016/j.chb.2008.12.007
  • Baddeley, A. D. (1986). Working memory. Oxford, UK: Oxford University Press.
  • Baddeley, A. D. (1992). Working Memory. Science, 255, 556–559. doi: 10.1126/science.1736359
  • Baddeley, A. D., & Hitch, G. J. (1994). Developments in the concept of working memory. Neuropsychology, 8, 485–493. doi: 10.1037/0894-4105.8.4.485
  • Baddeley, A. D., & Logie, R. H. (1999). Working memory: The multiple-component model. In A. Miyake & P. Shah (Eds.), Models of working-memory: Mechanisms of active maintenance and executive control (pp. 28–61). Cambridge, UK: Cambridge University Press.
  • Barrett, L. F., Tugade, M. M., & Engle, R. W. (2004). Individual differences in working memory capacity and dual-process theories of the mind. Psychological Bulletin, 130, 553–573. doi: 10.1037/0033-2909.130.4.553
  • Barrouillet, P., Bernardin, S., & Camos, V. (2004). Time constraints and resource sharing in adults’ working memory spans. Journal of Experimental Psychology: General, 133, 83–100. doi: 10.1037/0096-3445.133.1.83
  • Barrouillet, P., Bernardin, S., Portrat, S., Vergauwe, E., & Camos, V. (2007). Time and cognitive load in working memory. Journal of Experimental Psychology: Learning, Memory, and Cognition, 33, 570–585.
  • Blanshard, B. (1962). Reason and analysis. London, UK: George Allen & Unwin.
  • Block, R. A., Hancock, P. A., & Zakay, D. (2010). How cognitive load affects duration judgments: A meta-analytic review. Acta Psychologica, 134, 330–343. doi: 10.1016/j.actpsy.2010.03.006
  • Bratfisch, O., Borg, G., & Dornic, S. (1972). Perceived item-difficulty in three tests of intellectual performance capacity (Technical Report No. 29). Stockholm, Sweden: Institute of Applied Psychology.
  • Brisson, J., Mainville, M., Mailloux, D., Bealieu, C., Serres, J., & Sirois, S. (2013). Pupil diameter measurement errors as a function of gaze direction in corneal eyetrackers. Behavior Research Methods, 45, 1322–1331. doi: 10.3758/s13428-013-0327-0
  • Brünken, R., Plass, J. L., & Leutner, D. (2003). Direct measurement of cognitive load in multimedia learning. Educational Psychologist, 38, 53–61. doi: 10.1207/S15326985EP3801_7
  • Brünken, R., Plass, J. L., & Moreno, R. (2010). Current issues and open questions in cognitive load research. In J. L. Plass, R. Moreno, & R. Brünken (Eds.), Cognitive load theory (pp. 253–272). Cambridge, NY: Cambridge University Press.
  • Brünken, R., Seufert, T., & Paas, F. (2010). Measuring cognitive load. In J. L. Plass, R. Moreno, & R. Brünken (Eds.), Cognitive load theory (pp. 181–202). Cambridge, NY: Cambridge University Press.
  • Brünken, R., Steinbacher, S., Plass, J. L., & Leutner, D. (2002). Assessment of cognitive load in multimedia learning using dual-task methodology. Experimental Psychology, 49, 109–119. doi: 10.1027//1618-3169.49.2.109
  • Brünken, R., Steinbacher, S., Schnotz, W., & Leutner, D. (2001). Mentale Modelle und Effekte der Präsentations und Abrufkodalität beim Lernen mit Multimedia [Mental models and the effects of presentation and retrieval mode in multimedia learning]. Zeitschrift für Pädagogische Psychologie, 15, 15–27. doi: 10.1024//1010-0652.15.1.16
  • Bunce, S. C., Izzetoglu, K., Ayaz, H., Shewokis, P., Issetoglu, M., Pourrezaei, K., & Onaral, B. (2011). Implementation of fNIRS for monitoring levels of expertise and mental workload. In D. D. Schmorrow & C. M. Fidopiastis (Eds.), Foundations of augmented cognition. Directing the future of adaptive systems (pp. 13–22). Berlin, Germany: Springer.
  • Çakir, M. P., Ayaz, H., Izzetoğlu, M., Shewokis, P. A., Izzetoğlu, K., & Onaral, B. (2011). Bridging brain and educational sciences: An optical brain imaging study of visuospatial reasoning. Procedia – Social and Behavioral Sciences, 29, 300–309. doi: 10.1016/j.sbspro.2011.11.243
  • Callan, M. J., Sutton, R. M., & Dovale, C. (2010). When deserving translates into causing: The effect of cognitive load on immanent justice reasoning. Journal of Experimental Social Psychology, 46, 1097–1100. doi: 10.1016/j.jesp.2010.05.024
  • Callicott, J. H., Mattav, V. S., Bertolino, A., Finn, K., Coppola, R., Frank, J. A., … Weinberger, D. R. (1999). Physiological characteristics of capacity constraints in working memory as revealed by functional MRI. Cerebral Cortex, 9, 20–26. doi: 10.1093/cercor/9.1.20
  • Carswell, C. M. (2005). Assessing mental workload during laparoscopic surgery. Surgical Innovation, 12, 80–90. doi: 10.1177/155335060501200112
  • Chance, B., Anday, E., Nioka, S., Zhou, S., Hong, L., Worden, K., … Thomas, R. (1998). A novel method for fast imaging of brain function, non-invasively, with light. Optics Express, 2, 411–423. doi: 10.1364/OE.2.000411
  • Chandler, P., & Sweller, J. (1991). Cognitive load theory and the format of instruction. Cognition and Instruction, 8, 293–332. doi: 10.1207/s1532690xci0804_2
  • Chandler, P., & Sweller, J. (1992). The split-attention effect as a factor in the design of instruction. British Journal of Educational Psychology, 62, 233–246. doi: 10.1111/j.2044-8279.1992.tb01017.x
  • Chang, C., & Yang, F. (2010). Exploring the cognitive loads of high-school students as they learn concepts in web-based environments. Computers & Education, 55, 673–680. doi: 10.1016/j.compedu.2010.03.001
  • Chen, S., & Epps, J. (2013). Automatic classification of eye activity for cognitive load measurement with emotion interference. Computer Methods and Programs in Biomedicine, 110, 111–124. doi: 10.1016/j.cmpb.2012.10.021
  • Chen, S., Epps, J., Ruiz, N., & Chen, F. (2011, February). Eye activity as a measure of human mental effort in HCI. Paper presented at the International Conference on Intelligent User Interfaces (IUI'11), Palo, Alto, CA.
  • Cierniak, G., Scheiter, K., & Gerjets, P. (2009). Explaining the split-attention effect: Is the reduction of extraneous cognitive load accompanied by an increase in germane cognitive load? Computers in Human Behavior, 25, 315–324. doi: 10.1016/j.chb.2008.12.020
  • Coe, R., Aloisi, C., Higgins, S., & Major, L. E. (2014). What makes great teaching? Review of the underpinning research. London, UK: Sutton Trust. Retrieved from http://www.suttontrust.com/wp-content/uploads/2014/10/What-Makes-Great-Teaching-REPORT.pdf
  • Cowan, N. (2000). The magical number 4 in short-term memory: A reconsideration of mental storage capacity. Behavioral and Brain Sciences, 24, 87–185. doi: 10.1017/S0140525X01003922
  • Coyle, S., Ward, T., Markham, C., & McDarby, G. (2004). On the suitability of near-infrared (NIR) systems for next-generation brain-computer interfaces. Physiological Measurement, 25, 815–822. doi: 10.1088/0967-3334/25/4/003
  • Crossley, M., D'Arcy, C., & Rawson, N. S. (1997). Letter and category fluency in community-dwelling Canadian seniors: A comparison of normal participants to those with dementia of the Alzheimer or vascular type. Journal of Clinical and Experimental Neuropsychology, 19, 52–62. doi: 10.1080/01688639708403836
  • Davies, P. (2000). The relevance of systematic reviews to educational policy and practice. Oxford Review of Education, 26, 365–378. doi: 10.1080/713688543
  • De Jong, T. (2010). Cognitive load theory, educational research, and instructional design: Some food for thought. Instructional Science, 38, 105–134. doi: 10.1007/s11251-009-9110-0
  • DeLeeuw, K. E., & Mayer, R. E. (2008). A comparison of three measures of cognitive load: Evidence for separable measures of intrinsic, extraneous, and germane load. Journal of Educational Psychology, 100, 223–234. doi: 10.1037/0022-0663.100.1.223
  • Durantin, G., Gagnon, J.-F., Temblay, S., & Dehais, F. (2014). Using near infrared spectroscopy and heart rate variability to detect mental overload. Behavioural Brain Research, 259, 16–23. doi: 10.1016/j.bbr.2013.10.042
  • Dutke, S., & Rinck, M. (2006). Multimedia learning: Working memory and the learning of word and picture diagrams. Learning and Instruction, 16, 526–537. doi: 10.1016/j.learninstruc.2006.10.002
  • Eilam, B., & Poyas, Y. (2008). Learning with multiple representations: Extending multimedia learning beyond the lab. Learning and Instruction, 18, 368–378. doi: 10.1016/j.learninstruc.2007.07.003
  • Ferrari, M., & Quaresima, V. (2012). A brief review on the history of human functional near-infrared spectroscopy (fNIRS) development and fields of application. NeuroImage, 63, 921–935. doi: 10.1016/j.neuroimage.2012.03.049
  • Fink, A., & Neubauer, A. C. (2005). Individual differences in time estimation related to cognitive ability, speed of information processing and working memory. Intelligence, 33, 5–26. doi: 10.1016/j.intell.2004.09.001
  • Fishburn, F. A., Norr, M. E., Medvedev, A. V., & Vaidya, C. J. (2014). Sensitivity of fNIRS to cognitive state and load. Frontiers of Human Neuroscience, 8:76. doi: 10.3389/fnhum.2014.00076
  • Frank, S. L. (2013). Uncertainty reduction as a measure of cognitive load in science comprehension. Topics in Cognitive Science, 5, 475–494. doi: 10.1111/tops.12025
  • Freeman, W. J., Ahlfors, S. P., & Menon, V. (2009). Combining fMRI with EEG and MEG in order to relate patterns of brain activity to cognition. International Journal of Psychophysiology, 73, 43–52. doi: 10.1016/j.ijpsycho.2008.12.019
  • Galy, E., Cariou, M., & Mélan, C. (2012). What is the relationship between mental workload factors and cognitive loads types. International Journal of Psychophysiology, 83, 269–275. doi: 10.1016/j.ijpsycho.2011.09.023
  • Gavens, N., & Barrouillet, P. (2004). Delays of retention, processing efficiency, and attentional resources in working memory span development. Journal of Memory and Language, 51, 644–657. doi: 10.1016/j.jml.2004.06.009
  • Gerjets, P., Scheiter, K., & Cierniak, G. (2009). The scientific value of cognitive load theory: A research agenda based on the structuralist view of theories. Educational Psychology Review, 21, 43–54. doi: 10.1007/s10648-008-9096-1
  • Gibbons, H., & Stahl, J. (2010). Cognitive load reduces visual identity negative priming by disabling the retrieval of task-inappropriate prime information: An ERP study. Brain Research, 1330, 101–113. doi: 10.1016/j.brainres.2010.03.022
  • Goldstein, J. M., Jerram, M., Poldrack, R., Anagnoson, R., Breiter, H. C., Makris, N., … Seidman, L. J. (2005). Sex differences in prefrontal cortical brain activity during fMRI of auditory verbal working memory. Neuropsychology, 19, 509–519. doi: 10.1037/0894-4105.19.4.509
  • Gonzalez, C. (2005). Task workload and cognitive abilities in dynamic decision making. Human Factors, 47, 92–101. doi: 10.1518/0018720053653767
  • Gough, D., Oliver, S., & Thomas, J. (2013). Learning from research: Systematic reviews for informing policy decisions: A quick guide (A paper for the Alliance for Useful Evidence). London, UK: Nesta. Retrieved from http://www.alliance4usefulevidence.org/assets/Alliance-final-report-08141.pdf
  • Grandchamp, R., Braboszcz, C., & Delorme, A. (2014). Oculometric variations during mind wandering. Frontiers in Psychology, 5. doi: 10.3389/fpsyg.2014.00031
  • Greef, T., Lafeber, H., Oostendorp, H., & Lindenberg, J. (2009). Eye movement as indicators of mental workload to trigger adaptive automation. In D. D. Schmorrow, I. V. Estabrooke, & M. Grootjen (Eds.), Foundations of augmented cognition. Neuroergonomics and operational neuroscience (pp. 219–228). Berlin, Germany: Springer.
  • Grimes, D., Tan, D. S., Hudson, S. E., Shenoy, P., & Rao, R. P. N. (2008). Feasibility and pragmatics of classifying working memory load with and Electroencephalograph. Retrieved from http://research.microsoft.com/pubs/64270/chi2008-cogload.pdf
  • Halford, G. S., Baker, R., McCredden, J. E., & Bain, J. D. (2005). How many variables can humans process? Psychological Science, 16, 70–76. doi: 10.1111/j.0956-7976.2005.00782.x
  • Higgins, J. P. T., & Green, S. (2011). Cochrane handbook for systematic reviews of interventions (Version 5.1.0 [updated March 2011]). Retrieved from www.cochrane-handbook.org
  • Hockey, G. R. J. (1997). Compensatory control in the regulation of human performance under stress and high workload: A cognitive-energetical framework. Biological Psychology, 45, 73–93. doi: 10.1016/S0301-0511(96)05223-4
  • Howard-Jones, P. (2014). Neuroscience and education: A review of educational interventions and approaches informed by neuroscience. Bristol, UK: Education Endowment Foundation.
  • Huttunen, K., Keränen, H., Väyrynen, E., Pääkkönen, R., & Lenio, T. (2011). Effect of cognitive load on speech prosody in aviation: Evidence from military simulator flights. Applied Ergonomics, 42, 348–357. doi: 10.1016/j.apergo.2010.08.005
  • Irwin, D. E., & Thomas, L. E. (2010). Eyeblinks and cognition. In V. Coltheart (Ed.), Tutorials in visual cognition (pp. 121–141). New York, NY: Psychology Press.
  • Jacob, R. J. K., & Karn, K. S. (2003). Eye tracking in human-computer interaction and usability research: Ready to deliver the promises. In J. Hyona, R. Radasch, & H. Deubels (Eds.), The mind's eye: Cognitive and applied aspects of eye movement research (pp. 573–603). Oxford, UK: Elsevier Science.
  • Jaeggi, S. M., Buschkuehl, M., Etienne, A., Ozdoba, C., Perrig, W. J., & Nirkko, A. C. (2007). On how high performers keep cool brains in situations of cognitive overload. Cognitive, Affective, & Behavioral Neuroscience, 7, 75–89. doi: 10.3758/CABN.7.2.75
  • Jaeggi, S. M., Seewer, R., Nirkko, A. C., Eckstein, D., Schroth, G., Groner, R., & Gutbrod, K. (2003). Does excessive memory load attenuate activation in the prefrontal cortex? Load-dependant processing in single and dual tasks: Functional magnetic resonance imaging study. NeuroImage, 19, 210–225.
  • Jaušovec, N., & Jaušovec, K. (2004). Differences in induced brain activity during the performance of learning and working-memory tasks related to intelligence. Brain and Cognition, 54, 65–74. doi: 10.1016/S0278-2626(03)00263-X
  • Johnstone, A. H. (1997). Chemistry teaching – Science or alchemy? Journal of Chemical Education, 74, 262–268. doi: 10.1021/ed074p262
  • Kalyuga, S. (2009). Managing cognitive load in adaptive multimedia learning. London, UK: Information Science Reference.
  • Kalyuga, S., Ayres, P., Chandler, P., & Sweller, J. (2003). The expertise reversal effect. Educational Psychologist, 38, 23–31. doi: 10.1207/S15326985EP3801_4
  • Kalyuga, S., Chandler, P., & Sweller, J. (1998). Levels of expertise and instructional design. Human Factors, 40, 1–17. doi: 10.1518/001872098779480587
  • Kalyuga, S., & Sweller, J. (2005). Rapid dynamic assessment of expertise to improve the efficiency of adaptive e-learning. Educational Technology Research and Development, 53, 83–93. doi: 10.1007/BF02504800
  • Khawaja, M. A., Ruiz, N., & Chen, F. (2007, November). Potential speech features for cognitive load measurement. Paper presented at the OZCHI conference, Adelaide, Australia.
  • Kirschner, P. A., Ayres, P., & Chandler, P. (2011). Contemporary cognitive load theory research: The good, the bad and the ugly. Computers in Human Behaviour, 27, 99–105. doi: 10.1016/j.chb.2010.06.025
  • Klingner, J., Kumar, R., & Hanrahan, P. (2008). Measuring the task-evoked pupillary response with a remote eye tracker. In ETRA ’08: Proceedings of the 2008 Symposium on Eye Tracking Research & Applications (pp. 69–72). New York, NY: ACM. doi:10.1145/1344471.1344489
  • Klingner, J., Tversky, B., & Hanrahan, P. (2010). Effects of visual and verbal presentation on cognitive load in vigilance, memory, and arithmetic tasks. Psychophysiology, 48, 323–332. doi: 10.1111/j.1469-8986.2010.01069.x
  • Kramer, A. F. (1991). Physiological metrics of mental workload: A review of recent progress. In D. L. Damos (Ed.), Multiple-task performance (pp. 279–328). London, UK: Taylor & Francis.
  • Kramer, J. H., Delis, D. C., & Daniel, M. (1988). Sex differences in verbal learning. Journal of Clinical Psychology, 44, 907–915. doi: 10.1002/1097-4679(198811)44:6<907::AID-JCLP2270440610>3.0.CO;2-8
  • Leff, D. R., Orihuela-Espina, F., Elwell, C. E., Athanasiou, T., Delpy, D. T., Darzi, A. W., & Yang, G.-Z. (2011). Assessment of the cerebral cortex during motor task behaviours in adults: A systematic review of functional near infrared spectroscopy (fNIRS) studies. NeuroImage, 54, 2922–2936. doi: 10.1016/j.neuroimage.2010.10.058
  • Lejbak, L., Crossley, M., & Vrbancic, M. (2011). A male advantage for spatial and object but not verbal working memory using the n-back task. Brain and Cognition, 76, 191–196. doi: 10.1016/j.bandc.2010.12.002
  • Leppink, J., Paas, F., Van der Vleuten, C. P. M., Van Gog, T., & Van Merriënboer, J. J. G. (2013). Development of an instrument for measuring different types of cognitive load. Behavior Research Methods, 45, 1058–1072. doi: 10.3758/s13428-013-0334-1
  • Lin, T., Li, X., Wu, Z., & Tang, N. (2013). Automatic cognitive load classification using high-frequency interaction events: An exploratory study. International Journal of Technology and Human Interaction, 9(3), 73–88. doi: 10.4018/jthi.2013070106
  • Liu, T., Saito, H., Oi, M. (2012). Distinctive activation patterns under intrinsically versus extrinsically driven cognitive loads in prefrontal cortex: A near-infrared spectroscopy study using a driving video game. Neuroscience Letters, 506, 220–224. doi: 10.1016/j.neulet.2011.11.009
  • MacLeod, C. M. (1992). The Stroop task: The “Gold Standard” of attentional measures. Journal of Experimental Psychology: General, 121, 12–14. doi: 10.1037/0096-3445.121.1.12
  • Martin, S. (2010). Teachers using learning styles: Torn between research and accountability? Teaching and Teacher Education, 26, 1583–1591. doi: 10.1016/j.tate.2010.06.009
  • Martin, S. (2012). Does instructional format really matter? Cognitive load theory, multimedia and teaching English Literature. Educational Research and Evaluation, 18, 125–152.
  • Martin, S., & Vallance, M. (2008). The impact of synchronous inter-networked teacher training in information and communication technology integration. Computers & Education, 51, 34–53. doi: 10.1016/j.compedu.2007.04.001
  • Massa, L. J., & Mayer, R. E. (2006). Testing the ATI hypothesis: Should multimedia instruction accommodate verbalizer-visualizer cognitive style? Learning and Individual Differences, 16, 321–335. doi: 10.1016/j.lindif.2006.10.001
  • Matthews, G., Davies, D. R., & Holley, P. J. (1993). Cognitive predictors of vigilance. Human Factors, 35, 3–24.
  • Mayer, R. E. (2001). Multimedia learning. New York, NY: Cambridge University Press.
  • Mayer, R. E. (2003). The promise of multimedia learning: Using the same instructional design methods across different media. Learning and Instruction, 13, 125–139. doi: 10.1016/S0959-4752(02)00016-6
  • Mayer, R. E. (2008). Applying the science of learning: Evidence-based principles for the design of multimedia instruction. American Psychologist, 63, 760–769. doi: 10.1037/0003-066X.63.8.760
  • Mayer, R. E. (2009). Multimedia learning (2nd ed.). New York, NY: Cambridge University Press.
  • Mayer, R. E., & Moreno, R. (2002). Aids to computer-based multimedia learning. Learning and Instruction, 12, 107–119. doi: 10.1016/S0959-4752(01)00018-4
  • McQuaid, J. W. (2010). Using cognitive load to evaluate participation and design of an asynchronous course. The American Journal of Distance Education, 24, 177–194. doi: 10.1080/08923647.2010.519949
  • Miller, G. A. (1956). The magical number seven, plus or minus two: Some limits on our capacity to process information. Psychological Review, 63, 81–97. doi: 10.1037/h0043158
  • Miller, L. M., Chang, C. I., Wang, S., Beier, M. E., & Klisch, Y. (2011). Learning and motivational impacts of a multimedia science game. Computers & Education, 57, 1425–1433. doi: 10.1016/j.compedu.2011.01.016
  • Moray, N. (1979). Mental workload: Its theory and measurement. London, UK: Springer.
  • Moreno, R. (2006). When worked examples don't work: Is cognitive load theory at an impasse? Learning and Instruction, 16, 170–181. doi: 10.1016/j.learninstruc.2006.02.006
  • Moreno, R., & Park, B. (2010). Cognitive load theory: Historical development and relation to other theories. In J. L. Plass, R. Moreno, & R. Brünken (Eds.), Cognitive load theory (pp. 9–28). New York, NY: Cambridge University Press.
  • Murai, K., Hayashi, Y., Okazaki, T., Stone, L. C., & Mitomo, N. (2008). Evaluation of ship navigator's mental workload using nasal temperature and heart rate variability. In Proceedings of IEEE International Conference on Systems, Man and Cybernetics (pp. 228–232). Red Hook, NY: Curran Associates.
  • Nagel, B. J., Ohannessian, A., & Cummins, K. (2007). Performance dissociation during verbal and spatial working memory tasks. Perceptual and Motor Skills, 105, 243–250.
  • Niegemann, H. M. (2001). Neue lernmedien: Konzipieren, entwickeln, einsetzen [New instructional media: Conceptualize, develop, implement]. Bern, Switzerland: Huber.
  • Norman, M. A., Evans, J. D., Miller, W. S., & Heaton, R. K. (2000). Demographically corrected norms for the California Verbal Learning Test. Journal of Clinical and Experimental Neuropsychology, 22, 80–94. doi: 10.1076/1380-3395(200002)22:1;1-8;FT080
  • O'Brien, S. (2006). Eye-tracking and translation memory matches. Perspectives: Studies in Translatology, 14, 185–205.
  • O'Hare, E. D., Lu, L. H., Houston, S. M., Brookheimer, S. Y., & Sowell, E. R. (2008). Neurodevelopmental changes in verbal working memory load-dependency: An fMRI investigation. NeuroImage, 42, 1678–1685. doi: 10.1016/j.neuroimage.2008.05.057
  • Paas, F. (1992). Training strategies for attaining transfer of problem-solving skill in statistics: A cognitive-load approach. Journal of Educational Psychology, 84, 429–434. doi: 10.1037/0022-0663.84.4.429
  • Paas, F., Renkel, A., & Sweller, J. (2003). Cognitive load theory and instructional design: Recent developments. Educational Psychologist, 38, 1–3. doi: 10.1207/S15326985EP3801_1
  • Paas, F., Tuovinen, J., Tabbers, H., & Van Gerven, P. W. M. (2003). Cognitive load measurement as a means to advance cognitive load theory. Educational Psychologist, 38, 63–71. doi: 10.1207/S15326985EP3801_8
  • Paas, F., & Van Merriënboer, J. J. G. (1993). The efficiency of instructional conditions: An approach to combine mental effort and performance measures. Human Factors, 35, 737–743.
  • Paas, F., & Van Merriënboer, J. J. G. (1994). Variability of worked examples and transfer of geometrical problem-solving skills: A cognitive load approach. Journal of Educational Psychology, 86, 122–133. doi: 10.1037/0022-0663.86.1.122
  • Paivio, A. (1986). Mental representations: A dual coding approach. New York, NY: Oxford University Press.
  • Palinko, O., Kun, A. L., Shyrokov, A., & Heeman, P. (2010). Estimating cognitive load using remote eye tracking in a driving simulator. In Proceedings of the 2010 Symposium on Eye-Tracking Research & Applications (pp. 141–144). Austin, TX: ACM.
  • Peck, E. M., Afergan, D., Yuksel, B. F., Lalooses, F., & Jacob, R. J. K. (2014). Using fNIRS to measure mental workload in the real world. In S. H. Fairclough & K. Gilleade (Eds.), Advances in physiological computing (Human-Computer Interaction Series) (pp. 117–140). London, UK: Springer.
  • Peck, E. M., Yuksel, B. F., Ottley, A., Jacob, R. J. K., & Chang, R. (2013). Using fNIRS brain sensing to evaluate information visualisation interfaces. In CHI 2013 proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 473–482). Vancouver, BC: Association for Computing Machinery.
  • Plass, J. L., Chun, D. M., Mayer, R. E., & Leutner, D. (2003). Cognitive load in reading a foreign language text with multimedia aids and the influence of verbal and spatial abilities. Computers in Human Behavior, 19, 221–243. doi: 10.1016/S0747-5632(02)00015-8
  • Pollock, E., Chandler, P., & Sweller, J. (2002). Assimilating complex information. Learning and Instruction, 12, 61–86. doi: 10.1016/S0959-4752(01)00016-0
  • Popper, K. (1959). The logic of scientific discovery. New York, NY: Basic Books.
  • Popper, K. (1963). Conjectures and refutations. London, UK: Routledge.
  • Portrat, S., Camos, V., & Barrouillet, P. (2009). Working memory in children: A time-constrained functioning similar to adults. Journal of Experimental Child Psychology, 102, 368–374. doi: 10.1016/j.jecp.2008.05.005
  • Reid, N. (2008). A scientific approach to the teaching of chemistry. What do we know about how students learn in the sciences, and how can we make our teaching match this to maximise performance? Chemistry Education Research and Practice, 9, 51–59. doi: 10.1039/b801297k
  • Repovš, G., & Baddeley, A. (2006). The multi-component model of working memory: Exploration in experimental cognitive psychology. Neuroscience, 139, 5–21. doi: 10.1016/j.neuroscience.2005.12.061
  • Robertson, I. H., Manly, T., Andrade, J., Baddeley, B. T., & Yiend, J. (1997). “Oops!” Performance correlates of everyday attentional failures in traumatic brain injured and normal subjects. Neuropsychologia, 35, 747–758. doi: 10.1016/S0028-3932(97)00015-8
  • Ross, V., Jongen, E. M. M., Wang, W., Brijs, T., Brijs, K., Ruiter, R. A. C., & Wets, G. (2014). Investigating the influence of working memory capacity when driving behaviour is combined with cognitive load: An LCT study of young novice drivers. Accident Analysis and Prevention, 62, 377–387. doi: 10.1016/j.aap.2013.06.032
  • Salomon, G. (1984). Television is “easy” and print is “tough”: The differential investment of mental effort in learning as a function of perceptions and attributions. Journal of Educational Psychology, 76, 647–658. doi: 10.1037/0022-0663.76.4.647
  • Scharfenberg, F., & Bogner, F. X. (2013). Teaching gene technology in an outreach lab: Students’ assigned cognitive load clusters and the clusters’ relationship to learner characteristics, laboratory variables, and cognitive achievement. Research in Science Education, 43, 141–161. doi: 10.1007/s11165-011-9251-4
  • Schnotz, W. (2010). Reanalyzing the expertise reversal effect. Instructional Science, 38, 315–323. doi: 10.1007/s11251-009-9104-y
  • Schnotz, W., Boeckheler, J., & Grzondziel, H. (1999). Individual and co-operative learning with interactive animated pictures. European Journal of Psychology of Education, 14, 245–265. doi: 10.1007/BF03172968
  • Schnotz, W., & Kürschner, C. (2007). A reconsideration of cognitive load theory. Educational Psychology Review, 19, 469–508. doi: 10.1007/s10648-007-9053-4
  • Schoor, C., Bannert, M., & Brünken, R. (2012). Role of dual task design when measuring cognitive load during multimedia learning. Educational Technology Research and Development, 60, 753–768. doi: 10.1007/s11423-012-9251-8
  • Seufert, T., Jänen, I., & Brünken, R. (2007). The impact of intrinsic cognitive load on the effectiveness of graphical help for coherence formation. Computers in Human Behavior, 23, 1055–1071. doi: 10.1016/j.chb.2006.10.002
  • Shaw, T. H., Satterfield, K., Ramirez, R., & Finomore, V. (2013). Using cerebral haemovelocity to measure workload during spatialised auditory vigilance task in novice and experienced drivers. Ergonomics, 56, 1251–1263. doi: 10.1080/00140139.2013.809154
  • Shi, Y., Choi, E. H. C., Ruiz, N. F., & Taib, R. (2007). Galvanic skin response (GSR) as an index of cognitive load. ACM Digital Library. Extended abstracts on Human Factors in Computing Systems, 2651–2656. Retrieved from dl.acm.org/citation.cfm?id=1241057 doi: 10.1145/1240866.1241057
  • Shuler, C. (2009). Pockets of potential: Using mobile technologies to promote children's learning. Retrieved from http://www.joanganzcooneycenter.org/wp-content/uploads/2010/03/pockets_of_potential_1_.pdf
  • Siegle, G. J., Steinhauer, S. R., & Thase, M. E. (2004). Pupillary assessment and computational modeling of the Stroop task in depression. International Journal of Psychophysiology, 52, 63–76. doi: 10.1016/j.ijpsycho.2003.12.010
  • Smit, A. S., Eling, P. A. T. M., & Coenen, A. M. L. (2004). Mental effort causes vigilance decrease due to resource depletion. Acta Psychologica, 115, 35–42. doi: 10.1016/j.actpsy.2003.11.001
  • Solovey, E. T., Lalooses, F., Chauncey, K., Weaver, D., Scheutz, M., Sassaroli, A., … Jacob, R. J. K (2011). Sensing cognitive multitasking for a brain-based adaptive user interface. In CHI 2011 proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 383–392). Vancouver, BC: Association for Computing Machinery.
  • Speck, O., Ernst, T., Braun, J., Koch, C., Miller, E., & Chang, L. (2000). Gender differences in the functional organisation of the brain for working memory. NeuroReport, 11, 2581–2585. doi: 10.1097/00001756-200008030-00046
  • Strangman, G., Culver, J. P., Thompson, J. H., & Boas, D. A. (2002). A quantitative comparison of simultaneous BOLD fMRI and NIRS recordings during functional brain activation. NeuroImage, 17, 719–731. doi: 10.1006/nimg.2002.1227
  • Stroh, C. M. (1971). Vigilance: The problem of sustained attention. Oxford, UK: Pergamon Press.
  • Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12, 257–285. doi: 10.1207/s15516709cog1202_4
  • Sweller, J. (1994). Cognitive load theory, learning difficulty, and instructional design. Learning and Instruction, 4, 295–312. doi: 10.1016/0959-4752(94)90003-5
  • Sweller, J. (1999). Instructional design in technical areas. Camberwell, Australia: ACER Press.
  • Sweller, J., & Chandler, P. (1994). Why some material is difficult to learn. Cognition and Instruction, 12, 185–233. doi: 10.1207/s1532690xci1203_1
  • Sweller, J., Van Merriënboer, J. J. G., & Paas, F. (1998). Cognitive architecture and instructional design. Educational Psychology Review, 10, 251–296. doi: 10.1023/A:1022193728205
  • Sykes Tottenham, L., Saucier, D., Elias, L., & Gutwin, C. (2003). Female advantage for spatial location memory in both static and dynamic environments. Brain and Cognition, 53, 381–383. doi: 10.1016/S0278-2626(03)00149-0
  • Tabbers, H. K., Martens, R. L., & Van Merriënboer J. J. G. (2000, February). Multimedia instructions and cognitive load theory: Split-attention and modality effects. Paper presented at the National Convention of the Association for Educational Communications and Technology, Long Beach, CA.
  • Theeuwes, J., & Belopolsky, A. (2010). Top-down and bottom-up control of visual selection controversies and debate. In V. Coltheart (Ed.), Tutorials in visual cognition (pp. 67–92). New York, NY: Psychology Press.
  • Towse, J. N., & Hitch, G. J. (1995). Is there a relationship between task demand and storage space in tests of working memory capacity? The Quarterly Journal of Experimental Psychology, 48, 108–124. doi: 10.1080/14640749508401379
  • Tsunashima, H., & Yanagisawa, K. (2009). Measurement of brain function of car driving using functional near-infrared spectroscopy (fNIRS). Computational Intelligence and Neuroscience. Retrieved from http://dx.doi.org/10.1155/2009/164958
  • Unsworth, N., Schrock, J. C., & Engle, R. W. (2004). Working memory capacity and the Antisaccade Task: Individual differences in voluntary saccade control. Journal of Experimental Psychology: Learning, Memory, and Cognition, 30, 1302–1321.
  • Van Gerven, P. W. M., Paas, F., Van Merriënboer, J. J. G., & Schmidt, H. G. (2004). Memory load and the cognitive pupillary response in aging. Psychophysiology, 41, 167–174. doi: 10.1111/j.1469-8986.2003.00148.x
  • Van Gog, T., Kester, L., Nievelstein, F., & Paas, F. (2009). Uncovering cognitive processes: Different techniques that can contribute to cognitive load research and instruction. Computers in Human Behavior, 25, 325–331. doi: 10.1016/j.chb.2009.02.007
  • Van Gog, T., & Paas, F. (2008). Instructional efficiency: Revising the original construct in educational research. Educational Psychologist, 43, 16–26. doi: 10.1080/00461520701756248
  • Van Merriënboer, J. J. G., & Sweller, J. (2005). Cognitive load theory and complex learning: Recent developments and future directions. Educational Psychology Review, 17, 147–177. doi: 10.1007/s10648-005-3951-0
  • Van Orden, K. F., Limbert, W., Makeig, S., & Jung, T. (2009). Activity correlates of workload during a visuospatial memory task. Human Factors, 43, 111–121. doi: 10.1518/001872001775992570
  • Veenman, M. V. J., Prins, F. J., & Verheij, J. (2003). Learning styles: Self-reports versus thinking-aloud measures. British Journal of Educational Psychology, 73, 357–372. doi: 10.1348/000709903322275885
  • Voyer, D., Postma, A., Brake, B., & Imperato-McGinley, J. (2007). Gender differences in object location memory: A meta-analysis. Psychonomic Bulletin and Review, 14, 23–38. doi: 10.3758/BF03194024
  • Voyer, D., Voyer, S., & Bryden, M. P. (1995). Magnitude of sex differences in spatial abilities: A meta-analysis and consideration of critical variables. Psychology Bulletin, 117, 250–270. doi: 10.1037/0033-2909.117.2.250
  • Wallen, E., Plass, J. L., & Brünken, R. (2005). The function of annotations in the comprehension of scientific texts: Cognitive load effects and the impact of verbal ability. Educational Technology Research and Development, 53, 59–71. doi: 10.1007/BF02504798
  • Wauters, K., Desmet, P., & Van Den Noortgate, W. (2012). Item difficulty estimation: An auspicious collaboration between data and judgment. Computers & Education, 58, 1183–1193. doi: 10.1016/j.compedu.2011.11.020
  • Weiss, E. M., Ragland, J. D., Brensinger, C. M., Bilker, W. B., Deisenhammer, E. A., & Delazer, M. (2006). Sex differences in clustering and switching verbal fluency tasks. Journal of the International Neuropsychological Society, 12(4), 502–509. doi: 10.1017/S1355617706060656
  • Whelan, R. R. (2007). Neuroimaging of cognitive load in instructional multimedia. Educational Research Review, 2, 1–12. doi: 10.1016/j.edurev.2006.11.001
  • Wiebe, E. N., Roberts, E., & Behrend, T. S. (2010). An examination of two mental workload measurement approaches to understanding multimedia learning. Computers in Human Behavior, 26, 474–481. doi: 10.1016/j.chb.2009.12.006
  • Wittrock, M. C. (1974). Learning as a generative process. Educational Psychologist, 11, 87–95. doi: 10.1080/00461527409529129
  • Yap, T. F., Ambikairajah, E., Choi, E., & Chen, F. (2009, April). Phase based features for cognitive load measurement system. Paper presented at the IEEE International Conference on Acoustics, Speech, and Signal Processing, Taipei, Taiwan.
  • Yap, T. F., Epps, J., Ambikairajah, E., & Choi, E. H. C. (2011). Formant frequencies under cognitive load: Effects and classification. EURASIP Journal on Advances in Signal Processing, 2011:219253. doi: 10.1155/2011/219253
  • Yin, B., Chen, F., Ruiz, N., & Ambikairajah, E. (2008, March-April). Speech-based cognitive load monitoring system. Paper presented at the IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP, Las Vegas, NV.
  • Young, M. S., & Stanton, N. A. (2002). It's all relative: Defining mental workload in the light of Annett's paper. Ergonomics, 45, 1018–1020. doi: 10.1080/00140130210166816
  • Yuan, K., Steedle, J., Shavelson, R., Alonzo, A., & Oppezzo, M. (2006). Working memory, fluid intelligence, and science learning. Educational Research Review, 1, 83–98. doi: 10.1016/j.edurev.2006.08.005
  • Zheng, R., & Cook, A. (2012). Solving complex problems: A convergent approach to cognitive load measurement. British Journal of Educational Technology, 43, 233–246. doi: 10.1111/j.1467-8535.2010.01169.x

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.