Learning and assessment with images: A view of cognitive load through the lens of cerebral blood flow
Jay J. Loftus
Search for more papers by this authorMichele Jacobsen
Search for more papers by this authorCorresponding Author
Timothy D. Wilson
Address for correspondence: Dr. Timothy D. Wilson, Department of Anatomy and Cell Biology, University of Western Ontario in London, Ontario, Canada (www.anatatorium.com). Email: [email protected]Search for more papers by this authorJay J. Loftus
Search for more papers by this authorMichele Jacobsen
Search for more papers by this authorCorresponding Author
Timothy D. Wilson
Address for correspondence: Dr. Timothy D. Wilson, Department of Anatomy and Cell Biology, University of Western Ontario in London, Ontario, Canada (www.anatatorium.com). Email: [email protected]Search for more papers by this authorAbstract
Understanding the relationship between cognitive processing and learner performance on tasks using digital media has become increasingly important as the transition towards online learning programs increases. Determining the impact of implementation of instructional resources is often limited to performance outcomes and comparisons to the status quo. This study measured changes in cerebral blood velocity (CBV) of the right middle cerebral artery during visual learning tasks using static images. Transcranial Doppler ultrasonography was used to compare the changes in CBV during learning of individuals with high and low spatial ability. Our results show that there is a slight increase from baseline values of CBV in individuals with high spatial ability during the learning task for the present study. In contrast, individuals with low spatial ability experience a decrement from baseline during the learning task. These results suggest spatial ability mitigates cognitive load and potentially has an impact on learner performance on visual learning tasks.
References
- Aaslid, R. (1987). Visually evoked dynamic blood flow response of the human cerebral circulation. Stroke, 18, 771–775.
- Aaslid, R., Markwalder, T.-M., & Nornes, H. (1982). Noninvasive transcranial Doppler ultrasound recording of flow velocity in basal cerebral arteries. Journal of Neurosurgery, 57, 769–774.
- Ayres, P., & Paas, F. (2007). Making instructional animations more effective: a cognitive load approach. Applied Cognitive Psychology, 21, 695–700.
- Baddeley, A. D. (1986). Working memory. Oxford: Clarendon Press.
- Bakker, M. J., Hofmann, J., Churches, O. F., Badcock, N. A., Kohler, M., & Keage, H. A. (2014). Cerebrovascular function and cognition in childhood: a systematic review of transcranial doppler studies. BMC Neurology, 14, 43.
- Boban, M., Črnac, P., Junaković, A., Garami, Z., & Malojčić, B. (2014). Blood flow velocity changes in anterior cerebral arteries during cognitive tasks performance. Brain and cognition, 84, 26–33.
- Brown A. M., & Ransom B. R. (2007). Astrocyte glycogen and brain energy metabolism. Glia, 55, 1263–1271.
- Cupini, L. M., Matteis, M., Troisi, E., Sabbadini, M., Bernardi, G., Caltagirone, C. et al. (1996). Bilateral simultaneous transcranial Doppler monitoring of flow velocity changes during visuospatial and verbal working memory tasks. Brain, 119, 1249–1253.
- Dekker, S., Lee, N. C., Howard-Jones, P., & Jolles, J. (2012). Neuromyths in education: prevalence and predictors of misconceptions among teachers. Frontiers in Psychology, 3, 429. doi: 10.3389/fpsyg.2012.00429.
- Deppe, M., Knecht, S., Lohmann, H., & Ringelstein, E. B. (2004). A method for the automated assessment of temporal characteristics of functional hemispheric lateralization by transcranial Doppler sonography. Journal of Neuroimaging, 14, 226–230.
- Duschek, S., & Schandry, R. (2003). Functional transcranial Doppler sonography as a tool in psychophysiological research. Psychophysiology, 40, 436–454.
- Duschek, S., Werner, N., Kapan, N., & Reyes del Paso, G. A. (2008). Patterns of cerebral blood flow and systemic hemodynamics during arithmetic processing. Journal of Psychophysiology, 22, 9.
- Garg, A., Norman, G., Spero, L., & Taylor, I. (1999). Learning anatomy: do new computer models improve spatial understanding? Medical Teacher, 21, 519–522.
- Goswami, U. (2006). Neuroscience and education: from research to practice? Nature Reviews Neuroscience 7, 406–413.
- Gould, R. L., Brown, R. G., Owen, A. M., Ffytche, D. H., & Howard, R. J. (2003). fMRI BOLD response to increasing task difficulty during successful paired associates learning. Neuroimage, 20, 1006–1019.
- Harskamp, E. G., Mayer, R. E., & Suhre, C. (2007). Does the modality principle for multimedia learning apply to science classrooms? Learning and Instruction, 17, 465–477.
- Hasler, B. S., Kersten, B., & Sweller, J. (2007). Learner control, cognitive load and instructional animation. Applied Cognitive Psychology, 21, 713–729.
- Huk, T. (2006). Who benefits from learning with 3D models? the case of spatial ability. Journal of Computer Assisted Learning, 22, 392–404.
- 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.
- Kelley, R. E., Chang, J. Y., Scheinman, N. J., Levin, B. E., Duncan, R. C., & Lee, S. C. (1992). Transcranial Doppler assessment of cerebral flow velocity during cognitive tasks. Stroke, 23, 9–14.
- Khalil, M. K., Paas, F., Johnson, T. E., & Payer, A. F. (2005). Interactive and dynamic visualizations in teaching and learning of anatomy: a cognitive load perspective. Anatomical Record. Part B, The New Anatomist, 286, 8–14.
- Krejza, J., Szydlik, P., Liebeskind, D. S., Kochanowicz, J., Bronov, O., Mariak, Z. et al. (2005). Age and sex variability and normal reference values for the V(MCA)/V(ICA) index. American Journal of Neuroradiology, 26, 730–735.
- Lohman, D. F. (1996). Spatial ability and G. In I. Dennis & P. Tapsfield (Eds.). Human abilities: their nature and assessment (pp. 97–116). Hillsdale, NJ: Erlbaum.
- Lowe, R. (2004). Interrogation of a dynamic visualization during learning. Learning and Instruction, 14, 257–274.
- Mayer, R. E. (2002). Multimedia learning. Psychology of Learning and Motivation: Advances in Research and Theory, 41, 85–139.
- Mayer, R. E. (2008). Applying the science of learning: evidence-based principles for the design of multimedia instruction. American Psychologist, 63, 760–769.
- Mayer, R. E. (2010). Applying the science of learning to medical education. Medical Education, 44, 543–549.
- Mayer, R. E., Hegarty, M., Mayer, S., & Campbell, J. (2005). When static media promote active learning: annotated illustrations versus narrated animations in multimedia instruction. Journal of Experimental Psychology-Applied, 11, 256–265.
- Mayer, R. E., & Moreno, R. (1998). Split-attention effect in multimedia learning: evidence for dual processing systems in working memory. Journal of Educational Psychology, 90, 312–320.
- Mayer, R. E., & Moreno, R. (2003). Nine ways to reduce cognitive load in multimedia learning. Educational Psychologist, 38, 43–52.
- Meijer, F., & van den Broek, E. L. (2010). Representing 3D virtual objects: interaction between visuo-spatial ability and type of exploration. Vision Research, 50, 630–635.
- Miller, G. A. (1956). The magical number seven, plus or minus two: some limits on our capacity for processing information. Psychological Review, 63, 81–97.
- Moreno, R., & Mayer, R. (2007). Interactive multimodal learning environments. Educational Psychology Review, 19, 309–326.
- Nguyen, N., Nelson, A. J., & Wilson, T. D. (2012). Computer visualizations: factors that influence spatial anatomy comprehension. Anatomical Sciences Education, 5, 98–108.
- Nguyen, N. T. (2012) Anatomy: the relationship between internal and external visualizations. Anatomy & Cell Biology. Electronic Thesis and Dissertation Repository, University of Western Ontario, Ontario, Canada.
- Oldfield, R. C. (1971). The assessment and analysis of handedness: the Edinburgh inventory. Neuropsychologia, 9, 97–113.
- Ozcinar, Z. (2009). The topic of instructional design in research journals: a citation analysis for the years 1980-2008. Australasian Journal of Educational Technology, 25, 559–580.
- Paas, F., & Kester, L. (2006). Learner and information characteristics in the design of powerful learning environments. Applied Cognitive Psychology, 20, 281–285.
- Paas, F., Renkl, A., & Sweller, J. (2004). Cognitive load theory: instructional implications of the interaction between information structures and cognitive architecture. Instructional Science, 32, 1–8.
- Payne, H., Gutierrez-Sigut, E., Subik, J., Woll, B., & MacSweeney, M. (2015). Stimulus rate increases lateralisation in linguistic and non-linguistic tasks measured by functional transcranial Doppler sonography. Neuropsychologia, 72, 59–69.
- Peters, M., Laeng, B., Latham, K., Jackson, M., Zaiyouna, R., & Richardson, C. (1995). A Redrawn Vandenberg and Kuse Mental rotations test: different versions and factors that affect performance. Brain and Cognition, 28, 39–58.
- Reed, S. K. (2006). Cognitive architectures for multimedia learning. Educational Psychologist, 41, 87–98.
- Rummer, R., Schweppe, J., Scheiter, K., & Gerjets, P. (2008). Multimedia learning and the cognitive basis of the modality effect. Psychologische Rundschau, 59, 98–107.
- Rypma, B., & D'Esposito, M. (1999). The roles of prefrontal brain regions in components of working memory: effects of memory load and individual differences. Proceedings of the National Academy of Sciences, 96(11), 6558–6563.
- Sandrini, M., Rossini, P. M., & Miniussia, C. (2008). Lateralized contribution of prefrontal cortex in controlling task-irrelevant information during verbal and spatial working memory tasks: rTMS evidence. Neuropsychologia, 46, 2056–2063.
- Schmidt, P., Krings, T., Willmes, K., Roessler, F., Reul, J., & Thron, A. (1999). Determination of cognitive hemispheric lateralization by “Functional” transcranial Doppler cross-validated by functional MRI. Stroke, 30, 939–945.
- Shepard, R. N., & Metzler, J. (1971). Mental rotation of three-dimensional objects. Science, 171(3972), 701–703.
- Smith, E. E., & Jonides, J. (1997). Working memory: a view from neuroimaging. Cognitive Psychology, 33, 5–42.
- Stiller, K. D., Freitag, A., Zinnbauer, P., & Freitag, C. (2009). How pacing of multimedia instructions can influence modality effects: a case of superiority of visual texts. Australasian Journal of Educational Technology, 25, 184–203.
- Stroobant, N., & Vingerhoets, G. (2000). Transcranial Doppler Ultrasonography monitoring of cerebral hemodynamics during performance of cognitive tasks: a review. Neuropsychology Review, 10, 213–231.
- Sweller, J. (2003). Evolution of human cognitive architecture. Psychology of Learning and Motivation: Advances in Research and Theory, 43, 215–266.
-
Sweller, J. (2010) Cognitive load theory: recent theoretical advances. In J. L. Plass, R. Moreno, & R. Brünken (Eds.), Cognitive load theory (pp. 29–47). New York, NY, Cambridge University Press.
10.1017/CBO9780511844744.004 Google Scholar
- Tabbers, H. K., Martens, R. L., & van Merrienboer, J. J. G. (2004). Multimedia instructions and cognitive load theory: effects of modality and cueing. British Journal of Educational Psychology, 74, 71–81.
- Tomasi, D., Chang, L., Caparelli, E. C., & Ernst, T. (2007). Different activation patterns for working memory load and visual attention load. Brain Research, 1132, 158–165.
- Tsujimoto, S., Yamamoto, T., Kawaguchi, H., Koizumi, H., & Sawaguchi, T. (2004). Prefrontal cortical activation associated with working memory in adults and preschool children: an event-related optical topography study. Cerebral Cortex, 14, 703–712.
- Vandenberg, S. G., & Kuse, A. R. (1978). Mental rotations, a group test of three-dimensional spatial visualization. Perceptual and Motor Skills, 47, 599–604.
- Verhoeven, L., Schnotz, W., & Paas, F. (2009). Cognitive load in interactive knowledge construction. Learning and Instruction 19, 369–375.
- Weisberg, D. S., Keil, F. C., Goodstein, J., Rawson, E., & Gray, J. R. (2007). The seductive allure of neuroscience explanations. Journal of Cognitive Neuroscience, 20, 470–477.
- Willie, C. K., Colino, F. L., Bailey, D. M., Tzeng, Y. C., Binsted, G., Jones, L. W. et al. (2011). Utility of transcranial Doppler ultrasound for the integrative assessment of cerebrovascular function. Journal of Neuroscience Methods, 196, 221–237.
-
Wilson, T. D. (2015). Role of image and cognitive load in anatomical multimedia. In L. K. Chan, & W. Pawlina (Eds.), Teaching anatomy (pp. 237–246). Cham: Springer.
10.1007/978-3-319-08930-0_27 Google Scholar
- Wilson, T. D., Serrador, J. M., & Shoemaker, J. K. (2003). Head position modifies cerebrovascular response to orthostatic stress. Brain Research, 96, 261–268.
-
Whelan, R. R. (2007). Neuroimaging of cognitive load in instructional multimedia. Educational Research Review, 2, 1–12.
10.1016/j.edurev.2006.11.001 Google Scholar
- Wouters, P., Tabbers, H. K., & Paas, F. (2007). Interactivity in video-based models. Educational Psychology Review, 19, 327–342.
- Zang, Y. F., Jin, Z., Weng, X. C., Zhang, L., Zeng, Y. W., Yang, L. et al. (2005). Functional MRI in attention-deficit hyperactivity disorder: evidence for hypofrontality. Brain & Development, 27, 544–550.