Biology Textbook Graphics and Their Impact on Expectations of Understanding

References

• Ackerman, R., & Leiser, D. (2014). The effect of concrete supplements on metacognitive regulation during learning and open‐book test taking. British Journal of Educational Psychology, 84, 329–348.
   PubMed Web of Science ®Google Scholar
• Ball, B. H., Klein, K. N., & Brewer, G. A. (2014). Processing fluency mediates the influence of perceptual information on monitoring learning of educationally relevant materials. Journal of Experimental Psychology: Applied, 20, 336–348.
   PubMed Web of Science ®Google Scholar
• Brucker, B., Scheiter, K., & Gerjets, P. (2014). Learning with dynamic and static visualizations: Realistic details only benefit learners with high visuospatial abilities. Computers in Human Behavior, 36, 330–339.
   Web of Science ®Google Scholar
• Butcher, K. R. (2006). Learning from text with diagrams: Promoting mental model development and inference generation. Journal of Educational Psychology, 98, 182–197.
   Web of Science ®Google Scholar
• Carney, R. N., & Levin, J. R. (2002). Pictorial illustrations still improve students’ learning from text. Educational Psychology Review, 14, 5–26.
   Web of Science ®Google Scholar
• Danielson, R. W., & Sinatra, G. M. (2017). A relational reasoning approach to text-graphic processing. Educational Psychology Review, 29, 55–72.
   Web of Science ®Google Scholar
• Dimopoulos, K., Koulaidis, V., & Sklaveniti, S. (2003). Towards an analysis of visual images in school science textbooks and press articles about science and technology. Research in Science Education, 33, 189–216.
   Web of Science ®Google Scholar
• Freeman, S. (2011). Biological science. San Francisco, CA: Benjamin Cummings.
   Google Scholar
• Griffard, P. B. (2013). Deconstructing and decoding complex process diagrams in university biology. In D. F. Treagust & C.-Y. Tsui (Eds.) Multiple representations in biological education (pp. 165–183). Dordrecht, The Netherlands: Springer.
   Google Scholar
• Griffin, T. D., Wiley, J., & Salas, C. (2013). Supporting effective self-regulated learning: The critical role of monitoring. In R. Azevedo & V. Aleven (Eds.) International handbook of metacognition and learning technologies (pp. 19–34). New York, NY: Springer.
   Google Scholar
• Harp, S.F., & Mayer, R.E. (1997). The role of interest in learning from scientific text and illustrations. Journal of Educational Psychology, 89, 92–102.
   Web of Science ®Google Scholar
• Harp, S.F., & Mayer, R.E. (1998). How seductive details do their damage: A theory of cognitive interest in science learning. Journal of Educational Psychology, 90, 414–434.
   Web of Science ®Google Scholar
• Hinze, S. R., Williamson, V. M., Deslongchamps, G., Schultz, M. J., Williamson, K. C., & Rapp, D. N. (2013). Textbook treatments of electrostatic potential maps in general and organic chemistry. Journal of Chemical Education, 90, 1275–1281.
   Web of Science ®Google Scholar
• Höffler, T.N., & Leutner, D. (2007). Instructional animation versus static pictures. Learning and Instruction, 17, 722–738.
   Web of Science ®Google Scholar
• Hume, D. (1986). A treatise of human nature. In L. A. Selby-Bigge (Ed.), A treatise of human nature by David Hume, reprinted from the original edition in three volumes. Oxford: Clarendon Press. (Original work published 1739).
   Google Scholar
• Ikeda, K., Kitagami, S., Takahashi, T., Hattori, Y., & Ito, Y. (2013). Neuroscientific information bias in metacomprehension: The effect of brain images on metacomprehension judgment of neuroscience research. Psychonomic Bulletin & Review, 20, 1357–1363.
   PubMed Web of Science ®Google Scholar
• Imhof, B., Scheiter, K., & Gerjets, P. (2011). Learning about locomotion patterns from visualizations. Computers & Education, 57, 1961–1970.
   Web of Science ®Google Scholar
• Jaeger, A.J., & Wiley, J. (2014). Do illustrations help or harm metacomprehension accuracy? Learning and Instruction, 34, 58–73.
   Web of Science ®Google Scholar
• Kintsch, W. (1980). Learning from text, levels of comprehension, or: Why anyone would read a story anyway. Poetics, 9, 87–98.
   Web of Science ®Google Scholar
• Kintsch, W. (1998). Comprehension: A paradigm for cognition. New York, NY: Cambridge University Press.
   Google Scholar
• Korbach, A., Brünken, R., & Park, B. (2016). Learner characteristics and information processing in multimedia learning: A moderated mediation of the seductive details effect. Learning and Individual Differences, 51, 59–68.
   Web of Science ®Google Scholar
• Koriat, A. (1997). Monitoring one’s own knowledge during study: A cue-utilization approach to judgments of learning. Journal of Experimental Psychology. General, 126, 349–370.
   Web of Science ®Google Scholar
• Koulaidis, V., & Dimopoulos, K. (2005). The co-deployment of visual representations and written language as resources for meaning making in Greek primary school science textbooks. International Journal of Learning, 12, 243–254.
   Google Scholar
• Kress, G., & van Leeuwen, T. (1996). Reading images: The grammar of the visual design. London, UK: Routledge.
   Google Scholar
• Latour, B. (1987). Science in action. Milton Keynes: Open University Press.
   Google Scholar
• Lemoni, R., Lefkaditou, A., Stamou, A. G., Schizas, D., & Stamou, G. P. (2013). Views of nature and the human-nature relations: An analysis of the visual syntax of pictures about the environment in Greek primary school textbooks—diachronic considerations. Research in Science Education, 43, 117–140.
   Web of Science ®Google Scholar
• Lenzner, A., Schnotz, W., & Müller, A. (2013). The role of decorative pictures in learning. Instructional Science, 41, 811–831.
   Web of Science ®Google Scholar
• Levin, J. R., Anglin, G. J., & Carney, R. N. (1987). On empirically validating functions of pictures in prose. In D. M. Willows & H. A. Houghton (Eds.), The psychology of illustration. I. Basic research (pp. 51–85). New York, NY: Springer.
   Google Scholar
• Maki, R. H. (1998). Test predictions over text material. In D. J. Hacker, J. Dunlosky, & A. C. Graesser (Eds.), Metacognition in educational theory and practice (pp. 117–145). Hillsdale, NJ: Erlbaum.
   Google Scholar
• Mason, L., Pluchino, P., Tornatora, M. C., & Ariasi, N. (2013). An eye-tracking study of learning from science text with concrete and abstract illustrations. Journal of Experimental Education, 81, 356–384.
   Web of Science ®Google Scholar
• Mayer, R. E., & Gallini, J. K. (1990). When is an illustration worth ten thousand words? Journal of Educational Psychology, 82, 715–726.
   Web of Science ®Google Scholar
• Miller, K. R., & Levine, J. S. (2010). Biology. Boston, MA: Pearson.
   Google Scholar
• Padilla, M. J., Miaoulis, I., Cyr, M., Coolidge-Stoltz, E., Graff-Haight, D., Jenner, J., … Jones, L. C. (2001). Life science. Upper Saddle River, NJ: Prentice Hall.
   Google Scholar
• Park, S., Kim, M., Lee, Y., Son, C., & Lee, M. (2005). The effects of visual illustrations on learners’ achievement and interest in PDA-(Personal Digital Assistant) based learning. Journal of Educational Computing Research, 33, 173–187.
   Google Scholar
• Rey, G. D. (2012). A review of research and a meta-analysis of the seductive detail effect. Educational Research Review, 7, 216–237.
   Web of Science ®Google Scholar
• Sanchez, C.A., & Wiley, J. (2006). An examination of the seductive details effect in terms of working memory capacity. Memory & Cognition, 34, 344–355.
   PubMed Web of Science ®Google Scholar
• Scheiter, K., Gerjets, P., Huk, T., Imhof, B., & Kammerer, Y. (2009). The effects of realism in learning with dynamic visualizations. Learning and Instruction, 19, 481–494.
   Web of Science ®Google Scholar
• Serra, M. J., & Dunlosky, J. (2010). Metacomprehension judgments reflect the belief that diagrams improve learning from text. Memory, 18, 698–711.
   PubMed Web of Science ®Google Scholar
• Sung, E., & Mayer, R. E. (2012). When graphics improve liking but not learning from online lessons. Computers in Human Behavior, 28, 1618–1625.
   Web of Science ®Google Scholar
• Thiede, K. W., Griffin, T. D., Wiley, J., & Anderson, M. C. (2010). Poor metacomprehension accuracy as a result of inappropriate cue use. Discourse Processes, 47, 331–362.
   Web of Science ®Google Scholar
• Thiede, K. W., Wiley, J., & Griffin, T. D. (2011). Test expectancy affects metacomprehension accuracy. British Journal of Educational Psychology, 81, 264–273.
   PubMed Web of Science ®Google Scholar
• Treagust, D. F., & Tsui, C. (Eds.) (2013). Multiple representations in biological education. Dordrecht, The Netherlands: Springer.
   Google Scholar
• Wang, Z., Sundararajan, N., Adesope, O. O., & Ardasheva, Y. (in press). Moderating the seductive details effect in multimedia learning with note-taking. British Journal of Educational Technology, doi:10.1111/bjet.12476
   Google Scholar
• Wiley, J., Griffin, T. D., & Thiede, K. W. (2005). Putting the comprehension in metacomprehension. Journal of General Psychology, 132, 408–428.
   Web of Science ®Google Scholar
• Wiley, J., Thiede, K. W., & Griffin, T. D. (2016). Improving metacomprehension with the situation-model approach. In Mokhtari, K., (Ed). Improving reading comprehension through metacognitive reading instruction for first and second language readers (pp. 93–110). Lanham, MD: Rowman & Littlefield.
   Google Scholar