The Effects of Processing Multimodal Texts in Print and Digitally on Comprehension and Calibration

References

• Ackerman, R., & Goldsmith, M. (2011). Metacognitive regulation of text learning: On screen versus on paper. Journal of Experimental Psychology: Applied, 17(1), 18–32. https://doi.org/10.1037/a0022086
   Google Scholar
• Alexander, P. A. (2013). Calibration: What is it and why it matters? An introduction to the special issue on calibrating calibration. Learning and Instruction, 24, 1–3. https://doi.org/10.1016/j.learninstruc.2012.10.003
   Web of Science ®Google Scholar
• Alexander, P. A., & Singer, L. M. (2017, October). The enduring power of print for learning in a digital world. The Conversation. https://theconversation.com/the-enduring-power-of-print-for-learning-in-a-digital-world-84352
   Google Scholar
• Alvermann, D. E., & Wilson, A. A. (2011). Comprehension strategy instruction for multimodal texts in science. Theory into Practice, 50(2), 116–124. https://doi.org/10.1080/00405841.2011.558436
   Web of Science ®Google Scholar
• Bartholomé, T., & Bromme, R. (2009). Coherence formation when learning from text and pictures: What kind of support for whom? Journal of Educational Psychology, 101(2), 282–293. https://doi.org/10.1037/a0014312
   Web of Science ®Google Scholar
• Bol, L., Hacker, D. J., O'Shea, P., & Allen, D. (2005). The influence of overt practice, achievement level, and explanatory style on calibration accuracy and performance. The Journal of Experimental Education, 73(4), 269–290. https://doi.org/10.3200/JEXE.73.4.269-290
   Web of Science ®Google Scholar
• Canham, M., & Hegarty, M. (2010). Effects of knowledge and display design on comprehension of complex graphics. Learning and Instruction, 20(2), 155–166. https://doi.org/10.1016/j.learninstruc.2009.02.014
   Web of Science ®Google Scholar
• Coiro, J. (2021). Toward a multifaceted heuristic of digital reading to inform assessment, research, practice, and policy. Reading Research Quarterly, 56(1), 9–31. https://doi.org/10.1002/rrq.302
   Web of Science ®Google Scholar
• Cromley, J. G., Weisberg, S. M., Dai, T., Newcombe, N. S., Schunn, C. D., Massey, C., & Merlino, F. J. (2016). Improving middle school science learning using diagrammatic reasoning. Science Education, 100(6), 1184–1213. https://doi.org/10.1002/sce.21241
   Web of Science ®Google Scholar
• Delgado, P., & Salmerón, L. (2021). The inattentive on-screen reading: Reading medium affects attention and reading comprehension under time pressure. Learning and Instruction, 71, 101396. https://doi.org/10.1016/j.learninstruc.20
   PubMed Web of Science ®Google Scholar
• Dunlosky, J., & Thiede, K. W. (2013). Four cornerstones of calibration research: Why understanding students' judgments can improve their achievement. Learning and Instruction, 24, 58–61. https://doi.org/10.1016/j.learninstruc.2012.05.002
   Web of Science ®Google Scholar
• Firetto, C. M., & Van Meter, P. N. (2018). Inspiring integration in college students reading multiple biology texts. Learning and Individual Differences, 65, 123–134. https://doi.org/10.1016/j.lindif.2018.05.011
   Web of Science ®Google Scholar
• Fischhoff, B., Slovic, P., & Lichtenstein, S. (1977). Knowing with certainty: The appropriateness of extreme confidence. Journal of Experimental Psychology: Human Perception and Performance, 3(4), 552–564. https://doi.org/10.1037/0096-1523.3.4.552
   Web of Science ®Google Scholar
• Fry, E. (1968). A readability formula that saves time. Journal of Reading, 11(7), 513–578. https://www.jstor.org/stable/40013635
   Google Scholar
• Glenberg, A. M., & Epstein, W. (1985). Calibration of comprehension. Journal of Experimental Psychology: Learning, Memory, and Cognition, 11(4), 702–718. https://doi.org/10.1037/0278-7393.11.1-4.702
   Google Scholar
• Glenberg, A. M., Meyer, M., & Lindem, K. (1987). Mental models contribute to foregrounding during text comprehension. Journal of Memory & Language, 26(1), 69–83. https://doi.org/10.1016/0749-596X(87)90063-5
   Web of Science ®Google Scholar
• Guo, D., Zhang, S., Wright, K. L., & McTigue, E. M. (2020). Do you get the picture? A meta-analysis of the effect of graphics on reading comprehension. AERA Open, 6(1), 233285842090169–233285842090120. https://doi.org/10.1177/2332858420901696
   Web of Science ®Google Scholar
• Gutierrez, A. P., & Schraw, G. (2015). Effects of strategy training and incentives on students’ performance, confidence, and calibration. The Journal of Experimental Education, 83(3), 386–404. https://doi.org/10.1080/00220973.2014.907230
   Web of Science ®Google Scholar
• Hartwig, M. K., & Dunlosky, J. (2014). The contribution of judgment scale to the unskilled-and-unaware phenomenon: How evaluating others can exaggerate over-(and under-) confidence. Memory & Cognition, 42(1), 164–173. https://doi.org/10.3758/s13421-013-0351-4
   PubMed Web of Science ®Google Scholar
• Hattie, J. (2013). Calibration and confidence: Where to next? Learning and Instruction, 24, 62–66. https://doi.org/10.1016/j.learninstruc.2012.05.009
   Web of Science ®Google Scholar
• Jewitt, C. (2008). Multimodality and literacy in school classrooms. Review of Research in Education, 32(1), 241–267. https://doi.org/10.3102/0091732X07310586
   Web of Science ®Google Scholar
• Koriat, A., Ma'ayan, H., & Nussinson, R. (2006). The intricate relationships between monitoring and control in metacognition: lessons for the cause-and-effect relation between subjective experience and behavior. Journal of Experimental Psychology: General, 135(1), 36–69.
   Google Scholar
• Kress, G. R., & Van Leeuwen, T. (1996). Reading images: The grammar of visual design. Psychology Press.
   Google Scholar
• Lauer, C. (2009). Contending with terms: “Multimodal” and “multimedia” in the academic and public spheres. Computers and Composition, 26(4), 225–239. https://doi.org/10.1016/j.compcom.2009.09.001
   Google Scholar
• León, S. P., Pantoja Vallejo, A., & Nelson, J. B. (2021). Variability in the accuracy of self-assessments among low, moderate, and high performing students in university education. Practical Assessment, Research, and Evaluation, 26(1), 16. https://doi.org/10.7275/6q91-az58
   Google Scholar
• Lin, L. M., Zabrucky, K. M., & Moore, D. (2002). Effects of text difficulty and adults' age on relative calibration of comprehension. The American Journal of Psychology, 115(2), 187–198. http://www.press.uillinois.edu/about/permission.html https://doi.org/10.2307/1423434
   PubMed Web of Science ®Google Scholar
• List, A., van Meter, P., Lombardi, D., & Kendeou, P. (2020). Loggers and conservationists: Navigating the multiple resource forest through the trees. In P. van Meter, A. List, D. Lombardi, & P. Kendeou (Eds.), Handbook of learning from multiple representations and perspectives. Routledge. https://doi.org/10.4324/9780429443961-1
   Google Scholar
• Liu, J. (2013). Visual Images interpretive strategies in multimodal texts. Journal of Language Teaching and Research, 4(6), 1259–1263. https://doi.org/10.4304/jltr.4.6.1259-1263
   Google Scholar
• Mangen, A., Walgermo, B. R., & Brønnick, K. (2013). Reading linear texts on paper versus computer screen: Effects on reading comprehension. International Journal of Educational Research, 58, 61–68. https://doi.org/10.1016/j.ijer.2012.12.002
   Web of Science ®Google Scholar
• Mason, L., Pluchino, P., Tornatora, M. C., & Ariasi, N. (2013a). An eye-tracking study of learning from science text with concrete and abstract illustrations. The Journal of Experimental Education, 81(3), 356–384. https://doi.org/10.1080/00220973.2012.727885
   Web of Science ®Google Scholar
• Mason, L., Tornatora, M. C., & Pluchino, P. (2013b). Do fourth graders integrate text and picture in processing and learning from an illustrated science text? Evidence from eye-movement patterns. Computers & Education, 60(1), 95–109. https://doi.org/10.1016/j.compedu.2012.07.011
   Web of Science ®Google Scholar
• Mayer, R. E. (2002). Multimedia learning. In B. Ross (Ed.), Psychology of learning and motivation (Vol. 41, pp. 85–139). Academic Press.
   Google Scholar
• Mayer, R. E., & Fiorella, L. (2014). 12 principles for reducing extraneous processing in multimedia learning: Coherence, signaling, redundancy, spatial contiguity, and temporal contiguity principles. In R. E. Mayer (Ed.), The Cambridge handbook of multimedia learning (pp. 279–315). Cambridge University Press.
   Google Scholar
• McCarthy, K. S., & McNamara, D. S. (2021). The multidimensional knowledge in text comprehension framework. Educational Psychologist, 56(3), 196–119. https://doi.org/10.1080/00461520.2021.1872379
   Web of Science ®Google Scholar
• McNamara, D. S., Graesser, A. C., & Louwerse, M. M. (2012). Sources of text difficulty: Across the ages and genres. In J. P. Sabatini, E. Albro, & T. O'Reilly (Eds.), Measuring up: Advances in how to assess reading ability (pp. 89–116). Rowman & Littlefield.
   Google Scholar
• Moreno, R., & Mayer, R. E. (1999). Cognitive principles of multimedia learning: The role of modality and contiguity. Journal of Educational Psychology, 91(2), 358–368. https://doi.org/10.1037/0022-0663.91.2.358
   Web of Science ®Google Scholar
• Nietfeld, J. L., & Schraw, G. (2002). The effect of knowledge and strategy training on monitoring accuracy. The Journal of Educational Research, 95(3), 131–142. https://doi.org/10.1080/00220670209596583
   Web of Science ®Google Scholar
• O’Neil, K. E. (2011). Reading pictures: Developing visual literacy for greater comprehension. The Reading Teacher, 65(3), 214–223. https://doi.org/10.1002/TRTR.01026
   Web of Science ®Google Scholar
• Pipkin, B., Trent, D. D., Hazlett, R., & Bierman, P. (2014). Geology and the environment (7th ed.). Brooks/Cole.
   Google Scholar
• Rose, D., & Dalton, B. (2009). Learning to read in the digital age. Mind, Brain, and Education, 3(2), 74–83. https://doi.org/10.1111/j.1751-228X.2009.01057.x
   Web of Science ®Google Scholar
• Scheiter, K., Schubert, C., Schüler, A., Schmidt, H., Zimmermann, G., Wassermann, B., Krebs, M.-C., & Eder, T. (2019). Adaptive multimedia: Using gaze-contingent instructional guidance to provide personalized processing support. Computers & Education, 139, 31–47. https://doi.org/10.1016/j.compedu.2019.05.005
   Web of Science ®Google Scholar
• Scheiter, K., Schüler, A., Gerjets, P., Huk, T., & Hesse, F. W. (2014). Extending multimedia research: How do prerequisite knowledge and reading comprehension affect learning from text and pictures. Computers in Human Behavior, 31, 73–84. https://doi.org/10.1016/j.chb.2013.09.022
   Web of Science ®Google Scholar
• Schwamborn, A., Thillmann, H., Opfermann, M., & Leutner, D. (2011). Cognitive load and instructionally supported learning with provided and learner-generated visualizations. Computers in Human Behavior, 27(1), 89–93. https://doi.org/10.1016/j.chb.2010.05.028
   Web of Science ®Google Scholar
• Serafini, F. (2011). Expanding perspectives for comprehending visual images in multimodal texts. Journal of Adolescent & Adult Literacy, 54(5), 342–350. https://doi.org/10.1598/JAAL.54.5.4
   Web of Science ®Google Scholar
• Serafini, F., & Ladd, S. M. (2008). The challenge of moving beyond the literal in literature discussion. Journal of Language and Literacy Education, 4(2), 6–20.
   Google Scholar
• Singer, L. M., & Alexander, P. A. (2017a). Reading across mediums: Effects of reading digital and print texts on comprehension and calibration. The Journal of Experimental Education, 85(1), 155–172. https://doi.org/10.1080/00220973.2016.1143794
   Web of Science ®Google Scholar
• Singer, L. M., & Alexander, P. A. (2017b). Reading on paper and digitally: What the past decades of empirical research reveal. Review of Educational Research, 87(6), 1007–1041. https://doi.org/10.3102/0034654317722961
   Web of Science ®Google Scholar
• Singer Trakhman, L. M., Alexander, P. A., & Berkowitz, L. (2019). Effects of processing time on comprehension and calibration in print and digital mediums. Journal of Experimental Education, 27, 101–115. https://doi.org/10.1080/00220973.2017.1411877
   Web of Science ®Google Scholar
• Singer Trakhman, L. M., Alexander, P. A., & Silverman, A. B. (2018). Profiling reading in print and digital mediums. Learning and Instruction, 57, 5–17. https://doi.org/10.1016/j.learninstruc.2018.04.001
   Web of Science ®Google Scholar
• Støle, H., Mangen, A., & Schwippert, K. (2020). Assessing children's reading comprehension on paper and screen: A mode-effect study. Computers & Education, 151, 103861. https://doi.org/10.1016/j.compedu.2020.103861
   Web of Science ®Google Scholar
• Tirso, R., Geraci, L., & Saenz, G. D. (2019). Examining underconfidence among high-performing students: A test of the False Consensus Hypothesis. Journal of Applied Research in Memory and Cognition, 8(2), 154–165. https://doi.org/10.1016/j.jarmac.2019.04.003
   Web of Science ®Google Scholar
• Unsworth, L., & Cléirigh, C. (2014). Multimodality and reading: The construction of meaning through image-text interaction. In C. Jewitt (Ed.), The handbook of multimodal analysis (pp. 176–188). Routledge.
   Google Scholar
• Urban, M., & Urban, K. (2021). Unskilled but aware of it? Cluster analysis of creative metacognition from preschool age to early adulthood. The Journal of Creative Behavior, 55(4), 937–945. https://doi.org/10.1002/jocb.499
   Web of Science ®Google Scholar
• Van Leeuwen, T. (2015). Multimodality. In D. Tannen, H. Hamilton, & D. Schiffrin (Eds.), The handbook of discourse analysis (2nd Ed., pp. 447–465). John Wiley & Sons.
   Google Scholar
• Van Meter, P. N., Cameron, C., & Waters, J. R. (2017). Effects of response prompts and diagram comprehension ability on text and diagram learning in a college biology course. Learning and Instruction, 49, 188–198. https://doi.org/10.1016/j.learninstruc.2017.01.003
   Web of Science ®Google Scholar
• Wickelgren, W. A. (1977). Speed-accuracy tradeoff and information processing dynamics. Acta Psychologica, 41(1), 67–85. https://doi.org/10.1016/0001-6918(77)90012-9
   Web of Science ®Google Scholar