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Exploring the lack of a disfluency effect: evidence from eye movements

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Abstract

An eye-tracking study with 60 native Swedish speakers (18–30 years) was conducted to investigate the positive effects on learning outcomes predicted by the disfluency effect. Subtle low-pass filtering was used as a disfluency manipulation and compared with a control condition using regular text. The text was presented on four separate text presentation screens (TPSs), and eye movements were recorded. A free recall task was given 25 min later, and working memory capacity (WMC) was assessed to test if it would moderate learning outcomes. The disfluency manipulation had no effect on learning outcomes, total reading times on words or lines, first- or second-pass reading on lines, or average fixation durations. Moreover, the disfluency effect was not moderated by students’ WMC or self-reported prior knowledge of the topic. However, an adaptation to the disfluency manipulation was found. Total reading times on both words and lines were shorter in TPS 1 and 2 in the disfluency condition compared with the control condition, whereas reading times were longer in TPS 3 and 4. It is discussed if failures to replicate the disfluency effect arise from material features, with positive adaptations to disfluency (i.e., higher effort investment) possibly requiring more comprehensive materials.

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References

  • Baayen, R. H., Davidson, D. J., & Bates, D. (2008). Mixed-effects modeling with crossed random effects for subjects and items. Journal of Memory and Language, 59(4), 390–412. doi:10.1016/j.jml.2007.12.005.

    Article  Google Scholar 

  • Bates, D., Mächler, M., & Bolker, B. (2012). Fitting linear mixed-effects models using lme4. Journal of Statistical Software.

  • Becker, C. A., & Killion, T. H. (1977). Interaction of visual and cognitive effects in word recognition. Journal of Experimental Psychology: Human Perception and Performance, 3(3), 389–401. doi:10.1037/0096-1523.3.3.389.

    Google Scholar 

  • Bjork, R. A., Dunlosky, J., & Kornell, N. (2013). Self-regulated learning: beliefs, techniques, and illusions. Annual Review of Psychology, 64, 417–444. doi:10.1146/annurev-psych-113011-143823.

    Article  Google Scholar 

  • Chung, S. T. L., Jarvis, S. H., & Cheung, S.-H. (2007). The effect of dioptric blur on reading performance. Vision Research, 47(12), 1584–1594. doi:10.1016/j.visres.2007.03.007.

    Article  Google Scholar 

  • Clifton, C., Staub, A., & Rayner, K. (2007). Eye movements in reading words and sentences. In R. P. G. Van Gompel, M. H. Fischer, W. S. Murray, & R. L. Hill (Eds.), Eye movements: A window on mind and brain (pp. 341–371). Elsevier Ltd. http://doi.org/10.1016/b978-008044980-7/50017-3.

  • Conway, A. R. A., Kane, M. J., Bunting, M. F., Hambrick, D. Z., Wilhelm, O., & Engle, R. W. (2005). Working memory span tasks: a methodological review and user’s guide. Psychonomic Bulletin & Review, 12(5), 769–786. doi:10.3758/bf03196772.

    Article  Google Scholar 

  • Daneman, M., & Carpenter, P. A. (1980). Individual differences in working memory and reading. Journal of Verbal Learning and Verbal Behavior, 19(4), 450–466. doi:10.1016/S0022-5371(80)90312-6.

    Article  Google Scholar 

  • Daneman, M., & Merikle, P. M. (1996). Working memory and language comprehension: a meta-analysis. Psychonomic Bulletin & Review, 3(4), 422–433. doi:10.3758/BF03214546.

    Article  Google Scholar 

  • Diemand-Yauman, C., Oppenheimer, D. M., & Vaughan, E. B. (2011). Fortune favors the bold (and the italicized): effects of disfluency on educational outcomes. Cognition, 118(1), 111–115. doi:10.1016/j.cognition.2010.09.012.

    Article  Google Scholar 

  • Ehmke, C., & Wilson, S. (2007). Identifying web usability problems from eye-tracking data. In Proceedings of the 21st British HCI Group Annual Conference on People and Computers: HCI… but not as we know it. Volume 1 (pp. 119–128). British Computer Society. Retrieved from http://dl.acm.org/citation.cfm?id=1531294.1531311

  • Eitel, A., Scheiter, K., Schüler, A., Nyström, M., & Holmqvist, K. (2013). How a picture facilitates the process of learning from text: evidence for scaffolding. Learning and Instruction, 28, 48–63. doi:10.1016/j.learninstruc.2013.05.002.

    Article  Google Scholar 

  • Eitel, A., Kühl, T., Scheiter, K., & Gerjets, P. (2014). Disfluency meets cognitive load in multimedia learning: does harder-to-read mean better-to-understand? Applied Cognitive Psychology, 28(4), 488–501. doi:10.1002/acp.3004.

    Article  Google Scholar 

  • French, M. M. J., Blood, A., Bright, N. D., Futak, D., Grohmann, M. J., Hasthorpe, A.,... Tabor, J. (2013). Changing fonts in education: how the benefits vary with ability and dyslexia. The Journal of Educational Research, 106, 301–304. doi:10.1080/00220671.2012.736430.

  • Holcomb, P. J. (1993). Semantic priming and stimulus degradation: implications for the role of the N400 in language processing. Psychophysiology, 30(1), 47–61. doi:10.1111/j.1469-8986.1993.tb03204.x.

    Article  Google Scholar 

  • Hooge, I. T. C., & Erkelens, C. J. (1999). Peripheral vision and Oculomotor control during visual search. Vision Research, 39(8), 1567–1575. doi:10.1016/S0042-6989(98)00213-2.

    Article  Google Scholar 

  • Hyönä, J., Lorch, R. F., & Rinck, M. (2003). Eye movement measures to study global text processing. In R. Radach, J. Hyönä, & H. Deubel (Eds.), The mind’s eye: cognitive and applied aspects of eye movement research (pp. 313–334). Amsterdam: Elsevier Science. doi:10.1016/b978-044451020-4/50018-9.

    Chapter  Google Scholar 

  • Ilkowska, M., & Engle, R. W. (2010). Working memory capacity and self-regulation. In R. H. Hoyle (Ed.), Handbook of personality and self-regulation (pp. 265–290). Malden: Wiley-Blackwell. doi:10.1002/9781444318111.ch12.

    Google Scholar 

  • Jainta, S., Dehnert, A., Heinrich, S. P., & Jaschinski, W. (2011). Binocular coordination during reading of blurred and nonblurred text. Investigative Ophthalmology & Visual Science, 52(13), 9416–9424. doi:10.1167/iovs.11-8237.

    Article  Google Scholar 

  • Johnson, C. I., & Mayer, R. E. (2012). An eye movement analysis of the spatial contiguity effect in multimedia learning. Journal of Experimental Psychology: Applied, 18, 178–191. doi:10.1037/a0026923.

    Google Scholar 

  • Jordan, T. R., McGowan, V. A., & Paterson, K. B. (2012). Reading with a filtered fovea: the influence of visual quality at the point of fixation during reading. Psychonomic Bulletin & Review, 19(6), 1078–1084. doi:10.3758/s13423-012-0307-x.

    Article  Google Scholar 

  • Kane, M. J., Bleckley, M. K., Conway, A. R. A., & Engle, R. W. (2001). A controlled-attention view of working-memory capacity. Journal of Experimental Psychology: General, 130(2), 169–183. doi:10.1037//0096-3445.130.2.169.

    Article  Google Scholar 

  • Kühl, T., & Eitel, A. (in press). Effects of disfluency on cognitive and metacognitive processes and outcomes. Metacognition and Learning.

  • Legge, G. E., & Cheung, S. (2004). 49.1: Invited Paper: Psychophysics of reading: Implications for displaying text. In SID Symposium Digest of Technical Papers (Vol. 35, No. 1, pp. 1359-1361). Society for Information Display. Blackwell Publishing Ltd. doi:10.1889/1.1825762

  • Legge, G. E., Pelli, D. G., Rubin, G. S., & Schleske, M. M. (1985). Psychophysics of reading: I. Normal vision. Vision Research, 25(2), 239–252. doi:10.1016/0042-6989(85)90117-8.

    Article  Google Scholar 

  • Lehmann, Goussios, C., & Seufert, T. (in press). Working memory capacity and disfluency effect: An aptitude-treatment-interaction study. Metacognition and Learning.

  • Mason, L., Tornatora, M. C., & Pluchino, P. (2013). Do fourth graders integrate text and picture in processing and learning from an illustrated science text? Evidence from eye-movement patterns. Computers & Education, 60, 95–109. doi:10.1016/j.compedu.2012.07.011.

    Article  Google Scholar 

  • Mautone, P. D., & Mayer, R. E. (2001). Signaling as a cognitive guide in multimedia learning. Journal of Educational Psychology, 93, 377. doi:10.1037/0022-0663.93.2.377.

    Article  Google Scholar 

  • Meyer, A., Frederick, S., Burnham, T. C., Guevara Pinto, J. D., Boyer, T. W., Ball, L. J., & Schuldt, J. P. (2015). Disfluent fonts don’t help people solve math problems. Journal of Experimental Psychology: General, 144(2), e16–e30. doi:10.1037/xge0000049.

    Article  Google Scholar 

  • R Development Core Team. (2014). R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. Retrieved from: http://www.r-project.org/. Retrieved from http://www.r-project.org/ (Version 3.0.3)

  • Rayner, K. (1998). Eye movements in reading and information processing: 20 years of research. Psychological Bulletin, 124(3), 372–422. doi:10.1037/0033-2909.124.3.372.

    Article  Google Scholar 

  • Rayner, K. (2009). Eye movements and attention in reading, scene perception, and visual search. The Quarterly Journal of Experimental Psychology, 62(8), 1457–1506. doi:10.1080/17470210902816461.

    Article  Google Scholar 

  • Rayner, K., & Duffy, S. A. (1986). Lexical complexity and fixation times in reading: effects of word frequency, verb complexity, and lexical ambiguity. Memory & Cognition, 14(3), 191–201. doi:10.3758/bf03197692.

    Article  Google Scholar 

  • Rayner, K., Smith, T. J., Malcolm, G. L., & Henderson, J. M. (2009). Eye movements and visual encoding during scene perception. Psychological Science, 20(1), 6–10. doi:10.1111/j.1467-9280.2008.02243.x.

    Article  Google Scholar 

  • Rehder, B., & Hoffman, A. B. (2005). Eyetracking and selective attention in category learning. Cognitive Psychology, 51(1), 1–41. doi:10.1016/j.cogpsych.2004.11.001.

    Article  Google Scholar 

  • Rehder, B., Colner, R. M., & Hoffman, A. B. (2009). Feature inference learning and eyetracking. Journal of Memory and Language, 60(3), 393–419. doi:10.1016/j.jml.2008.12.001.

    Article  Google Scholar 

  • Reingold, E. M., & Rayner, K. (2006). Examining the word identification stages hypothesized by the E-Z reader model. Psychological Science, 17(9), 742–746. doi:10.1111/j.1467-9280.2006.01775.x.

    Article  Google Scholar 

  • Scheiter, K., & Eitel, A. (2015). Signals foster multimedia learning by supporting integration of highlighted text and diagram elements. Learning and Instruction, 36, 11–26. doi:10.1016/j.learninstruc.2014.11.002.

    Article  Google Scholar 

  • Schwonke, R., Berthold, K., & Renkl, A. (2009). How multiple external representations are used and how they can be made more useful. Applied Cognitive Psychology, 23, 1227–1243. doi:10.1002/acp.1526.

    Article  Google Scholar 

  • Unsworth, N., & Engle, R. W. (2005). Individual differences in working memory capacity and learning: evidence from the serial reaction time task. Memory & Cognition, 33(2), 213–220. doi:10.3758/bf03195310.

    Article  Google Scholar 

  • Unsworth, N., Heitz, R. P., Schrock, J. C., & Engle, R. W. (2005). An automated version of the operation span task. Behavior Research Methods, 37(3), 498–505. doi:10.3758/BF03192720.

    Article  Google Scholar 

  • Van Merriënboer, J. J. G., & Sluijsmans, D. M. A. (2009). Toward a synthesis of cognitive load theory, four-component instructional design, and self-directed learning. Educational Psychology Review, 21, 55–66. doi:10.1007/s10648-008-9092-5.

    Article  Google Scholar 

  • Yue, C. L., Castel, A. D., & Bjork, R. A. (2013). When disfluency is—and is not—a desirable difficulty: the influence of typeface clarity on metacognitive judgments and memory. Memory & Cognition, 41, 229–241. doi:10.3758/s13421-012-0255-8.

    Article  Google Scholar 

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Acknowledgments

This research has been funded by a grant from the Marcus och Amalia Wallenberg Stiftelse for the project “EyeLearn: Using visualizations of eye movements to enhance metacognition, motivation and learning.”

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Authors and Affiliations

  1. Centre for Languages and Literature and The Humanities Lab, Lund University, Box 201, SE-22100, Lund, Sweden

    Alexander Strukelj

  2. Leibniz-Institut für Wissensmedien and Eberhard Karls University of Tübingen, Tübingen, Germany

    Katharina Scheiter

  3. The Humanities Lab, Lund University, Lund, Sweden

    Marcus Nyström & Kenneth Holmqvist

Authors
  1. Alexander Strukelj
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  2. Katharina Scheiter
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  3. Marcus Nyström
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  4. Kenneth Holmqvist
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Corresponding author

Correspondence to Alexander Strukelj.

Appendices

Appendix 1: stimuli

Text was given in Swedish to participants, on four separate TPSs. Each TPS is indicated below.

TPS 1

In order to achieve lift, the airplane must move forward. As the airplane moves forward, its wings cut through the air. This allows the air to flow over the wing. The air hitting the front of the wing separates. Some air flows over the wing and some flows under the wing. As the air moves across the wing, the air pushes directly against the wing, or perpendicular to the surface of the wing. The air eventually meets up again at the back of the wing.

TPS 2

Air flows across the top surface of the wing differently than it flows across the bottom surface. The air flowing over the top of the wing has a longer distance to travel in the same amount of time as the air flowing under the wing. As a result, air traveling over the curved top of the wing flows faster than the air that flows under the bottom of the wing.

TPS 3

As a result of the air on the top of the wing traveling faster, the air pressure on the top surface of the wing differs from that on the bottom of the wing because air pressure decreases when air moves faster. As a result, the pressure on the top part of the wing decreases. The top surface of the wing now has less pressure exerted against it than the bottom surface of the wing.

TPS 4

The downward force of the faster-moving air on the top of the wing is not as great as the upward force of the slower moving air under the wing. This creates more upwards-directed force on the wing than downwards-directed force. This results in lift for the airplane, which can take off.

Appendix 2: core idea units in the free recall task

  1. 1.

    The upper surface of the wing is more curved (or longer).

  2. 2.

    The bottom surface is less curved (or shorter).

  3. 3.

    Air flows faster over the top surface of the wing (or air flowing over the top surface of the wing has a longer distance to travel in the same amount of time).

  4. 4.

    Air traveling over the bottom surface of the wing is slower (or has less distance to travel).

  5. 5.

    The top surface of the wing has less pressure (or pressure on the top of the wing decreases, or air on the top of the wing gets more spread out, or the downward force is not as great).

  6. 6.

    The bottom of the wing has more pressure (or the upward force is greater).

  7. 7.

    There is a net upward force on the wing, a lift.

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Strukelj, A., Scheiter, K., Nyström, M. et al. Exploring the lack of a disfluency effect: evidence from eye movements. Metacognition Learning 11, 71–88 (2016). https://doi.org/10.1007/s11409-015-9146-2

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  • DOI: https://doi.org/10.1007/s11409-015-9146-2

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