Advertisement

Frontiers of Education in China

, Volume 14, Issue 1, pp 90–116 | Cite as

Chinese EFL Learners’ Phonetics Learning Guided by Visuospatial Cues through the Medium of Mobile Phones

  • Huiyu YangEmail author
Research Article

Abstract

The relevant studies using a cross sectional view of speech organs supplemented with visuospatial cues and verbal text to explore EFL learners’ learning effectiveness and behavior through mobile devices when learning English phonetics are scarce. This study was attempted to investigate whether the presence of visuospatial cues can benefit EFL learners with different levels of prior knowledge in learning English phonetics through mobile devices. The present study investigated the interaction between the experimental condition and the learners’ prior knowledge on their task performances and cognitive load ratings. Fifty-six English as a foreign language (EFL) learners recruited from two sections of a linguistics course participated in the experiment. First, their background knowledge concerning English phonetics was evaluated to determine their prior knowledge level. Then, they were randomly assigned into two experimental conditions—picture-plus-text and picture-plus-text-plus-cueing. After the experimental treatment, the participants were administered retention and transfer tests as well as cognitive load measurement. Experimental treatment and prior knowledge were the independent variables, while retention test, transfer test, study time, and number of clicks were the dependent variables. The results of the present study emphasized the importance of visuospatial cues on inducing deep cognitive processing as indicated by the learners’ test performance and study patterns.

Keywords

cognitive load theory signaling principle visuospatial cueing mobile phone prior knowledge 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Amadieu, F., Mariné, C., & Laymay, C. (2011). The attention-guiding effect and cognitive load in the comprehension of animations. Computers in Human Behavior, 27(1), 36–40. doi:  https://doi.org/10.1016/j.chb.2010.05.009 CrossRefGoogle Scholar
  2. Ari, F., Flores, R., Inan, F. A., Cheon, J., Crooks, S. M., Paniukov, D., & Kurucay, M. (2014). The effects of verbally redundant information on student learning: An instance of reverse redundancy. Computers & Education, 76, 199–204. doi:  https://doi.org/10.1016/j.compedu.2014.04.002 CrossRefGoogle Scholar
  3. Boucheix, J. M., & Guignard, H. (2005). What animated illustrations conditions can improve technical document comprehension in young students? Format, signaling and control of the presentation. European Journal of Psychology of Education, 20(4), 369–388. doi:  https://doi.org/10.2307/23420384 CrossRefGoogle Scholar
  4. Boucheix, J. M., & Lowe, R. K. (2010). An eye tracking comparison of external pointing cues and internal continuous cues in learning with complex animations. Learning and Instruction, 20, 123–135. doi:  https://doi.org/10.1016/j.learninstruc.2009.02.015 CrossRefGoogle Scholar
  5. Boucheix, J. M., Lowe, R. K., Putri, D. K., & Groff, J. (2013). Cueing animations: Dynamic signaling aids information extraction and comprehension. Learning and Instruction, 25, 71–84. doi:  https://doi.org/10.1016/j.learninstruc.2012.11.005 CrossRefGoogle Scholar
  6. Crooks, S. M., Cheon, J., Inan, F., Ari, F., & Flores, R. (2012). Modality and cueing in multimedia learning: Examining cognitive and perceptual explanations for the modality effect. Computers in Human Behavior, 28(3), 1063–1071. doi:  https://doi.org/10.1016/j.chb.2012.01.010 CrossRefGoogle Scholar
  7. Hegarty, M., & Just, M. A. (1993). Constructing mental models of machines from text and diagrams. Journal of Memory and Language, 32(6), 717–742. doi:  https://doi.org/10.1006/jmla.1993.1036 CrossRefGoogle Scholar
  8. Hegarty, M., Kriz, S., & Cate, C. (2003). The roles of mental animations and external animations in understanding mechanical systems. Cognition and Instruction, 21(4), 325–360. doi:  https://doi.org/10.2307/3233804 CrossRefGoogle Scholar
  9. Horz, H., & Schnotz, W. (2010). Cognitive load in learning with multiple representations. In J. L. Plass, R. Moreno, & R. Brunken (Eds.), Cognitive load theory (pp. 229–252). New York, NY: Cambridge University Press.Google Scholar
  10. Huk, T., Steinke, M., & Floto, C. (2010). The educational value of visual cues and 3D-representational format in a computer animation under restricted and realistic conditions. Instructional Science, 38(5), 455–469. doi:  https://doi.org/10.2307/23372467 CrossRefGoogle Scholar
  11. Imhof, B., Scheiter, K., Edelmann, J., & Gerjets, P. (2013). Learning about locomotion patterns: Effective use of multiple pictures and motion indication arrows. Computers & Education, 65, 45–55. doi:  https://doi.org/10.1016/j.compedu.2013.01.017 CrossRefGoogle Scholar
  12. Inan, F. A., Crooks, S. M., Cheon, J., Ari, F., Flores, R., Kurucay, M., & Paniukov, D. (2015). The reverse modality effect: Examining student learning from interactive computer-based instruction. British Journal of Educational Technology, 46(1), 123–130. doi:  https://doi.org/10.1111/bjet.12129 CrossRefGoogle Scholar
  13. Jamet, E. (2014). An eye-tracking study of cueing effects in multimedia learning. Computers in Human Behavior, 32, 47–53. doi:  https://doi.org/10.1016/j.chb.2013.11.013 CrossRefGoogle Scholar
  14. Jamet, E., Gavota, M., & Quaireau, C. (2008). Attention guiding in multimedia learning. Learning and Instruction, 18(2), 135–145. doi:  https://doi.org/10.1016/j.learninstruc.2007.01.011 CrossRefGoogle Scholar
  15. Jian, Y. C., Wu, C. J., & Su, J. H. (2014). Learners’ eye movements during construction of mechanical kinematic representations from static diagrams. Learning and Instruction, 32, 51–62. doi:  https://doi.org/10.1016/j.learninstruc.2014.01.005 CrossRefGoogle Scholar
  16. Kalyuga, S., Chandler, P., & Sweller, J. (1999). Managing split-attention and redundancy in multimedia instruction. Applied Cognitive Psychology, 13(4), 351–371.CrossRefGoogle Scholar
  17. de Koning, B. B., Tabbers, H. K., Rikers, R. M. J. P., & Paas, F. (2007). Attention cueing as a means to enhance learning from an animation. Applied Cognitive Psychology, 21(6), 731–746. doi:  https://doi.org/10.1002/acp.1346 CrossRefGoogle Scholar
  18. de Koning, B. B., Tabbers, H. K., Rikers, R. M. J. P., & Paas, F. (2009). Towards a framework for attention cueing in instructional animations: Guidelines for research and design. Educational Psychology Review, 21(2), 113–140. doi:  https://doi.org/10.1007/s10648-009-9098-7 CrossRefGoogle Scholar
  19. de Koning, B. B., Tabbers, H. K., Rikers, R. M. J. P., & Paas, F. (2010a). Attention guidance in learning from a complex animation: Seeing is understanding?. Learning and Instruction, 20(2), 111–122. doi:  https://doi.org/10.1016/j.learninstruc.2009.02.010 CrossRefGoogle Scholar
  20. de Koning, B. B., Tabbers, H. K., Rikers, R. M. J. P., & Paas, F. (2010b). Learning by generating vs. receiving instructional explanations: Two approaches to enhance attention cueing in animations. Computers & Education, 55(2), 681–691. doi:  https://doi.org/10.1016/j.compedu.2010.02.027 CrossRefGoogle Scholar
  21. de Koning, B. B., Tabbers, H. K., Rikers, R. M. J. P., & Paas, F. (2011a). Attention cueing in an instructional animation: The Role of presentation speed. Computers in Human Behavior, 27(9), 41–15. doi:  https://doi.org/10.1016/j.chb.2010.05.010 CrossRefGoogle Scholar
  22. de Koning, B. B., Tabbers, H. K., Rikers, R. M. J. P., & Paas, F. (2011b). Improved effectiveness of cueing by self-explanations when learning from a complex animation. Applied Cognitive Psychology, 25(2), 183–194. doi:  https://doi.org/10.1002/acp.1661 CrossRefGoogle Scholar
  23. Kriz, S., & Hegarty, M. (2007). Top-down and bottom-up influences on learning from animation. International Journal of Human-Computer Studies, 65(11), 911–930. doi:  https://doi.org/10.1016/j.ijhcs.2007.06.005 CrossRefGoogle Scholar
  24. Lin, L., & Atkinson, R. K. (2011). Using animations and visual cueing to support learning and scientific concepts and processes. Computers & Education, 56(3), 650–658. doi:  https://doi.org/10.1016/j.compedu.2010.10.00 CrossRefGoogle Scholar
  25. Liu, T. C., Lin, Y. C., & Paas, F. (2013). Effects of cues and real objects on learning in a mobile device supported environment. British Journal of Educational Technology, 44(3), 386–399. doi:  https://doi.org/10.1111/j.1467-8535.2012.01331.x CrossRefGoogle Scholar
  26. Lowe, R. K., & Boucheix, J. M. (2008). Supporting relational processing in complex animated diagrams. In G. Stapleton, J. Howse, & J. Lee (Eds.), Diagrammatic representation and inference (pp. 391–394). Berlin, Germany: Springer.CrossRefGoogle Scholar
  27. Lowe, R. K., & Boucheix, J. M. (2011). Cueing complex animations: Does direction of attention foster learning processes?. Learning and Instruction, 21(5), 650–663. doi:  https://doi.org/10.1016/j.learninstruc.2011.02.002 CrossRefGoogle Scholar
  28. Lowe, R. K., & Boucheix, J. M. (2012). Dynamic diagrams: A composition alternative. In P. Cox, B. Plimmer, & P. Rogers (Eds.), Diagrammatic representation and inference. Diagrams 2012. Lecture Notes in Computer Science. Berlin, Germany: Springer.Google Scholar
  29. Lowe, R. K., & Boucheix, J. M. (2016). Principled animation design improves comprehension of complex dynamics. Learning and Instruction, 45, 72–84. doi:  https://doi.org/10.1016/j.learninstruc.2016.06.005 CrossRefGoogle Scholar
  30. Mautone, P. D., & Mayer, R. E. (2001). Signaling as a cognitive guide in multimedia learning. Journal of Educational Psychology, 93(2), 377–389. doi:  https://doi.org/10.1037/0022-0663.93.2.377 CrossRefGoogle Scholar
  31. Mayer, R. E. (2009). Multimedia learning (2nd ed.). Cambridge, MA: Cambridge University Press.CrossRefGoogle Scholar
  32. Mayer, R. E., & Moreno, R. (2010). Techniques that reduce extraneous cognitive load and manage intrinsic cognitive load during multimedia learning. In J. L. Plass, R. Moreno, & R. Brunken (Eds.), Cognitive load theory (pp. 131–152). New York, NY: Cambridge University Press.CrossRefGoogle Scholar
  33. Moreno, R. (2007). Optimizing learning from animations by minimizing cognitive load: Cognitive and affective consequences of signaling and segmentation methods. Applied Cognitive Psychology, 21(6), 765–781. doi:  https://doi.org/10.1002/acp.1348 CrossRefGoogle Scholar
  34. Ozcelik, E., Karakus, T., Kursun, E., & Cagiltay, K. (2009). An eye-tracking study of how color coding affects multimedia learning. Computers and Education, 53(2), 445–153. doi:  https://doi.org/10.1016/j.compedu.2009.03.002 CrossRefGoogle Scholar
  35. Ozcelik, E., Arslan-Ari, I., & Cagiltay, K. (2010). Why does signaling enhance multimedia learning? Evidence from eye movements. Computers in Human Behavior, 26(1), 110–117. doi:  https://doi.org/10.1016/j.chb.2009.09.001 CrossRefGoogle Scholar
  36. Paas, F. (1992). Training strategies for attaining transfer of problem-solving skill in statistics: A cognitive load approach. Journal of Educational Psychology, 84(4), 429–434. doi:  https://doi.org/10.1037/0022-0663.84.4.429 CrossRefGoogle Scholar
  37. Schneider, S., Beege, M., Nebel, S., & Rey, G. D. (2018). A meta-analysis of how signaling affects learning with media. Educational Research Review, 23, 1–24. doi:  https://doi.org/10.1016/j.edurev.2017.11.001 CrossRefGoogle Scholar
  38. Wu, M. L., & Tu, J. T. (2006). SPSS 与统计应用分析 [SPSS & the application and analysis of statistics]. 台北, 中国: 五南图书 [Taipei, China: Wu-Nan Book].Google Scholar

Copyright information

© Higher Education Press and Springer-Verlag GmbH Germany 2019

Authors and Affiliations

  1. 1.Department of EnglishGuangxi Normal UniversityGuilinChina

Personalised recommendations