Reader expertise and the literary significance of small-scale textual features in prose fiction
We use eye tracking to investigate the attention readers pay to different textual features to determine their significance in the appreciation of prose fiction. Previous research examined attention allocation to lexical and punctuation variants, and the impact on reading dynamics for the remainder of the text, demonstrating that readers notice both kinds of variants but assign less value to the latter (Carrol, Conklin, Guy, & Scott, 2016). Here, in two experiments, we examine two conditions that may affect attention allocation: We investigate the influence of reader expertise (Experiment 1) and whether performance is influenced by a task-specific “spot-the-difference” effect (Experiment 2). We found that expertise plays little role in readers’ greater sensitivity to lexical rather than punctuation changes, and that the advantage for lexical changes persisted when the time interval between exposures is increased. These results confirm earlier findings: that small-scale features may not possess the creative significance predicated of them by critics and text-editors.
Keywords: eye-tracking, prose-fiction, reader expertise, small-scale textual features, punctuation
Published online: 04 February 2020
[ p. 31 ]References
Bates, D., Maechler, M., Bolker, B., & Walker, S.
Bortolussi, M., & Dixon, P.
Carrol, G., Conklin, K., Guy, J., & Scott, R.
Chou, Y. M., Polansky, A. M., & Mason, R. L.
Conklin, K., Pellicer-Sánchez, A., & Carrol, G.
Filik, R., & Barber, E.
Goldman, S. R., McCarthy, K. S., & Burkett, C.
Gómez-Jiménez, E. M.
Guy, J., Scott, R., Conklin, K., & Carrol, G.
Graves, B., & Frederiksen, C. H.
Hakemulder, F., & van Peer, W.
Halliday, M. A. K.
Hill, R., & Murray, W.
Hirotani, M., Frazier, L., & Rayner, K.[ p. 32 ]
Hothorn, T., Bretz, F., & Westfall, P.
Hyönä, J., & Niemi, P.
Kaakinen, J. K., & Hyönä, J.
Lee, S., Lee, M., Park, H., Chang, M.-S., & Kwak, H. W.
Levy, B., Di Persio, R., & Hollingshead, A.
Levine, S., & Horton, W. S.
McCarthy, K. S.
R Core Team
(2017) R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. Retrieved from: https://www.R-project.org/
Sanford, A. J., & Filik, R.
Schotter, E., Bicknell, K., Howard, I., Levy, R., & Rayner, K.
Trueswell, J. C., Tanenhaus, M. K., & Garnsey, S. M.
Vipond, D., & Hunt, R. A.[ p. 33 ]
Ward, P., & Sturt, P.
Cited by other publications
Parente, Fabio, Kathy Conklin, Josephine M Guy & Rebekah Scott
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