2 Cognitive Studies May 1994 (Csikszentmihalyi, 1990) (Green & Brock, 2002) Csikszentmihalyi (1990). (Keller, Bless, Blomann, & Kleinböhl, 2011; Gaggi

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1 Cognitive Studies, 1(1), (May 1994) In reading, we are often engaged to the book, lose our self-awareness, transport ourselves into the narrative world, and have deep empathy for the characters in the books. These absorption phenomena have been characterized and classified based on reader s introspective report using the questionnaires. However this methodology relying on introspective reports alone may not be accurately enough to study the absorption: the readers in the absorption cannot reliably report their experiences, as they lose their self-awareness to some degree by definition. This motivates this study to build an alternative measures of absorption, which we can evaluate its reliability by its consistency across multiple subjective and objective measures of reader s states. We conducted two experiments by employing the first author as a subject in a natural and reader friendly situation. In the first experiment, we analyzed the cross correlation between reader s absorption ratings and statistics, CVR-R and fractal dimension, estimated from reader s heart rates. In the second experiment, we analyzed the relationship between reader s absorption ratings and bodily movements using the classification tree technique. The results of these two experiments suggest that the CVR-R and the fractal dimension estimated from heart rates, and the bodily movement can be used as alternative measures indicating the level of reader s absorption. Keywords: Reading, Absorption, Heart rates, Bodily movements Transportation (Green & Brock, 2000; Green & Carpenter, 2011) Identification (Cohen, 2001; De Graaf, Hoeken, Sanders, & Beentjes, 2012)Trait Ab- Describing temporal changes of absorption with reader s physical measures, by Miho Fuyama (Keio University), Shohei Hidaka (Japan Advanced Institute of Science and Technology). sorption (Tellegen & Atkinson, 1974) 1

2 2 Cognitive Studies May 1994 (Csikszentmihalyi, 1990) (Green & Brock, 2002) Csikszentmihalyi (1990). (Keller, Bless, Blomann, & Kleinböhl, 2011; Gaggioli, Cipresso, Serino, & Riva, 2013; Peifer, Schulz, Schächinger, Baumann, & Antoni, 2014) 1 1(Green & Brock, 2002; Cohen, 2001) 1 Keller et al. (2011), Peifer et al. (2014). D Mello, Chipman, and Graesser (2007) / 1.2

3 Vol. 1 No ( 1 ) ( 2 ) ( 3 ) (1) (2) 1.1 (3) (2) D Mello et al. (2007) (Keller et al., 2011; Gaggioli et al., 2013; Peifer et al., 2014) Keller et al. (2011), Gaggioli et al. (2013), Peifer et al. (2014)

4 4 Cognitive Studies May D Mello et al. (2007) (2013) / / No Polar RS800CXR-R R-R mybeat No.1 No.5 No.6 No

5 Vol. 1 No No.1 No No.8 No Table 1 Descriptive summary of the datasets obtained in Experiment 1. No / 10/ / / / / / / / 2/5 9 4/ / / / / / / / / / / ,-1,0,+1,+2) 5 D Mello et al. (2007) D Mello et al. (2007) (2013) D Mello et al. (2007) No.6 5 2

6 6 Cognitive Studies May Table 2 No Five most frequent bodily movements for each the absorption rating, -2 to 2. = = = = = Coefficient of Variation for R-R interval CVR-R 100 = R R 100 R R 100 R-R Hidaka and Kashyap (2013, 2014) (, 2007) Kantz and Schreiber (1997). / (, 2007). (Hidaka & Kashyap, 2013, 2014)

7 Vol. 1 No =0 Fig. 1 Cross correlation between the absorption ratings and CVR-Rs/fractal dimension Voss, Schulz, Schroeder, Baumert, and Caminal (2009) Hidaka and Kashyap (2013) p (Kantz & Schreiber, 1997),

8 8 Cognitive Studies May 1994 AIC Akaike s Information Criterion (Akaike, 1974) ) / 1)

$3 Moving averages of the absorption ratings and the fractal dimensions. -0.23-0.09 0.07 0.25-0.40-0.24 9 No.6 2 3 2 3 20 13 14 ( ) 60 1 2.2.5 No.$

9 Vol. 1 No Fig. 2 Moving averages of the absorption ratings and the CVR-Rs. 3 Fig. 3 Moving averages of the absorption ratings and the fractal dimensions No ( ) No.6 No.6 3 No

10 10 Cognitive Studies May No.6 Table 3 The correlation coefficients of the three pairs of variables for nine datasets. No CVR-R -0.05* -0.22* -0.04* -0.23* -0.12* -0.09* (-0.07*) -0.16* -0.22* -0.18* 0.15* 0.09* 0.07* 0.25* 0.10* 0.18* (0.11*) 0.23* 0.12* 0.11* CVR-R AIC No.7 No.9 AIC AIC AIClogL k AIC = 2(log L k) AIC AIC=n log 2 /n) +2 (n= AIC 4 No.7 No.9 3 No.8 No.7 No.8 2 AIC 4 AIC AIC Table 4 The results of model selection with AIC. 5 /AIC CVR-R + + CVR-R + CVR-R + + No * No * No * t p p.0001 No.8 AIC Table 5 The results of multiple regression analysis. CVR-R No.7 t No.8 t No.9 t p t No.7 No.9 No.7 No.8 9 AIC

11 Vol. 1 No AIC (Keller et al., 2011; Gaggioli et al., 2013; Peifer et al., 2014) 8 3 / / AIC No.8 No.9 No D Mello et al. (2007) (2013) No.6 No.7 No.6 7 2

12 12 Cognitive Studies May No Table 6 Example of the reader s bodily movements and the absorption ratings in the Data No.6. ( ) No.6 No No No ,-1,0,+1, No No =0 1 4 n n=10

13 Vol. 1 No No.6 No No.6 No.7 2-2() +2( ) Table 7 Frequency distributions of the absorption ratings No No % +2 19% D Mello et al. (2007) (2013) D Mello et al. (2007) (2013) Table 8. p<.05 * Results of the classification tree analysis % 55.1% p.0001) 4 No.7 1- No p <.000* <.000*

14 14 Cognitive Studies May No Fig. 4 A part of the classification tree of the Dataset No.6. 1 /

15 Vol. 1 No Kintsch (1988) Construction-Integration Zwaan, Langston, and Graesser (1995) Event-Indexing Gernsbacher (1997) Structure Building Structure Building Foundationlaying Mapping Shifting 3 (2015) (2015)

16 16 Cognitive Studies May 1994 Eco (1967) Green and Brock (2002) Flow 4.3 B Akaike, H. (1974). A new look at the statistical model identification. IEEE Transactions on Automatic Control, 19 (6), Cohen, J. (2001). Defining Identification: A Theoretical Look at the Identification of Audiences with Media Characters. Mass Communication & Society, 4 (3), Csikszentmihalyi, M. (1990). Flow: The psychology of optimal experience. New York: Harper and Row. De Graaf, A., Hoeken, H., Sanders, J., & Beentjes, J. W. J. (2012). Identification as a Mechanism of Narrative Persuasion. Communication Research, 39 (6), D Mello, S., Chipman, P., & Graesser, A. (2007). Posture as a predictor of learner s affective engagement. Proceedings of the 29th Annual Meeting of the Cognitive Science Society, Eco, U. (1967). Opera aperta. Milano: Bompiani. ( ) (2002)... (2015).., 5, III (2013). -. SKL-16-06, Gaggioli, A., Cipresso, P., Serino, S., & Riva, G. (2013). Psychophysiological correlates of flow during daily activities. Annual Review of Cybertherapy and Telemedicine 2013, Gernsbacher,M.A. (1997). Two decades of structure building. Discourse Processes, 23 (3), Green, M. C. & Brock, T. C. (2000). The role of transportation in the persuasiveness of public narratives. Journal of Personality and Social Psychology, 79 (5), Green, M. C. & Brock, T. C. (2002). In the mind s eye: Transportation imagery model of narrative persuasion. In M.C. Green, J.J. Strange, & T. C. Brock (Eds.), Narrative impact: Social and cognitive foundations, New York: Psychology Press. Green, M. C. & Carpenter, J. M. (2011). Transporting into narrative worlds: New directions for the scientific study of literature. Scientific Study of Literature, 1 (1), Hidaka, S. (2013). A computational model associating learning process, word attributes, and age of acquisition.. PLOS ONE, 8 (10), e Hidaka, S. & Kashyap, N. (2013). On the Estimation of Pointwise Dimension. arxiv, preprint arxiv: , Retrieved from

17 Vol. 1 No Hidaka, S. & Kashyap, N. (2014). The Generalist Approach to Frame Problems. Proceedings of The Third Asian Conference on Information Systems, Kantz, H. & Schreiber, T. (1997). Nonlinear Time Series Analysis. Cambridge, UK: Cambridge University Press. Keller, J., Bless, H., Blomann, F., & Kleinböhl, D. (2011). Physiological aspects of flow experiences: Skills-demand-compatibility effects on heart rate variability and salivary cortisol. Journal of Experimental Social Psychology, 47 (4), Kintsch, W. (1988). The role of knowledge in discourse comprehension: A constructionintegration model. Psychological Review, 95 (2), (2007). R-R. ( ), (4 )., :. Peifer, C., Schulz, A., Schächinger, H., Baumann,N., &Antoni,C.H. (2014). The relation of flow-experience and physiological arousal under stress - Can u shape it?. Journal of Experimental Social Psychology, 53, Tellegen, A. & Atkinson, G. (1974). Openness to absorbing and self-altering experiences( Absorption ), a trait related to hypnotic susceptibility. Journal of Abnormal Physchology, 83 (3), Voss, a., Schulz, S., Schroeder, R., Baumert, M., & Caminal, P. (2009). Methods derived from nonlinear dynamics for analysing heart rate variability. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 367 (1887), Young, L.-S. (1982). Dimension, entropy and Lyapunov exponents.ergodic Theory and Dynamical Systems, 2 (01), Zwaan, R. A., Langston, M. C., & Graesser, A. C. (1995). The Construction of Situation Models in Narrative Comprehension: An Event- Indexing Model. Psychological Science, 6 (5), A. (Young, 1982) Hidaka and Kashyap (2013, 2014) (Hidaka & Kashyap, 2013) dxr B(x, r) log B(x, r) d = lim r 0 log r ( ) λd x r x Weibull-gamma (Hidaka, 2013) P (r x n, d, λ) = dλn rx nd 1 exp λrx d (n 1)! (Hidaka & Kashyap, 2013) d, λ n- d Weibull-gamma AIC(Akaike, 1974) M (d 1, λ 1),..., (d M, λ M ) (x 1, x 2,..., x T ) (x t, x t+τ, x t+2τ,..., x t+nτ ) ˆd t τn τ 1, τ + 1 n 1, n + 1 τ = 50 50

18 18 Cognitive Studies May 1994 n = 6 (Received ) (Accepted ) () Indiana University 22 ( )

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23204.dvi Cognitive Studies, 23(2), 135-152. (June 2016) In reading, we are often engaged to the book, lose our self-awareness, transport ourselves into the narrative world, and have deep empathy for the characters