Abstract
When users interact with smart phones, the issue of fluency can influence their experience. However, there has been no previous clear definition and structure of smart phone fluency. The objective of this study is to confirm the factors influencing smart phone fluency and identify operational problems that affect smart phone fluency. A large-scale questionnaire survey was conducted, and 637 questionnaires were collected. We found that fluency is the most important feature of an easy-to-use smart phone. Moreover, the results confirmed the six factors of smart phone fluency: response delay, simplicity, operation error rate, connection, hardware, and visual experience. We also found that there were significant differences in the importance evaluation of visual experience and operation error rate among different age groups. In addition, opening the application, using the application, and opening the browser were the three operations in which people had the least fluent experiences. This study successfully confirmed the elements of smart phone fluency and contributed substantially to future smart phone design to shape a better user experience.
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References
Al-Showarah, S.A.: Dynamic recognition for user age-group classification using hand-writing based finger on smartphones. In: 2019 10th International Conference on Information and Communication Systems, pp. 140–146. IEEE (2019)
Agost, M.J., Vergara, M.: Relationship between meanings, emotions, product preferences and personal values. Application to ceramic tile floorings. Appl. Ergon. 45(4), 1076–1086 (2014). https://doi.org/10.1016/j.apergo.2014.01.008
Csikszentmihalyi, M., Mihaly, C.: Flow and the Foundations of Positive Psychology. Springer, New York (2014). https://doi.org/10.1007/978-94-017-9088-8
Dufau, S., et al.: Smart phone, smart science: how the use of smartphones can revolutionize research in cognitive science. Plos One 6(9), e24974 (2011). https://doi.org/10.1371/journal.pone.0024974
Galletta, D.F., Henry, R., McCoy, S., Polak, P.: Web site delays: how tolerant are users? J. Assoc. Inf. Syst. 5(1), 1 (2004)
Garcia-Ceja, E., Brena, R., Galván-Tejada, C.E.: Contextualized hand gesture recognition with smartphones. In: Martínez-Trinidad, J.F., Carrasco-Ochoa, J.A., Olvera-Lopez, J.A., Salas-Rodríguez, J., Suen, C.Y. (eds.) MCPR 2014. LNCS, vol. 8495, pp. 122–131. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-07491-7_13
Hagiya, T., Yazaki, T., Horiuchi, T., Kato, T.: Typing tutor: automatic error detection and instruction in text entry for elderly people. In: MobileHCI 2015 - Proceedings of the 17th International Conference on Human-Computer Interaction with Mobile Devices and Services Adjunct, pp. 696–703 (2015). https://doi.org/10.1145/2786567.2793690
Hassenzahl, M.: User experience (UX): towards an experiential perspective on product quality. Paper presented at the IHM (2008). https://doi.org/10.1145/1512714.1512717
Hassenzahl, M.: The thing and i: understanding the relationship between user and product. In: Blythe, M., Monk, A. (eds.) Funology 2. HIS, pp. 301–313. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-68213-6_19
Hohenstein, J., Khan, H., Canfield, K., Tung, S., Perez Cano, R.: Shorter wait times: the effects of various loading screens on perceived performance. In: Conference on Human Factors in Computing Systems – Proceedings, vol. 7, no. 12, pp. 3084–3090 (2016)
Jain, R., Bose, J., Arif, T.: Contextual adaptive user interface for android devices. In: 2013 Annual IEEE India Conference. IEEE (2013)
Jung, E.S., Im, Y.: Touchable area: an empirical study on design approach considering perception size and touch input behavior. Int. J. Ind. Ergon. 49, 21–30 (2015). https://doi.org/10.1016/j.ergon.2015.05.008
Kolly, S., Wattenhofer, R., Welten, S.: A personal touch: Recognizing users based on touch screen behavior. In: Proceedings of the 3rd International Workshop on Sensing Applications on Mobile Phones, PhoneSense 2012 - In Conjunction with ACM SenSys (2012). https://doi.org/10.1145/2389148.2389149
Law, E.L.C., van Schaik, P., Roto, V.: Attitudes towards user experience (UX) measurement. Int. J. Hum. Comput. Stud. 72(6), 526–541 (2014). https://doi.org/10.1016/j.ijhcs.2013.09.006
Li, J.W.: Evaluation system research and implementation of the smart phone user experience. Beijing University of Posts and Telecommunications, Beijing (2015). (Chinese)
Liu, X.Z., Ge, Y., Wang, C., Zhang, Q., Qu. W.N.: Dimension of smart phone fluency: a focus group interview (Submitted)
Nakagawa, T., Uwano, H.: Usability differential in positions of software keyboard on smartphone. In: 1st IEEE Global Conference on Consumer Electronics 2012, GCCE 2012, pp. 304–308 (2012)
Nguyen, D.T., Zhou, G., Xing, G.: Video: study of storage impact on smartphone application delay. In: MobiSys 2014 - Proceedings of the 12th Annual International Conference on Mobile Systems, Applications, and Services, p. 389. ACM (2014)
Norman, D., Miller, J., Henderson, A.: What you see, some of what's in the future, and how we go about doing it: HI at Apple Computer. Paper presented at the Conference Companion on Human Factors in Computing Systems (1995)
Oppenheimer, D.M.: The secret life of fluency. Trends Cogn. Sci. 12(6), 237–241 (2008). https://doi.org/10.1016/j.tics.2008.02.014
Park, B.-W., Lee, K.: A pilot study to analyze the effects of user experience and device characteristics on the customer satisfaction of smartphone users. In: Kim, T.-h, Adeli, H., Robles, R.J., Balitanas, M. (eds.) UCMA 2011. CCIS, vol. 151, pp. 421–427. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-20998-7_50
Ramsay, J., Barbesi, A., Preece, J.: A psychological investigation of long retrieval times on the World Wide Web. Interact. Comput. 10(1), 77–86 (1998). https://doi.org/10.1016/S0953-5438(97)00019-2
Ren, H.B., Zhou, J., Feng, W.Q.: Evaluation of the smart phone user experience based on MTS. Packag. Eng. (2017)
Sauer, J., Sonderegger, A.: The influence of prototype fidelity and aesthetics of design in usability tests: effects on user behaviour, subjective evaluation and emotion. Appl. Ergon. 40(4), 670–677 (2009). https://doi.org/10.1016/j.apergo.2008.06.006
Schleifer, L.M., Iii, B.C.A.: System response time and method of pay: stress effects in computer-based tasks. Int. J. Hum.-Comput. Interact. 1(1), 17 (1989)
Seva, R.R., Duh, H.B.L., Helander, M.G.: The marketing implications of affective product design. Appl. Ergon. 38(6), 723–731 (2007). https://doi.org/10.1016/j.apergo.2006.12.001
Seva, R.R., Gosiaco, K.G.T., Santos, M.C.E.D., Pangilinan, D.M.L.: Product design enhancement using apparent usability and affective quality. Appl. Ergon. 42(3), 511–517 (2011). https://doi.org/10.1016/j.apergo.2010.09.009
Shi., F.P.: Research on the model of consumer satisfaction. Jinan University (2005). (Chinese)
Si, Y.Q., Liu, L.: Study on the Influencing factors of the intelligent mobile phone user experience. Software 36(3), 111–115 (2015). (Chinese)
Szameitat, A.J., Rummel, J., Szameltat, D.P., Sterr, A.: Behavioral and emotional consequences of brief delays in human-computer interaction. Int. J. Hum. Comput. Stud. 67(7), 561–570 (2009). https://doi.org/10.1016/j.ijhcs.2009.02.004
Thomas, B.H., Calder, P.: Supporting cartoon animation techniques in direct manipulation graphical user interfaces. Inf. Softw. Technol. 47(5), 339–355 (2005). https://doi.org/10.1016/j.infsof.2004.09.003
van Kuijk, J., van Driel, L., van Eijk, D.: Usability in product development practice; an exploratory case study comparing four markets. Appl. Ergon. 47, 308–323 (2015). https://doi.org/10.1016/j.apergo.2014.10.007
Verwey, W.B.: Diminished motor skill development in elderly: indications for limited motor chunk use. Acta Physiol. 134(2), 206–214 (2010). https://doi.org/10.1016/j.actpsy.2010.02.001
Voelcker-Rehage, C.: Motor-skill learning in older adults—a review of studies on age-related differences. Eur. Rev. Aging Phys. Act. 5(1), 5–16 (2008). https://doi.org/10.1007/s11556-008-0030-9
Walsh, T., Nurkka, P., Walsh, R.: Cultural differences in smartphone user experience evaluation. Paper presented at the International Conference on Mobile & Ubiquitous Multimedia (2010)
Wang, C.Y., Chu, W.-C., Chen, H.-R., Hsu, C.-Y., Chen, M.: EverTutor: automatically creating interactive guided tutorials on smartphones by user demonstration. In: Conference on Human Factors in Computing Systems – Proceedings (2014). https://doi.org/10.1145/2556288.2557407
Winkielman, P., Cacioppo, J.T.: Mind at ease puts a smile on the face: psychophysiological evidence that processing facilitation elicits positive affect. J. Pers. Soc. Psychol. 81(6), 989–1000 (2001). https://doi.org/10.1037//0022-3514.81.6.989
Yan, Z., Niu, S., Wang, S.: Research on user experience evaluation methods of smartphone based on fuzzy theory. Paper presented at the International Conference on Intelligent Human-machine Systems & Cybernetics (2015)
Funding
This study was supported by grants from the National Key Research and Development Plan of China (2017YFB0802800); the National Natural Science Foundation of China (Grants No. 32071066, 32071064, 31771225, U1736220, 71971073).
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Liu, X., Qu, W., Wang, C., Zhang, Q., Ge, Y. (2021). A Survey Study of Factors Influencing Smart Phone Fluency. In: Harris, D., Li, WC. (eds) Engineering Psychology and Cognitive Ergonomics. HCII 2021. Lecture Notes in Computer Science(), vol 12767. Springer, Cham. https://doi.org/10.1007/978-3-030-77932-0_30
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