Abstract
A mixed-initiative interface conjoins aspects of both adaptable and adaptive interfaces in cases where adaptive customization assistance is added to an adaptable interface, improving the efficacy of customization, efficiency of interactions and user satisfaction. Although many studies showed the efficiency of adaptive customization support, they were either conducted within a laboratory with short-term settings or failed to consider the long-term results of the approach on the elderly. Thus, this study aims to assess the capabilities of adaptive assistance derived from the cognitive and behavioral information of users within an adaptive mixed-initiative UI/UX system (SmartSenior) designed to assist elderly people by improving their familiarity with smart devices. Drawing on cognitive and behavioral data of users, adaptive support was offered by way of customization suggestions that users could accept or disregard at their own discretion. For 10 weeks, 20 senior citizens used SmartSenior, and their actions within the interface were recorded. Half of the test subjects received support and the other half did not. The customization behavior and activity of the two groups were then compared, along with subjective responses concerning the customization support. Results demonstrated that test subjects who were supported made more effective use of SmartSenior’s customization features than those who went unsupported. Among the experimental group, subjects accepted most of the customization suggestions provided, and all of them praised the utility of the support and perceived it as beneficial. Moreover, the results show that customization support is more beneficial to users who would never customize of their own volition; such users will be increasingly likely to do so with support. In conclusion, adaptive customization support helps the elderly to more effectively customize their interface, and hence it would helpfully augment the standard adaptable UI/UX.
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Amditis A, Polychronopoulos A, Andreone L, Bekiaris E (2006) Communication and interaction strategies in automotive adaptive interfaces. Cogn Technol Work 8:193–199
Avola D, Spezialetti M, Placidi G (2013) Design of an efficient framework for fast prototyping of customized human–computer interfaces and virtual environments for rehabilitation. Comput Methods Progr Biomed 110:490–502
Avola D, Petracca A, Placidi G (2015) Design of a framework for personalised 3D modelling from medical images. Comput Methods Biomech Biomed Eng Imaging Vis 3:76–83
Bunt A, Conati C, McGrenere J (2004) What role can adaptive support play in an adaptable system? In: Paper presented at the proceedings of the 9th international conference on intelligent user interfaces, pp 117–124
Bunt A, Conati C, McGrenere J (2007) Supporting interface customization using a mixed-initiative approach. In: Paper presented at the proceedings of the 12th international conference on intelligent user interfaces, pp 92–101
Caplan B, Mendoza JE (2011) Edinburgh handedness inventory. In: Encyclopedia of clinical neuropsychology. Springer, New York, pp 928
Cockburn A, Gutwin C, Greenberg S (2007) A predictive model of menu performance. In: Paper presented at the proceedings of the SIGCHI conference on Human factors in computing systems, pp 627–636
Dannenbring GL, Briand K (1982) Semantic priming and the word repetition effect in a lexical decision task. Can J Psychol/Revue canadienne de psychologie 36:435
Debevc M, Meyer B, Donlagic D, Svecko R (1996) Design and evaluation of an adaptive icon toolbar. User Model User Adap Inter 6:1–21
Findlater L, Moffatt K, McGrenere J, Dawson J (2009) Ephemeral adaptation: the use of gradual onset to improve menu selection performance. In: Paper presented at the proceedings of the SIGCHI conference on human factors in computing systems, pp 1655–1664
Gajos KZ, Czerwinski M, Tan DS, Weld DS (2006) Exploring the design space for adaptive graphical user interfaces. In: Paper presented at the proceedings of the working conference on advanced visual interfaces, pp 201–208
Gajos KZ, Weld DS, Wobbrock JO (2010) Automatically generating personalized user interfaces with Supple. Artif Intell 174:910–950
Gonzales E, Matz-Costa C, Morrow-Howell N (2015) Increasing opportunities for the productive engagement of older adults: a response to population aging. Gerontol 55:252–261
Ham DH (2014) A model-based framework for classifying and diagnosing usability problems. Cogn Technol Work 16:373–388
Harrington M, Sawyer M (1992) L2 working memory capacity and L2 reading skill. Stud Second Lang Acquis 14:25–38
Hong SG, Trimi S, Kim DW (2016) Smartphone use and internet literacy of senior citizens. J Assist Technol 10:27–38
Höök K (2000) Steps to take before intelligent user interfaces become real. Interact Comput 12:409–426
Hooshyar D, Ahmad RB, Yousefi M, Fathi M, Horng SJ, Lim H (2016) Applying an online game-based formative assessment in a flowchart-based intelligent tutoring system for improving problem-solving skills. Comput Educ 94:18–36
Hooshyar D, Yousefi M, Lim H (2017) A systematic review of data-driven approaches in player modeling of educational games. Artif Intell Rev. https://doi.org/10.1007/s10462-017-9609-8
Hooshyar D, Yousefi M, Lim H (2018) Data-driven approaches to game player modeling: a systematic literature review. ACM Comput Surv 50:90
Ji H, Yun Y, Lee S, Kim K, Lim H (2017) An adaptable UI/UX considering user’s cognitive and behavior information in distributed environment. Clust Comput. https://doi.org/10.1007/s10586-017-0999-9
Johnson R, Kent S (2007) Designing universal access: web-applications for the elderly and disabled. Cogn Technol Work 9:209–218
Jorritsma W, Cnossen F, van Ooijen PMA (2015a) Improving the radiologist–CAD interaction: designing for appropriate trust. Clin Radiol 70:115–122
Jorritsma W, Cnossen F, van Ooijen PMA (2015b) Adaptive support for user interface customization: a study in radiology. Int J Hum Comput Stud 77:1–9
Kanasi E, Ayilavarapu S, Jones J (2016) The aging population: demographics and the biology of aging. Periodontology 2000 72:13–18
Keeble RJ, Macredie RD, Williams DS (2000) User environments and Individuals: experience with adaptive interface agents. Cogn Technol Work 2:16–26
Kimura D (1969) Spatial localization in left and right visual fields. Can J Psychol/Revue canadienne de psychologie 23:445
Ko HK (2016) Affordance planning strategy for mathematics app development for senior citizen using smart-devices. Commun Math Educ 30:85–99
Lutz W, Butz WP, Samir KC (2017) World population & human capital in the twenty-first century: an overview. Oxford University Press, Oxford
Marmaras N, Pavard B (1999) Problem-driven approach to the design of information technology systems supporting complex cognitive tasks. Cogn Technol Work 1:222–236
Mitchell J, Shneiderman B (1989) Dynamic versus static menus: an exploratory comparison. ACM SigCHI Bull 20:33–37
Newman SD, Carpenter PA, Varma S, Just MA (2003) Frontal and parietal participation in problem solving in the Tower of London: fMRI and computational modeling of planning and high-level perception. Neuropsychologia 41:1668–1682
Otsu K, Shibayama K (2016) Population aging and potential growth in Asia. Asian Dev Rev 33:56–73
Park J, Han SH (2011) Complementary menus: combining adaptable and adaptive approaches for menu interface. Int J Ind Ergon 41:305–316
Perea M, Rosa E, Gómez C (2002) Is the go/no-go lexical decision task an alternative to the yes/no lexical decision task? Mem Cogn 30:34–45
Randell R (2003) User customisation of medical devices: the reality and the possibilities. Cogn Technol Work 5:163–170
Savioja P, Liinasuo M, Koskinen H (2014) User experience: does it matter in complex systems? Cognit Technol Work 16:429–449
Shakshuki EM, Reid M, Sheltami TR (2015) An adaptive user interface in healthcare. Procedia Comput Sci 56:49–58
Shimoyama I, Ninchoji T, Uemura K (1990) The finger-tapping test: a quantitative analysis. Arch Neurol 47:681–684
Syer CA, Jad-Moussa R, Pelletier S, Shore BM (2003) Adaptive-creative versus routine-reproductive expertise in hypermedia design: an exploratory study. Cogn Technol Work 5:94–106
Thomas CG, Krogsæter M (1993) An adaptive environment for the user interface of Excel. In: Paper presented at the proceedings of the 1st international conference on intelligent user interfaces, pp 123–130
van Westrenen F (2011) Cognitive work analysis and the design of user interfaces. Cogn Technol Work 13:31–42
Van Ryseghem B, Ducasse S, Fabry J (2014) Seamless composition and reuse of customizable user interfaces with Spec. Sci Comput Progr 96:34–51
Yasuna ER, Green LS (1952) An evaluation of the Massachusetts vision test for visual screening of school children. Am J Ophthalmol 35:235–240
Acknowledgements
This work was supported by a Korea University Grant as well as Ministry of Culture, Sport and Tourism (MCST) and Korea Creative Content Agency (KOCCA) in the Culture Technology (CT) Research & Development Program 2018 (no. R2016030031).
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Hooshyar, D., Lee, S., Yang, Y. et al. Long-term effects of adaptive customization support on elderly people. Cogn Tech Work 21, 371–382 (2019). https://doi.org/10.1007/s10111-018-0516-9
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DOI: https://doi.org/10.1007/s10111-018-0516-9