Abstract
The past few years have seen tremendous development in web technologies. A range of websites and mobile applications have been developed to support a variety of online activities. The ubiquitous nature and increasing complexity of technology mean that ensuring accessibility remains challenging. Accessibility evaluation refers to the process of examining a product and establishing the extent to which it supports accessibility through the identification of potential barriers. While accessibility guidelines can guide the development process and automated evaluation tools can assist in measuring conformance, they do not guarantee that products will be accessible in a live context. The most reliable way to evaluate the accessibility of a product is to conduct a study with representative users interacting with the product. This chapter outlines a range of methods which can be used to ensure that a product is designed to meet the requirements and specific needs of users, from the ideation phase to the design and iterative development. The strengths and weaknesses of each method are described, as well as the primary considerations to ensure that the results of a study are reliable and valid, and also participants are treated ethically. This chapter concludes with a discussion of the field as well as an examination of future trends such as how data from user studies can be used to influence the design of future accessibility guidelines to improve their efficacy.
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Albanesi MG, Gatti R, Porta M, Ravarelli A (2011) Towards semi-automatic usability analysis through eye tracking. In: Proceedings of the 12th International Conference on Computer Systems and Technologies, ACM, New York, NY, USA, CompSysTech ’11, pp 135–141. https://doi.org/10.1145/2023607.2023631
Asakawa C, Takagi H (2008) Transcoding. In: Harper S, Yesilada Y (eds) Web accessibility, Springer, London, a foundation for research, human computer interaction series, pp 231–260
Bailey C, Gkatzidou V (2017) Considerations for implementing a holistic organisational approach to accessibility. In: Proceedings of the 14th Web for All Conference on the Future of Accessible Work, ACM, New York, NY, USA, W4A ’17, pp 7:1–7:4. https://doi.org/10.1145/3058555.3058571
Bevan N, Carter J, Harker S (2015) Iso 9241–11 revised: what have we learnt about usability since 1998? In: Kurosu M (ed) Human-computer interaction: design and evaluation. Springer International Publishing, Cham, pp 143–151
Blascheck T, Kurzhals K, Raschke M, Burch M, Weiskopf D, Ertl T (2017) Visualization of eye tracking data: a taxonomy and survey. Comput Graph Forum 36(8):260–284. https://doi.org/10.1111/cgf.13079
Borodin Y, Bigham JP, Dausch G, Ramakrishnan IV (2010) More than meets the eye: a survey of screen-reader browsing strategies. In: Proceedings of the 2010 International Cross Disciplinary Conference on Web Accessibility (W4A), ACM, New York, NY, USA, W4A ’10, pp 13:1–13:10. https://doi.org/10.1145/1805986.1806005
Brajnik G (2006) Web accessibility testing: when the method is the culprit. In: Miesenberger K, Klaus J, Zagler WL, Karshmer AI (eds) Computers helping people with special needs. Springer, Berlin, pp 156–163
Breen RL (2006) A practical guide to focus-group research. J Geogr High Educ 30(3):463–475. https://doi.org/10.1080/03098260600927575
Burton MC, Walther JB (2001) The value of web log data in use-based design and testing. J Comput-Mediat Commun 6(3):JCMC635. https://doi.org/10.1111/j.1083-6101.2001.tb00121.x
Clegg-Vinell R, Bailey C, Gkatzidou V (2014) Investigating the appropriateness and relevance of mobile web accessibility guidelines. In: Proceedings of the 11th Web for All Conference, ACM, New York, NY, USA, W4A ’14, pp 38:1–38:4. https://doi.org/10.1145/2596695.2596717
Cooper M, Sloan D, Kelly B, Lewthwaite S (2012) A challenge to web accessibility metrics and guidelines: putting people and processes first. In: Proceedings of the International Cross-disciplinary Conference on Web Accessibility, ACM, New York, NY, USA, W4A ’12, pp 20:1–20:4. https://doi.org/10.1145/2207016.2207028
Dix A, Finlay J, Abowd G, Beale R (2004) Evaluation techniques. In: Human-computer interaction, 3rd edn. Pearson Prentice Hall, pp 318–363
Ehmke C, Wilson S (2007) Identifying web usability problems from eye-tracking data. In: Proceedings of the 21st British HCI Group Annual Conference on People and Computers: HCI...but not as we know it - volume 1, British Computer Society, Swinton, UK, UK, BCS-HCI ’07, pp 119–128
Eraslan S, Yesilada Y (2015) Patterns in eyetracking scanpaths and the affecting factors. J Web Eng 14(5–6):363–385
Eraslan S, Yesilada Y, Harper S (2013) Understanding eye tracking data for re-engineering web pages. In: Sheng QZ, Kjeldskov J (eds) Current trends in web engineering. Springer International Publishing, Cham, pp 345–349
Eraslan S, Yesilada Y, Harper S (2014) Identifying patterns in eyetracking scanpaths in terms of visual elements of web pages. In: Casteleyn S, Rossi G, Winckler M (eds) Web engineering. Springer International Publishing, Cham, pp 163–180
Eraslan S, Yesilada Y, Harper S (2015) Eye tracking scanpath analysis techniques on web pages: a survey, evaluation and comparison. J Eye Mov Res 9(1). https://bop.unibe.ch/JEMR/article/view/2430
Eraslan S, Yesilada Y, Harper S (2016a) Eye tracking scanpath analysis on web pages: how many users? In: Proceedings of the ninth biennial ACM symposium on eye tracking research & applications, ACM, New York, NY, USA, ETRA ’16, pp 103–110. https://doi.org/10.1145/2857491.2857519
Eraslan S, Yesilada Y, Harper S (2016b) Scanpath trend analysis on web pages: clustering eye tracking scanpaths. ACM Trans Web 10(4):20:1–20:35. https://doi.org/10.1145/2970818
Eraslan S, Yesilada Y, Harper S (2016c) Trends in eye tracking scanpaths: segmentation effect? In: Proceedings of the 27th ACM Conference on Hypertext and Social Media, ACM, New York, NY, USA, HT ’16, pp 15–25. https://doi.org/10.1145/2914586.2914591
Eraslan S, Yesilada Y, Harper S, Davies A (2016d) What is trending in eye tracking scanpaths on web pages? In: Spink A, Riedel G, Zhou L, Teekens L, Albatal R, Gurrin C (eds) Proceedings of the 10th International Conference on Methods and Techniques in Behavioral Research (Measuring Behavior 2016), Dublin City University, MB 2016, pp 341–343
Eraslan S, Yaneva V, Yesilada Y, Harper S (2017a) Do web users with autism experience barriers when searching for information within web pages? In: Proceedings of the 14th Web for All Conference on the Future of Accessible Work, ACM, New York, NY, USA, W4A ’17, pp 20:1–20:4. https://doi.org/10.1145/3058555.3058566
Eraslan S, Yesilada Y, Harper S (2017b) Engineering web-based interactive systems: trend analysis in eye tracking scanpaths with a tolerance. In: Proceedings of the ACM SIGCHI symposium on engineering interactive computing systems, ACM, New York, NY, USA, EICS ’17, pp 3–8. https://doi.org/10.1145/3102113.3102116
Eraslan S, Yesilada Y, Harper S (2017c) Less users more confidence: how AOis dont affect scanpath trend analysis. J Eye Mov Res 10(4). https://bop.unibe.ch/JEMR/article/view/3882
Eraslan S, Yesilada Y, Harper S (2018) Crowdsourcing a corpus of eye tracking data on web pages: a methodology. In: Grant R, Allen T, Spink A, Sullivan M (eds) Proceedings of the 11th International Conference on Methods and Techniques in Behavioral Research (Measuring Behavior 2018), Manchester Metropolitan University, MB2018, pp 267–273
Eysenck MW (2005) Psychology for AS level, 3rd edn. Psychology Press, Hove, East Sussex
Gay L, Mills G, Airasian P (2009) Educational research: competencies for analysis and applications, 9th edn. Prentice Hall, Upper Saddle River, New Jersey
Gravetter FJ, Wallnau LB (2008) Statistics for behavioral sciences, 8th edn. Wadsworth Publishing
Hennick M (2007) International focus group research: a handbook for the health and social sciences. Cambridge University Press, Cambridge
Henry SL (2018) Involving users in evaluating web accessibility. https://www.w3.org/WAI/test-evaluate/involving-users/. Accessed 15 Aug 2018
Hesterberg TC (2015) What teachers should know about the bootstrap: resampling in the undergraduate statistics curriculum. Am Stat 69(4):371–386. https://doi.org/10.1080/00031305.2015.1089789, pMID:27019512
Holzinger A (2005) Usability engineering methods for software developers. Commun ACM 48(1):71–74. https://doi.org/10.1145/1039539.1039541
Jay C, Lunn D, Michailidou E (2008) End user evaluations. In: Harper S, Yesilada Y (eds) Web accessibility. A foundation for research, human computer interaction series. Springer, London, pp 107–126
Kouroupetroglou C, Koumpis A (2014) Challenges and solutions to crowdsourcing accessibility evaluations. https://www.w3.org/WAI/RD/2014/way-finding/paper5/. Accessed 9 July 2018
Kuniavsky M (2003) Observing the User Experience: A Practitioner’s Guide to User Research (Morgan Kaufmann series in interactive technologies). Morgan Kaufmann Publishers Inc., San Francisco
Leavitt M, Shneiderman B (2006) Research-based web design and usability guidelines. Department of Health and Human Services, Washington DC, US
Leedy P, Ormerod J (2016) Practical research: planning and design, 11th edn. Pearson
Lewis C (1982) Using the think aloud method in cognitive interface design. IBM Research Report, RC–9265 (\(\#\)40713), IBM Thomas J. Watson Research Center, Yorktown Heights, NY
Li L, Wang C, Song S, Yu Z, Zhou F, Bu J (2017) A task assignment strategy for crowdsourcing-based web accessibility evaluation system. In: Proceedings of the 14th Web for All Conference on the Future of Accessible Work, ACM, New York, NY, USA, W4A ’17, pp 18:1–18:4. https://doi.org/10.1145/3058555.3058573
Menges R, Kumar C, Müller D, Sengupta K (2017) Gazetheweb: a gaze-controlled web browser. In: Proceedings of the 14th Web for All Conference on the Future of Accessible Work, ACM, New York, NY, USA, W4A ’17, pp 25:1–25:2. https://doi.org/10.1145/3058555.3058582
Nielsen J (2003) Usability 101: introduction to usability. http://www.useit.com/alertbox/20030825.html. Accessed: 09 July 2018
Nielsen J (2004) Risks of quantitative studies. https://www.nngroup.com/articles/risks-of-quantitative-studies/. Accessed 01 July 2018
Pallant J (2007) SPSS survival manual: a step by step guide to data analysis using SPSS version 15, 4th edn. Open University Press/McGraw-Hill, Maidenhead
Poole A, Ball LJ (2005) Eye tracking in human-computer interaction and usability research: current status and future. In: Prospects, Chapter in C. Ghaoui (Ed.): encyclopedia of human-computer interaction. Idea Group Inc., Pennsylvania
Rello L, Ballesteros M (2015) Detecting readers with dyslexia using machine learning with eye tracking measures. In: Proceedings of the 12th Web for All Conference, ACM, New York, NY, USA, W4A ’15, pp 16:1–16:8. https://doi.org/10.1145/2745555.2746644
Rosenbaum S, Cockton G, Coyne K, Muller M, Rauch T (2002) Focus groups in HCI: wealth of information or waste of resources? In: CHI ’02 extended abstracts on human factors in computing systems, ACM, New York, NY, USA, CHI EA ’02, pp 702–703. https://doi.org/10.1145/506443.506554
Rubin J, Chisnell D (2008) Handbook of usability testing: how to plan, design and conduct effective tests. Wiley, New York
Sherief N, Jiang N, Hosseini M, Phalp K, Ali R (2014) Crowdsourcing software evaluation. In: Proceedings of the 18th International Conference on Evaluation and Assessment in Software Engineering, ACM, New York, NY, USA, EASE ’14, pp 19:1–19:4. https://doi.org/10.1145/2601248.2601300
Song S, Bu J, Wang Y, Yu Z, Artmeier A, Dai L, Wang C (2018) Web accessibility evaluation in a crowdsourcing-based system with expertise-based decision strategy. In: Proceedings of the internet of accessible things, ACM, New York, NY, USA, W4A ’18, pp 23:1–23:4. https://doi.org/10.1145/3192714.3192827
Yaneva V, Ha LA, Eraslan S, Yesilada Y, Mitkov R (2018) Detecting autism based on eye-tracking data from web searching tasks. In: Proceedings of the internet of accessible things, ACM, New York, NY, USA, W4A ’18, pp 16:1–16:10. https://doi.org/10.1145/3192714.3192819
Yen PY, Bakken S (2009) A comparison of usability evaluation methods: heuristic evaluation versus end-user think-aloud protocol–an example from a web-based communication tool for nurse scheduling. In: AMIA annual symposium proceedings, American Medical Informatics Association, vol 2009, p 714
Yesilada Y, Stevens R, Harper S, Goble C (2007) Evaluating DANTE: Semantic Transcoding for Visually Disabled Users. ACM Trans Comput-Hum Interact 14(3):14. https://doi.org/10.1145/1279700.1279704
Yesilada Y, Brajnik G, Vigo M, Harper S (2012) Understanding web accessibility and its drivers. In: Proceedings of the International Cross-Disciplinary Conference on Web Accessibility, ACM, New York, NY, USA, W4A ’12, pp 19:1–19:9, https://doi.org/10.1145/2207016.2207027
Yesilada Y, Harper S, Eraslan S (2013) Experiential transcoding: An eyetracking approach. In: Proceedings of the 10th International Cross-Disciplinary Conference on Web Accessibility, ACM, New York, NY, USA, W4A ’13, pp 30:1–30:4, https://doi.org/10.1145/2461121.2461134
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Eraslan, S., Bailey, C. (2019). End-User Evaluations. In: Yesilada, Y., Harper, S. (eds) Web Accessibility. Human–Computer Interaction Series. Springer, London. https://doi.org/10.1007/978-1-4471-7440-0_11
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