How to Help Older Adults Learn Smartphone Applications? A Case Study of Instructional Design for Video Training

  • Fengli Liu
  • Jia ZhouEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 826)


Video training is a useful way for older adults to learn to use smartphone applications, but the instructional design of adapting age-related changes is necessary to improve learning effectiveness. This study investigates the influence of visual cues and tapping methods on older adults’ intention to use, ease of learning, satisfaction, and task completion time when learning how to use smartphone applications through instructional videos. Twenty-four older adults learned smartphone applications using two tapping methods (the tapping with/without validation method) on three types of instructional videos with different visual cues (red rectangle, cartoon finger, and real finger). The results indicated that use of a cartoon finger contributed to higher intention to use, higher ease of learning, higher satisfaction, and shorter task completion time compared with use of a red rectangle or a real finger. Moreover, older adults preferred the tapping with validation method rather than that without validation method. These findings will be a useful reference for designers of instructional videos and developers of smartphones.


Older adults Video training Visual cues Tapping methods Smartphone applications 



This work was supported by funding from the National Natural Science Foundation of China (Grants nos. 71661167006) and Chongqing Municipal Natural Science Foundation (cstc2016jcyjA0406).


  1. 1.
    Plaisant C, Shneiderman B (2005) Show me! guidelines for producing recorded demonstrations. In: 2005 IEEE symposium on visual languages and human-centric computing, pp 171–178. IEEEGoogle Scholar
  2. 2.
    Boot WR, Nichols TA, Rogers WA, Fisk AD (2012) Design for aging. In: Handbook of human factors and ergonomics, Fourth Edn, pp 1442–1471Google Scholar
  3. 3.
    Hwangbo H, Yoon SH, Jin BS, Han YS, Ji YG (2013) A study of pointing performance of elderly users on smartphones. Int J Hum Comput Interact 29:604–618CrossRefGoogle Scholar
  4. 4.
    Kobayashi M, Hiyama A, Miura T, Asakawa C, Hirose M, Ifukube T (2011) Elderly user evaluation of mobile touchscreen interactions. In: IFIP conference on human-computer interaction, pp 83–99. Springer, HeidelbergGoogle Scholar
  5. 5.
    Chêne D, Pillot V, Chaumon MÉB (2016) Tactile interaction for novice user. In: International conference on human aspects of IT for the aged population, pp 412–423Google Scholar
  6. 6.
    Commodari E, Guarnera M (2008) Attention and aging. Aging Clin Exp Res 20:578–584CrossRefGoogle Scholar
  7. 7.
    Mayer RE, Moreno R (2003) Nine ways to reduce cognitive load in multimedia learning. Educ Psychol 38:43–52CrossRefGoogle Scholar
  8. 8.
    Norman DA, Nielsen J (2010) Gestural interfaces: a step backward in usability. Interactions 17: 46–49Google Scholar
  9. 9.
    Lin L, Atkinson RK, Savenye WC, Nelson BC (2016) Effects of visual cues and self-explanation prompts: empirical evidence in a multimedia environment. Interact Learn Environ 24:799–813CrossRefGoogle Scholar
  10. 10.
    de Koning BB, Tabbers HK, Rikers RM, Paas F (2009) Towards a framework for attention cueing in instructional animations: guidelines for research and design. Educ Psychol Rev 21:113–140CrossRefGoogle Scholar
  11. 11.
    de Koning BB, Tabbers HK, Rikers RM, Paas F (2010) Attention guidance in learning from a complex animation: seeing is understanding? Learn Instr 20:111–122CrossRefGoogle Scholar
  12. 12.
    Ozcelik E, Arslan-Ari I, Cagiltay K (2010) Why does signaling enhance multimedia learning? evidence from eye movements. Comput Hum Behav 26:110–117CrossRefGoogle Scholar
  13. 13.
    Ozcelik E, Karakus T, Kursun E, Cagiltay K (2009) An eye-tracking study of how color coding affects multimedia learning. Comput Educ 53:445–453CrossRefGoogle Scholar
  14. 14.
    Amadieu F, Mariné C, Laimay C (2011) The attention-guiding effect and cognitive load in the comprehension of animations. Comput Hum Behav 27:36–40CrossRefGoogle Scholar
  15. 15.
    Boucheix J-M, Guignard H (2005) What animated illustrations conditions can improve technical document comprehension in young students? format, signaling and control of the presentation. Eur J Psychol Educ 20:369–388CrossRefGoogle Scholar
  16. 16.
    de Koning BB, Tabbers HK, Rikers RM, Paas F (2007) Attention cueing as a means to enhance learning from an animation. Appl Cogn Psychol 21:731–746CrossRefGoogle Scholar
  17. 17.
    de Koning BB, Tabbers HK, Rikers RM, Paas F (2010) Learning by generating vs. receiving instructional explanations: two approaches to enhance attention cueing in animations. Comput Educ 55:681–691CrossRefGoogle Scholar
  18. 18.
    Jamet E, Gavota M, Quaireau C (2008) Attention guiding in multimedia learning. Learn Instr 18:135–145CrossRefGoogle Scholar
  19. 19.
    Lin L, Atkinson RK (2011) Using animations and visual cueing to support learning of scientific concepts and processes. Comput Educ 56:650–658CrossRefGoogle Scholar
  20. 20.
    Wouters P, Paas F, van Merriënboer JJ (2009) Observational learning from animated models: effects of modality and reflection on transfer. Contemp Educ Psychol 34:1–8CrossRefGoogle Scholar
  21. 21.
    Kühl T, Scheiter K, Gerjets P (2012) Enhancing learning from dynamic and static visualizations by means of cueingGoogle Scholar
  22. 22.
    Yung HI, Paas F (2015) Effects of cueing by a pedagogical agent in an instructional animation: a cognitive load approach. Educ Technol Soc 18:153–160Google Scholar
  23. 23.
    Mautone PD, Mayer RE (2001) Signaling as a cognitive guide in multimedia learning. J Educ Psychol 93:377CrossRefGoogle Scholar
  24. 24.
    Lowe R, Boucheix J-M (2011) Cueing complex animations: does direction of attention foster learning processes? Learn Instr 21:650–663CrossRefGoogle Scholar
  25. 25.
    Fisk AD, Czaja SJ, Rogers WA, Charness N, Sharit J (2009) Designing for older adults: principles and creative human factors approaches. CRC press, Boca RatonGoogle Scholar
  26. 26.
    Leonardi C, Albertini A, Pianesi F, Zancanaro M (2010) An exploratory study of a touch-based gestural interface for elderly. In: Proceedings of the 6th nordic conference on human-computer interaction: extending boundaries, pp 845–850. ACMGoogle Scholar
  27. 27.
    Stößel C, Wandke H, Blessing L (2009) An evaluation of finger-gesture interaction on mobile devices for elderly users. Prospektive Gestaltung von Mensch-Technik-Interaktion 8:470–475Google Scholar
  28. 28.
    Motti LG, Vigouroux N, Gorce P (2015) Improving accessibility of tactile interaction for older users: lowering accuracy requirements to support drag-and-drop interaction. Procedia Comput Sci 67:366–375CrossRefGoogle Scholar
  29. 29.
    Gorce P, Nadine V, Motti L (2017) Interaction techniques for older adults using touchscreen devices: a literature review from 2000 to 2013. J d’Interaction Personne-Système 3Google Scholar
  30. 30.
    Harada S, Sato D, Takagi H, Asakawa C (2013) Characteristics of elderly user behavior on mobile multi-touch devices. In: IFIP conference on human-computer interaction, pp 323–341. Springer, HeidelbergGoogle Scholar
  31. 31.
    Leonard VK, Jacko JA, Pizzimenti JJ (2005) An exploratory investigation of handheld computer interaction for older adults with visual impairments. In: Proceedings of the 7th international ACM SIGACCESS conference on computers and accessibility, pp 12–19. ACMGoogle Scholar
  32. 32.
    Lee J-H, Poliakoff E, Spence C (2009) The effect of multimodal feedback presented via a touch screen on the performance of older adults. In: International conference on haptic and audio interaction design, pp 128–135. Springer, HeidelbergGoogle Scholar
  33. 33.
    Davis FD (1989) Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q 13:319–340CrossRefGoogle Scholar
  34. 34.
    Renaud K, Van Biljon J (2008) Predicting technology acceptance and adoption by the elderly: a qualitative study. In: Proceedings of the 2008 annual research conference of the South African institute of computer scientists and information technologists on IT research in developing countries: riding the wave of technology, pp 210–219. ACMGoogle Scholar
  35. 35.
    Lewis JR (1995) IBM computer usability satisfaction questionnaires: psychometric evaluation and instructions for use. Int J Hum Comput Interact 7:57–78CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Industrial EngineeringChongqing UniversityChongqingPeople’s Republic of China

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