Academia.eduAcademia.edu

Outline

Title
Abstract
FAQs
Figures
Introduction
Summary
Re-Design
Interface Design Process
Method
Participants and Experiment Design
Procedure
Results
Discussion
Implications
Conclusion
References
All Topics
Engineering
Human Factors and Ergonomics

Investigating users' intuitive interaction with complex artefacts

Profile image of Vesna PopovicVesna PopovicProfile image of Douglas MaharDouglas MaharProfile image of Alethea BlacklerAlethea Blackler

2010

https://doi.org/10.1016/J.APERGO.2009.04.010
visibility

…

description

21 pages

link

1 file

Abstract

This paper examines the role of intuition in the way that people operate unfamiliar devices. Intuition is a type of cognitive processing that is often non-conscious and utilises stored experiential knowledge. Intuitive interaction involves the use of knowledge gained from other products and/or experiences. Two initial experimental studies revealed that prior exposure to products employing similar features helped participants to complete set tasks more quickly and intuitively, and that familiar features were intuitively used more often than unfamiliar ones. A third experiment confirmed that performance is affected by a person's level of familiarity with similar technologies, and also revealed that appearance (shape, size and labelling of features) seems to be the variable that most affects time spent on a task and intuitive uses during that time. Age also seems to have an effect. These results and their implications are discussed.

FAQs

sparkles

AI

What defines intuitive interaction in product design?add

Intuitive interaction is defined as using knowledge gained through prior experiences with familiar features, allowing for non-conscious and rapid use.

How does prior experience influence intuitive interaction speed?add

The research shows a strong negative correlation (r(18) = -0.69, p < .01) between technology familiarity and the time taken to complete tasks, indicating faster intuitive interactions.

What is the impact of feature appearance versus location on intuitive use?add

Experiment 3 revealed that changing a feature's appearance significantly enhanced intuitive use, outperforming location changes in facilitating user interactions.

How do age differences affect intuitive interaction capabilities?add

Older participants exhibited slower and less intuitive interactions, with significant disparities in performance (F(2, 48) = 5.627, p < .01) compared to younger groups.

What role does the Recognition Primed Decision model play in intuition?add

The RPD model illustrates how experienced individuals utilize intuition to make rapid decisions based on familiar patterns and prior experiences.

Figures (24)
Fig. 1. Laboratory set-up during experiments.
Fig. 1. Laboratory set-up during experiments.
Fig. 3. Time to complete operations plotted against technology familiarity score.
Fig. 3. Time to complete operations plotted against technology familiarity score.
Fig. 2. Time to complete operations plotted against level of expertise.
Fig. 2. Time to complete operations plotted against level of expertise.
Fig. 5. Mean familiarity of features plotted against mean percentage of intuitive uses of features (correct and correct-but-inappropriate).
Fig. 5. Mean familiarity of features plotted against mean percentage of intuitive uses of features (correct and correct-but-inappropriate).
Fig. 4. Technology familiarity score plotted against percentage of intuitive first uses (correct and correct-but-inappropriate).
Fig. 4. Technology familiarity score plotted against percentage of intuitive first uses (correct and correct-but-inappropriate).
Fig. 6. Remote control default interface on VCR main screen. The procedures for the experiment and interview were the same as for Experiment 1, with some exceptions. Firstly, the technology familiarity questionnaire was completed as a part of recruitment rather than part of the follow-up interview. Secondly, the remote control was the mediating product instead of the camera, and the operations were therefore different:
Fig. 6. Remote control default interface on VCR main screen. The procedures for the experiment and interview were the same as for Experiment 1, with some exceptions. Firstly, the technology familiarity questionnaire was completed as a part of recruitment rather than part of the follow-up interview. Secondly, the remote control was the mediating product instead of the camera, and the operations were therefore different:
Fig. 7. Time to complete operations for each technology familiarity group. For time to complete operations for each age group, Levene’s test showed a breach of homogeneity, F(3, 26) = 8.73, p < .0001, so the alpha level of 0.25 was again adopted. Age group had a signifi- cant main effect on time to complete operations, F(3, 26) = 11.26, p <.0001. This relationship is shown in Fig. 8. The Tukey post hoc test showed that there were significant differences in time to complete tasks between the 18-34 age group and the 45-54 (p=.005) and >55 (p=.001) age groups. In addition, there was
Fig. 7. Time to complete operations for each technology familiarity group. For time to complete operations for each age group, Levene’s test showed a breach of homogeneity, F(3, 26) = 8.73, p < .0001, so the alpha level of 0.25 was again adopted. Age group had a signifi- cant main effect on time to complete operations, F(3, 26) = 11.26, p <.0001. This relationship is shown in Fig. 8. The Tukey post hoc test showed that there were significant differences in time to complete tasks between the 18-34 age group and the 45-54 (p=.005) and >55 (p=.001) age groups. In addition, there was
Fig. 9. Intuitive first uses (correct and correct-but-inappropriate) by technology} familiarity group. The percentage of intuitive uses of the features was compared with the familiarity of the features, as rated by participants during the interviews. It was found that the mean familiarity of the features correlated strongly and positively with the mean of the
Fig. 9. Intuitive first uses (correct and correct-but-inappropriate) by technology} familiarity group. The percentage of intuitive uses of the features was compared with the familiarity of the features, as rated by participants during the interviews. It was found that the mean familiarity of the features correlated strongly and positively with the mean of the
Fig. 8. Time to complete operations by age group. a significant difference between the 35-44 group and the >55 group (p < .05).
Fig. 8. Time to complete operations by age group. a significant difference between the 35-44 group and the >55 group (p < .05).
Fig. 11. Mean familiarity of features plotted against mean percentage of intuitive uses of features (correct and correct-but-inappropriate). The relationships between time, TF score and intuitive uses of the features supported the findings of Experiment 1. People use their previous experience with similar features in order to use new features intuitively. Again, the data on intuitive first uses are particularly important as they strongly suggest that people are able
Fig. 11. Mean familiarity of features plotted against mean percentage of intuitive uses of features (correct and correct-but-inappropriate). The relationships between time, TF score and intuitive uses of the features supported the findings of Experiment 1. People use their previous experience with similar features in order to use new features intuitively. Again, the data on intuitive first uses are particularly important as they strongly suggest that people are able
Fig. 10. Intuitive first uses (correct and correct-but-inappropriate) by age group.
Fig. 10. Intuitive first uses (correct and correct-but-inappropriate) by age group.
Fig. 12. Intuitive first uses of features (correct and correct-but-inappropriate) by familiarity of features.
Fig. 12. Intuitive first uses of features (correct and correct-but-inappropriate) by familiarity of features.
Specified features for remote control re-design. Table 2
Specified features for remote control re-design. Table 2
Interface designs for Experiment 3. Table 3
Interface designs for Experiment 3. Table 3
Fig. 13. Location-Appearance interface on VCR main screen.
Fig. 13. Location-Appearance interface on VCR main screen.
Experimental groups for Experiment 3. Table 4
Experimental groups for Experiment 3. Table 4
Fig. 14. Time to complete operations by technology familiarity score.
Fig. 14. Time to complete operations by technology familiarity score.
Fig. 15. Time to complete operations by interface and age group.
Fig. 15. Time to complete operations by interface and age group.
Fig. 16. Percentage of intuitive first uses (correct only) by interface and age group. The percentage of intuitive first uses (correct only) showed a significant main effect between the interfaces, F(3, 48) = 5.584,
Fig. 16. Percentage of intuitive first uses (correct only) by interface and age group. The percentage of intuitive first uses (correct only) showed a significant main effect between the interfaces, F(3, 48) = 5.584,
Fig. 18. Percentage of intuitive uses (correct only) by interface and age group.
Fig. 18. Percentage of intuitive uses (correct only) by interface and age group.
Fig. 17. Percentage of intuitive first uses (correct and correct-but-inappropriate) by interface and age group.
Fig. 17. Percentage of intuitive first uses (correct and correct-but-inappropriate) by interface and age group.
How often do you use the following products? (if you have never used a product of the type, please tick never)
How often do you use the following products? (if you have never used a product of the type, please tick never)

Related papers

Towards a Design Methodology for Applying Intuitive Interaction
Douglas Mahar

Intuitive interaction involves utilising knowledge gained through other products or experience(s). Therefore, products that people use intuitively are those with features they have encountered before. This position has been supported by experimental studies. The findings suggest that relevant past experience is transferable between products, and probably also between contexts, and performance is affected by a person's level of familiarity with similar technologies.

View PDFchevron_right
Intuitive user interfaces
Klaus Bærentsen

Scandinavian Journal of Information Systems, 2000

The paper outlines an approach to the development of intuitively understandable on-screen user interfaces. Users have been found to explain the operation of equipment with screen based user interfaces in terms of handling "objects" and interacting with "agents" in a virtual "space". These metaphorical descriptions may reflect general and fundamental principles of cognition that are rooted in the evolution of the human species. It is postulated that presentation of information on the interface as scenes, objects and actors can call upon instinctive capacities for direct perceptual information pickup, intuitive cognitive functions and natural behavioral tendencies. In order to initiate learning of complex functions that cannot be perceived directly may necessitate the use of symbolic information. This must be based on an analysis of the most appropriate way to map the new functions to the users' prior conceptual understanding of technological objects and functions.

View PDFchevron_right
Intuitive Interaction Applied to Interface Design
Douglas Mahar

Intuitive interaction involves utilising knowledge gained through other products or experience(s). Therefore, products that people use intuitively are those with features they have encountered before. This position has been supported by experimental studies. The findings suggest that relevant past experience is transferable between products, and probably also between contexts, and performance is affected by a person's level of familiarity with similar technologies. Appearance (shape, size and labelling of features) seems to be the variable that most affects time on task and intuitive uses.

View PDFchevron_right
Concepts of intuitive interaction
Douglas Mahar

Intuition is a type of cognitive processing that is often non-conscious and utilises stored experiential knowledge. Intuitive interaction involves the use of knowledge gained from other products and/or experiences. We have developed novel approaches and techniques for studying intuitive use of interfaces, and shown that intuitive interaction is based on past experience with similar artifacts. Based on our empirical work we have developed principles and tools for designers to assist them in making interfaces more intuitive. These principles are discussed in this paper.

View PDFchevron_right
Intuitive Use of User Interfaces: Defining a Vague Concept
Johann Habakuk Israel

2007

In this paper we present a general definition of the concept 'intuitive use of user interfaces' on the basis of our current interdisciplinary work. 'Intuitive use' is regarded as a characteristic of human-machine systems. It refers to a special kind of interaction process between users and technical systems that use the users' intuition. The main part of the paper deals with central aspects of this definition in detail and discusses pre-conditions and restrictions of the use of the concept. The main aspects that we discuss are the design of technical systems, application and non-conscious use of previous knowledge, intuition as a non-conscious process, interaction, and effectiveness. We complement this discussion by addressing the relationship between aesthetics and intuitive use.

View PDFchevron_right
Investigating Prior Experience and Product Learning through Novel Interface Interaction: A Pilot Study
pat langdon

Lecture Notes in Computer Science, 2009

In keeping with the ethos of Inclusive Design, this paper outlines a pilot study investigating how individuals perceive, process and respond to stimuli during interaction with products, and aims to reveal what occurs during novel product interaction whereupon users may posses limited, or non-existent, internal representations. Other areas of interest included the generational effect and the effects of ageing, upon interaction. A novel product is presented to a small number of participants who are recorded interacting with it whilst providing concurrent protocol and information elicited regarding the development of internal representations. The expectation was that prior experience with similar products would affect users' ability to interact with the product, and that this might be age-related. Whilst this was confirmed to a limited extent in the pilot study, experimentation provided clear evidence of internalised concept development that would, in itself, validate full-scale examination.

View PDFchevron_right
Understanding human-technology interactions: the role of prior experience and age
Marita O'Brien

Everyday technologies are intended for use by everyone with no specific training and minimal instructions. Prior research (e.g., Norman, 2002; Polson&Lewis, 1990) suggests that these technologies are usable if users can leverage their prior experience. However, different users will leverage difference experiences to operate the same technologies (Blackler, Popovic,&Mahar, 2003a). This dissertation systematically examined use of prior knowledge in the operation of everyday technology by diverse users, specifically users of different ages and experience levels. In Study 1 encounters with everyday technologies were self-reported by younger adults, older adults with low technology experience, and older adults with high technology experience. Comparisons of technology repertoires for each participant group indicated similar usage between younger adults and high tech older adults that differed in expected domains. Low tech older adults used fewer technologies, but overall they used more t...

View PDFchevron_right
Redundancy in interface design and its impact on intuitive use of a product in older users
Raghavendra Reddy Gudur

Many older adults have difficulty using modern consumer products due to their complexity both in terms of functionality and interface design. It has been observed that older people also have more problems learning new systems. It was hypothesised that designing technological products that are more intuitive for older people to use can solve this problem. An intuitive interface allows a user's to employ prior knowledge, thus minimizing the learning needed for effective interaction. This paper discusses an experiment investigating the effectiveness of redundancy in interface design. The primary objective of this experiment was to find out if using more than one modality for a product's interface improves the speed and intuitiveness of interactions for older adults. Preliminary analysis showed strong correlation between technology familiarity and time on tasks, but redundancy in interface design improved speed and accuracy of use only for participants with moderate to high technology familiarity.

View PDFchevron_right
User Familiarity in User Interfaces
Mark Billinghurst

2006

Previous work discussed a model of cognitive distance with the novel concepts of" tech bias"," velocity" and" inertia". This paper presents a revised version of the model of human factors involved, and describes a pilot study that suggests the model presented allows for a very high degree of confidence in predicting the effect a user's familiarity with a problem domain and specific implementation will have on their perception of the directness of the user interface.

View PDFchevron_right
Expert and Novice User Differences and Implications for Product Design and Useability
Vesna Popovic

2000

This paper explores differences and similarities between novice and expert users of interactive artifacts. In order to achieve this, protocol analysis was used to identify users' cognitive categories, knowledge categories and knowledge representation. This research is based on the premises that knowledgedomain-specific knowledge in particular -plays a significant role in distinguishing a novice from an expert user, and the way in which they use technologically interactive devices. The differences between expert and novice users were compared and identified with associated knowledge and knowledge representation for each cognitive category. These constitute the features that differentiate them as they reflect the kind of processes, representations, strategies or knowledge organisation that may occur for each cognitive category during the interaction. The paper also addresses the transitional process through which a novice becomes an expert and concludes about this finding's implication to design.

View PDFchevron_right

References (83)

  1. Agor, W.H., 1986. The Logic of Intuitive Decision Making: a Research-based Approach for Top Management. Quorum Books, New York.
  2. Ardey, G.F., 1998. Fusion and Display of Data According to the Design Philosophy of Intuitive Use, In: Proceedings of RTO SCI Symposium on Sensor Data Fusion and Integration of the Human Element, Ottawa.
  3. Baars, B.J., 1988. A Cognitive Theory of Consciousness. Cambridge University Press, Cambridge.
  4. Baracat, B., Marquie, J.C., 1994. Training the middle-aged in new computer tech- nology: a pilot study using signal detection theory in a real-life word-pro- cessing learning situation. In: Snel, J., Cremer, R. (Eds.), Work and Aging: a European Perspective. Taylor and Francis, London, pp. 197-211.
  5. Bastick, T.,1982. Intuition: How we Think and Act. John Wiley and Sons, Chichester, UK.
  6. Bastick, T., 2003. Intuition. Evaluating the Construct and its Impact on Creative Thinking. Stoneman and Lang, Kingston, Jamaica.
  7. Birkle, T.K., Jacob, K.D., 1988. The Latest Advances in Predicting Sound System Performance in Real Spaces: Combining Intuitive User Interface with Acousti- cally Relevant Output, In: Proceedings of 6th International Conference on Sound Reinforcement, Nashville, TN.
  8. Blackler, A., 2008. Intuitive Interaction with Complex Artefacts: Empirically-based Research. VDM Verlag, Saarbru ¨cken, Germany.
  9. Blackler, A., Hurtienne, J., 2007. Towards a unified view of intuitive interaction: definitions, models and tools across the world. MMI-Interaktiv 13 (Aug 2007), 37-55.
  10. Blackler, A., Popovic, V., Mahar, D., 2002. Intuitive use of products. In: Durling, D., Shackleton, J. (Eds.), Proceedings of Common Ground Design Research Society International Conference 2002, London.
  11. Blackler, A., Popovic, V., Mahar, D., 2003a. Designing for Intuitive Use of Products. An Investigation, In: Proceedings of 6th Asia Design Conference, Tsukuba, Japan.
  12. Blackler, A., Popovic, V., Mahar, D., 2003b. The nature of intuitive use of products: an experimental approach. Design Studies 24 (6), 491-506.
  13. Blackler, A., Popovic, V., Mahar, D., 2004a. Intuitive interaction with complex arte- facts. In: Redmond, J., Durling, D., DeBono, A. (Eds.), Proceedings of Future- ground Design Research Society International Conference, Melbourne.
  14. Blackler, A., Popovic, V., Mahar, D., 2004b. Studies of intuitive use employing observation and concurrent protocol. In: Marjanovic, D. (Ed.), Proceedings of Design 2004 8th International Design Conference, Dubrovnik, Croatia.
  15. Blackler, A., Popovic, V., Mahar, D., 2005. Intuitive Interaction Applied to Interface Design, In: Proceedings of International Design Congress, Douliou, Taiwan.
  16. Blackler, A., Popovic, V., Mahar, D., 2006. Towards a design methodology for applying intuitive interaction. In: Friedman, K., Love, T., Co ˆrte-Real, E., Rust, C. (Eds.), Proceedings of Wonderground, Design Research Society International Conference, Lisbon, Portugal.
  17. Blackler, A., Popovic, V., Mahar, D., 2007. Empirical investigations into intuitive interaction: a summary. MMI-Interaktiv 13 (Aug 2007), 4-24.
  18. Bocker, M., Suwita, A., 1999. The evaluation of the Siemens C10 Mobile Phone: usability testing beyond ''Quick and Dirty''. Proceedings of the Human Factors and Ergonomics Society Annual Meeting 1999 (1), 379-383.
  19. Boucouvalas, M., 1997. Intuition: the concept and the experience. In: Davis-Floyd, R., Arvidson, P.S. (Eds.), Intuition: the Inside Story Interdisciplinary Perspectives. Routledge, New York, pp. 3-18.
  20. Bowers, K.S., 1984. On being unconsciously influenced and informed. In: Bowers, K.S., Meichenbaum, D. (Eds.), The Unconscious Reconsidered. John Wiley and Sons, Toronto, pp. 227-272.
  21. Bowers, K.S., Regehr, G., Balthazard, C., Parker, K., 1990. Intuition in the context of discovery. Cognitive Psychology 22, 72-110.
  22. Cappon, D., 1994. A new approach to intuition. Omni 16 (1), 34-38.
  23. Carroll, R.T., 2003. Myers-Briggs type indicator. Available from: http://skepdic.com/ myersb.html (Retrieved 07.02.2005).
  24. CEI/IEC, 1998. International Standard 60417-2 Graphical symbols for use on equipment. first ed.
  25. Clark, A., 1997. Being There. Putting Brain, Body, and World Together Again. MIT Press, Cambridge, MA.
  26. Cremer, R., 1994. Matching vocational training programmes to age-related mental change -a social policy objective. In: Snel, J., Cremer, R. (Eds.), Work and Aging: a European Perspective. Taylor and Francis, London, pp. 274-282.
  27. Dorfman, J., Shames, V.A., Kihlstrom, J.F., 1996. Intuition, incubation, and insight: implicit cognition in problem solving. In: Underwood, G. (Ed.), Implicit Cogni- tion. Oxford University Press, New York, pp. 257-296.
  28. Dreyfus, H.L., Dreyfus, S.E., Athanasiou, T., 1986. Mind Over Machine: the Power of Human Intuition and Expertise in the Era of the Computer. Free Press, New York.
  29. Eysenck, H.J., 1995. Genius the Natural History of Creativity. Cambridge University Press, Cambridge.
  30. Fischbein, E., 1987. Intuition in Science and Mathematics. Reidel, Dordrecht, Holland.
  31. Fisk, A.D., Rogers, W.A., Charness, N., Czaja, S.J., Sharit, J., 2004. Designing for Older Adults: Principles and Creative Human Factors Approaches. CRC Press, Boca Raton, Florida.
  32. Frank, T., Cushcieri, A., 1997. Prehensile atraumatic grasper with intuitive ergo- nomics. Surgical Endoscopy 1997 (11), 1036-1039.
  33. Hammond, K.R., 1993. Naturalistic decision making from a Brunswikian viewpoint: its past, present, future. In: Klein, G.A., Orasanu, J., Calderwood, R., Zsambok, C.E. (Eds.), Decision Making in Action: Models and Methods. Ablex, Norwood, NJ, pp. 205-227.
  34. Howard, J.H., Howard, D.V., 1997. Learning and memory. In: Fisk, A.D., Rogers, W.A. (Eds.), Handbook of Human Factors and the Older Adult. Academic Press, San Diego, pp. 7-26.
  35. Hurtienne, J., Blessing, L., 2007. Design for Intuitive Use -Testing image schema theory for user interface design, In: Proceedings of 16th International Confer- ence on Engineering Design, Paris, 2007.
  36. Hurtienne, J., Israel, J.H., 2007. Image schemas and their metaphorical extensions - intuitive patterns for tangible interaction. In: Ullmer, B., Schmidt, A., Hornecker, E., Hummels, C., Jacob, R.J.K., Hoven, E.v. d. (Eds.), Proceedings of TEI'07. First International Conference on Tangible and Embedded Interaction, New York.
  37. Isen, A.M., Diamond, G.A., 1989. Affect and automaticity. In: Uleman, J.S., Bargh, J.A. (Eds.), Unintended Thought. The Guilford Press, New York, pp. 124-152.
  38. ISO/IEC, 2003. International Standard 18035. Information Technology -Icon symbols and functions for controlling multimedia software applications first ed.
  39. Jacoby, L.L., Witherspoon, D., 1982. Remembering without awareness. Canadian Journal of Psychology 36 (2), 300-324.
  40. Kang, S.B., 1998. Hands-free navigation in VR environments by tracking the head. International Journal of Human-Computer Studies 48, 247-266.
  41. Keppel, G., 1991. Design and analysis: A researcher's handbook. Prentice-Hall, New Jersey.
  42. King, L., Clark, J.M., 2002. Intuition and the development of expertise in surgical ward and intensive care nurses. Journal of Advanced Nursing 37 (4), 322-329.
  43. Klein, G., 1993. A Recognition-primed Decision (RPD) model of rapid decision making. In: Klein, G.A., Orasanu, J., Calderwood, R., Zsambok, C.E. (Eds.), Deci- sion Making in Action: Models and Methods. Ablex, Norwood, NJ, pp. 138-147.
  44. Klein, G., 1998. Sources of Power: How People Make Decisions. MIT Press, Cam- bridge, MA.
  45. Knopfle, C., Voss, G., 2000. An intuitive VR interface for design review. In: Di Gesu, V., Levialdi, S., Tarantinao, L. (Eds.), Proceedings of Working Conference on Advanced Visual Interfaces, Palermo, Italy.
  46. Kok, A., Lorist, M.M., Cremer, R., Snel, J., 1994. Age-related differences in mental work capacity: effects of task complexity and stressors on performance. In: Snel, J., Cremer, R. (Eds.), Work and Aging: a European Perspective. Taylor and Francis, London, pp. 139-161.
  47. Langdon, P., Lewis, T., Clarkson, J., 2007. The effects of prior experience on the use of consumer products. Universal Access in the Information Society 6 (2), 179-191.
  48. Laughlin, C., 1997. The nature of intuition: a neurophysiological approach. In: Davis- Floyd, R., Arvidson, P.S. (Eds.), Intuition: The Inside Story Interdisciplinary Perspectives. Routledge, New York, pp. 19-37.
  49. Lehikoinen, J., Roykkee, M., 2001. N-fingers: a finger-based interaction technique for wearable computers. Interacting with Computers 13 (2001), 601-625.
  50. Lewis, T., Langdon, P.M., Clarkson, P.J., 2008. Prior experience of domestic micro- wave cooker interfaces: a user study. In: Designing Inclusive Futures. Springer Verlag, pp. 3-14.
  51. Logan, G.D., 1985. Skill and automaticity: relations, implications, and future direc- tions. Canadian Journal of Psychology 39 (2), 367-386.
  52. Marsh, A., Setchi, R., 2008. Design for intuitive use: a study of mobile phones. Paper presented at the 4th I*PROMS Virtual International Conference. Available from: http://conference.iproms.org/conference/download/4000/91 (Retrieved 25.09.08).
  53. McMullen, S., 2001. Usability testing on a library web site redesign project. Refer- ence Services Review 29 (1), 7-22.
  54. Mescellany, P., 2002. Is there a UI generation gap? Available from: http://www. peterme.com/archives/00000348.html (Retrieved 07.07.05).
  55. Mohs, C., Hurtienne, J., Israel, J.H., Naumann, A., Kindsmu ¨ller, M.C., Meyer, H.A., et al., 2006. IUUI -intuitive use of user interfaces. In: Bosenick, T., Hassenzahl, M., Mu ¨ller-Prove, M., Peissner, M. (Eds.), Proceedings of Usability Professionals 2006, Stuttgart.
  56. Murakami, T., 1995. Direct and Intuitive Input Device for 3-D Shape Design, In: Proceedings of Design Engineering Technical Conference.
  57. Noddings, N., Shore, P.J., 1984. Awakening the Inner Eye Intuition in Education. Teachers College Press, Columbia University.
  58. Norman, D., 2002. The UI generation gap. Available from: http://www.peterme. com/archives/00000353.html (Retrieved 07.07.2005).
  59. O'Brien, M.A., Rogers, W.A., Fisk, A.D., 2008a. Developing a Framework for Intuitive Human-Computer Interaction. Paper presented at the 52nd Annual Meeting of the Human Factors and Ergonomics Society.
  60. O'Brien, M.A., Rogers, W.A., Fisk, A.D., 2008b. Understanding Intuitive Technology Use in Older Persons. Paper presented at the IFA's 9th Global Conference on Ageing.
  61. Okoye, H.C., 1998. Metaphor Mental Model Approach to Intuitive Graphical User Interface Design. Unpublished doctoral dissertation, Cleveland State University, Cleveland.
  62. Pearson, R., van Schaik, P., 2003. The effect of spatial layout of and link colour in web pages on performance in a visual search task and an interactive search task. International Journal of Human-Computer Studies 59 (2003), 327-353.
  63. Perkins, R., Keller, D.S., Ludolph, F., 1997. Inventing the Lisa user interface. Inter- actions JanþFeb, 40-53.
  64. Proctor, R.W., Lu, C.-H., Wang, H., Dutta, A., 1995. Activation of response codes by relevant and irrelevant stimulus information. Acta Psychologica 90, 275-286.
  65. Rabbitt, P.M.A., Carmichael, A., 1994. Designing communications and informa- tion-handling systems for elderly and disabled users. In: Snel, J., Cremer, R. (Eds.), Work and Aging: a European Perspective. Taylor and Francis, London, pp. 143-195.
  66. Raisamo, R., Raiha, K.J., 2000. Design and evaluation of the alignment stick. Inter- acting with Computers 12 (2000), 483-506.
  67. Raskin, J., 1994. Intuitive equals familiar. Communications of the ACM 37 (9), 17-18.
  68. Rasmussen, J., 1990. Skills, rules, and knowledge; signals, signs, and symbols, and other distinctions in human performance models. In: Venturino, M. (Ed.), Selected Readings in Human Factors. The Human Factors Society, Santa Monica, CA, pp. 61-70.
  69. Rasmussen, J., 1993. Deciding and doing: decision making in natural contexts. In: Klein, G.A., Orasanu, J., Calderwood, R., Zsambok, C.E. (Eds.), Decision Making in Action: Models and Methods. Ablex, Norwood, NJ, pp. 159-171.
  70. Reber, A.S., 1992. An evolutionary context for the cognitive unconscious. Philo- sophical Psychology 5 (1), 33-52.
  71. Reber, A.S., Walkenfield, F.F., Hernstadt, R., 1991. Implicit and explicit learning: individual differences and IQ. Journal of Experimental Psychology: Learning, Memory and Cognition 17 (5), 888-896.
  72. Richman, H.B., Gobet, F., Staszewski, J.J., Simon, H.A., 1996. Perceptual and memory processes in the acquisition of expert performance: the EPAM model. In: Ericsson, K.A. (Ed.), The Road to Excellence. The Acquisition of Expert Perfor- mance in the Arts and Sciences, Sports and Games. Lawrence Erlbaum Associ- ates, Mahwah, NJ, pp. 167-187.
  73. Rudinger, G., Espey, J., Neuf, H., Paus, E., 1994. Aging and modern technology: how to cope with products and services. In: Snel, J., Cremer, R. (Eds.), Work and Aging: a European Perspective. Taylor and Francis, London, pp. 163-171.
  74. Rutter, B.G., Becka, A.M., Jenkins, D., 1997. A user-centered approach to ergonomic seating: a case study. Design Management Journal Spring, 27-33.
  75. Salk, J., 1983. Anatomy of Reality Merging of Intuition and Reason. Columbia University Press, New York.
  76. Smith, D., Irby, C., Kimball, R., Verplank, B., 1982. Designing the star user interface. Byte 7 (4), 242-282.
  77. Thomas, B., van-Leeuwen, M., 1999. The user interface design of the fizz and spark GSM telephones. In: Green, W.S., Jordan, P.W. (Eds.), Human Factors in Product Design. Current Practice and Future Trends. Taylor and Francis, London, pp. 103- 112.
  78. Vera, A.H., Simon, H.A., 1993. Situated action: a symbolic interpretation. Cognitive Science 17, 7-48.
  79. Vermeeren, A.P.O.S., 1999. Designing scenarios and tasks for user trials of home electronic devices. In: Green, W.S., Jordan, P.W. (Eds.), Human Factors in Product Design. Current Practice and Future Trends. Taylor and Francis, London, pp. 47-55.
  80. Vroubel, M., Markopoulos, P., Bekker, M., 2001. FRIDGE: exploring intuitive inter- action styles for home information appliances. CHI, 207-208.
  81. Wickens, C.D., 1992. Engineering Psychology and Human Performance, second ed. HarperCollins Publishers, Inc, New York.
  82. Wickens, C.D., Gordon, S.E., Liu, Y., 1998. An Introduction to Human Factors Engi- neering. Addison-Wesley Educational Publishers Inc, New York.
  83. Woolhouse, L.S., Bayne, R., 2000. Personality and the use of intuition: individual differences in strategy and performance on an implicit learning task. European Journal of Personality 14, 157-169.

Related papers

Intuitive interaction with complex artefacts
Vesna Popovic

2006

This thesis examines the role of intuition in the way that people operate unfamiliar devices, and the importance of this for designers. Intuition is a type of cognitive processing that is often non-conscious and utilises stored experiential knowledge.

View PDFchevron_right
The nature of intuitive use of products: an experimental approach
Douglas Mahar

Design Studies, 2003

The term "intuitive use" has been widely used with respect to various products and systems but has not yet been adequately defined. Through an extensive literature review, it was concluded that intuition is a cognitive process that utilises knowledge gained through prior experience. Intuitive use of products involves utilising knowledge gained through other products or experience(s). Therefore, products that people use intuitively should be those with features they have encountered before. A set of experiments with a digital camera was conducted to test the thesis. The results of these experiments support the thesis. It was found that prior knowledge of features or functions of the camera allowed participants to use those features intuitively, whereas unfamiliar features or functions had to be figured out, which was more time consuming and effortful.

View PDFchevron_right
Designing for Intuitive Use of Products: An Investigation
Douglas Mahar

This paper will explore the application of "intuitive use" to design. A literature review has revealed that intuition is based on experiential knowledge. Therefore, people can only use intuitive processing if they have had previous experience to draw on, and so the things that humans use intuitively are those that employ features which they have encountered before. In a previous study, these authors found through experimentation that prior knowledge of features or functions of a digital camera allowed participants to use those features intuitively, whereas unfamiliar features or functions had to be worked out, which was more time consuming and effortful.

View PDFchevron_right
Empirical investigations into intuitive interaction: a summary
Douglas Mahar

Intuition is a type of cognitive processing that is often non-conscious and utilises stored experiential knowledge. Intuitive interaction involves the use of knowledge gained from other products and/or experiences. We have developed novel approaches and techniques for studying intuitive use of interfaces, and shown that intuitive interaction is based on past experience with similar things , b, 2004a, b, 2005. Two initial experimental studies revealed that prior exposure to products employing similar features helped participants to complete set tasks more quickly and intuitively, and that familiar features were intuitively used more often than unfamiliar ones. A third experiment revealed that appearance of features seems to be the variable that most affects time spent on a task and intuitive uses. Based on our empirical work, we have developed principles and tools for designers to assist them in making interfaces more intuitive.

View PDFchevron_right
Studies of Intuitive Use Employing Observation and Concurrent Protocol
Douglas Mahar
View PDFchevron_right

Related topics

  • Applied Ergonomics
  • Medical Physiology
  • Task Performance and Analysis
  • Equipment Design

    • Cited by

    Ageing, Technology Anxiety and Intuitive Use of Complex Interfaces
    Vesna Popovic

    Lecture Notes in Computer Science, 2013

    This paper presents the outcome of a study that investigated the relationships between technology prior experience, self-efficacy, technology anxiety, complexity of interface (nested versus flat) and intuitive use in older people. The findings show that, as expected, older people took less time to complete the task on the interface that used a flat structure when compared to the interface that used a complex nested structure. All age groups also used the flat interface more intuitively. However, contrary to what was hypothesised, older age groups did better under anxious conditions. Interestingly, older participants did not make significantly more errors compared with younger age groups on either interface structures.

    View PDFchevron_right
    A toolkit for animal touchscreen slider design
    Clint Zeagler

    Proceedings of the Fifth International Conference on Animal-Computer Interaction

    Animal-computer interaction is a quickly growing field in computer science however unlike HCI, there are no tools to ease interface development for its users, increasing overhead. Here, we present the beginning of a toolkit created specifically for animal interactions. We implement a gesturebased interface, a slider, as it is highly configurable in shape, colour, and feedback allowing it to be as simple or complex as desired. The resultant interface can be in any shape, provides 20 run-time configuration options, and collects usage data for qualitative analysis. The toolkit reduces the effort needed to build gestural animal interfaces for research or everyday use. CCS CONCEPTS • Human-centered computing → Touch screens; User interface toolkits; KEYWORDS Touchscreen; Toolkit; Virtual User Interface; Animal Computer Interaction 1 INTRODUCTION An increasing subset of the animal kingdom is being evaluated in interaction studies as the Animal-Computer Interaction (ACI) field grows. However, existing interface design tools are understandably designed for human interaction

    View PDFchevron_right
    Connected cane: Tactile button input for controlling gestures of iOS voiceover embedded in a white cane
    Vincent Martin

    Assistive Technology, 2017

    Accessibility of assistive consumer devices is an emerging research area with potential to benefit both users with and without visual impairments. In this article, we discuss the research and evaluation of using a tactile button interface to control an iOS device's native VoiceOver Gesture navigations (Apple Accessibility, 2014). This research effort identified potential safety and accessibility issues for users trying to interact and control their touchscreen mobile iOS devices while traveling independently. Furthermore, this article discusses the participatory design process in creating a solution that aims to solve issues in utilizing a tactile button interface in a novel device. The overall goal of this study is to enable visually impaired white cane users to access their mobile iOS device's capabilities navigation aids more safely and efficiently on the go.

    View PDFchevron_right
    Intuitive Interaction with Motion Controls in a Tennis Video Game
    Thea Blackler

    Proceedings of the Annual Symposium on Computer-Human Interaction in Play, 2020

    This paper broadens understanding of intuitive use in games by testing the influence of three naturally mapped motion control interfaces in the context of a tennis video game. It also extends exploratory work on natural mapping and intuitive interaction in video games by refining instruments to measure game technology familiarity. Repeated-measures experiment data (N = 120) is analysed via mixed ANOVAs with four distinct player characteristic variables. As with broader intuitive interaction research, results show that more familiar players performed more effectively; however, where differences exist, they point towards increased intuitive use gains with more naturally mapped control interfaces. Subjective measures suggest that control interfaces were perceived as more intuitive when they had higher levels of natural mapping, yet also point to the influencing roles of familiarity and the dimensions of the control types in shaping these perceptions.

    View PDFchevron_right
    580 California St., Suite 400
    San Francisco, CA, 94104
    © 2025 Academia. All rights reserved