The challenge of interface design for communication theory: from interaction metaphor to contexts of discovery

Keeler, Mary; Denning, Susan

doi:10.1016/0953-5438(91)90018-w

Cited by 13 publications

(4 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…If they collect too small a sample, they might fail to detect problems that, uncorrected, would reduce the usability of the product. Discussing usability testing, Keeler and Denning (1991) showed a common negative attitude toward small-sample usability studies when they stated, "actual [usability] test procedures cut corners in a manner that would be unacceptable to true empirical investigations. Test groups are small (between 6 and 20 subjects per test)" (p. 290).…”

Section: Introductionmentioning

confidence: 99%

Sample Sizes for Usability Studies: Additional Considerations

1994

View full text Add to dashboard Cite

Recently, Virzi (1992) presented data that support three claims regarding sample sizes for usability studies. The claims were (1) observing four or five participants will allow a usability practitioner to discover 80% of a product's usability problems, (2) observing additional participants will reveal fewer and fewer new usability problems, and (3) more severe usability problems are easier to detect with the first few participants. Results from an independent usability study clearly support the second claim, partially support the first, but fail to support the third. Problem discovery shows diminishing returns as a function of sample size. Observing four to five participants will uncover about 80% of a product's usability problems, as long as the average likelihood of problem detection ranges between .32 and .42, as in Virzi (1992). If the average likelihood of problem detection is lower, then a practitioner will need to observe more than five participants to discover 80% of the problems. Using behavioral categories for problem severity (or impact), these data showed no correlation between problem severity (impact) and rate of discovery. The data provided evidence that the binomial probability formula may provide a good model for predicting problem-discovery curves, given an estimate of the average likelihood of problem detection. Finally, data from economic simulations that estimated return-on-investment (ROI) under a variety of settings showed that only the average likelihood of problem detection strongly influenced the range of sample sizes for maximum ROI. Other variables, such as the number of problems available for discovery, costs to run a study, costs of fixing problems and costs of failing to fix problems, had a much smaller influence on the sample size that maximized ROI.

show abstract

Section: Introductionmentioning

confidence: 99%

Sample Sizes for Usability Studies: Additional Considerations

1994

View full text Add to dashboard Cite

show abstract

“…This is a common research technique in studies of user-interface interaction (e.g., Wang et al, 2000;Light and Wakeman, 2001), as it captures some of the frustrations that users experience when trying to communicate with an interface as a conversational partner that does not appear to 'understand' them (see Keeler and Denning, 1991). Before being presented with the interface, participants were briefed on their task, which was to apply for a mortgage online.…”

Section: Data Collectionmentioning

confidence: 99%

Evaluating the effectiveness of customers’ communication experiences with online retailers – A study of e-mortgages

Coughlan

Macredie

Patel

2007

Interacting with Computers

View full text Add to dashboard Cite

Retailers increasingly use the Internet for supporting customer interaction in the delivery of products and services online, whilst simultaneously displacing direct communication to a seller with 'faceless' technology. Research has tended to marginalise the importance of this communication change, possibly because of the lack of appropriate models for evaluating communication effectiveness. This paper therefore seeks to develop and apply such an evaluative model, which is underpinned by communication theory. The context of application is e-mortgage lending -based on the selection of two banks' interfaces -as evidence suggests that this type of e-commerce activity presents difficulties in electronic communication where, for example, the customer need for face-to-face mortgage advice prevails. Findings from the model's application reveal that whilst users respond socially to the interfaces, a number of communication problems can be identified by theme. Reflection is provided on the model's usefulness for evaluating the effectiveness of customers' online communication experiences.

show abstract

“…de Castro Salgado et al (2011), but the literature on computer technology design provides few reflective analysis of interaction, such as the assessment by e.g. Keeler and Denning (1991). Precedent critiques by Dreyfus (1992), and by Winograd and Flores (1988) only lightly touch upon the issue of interaction per se.…”

Section: Where Interaction Is Notmentioning

confidence: 99%

Where the Interaction Is Not

Pineda¹

2016

International Journal of Art, Culture, Design, and Technology

View full text Add to dashboard Cite

The concept of interaction is foundational in technology interface design with its presuppositions being taken for granted. But the interaction metaphor has become ambiguous to the extent that its application to interface design contributes to misalignments between people's expected and actual experience with computers. This article re-examines the presuppositions governing human-computer interaction with the motivation of strengthening weaknesses in their foundational concepts. It argues for abandoning the interaction metaphor to refocus design discourse toward the mediation roles of technology interfaces. ‘Remediation', i.e. representation of one medium in another, is proposed as a conceptual model that more precisely describes the human-to-computer actions.

show abstract

The challenge of interface design for communication theory: from interaction metaphor to contexts of discovery

Cited by 13 publications

References 9 publications

Sample Sizes for Usability Studies: Additional Considerations

Sample Sizes for Usability Studies: Additional Considerations

Evaluating the effectiveness of customers’ communication experiences with online retailers – A study of e-mortgages

Where the Interaction Is Not

Contact Info

Product

Resources

About