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Set of candidate items for comprehensibility 3

Set of candidate items for comprehensibility 3

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Conference Paper
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The UEQ+ is a modular framework for the construction of UX questionnaires. The researcher can pick those scales that fit his or her research question from a list of 16 available UX scales. Currently, no UEQ+ scales are available to allow measuring the quality of voice interactions. Given that this type of interaction is increasingly essential for t...

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Context 1
... highest loadings are found in items 3, 4, 5, and 8. The introductory sentence is as follows: Table 3 shows the corresponding results for the scale Comprehensibility. The three highest loadings are found in items 1, 4, and 8. Item 8 was not selected because it showed an overlap with item 9 of Response quality (see table 2). ...

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Citations

... Recent research includes several attempts to define important UX aspects of VUI using an expertdriven process (Hone and Graham, 2000;Kocaballi et al., 2019;Klein et al., 2020a). To the best of our knowledge, however, there is no user-driven identification of relevant UX aspects for VUIs that is based on up-to-date user data. ...
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... Walaupun metode UEQ telah banyak digunakan untuk mengukur pengalaman pengguna berbagai aplikasi termasuk pembelajaran elektronik [6]- [11], sistem pengelolaan administrasi akademik [12], [13], e-commerce [14]- [16], aplikasi kesehatan [17], [18], dan e-government [19], hingga saat ini masih sedikit sekali penelitian yang memanfaatkan UEQ+ karena framework ini masih tergolong baru. Beberapa penelitian yang telah menggunakan UEQ+ di antaranya adalah penelitian yang mengukur pengalaman pengguna dari voice assistant [20], [21], aplikasi ujian mobile [22], dan website universitas [23]. ...
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Chapter
In recent years there has been an increase of voice interfaces, driven by developments in Artificial Intelligence and the expansion of commercial devices that use them, such as smart assistants present on phones or smart speakers. One field that could take advantage of the potential of voice interaction is in the self-administered surveys data collection, such as standardized UX evaluation questionnaires. This work proposes a set of conversational design patterns for standardized UX evaluation questionnaires that use semantic difference scales as a means of collecting quantitative information on user experience, as is the case of AttrakDiff and UEQ (User Experience Questionnaire). The presented design patterns seek to establish a natural conversation created in accordance with the user, the conservation of context between subsequent questions, the minimization of statements and with statement repair mechanisms not completely understood by the user or voice agent, as eliciting explanation of a concept or repetition.
... Existing questionnaires should be extended or a new questionnaire should be created to evaluate VAs, which should lead to improvements in VAs. For example, a new and flexible method is the modular framework UEQ+ based on various scales to construct a product-specific questionnaire for which three VUI scales have been developed but not yet validated [16]. Others, however, focus on exploring current users, use cases, and systems to understand VA interaction, as well as finding design patterns [2,6,28]. ...
... Another category could be response quality, which combines other answer options such as ability to answer quicker, sound more natural, ability to distinguish between users, and ability to recognize feelings. These categories merge appropriate response options as, e.g., the voice quality scales of the UEQ+ framework, which contain four bipolar item-pairs with 7-point Likert-type scales [16,25]. These scales contain very similar product characteristics as those that are assigned to UX aspects. ...
... Therefore, we intend to ask them about how they use VAs in order to identify research gaps regarding assessment methods and the VA context of use [14]. Our study results can help extend measurement methods, e.g., scale construction for the UEQ+ framework regarding VUI assessment [16]. Hence, we must define relevant UX criteria depending on the VA use case and apply the factorial analysis to identify single factors [17]. ...
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... We must keep in mind that users have dierent needs (e.g., children vs. parents vs. people with disabilities) that could result in dierent design solutions. Research has already started to explore with questionnaires [9,10] and interviews the risks and opportunities of VAs (e.g., cultures [6,22], use cases [1,3], existing users, or potential users [1,3,22]). ...
... An example could be using ambient light to encode whether or not the microphone is listening [11]. In addition, we can design prototypes with dierent users, design concepts, and use cases and employ qualitative (e.g., interviews) and quantitative evaluation (e.g., questionnaires for VUIs [9]) to determine which designs are accepted by users or raise concerns. I also developed systems for user groups that need more protection, such as children [16,19,20]. ...
... The advantage of the context analysis is the structured way in which assumptions are backed up or put into context by users' statements. Additionally, we should consider using the existing UEQplus Framework with newly developed VUI scales to measure VAs [9,21]. ...
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... In a second step, we updated the list of UX factors Hinderks et al. (2020b) by including the UX factors from the UX questionnaire 'User Experience Questionnaire Plus (UEQ+)' Schrepp and Thomaschewski (2019b). Additionally, we included the UX factors from Klein et al. (2020) and Otten et al. (2020). These UX factors are specifically for voice assistants, such as Alexa, Siri, or Google Home. ...
... 4 Overview of all UX Factors fromHinderks et al. (2020b),Schrepp and Thomaschewski (2019b),Klein et al. (2020), andOtten et al. (2020) Dependability: The product always responds to user interaction in a predictable and consistent way.UX factorHinderks Schrepp Klein Otten Ease of Use: The product is easy to operate. X Efficiency: The user can reach their goals with minimum time required and minimum physical effort. ...
Thesis
Context. Agile methods are increasingly being used by companies, to develop digital products and services faster and more effectively. Today's users not only demand products that are easy to use, but also products with a high User Experience (UX). Agile methods themselves do not directly support the development of products with a good user experience. In combination with UX activities, it is potentially possible to develop a good UX. Objective. The objective of this PhD thesis is to develop a UX Lifecycle, to manage the user experience in the context of Agile methods. With this UX Lifecycle, Agile teams can manage the UX of their product, in a targeted way. Method. We developed the UX Lifecycle step by step, according to the Design Science Research Methodology. First, we conducted a Structured Literature Review (SLR) to determine the state of the art of UX management. The result of the SLR concludes in a GAP analysis. On this basis, we derived requirements for UX management. These requirements were then implemented in the UX Lifecycle. In developing the UX Lifecycle, we developed additional methods (UX Poker, UEQ KPI, and IPA), to be used when deploying the UX Lifecycle. Each of these methods has been validated in studies, with a total of 497 respondents from three countries (Germany, England, and Spain). Finally, we validated the UX Lifecycle, as a whole, with a Delphi study, with a total of 24 international experts from four countries (Germany, Argentina, Spain, and Poland). Results. The iterative UX Lifecycle (Figure 1) consists of five steps: Initial Step 0 ‘Preparation’, Step 1 ‘UX Poker’ (before development/Estimated UX), Step 2 ‘Evaluate Prototype’ (during development/Probable UX), Step 3 ‘Evaluate Product Increment’ (after development/Implemented UX), and a subsequent Step 4 ‘UX Retrospective’. With its five steps, the UX Lifecycle provides the structure for continuously measuring and evaluating the UX, in the various phases. This makes it possible to develop the UX in a targeted manner, and to check it permanently. In addition, we have developed the UX Poker method. With this method, the User Experience can be determined by the Agile team, in the early phases of development. The evaluation study of UX Poker has indicated that UX Poker can be used to estimate the UX for user stories. In addition, UX Poker inspires a discussion about UX, that results in a common understanding of the UX of the product. To interpret the results from the evaluation of a prototype and product increment, we developed or derived the User Experience Questionnaire KPI and Importance-Performance Analysis. In a first study, we were able to successfully apply the two methods and, in combination with established UEQ methods, derive recommendations for action, regarding the improvement of the UX. This would not have been possible without their use. The results of the Delphi study, to validate the UX Lifecycle, reached consensus after two rounds. The results of the evaluation and the comments lead to the conclusion, that the UX Lifecycle has a sufficiently positive effect on UX management. Conclusion. The goal-oriented focus on UX factors and their improvement, as propagated in the UX Lifecycle, are a good way of implementing UX management in a goal-oriented manner. By comparing the results from UX Poker, the evaluation of the prototype, and product increment, the Agile team can learn more about developing a better UX, within a UX retrospective. The UX Lifecycle will have a positive effect on UX management. The use of individual components of the UX Lifecycle, such as UX Poker or Importance-Performance Analysis, already helps an Agile team to improve the user experience. But only in combination with the UX Lifecycle and the individual methods and approaches presented in this PhD thesis, is a management of the user experience in a targeted manner possible, in our view. This was the initial idea of this PhD thesis, which we are convinced we could implement.
... The UEQ+ contains 20 scales to measure specific UX aspects, which can be combined into a product-related questionnaire. The newly constructed scales for voice quality consider the UX aspects of VUIs and fill the voice interaction gap within UEQ+ [13]. ...
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Voice user interfaces (VUI) are currently a trending topic but the ability to measure and improve the user experience (UX) is still missing. We aim to develop a tool selector as a web application that can provide a suitable tool to measure UX quality of VUIs. The UX tool selector for VUIs will include a UX measurement toolbox containing several existing and new VUI assessment methods. The UX tool selector will provide context-dependent measurement recommendations without prior extensive research to evaluate and improve VUIs.
... Stimulation). o Useful tool for evaluating [7] o Existing tools measure usability [8] o • Research gap o UEQ+ lacks scales for VUI. ...
Presentation
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Präsentation zum World Usability Day in Osnabrück am 12.11.2020
... Existing questionnaires need to be extended or a new questionnaire should be created to evaluate VAs, which should lead to improvements in VAs. For example, a new and flexible method is the modular framework UEQ+ based on various scales to construct a product-specific questionnaire for which three VUI scales have been developed but not validated yet (Klein et al., 2020b). ...
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Voice user interfaces (VUIs) or voice assistants (VAs) such as Google Home or Google Assistant (Google), Cortana (Mircosoft), Siri (Apple) or Alexa (Amazon) are highly available in the consumer sector and present a smart home trend. Still, the acceptance seems to be culture-dependent, while the syntax of communication poses a challenge. So, there are some basic questions: 'Why do people buy VAs?' 'What do they use them for?' 'What could be improved in the future?'. We explore the opinion of a German technology-based user group to identify the challenges and opportunities of VAs. We focus on the interaction behaviour, frequency of use, concerns, and opinions of this target group as they show a higher variety of interaction as well as privacy concerns in representative population studies. Our preliminary findings confirm previous results (missing accuracy of commands and serious concerns about privacy issues) and show that technology-based users from Germany are intensive users, although with particular concerns about data collection. Probably, there is a correlation between privacy concerns and speech intelligibility as queries relating to VAs are problematic due to repetitions and refinement.