Powerful and consistent analysis of likert-type rating scales

Kaptein, Maurits; Nass, Clifford; Markopoulos, Panos

doi:10.1145/1753326.1753686

Cited by 102 publications

(78 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…However, it is worth noting that both the radar and bar graph are skewed towards high values, indicating that neither visualization is particularly difficult to understand. Preference and Ease of use data was collected using a standard 5 point Likert scale, and as such is not suitable for standard parametric analysis due to the lack of normality [17]. We applied the Aligned Rank Transformation (ART) using the ART-Tool [24] to transform our Likert rating scales for Radar Preference, Bar Preference, Radar Ease-of-Use, and Bar Ease-of-Use into normalized distributions which can then be correctly analyzed using standard parametric analysis.…”

Section: 3mentioning

confidence: 99%

Towards Adaptive Information Visualization: On the Influence of User Characteristics

Toker

Conati

Carenini

et al. 2012

Lecture Notes in Computer Science

View full text Add to dashboard Cite

Abstract. The long-term goal of our research is to design information visualization systems that adapt to the specific needs, characteristics, and context of each individual viewer. In order to successfully perform such adaptation, it is crucial to first identify characteristics that influence an individual user's effectiveness, efficiency, and satisfaction with a particular information visualization type. In this paper, we present a study that focuses on investigating the impact of four user characteristics (perceptual speed, verbal working memory, visual working memory, and user expertise) on the effectiveness of two common data visualization techniques: bar graphs and radar graphs. Our results show that certain user characteristics do in fact have a significant effect on task efficiency, user preference, and ease of use. We conclude with a discussion of how our findings could be effectively used for an adaptive visualization system. Keywords: User characteristics, User Evaluation, Adaptive Information Visualization. IntroductionInformation visualization is a thriving area of research in the study of human/computer communication. Though the field has made substantial progress in measuring and formalizing visualization effectiveness, results and suggestions from the literature are sometimes inconclusive and conflicting [19]. We believe this may be attributed to the fact that existing visualizations are designed mostly around the target data set and associated task model, with little consideration for user differences. Both long term user characteristics (e.g., cognitive abilities and expertise) and short term factors (e.g., cognitive load and attention) have often been overlooked in the design of information visualizations, despite studies linking individual differences to visualization efficacy for search and navigation tasks [1,8], for information seeking tasks [7,25], as well as anecdotal evidence of diverse personal visualization preferences [3]. Our long term goal is to explore the possibilities of user-centered visualizations, which understand that different users have different visualization needs and abilities, and which can adapt to these differences. However, before adaptation strategies can be effectively specified, we believe that the influence of user characteristics on visua-

show abstract

Section: 3mentioning

confidence: 99%

Towards Adaptive Information Visualization: On the Influence of User Characteristics

Toker

Conati

Carenini

et al. 2012

Lecture Notes in Computer Science

View full text Add to dashboard Cite

show abstract

“…At the end of each experiment, a few questions were used to survey the participants. For each question, the participants can specify their level of agreement in 5-point Likert scale [22]: strongly agree (5), agree (4), neutral (3), disagree (2), or strongly disagree (1). The survey question "is WYSIWYG format editor easy to learn?"…”

Section: Discussionmentioning

confidence: 99%

A Report Generator for Database and Web Applications

Chen

2012

IEICE Trans. Inf. & Syst.

View full text Add to dashboard Cite

SUMMARYReport generation is one of the most important tasks for database and e-commerce applications. Current report tools typically provide a set of predefined components that are used to specify report layout and format. However, available layout options are limited, and WYSIWYG formatting is not allowed. This paper proposes a four-phase report generation process to overcome these problems. The first phase retrieves source tables from the database. The second phase reorganizes the layout of the source tables by transferring the source tables into a set of new flat tables (in the first normal form). The third phase restructures the flat tables into a nested table (report) by specifying the report structure. The last phase formats the report with a WYSIWYG format editor supporting a number of formatting rules designed specifically for nested reports. Each phase of the proposed process supports visual programming, giving an easy-to-use user interface and allowing very flexible report layouts and formats. A visual end-user-programming tool, called TPS, is developed to demonstrate the proposed process and show that reports with sophisticated layouts can be created without writing low-level report generation programs.

show abstract

“…In respect of the recommendations of this qualitative study, the model then was revised as the input of the quantitative validation [18] in the second stage of the examinations. The five Likert scale [50] questionnaires were sent to 130 IS project stakeholders in the sample institution and around 48% (n=62) of these respondents responded the survey. Considering the strong of the statistics software in exploration and prediction of a small sample size [51][52], the researchers used the SmartPLS 2.0 to analyze the measurement and its structural models of the model.…”

Section: Methodsmentioning

confidence: 99%

A Coherent Framework for Understanding the Success of an Information System Project

et al. 2016

View full text Add to dashboard Cite

This paper elucidates the sequential revisions of an information system (IS) project framework across the research model development and its examinations. The authors adopted, adapted, and combined five concepts of the project management discipline and the information processing theory Keywords: ICT project framework, multi-dimensional perspectives, interrelation concept, model validationCopyright © 2016 Universitas Ahmad Dahlan. All rights reserved. IntroductionOne of reasons why numerous studies [1][2][3] indicated that the IS project management is the immature discipline; it may because the performance of the projects still show its high failure rate [4]. As it was initiated by the Standish Group's report in the mid of 1990s, and the similar announcements were presented by numerous survey studies [5][6][7]. In respect of this issue, Subiyakto and Ahlan [8][9] identified several gaps of this field, among others, there are the ambiguity of the project success definition [10][11][12], the use of the partial perspective in its success measurement [12][13][14][15], and the tendency of the critical success factor (CSF) determination methods [7,9]. Accordingly, they proposed a coherent-conceptual framework based on their scanning the depth and breadth of the body of knowledge in the research field [8]. They hoped that the framework will be one of references for researchers and practitioners to understand the success of an IS project in term of its multi-dimensions. Sequentially, these scholars developed their IS project success model [16] and then, examined the model qualitatively [17] and quantitatively [18].The next questions are how to explore the framework following its development and the examinations of the research model and how to understand the interrelationship between this framework and the model. These issues may be a triviality for many scholars who had experiences and expertise in the research works, but these are not for the beginners or inexpert ones in the works. Besides the clarity of the interrelationship is one of the significant points of a research model assessment, it is also rare to be presented in many literatures. This paper demonstrates the development and its revisions of an IS project framework and its interrelationship with the research model. The objectives are to explore theoretically the revised framework and to understand its interrelationship with the examined model. This framework and its model mapping, which were represented here, they may be a learning point for scholars, particularly in their model validity developments. There are the four main sections of the paper. First, the literature review section elucidates the basis theories and concepts of the

show abstract

Powerful and consistent analysis of likert-type rating scales

Cited by 102 publications

References 13 publications

Towards Adaptive Information Visualization: On the Influence of User Characteristics

Towards Adaptive Information Visualization: On the Influence of User Characteristics

A Report Generator for Database and Web Applications

A Coherent Framework for Understanding the Success of an Information System Project

Contact Info

Product

Resources

About