The MDS-ANAVA technique for assessing knowledge representationdifferences between skill groups

Knowledge representation is one of important factors that determine human performance on cognitive tasks. Due to different levels of experience, different groups of people may develop different knowledge representations which lead to different levels of performance on cognitive tasks. If knowledge representation differences exist between skill groups such as experts and novices, those differences can be used to guide the training of novices for skill acquisition, and to assist the design of jobs and tools for performance enhancement. A technique is presented in this paper for assessing knowledge representation differences between skill groups, based on multidimensional scaling (MDS) of dissimilarity data and analysis of angular variance (ANAVA). The MDS-ANAVA technique was applied to two sets of dissimilarity data that were obtained from ten experts and ten novices in the computer domain, one set concerning 23 concepts in C computer programming, and another set concerning 21 concepts in the UNIX operating system. Knowledge representation differences from the MDS-ANAVA technique are compared with those from the hierarchical clustering technique. The MDS-ANAVA technique shows several advantages to the hierarchical clustering technique in testing the statistical significance of knowledge representation differences between skill groups and revealing features underlying knowledge representations of skill groups     

Experts' systems instead of expert systems

By studying several cases of expert systems' use, a variety of difficulties were identified as directly depending on specific characteristics of experts and their tasks. This concerns more than the questions: “May experts be replaced by machines?” or “Is experts' knowledge explicable?”. The organisational structure of their work as well as the cyclic, non-plannable way of their task performing have further relevance. The paper introduces the concept of experts' systems to deal with diversities of their expertise and complexities of their work. It draws a distinction between non-monotonic problem solving, exploration, medium and modification, and argues that these modes are not reducible to yet another improved input/output strategy or dialogue style but introduce additional functions supporting the human-computer interaction according to experts' needs. In the first few sections, the paper covers the theoretical and empirical results of our research, whereas Section 4 introduces our design suggestions for experts' systems.     

基于双层专家权重确定的风险型大群体决策

针对风险型大群体决策问题,考虑专家权重确定的复杂性,提出基于累积前景理论的决策信息处理和考虑双层专家权重确定的大群体决策方法.采用二元语义获取并表达专家的评价信息;基于累积前景理论计算方案的综合前景价值矩阵;采用双层专家权重确定方法,第1层利用聚类方法对大群体成员价值向量进行聚类,根据聚类结果确定聚集群权重, 第2层利用熵权法获得专家熵权,二者结合得到专家权重.通过确定专家权重和综合前景价值矩阵得出最终的决策结果.最后通过算例表明了所提出方法的可行性和有效性.     

A Design Thinking Rationality Framework: Framing and Solving Design Problems in Early Concept Generation

The concept of “Design Thinking” opens up debate regarding the prevalent human–computer interaction design practice. This article focuses specifically on the cognitive processes of designers during their early design activities. Two groups of designers—experts and novices—were asked to develop a fictitious vacuum cleaner. We then examined the different ways in which these groups manage their design thinking processes and how the groups choose design concepts. The empirical study revealed that expert designers are effective at framing design problems. They make quick decisions (through the use of the affect heuristic) but are more wedded to their own previously developed design concepts, which they do not change in subsequent design stages. In contrast, novice designers are less skilled in framing new design problems but better able to renounce their initial design concepts. These diverse design thinking approaches are linked to potential problems. We then discuss how to address these concerns in conjunction with empathy for the artifact (i.e., artifact empathy via the mediated self) or user (i.e., user empathy via the simulated self), problem framing with second-order semantic connotations, and irrationality when analyzing design solutions. Finally, we propose a design thinking rationality framework that can establish a designer's view of design activities and thereby assist designers educated in both creative and rational design decisions.     

HCI and business practices in a collaborative method for augmented reality systems

ContextEvery interactive system is composed of a functional core and a user interface. However, the software engineering (SE) and human–computer interaction (HCI) communities do not share the same methods, models or tools. This usually induces a large work overhead when specialists from the two domains try to connect their applicative studies, especially when developing augmented reality systems that feature complex interaction cores.ObjectiveWe present in this paper the essential activities and concepts of a development method integrating the SE and HCI development practices, from the specifications down to the design, as well as their application on a case study.MethodThe efficiency of the method was tested in a qualitative study involving four pairs of SE and HCI experts in the design of an application for which an augmented reality interaction would provide better user performance than a classic interactive system. The effectivity of the method was evaluated in a qualitative study comparing the quality of three implementations of the same application fragment (based on the same analysis model), using software engineering metrics.ResultsThe first evaluation confirmed the ease of use of our method and the relevance of our tools for guiding the design process, but raised concerns on the handling of conflicting collaborative activities. The second evaluation gave indications that the structure of the analysis model facilitates the implementation of quality software (in terms of coupling, stability and complexity).ConclusionIt is concluded that our method enables design teams with different backgrounds in application development to collaborate for integrating augmented reality applications with information systems. Areas of improvement are also described.     

专家交互情境下不完备群组DEMATEL决策方法

为克服现有群组DEMATEL存在的尚未考虑群组专家之间的信息交互、对于不完备专家判断信息的推断机理不明确等缺陷,基于社交网络中的信任关系理论和凝聚层次聚类理论,通过给出不完备群组DEMATEL初始直接影响矩阵残缺值的推断方法和专家交互情境下群组DEMATEL直接影响矩阵信息修正方法,提出专家交互情境下不完备群组DEMATEL决策方法的实现步骤.最后,通过算例对比分析反映出通过专家多轮次交互,群组专家之间的共识度以及决策结果的可靠性持续提升,从而验证了所提出方法的科学性和可行性.     

Security and human computer interfaces

Computer users are exposed to technology mainly through user interfaces. Most users' perceptions are based on their experience with these interfaces. HCI (human computer interaction) is concerned with these interfaces and how they can be improved. Considerable research has been conducted and major advances have been made in the area of HCI. Information security is becoming increasingly important and more complex as business is conducted electronically. However, state-of-the-art security-related product development has ignored general aspects of HCI. The objective of this paper is to promote and enable security awareness of end-users in their interaction with computer systems. It thus aims to consolidate and integrate the two fields of information security and HCI. HCI as a research discipline is a well developed field of study, and the authors are of the opinion that the use of security technologies can be significantly enhanced by employing proven HCI concepts in the design of these technologies. In order to achieve this, various criteria for a successful HCI in a security-specific environment will be examined. Part of the Windows XP Internet Connection Firewall will be used as a case study and analysed according to these criteria, and recommendations will be made.     

考虑群体信任的网络安全态势多维偏好评级方法

现有网络安全态势评级方法难以同时兼顾专家间信任信息、偏好信息以及客观异质信息等多源信息,为此,建立基于群体信任的网络安全态势多维偏好评级模型.在描述网络安全态势多维偏好评级问题的基础上,提出社会网络中信任信息不确定程度度量方法,进一步建立一种考虑单链信任信息不确定性和内部差异性、多链间信任非补偿性和内部差异性的不完整信任网络构造模型,据此确定专家权重;定义基于级别特征值的客观排序、专家偏好的群体一致性程度和群体非一致性程度,进一步建立包含专家信任信息、偏好信息和评级信息等在内的网络安全态势评级多维偏好分段变权综合优化模型,获得基于二元语义的网络安全态势等级和等级区分度.所提出方法为构建和检验网络安全态势评级提供理论依据,有助于研发先进的网络安全态势评级系统,提高网络安全防护能力.     

Why structure and genre matter for users of digital information: A longitudinal experiment with readers of a web-based newspaper

In an effort to understand the impact of designing for digital genres on users’ mental representations of structure, a two-phase study was conducted. In phase 1, six expert news readers and a panel of HCI experts were solicited for input regarding genre-conforming and genre-violating web news page design, navigation, and story categorization. In phase 2, a longitudinal experiment with a group of 25 novice web news readers who were exposed to one of the two designs over 5 sessions is reported. During these sessions a variety of user data were captured, including: comprehension (recall, recognition), usability (time on task, accuracy, user satisfaction), and navigation (path length, category node hits).The between-group difference of web site design was significant for comprehension, usability, and navigation with the users of the genre-conforming design demonstrating better performance. The within-group difference of time was significant across these three measures as well, with performance improving over time. No interaction effect was found between web site design and time on comprehension or usability. However, a surprising interaction effect was found on navigation; specifically the breadth of navigation (i.e. the number of nodes visited for two classes of tasks) increased over time more dramatically for the genre-violating group than for the genre-conforming group. By examining the changes in these data over time and between the two designs, evidence for the development of users’ mental representations of structure was captured.     

Unfolding Edges: Adding Context to Edges in Multivariate Graph Visualization

Existing work on visualizing multivariate graphs is primarily concerned with representing the attributes of nodes. Even though edges are the constitutive elements of networks, there have been only few attempts to visualize attributes of edges. In this work, we focus on the critical importance of edge attributes for interpreting network visualizations and building trust in the underlying data. We propose ‘unfolding of edges’ as an interactive approach to integrate multivariate edge attributes dynamically into existing node-link diagrams. Unfolding edges is an in-situ approach that gradually transforms basic links into detailed representations of the associated edge attributes. This approach extends focus+context, semantic zoom, and animated transitions for network visualizations to accommodate edge details on-demand without cluttering the overall graph layout. We explore the design space for the unfolding of edges, which covers aspects of making space for the unfolding, of actually representing the edge context, and of navigating between edges. To demonstrate the utility of our approach, we present two case studies in the context of historical network analysis and computational social science. For these, web-based prototypes were implemented based on which we conducted interviews with domain experts. The experts' feedback suggests that the proposed unfolding of edges is a useful tool for exploring rich edge information of multivariate graphs.     

Expertise Recognition and Influence in Intercultural Groups: Differences Between Face-to-Face and Computer-Mediated Communication

Expertise recognition is challenging in teamwork, particularly in intercultural collaboration. This research seeks to investigate how cultural differences in communication styles may affect expertise recognition and influence in face-to-face (FtF) versus text-based computer-mediated communication (CMC). Using experimental intercultural groups, we found that in FtF groups East Asian experts had a lower participation rate, and were perceived as less competent, less confident, and less influential than experts from Western culture. No such differences occurred in CMC. The results support mediated moderation effect of perceived confidence on expert influence such that changes in perceptions of Chinese and American experts' confidence accounted for their different levels of influence in CMC versus FtF. No such effect was found with participation rate.     

A pattern approach to interaction design

To create successful interactive systems, user interface designers need to cooperate with developers and application domain experts in an interdisciplinary team. These groups, however, usually lack a common terminology to exchange ideas, opinions and values. This paper presents an approach that uses pattern languages to capture this knowledge in software development, human-computer interaction (HCI) and the application domain. A formal, domain-independent definition of design patterns allows for computer support without sacrificing readability, and pattern use is integrated into the usability engineering life cycle. As an example, experience from building an award-winning interactive music exhibit was turned into a pattern language, which was then used to inform follow-up projects and support HCI education.An earlier version of this paper appeared in theProceedings of the DIS 2000 International Conference on Designing Interactive Systems (16–19 August 2000, New York) and appears by permission of the ACM Press.     

A consensus‐ and harmony‐based feedback mechanism for multiple attribute group decision making with correlated intuitionistic fuzzy sets

In this study, an interactive consensus model is proposed for correlated multiple attribute group decision making (MAGDM) problems with intuitionistic triangular fuzzy numbers (ITFNs). The harmony degree (HD) is investigated to determine the degree of maintaining experts' original information while the consensus level is defined as the proximity degree (PD) between an expert and other experts on three levels: evaluation elements of alternatives, alternatives, and decision matrices. Combining HD and PD, a three‐dimensional feedback mechanism is proposed to identify discordant experts, alternatives, and corresponding preference values that contribute less to consensus, and provides advice to reach a higher consensus level. Additionally, visual representation of experts' consensus position within the group is provided. Furthermore, a graphical simulation of future consensus and harmony status, if the recommended values were to be implemented, is also provided. Therefore, our proposed feedback mechanism guarantees that it increases the consensus level of the set of experts while maintaining, as much as possible, experts' original information. Then, the PD‐induced intuitionistic triangular fuzzy correlated averaging (PD‐IITFCA) operator is investigated to aggregate the interactive individual opinions between experts. Finally, the intuitionistic triangular fuzzy correlated averaging (ITFCA) operator is developed to aggregate the evaluation elements of alternatives under correlative attributes. Based on the score and accurate functions of ITFNs, an order relation is proposed to obtain the final solution of alternatives.     

Visualization of Eye Tracking Data: A Taxonomy and Survey

This survey provides an introduction into eye tracking visualization with an overview of existing techniques. Eye tracking is important for evaluating user behaviour. Analysing eye tracking data is typically done quantitatively, applying statistical methods. However, in recent years, researchers have been increasingly using qualitative and exploratory analysis methods based on visualization techniques. For this state‐of‐the‐art report, we investigated about 110 research papers presenting visualization techniques for eye tracking data. We classified these visualization techniques and identified two main categories: point‐based methods and methods based on areas of interest. Additionally, we conducted an expert review asking leading eye tracking experts how they apply visualization techniques in their analysis of eye tracking data. Based on the experts' feedback, we identified challenges that have to be tackled in the future so that visualizations will become even more widely applied in eye tracking research.     

Mental imagery and software visualization in high-performance software development teams

This paper considers the relationship between mental imagery and software visualization in professional, high-performance software development. It presents overviews of four empirical studies of professional software developers in high-performing teams: (1) expert programmers’ mental imagery, (2) how experts externalize their mental imagery as part of teamwork, (3) experts’ use of commercially available visualization software, and (4) what tools experts build themselves, how they use the tools they build for themselves, and why they build tools for themselves. Through this series of studies, the paper provides insight into a relationship between how experts reason about and imagine solutions, and their use of and requirements for external representations and software visualization. In particular, it provides insight into how experts use visualization in reasoning about software design, and how their requirements for the support of design tasks differ from those for the support of other software development tasks. The paper draws on theory from other disciplines to explicate issues in this area, and it discusses implications for future work in this field.     

HCI ‘Intraface Model’ for System Design

We outline an alternative model of the interface in HCI, the ‘intraface’, in response to design issues arising from navigational and learning problems in hypertext domains. Ours is a model of general application to computer systems. It is composed of four key elements, identifiable within a dynamic interconnected context. These are the user; his/her interests; the tools employed and the ‘ensemble’ of representations brought to bear. In this paper we sketch the present shortcomings of HCI design before outlining the background for the model which draws upon two themes in contemporary psychology, conversational analysis and ‘affordance’ realist theories in perception. This framework allows for the development of principles of cooperation, user engagement and learning in HCI environments.     

MotionGlyphs: Visual Abstraction of Spatio-Temporal Networks in Collective Animal Behavior

Domain experts for collective animal behavior analyze relationships between single animal movers and groups of animals over time and space to detect emergent group properties. A common way to interpret this type of data is to visualize it as a spatio-temporal network. Collective behavior data sets are often large, and may hence result in dense and highly connected node-link diagrams, resulting in issues of node-overlap and edge clutter. In this design study, in an iterative design process, we developed glyphs as a design for seamlessly encoding relationships and movement characteristics of a single mover or clusters of movers. Based on these glyph designs, we developed a visual exploration prototype, MotionGlyphs, that supports domain experts in interactively filtering, clustering, and animating spatio-temporal networks for collective animal behavior analysis. By means of an expert evaluation, we show how MotionGlyphs supports important tasks and analysis goals of our domain experts, and we give evidence of the usefulness for analyzing spatio-temporal networks of collective animal behavior.     

Software Process Improvement Motivators: An Analysis using Multidimensional Scaling

In this paper we present an analysis of software practitioners' motivations for software process improvement (SPI). Our findings are based on an empirical study of SPI in 13 software companies where we conducted focus groups with nearly 200 software practitioners. Our aim is to better understand how companies can maximise practitioner support for SPI. This insight should help SPI managers establish more effective SPI implementation strategies. In this paper we introduce the use of multidimensional scaling (MDS) in SPI research. MDS is a social science data analysis technique designed to generate a rich visual understanding of human issues. By using MDS we found evidence to suggest distinct clusters of punitive and rewarding SPI motivators. Furthermore our analysis also suggests that different clusters of motivations exist for different staff groups.     

Assessing determinants of desirable ES impact on end-user jobs

To increase the likelihood of experts systems' success it is useful to identify the more important determinants to focus managerial attention and resources. Seven major determinants of expert system success, here defined as desirable impact of the system on users' jobs, have been identified from the literature. DuPont's collection of expert systems (ES) provided the sample of 114 applications used in this study. The results corroborate much of what has been proposed in the literature, except for user characteristics which have been found to have no significant relationship to the measure of success. Based on the results, some recommendations are made to expert system development managers, including: (1) besides the recommendations already proposed in the literature, managers should deliberately seek to deal with important, large, labour intensive and complex problems which are important to the organization; (2) the selection of a development shell with the characteristics described in this study, and which matches the problem at hand is an important determinant of success; and (3) even though the primary source of knowledge is one or more domain experts, user involvement in the development process remains an important factor for ES to have a desirable impact on the latter's jobs.