Despite the prevalence of mental health conditions, stigma, lack of awareness, and limited resources impede access to care, creating a need to improve mental health support. The recent surge in scientific and commercial interest in conversational agents and their potential to improve diagnosis and treatment seems a potentially fruitful area in this respect, particularly for young adults who widely use such systems in other contexts. Yet, there is little research that considers the acceptability of conversational agents in mental health. This study, therefore, presents three research activities that explore whether conversational agents and, in particular, chatbots can be an acceptable solution in mental healthcare for young adults. First, a survey of young adults (in a university setting) provides an understanding of the landscape of mental health in this age group and of their views around mental health technology, including chatbots. Second, a literature review synthesises current evidence relating to the acceptability of mental health conversational agents and points to future research priorities. Third, interviews with counsellors who work with young adults, supported by a chatbot prototype and user-centred design techniques, reveal the perceived benefits and potential roles of mental health chatbots from the perspective of mental health professionals, while suggesting preconditions for the acceptability of the technology. Taken together, these research activities: provide evidence that chatbots are an acceptable solution to offering mental health support for young adults; identify specific challenges relating to both the technology and environment; and argue for the application of user-centred approaches during development of mental health chatbots and more systematic and rigorous evaluations of the resulting solutions.

The effects of gender in human communication and human-computer interaction are well-known, yet little is understood about how it influences performance in the complex, collaborative tasks in computer-mediated settings – referred to as Computer-Supported Collaborative Work (CSCW) – that are increasingly fundamental to the way in which people work. In such tasks, visual feedback about objects and events is particularly valuable because it facilitates joint reference and attention, and enables the monitoring of people's actions and task progress. As such, software to support CSCW frequently provides shared visual workspace. While numerous studies describe and explain the impact of visual feedback in CSCW, research has not considered whether there are differences in how females and males use it, are aided by it, or are affected by its absence. To address these knowledge gaps, this study explores the effect of gender – and its interactions within pairs – in CSCW, with and without visual feedback. An experimental study is reported in which mixed-gender and same-gender pairs communicate to complete a collaborative navigation task, with one of the participants being under the impression that s/he is interacting with a robot (to avoid gender-related social preconceptions). The study analyses performance, perceptions and communication strategies. As predicted, there was a significant benefit associated with visual feedback in terms of language economy and efficiency. However, it was also found that visual feedback may be disruptive to task performance, because it relaxes the users’ precision criteria and inflates their assumptions of shared perspective. While no actual performance difference was found between males and females in the navigation task, females rated their own performance less positively than did males. In terms of communication strategies, males had a strong tendency to introduce novel vocabulary when communication problems occurred, while females exhibited more conservative behaviour. When visual feedback was removed, females adapted their strategies drastically and effectively, increasing the quality and specificity of the verbal interaction, repeating and re-using vocabulary, while the behaviour of males remained consistent. These results are used to produce design recommendations for CSCW systems that will suit users of both genders and enable effective collaboration.

There is strong research evidence showing that people naturally align to each other’s vocabulary, sentence structure, and acoustic features in dialog, yet little is known about how the alignment mechanism operates in the interaction between users and computer systems let alone how it may be exploited to improve the efficiency of the interaction. This article provides an account of lexical alignment in human–computer dialogs, based on empirical data collected in a simulated human–computer interaction scenario. The results indicate that alignment is present, resulting in the gradual reduction and stabilization of the vocabulary-in-use, and that it is also reciprocal. Further, the results suggest that when system and user errors occur, the development of alignment is temporarily disrupted and users tend to introduce novel words to the dialog. The results also indicate that alignment in human–computer interaction may have a strong strategic component and is used as a resource to compensate for less optimal (visually impoverished) interaction conditions. Moreover, lower alignment is associated with less successful interaction, as measured by user perceptions. The article distills the results of the study into design recommendations for human–computer dialog systems and uses them to outline a model of dialog management that supports and exploits alignment through mechanisms for in-use adaptation of the system’s grammar and lexicon.

More than 2 billion people are using the Internet at present, assisted by the mediating activities of software agents that deal with the diversity and complexity of information. There are, however, ethical issues due to the monitoring-and-surveillance, data-mining, and autonomous nature of software agents. Considering the context, this study aims to comprehend stakeholders’ perspectives on the social network service environment to identify the main considerations for the design of software agents in social network services in the near future. Twenty-one stakeholders, belonging to 3 key stakeholder groups, were recruited using a purposive sampling strategy for unstandardized semistructured e-mail interviews. The interview data were analyzed using a qualitative content analysis method. It was possible to identify 3 main considerations for the design of software agents in social network services, which were classified into the following categories: comprehensive understanding of users’ perception of privacy, user type recognition algorithms for software agent development, and existing software agents enhancement.

Teaching programming to beginners is a complex task. In this article, the effects of three factors—choice of programming language, problem-solving training, and the use of formative assessment—on learning to program were investigated. The study adopted an iterative methodological approach carried out across 4 consecutive years. To evaluate the effects of each factor (implemented as a single change in each iteration) on students’ learning performance, the study used quantitative, objective metrics. The findings revealed that using a syntactically simple language (Python) instead of a more complex one (Java) facilitated students’ learning of programming concepts. Moreover, teaching problem solving before programming yielded significant improvements in student performance. These two factors were found to have variable effects on the acquisition of basic programming concepts. Finally, it was observed that effective formative feedback in the context of introductory programming depends on multiple parameters. The article discusses the implications of these findings, identifies avenues for further research, and argues for the importance of studies in computer science education anchored on sound research methodologies to produce generalizable results.

This paper presents a novel approach to social data analysis, exploring the use of microblogging to manage interaction between humans and robots, and presenting and evaluating an architecture that extends the use of social networks to connect humans and devices. The approach uses natural language processing – in the form of simple grammar-based techniques – to extract features of interest from textual data retrieved from a microblogging platform in real-time and generate appropriate executable code for the robot. The simple rule-based solution exploits some of the ‘natural’ constraints imposed by microblogging platforms to manage the potential complexity of the interactions and create bi-directional communication. In order to evaluate the developed system, an analysis of real-time, user-generated social media data is presented. The analysis demonstrates the feasibility of producing programmes from the social media data which lead to executable actions by a front-end application – an approach of immediate relevance to web-based systems, like question–answering engines, personal digital assistants, and smart home/office devices.

The debate concerning how many participants represents a sufficient number for interaction testing is well-established and long-running, with prominent contributions arguing that five users provide a good benchmark when seeking to discover interaction problems. We argue that adoption of five users in this context is often done with little understanding of the basis for, or implications of, the decision. We present an analysis of relevant research to clarify the meaning of the five-user assumption and to examine the way in which the original research that suggested it has been applied. This includes its blind adoption and application in some studies, and complaints about its inadequacies in others. We argue that the five-user assumption is often misunderstood, not only in the field of Human-Computer Interaction, but also in fields such as medical device design, or in business and information applications. The analysis that we present allows us to define a systematic approach for monitoring the sample discovery likelihood, in formative and summative evaluations, and for gathering information in order to make critical decisions during the interaction testing, while respecting the aim of the evaluation and allotted budget. This approach -- which we call the Grounded Procedure -- is introduced and its value argued.

Many studies have identified gender differences in communication related to spatial navigation in real and virtual worlds. Most of this research has focused on single-party communication (monologs), such as the way in which individuals either give or follow route instructions. However, very little work has been reported on spatial navigation dialogs and whether there are gender differences in the way that they are conducted. This article will address the lack of research evidence by exploring the dialogs between partners of the same and of different gender in a simulated Human-Robot Interaction study. In the experiments discussed in this article, pairs of participants communicated remotely; in each pair, one participant (the instructor) was under the impression that s/he was giving route instructions to a robot (the follower), avoiding any perception of gendered communication. To ensure the naturalness of the interaction, the followers were given no guidelines on what to say, however, each had to control a robot based on the user's instructions. While many monologe-based studies suggest male superiority in a multitude of spatial activities and domains, this study of dialogs highlights a more complex pattern of results. As anticipated, gender influences task performance and communication. However, the findings suggest that it is the interaction—the combination of gender and role (i.e., instructor or follower)—that has the most significant impact. In particular, pairs of female users/instructors and male “robots”/followers are associated with the fastest and most accurate completion of the navigation tasks. Moreover, dialoge-based analysis illustrates how pairs of male users/instructors and female “robots”/followers achieved successful communication through “alignment” of spatial descriptions. In particular, males seem to adapt the content of their instructions when interacting with female “robots”/followers and employ more landmark references compared to female users/instructors or when addressing males (in male-male pairings). This study describes the differences in how males and females interact with the system, and proposes that any female “disadvantage” in spatial communication can disappear through interactive mechanisms. Such insights are important for the design of navigation systems that are equally effective for users of either gender.

The increasing popularity and use of Open Source Software (OSS) has led to significant interest from research communities and enterprise practitioners, notably in the small business sector where this type of software offers particular benefits given the financial and human capital constraints faced. However, there has been little focus on developing valid frameworks that enable critical evaluation and common understanding of factors influencing OSS adoption. This paper seeks to address this shortcoming by presenting a theory-grounded framework for exploring these factors and explaining their influence on OSS adoption, with the context of study being small- to medium-sized Information Technology (IT) businesses in the U.K. The framework has implications for this type of business – and, we will suggest, more widely – as a frame of reference for understanding, and as tool for evaluating benefits and challenges in, OSS adoption. It also offers researchers a structured way of investigating adoption issues and a base from which to develop models of OSS adoption. The study reported in this paper used the Decomposed Theory of Planned Behaviour (DTPB) as a basis for the research propositions, with the aim of: (i) developing a framework of empirical factors that influence OSS adoption; and (ii) appraising it through case study evaluation with 10 U.K. Small- to medium-sized enterprises in the IT sector. The demonstration of the capabilities of the framework suggests that it is able to provide a reliable explanation of the complex and subjective factors that influence attitudes, subjective norms and control over the use of OSS. The paper further argues that the DTPB proved useful in this research area and that it can provide a variety of situation-specific insights related to factors that influence the adoption of OSS.

editorial Free Access Share on Editorial: Data mining for understanding user needs Authors: Sherry Y. Chen Brunel University, UK Brunel University, UKView Profile , Robert D. Macredie Brunel University, UK Brunel University, UKView Profile , Xiaohui Liu Brunel University, UK Brunel University, UKView Profile , Alistair Sutcliffe University of Manchester, UK University of Manchester, UKView Profile Authors Info & Claims ACM Transactions on Computer-Human InteractionVolume 17Issue 1March 2010 Article No.: 1pp 1–6https://doi.org/10.1145/1721831.1721832Published:06 April 2010Publication History 7citation1,123DownloadsMetricsTotal Citations7Total Downloads1,123Last 12 Months15Last 6 weeks1 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my Alerts New Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF

A user's cognitive style impacts the way they organize and process information. This paper considers how cognitive style impacts a user's ability to acquire spatial knowledge from a range of virtual environments. Our results show that holist (field independent) users acquire spatial knowledge faster in low complex large environments, which support learning of relative visual references. Analytic (field dependent) users acquire spatial knowledge faster in complex environments, which obstruct the field of view and therefore support procedural learning. User specific limitations must be considered when defining required exposure time in virtual training environments.

People are increasingly seeking to use the Web to carry out activities that were traditionally conducted through face-to-face communication. From the perspective of this Special Issue, this change in communication channel raises two noteworthy issues. First, Web interfaces are in effect emulating traditional human roles. We see this across a diverse range of e-applications (and typical roles performed) including: e-commerce (e.g., salesperson/financial adviser); e-government (e.g., welfare/tax security officer); e-health (e.g., doctor/counsellor); and e-learning (e.g., trainer/teacher). Second, despite the faceless nature of the interaction and the absence of nonverbal cues, people still respond socially to Web interfaces. This suggests that although Information and Communication Technologies (ICT) such as the Internet offer an alternative channel for communication, people’s general expectations of face-to-face communication may be carried over to online environments. This signals a need for researchers and practitioners to understand the ways in which communication has been conducted traditionally, how and why new media attract users and what these media might offer when face-to-face communication is moved online.

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.

Many of the issues associated with the inefficiency and ineffectiveness of information systems development (ISD) have been attributed to the poor relationship between business and IT colleagues. Relational issues relating to collaboration and communication before, during and after ISD lead to dissatisfaction with information systems and services. To address these relational issues, many organisations have introduced relationship management initiatives (RM). Yet, their effects have been debatable. This paper argues that this is partly because there is no appropriate evaluative framework for RM. In response, this paper proposes a framework, based on social capital theory, for conceptualising the effects of change management interventions in the poor relationship between business and IT colleagues. The research adopts a case study approach to this end. It explores the strengths and limitations of the approach and suggests new directions for its further development. Overall, the research shows that there is a potential merit in using a social capital approach for the evaluation of change management interventions that aim to improve the collaboration between business and IT, during ISD and beyond.

There has been tremendous growth in Web-based instruction over the past few years. Because the user group of Web-based instruction includes learners from heterogeneous backgrounds, individual differences become an important issue in the development of Web-based instructional programs. Among a variety of individual differences, cognitive style is a particularly important characteristic. This study aims to determine the relationships between learners' cognitive styles and their perceptions and attitudes toward the features of a Web-based instructional program. The results indicate that cognitive styles influence students' reactions to nonlinear interaction, independent learning, and navigation tools and the difficulties and problems that they encounter. The findings are applied to develop a learning model that can support the design of Web-based instructional programs.

Abstract In this article we demonstrate the use of an integrative approach to visualizing and tracking the development of scientific paradigms. This approach is designed to reveal the long‐term process of competing scientific paradigms. We assume that a cluster of highly cited and cocited scientific publications in a cocitation network represents the core of a predominant scientific paradigm. The growth of a paradigm is depicted and animated through the rise of citation rates and the movement of its core cluster towards the center of the cocitation network. We study two cases of competing scientific paradigms in the real world: (1) the causes of mass extinctions, and (2) the connections between mad cow disease and a new variant of a brain disease in humans—vCJD. Various theoretical and practical issues concerning this approach are discussed.

Abstract There has been an increased growth in the use of hypermedia to deliver learning and teaching material. However, much remains to be learned about how different learners perceive such systems. Therefore, it is essential to build robust learning models to illustrate how hypermedia features are experienced by different learners. Research into individual differences suggests cognitive styles have a significant effect on student learning in hypermedia systems. In particular, Witkin's Field Dependence has been extensively examined in previous studies. This article reviews the published findings from empirical studies of hypermedia learning. Specifically, the review classifies the research into five themes: nonlinear learning, learner control, navigation in hyperspace, matching and mismatching, and learning effectiveness. A learning model, developed from an analysis of findings of the previous studies, is presented. Finally, implications for the design of hypermedia learning systems are discussed.

This paper introduces the motivation for and concept of the "new usability" and positions it against existing approaches to usability. It is argued that the contexts of emerging products and systems mean that traditional approaches to usability engineering and evaluation are likely to prove inappropriate to the needs of "digital consumers." The paper briefly reviews the contributions to this special issue in terms of their relation to the idea of the "new usability" and their individual approaches to dealing with contemporary usability issues. This helps provide a background to the "new usability" research agenda, and the paper ends by posing what are argued to be the central challenges facing the area and those which lie at the heart of the proposed research agenda.

The development of ‘intelligent’ or ‘adaptive’ user interfaces has been a strong research theme in Human–Computer Interaction for many years, with the terms often used interchangeably. In this article we will argue that seeing these terms as interchangeable can be misleading and can have implications for the expectations of systems both from the designer’s and user’s perspectives. We will suggest that the emphasis at the interface should be on adaptation, leaving intelligent behaviour to the user. The article argues that realistic expectations of available interaction information must be maintained when specifying the behaviour of an adaptive interface, such as the one containing agents. This article illustrates the process of the design and implementation of a set of software agents which act as Web Assistants, aiding the user in browsing the world wide web (WWW): issues in specifying the agents’ functionality and adaptation characteristics; issues in designing the adaptation and inference rules required for each agent and implementing and integrating them within a user interface. The process raises both architectural and implementation issues which lead to conclusions drawn at the end of the article, concerning adaptivity versus intelligence and considering specifically the quality of interaction information available and the need to maintain realistic expectations on the part of the designers of adaptive systems.

The practical significance of identifying and accommodating individual differences has been established across a number of fields of research. There is a renewed interest in individual differences due to the advances in virtual environments, especially through far-reaching technologies such as information visualization and 3D graphical user interfaces on the World Wide Web. The effects of individual differences on the use of these new technologies are yet to be found out. More fundamentally, theories and methods developed for the earlier generations of information systems are subject to a close examination of their applicability, efficiency, and effectiveness. In this article, we present a brief historical overview of research in individual differences in the context of virtual environments. In particular, we highlight the notion of structure in the perception of individual users of an information system and the role of individuals' abilities to recognize and use such structures to perform various information-intensive tasks. Striking the balance between individuals' abilities and the demanding task for detecting, understanding, and utilizing such structures is an emerging theme across the five articles in this special issue. We outline the approaches and the major findings of these articles with reference to this central theme.