The Effects of Computer Mediated Communication on Computer-Based Training

Student performance using computer-based training (CBT) may be related to the degree of interaction that occurs between students and the instructor, or between students and each other. This is significant in that the individualized nature of CBT (and perhaps Web-based training) is contrary to the social interaction needs of students. Using relevant pedagogical and social communication theories as a basis, this study employed empirical research methods on undergraduate participants to achieve the following objectives: to explore the use of computer mediated communication (CMC) as a surrogate for face-to-face interaction with CBT students, and to provide research-based recommendations for human resource development (HRD) managers charged with deployment of these and related technologies. The research results showed that undergraduate CBT participants who were sent personalized email once per week performed significantly better than participants who were sent no email

Programming pedagogy in the age of accessible artificial intelligence

In recent years, new teaching opportunities have emerged as artificial intelligence has gained increasing attention in computational thinking education. However, to design effective pedagogy based on the present research landscape, the technology solution must be tailored to a learning environment through a collaboration between human-computer interaction and human-artificial intelligence interaction research. The thesis aims to enhance programming experiences and increase accessibility to programming resources for students in remote schools and post-secondary graduate settings using human-computer interaction and human-artificial intelligence interaction techniques. It addresses the limited computational thinking education resources and the potential of artificial intelligence-assisted coding in a self-learning method suitable for remote Northwestern First Nation communities in Canada. This thesis proposes methods to cater to students’ learning styles in two different learning environments using human-computer interaction for kindergarten to grade 12 students and human-artificial intelligence interaction for university students. Incorporating these research principles can help novice programmers overcome cognitive overload and poor user experience and achieve an optimal user experience. The thesis begins with bibliometric analysis and provides a holistic perspective of computational thinking and artificial intelligence trending strategies. It then presents an empirical study on human-computer interaction, investigating computational thinking in remote kindergarten to grade 12 schools with blended learning environments. It also presents another empirical study on human-artificial intelligence interaction to experiment with a self-learning style for artificial intelligence coding assistants for university students using massive open online courses. [...

A novel facial expression recognition method using bi-dimensional EMD based edge detection

Facial expressions provide an important channel of nonverbal communication. Facial recognition techniques detect people’s emotions using their facial expressions and have found applications in technical fields such as Human-Computer-Interaction (HCI) and security monitoring. Technical applications generally require fast processing and decision making. Therefore, it is imperative to develop innovative recognition methods that can detect facial expressions effectively and efficiently. Traditionally, human facial expressions are recognized using standard images. Existing methods of recognition require subjective expertise and high computational costs. This thesis proposes a novel method for facial expression recognition using image edge detection based on Bi-dimensional Empirical Mode Decomposition (BEMD). In this research, a BEMD based edge detection algorithm was developed, a facial expression measurement metric was created, and an intensive database testing was conducted. The success rates of recognition suggest that the proposed method could be a potential alternative to traditional methods for human facial expression recognition with substantially lower computational costs. Furthermore, a possible blind-detection technique was proposed as a result of this research. Initial detection results suggest great potential of the proposed method for blind-detection that may lead to even more efficient techniques for facial expression recognition

THE RANGE AND ROLE OF THEORY IN INFORMATION SYSTEMS DESIGN RESEARCH: FROM CONCEPTS TO CONSTRUCTION

This paper reports results from a field study of cross-disciplinary design researchers in information systems, software engineering, human-computer interaction, and computer-supported cooperative work. The purpose of the study was to explore how these different disciplines conceptualize and conduct design-as-research. The focus in this paper is on how theories are used in a design research project to motivate and inform the particulars of designed artifacts and design methods. Our objective was to better understand how elements of a theory are translated into design action, and how theoretical propositions are translated and then realized in designed artifacts. The results reveal a broad diversity in the processes through which theories are translated into working artifacts. The paper contributes to our understanding of design research in information systems by providing empirical support for existing constructs and frameworks, identifying some new approaches to translating theoretical concepts into research designs, and suggesting ways in which action and artifact-oriented research can more effectively contribute to a cumulative and progressive science of design

Using crowdsourced mathematics to understand mathematical practice

Records of online collaborative mathematical activity provide us with a novel, rich, searchable, accessible and sizeable source of data for empirical investigations into mathematical practice. In this paper we discuss how the resources of crowdsourced mathematics can be used to help formulate and answer questions about mathematical practice, and what their limitations might be. We describe quantitative approaches to studying crowdsourced mathematics, reviewing work from cognitive history (comparing individual and collaborative proofs); social psychology (on the prospects for a measure of collective intelligence); human-computer interaction (on the factors that led to the success of one such project); network analysis (on the differences between collaborations on open research problems and known-but-hard problems); and argumentation theory (on modelling the argument structures of online collaborations). We also give an overview of qualitative approaches, reviewing work from empirical philosophy (on explanation in crowdsourced mathematics); sociology of scientific knowledge (on conventions and conversations in online mathematics); and ethnography (on contrasting conceptions of collaboration). We suggest how these diverse methods can be applied to crowdsourced mathematics and when each might be appropriate

Social epistemology and online knowledge exchange

This document summarises the submitted research which has investigated online knowledge exchange and related it to the philosophical field of social epistemology. The broad aims have been: firstly to investigate what social epistemology theory can offer in the way of guidance and evaluative frameworks for the design of knowledge systems; and secondly, to determine what the empirical study of knowledge exchange platforms can tell us about epistemology as emerging from online practice. The submitted work consists of six papers that are a mixture of review/position papers and reports of empirical investigation. These have been published in information science journals and conference proceedings. However, following the established tradition of information science, the work is positioned as being cross disciplinary in ambition.After introducing the submitted papers and the inspiration for the research, the main theoretical positions of the research are outlined and justified. These were a naturalised social epistemological position, inspired by Alvin Goldman, but widened to a situated and systems-oriented view. The naturalised view of epistemology allows for consideration of evidence from psychology, and here some key theories in social and cognitive psychology are outlined. Finally, as the subject is human-computer-human interaction, the sociotechnical setting is established. Further, the main platforms of study in the empirical work — social question answering systems — are introduced and described.The main methodology and research approaches followed are presented next. A mixed methods philosophy was deemed suitable for this area of research and — alongside the review work — the broad web science method of combining network and data investigation with qualitative methods is justified. Review work included early collaborations with an information scientist and a philosopher which helped to bring together and clarify epistemological and sociotechnical themes. The discussion section presents some of the main themes and conclusions of the submitted work, including: 1) The identification of knowledge patterns and practices online; 2) Criteria for online knowledge exchange distilled from the social epistemology literature; 3) Some triangulations where theory from philosophy and psychology seemed to corroborate and serve to explain online behaviour; 4) Socio-temporal aspects to online knowledge exchange that are perhaps under developed in philosophy but apparent in practice; 5) Credibility cues and bias, seen as crucial to a rounded study of user interaction with online sources; and finally 6) Interventions suggested by the research which would aim to raise the quality and effectiveness of social media knowledge systems.Finally, conclusions and suggestions for further work are presented. These follow on from the submitted strands of research and present possibilities for how the work may be extended and improved upon. In common with the research, these combine philosophy, modelling, interaction design and qualitative methods. Such a combination is seen as essential to developing an enhanced understanding of how the web serves and could serve as a platform for human knowledge

Eliciting and describing users' models of computer systems

The topic of this thesis is users' models: the representations users may form of the computer system which they are interacting with. It has been proposed that user interfaces which support the construction of appropriate users' models facilitate learning and use of computer systems. Users' models have been a topic of research in human-computer interaction (HCI) since 1984, but to date, no knowledge exists which could be applied by designers of computer systems. The aim of the thesis is to address this problem and contribute to the development of an integrated and applicable body of knowledge on users' models. The thesis commences with an examination of the history and current state of the discipline of human-computer interaction to establish the context and determine the appropriate methods for conducting research on users' models. Since mental representations and mental models originate from the related disciplines of psychology and cognitive science, the review of the literature starts with an outline of the relevant theories, followed by a review of the theoretical and empirical work to date on users' model in HCI. The review concludes that more exploratory empirical work is required to obtain data from which evidence for, and descriptions of, users' models could be derived; however, suitable methods for eliciting and describing users' models have to be devised first. The second part of the thesis describes a series of five observational studies of users interacting with application software. The studies employed different scenarios, ranging from traditional experimental-style scenarios, with users working through a series of tasks, to constructive interaction scenarios, where users interacted with a co-investigator playing the role of a learner or co-learner. All studies were recorded on video, transcribed and analysed. Advantages and drawbacks of the scenarios for eliciting users' models are identified and discussed. The analysis of the tapes and transcripts provides some evidence of users' models; the conclusions of the thesis provide an outline of how theories regarding users' models can be formulated, and tested, using the data collected

Eliciting and describing users' models of computer systems

The topic of this thesis is users' models: the representations users may form of the computer system which they are interacting with. It has been proposed that user interfaces which support the construction of appropriate users' models facilitate learning and use of computer systems. Users' models have been a topic of research in human-computer interaction (HCI) since 1984, but to date, no knowledge exists which could be applied by designers of computer systems. The aim of the thesis is to address this problem and contribute to the development of an integrated and applicable body of knowledge on users' models. The thesis commences with an examination of the history and current state of the discipline of human-computer interaction to establish the context and determine the appropriate methods for conducting research on users' models. Since mental representations and mental models originate from the related disciplines of psychology and cognitive science, the review of the literature starts with an outline of the relevant theories, followed by a review of the theoretical and empirical work to date on users' model in HCI. The review concludes that more exploratory empirical work is required to obtain data from which evidence for, and descriptions of, users' models could be derived; however, suitable methods for eliciting and describing users' models have to be devised first. The second part of the thesis describes a series of five observational studies of users interacting with application software. The studies employed different scenarios, ranging from traditional experimental-style scenarios, with users working through a series of tasks, to constructive interaction scenarios, where users interacted with a co-investigator playing the role of a learner or co-learner. All studies were recorded on video, transcribed and analysed. Advantages and drawbacks of the scenarios for eliciting users' models are identified and discussed. The analysis of the tapes and transcripts provides some evidence of users' models; the conclusions of the thesis provide an outline of how theories regarding users' models can be formulated, and tested, using the data collected

How to Engineer Gamification: The Consensus, the Best Practice and the Grey Areas.

Gamification typically refers to the use of game elements in a business context in order to change users’ behaviors, mainly increasing motivation and engagement, towards a certain task or a strategic objective. Gamification has received a good deal of emphasis in both academia and industry across various disciplines, e.g., psychology and human computer interaction, and application areas, e.g. education and marketing. Despite the increasing interest, we still need a unified and holistic picture of how to engineer gamification including: the meaning of the term; its development process; the stakeholders and disciplines which need to be involved in it; and the concerns and risks an ad-hoc design could raise for both businesses and users. To address this need, this paper reports on a review of the literature on a range of gamification techniques and applications, followed by empirical research which involved collecting expert opinions using qualitative and quantitative methods. Based on the results of this research,we provide a body of knowledge about gamification and highlight good practice principles and areas of gamification that are debatable and require further investigation