The research teaching nexus in the computing disciplines: a comparative survey

Many institutions make claims in strategy documents and official publications that students will receive an education which is research-led, research-informed, or guided by the scholarship of teaching and learning. Academics who teach regularly experience at first-hand the sometimes conflicting demands of research, teaching and supporting learning. Curricula guidelines are unlikely to help in developing any sophisticated understanding of ways in which research and teaching can be symbiotically applied, since such guidelines most typically deal with the content rather than the educational process experienced by our undergraduates. For these reasons an academic’s understanding of the research teaching nexus is more likely to be informed by their own workaday experience of designing and delivering educational experiences than from an analysis of the students’ perspective. If academics in the computing disciplines are to effectively deliver on their institutional missions to be scholarly, research-led or research-informed in their educational approaches, a clearer understanding of the possible meanings and implications of these terms in the context of the typical computing curricula would be of assistance. This paper presents and analyses the results of a survey conducted at two Universities which sought to identify how far their undergraduate curriculum was informed by research. This data is presented alongside qualitative data gathered from academics which explores their attitudes towards, and understanding of, the various terms commonly used to describe a research-informed approach to education in the computing disciplines

Designing for frustration and disputes in the family car

This article appears with the express permission of the publisher, IGI Global.Families spend an increasing amount of time in the car carrying out a number of activities including driving to work, caring for children and co-ordinating drop-offs and pickups. While families travelling in cars may face stress from difficult road conditions, they are also likely to be frustrated by coordinating a number of activities and resolving disputes within the confined space of car. A rising number of in-car infotainment and driver-assistance systems aim to help reduce the stress from outside the vehicle and improve the experience of driving but may fail to address sources of stress from within the car. From ethnographic studies of family car journeys, we examine the work of parents in managing multiple stresses while driving, along with the challenges of distractions from media use in the car. Keeping these family extracts as a focus for analysis, we draw out some design considerations that help build on the observations from our empirical work.Microsoft Research and the Dorothy Hodgkin Awar

The ethics of forgetting in an age of pervasive computing

In this paper, we examine the potential of pervasive computing to create widespread sousveillance, that will complement surveillance, through the development of lifelogs; socio-spatial archives that document every action, every event, every conversation, and every material expression of an individual’s life. Examining lifelog projects and artistic critiques of sousveillance we detail the projected mechanics of life-logging and explore their potential implications. We suggest, given that lifelogs have the potential to convert exterior generated oligopticons to an interior panopticon, that an ethics of forgetting needs to be developed and built into the development of life-logging technologies. Rather than seeing forgetting as a weakness or a fallibility we argue that it is an emancipatory process that will free pervasive computing from burdensome and pernicious disciplinary effects

Towards memory supporting personal information management tools

In this article we discuss re-retrieving personal information objects and relate the task to recovering from lapse(s) in memory. We propose that fundamentally it is lapses in memory that impede users from successfully re-finding the information they need. Our hypothesis is that by learning more about memory lapses in non-computing contexts and how people cope and recover from these lapses, we can better inform the design of PIM tools and improve the user's ability to re-access and re-use objects. We describe a diary study that investigates the everyday memory problems of 25 people from a wide range of backgrounds. Based on the findings, we present a series of principles that we hypothesize will improve the design of personal information management tools. This hypothesis is validated by an evaluation of a tool for managing personal photographs, which was designed with respect to our findings. The evaluation suggests that users' performance when re-finding objects can be improved by building personal information management tools to support characteristics of human memory

Using motivation derived from computer gaming in the context of computer based instruction

This paper was originally presented at the IEEE Technically Sponsored SAI Computing Conference 2016, London, 13-15 July 2016. Abstract— this paper explores how to exploit game based motivation as a way to promote engagement in computer-based instruction, and in particular in online learning interaction. The paper explores the human psychology of gaming and how this can be applied to learning, the computer mechanics of media presentation, affordances and possibilities, and the emerging interaction of playing games and how this itself can provide a pedagogical scaffolding to learning. In doing so the paper focuses on four aspects of Game Based Motivation and how it may be used; (i) the game player’s perception; (ii) the game designers’ model of how to motivate; (iii) team aspects and social interaction as a motivating factor; (iv) psychological models of motivation. This includes the increasing social nature of computer interaction. The paper concludes with a manifesto for exploiting game based motivation in learning

Connected Learning Journeys in Music Production Education

The field of music production education is a challenging one, exploring multiple creative, technical and entrepreneurial disciplines, including music composition, performance electronics, acoustics, musicology, project management and psychology. As a result, students take multiple ‘learning journeys’ on their pathway towards becoming autonomous learners. This paper uniquely evaluates the journey of climbing Bloom’s cognitive domain in the field of music production and gives specific examples that validate teaching music production in higher education through multiple, connected ascents of the framework. Owing to the practical nature of music production, Kolb’s Experiential Learning Model is also considered as a recurring function that is necessary for climbing Bloom’s domain, in order to ensure that learners are equipped for employability and entrepreneurship on graduation. The authors’ own experiences of higher education course delivery, design and development are also reflected upon with reference to Music Production pathways at both the University of Westminster (London, UK) and York St John University (York, UK)

Towards a Physiological Computing Infrastructure for Researching Students’ Flow in Remote Learning – Preliminary Results from a Field Study

With the advent of physiological computing systems, new avenues are emerging for the field of learning analytics related to the potential integration of physiological data. To this end, we developed a physiological computing infrastructure to collect physiological data, surveys, and browsing behavior data to capture students’ learning journey in remote learning. Specifically, our solution is based on the Raspberry Pi minicomputer and Polar H10 chest belt. In this work-in-progress paper, we present preliminary results and experiences we collected from a field study with medical students using our developed infrastructure. Our results do not only provide a new direction for more effectively capturing different types of data in remote learning by addressing the underlying challenges of remote setups, but also serve as a foundation for future work on developing a less obtrusive, (near) real-time measurement method based on the classification of cognitive-affective states such as flow or other learning-relevant constructs with the captured data using supervised machine learning