Flexible learning in computer science

This paper outlines the concept of Flexible Pedagogy and how it can assist in addressing some of the issues facing STEM disciplines in general, and Computer Science in particular. The paper considers what flexible pedagogy is and how technologies developed by Computer Science can enable flexibility. It then describes some of the issues facing STEM education, with a particular focus on Computer Science education in Higher Education. Finally, it considers how flexible approaches to teaching and learning are particularly pertinent to the issues faced in Computer Science and future opportunities

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

A guidance and evaluation approach for mHealth education applications

© Springer International Publishing AG 2017. A growing number of mobile applications for health education are being utilized to support different stakeholders, from health professionals to software developers to patients and more general users. There is a lack of a critical evaluation framework to ensure the usability and reliability of these mobile health education applications (MHEAs). Such a framework would facilitate the saving of time and effort for the different user groups. This paper describes a framework for evaluating mobile applications for health education, including a guidance tool to help different stakeholders select the one most suitable for them. The framework is intended to meet the needs and requirements of the different user categories, as well as improving the development of MHEAs through software engineering approaches. A description of the evaluation framework is provided, with its efficient hybrid of selected heuristic evaluation (HE) and usability evaluation (UE) factors. Lastly, an account of the quantitative and qualitative results for the framework applied to the Medscape and other mobile apps is given. This proposed framework - an Evaluation Framework for Mobile Health Education Apps - consists of a hybrid of five metrics selected from a larger set during heuristic and usability evaluation, the choice being based on interviews with patients, software developers and health professionals

Flexible virtual environments: Gamifying immersive learning

© Springer International Publishing AG 2017. The availability of Virtual Reality (VR) and Virtual Environment (VE) equipment - with the launch of domestic technologies such as the Oculus Rift, Microsoft Hololens and Sony Playstation VR) - offer new ways to enable interactive immersive experiences [16]. The opportunities these create in learning and training applications are immense: but create new challenges . Meanwhile, current virtual learning environments are typically web or app based technologies, sometimes perceived as having little value added from a user perspective beyond improved User Interfaces to access some content [6]. The challenge is how the human computer interaction features of such VE platforms may be used in education in a way that adds value, especially for computer mediated instruction. This paper will outline some of the issues, and opportunities, as well as some of the open questions about how such technologies can be used effectively in a higher education context, along with a proposed framework for embedding a learning engine within a virtual reality or environment system. Three-dimensional technologies: from work-walls, through CAVES to the latest headsets offer new ways to immerse users in computer generated environments. Immersive learning [1] is increasingly common in training applications, and is beginning to make inroads into formal education. The recent rise in such off-the-shelf technologies means that Augmented Learning becomes a realistic mainstream tool [13]. Much of this use is built in game environments using game engines, where these serious games provide learning effects as an intended consequence of playing

Evaluation of mobile health education applications for health professionals and patients

Paper presented at 8th International conference on e-Health (EH 2016), 1-3 July 2016, Funchal, Madeira, Portugal. ABSTRACT Mobile applications for health education are commonly utilized to support patients and health professionals. A critical evaluation framework is required to ensure the usability and reliability of mobile health education applications in order to facilitate the saving of time and effort for the various user groups; thus, the aim of this paper is to describe a framework for evaluating mobile applications for health education. The intended outcome of this framework is to meet the needs and requirements of the different user categories and to improve the development of mobile health education applications with software engineering approaches, by creating new and more effective techniques to evaluate such software. This paper first highlights the importance of mobile health education apps, then explains the need to establish an evaluation framework for these apps. The paper provides a description of the evaluation framework, along with some specific evaluation metrics: an efficient hybrid of selected heuristic evaluation (HE) and usability evaluation (UE) factors to enable the determination of the usefulness and usability of health education mobile apps. Finally, an explanation of the initial results for the framework was obtained using a Medscape mobile app. The proposed framework - An Evaluation Framework for Mobile Health Education Apps – is a hybrid of five metrics selected from a larger set in heuristic and usability evaluation, filtered based on interviews from patients and health professionals. These five metrics correspond to specific facets of usability identified through a requirements analysis of typical users of mobile health apps. These metrics were decomposed into 21 specific questionnaire questions, which are available on request from first author

Maximising gain for minimal pain: Utilising natural game mechanics

This paper considers the application of natural games mechanics within higher education as a vehicle to encourage student engagement and achievement of desired learning outcomes. It concludes with desiderata of features for a learning environment when used for assessment and a reflection on the gap between current and aspired learning provision. The context considered is higher (tertiary) education, where the aims are both to improve students’ engagement with course content and also to bring about potential changes in the students’ learning behaviour. Whilst traditional approaches to teaching and learning may focus on dealing with large classes, where the onus is frequently on efficiency and on the effectiveness of feedback in improving understanding and future performance, intelligent systems can provide technology to enable alternative methods that can cope with large classes that preserve the cost-benefits. However, such intelligent systems may also offer improved learning outcomes via a personalised learning experience. This paper looks to exploit particular properties which emerge from the game playing process and seek to engage them in a wider educational context. In particular we aim to use game engagement and Flow as natural dynamics that can be exploited in the learning experience

Tetrads of lines spanning PG(7,2)

Our starting point is a very simple one, namely that of a set L_4 of four mutually skew lines in PG(7,2): Under the natural action of the stabilizer group G(L_4) < GL(8,2) the 255 points of PG(7,2) fall into four orbits omega_1, omega_2, omega_3 omega_4; of respective lengths 12, 54, 108, 81: We show that the 135 points in omega_2 \cup omega_4 are the internal points of a hyperbolic quadric H_7 determined by L_4; and that the 81-set omega_4 (which is shown to have a sextic equation) is an orbit of a normal subgroup G_81 isomorphic to (Z_3)^4 of G(L_4): There are 40 subgroups (isomorphic to (Z_3)^3) of G_81; and each such subgroup H < G_81 gives rise to a decomposition of omega_4 into a triplet of 27-sets. We show in particular that the constituents of precisely 8 of these 40 triplets are Segre varieties S_3(2) in PG(7,2): This ties in with the recent finding that each Segre S = S_3(2) in PG(7,2) determines a distinguished Z_3 subgroup of GL(8,2) which generates two sibling copies S'; S" of S.Comment: Some typos correcte

Collaborative hybrid agent provision of learner needs using ontology based semantic technology

© Springer International Publishing AG 2017. This paper describes the use of Intelligent Agents and Ontologies to implement knowledge navigation and learner choice when interacting with complex information locations. The paper is in two parts: the first looks at how Agent Based Semantic Technology can be used to give users a more personalised experience as an individual. The paper then looks to generalise this technology to allow users to work with agents in hybrid group scenarios. In the context of University Learners, the paper outlines how we employ an Ontology of Student Characteristics to personalise information retrieval specifically suited to an individual’s needs. Choice is not a simple “show me your hand and make me a match” but a deliberative artificial intelligence (AI) that uses an ontologically informed agent society to consider the weighted solution paths before choosing the appropriate best. The aim is to enrich the student experience and significantly re-route the student’s journey. The paper uses knowledge-level interoperation of agents to personalise the learning space of students and deliver to them the information and knowledge to suite them best. The aim is to personalise their learning in the presentation/format that is most appropriate for their needs. The paper then generalises this Semantic Technology Framework using shared vocabulary libraries that enable individuals to work in groups with other agents, which might be other people or actually be AIs. The task they undertake is a formal assessment but the interaction mode is one of informal collaboration. Pedagogically this addresses issues of ensuring fairness between students since we can ensure each has the same experience (as provided by the same set of Agents) as each other and an individual mark may be gained. This is achieved by forming a hybrid group of learner and AI Software Agents. Different agent architectures are discussed and a worked example presented. The work here thus aims at fulfilling the student’s needs both in the context of matching their needs but also in allowing them to work in an Agent Based Synthetic Group. This in turn opens us new areas of potential collaborative technology

Tetrads of lines spanning PG(7,2)

Our starting point is a very simple one, namely that of a set L₄ of four mutually skew lines in PG(7,2). Under the natural action of the stabilizer group G(L₄)&lt;GL(8,2) the 255 points of PG(7,2) fall into four orbits ω₁,ω₂,ω₃,ω4, of respective lengths 12,54,108,81. We show that the 135 points ∈ω₂∪ω₄ are the internal points of a hyperbolic quadric H7 determined by L₄, and that the 81-set ω₄ (which is shown to have a sextic equation) is an orbit of a normal subgroup G₈₁≅(Z₃)4 of G(L4). There are 40 subgroups ≅(Z₃)3 of G₈₁, and each such subgroup H&lt;G₈₁ gives rise to a decomposition of ω4 into a triplet {RH,R′H,R′′H} of 27-sets. We show in particular that the constituents of precisely 8 of these 40 triplets are Segre varieties S₃(2) in PG(7,2). This ties in with the recent finding 225-239 --- that each S=S₃(2) in PG(7,2) determines a distinguished Z₃ subgroup of GL(8,2) which generates two sibling copies S′,S′′ of S