Towards a competency model for adaptive assessment to support lifelong learning

Adaptive assessment provides efficient and personalised routes to establishing the proficiencies of learners. We can envisage a future in which learners are able to maintain and expose their competency profile to multiple services, throughout their life, which will use the competency information in the model to personalise assessment. Current competency standards tend to over simplify the representation of competency and the knowledge domain. This paper presents a competency model for evaluating learned capability by considering achieved competencies to support adaptive assessment for lifelong learning. This model provides a multidimensional view of competencies and provides for interoperability between systems as the learner progresses through life. The proposed competency model is being developed and implemented in the JISC-funded Placement Learning and Assessment Toolkit (mPLAT) project at the University of Southampton. This project which takes a Service-Oriented approach will contribute to the JISC community by adding mobile assessment tools to the E-framework

Investigation into Mobile Learning Framework in Cloud Computing Platform

Abstract—Cloud computing infrastructure is increasingly used for distributed applications. Mobile learning applications deployed in the cloud are a new research direction. The applications require specific development approaches for effective and reliable communication. This paper proposes an interdisciplinary approach for design and development of mobile applications in the cloud. The approach includes front service toolkit and backend service toolkit. The front service toolkit packages data and sends it to a backend deployed in a cloud computing platform. The backend service toolkit manages rules and workflow, and then transmits required results to the front service toolkit. To further show feasibility of the approach, the paper introduces a case study and shows its performance

A SMASHing approach for developing staff and student digital capabilities within a community of practice

SMASH is a student-led partnership which considers how social media could be used to enhance learning and teaching. Mentored by their tutor, members of the team identified three key areas where social media may be utilised: within learning activities, as a means of organising learning and as a way of showcasing learning. The three strands of this framework have provided a focus to develop a range of resources and the foundation for a digital toolkit. This case study reflects upon not just the outputs developed thus far, but also on the experience, the learning gained and the sense of belonging and identify as a result of being part of this community of practice

Promoting the concept of competency maps and interprofessional assessments linked to e-portfolios to enhance the student learning experience in preparation for work based learning, employability and life long learning.

Assessment and Learning in Practice Settings (ALPS) is a collaborative Centre for Excellence in Teaching and Learning (CETL) comprising five Higher Education Institutions (HEI) with proven reputations for excellence in learning and teaching in Health and Social Care (H&SC): the University of Bradford, the University of Huddersfield, the University of Leeds (lead site); Leeds Metropolitan University, and York St John University. There are 16 professions across the partnership from Audiology to Social Work, and a wide range of partners including NHS Yorkshire and the Humber and commercial partners who are working towards a framework of interprofessional assessment of common competences in the H&SC professions. The focus of this paper is the development of the common competency maps for communication, teamwork, and ethical practice along with a set of standardised tools to assess these across the sixteen professional groups. The aim of the ALPS CETL is to ensure that students graduating from courses in H&SC are fully equipped to perform confidently and competently at the start of their professional careers. Fundamental to the care of service users within modern Health and Social Care are key skills commonly utilised by the range of professionals involved in ALPS. Key skills and learning outcomes vary across the 16 pre-registration H&SC courses but central to the practice of all of the professional groups represented by ALPS is a high level of professional competence in communication, teamwork and ethical practice. In order to make explicit this pretext it was decided that mapping these common skills would enable students to navigate their way through the professional competencies allowing them to gain confidence and competence in practice settings. ALPS worked with a commercial partner, MyKnowledgeMap Ltd. (MKM), to facilitate this process which resulted in interactive and creative competency maps from which multiprofessional assessment tools were derived for students to validate their skills in their practice placements. ALPS has developed a shared services platform that enables these common assessment tools to be delivered onto mobile devices used by the students in their practice placements. Central to the ALPS process was the development of an e-portfolio tool to which the student could publish their completed tools and any relevent supporting documents and gain feedback from their tutor back at their University, further perpetuating the learning process and enabling the tutor to evaluate the students progress. This paper discusses how these processes championed by ALPS can be transferred and shared across professions and describes the challenges, benefits and future potential of this approach aimed at enhancing the students ability to learn and produce effective assessments in practice settings

Improving Medicaid Managed Care for Youth With Serious Behavioral Health Needs: A Quality Improvement Toolkit

Profiles successful initiatives by Medicaid managed care organizations in a collaboration to implement systems of care emphasizing early identification, coordination and management, and various services and supports in the least restrictive settings

Environmental Sensing by Wearable Device for Indoor Activity and Location Estimation

We present results from a set of experiments in this pilot study to investigate the causal influence of user activity on various environmental parameters monitored by occupant carried multi-purpose sensors. Hypotheses with respect to each type of measurements are verified, including temperature, humidity, and light level collected during eight typical activities: sitting in lab / cubicle, indoor walking / running, resting after physical activity, climbing stairs, taking elevators, and outdoor walking. Our main contribution is the development of features for activity and location recognition based on environmental measurements, which exploit location- and activity-specific characteristics and capture the trends resulted from the underlying physiological process. The features are statistically shown to have good separability and are also information-rich. Fusing environmental sensing together with acceleration is shown to achieve classification accuracy as high as 99.13%. For building applications, this study motivates a sensor fusion paradigm for learning individualized activity, location, and environmental preferences for energy management and user comfort.Comment: submitted to the 40th Annual Conference of the IEEE Industrial Electronics Society (IECON

Wearable and mobile devices

Information and Communication Technologies, known as ICT, have undergone dramatic changes in the last 25 years. The 1980s was the decade of the Personal Computer (PC), which brought computing into the home and, in an educational setting, into the classroom. The 1990s gave us the World Wide Web (the Web), building on the infrastructure of the Internet, which has revolutionized the availability and delivery of information. In the midst of this information revolution, we are now confronted with a third wave of novel technologies (i.e., mobile and wearable computing), where computing devices already are becoming small enough so that we can carry them around at all times, and, in addition, they have the ability to interact with devices embedded in the environment. The development of wearable technology is perhaps a logical product of the convergence between the miniaturization of microchips (nanotechnology) and an increasing interest in pervasive computing, where mobility is the main objective. The miniaturization of computers is largely due to the decreasing size of semiconductors and switches; molecular manufacturing will allow for “not only molecular-scale switches but also nanoscale motors, pumps, pipes, machinery that could mimic skin” (Page, 2003, p. 2). This shift in the size of computers has obvious implications for the human-computer interaction introducing the next generation of interfaces. Neil Gershenfeld, the director of the Media Lab’s Physics and Media Group, argues, “The world is becoming the interface. Computers as distinguishable devices will disappear as the objects themselves become the means we use to interact with both the physical and the virtual worlds” (Page, 2003, p. 3). Ultimately, this will lead to a move away from desktop user interfaces and toward mobile interfaces and pervasive computing

Location-based and contextual mobile learning. A STELLAR Small-Scale Study

This study starts from several inputs that the partners have collected from previous and current running research projects and a workshop organised at the STELLAR Alpine Rendevous 2010. In the study, several steps have been taken, firstly a literature review and analysis of existing systems; secondly, mobile learning experts have been involved in a concept mapping study to identify the main challenges that can be solved via mobile learning; and thirdly, an identification of educational patterns based on these examples has been done. Out of this study the partners aim to develop an educational framework for contextual learning as a unifying approach in the field. Therefore one of our central research questions is: how can we investigate, theorise, model and support contextual learning