Engaging sport students in assessment and formative feedback

Sport as a discipline in higher education is grappling with the challenge of providing authentic and relevant assessment that engages students in their learning. The centrality of assessment to the student experience is now well accepted within the research literature (Brown and Knight, 1994; Rust, 2002). In particular, formative assessment, or assessment that creates feedback to support future teaching and learning experiences, can be a powerful tool for enhancing learning (see Black and Wiliam, 1998). Given that feedback is most effective if it is considered or reflected upon, one of the key challenges is to actively engage sport students in formative assessment processes. This guide offers advice in designing and facilitating sport students’ involvement in assessment and enhancing their engagement with the feedback they receive. The aim is to support sport programme teams by taking a pragmatic approach, combining a clear academic rationale based on assessment for learning principles with case study examples of successful formative assessment exercises emphasising innovative approaches to giving feedback. The guide consists of three key sections focused on: 1) Providing staff in HLST with background knowledge of formative assessment and formative feedback and how it relates to their subject. 2) Providing case study examples of how to effectively engage sport students with assessment feedback so that it feeds-forward to aid learning. 3) Providing a resource of references and sources of support for tutors wishing to further their learning in this area

Challenges for information technology supporting educational assessment

This article examines the scope for IT-enabled assessments to serve simultaneously both learners and the enterprise of education. The article proposes ways of combining frameworks that come from two different perspectives: 1) a conceptual approach to assessment design for computerized assessment based on evidence-centred design (ECD) and 2) a framework for formative assessment based on empirical research in classrooms. The article argues that combining the ECD and formative assessment frameworks and building on the opportunities provided by computerized assessments as well as harnessing teachers' and students' experience and developing their validation processes could enable assessments to address simultaneously assessment FOR learning and assessment OF learning. Strategies would include harnessing the benefits of embedded continuous unobtrusive measuring of performance while learners are engaged in interesting computerized tasks designed to support their learning. Learners need to be involved in discussing and negotiating their learning so we conceptualize these embedded unobtrusive processes as ‘quiet assessment’, whose volume can be turned up by learners whenever they wish, to give them access to meaningful representations of evidence and arguments about their achievements. These strategies could enable a wider range of measures to contribute to judgements of students' achievements, thus supporting their learning in 21st-century contexts

Assessment for learning: using minor assessment to promote major learning

The authors have previously reported the effectiveness of using self and peer assessment to improve learning outcomes in groupwork by providing opportunities to practise, assess and provide feedback on studentsâ attribute development. Combining this research and that reported in the literature regarding learning-oriented assessment we theorised that self and peer assessment would be an ideal tool to develop and efficiently facilitate activities specifically designed to be student centred and promote learning. In this paper we report the effectiveness of a self and peer assessment activity specifically designed to promote collaborative peer learning, require students to take responsibility for their learning and improve their judgement, while at the same time only imposing a small assessment load on academics

Psychometrics in Practice at RCEC

A broad range of topics is dealt with in this volume: from combining the psychometric generalizability and item response theories to the ideas for an integrated formative use of data-driven decision making, assessment for learning and diagnostic testing. A number of chapters pay attention to computerized (adaptive) and classification testing. Other chapters treat the quality of testing in a general sense, but for topics like maintaining standards or the testing of writing ability, the quality of testing is dealt with more specifically.\ud All authors are connected to RCEC as researchers. They present one of their current research topics and provide some insight into the focus of RCEC. The selection of the topics and the editing intends that the book should be of special interest to educational researchers, psychometricians and practitioners in educational assessment

'Its not like anything Joe and I have experienced before': Family workshops at Tate Modern

Supporting Children's Learning in the Early Years is aimed at early years practitioners who are developing their knowledge and understanding of professional practice through studying at undergraduate level. The book encourages readers to consider their professional development as reflective practitioners, building on and supporting the government agenda to provide quality provision for young children and their families. Combining theory and practice, and bringing together current research and thinking in a broad range of areas, the book covers: Learning environments: young children as learners, assessment of learning, well being and children's rights, diversity and inclusion. Learning and development: children's development including social and emotional development, literacy and mathematical development, the potential of ICT, fostering creativity, musical development and knowledge and understanding of the world. Reflective practice: the learning environment, safeguarding and wellbeing, the reflective practitioner. Throughout, the contributions in this book encourage the reader to consider the diverse range of experiences which young children bring to early years and early primary settings and suggest ways in which they can be supported. The book will also be a valuable and unique resource for training providers of a range of courses at further and higher education level that prepare people to work with, and lead in, early years settings in the UK

A Generic Conceptual Model for Risk Analysis in a Multi-agent Based Collaborative Design Environment

Organised by: Cranfield UniversityThis paper presents a generic conceptual model of risk evaluation in order to manage the risk through related constraints and variables under a multi-agent collaborative design environment. Initially, a hierarchy constraint network is developed to mapping constraints and variables. Then, an effective approximation technique named Risk Assessment Matrix is adopted to evaluate risk level and rank priority after probability quantification and consequence validation. Additionally, an Intelligent Data based Reasoning Methodology is expanded to deal with risk mitigation by combining inductive learning methods and reasoning consistency algorithms with feasible solution strategies. Finally, two empirical studies were conducted to validate the effectiveness and feasibility of the conceptual model.Mori Seiki – The Machine Tool Compan

Riemannian tangent space mapping and elastic net regularization for cost-effective EEG markers of brain atrophy in Alzheimer's disease

The diagnosis of Alzheimer's disease (AD) in routine clinical practice is most commonly based on subjective clinical interpretations. Quantitative electroencephalography (QEEG) measures have been shown to reflect neurodegenerative processes in AD and might qualify as affordable and thereby widely available markers to facilitate the objectivization of AD assessment. Here, we present a novel framework combining Riemannian tangent space mapping and elastic net regression for the development of brain atrophy markers. While most AD QEEG studies are based on small sample sizes and psychological test scores as outcome measures, here we train and test our models using data of one of the largest prospective EEG AD trials ever conducted, including MRI biomarkers of brain atrophy.Comment: Presented at NIPS 2017 Workshop on Machine Learning for Healt

Automatic Labeling of Special Diagnostic Mammography Views from Images and DICOM Headers.

Applying state-of-the-art machine learning techniques to medical images requires a thorough selection and normalization of input data. One of such steps in digital mammography screening for breast cancer is the labeling and removal of special diagnostic views, in which diagnostic tools or magnification are applied to assist in assessment of suspicious initial findings. As a common task in medical informatics is prediction of disease and its stage, these special diagnostic views, which are only enriched among the cohort of diseased cases, will bias machine learning disease predictions. In order to automate this process, here, we develop a machine learning pipeline that utilizes both DICOM headers and images to predict such views in an automatic manner, allowing for their removal and the generation of unbiased datasets. We achieve AUC of 99.72% in predicting special mammogram views when combining both types of models. Finally, we apply these models to clean up a dataset of about 772,000 images with expected sensitivity of 99.0%. The pipeline presented in this paper can be applied to other datasets to obtain high-quality image sets suitable to train algorithms for disease detection

Facilitating independence in personal activities of daily living after a severe traumatic brain injury

This is the author's accepted manuscript. The final published article is available from the link below.Aims: This study examined the effectiveness of two components of a treatment programme typically used by occupational therapists (OTs) in personal activities of daily living (PADL) rehabilitation. Methods: A multiple baseline probe design across PADL tasks was used, one which is particularly suited to the examination of the effects of complex interventions on skill performance. The subjects were two male adults with severe brain injuries and cognitive impairments who were in the acute stages of recovery. The OT treatment program consisted of a combination of errorless learning and strategy training approaches. The impact of the program was measured by the number of steps completed independently in each of these tasks, the level and type of assistance required, and by administering the UK Functional Independence Measure and the Assessment of Motor and Process Skills. Findings: Errorless learning and strategy training, as used within an OT programme, was demonstrated to be effective in reducing the amount of assistance both participants required to complete the targeted PADL tasks. Further, there was evidence of generalization of training effects among trained and untrained activities. Conclusions: Selecting and combining treatment techniques based on detailed assessment of functional performance is an area of high clinical importance but with limited research; the current study stands as an attempt towards that direction