Personalised automated assessments

Consider an evaluator, or an assessor, who needs to assess a large amount of information. For instance, think of a tutor in a massive open online course with thousands of enrolled students, a senior program committee member in a large peer review process who needs to decide what are the final marks of reviewed papers, or a user in an e-commerce scenario where the user needs to build up its opinion about products evaluated by others. When assessing a large number of objects, sometimes it is simply unfeasible to evaluate them all and often one may need to rely on the opinions of others. In this paper we provide a model that uses peer assessments to generate expected assessments and tune them for a particular assessor. Furthermore, we are able to provide a measure of the uncertainty of our computed assessments and a ranking of the objects that should be assessed next in order to decrease the overall uncertainty of the calculated assessments.This work is supported by the CollectiveMind project (funded by the Spanish Ministry of Economy and Competitiveness, under grant number TEC2013-49430-EXP) and the PRAISE project (funded by the European Commission, under grant number 318770).Peer reviewe

Intelligent and adaptive tutoring for active learning and training environments

Active learning facilitated through interactive and adaptive learning environments differs substantially from traditional instructor-oriented, classroom-based teaching. We present a Web-based e-learning environment that integrates knowledge learning and skills training. How these tools are used most effectively is still an open question. We propose knowledge-level interaction and adaptive feedback and guidance as central features. We discuss these features and evaluate the effectiveness of this Web-based environment, focusing on different aspects of learning behaviour and tool usage. Motivation, acceptance of the approach, learning organisation and actual tool usage are aspects of behaviour that require different evaluation techniques to be used

Game of Stones:feasibility randomised controlled trial of how to engage men with obesity in text message and incentive interventions for weight loss

Objectives To examine the acceptability and feasibility of narrative text messages with or without financial incentives to support weight loss for men. Design Individually randomised three-arm feasibility trial with 12 months’ follow-up. Setting Two sites in Scotland with high levels of disadvantage according to Scottish Index for Multiple Deprivation (SIMD). Participants Men with obesity (n=105) recruited through community outreach and general practitioner registers. Interventions Participants randomised to: (A) narrative text messages plus financial incentive for 12 months (short message service (SMS)+I), (B) narrative text messages for 12 months (SMS only), or (C) waiting list control. Outcomes Acceptability and feasibility of recruitment, retention, intervention components and trial procedures assessed by analysing quantitative and qualitative data at 3, 6 and 12 months. Results 105 men were recruited, 60% from more disadvantaged areas (SIMD quintiles 1 or 2). Retention at 12 months was 74%. Fewer SMS+I participants (64%) completed 12-month assessments compared with SMS only (79%) and control (83%). Narrative texts were acceptable to many men, but some reported negative reactions. No evidence emerged that level of disadvantage was related to acceptability of narrative texts. Eleven SMS+I participants (31%) successfully met or partially met weight loss targets. The cost of the incentive per participant was £81.94 (95% CI £34.59 to £129.30). Incentives were acceptable, but improving health was reported as the key motivator for weight loss. All groups lost weight (SMS+I: −2.51 kg (SD=4.94); SMS only: −1.29 kg (SD=5.03); control: −0.86 kg (SD=5.64) at 12 months). Conclusions This three-arm weight management feasibility trial recruited and retained men from across the socioeconomic spectrum, with the majority from areas of disadvantage, was broadly acceptable to most participants and feasible to deliver

Data-driven personalisation and the law - a primer: collective interests engaged by personalisation in markets, politics and law

Interdisciplinary Workshop on â��Data-Driven Personalisation in Markets, Politics and Law' on 28 June 2019Southampton Law School will be hosting an interdisciplinary workshop on the topic of â��Data-Driven Personalisation in Markets, Politics and Law' on Friday 28 June 2019, which will explore the pervasive and growing phenomenon of â��personalisationâ�� â�� from behavioural advertising in commerce and micro-targeting in politics, to personalised pricing and contracting and predictive policing and recruitment. This is a huge area which touches upon many legal disciplines as well as social science concerns and, of course, computer science and mathematics. Within law, it goes well beyond data protection law, raising questions for criminal law, consumer protection, competition and IP law, tort law, administrative law, human rights and anti-discrimination law, law and economics as well as legal and constitutional theory. Weâ��ve written a position paper, https://eprints.soton.ac.uk/428082/1/Data_Driven_Personalisation_and_the_Law_A_Primer.pdf which is designed to give focus and structure to a workshop that we expect will be strongly interdisciplinary, creative, thought-provoking and entertaining. We like to hear your thoughts! Call for papers! Should you be interested in disagreeing, elaborating, confirming, contradicting, dismissing or just reflecting on anything in the paper and present those ideas at the workshop, send us an abstract by Friday 5 April 2019 (Ms Clare Brady [email protected] ). We aim to publish an edited popular law/social science book with the most compelling contributions after the workshop.Prof Uta Kohl, Prof James Davey, Dr Jacob Eisler<br/

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