Automated user modeling for personalized digital libraries

Digital libraries (DL) have become one of the most typical ways of accessing any kind of digitalized information. Due to this key role, users welcome any improvements on the services they receive from digital libraries. One trend used to improve digital services is through personalization. Up to now, the most common approach for personalization in digital libraries has been user-driven. Nevertheless, the design of efficient personalized services has to be done, at least in part, in an automatic way. In this context, machine learning techniques automate the process of constructing user models. This paper proposes a new approach to construct digital libraries that satisfy user’s necessity for information: Adaptive Digital Libraries, libraries that automatically learn user preferences and goals and personalize their interaction using this information

A self-regulated learning approach : a mobile context-aware and adaptive learning schedule (mCALS) tool

Self-regulated students are able to create and maximize opportunities they have for studying or learning. We combine this learning approach with our Mobile Context-aware and Adaptive Learning Schedule (mCALS) tool which will create and enhance opportunities for students to study or learn in different locations. The learning schedule is used for two purposes, a) to help students organize their work and facilitate time management, and b) for capturing the users’ activities which can be retrieved and translated as learning contexts later by our tool. These contexts are then used as a basis for selecting appropriate learning materials for the students. Using a learning schedule to capture and retrieve contexts is a novel approach in the context-awareness mobile learning field. In this paper, we present the conceptual model and preliminary architecture of our mCALS tool, as well as our research questions and methodology for evaluating it. The learning materials we intend to use for our tool will be Java for novice programmers. We decided that this would be appropriate because large amounts of time and motivation are necessary to learn an object-oriented programming language such as Java, and we are currently seeking ways to facilitate this for novice programmers

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

Local agency, adaptation and the shadow system: The institutional architecture of social learning in rural areas of the UK and India

Rural communities across the world face at times a range of environmental, social and economic pressures that threaten their viability in their current form. The ability of local actors to exercise agency in response to potential and emerging threats is of key interest in understanding their capacity to adapt. This paper argues that top-down narratives which focus on canonical organisations and formal institutions are at best a partial account of rural adaptation. More attention needs to be paid to the shadow system, the web of informal and often hidden relationships that permeate public and private life. In the organisational and institutional literature, shadow systems have been discounted as either too complex to be tractable or an inevitable source of corruption and nepotism. Two case studies are presented to establish that neither claim is inexorably true: (i) the adaptation of dairy farmers to market and climate change in Carmarthenshire, South Wales and (ii) NGO mediation of community/state interaction in Tamilnadu, South India. In conclusion, some theoretical and methodological themes are highlighted for further research. These hold the potential to enable a better understanding of the shadow system, and its potential and pitfalls as a site of local agency in rural adaptation. Acnowledgements: This paper draws on learning from two research projects: (i) 'Rapid climate change in the UK: towards an institutional theory of adaptation', funded by the UK Economic and Social Science Research Council's Environment and Human Behaviour Programme, and (ii) 'Thaan Vuzha Nilam Tharisu: The land without a farmer becomes barren', carried out by SPEECH, a Tamil NGO, as part of a larger International Institute for Environment and Development research programme – 'Policies that Work for Sustainable Agriculture and Regenerating Rural Economies.� The authors gratefully acknowledge the financial and institutional assistance that made this research possible

PACMAS: A Personalized, Adaptive, and Cooperative MultiAgent System Architecture

In this paper, a generic architecture, designed to support the implementation of applications aimed at managing information among different and heterogeneous sources, is presented. Information is filtered and organized according to personal interests explicitly stated by the user. User pro- files are improved and refined throughout time by suitable adaptation techniques. The overall architecture has been called PACMAS, being a support for implementing Personalized, Adaptive, and Cooperative MultiAgent Systems. PACMAS agents are autonomous and flexible, and can be made personal, adaptive and cooperative, depending on the given application. The peculiarities of the architecture are highlighted by illustrating three relevant case studies focused on giving a support to undergraduate and graduate students, on predicting protein secondary structure, and on classifying newspaper articles, respectively

Anticipatory Mobile Computing: A Survey of the State of the Art and Research Challenges

Today's mobile phones are far from mere communication devices they were ten years ago. Equipped with sophisticated sensors and advanced computing hardware, phones can be used to infer users' location, activity, social setting and more. As devices become increasingly intelligent, their capabilities evolve beyond inferring context to predicting it, and then reasoning and acting upon the predicted context. This article provides an overview of the current state of the art in mobile sensing and context prediction paving the way for full-fledged anticipatory mobile computing. We present a survey of phenomena that mobile phones can infer and predict, and offer a description of machine learning techniques used for such predictions. We then discuss proactive decision making and decision delivery via the user-device feedback loop. Finally, we discuss the challenges and opportunities of anticipatory mobile computing.Comment: 29 pages, 5 figure