Adaption of Courses and Learning Environment to the User Context in dotLRN

The explosive growth of Internet during the last years has been reflected in the ever-increasing amount of the diversity and heterogeneity of user preferences, types and features of devices and access networks. Usually the heterogeneity in the context of the users which request Web contents is not taken into account by the servers that deliver them implying that these contents will not always suit their needs. In the particular case of e-learning platforms this issue is especially critical due to the fact that it puts at stake the knowledge acquired by their users. In the following paper we present a system that aims to provide the dotLRN e-learning platform with the capability to adapt to its users context. By integrating dotLRN with a multi-agent hypermedia system, online courses being undertaken by students as well as their learning environment are adapted in real time

Informed recommender: basing recommendations on consumer product reviews

Recommender systems attempt to predict items in which a user might be interested, given some information about the user's and items' profiles. Most existing recommender systems use content-based or collaborative filtering methods or hybrid methods that combine both techniques (see the sidebar for more details). We created Informed Recommender to address the problem of using consumer opinion about products, expressed online in free-form text, to generate product recommendations. Informed recommender uses prioritized consumer product reviews to make recommendations. Using text-mining techniques, it maps each piece of each review comment automatically into an ontology

Embedding Emotional Context in Recommender Systems

Emotions are crucial for user's decision making in recommendation processes. We first introduce ambient recommender systems, which arise from the analysis of new trends on the exploitation of the emotional context in the next generation of recommender systems. We then explain some results of these new trends in real-world applications through the smart prediction assistant (SPA) platform in an intelligent learning guide with more than three million users. While most approaches to recommending have focused on algorithm performance. SPA makes recommendations to users on the basis of emotional information acquired in an incremental way. This article provides a cross-disciplinary perspective to achieve this goal in such recommender systems through a SPA platform. The methodology applied in SPA is the result of a bunch of technology transfer projects for large real-world rccommender systems

Modelling the Human Values Scale from Consumers Transactional Data Bases

The main objective of this paper aims at developing a methodology that takes into account the human factor extracted from the data base used by the recommender systems, and which allow to resolve the specific problems of prediction and recommendation. In this work, we propose to extract the user's human values scale from the data base of the users, to improve their suitability in open environments, such as the recommender systems. For this purpose, the methodology is applied with the data of the user after interacting with the system. The methodology is exemplified with a case study

Curriculum sequencing for an e-learning system based on learning styles

This work shows the use of adaptation techniques involved in an e-learning system that considers students' learning styles and students' knowledge states. The mentioned e-learning system is built on a multiagent framework designed to examine opportunities to improve the teaching and to motivate the students to learn what they want in a user-friendly and assisted environment

User Experience (a hidden barrier) in OER

More Open Education Resources (OER) and learning environments are being created and starting to mature and there are a number of barriers to learning and creator participation. One often overlooked barrier that has been given less attention, especially within OERs, is user experience (UX). UX is the way a person feels about using a product, system or service. We are creatures with emotional needs and, in the rush to get great content open and available sometimes the usability, the wow factor and good design principles get left by the wayside. I will demonstrate ways to think about UX for your OER and learning environments and why this is an important factor in helping engage learners with our educational materials. ‘The real payoff comes when we can make that remarkability last. When we can make people continually feel our work is worthy of discussion. When—for weeks, months, maybe even years— the people who engage with our work continue to sing its praises to everybody they meet’– (Jared Spool in Walter, A. Designing for Emotion). Walter, A. (2011) Designing for Emotion, A Book Apart. http://www.abookapart.com/products/designing-for-emotion

Quantifying carbon-cycle feedbacks

Perturbations to the carbon cycle could constitute large feedbacks on future changes in atmospheric CO2 concentration and climate. This paper demonstrates how carbon cycle feedback can be expressed in formally similar ways to climate feedback, and thus compares their magnitudes. The carbon cycle gives rise to two climate feedback terms: the concentration–carbon feedback, resulting from the uptake of carbon by land and ocean as a biogeochemical response to the atmospheric CO2 concentration, and the climate–carbon feedback, resulting from the effect of climate change on carbon fluxes. In the earth system models of the Coupled Climate–Carbon Cycle Model Intercomparison Project (C4MIP), climate–carbon feedback on warming is positive and of a similar size to the cloud feedback. The concentration–carbon feedback is negative; it has generally received less attention in the literature, but in magnitude it is 4 times larger than the climate–carbon feedback and more uncertain. The concentration–carbon feedback is the dominant uncertainty in the allowable CO2 emissions that are consistent with a given CO2 concentration scenario. In modeling the climate response to a scenario of CO2 emissions, the net carbon cycle feedback is of comparable size and uncertainty to the noncarbon–climate response. To quantify simulated carbon cycle feedbacks satisfactorily, a radiatively coupled experiment is needed, in addition to the fully coupled and biogeochemically coupled experiments, which are referred to as coupled and uncoupled in C4MIP. The concentration–carbon and climate–carbon feedbacks do not combine linearly, and the concentration–carbon feedback is dependent on scenario and time.

Negative correlations between control performance and verbalizable knowledge: indicators for implicit learning in process control tasks?

Negative correlations between task performance in dynamic control tasks and verbalizable knowledge, as assessed by a post-task questionnaire, have been interpreted as dissociations that indicate two antagonistic modes of learning, one being “explicit”, the other “implicit”. This paper views the control tasks as finite-state automata and offers an alternative interpretation of these negative correlations. It is argued that “good controllers” observe fewer different state transitions and, consequently, can answer fewer post-task questions about system transitions than can “bad controllers”. Two experiments demonstrate the validity of the argument by showing the predicted negative relationship between control performance and the number of explored state transitions, and the predicted positive relationship between the number of explored state transitions and questionnaire scores. However, the experiments also elucidate important boundary conditions for the critical effects. We discuss the implications of these findings, and of other problems arising from the process control paradigm, for conclusions about implicit versus explicit learning processes.

Involving users in expert system development

The ultimate criterion of success for interactive expert systems is that they will be used, and used to effect, by individuals other than the system developers. A key ingredient of success in most systems is involving users in the specification and development of systems as they are being built. However, until recently, system designers have paid little attention to ascertaining user needs and to developing systems with corresponding functionality and appropriate interfaces to match those requirements. Although the situation is beginning to change, many developers do not know how to go about involving users, or else tackle the problem in an inadequate way. This paper discusses the need for user involvement and considers why many developers are still not involving users in an optimal way. It looks at the different ways in which users can be involved in the development process and describes how to select appropriate techniques and methods for studying users. Finally, it discusses some of the problems inherent in involving users in expert system development, and recommends an approach which incorporates both ethnographic analysis and formal user testing.

Modeling the user knowledge by belief networks

This paper describes the user modeling component of EPIAIM, a consultation system for data analysis in epidemiology. The component is aimed at representing knowledge of concepts in the domain, so that their explanations can be adapted to user needs. The first part of the paper describes two studies aimed at analysing user requirements. The first one is a questionnaire study which examines the respondents' familiarity with concepts. The second one is an analysis of concept descriptions in textbooks and from expert epidemiologists, which examines how discourse strategies are tailored to the level of experience of the expected audience. The second part of the paper describes how the results of these studies have been used to design the user modeling component of EPIAIM. This module works in a two-step approach. In the first step, a few trigger questions allow the activation of a stereotype that includes a "body" and an "inference component". The body is the representation of the body of knowledge that a class of users is expected to know, along with the probability that the knowledge is known. In the inference component, the learning process of concepts is represented as a belief network. Hence, in the second step the belief network is used to refine the initial default information in the stereotype's body. This is done by asking a few questions on those concepts where it is uncertain whether or not they are known to the user, and propagating this new evidence to revise the whole situation. The system has been implemented on a workstation under UNIX. An example of functioning is presented, and advantages and limitations of the approach are discussed.

User interface standards for expert systems: are they appropriate?

In recent years there has been a growing debate over whether or not standards should be produced for user system interfaces. Those in favor of standardization argue that standards in this area will result in more usable systems, while those against argue that standardization is neither practical nor desirable. The present paper reviews both sides of this debate in relation to expert systems. It argues that in many areas guidelines are more appropriate than standards for user interface design.

PRISM and ENES: a European approach to Earth system modelling

Europe's widely distributed climate modelling expertise, now organized in the European Network for Earth System Modelling (ENES), is both a strength and a challenge. Recognizing this, the European Union's Program for Integrated Earth System Modelling (PRISM) infrastructure project aims at designing a flexible and friendly user environment to assemble, run and post-process Earth System models. PRISM was started in December 2001 with a duration of three years. This paper presents the major stages of PRISM, including: (1) the definition and promotion of scientific and technical standards to increase component modularity; (2) the development of an end-to-end software environment (graphical user interface, coupling and I/O system, diagnostics, visualization) to launch, monitor and analyse complex Earth system models built around state-of-art community component models (atmosphere, ocean, atmospheric chemistry, ocean bio-chemistry, sea-ice, land-surface); and (3) testing and quality standards to ensure high-performance computing performance on a variety of platforms. PRISM is emerging as a core strategic software infrastructure for building the European research area in Earth system sciences. Copyright (c) 2005 John Wiley & Sons, Ltd.

Case-based analysis in user requirements modelling for knowledge construction

Context: Learning can be regarded as knowledge construction in which prior knowledge and experience serve as basis for the learners to expand their knowledge base. Such a process of knowledge construction has to take place continuously in order to enhance the learners’ competence in a competitive working environment. As the information consumers, the individual users demand personalised information provision which meets their own specific purposes, goals, and expectations. Objectives: The current methods in requirements engineering are capable of modelling the common user’s behaviour in the domain of knowledge construction. The users’ requirements can be represented as a case in the defined structure which can be reasoned to enable the requirements analysis. Such analysis needs to be enhanced so that personalised information provision can be tackled and modelled. However, there is a lack of suitable modelling methods to achieve this end. This paper presents a new ontological method for capturing individual user’s requirements and transforming the requirements onto personalised information provision specifications. Hence the right information can be provided to the right user for the right purpose. Method: An experiment was conducted based on the qualitative method. A medium size of group of users participated to validate the method and its techniques, i.e. articulates, maps, configures, and learning content. The results were used as the feedback for the improvement. Result: The research work has produced an ontology model with a set of techniques which support the functions for profiling user’s requirements, reasoning requirements patterns, generating workflow from norms, and formulating information provision specifications. Conclusion: The current requirements engineering approaches provide the methodical capability for developing solutions. Our research outcome, i.e. the ontology model with the techniques, can further enhance the RE approaches for modelling the individual user’s needs and discovering the user’s requirements.

An assessment of the benefits and limitations of the shamba agroforestry system in Kenya and of management and policy requirements for its successful and sustainable reintroduction

The shamba system involves farmers tending tree saplings on state-owned forest land in return for being permitted to intercrop perennial food crops until canopy closure. At one time the system was used throughout all state-owned forest lands in Kenya, accounting for a large proportion of some 160,000 ha. The system should theoretically be mutually beneficial to both local people and the government. However the system has had a chequered past in Kenya due to widespread malpractice and associated environmental degradation. It was last banned in 2003 but in early 2008 field trials were initiated for its reintroduction. This study aimed to: assess the benefits and limitations of the shamba system in Kenya; assess the main influences on the extent to which the limitations and benefits are realised and; consider the management and policy requirements for the system's successful and sustainable operation. Information was obtained from 133 questionnaires using mainly open ended questions and six participatory workshops carried out in forest-adjacent communities on the western slopes of Mount Kenya in Nyeri district. In addition interviews were conducted with key informants from communities and organisations. There was strong desire amongst local people for the system's reintroduction given that it had provided significant food, income and employment. Local perceptions of the failings of the system included firstly mismanagement by government or forest authorities and secondly abuse of the system by shamba farmers and outsiders. Improvements local people considered necessary for the shamba system to work included more accountability and transparency in administration and better rules with respect to plot allocation and stewardship. Ninety-seven percent of respondents said they would like to be more involved in management of the forest and 80% that they were willing to pay for the use of a plot. The study concludes that the structural framework laid down by the 2005 Forests Act, which includes provision for the reimplementation of the shamba system under the new plantation establishment and livelihood improvement scheme (PELIS) [It should be noted that whilst the shamba system was re-branded in 2008 under the acronym PELIS, for the sake of simplicity the authors continue to refer to the 'shamba system' and 'shamba farmers' throughout this paper.], is weakened because insufficient power is likely to be devolved to local people, casting them merely as 'forest users' and the shamba system as a 'forest user right'. In so doing the system's potential to both facilitate and embody the participation of local people in forest management is limited and the long-term sustainability of the new system is questionable. Suggested instruments to address this include some degree of sharing of profits from forest timber, performance related guarantees for farmers to gain a new plot and use of joint committees consisting of local people and the forest authorities for long term management of forests.

PGR forum: serving the crop wild relative user community

The Euro-Mediterranean region is an important centre for the diversity of crop wild relatives. Crops, such as oats (Avena sativa), sugar beet (Beta vulgaris), apple (Malus domestica), annual meadow grass (Festuca pratensis), white clover (Trifolium repens), arnica (Arnica montana), asparagus (Asparagus officinalis), lettuce (Lactuca sativa), and sage (Salvia officinalis) etc., all have wild relatives in the region. The European Community funded project, PGR Forum (www.pgrforum.org) is building an online information system to provide access to crop wild relative data to a broad user community; including plant breeders, protected area managers, policy-makers, conservationists, taxonomists and the wider public. The system will include data on uses, geographical distribution, biology, population and habitat information, threats (including IUCN Red List assessments) and conservation actions. This information is vital for the continued sustainable utilisation and conservation of crop wild relatives. Two major databases have been utilised as the backbone to a Euro-Mediterranean crop wild relative catalogue, which forms the core of the information system: Euro+Med PlantBase (www.euromed.org.uk) and Mansfeld’s World Database of Agricultural and Horticultural Crops (http://mansfeld.ipk-gatersleben.de). By matching the genera found within the two databases, a preliminary list of crop wild relatives has been produced. Around 20,000 of the 30,000+ species listed in Euro+Med PlantBase can be considered crop wild relatives, i.e. those species found within the same genus as a crop. The list is currently being refined by implementing a priority ranking system based on the degree of relatedness of taxa to the associated crop.