On optimal learning schedules and the marginal value of cumulative cultural evolution.

The age-dependent choice between expressing individual learning (IL) or social learning (SL) affects cumulative cultural evolution. A learning schedule in which SL precedes IL is supportive of cumulative culture because the amount of nongenetically encoded adaptive information acquired by previous generations can be absorbed by an individual and augmented. Devoting time and energy to learning, however, reduces the resources available for other life-history components. Learning schedules and life history thus coevolve. Here, we analyze a model where individuals may have up to three distinct life stages: "infants" using IL or oblique SL, "juveniles" implementing IL or horizontal SL, and adults obtaining material resources with learned information. We study the dynamic allocation of IL and SL within life stages and how this coevolves with the length of the learning stages. Although no learning may be evolutionary stable, we find conditions where cumulative cultural evolution can be selected for. In that case, the evolutionary stable learning schedule causes individuals to use oblique SL during infancy and a mixture between IL and horizontal SL when juvenile. We also find that the selected pattern of oblique SL increases the amount of information in the population, but horizontal SL does not do so.

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

Motivation des patients à participer à un essai clinique de phase I en oncologie

Chaque année en Suisse, 15000 personnes meurent du cancer, ce qui en fait la deuxième cause de mortalité [1]. Il est donc nécessaire d'introduire sur le marché de nouveaux traitements plus efficaces. Ces derniers doivent passer par une période d'essais cliniques qui comporte plusieurs phases, dont la phase I. Celle-ci sert principalement à déterminer la dose maximale tolérable d'un médicament, en exposant le patient à des doses croissantes. Déterminer les motivations des patients à participer à la phase I d'un essai clinique, alors que les bénéfices personnels sont relativement faibles [3].

Engaging students in an e-learning experience : how to manage information resources through wikis and web blogs

The purpose of this paper is to describe the collaboration between librarians and scholars, from a virtual university, in order to facilitate collaborative learning on how to manage information resources. The personal information behaviour of e-learning students when managing information resources for academic, professional and daily life purposes was studied from 24 semi-structured face-to-face interviews. The results of the content analysis of the interview' transcriptions, highlighted that in the workplace and daily life contexts, competent information behaviour is always linked to a proactive attitude, that is to say, that participants seek for information without some extrinsic reward or avoiding punishment. In the academic context, it was observed a low level of information literacy and it seems to be related with a prevalent uninvolved attitude.

Train-the-trainer: E-learning zur Förderung einer praxisorientiertem Vermittlung von evidenzbasierter Medizin

Hintergrund: Trotz ihrer Etablierung als essentieller Bestandteil der medizinischen Weiter-/Fortbildung werden europa- wie schweizweit kaum Kurse in evidenzbasierter Medizin (ebm) angeboten, die - integriert im klinischen Alltag - gezielt Fertigkeiten in ebm vermitteln. Noch grössere Defizite finden sich bei ebm- Weiterbildungsmöglichkeiten für klinische Ausbilder (z.B. Oberärzte). Als Weiterführung eines EU-finanzierten, klinisch integrierten E-learning- Programms für Weiterbildungsassistenten (www.ebm-unity.org) entwickelte eine europäische Gruppe von medical educators gezielt für Ausbilder ein e-learning-Curriculum zur Vermittlung von ebm im Rahmen der klinischen Weiterbildung. Methode: Die Entwicklung des Curriculums umfasst folgende Schritte: Beschreibung von Lernzielen, Identifikation von klinisch relevanten Lernumgebungen, Entwicklung von Lerninhalten und exemplarischen didaktischen Strategien, zugeschnitten auf die jeweilige Lernumgebungen, Design von web-basierten Selbst-Lernsequenzen mit Möglichkeiten zur Selbstevaluation, Erstellung eines Handbuchs. Ergebnisse: Lernziele des Tutoren-Lehrgangs sind der Erwerb von Fertigkeiten zur Vermittlung der 5 klassischen ebm-Schritte: PICO- (Patient-Intervention-Comparison-Outcome)-Fragen, Literatursuche, kritische Literaturbewertung, Übertragung der Ergebnisse im eigenen Setting und Implementierung). Die Lehrbeispiele zeigen angehenden ebm-Tutoren, wie sich typische klinische Situationen wie z.B. Stationsvisite, Ambulanzsprechstunde, Journalclub, offizielle Konferenzen, Audit oder das klinische Assessment von Weiterbildungsassistenten gezielt für die Vermittlung von ebm nutzen lassen. Kurze E-Learning-Module mit exemplarischen «real-life»-Video-Clips erlauben flexibles Lernen zugeschnitten auf das knappe Zeitkontingent von Ärzten. Eine Selbst-Evaluation ermöglicht die Überprüfung der gelernten Inhalte. Die Pilotierung des Tutoren-Lehrgangs mit klinisch tätigen Tutoren sowie die Übersetzung des Moduls in weitere Sprachen sind derzeit in Vorbereitung. chlussfolgerung: Der modulare Train-the-Trainer-Kurs zur Vermittlung von ebm im klinischen Alltag schliesst eine wichtige Lücke in der Dissemination von klinischer ebm. Webbasierte Beispiele mit kurzen Sequenzen demonstrieren typische Situationen zur Vermittlung der ebm-Kernfertigkeiten und bieten medical educators wie Oberärzten einen niedrigschwelligen Einstieg in «ebm» am Krankenbett. Langfristiges Ziel ist eine europäische Qualifikation für ebm- Learning und -Teaching in der Fort- und Weiterbildung. Nach Abschluss der Evaluation steht das Curriculum interessierten Personen und Gruppen unter «not-for-profit»-Bedingungen zur Verfügung. Auskünfte erhältlich von rkunz@uhbs.ch. Finanziert durch die Europäische Kommission - Leonardo da Vinci Programme - Transfer of Innovation - Pilot Project for Lifelong Learn- ing 2007 und das Schweizerische Staatssekretariat für Bildung und Forschung.

Implementing statistical learning methods through Bayesian networks (Part 2): bayesian evaluations for results of black toner analyses in forensic document examination

This paper presents and discusses the use of Bayesian procedures - introduced through the use of Bayesian networks in Part I of this series of papers - for 'learning' probabilities from data. The discussion will relate to a set of real data on characteristics of black toners commonly used in printing and copying devices. Particular attention is drawn to the incorporation of the proposed procedures as an integral part in probabilistic inference schemes (notably in the form of Bayesian networks) that are intended to address uncertainties related to particular propositions of interest (e.g., whether or not a sample originates from a particular source). The conceptual tenets of the proposed methodologies are presented along with aspects of their practical implementation using currently available Bayesian network software.

Capitalism in the classroom : the impact of self-enhancement values and normative assessment on student motivation, goals and attitudes towards cheating

Abstract The neo-liberal capitalist ideology has come under heavy fire with anecdotal evidence indicating a link between these same values and unethical behavior. Academic institutions reflect social values and act as socializing agents for the young. Can this explain the high and increasing rates of cheating that currently prevail in education? Our first chapter examines the question of whether self-enhancement values of power and açhievement, the individual level equivalent of neo-liberal capitalist values, predict positive attitudes towards cheating. Furthermore, we explore the mediating role of motivational factors. Results of four studies reveal that self-enhancement value endorsement predicts the adoption of performance-approach goals, a relationship mediated by introjected regulation, namely desire for social approval and that self-enhancement value endorsement also predicts the condoning of cheating, a relationship mediated by performance-approach goal adoption. However, self-transcendence values prescribed by a normatively salient source have the potential to reduce the link between self-enhancement value endorsément and attitudes towards cheating. Normative assessment constitutes a key tool used by academic institutions to socialize young people to accept the competitive, meritocratic nature of a sociéty driven by a neo-liberal capitalist ideology. As such, the manifest function of grades is to motivate students to work hard and to buy into the competing ethos. Does normative assessment fulfill these functions? Our second chapter explores the reward-intrinsic motivation question in the context of grading, arguably a high-stakes reward. In two experiments, the relative capacity of graded high performance as compared to the task autonomy experienced in an ungraded task to predict post-task intrinsic motivation is assessed. Results show that whilst the graded task performance predicts post-task appreciation, it fails to predict ongoing motivation. However, perceived autonomy experienced in non-graded condition, predicts both post-task appreciation and ongoing motivation. Our third chapter asks whether normative assessment inspires the spirit of competition in students. Results of three experimental studies reveal that expectation of a grade for a task, compared to no grade, induces greater adoption of performance-avoidance, but not performance-approach, goals. Experiment 3 provides an explanatory mechanism for this, showing that reduced autonomous motivation experienced in previous graded tasks mediates the relationship between grading and adoption of performance avoidance goals in a subsequent task. The above results, when combined, provide evidence as to the deleterious effects of self enhancement values and the associated practice of normative assessment in school on student motivation, goals and ethics. We conclude by using value and motivation theory to explore solutions to this problem.

Cap a una definició inclusiva de l'e-learning

Peer-reviewed

Learning spatial filters for multispectral image segmentation

We present a novel filtering method for multispectral satellite image classification. The proposed method learns a set of spatial filters that maximize class separability of binary support vector machine (SVM) through a gradient descent approach. Regularization issues are discussed in detail and a Frobenius-norm regularization is proposed to efficiently exclude uninformative filters coefficients. Experiments carried out on multiclass one-against-all classification and target detection show the capabilities of the learned spatial filters.

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

Searching for and positioning of contextualized learning objects

Learning object economies are marketplaces for the sharing and reuse of learning objects (LO). There are many motivations for stimulating the development of the LO economy. The main reason is the possibility of providing the right content, at the right time, to the right learner according to adequate quality standards in the context of a lifelong learning process; in fact, this is also the main objective of education. However, some barriers to the development of a LO economy, such as the granularity and editability of LO, must be overcome. Furthermore, some enablers, such as learning design generation and standards usage, must be promoted in order to enhance LO economy. For this article, we introduced the integration of distributed learning object repositories (DLOR) as sources of LO that could be placed in adaptive learning designs to assist teachers’ design work. Two main issues presented as a result: how to access distributed LO, and where to place the LO in the learning design. To address these issues, we introduced two processes: LORSE, a distributed LO searching process, and LOOK, a micro context-based positioning process, respectively. Using these processes, the teachers were able to reuse LO from different sources to semi-automatically generate an adaptive learning design without leaving their virtual environment. A layered evaluation yielded good results for the process of placing learning objects from controlled learning object repositories into a learning design, and permitting educators to define different open issues that must be covered when they use uncontrolled learning object repositories for this purpose. We verified the satisfaction users had with our solution

Motivating Employees of the Public Sector: Does Public Service Motivation Matter?

This article analyzes if, and to what extent, the public service motivation (PSM) construct has an added value to explain work motivation in the public sector. In order to address the specificity of PSM when studying work motivation, the theoretical model underlying this empirical study compares PSM with two other explanatory factors: material incentives, such as performance-related pay, and team relations and support, such as recognition by superiors. This theoretical model is then tested with data collected in a national survey of 3,754 civil servants at the Swiss municipal level. Results of a structural equations model clearly show the relevance of PSM. They also provide evidence for the importance of socio-relational motivating factors, whereas material incentives play an anecdotal role.

Proactive motivation and engagement in career behaviors: Investigating direct, mediated, and moderated effects

Proactive career behaviors become increasingly important in today's career environment, but little is known about how and when motivational patterns affect individual differences. In a six-month longitudinal study among German university students (Study 1; N = 289) it was demonstrated that motivation in terms of "can do" (self-efficacy and context beliefs), "reason to" (autonomous career goals), and "energized to" (positive affect) significantly predicted career behaviors. Contrary to expectation, negative context beliefs had a positive effect when combined with other motivational states. Study 2 replicated and extended those results by investigating whether "can do" motivation mediates the effect of proactive personality and whether those effects are conditional upon the degree of career choice decidedness. We tested a moderated multiple mediation model with a unique sample of 134 German students, assessed three times, each interval being 6 weeks apart. The results showed that effects of proactivity were partially carried through higher self-efficacy beliefs but not context beliefs. Supporting a moderation model, indirect effects through self-efficacy beliefs were not present for students with very low decidedness.

Decoding sequence learning from single-trial intracranial EEG in humans.

We propose and validate a multivariate classification algorithm for characterizing changes in human intracranial electroencephalographic data (iEEG) after learning motor sequences. The algorithm is based on a Hidden Markov Model (HMM) that captures spatio-temporal properties of the iEEG at the level of single trials. Continuous intracranial iEEG was acquired during two sessions (one before and one after a night of sleep) in two patients with depth electrodes implanted in several brain areas. They performed a visuomotor sequence (serial reaction time task, SRTT) using the fingers of their non-dominant hand. Our results show that the decoding algorithm correctly classified single iEEG trials from the trained sequence as belonging to either the initial training phase (day 1, before sleep) or a later consolidated phase (day 2, after sleep), whereas it failed to do so for trials belonging to a control condition (pseudo-random sequence). Accurate single-trial classification was achieved by taking advantage of the distributed pattern of neural activity. However, across all the contacts the hippocampus contributed most significantly to the classification accuracy for both patients, and one fronto-striatal contact for one patient. Together, these human intracranial findings demonstrate that a multivariate decoding approach can detect learning-related changes at the level of single-trial iEEG. Because it allows an unbiased identification of brain sites contributing to a behavioral effect (or experimental condition) at the level of single subject, this approach could be usefully applied to assess the neural correlates of other complex cognitive functions in patients implanted with multiple electrodes.