Personalization of tagging systems

Social media systems have encouraged end user participation in the Internet, for the purpose of storing and distributing Internet content, sharing opinions and maintaining relationships. Collaborative tagging allows users to annotate the resulting user-generated content, and enables effective retrieval of otherwise uncategorised data. However, compared to professional web content production, collaborative tagging systems face the challenge that end-users assign tags in an uncontrolled manner, resulting in unsystematic and inconsistent metadata.This paper introduces a framework for the personalization of social media systems. We pinpoint three tasks that would benefit from personalization: collaborative tagging, collaborative browsing and collaborative search. We propose a ranking model for each task that integrates the individual user’s tagging history in the recommendation of tags and content, to align its suggestions to the individual user preferences. We demonstrate on two real data sets that for all three tasks, the personalized ranking should take into account both the user’s own preference and the opinion of others.     

Goal striving, coping, and well-being: a prospective investigation of the self-concordance model in sport

Developing upon cross-sectional research (Smith, Ntoumanis, & Duda, 2007) supporting the self-concordance model (Sheldon & Elliot, 1999) as a framework for contextual goal striving, the current study investigated the assumptions of the model in relation to season-long goal striving in sport. The study additionally examined the role of coping strategies in the persistence of goal-directed effort. Structural equation modeling analysis with a sample of 97 British athletes indicated that start-of-season autonomous goal motives were linked to midseason effort, which subsequently predicted end-of-season goal attainment. Attainment was positively related to changes in psychological need satisfaction, which, in turn, predicted changes in emotional well-being. In a second model, autonomous and controlled motives positively predicted task- and disengagement-oriented coping strategies, respectively. In turn, these strategies were differentially associated with effort. The findings provide support for contextual adaptations of the self-concordance model and demonstrate the role of coping strategies in the goal striving process.     

How you provide corrective feedback makes a difference: the motivating role of communicating in an autonomy-supporting way

We relied on self-determination theory (SDT; Deci & Ryan, 2000) to investigate to what extent autonomy-supporting corrective feedback (i.e., feedback that coaches communicate to their athletes after poor performance or mistakes) is associated with athletes' optimal motivation and well-being. To test this hypothesis, we conducted a cross-sectional study with 337 (67.1% males) Greek adolescent athletes (age M = 15.59, SD = 2.37) from various sports. Aligned with SDT, we found through path analysis that an autonomy-supporting versus controlling communication style was positively related to future intentions to persist and well-being and negatively related to ill-being. These relations were partially mediated by the perceived legitimacy of the corrective feedback (i.e., the degree of acceptance of corrective feedback), and, in turn, by intrinsic motivation, identified regulation, and external regulation for doing sports. Results indicate that autonomy-supporting feedback can be still motivating even in cases in which such feedback conveys messages of still too low competence.     

Predicting objectively assessed physical activity from the content and regulation of exercise goals: evidence for a mediational model

Grounded in self-determination theory (Deci & Ryan, 2000), the purpose of this work was to examine effects of the content and motivation of adults' exercise goals on objectively assessed moderate-to-vigorous physical activity (MVPA). After reporting the content and motivation of their exercise goals, 101 adult participants (Mage = 38.79 years; SD = 11.5) wore an ActiGraph (GT1M) accelerometer for seven days. Accelerometer data were analyzed to provide estimates of engagement in MVPA and bouts of physical activity. Goal content did not directly predict behavioral engagement; however, mediation analysis revealed that goal content predicted behavior via autonomous exercise motivation. Specifically, intrinsic versus extrinsic goals for exercise had a positive indirect effect on average daily MVPA, average daily MVPA accumulated in 10-min bouts and the number of days on which participants performed 30 or more minutes of MVPA through autonomous motivation. These results support a motivational sequence in which intrinsic versus extrinsic exercise goals influence physical activity behavior because such goals are associated with more autonomous forms of exercise motivation.     

Language and Tools for Networkers

Abstract

The network society has a major impact on knowledge systems, and in agricultural and rural development. It has changed relationships between actors such as farmers, extension workers, researchers, policy-makers, businessmen and consumers. These changes require different language, concepts and tools compared to the time that it was thought that science led the way and new findings had to be disseminated to target groups. Also the language of the market, talking about clients and knowledge producers, demand-driven systems and calculable results, is insufficient to describe what actually happens in innovative farmers’ networks or to guide knowledge workers in what to do for speeding up such processes. This article describes experiences from a large scale experiment in the Netherlands: the ‘Networks in Animal Husbandry’ programme (2004–2007). The basic idea was to ask farmers to come up with innovative ideas that could help the sector farther along the track of sustainable development, and then to assist them with scientific expertise. The facilitators were embedded in a learning community and provided with language, tools and methods that grew along the way. After a total of 120 networks and many peer consultation meetings with the facilitators, a huge number of experiences have been registered. Their work required a new generation of tools: as ‘free actors’ they had to learn how to navigate in unknown areas, recognise at any moment what was at stake and intervene appropriately. The FAN approach emerged: Free Actors in Networks.     

Linear feature extraction for ranking

We address the feature extraction problem for document ranking in information retrieval. We then propose LifeRank, a Linear feature extraction algorithm for Ranking. In LifeRank, we regard each document collection for ranking as a matrix, referred to as the original matrix. We try to optimize a transformation matrix, so that a new matrix (dataset) can be generated as the product of the original matrix and a transformation matrix. The transformation matrix projects high-dimensional document vectors into lower dimensions. Theoretically, there could be very large transformation matrices, each leading to a new generated matrix. In LifeRank, we produce a transformation matrix so that the generated new matrix can match the learning to rank problem. Extensive experiments on benchmark datasets show the performance gains of LifeRank in comparison with state-of-the-art feature selection algorithms.     

Study persistence and academic achievement as a function of the type of competing tendencies

In order to understand and predict students’ achievement and persistence at learning activities, many contemporary motivational models consider how much students are motivated for their school work. However, students’ achievement and persistence might not only be affected by their amount of study motivation, but also by the motivation to engage in competing alternative activities, as suggested three decades ago by Atkinson and Birch in their “Dynamics of Action” (1970). Building on this line of theorizing, the present contribution indicates that it is not only instructive to consider the level of students’ motivation for these competing activities, but also the type of activities they engage in, that is leisure vs. working activities. Two studies demonstrated that whereas time spent on working activities is inversely related to study motivation, attitude, persistence and academic achievement, such relationships were not found for leisure time engagement. Spending some time on leisure time activities does not interfere with optimal learning.     

How do high school students solve probability problems? A mixed methods study on probabilistic reasoning

When studying a complex research phenomenon, a mixed methods design allows to answer a broader set of research questions and to tap into different aspects of this phenomenon, compared to a monomethod design. This paper reports on how a sequential equal status design (QUAN → QUAL) was used to examine students’ reasoning processes when solving probability problems. A select clustered sampling resulted in the inclusion of 168 high school students in a first, quantitative phase, in which a questionnaire was used to assess how they solved probability problems. This questionnaire included probability items that were based on the outcome orientation, the representativeness misconception, and the equiprobability bias. In a second, qualitative phase, 18 students who were purposefully sampled from the first research phase were interviewed in order to conduct an in-depth study of their probabilistic reasoning processes. In this paper, we illustrate and discuss how several mixed methods research purposes were realized throughout our study: development, expansion, and initiation.