Risks of Friendships on Social Networks

In this paper, we explore the risks of friends in social networks caused by their friendship patterns, by using real life social network data and starting from a previously defined risk model. Particularly, we observe that risks of friendships can be mined by analyzing users' attitude towards friends of friends. This allows us to give new insights into friendship and risk dynamics on social networks.Comment: 10 pages, 8 figures, 3 tables. To Appear in the 2012 IEEE International Conference on Data Mining (ICDM

Cross-Country Evidence on Teacher Performance Pay

The general-equilibrium effects of performance-related teacher pay include long-term incentive and teacher-sorting mechanisms that usually elude experimental studies but are captured in cross-country comparisons. Combining country-level performance-pay measures with rich PISA-2003 international achievement micro data, this paper estimates student-level international education production functions. The use of teacher salary adjustments for outstanding performance is significantly associated with math, science, and reading achievement across countries. Scores in countries with performance-related pay are about one quarter standard deviations higher. Results avoid bias from within-country selection and are robust to continental fixed effects and to controlling for non-performance-based forms of teacher salary adjustments.PISA, teacher performance pay, international, student achievement

Cross-Country Evidence on Teacher Performance Pay

The general-equilibrium effects of performance-related teacher pay include long-term incentive and teacher-sorting mechanisms that usually elude experimental studies but are captured in cross-country comparisons. Combining country-level performance-pay measures with rich PISA-2003 international achievement micro data, this paper estimates student-level international education production functions. The use of teacher salary adjustments for outstanding performance is significantly associated with math, science, and reading achievement across countries. Scores in countries with performance-related pay are about one quarter standard deviations higher. Results avoid bias from within-country selection and are robust to continental fixed effects and to controlling for non-performance-based forms of teacher salary adjustments.teacher performance pay, student achievement, international, PISA

A comparison of A-level performance in economics and business studies: how much more difficult is economics?

This paper uses ALIS data to compare academic performance in two subjects often viewed as relatively close substitutes for one another at A-level. The important role of GCSE achievement is confirmed for both subjects. There is evidence of strong gender effects and variation in outcomes across Examination Boards. A counterfactual exercise suggests that if the sample of Business Studies candidates had studied Economics nearly 40% of those who obtained a grade C or better in the former subject would not have done so in the latter. The opposite exercise uggests that 12% more Economics candidates would have achieved a grade C or better if they had taken Business Studies. In order to render a Business Studies A-level grade comparable to an Economics one in terms of relative difficulty, we estimate that a downward adjustment of 1.5 UCAS points should be applied to the former subject. This adjustment is lower than that suggested by correction factors based on conventional subject pair analysis for these two subjects

Distributed-based massive processing of activity logs for efficient user modeling in a Virtual Campus

This paper reports on a multi-fold approach for the building of user models based on the identification of navigation patterns in a virtual campus, allowing for adapting the campus’ usability to the actual learners’ needs, thus resulting in a great stimulation of the learning experience. However, user modeling in this context implies a constant processing and analysis of user interaction data during long-term learning activities, which produces huge amounts of valuable data stored typically in server log files. Due to the large or very large size of log files generated daily, the massive processing is a foremost step in extracting useful information. To this end, this work studies, first, the viability of processing large log data files of a real Virtual Campus using different distributed infrastructures. More precisely, we study the time performance of massive processing of daily log files implemented following the master-slave paradigm and evaluated using Cluster Computing and PlanetLab platforms. The study reveals the complexity and challenges of massive processing in the big data era, such as the need to carefully tune the log file processing in terms of chunk log data size to be processed at slave nodes as well as the bottleneck in processing in truly geographically distributed infrastructures due to the overhead caused by the communication time among the master and slave nodes. Then, an application of the massive processing approach resulting in log data processed and stored in a well-structured format is presented. We show how to extract knowledge from the log data analysis by using the WEKA framework for data mining purposes showing its usefulness to effectively build user models in terms of identifying interesting navigation patters of on-line learners. The study is motivated and conducted in the context of the actual data logs of the Virtual Campus of the Open University of Catalonia.Peer ReviewedPostprint (author's final draft

Do Gender Stereotypes Reduce Girls' Human Capital Outcomes? Evidence from a Natural Experiment

Schools and teachers are often said to be a source of stereotypes that harm girls. This paper tests for the existence of gender stereotyping and discrimination by public high-school teachers in Israel. It uses a natural experiment based on blind and non-blind scores that students receive on matriculation exams in their senior year. Using data on test results in several subjects in the humanities and sciences, I found, contrary to expectations, that male students face discrimination in each subject. These biases widen the female male achievement gap because girls outperform boys in all subjects, except English, and at all levels of the curriculum. The bias is evident in all segments of the ability and performance distribution and is robust to various individual controls. Several explanations based on differential behavior between boys and girls are not supported empirically. However, the size of the bias is very sensitive to teachers' characteristics, suggesting that the bias against male students is the result of teachers', and not students', behavior.

Multilevel modelling of refusal and noncontact nonresponse in household surveys: evidence from six UK government surveys

This paper analyses household unit nonresponse and interviewer effects in six major UK government surveys using a multilevel multinomial modelling approach. The models are guided by current conceptual frameworks and theories of survey participation. One key feature of the analysis is the investigation of survey dependent and independent effects of household and interviewer characteristics, providing an empirical exploration of the leverage-salience theory. The analysis is based on the 2001 UK Census Link Study, a unique data source containing an unusually rich set of auxiliary variables, linking the response outcome of six surveys to census data, interviewer observation data and interviewer information, available for respondents and nonrespondents