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Social annotation (SA) is a genre of learning technology that enables the annotation of digital resources for information sharing, social interaction and knowledge production. This study aims to examine the perceived value of SA as contributing to learning in multiple undergraduate courses.

In total, 59 students in 3 upper-level undergraduate courses at a Canadian university participated in SA-enabled learning activities during the winter 2019 semester. A survey was administered to measure how SA contributed to students’ perceptions of learning and sense of community.

A majority of students reported that SA supported their learning despite differences in course subject, how SA was incorporated and encouraged and how widely SA was used during course activities. While findings of the perceived value of SA as contributing to the course community were mixed, students reported that peer annotations aided comprehension of course content, confirmation of ideas and engagement with diverse perspectives.

Studies about the relationships among SA, learning and student perception should continue to engage learners from multiple courses and from multiple disciplines, with indicators of perception measured using reliable instrumentation.

Researchers and faculty should carefully consider how the technical, instructional and social aspects of SA may be used to enable course-specific, personal and peer-supported learning.

This study found a greater variance in how undergraduate students perceived SA as contributing to the course community. Most students also perceived their own and peer annotations as productively contributing to learning. This study offers a more complete view of social factors that affect how SA is perceived by undergraduate students.

This paper aims to examine the nature and sufficiency of descriptive information included in open datasets and the nature of comments and questions users write in relation to specific datasets. Open datasets are provided to facilitate civic engagement and government transparency. However, making the data available does not guarantee usage. This paper examined the nature of context-related information provided together with the datasets and identified the challenges users encounter while using the resources.

The authors extracted descriptive text provided together with (often at the top of) datasets (N = 216) and the nature of questions and comments users post in relation to the dataset. They then segmented text descriptions and user comments into “idea units” and applied open-coding with constant comparison method. This allowed them to come up with thematic issues that descriptions focus on and the challenges users encounter.

Results of the analysis revealed that context-related descriptions are limited and normative. Users are expected to figure out how to use the data. Analysis of user comments/questions revealed four areas of challenge they encounter: organization and accessibility of the data, clarity and completeness, usefulness and accuracy and language (spelling and grammar). Data providers can do more to address these issues.

The purpose of the study is to understand the nature of open data provision and suggest ways of making open data more accessible to “non expert users”. As such, it is not focused on generalizing about open data provision in various countries as such provision may be different based on jurisdiction.

The study provides insight about ways of organizing open dataset that the resource can be accessible by the general public. It also provides suggestions about how open data providers could consider users' perspectives including providing continuous support.

Research on open data often focuses on technological, policy and political perspectives. Arguably, this is the first study on analysis of context-related information in open-datasets. Datasets do not “speak for themselves” because they require context for analysis and interpretation. Understanding the nature of context-related information in open dataset is original idea.

Methods of testing simple hypotheses about lifetime parameters from doubly censored data are given on the basis of the maximum likelihood principle. It is shown that, under the assumptions of standard type, the asymptotic distribution of proposed statistics is chi‐square or linear combination of chi‐square distributions. The choice of statistics optimal from the point of view of power is discussed and illustrated by several examples.

Proposes a partially parametric estimation of a survival function when data may be both left and right censored. Assuming that the chance of censoring is not related to the individual’s survival time, the proposed estimator treats the uncensored observations non parametrically and uses parametic models for the censored observations. In this way, the results extend Klein et al.’s work (1990) to the doubly censored data case. Shows some of the properties of the estimator when the correct theoretical parametric model is selected.

Goodness‐of‐fit test based on K_ϕ‐divergence between observed and theoretical frequencies are considered. The asymptotic chi‐square null distribution and three alternative approximations to the exact distribution function of this family are compared in small samples. Numerical results are presented for the symmetric null hypothesis for different multinomial sample sizes with various cell numbers. Exact power under specific alternatives to the symmetric null hypothesis are calculated and a comparison with the family of power divergence statistics is made.

This paper analyzes the evolution of research undertaken in the last 35 years on tourist demand in Spain. The research considered has been classified into three fields with their own specific touristic characteristics; research projects that have been oriented toward the study of demand as a whole, those that study the origin of demand in specific zones and destinations and thirdly, those that address the demand of concrete tourist products and services. Forecast studies on tourist demand which are included in some of the above will also be included in this paper. The revision of these studies will take three basic factors into account: the area and the objectives of the project, the method used and the application and practical utility of the study.

The aim of this paper is to consider the role of mass mobilisations against international business in Bolivia and analyse their wider implications for the structure of the state, relating this to recent studies looking at the scope of resistance to international business.

The analysis draws from a series of formal interviews with key political actors in Bolivia which were part of a wider ethnographic study exploring the emergence of the new hegemonic bloc in the country. The narrative is framed using the discourse theory of Laclau, and the methodology inspired by Bourdieu's understanding of social ethnography.

The paper finds that the uprisings against international business in Cochabamba in 2000 and El Alto in 2003 were pivotal in developing a wider critical consciousness to oppose neoliberalism in Bolivia. Subsequently, these social movements constructed a new identity as the “people” and implemented a more radical form of democracy.

The time period studied is such that it was impossible to assess whether or not this counter‐hegemonic movement has established a hegemonic bloc that has the potential to filter out into international resistance movements against business.

The paper offers a range of insights that may be useful to social movements concerned with constructing national and international struggles against capitalism and/or neoliberalism.

As far as is known, this is one of the first papers to outline how civil society resistance to international business can lead to wholesale shifts in the balance of power within a nation state and the construction of a substantively new political order.

Taiwan experiences frequent seismic activity. Major earthquakes in recent history have seriously damaged the school buildings. School buildings in Taiwan are intended to serve both as places of education and as temporary shelters in the aftermath of major earthquakes. Therefore, the seismic performance assessments of school buildings are critical issues that deserve investigation.

This paper develops a methodology that uses principal component analysis to generalize the seismic factors from the basic seismic parameters of school buildings, uses data mining to cluster different school building sizes and uses grey theory to analyze the relationship between seismic factors and the seismic performance of school buildings. Additionally, this paper employs the Artificial Neural Network (ANN) to deduce the seismic assessment model for school buildings. Finally, it adopts support vector machine to validate the ANN’s deductive results.

An empirical study was conducted on 326 school buildings in the central area of Taichung City, Taiwan, to illustrate the effectiveness of the proposed approach. Results show that thickness of wall and width of middle-row column relate significantly with school-building seismic performance.

This paper provides a model that structural engineers or architects may use to design school buildings that are adequately resistant to earthquakes as well as a reference for future academic research.

Several coefficients, called divergences, have been suggested in the statistical literature to reflect the fact that some probability distributions are “closer together” than others and consequently that it may be easier to distinguish between the distributions of one pair than between those of another. When comparing three biological populations, it is often interesting to measure how two of them “move apart” from the third. Deals with the statistical analysis of this problem by means of bivariate divergence statistics. Provides a unified study, depicting the behaviour and relative merits of traditional divergences, by using the (h,ø), divergence family of statistics introduced by Menéndez et al.

Uses a unified expression, called H_h,v^φ1^φ2 entropy to study the asymptotic properties of entropy estimates. Shows that the asymptotic distribution of entropy estimates, in a stratified random sampling set‐up, is normal. Based on the asymptotic precision of entropy estimates, optimum sample size allocations are developed under various constraints. Gives the relative precision of stratified and simple random sampling. Also provides applications to test statistical hypotheses and to build confidence intervals.