Characterising effective eLearning resources

The widespread availability of digital learning resources in a variety of media formats offers the possibility to make a profound difference in education. This potential has not been fully realised for range of interrelated reasons. In this paper we study the key characteristics of learning resources that have proved effective in changing learning and teaching, and relate them to existing frameworks for understanding resources. We outline the relationships between resources, their users, and the way they are used, and explore issues that influence practitioners in choosing a particular resource. Our study is based on a review of resources for e-learning and chemistry in post-compulsory education, undertaken for the UK Joint Information Systems Committees (JISC), as part of a wider study examining ‘The Effectiveness of Resources, Tools and Support Services used by Tutors in Designing and Delivering E-Learning Activities’.     

Connecting the dots: Understanding the interrelated impacts of type,quality and children's awareness of design features and the mathematics content learning goals in digital math games and related learning outcomes

This study focused on an examination of how type, quality and children's awareness of design features in digital math games, along with an awareness of the mathematics goals of the game, were related to learning outcomes. We conducted a parallel conversion mixed methods study with 45 students in Grades 3 and 4 (ages 9–10). Students participated in clinical interviews using three digital math games. The results suggest a moderated mediation relationship in which the quality of the design features moderated the mediating impact of children's awareness of the game's design features, specifically when the child was aware of the mathematics content learning goal (MCLG) of the game. These findings show how important it is that design features are of high quality in a digital math game, and how this is intertwined with children's awareness of the features and the MCLG. When these variables intertwined in just the right way, the interactions between the children and the digital math game afforded mathematical learning growth.     

Speed-accuracy characteristics of human-machine cooperative manipulation using virtual fixtures with variable admittance

This work explores the effect of virtual fixture admittance on the performance, defined by error and time, of task execution with a human-machine cooperative system. A desired path is obtained using computer vision, and virtual fixtures for assistance in planar path following were implemented on an admittance-controlled robot. The admittance controller uses a velocity gain, so that the speed of the robot is proportional to the force applied by the operator. The level of virtual fixture guidance is determined by the admittance ratio, which is the ratio of the admittance gain of the force components orthogonal to the path to the gain of the force components parallel to the path. In Experiment 1, we found a linear relationship between admittance ratio and performance. In Experiment 2, we examined the effect of admittance ratio on the performance of three tasks: path following, off-path targeting, and obstacle avoidance. An algorithm was developed to select an appropriate admittance ratio based on the nature of the task. Automatic admittance ratio tuning is recommended for next-generation virtual fixtures. Actual or potential applications of this research include surgery, assembly, and manipulation at the macro and micro scales.     

Experimental study of diffusion-based extraction from a cell suspension

A recently proposed application of microfluidics is the post-thaw processing of biological cells. Numerical simulations suggest that diffusion-based extraction of the cryoprotective agent dimethyl sulfoxide (DMSO) from blood cells is viable and more efficient than centrifugation, the conventional method of DMSO removal. In order to validate the theoretical model used in these simulations, a prototype was built and the flow of two parallel streams, a suspension of Jurkat cells containing DMSO and a wash stream that contained neither cells nor DMSO, was characterized experimentally. DMSO transport in a rectangular channel (depth 500 μm, width 25 mm and overall length 125 mm) was studied as a function of three dimensionless parameters: depth ratio of the streams, cell volume fraction in the cell solution, and the Peclet number (Pe) based on channel depth, average flow rate and the diffusion coefficient for DMSO in water. In our studies, values of Pe ranged from O(10³) to O(10⁴). Laminar flow was ensured by keeping the Reynolds number between O(1) and O(10). Experimental results based on visual and quantitative data demonstrate conclusively that a microfluidic device can effectively remove DMSO from liquid and cell laden streams without compromising cell recovery. Also, flow conditions in the microfluidic device appear to have no adverse effect on cell viability at the outlet. Further, the results demonstrate that we can predict the amount of DMSO removed from a given device with the theoretical model mentioned previously.     

The integration of a satellite spectral analysis into a heather moorland management model (HMMM): The case of Moidach More,northeast Scotland,U.K.

In this paper, high resolution, remotely-sensed data are investigated as a source of management information for moorland vegetation communities on a hypothetical farm in a marginal farming area of Scotland. A hybrid technique for vegetation mapping is adopted. This involves unsupervised machine classification of spectral variation in digitally enhanced air photographs and satellite imagery, together with visual interpretation of the imagery in both the laboratory and the field. This technique enables relative estimates of annual gross biomass production, for a range of vegetation types, to be obtained. The data are integrated into a simple heather moorland management model (HMMM), to produce potential sheep-stocking capacities under a range of management scenarios, the possible financial implications of these scenarios are also assessed.     

Characteristics of college cyberbullies

Cyberbullying is a newer variation of bullying that utilizes technology to harass. This study investigated the psychological symptomology, suicidal behaviors, aggressive tendencies, and illegal behaviors of college cyberbullies. Sixty cyberbullies and 19 cyberbully/victims (participants who cyberbullied and were victims of cyberbullying) scored higher in psychological symptoms of depression, hostility, interpersonal sensitivity, paranoia, phobic anxiety, and psychoticism than participants who were uninvolved with cyberbullying. The cyberbullies also endorsed more suicidal behaviors and scored higher in aggression. The cyberbully/victims engaged in more violent and drug crimes than cyberbullies and controls. These findings indicate perpetrators of cyberbullying have more psychological distress, aggressive tendencies, and engage in more illegal behaviors than those who do not cyberbully. This is the first study to show the distress cyberbullies are experiencing.     

Learning Organizations in Construction

The transformation of organizations from production-oriented entities to proactive learning entities that continuously leverage the knowledge of the workforce is a primary objective of management researchers. This focus has significant relevance to the construction industry where production-related research has predominantly overshadowed organizational development research. As one effort to change this emphasis, the writers present a research effort designed to study current organization learning techniques and technologies fielded by organizations both inside and outside of the construction industry. Through a series of exploratory case studies, the writers developed a maturity model together with the Construction Industry Institute that provides construction organizations with a framework for developing a learning organization culture. The maturity model focuses on learning organization characteristics of leadership, processes and infrastructure, communication/collaboration, education, and culture at the organization, community, and individual levels. This paper introduces the results of that effort including a presentation of the learning organization maturity model, framework application, and the overall characteristics of a learning organization.     

Bare necessities: the argument for a ‘revenge porn’ exception in Section 230 immunity

‘Revenge porn’ is the online posting of nude or sexually explicit photographs or videos of a former lover without his or her consent. Despite the malicious intent behind revenge porn, victims are provided with little to no relief due to Section 230 of the Federal Communications Decency Act, also known as the ‘Good Samaritan’ provisions. Section 230 unambiguously provides blanket immunity for website operators and Internet service providers that feature user-generated content, including revenge porn.

In Section 1, I discuss the purpose of Section 230 of the Communication Decency Act. In Section 2, I analyze the legal impact of the blanket immunity established in Section 230. In Section 3, I examine the potential remedies already in existence for revenge porn victims and highlight their inadequacies. In Section 4, I argue Congress should create a narrow exception to Section 230 immunity specifically geared toward revenge porn. The exception would establish a definition of revenge porn, which would prevent over-deterrence. Additionally, the exception would institute a takedown procedure similar to the process found in the Digital Millennium Copyright Act. In creating a narrow exception, the spirit of Section 230 will remain while also providing adequate legal relief for victims of revenge porn.     

Intelligent security and access control framework for service-oriented architecture

One of the most significant difficulties with developing Service-Oriented Architecture (SOA) involves meeting its security challenges, since the responsibilities of SOA security are based on both the service providers and the consumers. In recent years, many solutions to these challenges have been implemented, such as the Web Services Security Standards, including WS-Security and WS-Policy. However, those standards are insufficient for the new generation of Web technologies, including Web 2.0 applications. In this research, we propose an intelligent SOA security framework by introducing its two most promising services: the Authentication and Security Service (NSS), and the Authorization Service (AS). The suggested autonomic and reusable services are constructed as an extension of WS-¹ security standards, with the addition of intelligent mining techniques, in order to improve performance and effectiveness. In this research, we apply three different mining techniques: the Association Rules, which helps to predict attacks, the Online Analytical Processing (OLAP) Cube, for authorization, and clustering mining algorithms, which facilitate access control rights representation and automation. Furthermore, a case study is explored to depict the behavior of the proposed services inside an SOA business environment. We believe that this work is a significant step towards achieving dynamic SOA security that automatically controls the access to new versions of Web applications, including analyzing and dropping suspicious SOAP messages and automatically managing authorization roles.     

What do you learn about someone over time? The relationship between length of acquaintance and consensus and self-other agreement in judgments of personality.

Theory and research examining length of acquaintance and consensus among personality judgments have predominantly examined each dimension of personality separately. In L. J. Cronbach's (1955) terminology, this trait-centered approach combines consensus on elevation, differential elevation, and differential accuracy in personality judgments. The current article extends D. A. Kenny's (1991, 1994) weighted average model (WAM)--a theoretical model of the factors that influence agreement among personality judgments--to separate out two of Cronbach's components of consensus: stereotype accuracy and differential accuracy. Consistent with the predictions based on the WAM, as length of acquaintance increased, self-other agreement and consensus differential accuracy increased, stereotype accuracy decreased, and trait-level or raw profile correlations generally remained unchanged. Discussion focuses on the conditions under which a relationship between length of acquaintance and consensus and self-other agreement among personality evaluations emerges and how impressions change over time. (PsycINFO Database Record (c) 2010 APA, all rights reserved)