A Content Analysis of Youth Internet Safety Programs: Are Effective Prevention Strategies Being Used?

ABSTRACT: Almost half of youth in the U.S. report receiving internet safety education (ISE) in their schools. Unfortunately, we know little about what educational messages make a difference in problems such as cyberbullying, sexting, or online predators. To consider directions for improving effectiveness, a content analysis was conducted on materials from four ISE programs. Results indicate that ISE programs are mostly not incorporating proven educational strategies. Common ISE messages have proliferated without a clear rationale for why they would be effective. It is recommended that program developers and other stakeholders reconsider ISE messages, improve educational strategies, and participate in evaluation. The field must also consider whether ISE messages would be better delivered through broader youth safety prevention programs versus stand-alone lessons

Peer mediation for conflict management: a Singaporean case study

The burgeoning interest in conflict and its management has recently begun to impact on schools and school systems worldwide. Motivated by a concern for increasing levels of violence in schools and student�student conflict, many school administrators are looking at conflict management programs as a means of dealing with the problem. Most of the more widely used programs have their origins in the United States; their appropriateness and effectiveness in other countries and cultures is, at best, unknown, and in some respects open to conjecture. In this paper the cultural appropriateness of a peer mediation program in a primary school in Singapore is the subject of investigation. The study also addresses, in an exploratory manner, the effectiveness of peer mediation as a mechanism for student�student conflict management

Integrating the IS with the enterprise: Key EAI research challenges

Enterprise Application Integration (EAI) technologies provide the means to integrate strategic business solutions within and across the component parts of organisational information system infrastructures. The continuing development of both digitally integrated business models, through various eCommerce and eBusiness initiatives, has meant that the importance of EAI within enterprise IS, has increased significantly. Noting that EAI incurs not only technological but stakeholder-level commitments, this paper outlines the product of a sustained investigation into key challenges within Enterprise IS and EAI, and provides a framework for future research and investigation into this emerging and evolving area

Becoming eco-responsible, active citizens through participation in the Eco Ambassadors project - a reflective analysis

This article offers a reflective analysis of the Eco Ambassadors Project as an example of the some of the ways in which learning about environmental issues and active citizenship can be encouraged and enabled through collaboration and negotiated participation. Some policy background to the project is given, followed by a critical consideration of the theoretical framework of situated learning and participation in a community of practice in relation to the project alongside theories of citizenship. Three activities undertaken during the project are highlighted and these are critically examined in relation to the theories under consideration. The paper argues that the theoretical framework of learning by participation can usefully augment and help better explain how learners develop their identities as citizens, and that through participation people can become active members of communities that are environmentally and politically aware

Knowledge dependencies in fuzzy information systems evaluation

Experience and research within the field of Information Systems Evaluation (ISE), has traditionally centered on providing tools and techniques for investment justification and appraisal, based upon explicit knowledge which encodes financial and other direct situational factors (such as accounting, costing and risk metrics). However, such approaches tend not to include additional causal interdependencies that are based upon tacit knowledge and are inherent within such a decision-making task. The authors show the results of applying a cognitive mapping approach, in the guise of a Fuzzy Cognitive Mapping (FCM) simulation, i.e. Fuzzy Information Systems Evaluation (F-ISE), in order to highlight the usefulness of applying such a technique. The authors highlight those contingent and necessary knowledge dependencies, in an exploratory sense, which relate to the investment appraisal decision-making task, in terms of the interplay between tacit and explicit knowledge, in this regard

Group-In: Group Inference from Wireless Traces of Mobile Devices

This paper proposes Group-In, a wireless scanning system to detect static or mobile people groups in indoor or outdoor environments. Group-In collects only wireless traces from the Bluetooth-enabled mobile devices for group inference. The key problem addressed in this work is to detect not only static groups but also moving groups with a multi-phased approach based only noisy wireless Received Signal Strength Indicator (RSSIs) observed by multiple wireless scanners without localization support. We propose new centralized and decentralized schemes to process the sparse and noisy wireless data, and leverage graph-based clustering techniques for group detection from short-term and long-term aspects. Group-In provides two outcomes: 1) group detection in short time intervals such as two minutes and 2) long-term linkages such as a month. To verify the performance, we conduct two experimental studies. One consists of 27 controlled scenarios in the lab environments. The other is a real-world scenario where we place Bluetooth scanners in an office environment, and employees carry beacons for more than one month. Both the controlled and real-world experiments result in high accuracy group detection in short time intervals and sampling liberties in terms of the Jaccard index and pairwise similarity coefficient.Comment: This work has been funded by the EU Horizon 2020 Programme under Grant Agreements No. 731993 AUTOPILOT and No.871249 LOCUS projects. The content of this paper does not reflect the official opinion of the EU. Responsibility for the information and views expressed therein lies entirely with the authors. Proc. of ACM/IEEE IPSN'20, 202

A Common-Factor Approach for Multivariate Data Cleaning with an Application to Mars Phoenix Mission Data

Data quality is fundamentally important to ensure the reliability of data for stakeholders to make decisions. In real world applications, such as scientific exploration of extreme environments, it is unrealistic to require raw data collected to be perfect. As data miners, when it is infeasible to physically know the why and the how in order to clean up the data, we propose to seek the intrinsic structure of the signal to identify the common factors of multivariate data. Using our new data driven learning method, the common-factor data cleaning approach, we address an interdisciplinary challenge on multivariate data cleaning when complex external impacts appear to interfere with multiple data measurements. Existing data analyses typically process one signal measurement at a time without considering the associations among all signals. We analyze all signal measurements simultaneously to find the hidden common factors that drive all measurements to vary together, but not as a result of the true data measurements. We use common factors to reduce the variations in the data without changing the base mean level of the data to avoid altering the physical meaning.Comment: 12 pages, 10 figures, 1 tabl