THE EFFECTIVENESS OF COLLEGE READINESS COLLEGE PREPARATORY PROGRAMS FOR LOW-INCOME TEENAGERS

High school students from low-income backgrounds experience academic under-preparedness, financial distress, and socialization challenges when entering college. For these students, challenges may begin in the K-12 setting, where this population is more likely to face limitations in college counseling, lack highly qualified teachers, and have limited access to college programs. First generation college students are less likely to pursue and persist in higher education than their peers with different backgrounds (OECD, 2012). Because of this, low-income students may seek out or be invited to join supplemental programs, including summer bridge and afterschool programs, to help them become college ready. The research explores the main component of transitional academic support within a specific program. The study also describes how various stakeholders in precollege programming promote student persistence to and through college. This qualitative study utilizes a single case study approach using semi-structured interviews and an analysis of the program website. The resultant data illustrates the student supports, delivery methods, and culturally relevant pedagogy used within the program. As seen in the findings of this study, relationships and team collaboration is important to maintain academic preparedness and cultural relevant instruction. This study adds to the growing body of literature on associations between after school college preparation programs and collegiate success, specifically from the perspectives of designers and implementers of after school programs (Tichavakunda, 2019)

Predicting the performance of users as human sensors of security threats in social media

While the human as a sensor concept has been utilised extensively for the detection of threats to safety and security in physical space, especially in emergency response and crime reporting, the concept is largely unexplored in the area of cyber security. Here, we evaluate the potential of utilising users as human sensors for the detection of cyber threats, specifically on social media. For this, we have conducted an online test and accompanying questionnaire-based survey, which was taken by 4,457 users. The test included eight realistic social media scenarios (four attack and four non-attack) in the form of screenshots, which the participants were asked to categorise as “likely attack” or “likely not attack”. We present the overall performance of human sensors in our experiment for each exhibit, and also apply logistic regression and Random Forest classifiers to evaluate the feasibility of predicting that performance based on different characteristics of the participants. Such prediction would be useful where accuracy of human sensors in detecting and reporting social media security threats is important. We identify features that are good predictors of a human sensor’s performance and evaluate them in both a theoretical ideal case and two more realistic cases, the latter corresponding to limited access to a user’s characteristics

A taxonomy of attacks and a survey of defence mechanisms for semantic social engineering attacks

Social engineering is used as an umbrella term for a broad spectrum of computer exploitations that employ a variety of attack vectors and strategies to psychologically manipulate a user. Semantic attacks are the specific type of social engineering attacks that bypass technical defences by actively manipulating object characteristics, such as platform or system applications, to deceive rather than directly attack the user. Commonly observed examples include obfuscated URLs, phishing emails, drive-by downloads, spoofed web- sites and scareware to name a few. This paper presents a taxonomy of semantic attacks, as well as a survey of applicable defences. By contrasting the threat landscape and the associated mitigation techniques in a single comparative matrix, we identify the areas where further research can be particularly beneficial

Social engineering in the internet of everything

The Internet of Everything is becoming a reality, with fridges, smart TVs, cars, medical monitoring equipment and industrial control systems all communicating via the Internet. There have already been cases where smart toys have been exploited by hackers to steal personal information. Social engineering attacks on these devices which have little or no security are already a reality with hackers being quick to exploit any weakness in cyber space. This article reviews past cases, gives three scenarios which could lead to the owner of an IoT device giving private information to hackers and then proposes defence recommendations

An eye for deception: A case study in utilizing the human-as-a-security-sensor paradigm to detect zero-day semantic social engineering attacks

In a number of information security scenarios, human beings can be better than technical security measures at detecting threats. This is particularly the case when a threat is based on deception of the user rather than exploitation of a specific technical flaw, as is the case of spear-phishing, application spoofing, multimedia masquerading and other semantic social engineering attacks. Here, we put the concept of the humanas-a-security-sensor to the test with a first case study on a small number of participants subjected to different attacks in a controlled laboratory environment and provided with a mechanism to report these attacks if they spot them. A key challenge is to estimate the reliability of each report, which we address with a machine learning approach. For comparison, we evaluate the ability of known technical security countermeasures in detecting the same threats. This initial proof of concept study shows that the concept is viable

You are probably not the weakest link: Towards practical prediction of susceptibility to semantic social engineering attacks

Semantic social engineering attacks are a pervasive threat to computer and communication systems. By employing deception rather than by exploiting technical vulnerabilities, spear-phishing, obfuscated URLs, drive-by downloads, spoofed websites, scareware, and other attacks are able to circumvent traditional technical security controls and target the user directly. Our aim is to explore the feasibility of predicting user susceptibility to deception-based attacks through attributes that can be measured, preferably in real-time and in an automated manner. Toward this goal, we have conducted two experiments, the first on 4333 users recruited on the Internet, allowing us to identify useful high-level features through association rule mining, and the second on a smaller group of 315 users, allowing us to study these features in more detail. In both experiments, participants were presented with attack and non-attack exhibits and were tested in terms of their ability to distinguish between the two. Using the data collected, we have determined practical predictors of users' susceptibility against semantic attacks to produce and evaluate a logistic regression and a random forest prediction model, with the accuracy rates of. 68 and. 71, respectively. We have observed that security training makes a noticeable difference in a user's ability to detect deception attempts, with one of the most important features being the time since last self-study, while formal security education through lectures appears to be much less useful as a predictor. Other important features were computer literacy, familiarity, and frequency of access to a specific platform. Depending on an organisation's preferences, the models learned can be configured to minimise false positives or false negatives or maximise accuracy, based on a probability threshold. For both models, a threshold choice of 0.55 would keep both false positives and false negatives below 0.2

An Evaluation of Equid Welfare Perceptions and Knowledge Discrepancies

Equids are used as beasts of burden, show animals, and as a protein and milk source throughout the world; the uses vary from country to country. The depth and topical range of knowledge also varies significantly. This study identifies topical and geographical areas that need education on equid management and welfare, and ways to best distribute educational material. Knowledge related to husbandry, management, and health needs was measured and observed through the distribution of in-depth surveys and on-farm observation. Surveys and observations took place in Spain, Portugal, and Italy to determine how equid owners use their equids and how owners prioritize management and care practices, sources of information used for equid education, perceived credibility of sources used, current perceived knowledge of equid welfare, and owner perceived importance of welfare knowledge. The overall response rate among the 3 countries described competitive showing as the primary use of equids. The cumulative response in all countries showed that books were the most commonly used source of information; though, the cumulative response for the countries collectively resulted in seminars being perceived to have the highest credibility amongst equid owners. Overall, owners in Spain, Portugal, and Italy generally had a perceived knowledge of “average” for equid care practices. Using a mean weighted discrepancy score, lameness and nutrition were identified as areas in which the largest “gap” between perceived knowledge and perceived importance occurred. This gap identifies these areas as the target subjects for future educational programs. It is concluded that the dissemination of educational information would be most effective if provided through seminars

Assessing the cyber-trustworthiness of human-as-a-sensor reports from mobile devices

The Human-as-a-Sensor (HaaS) paradigm, where it is human users rather than automated sensor systems that detect and report events or incidents has gained considerable traction over the last decades, especially as Internet-connected smartphones have helped develop an information sharing culture in society. In the law enforcement and civil protection space, HaaS is typically used to harvest information that enhances situational awareness regarding physical hazards, crimes and evolving emergencies. The trustworthiness of this information is typically studied in relation to the trustworthiness of the human sensors. However, malicious modification, prevention or delay of reports can also be the result of cyber or cyber-physical security breaches affecting the mobile devices and network infrastructure used to deliver HaaS reports. Examples of these can be denial of service attacks, where the timely delivery of reports is important, and location spoofing attacks, where the accuracy of the location of an incident is important. The aim of this paper is to introduce this cyber-trustworthiness aspect in HaaS and propose a mechanism for scoring reports in terms of their cyber-trustworthiness based on features of the mobile device that are monitored in real-time. Our initial results show that this is a promising line of work that can enhance the reliability of HaaS

Winning and losing in the creative industries: an analysis of creative graduates' career opportunities across creative disciplines

Following earlier work looking at overall career difficulties and low economic rewards faced by graduates in creative disciplines, the paper takes a closer look into the different career patterns and economic performance of “Bohemian” graduates across different creative disciplines. While it is widely acknowledged in the literature that careers in the creative field tend to be unstructured, often relying on part-time work and low wages, our knowledge of how these characteristics differ across the creative industries and occupational sectors is very limited. The paper explores the different trajectory and career patterns experienced by graduates in different creative disciplinary fields and their ability to enter creative occupations. Data from the Higher Education Statistical Agency (HESA) are presented, articulating a complex picture of the reality of finding a creative occupation for creative graduates. While students of some disciplines struggle to find full-time work in the creative economy, for others full-time occupation is the norm. Geography plays a crucial role also in offering graduates opportunities in creative occupations and higher salaries. The findings are contextualised in the New Labour cultural policy framework and conclusions are drawn on whether the creative industries policy construct has hidden a very problematic reality of winners and losers in the creative economy

Changing practice to support self-management and recovery in mental illness: application of an implementation model

Author Version made available in accordance with the publisher's policyHealth services introducing practice changes need effective implementation methods. Within the setting of a community mental health service offering recovery-oriented psychosocial support for people with mental illness, we aimed to (a) identify a well-founded implementation model and (b) assess its practical usefulness in introducing a new program for recovery-oriented self-management support. We reviewed the literature to identify implementation models applicable to community mental health, and having corresponding measurement tools. We used one of these models to inform organisational change strategies. The literature review showed few models with corresponding tools. The Promoting Action on Research Implementation in Health Services (PARIHS) model and the related Organizational Readiness to Change Assessment (ORCA) tool were used. PARIHS proposes prerequisites for health service change and the ORCA measures the extent to which these prerequisites are present. Application of the ORCA at two time points during implementation of the new program showed strategy-related gains for some prerequisites but not for others, reflecting observed implementation progress. Additional strategies to address target prerequisites could be drawn from the PARIHS model. The PARIHS model and ORCA tool have potential in designing and monitoring practice change strategies in community mental health. Further practical use and testing of implementation models appears justified in overcoming barriers to change