Making geography mobile: using location aware technology to improve student performance in physical geography

With the increased availability of new technologies, geography educators are revisiting their pedagogical approaches to teaching and calling for opportunities to share local and international practices which will enhance the learning experience and improve students’ performance. This paper reports on the use of handheld mobile devices, fitted with GPS, by secondary (high) school pupils in geography. Two location-aware activities were completed over one academic year (one per semester) and pre-test and post-test scores for both topics revealed a statistically significant increase in pupils’ performance as measured by the standard national assessments. A learner centred educational approach was adopted with the first mobile learning activity being created by the teacher as an exemplar of effective mobile learning design. Pupils built on their experiences of using mobile learning when they were required to created their own location aware learning task for peer use. An analysis of the qualitative data from the pupils’ journals, group diaries and focus group interviews revealed the five pillars of learner centred education are addressed when using location aware technologies and the use of handheld mobile devices offered greater flexibility and autonomy to the pupils thus altering the level of power and control away from the teacher. Due to the relatively small number of participants in the study, the results are more informative than generalisable however in light of the growing interest in geo-spatial technologies in geography education, this paper offers encouragement and insight into the use of location aware technology in a compulsory school context

Making Social Work Education App’ier : The Process of Developing Information-based Apps for Social Work Education and Practice

Mobile App technology in social work education remains in the embryonic stages of development with a few notable exceptions. The use of Apps in College and University settings has been reported in other sectors of higher education, although there is a paucity of research in relation to its relevance to social work education and practice. The following article describes the creation of four social work education and practice Apps by a team of social work educators. The primary focus is on the design process and the partnership approach to the creation of the tools. It also outlines the rationale for the App development, the working process and the theoretical framework underpinning mobile learning. Furthermore, it provides information on the level of usage of the Apps according to geographical location, download information and time spent on each section of the App. The article also incorporates a pragmatic summary of developmental guidelines which may aid social work educators in the development and implementation of specialist information-based Apps for education and practice.

The Use of Audio Podcasts to Enhance the Delivery of a Computer Networks Course

Experience obtained in the support of mobile learning using podcast audio is reported. The paper outlines design, storage and distribution via a web site. An initial evaluation of the uptake of the approach in a final year computing module was undertaken. Audio objects were tailored to meet different pedagogical needs resulting in a repository of persistent glossary terms and disposable audio lectures distributed by podcasting. An aim of our approach is to document the interest from the students, and evaluate the potential of mobile learning for supplementing revision

Exploring the mobile structural assessment tool: Concept maps for learning website: Concept Maps for Learning Website

In this paper, we describe how the pathfinder algorithm converts relatedness ratings of concept pairs to concept maps; we also present how this algorithm has been used to develop the Concept Maps for Learning website (www.conceptmapsforlearning.com) based on the principles of effective formative assessment. The pathfinder networks, one of the network representation tools, claim to help more students memorize and recall the relations between concepts than spatial representation tools (such as Multi- Dimensional Scaling). Therefore, the pathfinder networks have been used in various studies on knowledge structures, including identifying students’ misconceptions. To accomplish this, each student’s knowledge map and the expert knowledge map are compared via the pathfinder software, and the differences between these maps are highlighted. After misconceptions are identified, the pathfinder software fails to provide any feedback on these misconceptions. To overcome this weakness, we have been developing a mobile-based concept mapping tool providing visual, textual and remedial feedback (ex. videos, website links and applets) on the concept relations. This information is then placed on the expert concept map, but not on the student’s concept map. Additionally, students are asked to note what they understand from given feedback, and given the opportunity to revise their knowledge maps after receiving various types of feedback.

Using location-aware technology for learning Geography in a real digital space outside the classroom

The use of new mobile technologies is still in its infancy in many secondary schools and there is limited evidence of the educational and pedagogical benefits on pupils’ learning in the formal school context. This qualitative study focuses on the use of handheld devices to teach a topic in geography to an examination class. Action research combined with pupil observations and focus group interviews are used to capture the pupils’ experiences of using mediascapes. Activity Theory is used as a lens to structure the analysis of the data and to report on the cognitive and affective impact of m-learning on pupils’ academic performance in the topic. Increased attainment and the development of wider skills for lifelong learning were identified in the study. The adaptability of the majority of pupils to the technology resulted in increased levels of willingness to learn in this novel context.

Contingency Learning and Reactivity in Preterm and Full-Term Infants at 3 Months

Learning difficulties in preterm infants are thought to reflect impairment in arousal regulation. We examined relationships among gestational age, learning speed, and behavioral and physiological reactivity in 55 preterm and 49 full-term infants during baseline, contingency, and nonreinforcement phases of a conjugate mobile paradigm at 3 months corrected age. For all infants, negative affect, looking duration, and heart rate levels increased during contingency and nonreinforcement phases, whereas respiratory sinus arrhythmia (RSA, an index of parasympathetic activity) decreased and cortisol did not change. Learners showed greater RSA suppression and less negative affect than nonlearners. This pattern was particularly evident in the preterm group. Overall, preterm infants showed less learning, spent less time looking at the mobile, and had lower cortisol levels than full-term infants. Preterm infants also showed greater heart rate responses to contingency and dampened heart rate responses to nonreinforcement compared to full-term infants. Findings underscore differences in basal and reactivity measures in preterm compared to full-term infants and suggest that the capacity to regulate parasympathetic activity during a challenge enhances learning in preterm infants.

Cortisol, contingency learning, and memory in preterm and full-term infants

Cortisol plays an important role in learning and memory. An inverted-U shaped function has been proposed to account for the positive and negative effects of cortisol on cognitive performance and memory in adults, such that too little or too much impair but moderate amounts facilitate performance. Whether such relationships between cortisol and mental function apply to early infancy, when cortisol secretion, learning, and memory undergo rapid developmental changes, is unknown. We compared relationships between learning/memory and cortisol in preterm and full-term infants and examined whether a greater risk for adrenal insufficiency associated with prematurity produces differential cortisol-memory relationships. Learning in three-month old (corrected for gestational age) preterm and full-term infants was evaluated using a conjugate reinforcement mobile task. Memory was tested by repeating the same task 24h later. Salivary cortisol samples were collected before and 20 min after the presentation of the mobile. We found that preterm infants had lower cortisol levels and smaller cortisol responses than full-term infants. This is consistent with relative adrenal insufficiency reported in the neonatal period. Infants who showed increased cortisol levels from 0 to 20 min on Day 1 had significantly better memory, regardless of prematurity, than infants who showed decreased cortisol levels.

Android Malware Detection Using Parallel Machine Learning Classifiers

Mobile malware has continued to grow at an alarming rate despite on-going mitigation efforts. This has been much more prevalent on Android due to being an open platform that is rapidly overtaking other competing platforms in the mobile smart devices market. Recently, a new generation of Android malware families has emerged with advanced evasion capabilities which make them much more difficult to detect using conventional methods. This paper proposes and investigates a parallel machine learning based classification approach for early detection of Android malware. Using real malware samples and benign applications, a composite classification model is developed from parallel combination of heterogeneous classifiers. The empirical evaluation of the model under different combination schemes demonstrates its efficacy and potential to improve detection accuracy. More importantly, by utilizing several classifiers with diverse characteristics, their strengths can be harnessed not only for enhanced Android malware detection but also quicker white box analysis by means of the more interpretable constituent classifiers.

English Language Education at University: Trends and Challenges in Teaching and Learning Academic Discourse in the UK

This chapter discusses English Language Education at university and highlights a number of trends and their associated challenges in teaching and learning academic discourse. Academic discourse refers to the ways in which language is used by participants in academia. It encompasses written discourse, from article and book publishing, PhD theses to course assignments; spoken discourse, from study groups, tutorials, conference presentations to inaugural lectures; and more recently, computer-mediated discourse, from asynchronous text-based conferencing to academic blogs. The role of English language educators in preparing students and academics for successful participation in these academic events, or the academy, in English is not to be underestimated. Academic communication is not only vital to an individual’s success at university, but to the maintenance and creation of academic communities and to scientific progress itself (Hyland, 2009). This chapter presents an overview of academic discourse and discusses recent issues which have an impact on teaching and learning English at university and discusses their associated challenges: first, the increasing internationalisation of universities. Second, the emergence of a mobile academe in its broadest sense, in which students and academics move across traditional geopolitical, institutional and disciplinary boundaries, is discussed. Third, the growth of UK transnational higher education is examined as a trend which sees academics and students vicariously or otherwise involved in English language teaching and learning. Fourth, the chapter delves into the rapid and ongoing development in technology assisted and online learning. While responding to trends can be difficult, they can also inspire ingenuity. Furthermore, such trends and challenges will not emerge in the same manner in different contexts. The discussion in this chapter is illustrated with examples from a UK context but the implications of the trends and challenges are such that they reach beyond borders.

High accuracy android malware detection using ensemble learning

With over 50 billion downloads and more than 1.3 million apps in Google’s official market, Android has continued to gain popularity amongst smartphone users worldwide. At the same time there has been a rise in malware targeting the platform, with more recent strains employing highly sophisticated detection avoidance techniques. As traditional signature based methods become less potent in detecting unknown malware, alternatives are needed for timely zero-day discovery. Thus this paper proposes an approach that utilizes ensemble learning for Android malware detection. It combines advantages of static analysis with the efficiency and performance of ensemble machine learning to improve Android malware detection accuracy. The machine learning models are built using a large repository of malware samples and benign apps from a leading antivirus vendor. Experimental results and analysis presented shows that the proposed method which uses a large feature space to leverage the power of ensemble learning is capable of 97.3 % to 99% detection accuracy with very low false positive rates.

A Proposed Framework for Simulation Based Learning of Inheritance

Different types of serious games have been used in elucidating computer science areas such as computer games, mobile games, Lego-based games, virtual worlds and webbased games. Different evaluation techniques have been conducted like questionnaires, interviews, discussions and tests. Simulation have been widely used in computer science as a motivational and interactive learning tool. This paper aims to evaluate the possibility of successful implementation of simulation in computer programming modules. A framework is proposed to measure the impact of serious games on enhancing students understanding of key computer science concepts. Experiments will be held on the EEECS of Queen’s University Belfast students to test the framework and attain results.