Looking to the future: M-learning with the iPad

Might Apple’s new iPad gain unprecedented traction in education, or is just another example of the over-hyping of new devices in a time of technological determinism (Postman, 2000)? This paper explores the potential affordances and limitations of the Apple iPad in the wider context of emergent mobile learning theory, and the social and economic drivers that fuel technology development. Against the background of effective teaching and learning, the functionality offered by the iPad, and its potential uses for learning, are discussed. A critical review of the way the iPad may support learning, that draws on learning theory, contemporary articles and e-learning literature, suggests that the device may offer an exciting platform for consuming and creating content in a collaborative, interactive way. However, of greater importance is that effective, evidence-driven, innovative practices, combined with a clear-sighted assessment of the advantages and limitations of any product, should take priority over the device itself

Case Study-Based Approach of Quantum Machine Learning in Cybersecurity: Quantum Support Vector Machine for Malware Classification and Protection

Quantum machine learning (QML) is an emerging field of research that leverages quantum computing to improve the classical machine learning approach to solve complex real world problems. QML has the potential to address cybersecurity related challenges. Considering the novelty and complex architecture of QML, resources are not yet explicitly available that can pave cybersecurity learners to instill efficient knowledge of this emerging technology. In this research, we design and develop QML-based ten learning modules covering various cybersecurity topics by adopting student centering case-study based learning approach. We apply one subtopic of QML on a cybersecurity topic comprised of pre-lab, lab, and post-lab activities towards providing learners with hands-on QML experiences in solving real-world security problems. In order to engage and motivate students in a learning environment that encourages all students to learn, pre-lab offers a brief introduction to both the QML subtopic and cybersecurity problem. In this paper, we utilize quantum support vector machine (QSVM) for malware classification and protection where we use open source Pennylane QML framework on the drebin215 dataset. We demonstrate our QSVM model and achieve an accuracy of 95% in malware classification and protection. We will develop all the modules and introduce them to the cybersecurity community in the coming days

Evaluation of emerging screening technologies for the on-site detection and identification of methamphetamine and its precursors in simulated clandestine lab operations

Stimulant drugs comprise one of the top drug categories abused in the United States. Due to its accessibility, low price, and manufacturing simplicity, methamphetamine is frequently placed within the top 10 seized drugs in the country. As of March 2023, methamphetamine is the most seized controlled substance in the United States, with 34,291 kg. In 2022, the United States seized over 79,000 kg of methamphetamine. One reason for the proliferation of methamphetamine is related to the production itself, which does not require large warehouses but can be manufactured in houses using relatively accessible materials and small containers. When a clandestine laboratory is investigated, law enforcement and CSIs must be able to identify what drug is being produced and what hazards are associated with the production method being utilized by the clandestine laboratory. Due to shifting manufacturing routes by underground chemists, it has become difficult for forensic scientists to identify illicit substances and their respective precursors reliably. Indeed, rapid analytical tools that facilitate the identification of legal and scheduled drugs are highly desirable for first responders, health personnel, and forensic chemists. This thesis addresses this deficit by investigating Raman Spectroscopy and Direct Analysis in Real-Time Mass Spectrometry (DART-MS) to determine ways to improve mixture identification. This research focuses on methamphetamine and its precursors, ephedrine, and pseudoephedrine. However, the scope was expanded to include several other drugs and cutting agents of concern in the United States. This research compared three Portable Raman instrumentations for detecting methamphetamine and its precursors in binary mixtures. From a practical perspective, the TacticID GP from B&W Tek (Newark, DE) and the Mira XTR DS from Metrohm USA (Riverview, FL) were determined to be suitable for on-site detection due to their simple operation and color-coded results that provide immediate safety information for the results, in case the user is not familiar with the compound. The mixture analysis function allowed for better identification of the controlled substance due to the controlled substance being the minor component in most cases. The iRaman Prime from B&W Tek (Newark, DE) had limitations for the mixtures. Software used to compare the collected spectrum to the library does not include the mixture analysis function to help identify complex samples. There are other software present; however, the software requires an additional understanding of statistical analysis that first responders may not be equipped with. This research also sought to improve Raman’s detection of mixtures using machine learning, specifically convolutional neural networks or CNN. The iRaman Prime from B&W Tek (Newark, DE) was used for this purpose, which had the most difficulty identifying mixtures due to the built-in software available. Using CNN, the ability to identify both components in the mixtures improved to 94.0 % compared to 71.5 % using cosine similarity. However, the algorithm had difficulty identifying the drugs and adulterants in the authentic samples. The difficulty is because the authentic samples consisted of more complex samples, with more than two compounds present. Further research can be done to train the algorithm with more complex samples or include the class of compounds to give an overall result for compounds not in the training set. Lastly, the utility of DART-MS was investigated for methamphetamines. The Data Interpretation Tool (DIT) v. 2 from NIJ/NIST was used to see how well DART-MS could identify multiple components in mixtures. Authentic samples from the Maryland State Police Forensic Sciences Division were used as more complex samples to compare these instruments with more realistic ones. The DIT and DART-MS identified 82.5 % of the binary mixtures. The DIT also successfully identified at least one controlled substance in the samples containing controlled substances. This thesis demonstrates that the combination of Raman Spectroscopy with CNN and DART-MS with DIT improves their respective instrument\u27s ability to detect mixtures, making them better equipped for use in clandestine operations and regular forensic casework

Mobile technologies for (English) language learning: An exploration in the context of Bangladesh

Milton’s (2002) literature review of languages, technology and learning found that language laboratories “…proved to be a useful tool, but only one tool, in the hands of a good teacher, and a huge waste of time and money in the hands of a bad teacher” (p16) with computer language labs being “..something of an oddity… [with] no clear method or best practice for using them’ (p17). Instead, Milton identified numerous examples of effective language learning supported by broadcast (radio) or recorded (tape, CD) audio. Recently, research has begun to focus upon mobile learning (e.g. Naismith et al, 2004), but the potential of mobile media players (for example, the iPod) is only recently being explored. It has been suggested that language learning is one of the disciplines particularly likely to benefit from widespread ownership of mobile devices such as phones and media players (Kukulska-Hulme, 2006). For example, Rosell-Aguilar (2007) has begun to develop a theoretically informed pedagogy of podcasting, as a means of providing language-learning resources on mobile devices, suggesting podcasts offer a number of advantages for language learning (p. 479). This paper examines the opportunities for mobile language learning in the context of Bangladesh, where mobile devices are becoming increasingly affordable and ubiquitous. It is hoped that this paper also provides some insights into mobile learning for language education policy makers, distance education institutions and language teachers

KYPO4INDUSTRY: A Testbed for Teaching Cybersecurity of Industrial Control Systems

There are different requirements on cybersecurity of industrial control systems and information technology systems. This fact exacerbates the global issue of hiring cybersecurity employees with relevant skills. In this paper, we present KYPO4INDUSTRY training facility and a course syllabus for beginner and intermediate computer science students to learn cybersecurity in a simulated industrial environment. The training facility is built using open-source hardware and software and provides reconfigurable modules of industrial control systems. The course uses a flipped classroom format with hands-on projects: the students create educational games that replicate real cyber attacks. Throughout the semester, they learn to understand the risks and gain capabilities to respond to cyber attacks that target industrial control systems. Our described experience from the design of the testbed and its usage can help any educator interested in teaching cybersecurity of cyber-physical systems

AN ETHNOHISTORICAL EXPLORATION OF EDUCATIONAL TECHNOLOGY IMPLEMENTATION IN METROPOLITAN OMAHA AREA PUBLIC SCHOOLS: ONE LEADERSHIP PERSPECTIVE

An Ethnohistorical Exploration of Educational Technology Implementation in Metropolitan Omaha Area Public Schools is a written account of the evolution of 1:1 program in five public school districts. These metropolitan Omaha area districts share their journey in developing programs that provide equity in accessing educational technology to all students. An annotated history of educational technology and the International Society for Technology in Education (ISTE) standards and their effect on education and educators is also addressed

Horizon Report Europe - 2014 Schools Edition

The NMC Horizon Project from the New Media Consortium is a long-term investigation launched in 2002 that identifies and describes emerging technologies likely to have a large impact over the coming five years in education around the globe. The NMC Horizon Report Europe: 2014 Schools Edition, the first of its kind for Europe, examines six key trends, six significant challenges and six important developments in educational technology that are very likely to impact educational change processes in European schools over the next five years (2014-2018). The topics within each section were carefully selected by the Horizon Project Europe Expert Panel, a body of 53 experts in European education, technology, and other fields. They come from 22 European countries, as well as international organisations and European networks. Throughout the report, references and links are made to more than 150 European publications (reports, articles, policy documents, blog posts etc.), projects (both EU-funded and national initiatives) and various policy initiatives from all over Europe. The Creative Classrooms multidimensional framework, developed by European Commission’s JRC-IPTS on behalf of DG EAC, was used for analysing the trends, challenges and technologies impacting European schools over the next five years. The analysis reveals that a systemic approach is needed for integrating new technologies in European schools and impacting educational change over the next five years.JRC.J.3-Information Societ