This post is about the new Google Trends Tutorials YouTube series. In these videos you'll learn how to use Google Trends to analyze patterns in Google Search and Youtube searches, and use them to create interesting content online.

This paper systematically discusses the security and privacy concerns for e-learning systems. A five-layer architecture of e-learning system is proposed. The security and privacy concerns are addressed respectively for five layers. This paper further examines the relationship among the security and privacy policy, the available security and privacy technology, and the degree of e-learning privacy and security. The digital identity attributes are introduced to e-learning portable devices to enhance the security and privacy of e-learning systems. This will provide significant contributions to the knowledge of e-learning security and privacy research communities and will generate more research interests.

With the emergence of the Web 2.0 phenomena, technology-assisted social networking has become the norm. The potential of social software for collaborative learning purposes is clear, but as yet there is little evidence of realisation of the benefits. In this paper we consider Information and Communication Technology student attitudes to collaboration and via two case studies the extent to which they exploit the use of wikis for group collaboration. Even when directed to use a particular wiki designed for the type of project they are involved with, we found that groups utilized the wiki in different ways according to the affordances ascribed to the wiki. We propose that the integration of activity theory with an affordances perspective may lead to improved technology, specifically Web 2.0, assisted collaboration.

Computer Supported Collaborative Learning could highly impact education around the world if the proper Collaborative Learning tools are set in place. In this paper we describe the design of a collaborative learning activity for teaching Chemistry to Chilean students. We describe a PDA-based software tool that allows teachers to create workgroups in their classrooms in order to work on the activity. The developed software tool has three modules: one module for teachers, which runs on a PC and lets them create the required pedagogical material; second, there is a PDA module for students which lets them execute the activity; finally, a third module allows the teacher set workgroups and monitor each workgroup during the activity.

Responsive open learning environments (ROLEs) are the next generation of personal learning environments (PLEs). While PLEs rely on the simple aggregation of existing content and services mainly using Web 2.0 technologies, ROLEs are transforming lifelong learning by introducing a new infrastructure on a global scale while dealing with existing learning management systems, institutions, and technologies. The requirements engineering process in highly populated test-beds is as important as the technology development. In this paper, we will describe first experiences deploying ROLEs at two higher learning institutions in very different cultural settings. The Shanghai Jiao Tong University in China and at the “Center for Learning and Knowledge Management and Department of Information Management in Mechanical Engineering” (ZLW/IMA) at RWTH Aachen University have exposed ROLEs to theirs students in already established courses. The results demonstrated to readiness of the technology for large-scale trials and the benefits for the students leading to new insights in the design of ROLEs also for more informal learning situations.

The paper explores the application of Web 2.0 technologies to support product development efforts in a global, virtual and cross-functional setting. It analyses the dichotomy between the prevailing hierarchical structure of CAD/PLM/PDM systems and the principles of the Social Web under the light of the emerging product development trends. Further it introduces the concept of Engineering 2.0, intended as a more bottom up and lightweight knowledge sharing approach to support early stage design decisions within virtual and cross-functional product development teams. The lessons learned collected from a cross-company study highlight how to further developblogs, wikis, forums and tags for the benefit of new product development teams, highlighting opportunities, challenges and no-go areas.

Improving website structures is the main task of a website designer. In recent years, numerous web engineering researchers have investigated navigation recommendation systems. Page recommendation systems are critical for mobile website navigation. Accordingly, we propose a smart and adaptive navigation recommendation system based on reinforcement learning. In this system, user navigation history is used as the input for reinforcement learning model. The model calculates a surf value for each page of the website; this value is used to rank the pages. On the basis of this ranking, the website structure is modified to shorten the user navigation path length. Experiments were conducted to evaluate the performance of the proposed system. The results revealed that user navigation paths could be decreased by up to 50% with training on 12 months of data, indicating that users could more easily find a target web page with the help of the proposed adaptive navigation recommendation system.

Image forgery detection techniques refer to the process of detecting manipulated or altered images, which can be used for various purposes, including malicious intent or misinformation. Image forgery detection is a crucial task in digital image forensics, where researchers have developed various techniques to detect image forgery. These techniques can be broadly categorised into active, passive, machine learning-based and hybrid. Active approaches involve embedding digital watermarks or signatures into the image during the creation process, which can later be used to detect any tampering. On the other hand, passive approaches rely on analysing the statistical properties of the image to detect any inconsistencies or irregularities that may indicate forgery. In this paper for the detection of scaling and cropping attack a deep learning method has been proposed using ResNet. The proposed method (Res-Net-Adam-Adam) is able to achieve highest amount of accuracy of 99.14% (0.9914) while detecting fake and real images.

The confluence of the internet of things (IoT) with smart grids has ushered in a paradigm shift in energy management, promising unparalleled efficiency, economic robustness and unwavering reliability. However, this integrative evolution has concurrently amplified the grid's susceptibility to cyber intrusions, casting shadows on its foundational security and structural integrity. Machine learning (ML) and deep learning (DL) emerge as beacons in this landscape, offering robust methodologies to navigate the intricate cybersecurity labyrinth of IoT-infused smart grids. While ML excels at sifting through voluminous data to identify and classify looming threats, DL delves deeper, crafting sophisticated models equipped to counteract avant-garde cyber offensives. Both of these techniques are united in their objective of leveraging intricate data patterns to provide real-time, actionable security intelligence. Yet, despite the revolutionary potential of ML and DL, the battle against the ceaselessly morphing cyber threat landscape is relentless. The pursuit of an impervious smart grid continues to be a collective odyssey. In this review, we embark on a scholarly exploration of ML and DL's indispensable contributions to enhancing cybersecurity in IoT-centric smart grids. We meticulously dissect predominant cyber threats, critically assess extant security paradigms, and spotlight research frontiers yearning for deeper inquiry and innovation.

Drawing on the MOA framework, this study establishes a research model that explains the usage intention of robo-advisors. In the model, three predictors that consist of technology relative advantage, technology herding, and technology familiarity influence usage intention of robo-advisors directly and indirectly via the partial mediation of trust. At the same time, the effects of the three predictors on trust are hypothetically moderated by learning goal orientation and perceived performance risk respectively. Statistical analyses are provided using the data of working professionals from the insurance industry in Taiwan. Based on its empirical findings, this study discusses important theoretical and practical implications.

Aiming at the problem of aggravation of traffic congestion caused by unstable signal control of traffic signal control system, the Multi-Agent Deep Deterministic Policy Gradient-based Traffic Cyclic Signal (MADDPG-TCS) control algorithm is used to control the time and data dimensions of the signal control scheme. The results show that the maximum vehicle delay time and vehicle queue length of the proposed algorithm are 11.33 s and 27.18 m, which are lower than those of the traditional control methods. Therefore, this method can effectively reduce the delay of traffic signal control and improve the stability of signal control.

Physical Layer Security (PLS) and relay technology have emerged as viable methods for enhancing the security of wireless networks. Relay technology adoption enhances the extent of coverage and enhances dependability. Moreover, it can improve the PLS. Choosing relay and jammer nodes from the group of intermediate nodes effectively mitigates the presence of powerful eavesdroppers. Current methods for Joint Relay and Jammer Selection (JRJS) address the optimisation problem of achieving near-optimal secrecy. However, most of these techniques are not scalable for large networks due to their computational cost. Secrecy will decrease if eavesdroppers are aware of the relay and jammer intermediary nodes because beamforming can be used to counter the jammer. Consequently, this study introduces a multi-agent Q-learning-based PLS-enhanced secured joint relay and jammer in dual-hop wireless cooperative networks, considering the existence of several eavesdroppers. The performance of the suggested algorithm is evaluated in comparison to the current algorithms for secure node selection. The simulation results verified the superiority of the proposed algorithm.

To achieve psychological and emotional analysis of massive internet chats, researchers have used statistical methods, machine learning, and neural networks to analyse the dynamic tendencies of texts dynamically. For long readers, the author first compares and explores the differences between the two psychoanalysis algorithms based on the emotion dictionary and machine learning for simple sentences, then studies the expansion algorithm of the emotion dictionary, and finally proposes an extended text psychoanalysis algorithm based on conditional random field. According to the experimental results, the mental dictionary's accuracy, recall, and F-score based on the cognitive understanding of each additional ten words were calculated. The optimisation decreased, and the memory and F-score improved. An <i>F</i>-value greater than 1, which is the most effective indicator for evaluating the effectiveness of a mental analysis problem, can better demonstrate that the algorithm is adaptive in the literature dictionary. It has been proven that this scheme can achieve good results in analysing emotional tendencies and has higher efficiency than ordinary weight-based psychological sentiment analysis algorithms.

In order to reduce the challenges encountered by learners and educators in engaging in educational activities, this paper classifies learners' roles in virtual learning communities, and explores the role of behaviour characteristics and their positions in collaborative knowledge construction networks in promoting the process of knowledge construction. This study begins with an analysis of the relationship structure among learners in the virtual learning community and then applies the FCM algorithm to arrange learners into various dimensional combinations and create distinct learning communities. The test results demonstrate that the FCM method performs consistently during the clustering process, with less performance oscillations, and good node aggregation, the ARI value of the model is up to 0.90. It is found that they play an important role in the social interaction of learners' virtual learning community, which plays a certain role in promoting the development of artificial intelligence.

For a long time, high school students have been forced to practice selecting correct answers on college scholastic ability tests. Recently, it has been suggested that schools introduce biomimicry activities for STEM education to develop students' 21st century competency. However, there have been arguments about which system is more appropriate in terms of enhancing a student's competency development. Therefore, we evaluated neurological evidence of students' competency using fMRI scans taken during the selecting a correct answer for a biology question and during a biomimicry activity. Results showed that the repetitive practice of selecting correct responses limited a student's neurological activities to the brain network of the visual cortex and the front-parietal working memory cortex. However, the biomimicry activity simultaneously involved diverse prefrontal, parietal and temporal cortexes, and the putamen, limbic and cerebellum lobes. Therefore, this study proposes that the biomimicry activities could stimulate their coordinated brain development.

The use of blended learning is well suited for classes that involve a high level of experiential inquiry such as internship courses. These courses allow students to combine applied, face-to-face fieldwork activities with a reflective academic component delivered online. Therefore, the purpose of this article is to describe the pedagogical design and implementation of a pilot blended learning format internship course. After implementation, the pilot class was assessed. Results of the survey and focus group revealed high levels of student satisfaction in the areas of course structure, faculty-student interaction, and application of theory to the “real-world” experience undertaken by students during the internship. Lower levels of satisfaction with the course’s academic rigor and a sense of community were also reported. Notably, students with experience in blended learning expressed lower levels of overall satisfaction, but reported higher levels of satisfaction with the course’s rigor and sense of community. The paper concludes by offering implications for instructors seeking to implement blended learning approaches.

Many parents, educators, and policy makers see great potential for leveraging tools like laptop computers, tablets, and smartphones in the classrooms of the world. Although increasing students’ technology access may be associated with increased student achievement, there is little research directly investigating objective measures of student achievement. This study addresses the short-term and long-term quantitative impacts of one of the world’s first school efforts to provide Kindergarten through 3rd grade classrooms with 1:1 iPad access and a range of English Language Arts (ELA) and math Apps. This report summarizes two investigations conducted during this iPad implementation. First, a 9-week pre/post randomized control trial was conducted in which 8 Kindergarten classes used literacy and numeracy apps while another 8 Kindergarten classes used their traditional (non-iPad) resources. At the end of this short implementation period, slightly stronger literacy performance gains were observed in the iPad settings. In a second longitudinal study, three years of assessment data were explored before and after the 1:1 iPad implementation in grades K to 2. Results from the longitudinal study provide emerging evidence of potential increases in ELA achievement, but no consistent results in math achievement. This paper adds to the sparse literature in this area and provides a springboard for further research.

As mobile devices become prevalent, there is always a need for apps.  How hard is it to develop an app especially a cross-platform app? The paper shares an experience in a project involved the development of a student services web app that can be run on cross-platform mobile devices.  The paper first describes the background of the project, the clients, and the proposed solution.  Then, it focuses on the step-by-step development processes and provides the illustration of written codes and techniques used.  The goal is for readers to gain an understanding on how to develop a mobile-friendly web app.  The paper concludes with teaching implications and offers thoughts for further development.  

This research study explores peer teaching and learning without a domain expert teacher, within the context of an activity where teams of second level students (~16 years old) are required to create a learning experience for their peers. The study looks at how participants would like to be taught and how they would teach their peers if given the opportunity and examines the support they require, their motivation levels, and if they actually learn curriculum content using this approach. An exploratory case study methodology was used, and the findings suggest that students want varied learning experiences that include many of the elements which would fall under the heading of 21st century learning, that with some support and encouragement they can create innovative learning experiences for their peers, and that they can learn curriculum content from the process.

Increasingly, numerous universities have identified benefits of flipped learning environments and have been encouraging instructors to adapt such methodologies in their respective classrooms, at a time when departments are facing significant budget constraints. This article proposes an instructional design framework utilized to strategically enhance traditional flipped methodologies in a first-year engineering course, by using low-cost technology aids and proven pedagogical techniques to enhance student learning. Implemented in a first-year engineering course, this modified flipped model demonstrated an improved student awareness of essential engineering concepts and improved academic performance through collaborative and active learning activities, including flipped learning methodologies, without the need for expensive, formal active learning spaces. These findings have been validated through two studies and have shown similar results confirming that student learning is improved by the implementation of multi-pedagogical strategies in-formed by the use of an instructional design in a traditional classroom setting.

Mobile devices are the constant companions of technology users of all ages. Studies show, however, that making calls is a minimal part of our engagement with today’s smart phones and that even texting has fallen off, leaving web browsing, gaming, and social media as top uses. A cross-disciplinary group of faculty at our university came together in the mLearning Scholars group to study the potential for using mobile devices for student learning. The group met bi-weekly throughout a semester and shared thoughts, ideas, resources, and examples, while experimenting with mobile learning activities in individual classes. This paper summarizes student perceptions and adoption intent for using mobile devices for learning, and discusses implementation issues for faculty in adding mobile learning to a college course. Outcomes reflect that mobile learning adoption is not a given, and students need help in using and understanding the value in using personal devices for learning activities.

This paper examines how to leverage the design studio learning environment throughout long-term Digital Design education in order to support students to progress from tactical, well-defined, device-centric routine design, to confidently design sustainable solutions for strategic, complex, problems for a wide range of devices and platforms in the digital space. We present a framework derived from literature on design, creativity, and theories on learning that: (a) implements a theory of formal learning sequences as a user-centered design process in the studio; and (b) describes design challenge progressions in the design studio environment modeled in seven dimensions. The framework can be used as a tool for designing, evaluating, and communicating course progressions within – and between series of – design studio courses. This approach is evaluated by implementing a formal learning sequence framework in a series of design studio courses that progress in an undergraduate design-oriented Informatics program. Reflections from students, teachers, and external clients indicate high student motivation and learning goal achievement, high teacher satisfaction and skill development, and high satisfaction among external clients.

Aim/Purpose: The traditional method of teaching e-safety by lecturing is not very effective. Despite learners often being equipped with the right knowledge, they reject the need to act accordingly. There is a need to improve the way digital e-safety is taught. Background: The study compares four different teaching styles, examining how each affected the way students perceive a range of e-safety keywords and consequently the way they approach this issue. Methodology: The semantic differential technique was used to carry out the research. Students completed a semantic differential questionnaire before and after lessons. A total of 405 first year undergraduates took part in the study. Contribution: The paper contributes to the debate on appropriate methods for teaching e-safety, with an aim to influence learners’ attitudes. Findings: Experience-based learning seems to be very effective, confronting students with an e-safety situation and providing them with a negative experience. This teaching method had the biggest influence on students who were deceived by the prepared e-safety risk situation. Recommendations for Practitioners: E-safety instruction can be enhanced by ensuring that lessons provide students with a personal experience. Recommendation for Researchers: The semantic differential technique can be used to measure changes in learners’ attitudes during the teaching process. Impact on Society: Our findings may bring improvements to the way e-safety topics are taught, which could, in turn, evoke in learners a more positive e-safety attitude and a desire to improve their e-safety behavior. Future Research: More research needs to be carried out to examine how the experiential learning method affects the attitudes of younger learners (primary, middle, and high school students).