Knowledge Community: A Knowledge-Building System for Global Collaborative Project Learning

The wave of a knowledge economy drives today's education to equip students with knowledge building abilities. While collaborative learning has been proven to be an effective constructivist pedagogy, it is difficult to elicit, coordinate, and capture the corresponding knowledge construction process. The situation becomes more challenging when learning is conducted in a distributed environment in which the participants are scattered in different geographical locations. In this paper, we depict the theories, architecture, applications, and analysis of a Web-based computer-supported collaborative learning and knowledge-building system called Knowledge Community (KC), which currently serves a series of 3I (interdisciplinary, interschool, and international) Project Learning activities with more than 10 000 students and teachers participating globally. We also describe the corresponding 3I Project Learning model, a novel technology-enabled pedagogy in which learners perform collaborative, comparative study projects with peers from other countries. Technologically, KC is the use of Web technologies to provide a collaborative learning environment. Pedagogically, KC with its embedded learning theories has created a new learning culture that meets the demands of knowledge economy.     

The Use of Active Methodologies for Teaching–Learning Systems in Telecommunications

This article discusses the adoption of the Problem Based Learning (PBL) and Project Based Learning (P2BL) approaches in the teaching/learning process of telecommunications. A computational environment was defined to combine these two approaches which focused on the teaching of courses that cover topics related to telecommunications systems. Newly graduated professionals face difficulties when entering the job market, as they have to deal with situations that are not experienced in the academic world. There is still a tendency to rely on traditional approaches for the teaching of telecommunications systems that have proved to be inefficient, as they are only concerned with content and not the applications that the student will require in the job market. The aim of this research is to investigate whether the adoption of PBL and P2BL in a computational environment can enhance student learning more effectively than the traditional teaching approach. This involved conducting an experiment in 7 undergraduate classes to compare the performance of the students that adopted PBL and P2BL with that of the students who were taught with the traditional approach. Data were collected on the grades obtained by the students in the courses and these were statistically analyzed. The results show that the adoption of PBL and P2BL led to the students achieving a 32% increase in performance. However, it was noted that the infrastructure of the institutions directly influences the way the approaches are adopted and, hence affects, the results.

     

Organisation of e-learning in a pervasive campus — a case study

Pervasive learning as key technology for tomorrow’s learning will enhance and modernise education — not just in academic teaching. Pervasive learning can be regarded as the latest evolutionof e-learning made possible through recent highly mobile techniques. Through the use of pervasive computing and the use of omnipresent technologies, the presence of these technologies is becoming less conspicuous. Such development leads towards a new organisation of the whole learning environment, called a pervasive campus. This further advances mobile learning for an effectively organised blended learning. In this paper, we propose an architecture with related components and services that facilitates the implementation of pervasive campus applications in dynamic and complex environments, such as those encountered in pervasive communities. We describe scalable, efficient (just-in-time) techniques for the synergistic integration of services into a pervasive campus.     

A Robust User Authentication Scheme Using Dynamic Identity in Wireless Sensor Networks

In modern, wireless sensor networks (WSNs) stand for the next evolutionary and innovative development step in utilities, industrial, building, home, shipboard, and transportation systems automation. The feature of WSNs is easy to deploy and has wide range of applications. Therefore, in distributed and unattended locations, WSNs are deployed to allow a legitimated user to login to the network and access data. Consequently, the authentication between users and sensor nodes has become one of the important security issues. In 2009, M. L. Das proposed a two-factor authentication for WSNs. Based on one-way hash function and exclusive-OR operation, the scheme is well-suited for resource constrained environments. Later, Khan and Algahathbar pointed out the flaws and vulnerabilities of Das’s scheme and proposed an alternative scheme. However, Vaidya et al. found that both Das’s and Khan–Algahathbar’s schemes are vulnerable to various attacks including stolen smart card attacks. Further, Vaidya et al. proposed an improved two-factor user authentication to overcome the security weakness of both schemes. In this paper, we show that Vaidya et al.’s scheme still exposes to a malicious insider attack that seriously threatens the security of WSNs. Furthermore, we propose an improve scheme that mends those vulnerabilities.     

E—Learning系统的个性化推荐方法研究

以E—Learning系统建设为背景,通过采用文献查找、调查研究等方法探讨个性化推荐理论的内涵,并结合当前建设中的E—Learning系统,分析了目前常用的个性化推荐策略,并进行介绍比较和分析以后,总结经验,以应用于E—Learning系统的建设。提出适合于E—learning系统建设的个性化推荐策略：采用关联规则推荐策略和协同过滤技术,基于WEB技术建立一个虚拟学习系统,利用推荐算法,结合用户需求,将学习的资源、学习活动和学习策略进行整合,向用户推荐完整的满足用户需求的E—Learning学习方案。     

基于PBL的单片机原理课程教学改革探索

PBL教学法是一种以问题为基础,学生自主讨论和学习的教学方法。通过在单片机原理课程中进行PBL教学法尝试,提出了PBL教学法的具体应用措施和教学效果。最后分析了PBL教学法的不足和改进办法。     

The security-based optimization algorithm for enhancing the energy efficiency of wireless sensor networks

In the upcoming era, one of the emergent technologies is “Wireless Sensor Networks (WSNs),” which has provided various solutions in the field of defense, surveillance, and so on. But the main problems in the WSNs are security and energy-efficient routing to the researchers. The deployment of security algorithms can monitor only the unauthorized signals to ensure security, but it lacks and leads to higher energy consumption, whereas the deployment of energy-efficient routing algorithms is used only for the selection of routing paths, but it fails to ensure security. Hence, the main intent of this research work is to solve both problems by the following proposed models. Model 1 is “Identity-Based Aggregate Signatures (IBAS)” that is the most effective security-based framework protocol in this research work. Model 2 is the integration of IBAS and “Fuzzy Logic System (FLS)” that acts as an energy-efficient algorithm, and here, FLS is used to find the optimal path from source to destination to transmit the data. Model 3 is the combination of IBAS and the “Whale Optimization Algorithm (WOA)” for higher energy efficiency and auto localization by analyzing the entire route in WSN. Model 4 is the combination of IBAS, WOA, and the “Reinforcement Theory of WOA (RTWOA)” energy-efficiency model with a twofold and weight factor strategy for better speed and accuracy. These models ensure security, energy efficiency, and auto localization. The simulation parameters such as “Energy Efficiency,” “Packet Delivery Ratio,” “Average delay,” “Throughput,” and “Energy Consumption” are evaluated, and results show that the performance of energy efficiency and security is higher in Model 4 when compared to the other three models.     

“智能控制”课程中模糊控制PBL教学研究

基于项目的学习(PBL)是一种以学生为中心的教学模式。本文在“智能控制”课程教学中引入PBL教学模式,以寻迹小车仿真为例设计了PBL模糊控制教学案例,探讨了开展PBL案例教学的设计步骤与实施方法。教学实践表明,PBL教学模式可以增强学生的学习兴趣,促进学生提升自主学习能力,实现强化团队协作和创新能力的培养目标。     

IoTFLiP: IoT-based flipped learning platform for medical education

Case-Based Learning (CBL) has become an effective pedagogy for student-centered learning in medical education, which is founded on persistent patient cases. Flippped learning and Internet of Things (IoTs) concepts have gained significant attention in recent years. Using these concepts in conjunction with CBL can improve learning ability by providing real evolutionary medical cases. It also enables students to build confidence in their decision making, and efficiently enhances teamwork in the learing environment. We propose an IoT-based Flip Learning Platform, called IoTFLiP, where an IoT infrastructure is exploited to support flipped case-based learning in a cloud environment with state of the art security and privacy measures for personalized medical data. It also provides support for application delivery in private, public, and hybrid approaches. The proposed platform is an extension of our Interactive Case-Based Flipped Learning Tool (ICBFLT), which has been developed based on current CBL practices. ICBFLT formulates summaries of CBL cases through synergy between students' and medical expert knowledge. The low cost and reduced size of sensor device, support of IoTs, and recent flipped learning advancements can enhance medical students' academic and practical experiences. In order to demonstrate a working scenario for the proposed IoTFLiP platform, real-time data from IoTs gadgets is collected to generate a real-world case for a medical student using ICBFLT.     

PBL教学法在“数字电子技术基础”中的应用

基于问题的教学方法(Problem-Based Learning,PBL)以学生为主体、以问题为中心,是适应工程教育专业认证和改革人才培养模式的重要手段。本文以“数字电子技术基础”课程的组合逻辑电路设计授课过程为例,介绍了PBL教学法的主要实施过程。通过问题设定、设计实施、学生分组、任务分析、教师引导、讨论改进、成果展示、综合评价等环节,引导学生进入真实的问题情境,利用解决问题作为学生获取新知识的起始点。PBL教学法的实施有助于提升学生自主学习、分析解决问题、团结协作等方面的综合素养。     

面向物联网的无线传感器网络综述

在分析无线传感器网络国内外研究现状及技术成熟度的基础上,从技术层面阐述了无线传感器网络与物联网之间的相互关系,总结了无线传感器网络系统执行所需要的信息采集系统设计、网络服务支持和网络通信协议设计等关键技术,说明了无线传感器网络未来发展所面临的挑战,并提出了面向物联网的无线传感器网络发展新思路。     

Diagnosis of learner dropout based on learning styles for online distance learning

The amount of data generated by computer systems in Online Distance Learning (ODL) contains rich information. One example of this information we define as the Learner Learning Trail (LLT), which is the sequence of interactions between the students and the virtual environment. Another example is the Learner Learning Style (LLS), which is associated with the student behavior and choices during the learning process. This information can be used to identify learner behavior and learning style. We perceived, after the study of related literature, that the research field of learner diagnosis for ODL does not apply the conjoint use of LLT and LLS. In this article, we propose a model capable of integrating data generated from the behavior of students in ODL with cognitive aspects of them, such as their Learning Styles, by crossing LLT with LLS. We also propose the CPAD method (Collect, Preprocessing, Analysis, Diagnosis), which is implemented by collecting the raw data regarding learning activities, preprocessing the data into structured time sequences, analyzing the sequences regarding the learning styles and using this analysis to diagnose the learner behavior. We selected the dropout to investigate, once the dropout rate in ODL is a real problem in universities around the world. In addition, the dropout is a student decision which can be associated with previous students behaviors. We performed a study with 202 learners to evaluate if learning styles are capable of explaining aspects of the student behavior. The results suggest that Sequential/Global learning style dimension is more capable of explaining the dropout than the other dimensions. Also, we performed four classification experiments to verify how the dimensions of Felder-Silverman Learning Style Model influence the learner diagnosis. We perceived that the Sequential/Global dimension could provide a higher accuracy average with lower variation independently of the diagnosis technique.     

网络攻防——魔和道的持久对峙

通过对当今信息化时代的特征分析,给出了信息安全建设的大背景。。对网络攻击技术的演进和形式变化进行了解析,对新时期下主要网络攻击技术进行了剖析,在此基础上,提出了国家、企业在信息安全保障工作方面应考虑的新对策和新技术。     

“数字电子技术基础”MOOC设计与应用

采用线上线下混合教学模式已经成为提升教学质量的必要手段。2021年3月数字电子技术基础在中国大学MOOC平台上线,基于项目教学法,重构知识体系,以4个精心设计的、循序渐进的、侧重不同知识点的、具有代表性的项目为课程脉络主线,讲解过程中广泛采用对比教学法、层次教学法、错误引导法,逐步引领学生建构知识体系。本MOOC课程可有效缓解学时不断减少与挑战度要求不断提高之间的矛盾。     

An enhanced wireless sensor network localization scheme for radio irregularity models using hybrid fuzzy deep extreme learning machines

Localization is one of the key challenges facing wireless sensor networks (WSNs), particularly in the absence of global positioning equipment such as GPS. However, equipping WSNs with GPS sensors entails the additional costs of hardware logic and increased power consumption, thereby lowering the lifetime of the sensor, which is normally operated on a non-rechargeable battery. Range-free-based localization schemes have shown promise compared to range-based approaches as preferred and cost-effective solutions. Typical range-free localization algorithms have a key advantage: simplicity. However, their precision must be improved, especially under varying node densities, sensing coverage conditions, and topology diversity. Thus, this work investigates the probable integration of two soft-computing techniques, namely, Fuzzy Logic (FL) and Extreme Learning Machines (ELMs), with the goal of enhancing the approximate localization precision while considering the above factors. In stark contrast to ELMs, FL methods yield high accuracy under low node density and limited coverage conditions. In addition, as a hybrid scheme, extra steps are integrated to compensate for the effects of irregular topology (i.e., noisy signal density due to obstacles). Signal and weight are normalized during the fuzzy states, while the ELM uses a deep learning concept to adjust the signal coverage, including the spring force error estimation enhancement. The performance of our hybrid scheme is evaluated via simulations that demonstrate the scheme’s effectiveness compared with other soft-computing-based range-free localization schemes.     

A survey on communication and data management issues in mobile sensor networks

Wireless sensor networks (WSNs) which is proposed in the late 1990s have received unprecedented attention, because of their exciting potential applications in military, industrial, and civilian areas (e.g., environmental and habitat monitoring). Although WSNs have become more and more prospective in human life with the development of hardware and communication technologies, there are some natural limitations of WSNs (e.g., network connectivity, network lifetime) due to the static network style in WSNs. Moreover, more and more application scenarios require the sensors in WSNs to be mobile rather than static so as to make traditional applications in WSNs become smarter and enable some new applications. All this induce the mobile wireless sensor networks (MWSNs) which can greatly promote the development and application of WSNs. However, to the best of our knowledge, there is not a comprehensive survey about the communication and data management issues in MWSNs. In this paper,focusing on researching the communication issues and data management issues in MWSNs, we discuss different research methods regarding communication and data management in MWSNs and propose some further open research areas in MWSNs.Copyright © 2011 John Wiley & Sons, Ltd.     

Can COVID-19 pandemic influence experience response in mobile learning?

The mass spreading of COVID-19 has changed the paradigm of the education industry. In China and many other nations, universities have introduced compulsory remote education programs such as mobile learning (m-learning) to prevent public health hazards caused by the pandemic. However, so far, there is still a lack of understanding of student’s learning experience responses in compulsory m-learning programs. As such, there is a necessity to explore the factors and mechanisms which drives students’ experience. This paper evaluates the influence of both pedagogy and technology on learner’s compulsory m-learning experience response (ER) by extending the mobile technology acceptance model (MTAM) during the COVID-19 pandemic. An online self-administered questionnaire was used to collect the data, which was then analysed through SmartPLS 3.2.9. Importance-performance matrix analysis was applied as a post-hoc procedure to gauge the importance and performance of the exogenous constructs. The results revealed that perceptions of m-learning’s learning content quality, user interface, and system’s connectivity affect the perceived mobile usefulness and easiness which in turn affects ER. This paper validates MTAM in the field of education by integrating MTAM with pedagogy and technology attributes under a social emergency setting such as the COVID-19 pandemic. In addition, the current research explains users' ER rather than behaviour intention which is commonly adopted in past studies.     

An efficient UE cluster head selection algorithm in wireless sensor networks and cellular networks

Wireless Sensor Networks (WSNs) have been applied in many different areas. Energy efficient algorithms and protocols have become one of the most challenging issues for WSN. Many researchers focused on developing energy efficient clustering algorithms for WSN, but less research has been concerned in the mobile User Equipment (UE) acting as a Cluster Head (CH) for data transmission between cellular networks and WSNs. In this paper, we propose a cellular-assisted UE CH selection algorithm for the WSN, which considers several parameters to choose the optimal UE gateway CH. We analyze the energy cost of data transmission from a sensor node to the next node or gateway and calculate the whole system energy cost for a WSN. Simulation results show that better system performance, in terms of system energy cost and WSNs life time, can be achieved by using interactive optimization with cellular networks.     

Integrating a mobile health applications for self-management to enhance Telecare system

A dramatic global increase in the pervasiveness of chronic illness has coincided with a reduction in the availability of healthcare resources, coupled with increased costs for care, forcing a fundamental reevaluation of care processes. These trends have driven interest in the use of advanced healthcare information systems and telematics applications to improve care availability while reducing overall costs, but such measures require taking an integrated approach to a range of interrelated social, economic, political and cultural impacts and challenges. Telecare technologies allow hospitals to continuously monitor biomedical indicators, while providing patients with online services such as clinical appointment scheduling, medical consulting, remote alerts, etc. Telecare has the potential to transform the healthcare industry by reducing costs, increasing quality, and enhancing patient satisfaction. The development of a real-time monitoring healthcare service model through the integration of information and communications technologies (ICT) has emerged as a research priority. This study explores the design, value creation, development and evaluation of Telecare systems and mobile health applications for autonomous health management to ensure appropriate home-based health monitoring and treatment while improving care performance. A well-defined methodology is needed to develop artifacts due to increasing disease complexity. This study develops an Android-based self-management application based on design science research methodology. The App assists users in collecting and monitoring indicators to prompt appropriate care services. This study uses individual home self-care as the basic Telecare unit to design a service model integrating six kinds of healthcare services. Usability testing is conducted to reflect five constructs: system usefulness, ease of learning, information quality, interface quality, and overall satisfaction. Experimental results support previous research findings regarding the Chronic Care Model and enhance the effectiveness of mobile-based services. Our work provides a useful reference to researchers and practitioners interested in understanding how hospitals can better facilitate more effective mobile-based technology adoption in today’s e-health environment.     

MEMIS: A Mobile-Supported English-Medium Instruction System

Education is one of the most important elements in our lives, as it provides a direct gain in knowledge. Thus, in order to provide better academic achievement, more and more instructors are adapting collaborative learning to their classes. However, two major problems lurk behind collaborative learning. First, it is difficult to apply collaborative learning because students tend to engage passively with traditional lectures. As a result, interactive technologies such as clickers have been applied to increase interactive learning and raise the rate of interaction. Nevertheless, these interactive technologies still have some limitations, such as limited mobility, high costs, setup issues, technical difficulties, and little support of higher-order thinking skills. Second, recently there has been an increasing number of EMI (English as Medium of Instruction) courses added to university course offerings in countries where English is not the first language. The goal of these courses is to support university internationalization and address the global status of English. However, it is even harder to achieve in-class interaction in large EMI lecture courses. In addition, some studies argue that EMI courses might affect the overall learning of course content because of students’ poor lecture comprehension and passive engagement in class.In order to address the limitations of interactive technologies, encourage more collaborative learning, facilitate greater in-class interaction in large lecture courses, and resolve students’ poor lecture comprehension in EMI courses, the author introduces MEMIS (Mobile-Supported English-Medium Instruction System), which includes both a T&S (Teachers & Students) mobile app and an EMI pedagogical method. The author first provides detailed implementation and all the features of the T&S mobile app, which improves students’ perceptions of classroom participation and in-class interaction. Then the author explains how she develops her EMI pedagogy such that it utilizes the features of the T&S mobile app to: 1) increase students’ overall learning in her EMI course, 2) develop students’ construction of knowledge and higher-order thinking, and 3) achieve all six cognitive processes from Bloom’s revised taxonomy. The author adapts a quasi-experimental design, statistically analyzes the effectiveness of both exam scores and final grades between a control group and an experimental group, and then asks students to evaluate their experiences and provide feedback about MEMIS. Based on both statistical results and students’ overall feedback, the author confirms that MEMIS is an effective approach that improves lecture comprehension, encourages more class engagement, promotes collaborative learning, and achieves better learning outcomes.