scholarly journals تکنولوجیا التدریب الإلکترونی المصغر عبر الویب وأثره على تنمیة الجانب المعرفی والأدائی لکفایات تصمیم استراتیجیات التعلم الإلکترونی لدى معلمی التعلیم الثانوی Micro e-training technology via the web and its impact on development the cognitive and performance aspects of e-learning strategies design competencies

Author(s):  
سهیر حمدى فرج
Author(s):  
Carmel McNaught ◽  
Paul Lam ◽  
Kin-Fai Cheng

The chapter will describe an expert review process used at The Chinese University of Hong Kong. The mechanism used involves a carefully developed evaluation matrix which is used with individual teachers. This matrix records: (1) the Web functions and their use as e-learning strategies in the course Web site; (2) how completely these functions are utilized; and (3) the learning design implied by the way the functions selected are used by the course documentation and gauged from conversations with the teacher. A study of 20 course Web sites in the academic years 2005–06 and 2006–07 shows that the mechanism is practical, beneficial to individual teachers, and provides data of relevance to institutional planning for e-learning.


Author(s):  
Shalin Hai-Jew

Information and visualization imagery conveys data for more effective learning and comprehension, memory retention; analytic tractability; decision-making and information aesthetics. These types of visualization imagery may be built both in simple and complex ways. Complex and live data streams may be collated and delivered via interactive tools delivered via the Web, with some bolstering simulation learning. This chapter addresses the types of visualizations used in e-learning, strategies for creating these, and the ways to avoid unintended and negative learning.


2011 ◽  
pp. 752-778
Author(s):  
Shalin Hai-Jew

Information and visualization imagery conveys data for more effective learning and comprehension, memory retention; analytic tractability; decision-making and information aesthetics. These types of visualization imagery may be built both in simple and complex ways. Complex and live data streams may be collated and delivered via interactive tools delivered via the Web, with some bolstering simulation learning. This chapter addresses the types of visualizations used in e-learning, strategies for creating these, and the ways to avoid unintended and negative learning.


2013 ◽  
Vol 7 (2) ◽  
pp. 574-579 ◽  
Author(s):  
Dr Sunitha Abburu ◽  
G. Suresh Babu

Day by day the volume of information availability in the web is growing significantly. There are several data structures for information available in the web such as structured, semi-structured and unstructured. Majority of information in the web is presented in web pages. The information presented in web pages is semi-structured.  But the information required for a context are scattered in different web documents. It is difficult to analyze the large volumes of semi-structured information presented in the web pages and to make decisions based on the analysis. The current research work proposed a frame work for a system that extracts information from various sources and prepares reports based on the knowledge built from the analysis. This simplifies  data extraction, data consolidation, data analysis and decision making based on the information presented in the web pages.The proposed frame work integrates web crawling, information extraction and data mining technologies for better information analysis that helps in effective decision making.   It enables people and organizations to extract information from various sourses of web and to make an effective analysis on the extracted data for effective decision making.  The proposed frame work is applicable for any application domain. Manufacturing,sales,tourisum,e-learning are various application to menction few.The frame work is implemetnted and tested for the effectiveness of the proposed system and the results are promising.


Author(s):  
Célia Quintas ◽  
Ana Luísa Teixeira ◽  
Isabel Fernandes Silva ◽  
Jane Rodrigues Duarte

Knowledge management and learning are buzzwords in today’s society, both in terms of company competitiveness as well as in terms of education. Human resources are thus a priority for individuals and companies. The concept of knowledge management and of learning organizations has been object of increased interest by managers and scholars. The increased focus on these issues brings forth the individual as a crucial element in this process; individuals become key elements in competitiveness (Nonaka & Takeuchi: 1995) and protagonists of their own learning process (Senge: 1992).Additionally, the learning methodologies and strategies have also changed in the past decades, so that currently much is offered by means of b-learning and e-learning courses that, on the one hand, allow students to opt for several learning strategies, and on the other hand, require them to actively participate in their learning path. In fact, the evolution of ICT in studies and the growing experience of both teachers and students have gradually adapted to new methodologies. However, while materials and subject matter have been made easier and more accessible to students who do not attend classroom sessions, an underlying problem has always been present: bridging the physical distance among all the stakeholders involved in the learning process and all the difficulties that may emerge from this.Since its first edition in 2001, this Post-Graduation Program, now in its 12th edition, has undergone several changes, from its study plan to learning regime. As a means of responding to the demands of today’s market and in particular new learning styles, new possibilities have been made for attending the course which range from classroom, to blending and e-learning formats. As a means of fostering group spirit, synchronous and asynchronous participation of all students several changes were introduced this academic year. Besides the use of the Moodle platform, a Virtual Learning Environment (VLE) wiziq has been introduced.In 2013-14, the program includes students from Portugal (including the Azores), Mexico and Nigeria. Moreover, this Post-Graduation Program allows students to opt for f2f, b-learning and e-learning regimes, i.e., within the same group, some students attend classes by means of a VLE, others attend some classes f2f and others using the VLE and others attend f2f classes regularly, though they also have access to the VLE. A program that combines three learning approaches/methodologies/strategies allows the possibility of assessing possible differences in terms of efficiency of these three learning methodologies, considering that these imply a change in expectations, attitude and cognitive process.Our paper focuses on a study carried out in a Post-Graduation Program at a Portuguese university, on perceived satisfaction regarding the use of ICT tools in the program, a theme which has already been object of study at UAL in recent years, both in terms of assessing and monitoring learning progress, of learner attitude toward their learning paths (Fernandes Silva & Rodrigues Duarte. 2011a & b) and the tools and methodologies made available to them and of perceived satisfaction (Fernandes Silva & Quintas: 2013).This paper corresponds to a 1st stage of a broader study that will involve all students in the referred program in 2013-14 as well as all the lecturers. Initially, a qualitative analysis is carried out based on semi-structured interviews; at a 2nd stage, we aim to create a questionnaire to be applied to a wider population.


Akademika ◽  
2019 ◽  
Vol 8 (01) ◽  
pp. 81-100
Author(s):  
Eva Kristiyani ◽  
Iffah Budiningsih

The aim of this research is to know the influence of e-learning learning strategy and interest in learning to accounting learning result. This research was conducted at SMK Permata Bangsa Kelurahan Jakasetia, South Bekasi Subdistrict, Bekasi City involving 56 samples taken with random sampling technique to the equivalent class. Instrument used in this research is the accounting test and questionnaire interest in student learning; and the data analysis using two-way ANAVA and Tukey Test. The results of this study obtained: (1) there is a significant difference between the learning outcomes of students who are taught with e-learning learning strategies and expository strategies in which the results of student accounting learning taught by e-learning strategy is higher than the students taught by strategy expository learning. (2) There is an interaction between students who are taught using learning strategies with interest in learning on accounting learning outcomes. (3) This means that the result of group accounting learning which is taught using e-learning learning strategy is significantly higher than that taught using expository learning strategy in students who have high learning interest. (4) While the learning result of student group accounting that is taught using e-learning strategy is same as learning result which is taught using expository learning strategy to students who have low learning interest, influenced by student environment factor and learning design factor in research.


Author(s):  
M. Ilayaraja ◽  
S. Hemalatha ◽  
P. Manickam ◽  
K. Sathesh Kumar ◽  
K. Shankar

Cloud computing is characterized as the arrangement of assets or administrations accessible through the web to the clients on their request by cloud providers. It communicates everything as administrations over the web in view of the client request, for example operating system, organize equipment, storage, assets, and software. Nowadays, Intrusion Detection System (IDS) plays a powerful system, which deals with the influence of experts to get actions when the system is hacked under some intrusions. Most intrusion detection frameworks are created in light of machine learning strategies. Since the datasets, this utilized as a part of intrusion detection is Knowledge Discovery in Database (KDD). In this paper detect or classify the intruded data utilizing Machine Learning (ML) with the MapReduce model. The primary face considers Hadoop MapReduce model to reduce the extent of database ideal weight decided for reducer model and second stage utilizing Decision Tree (DT) classifier to detect the data. This DT classifier comprises utilizing an appropriate classifier to decide the class labels for the non-homogeneous leaf nodes. The decision tree fragment gives a coarse section profile while the leaf level classifier can give data about the qualities that influence the label inside a portion. From the proposed result accuracy for detection is 96.21% contrasted with existing classifiers, for example, Neural Network (NN), Naive Bayes (NB) and K Nearest Neighbor (KNN).


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