An E-Learning system that provides vast quantities of annotated resources (fragments or learning objects) and produces semantically rich feedback is very desirable. It is an accepted psychological principle that some of the essential elements needed for effective learning are custom learning and semantic feedback. In this paper we are making use of a collection (ontology) of metadata for the design of a custom E-Learning system that also provides learners with effective semantic educational feedback support. The learning domain is “mobile computing.” We define various concepts in the domain and the relationships among them as the ontology, and build a system to utilize them in customizing the E-Learning process. The ontology is also used to provide informative feedback from the system during learning and/or during assessment. The focus in this research is on the representation of ontology using languages/grammars, grammar analysis techniques, algorithms, and AI mechanisms to customize the learning and create effective feedbacks. The proposed mechanisms, based on ontology, are used to assemble virtual courses and create a rich supply of feedbacks, not only in assessment situations but also in the context of design-oriented education. We are targeting feedbacks similar to ones in programming environments and design editors.

Hybrid ontology-based feedback e-learning system for mobile computing

Nowadays automated data collection tools and mature database technology lead to tremendous amounts of data stored in databases, data warehouses and other information repositories in business organizations. In this paper, a novel approach of developing a decision support system using on-line analytical processing (OLAP) is presented. The OLAP application is optimal for data queries that do not change data. The system database is designed to promote: heavy indexing to improve query performance, denormalisation of the database to satisfy common query requirements and improve query response times, and use of a star-snowflake schema to organize the data within the database. The existing partitioning strategy is used to partition the fact table by time into equal segments, differentsize segments and on different dimension of data warehouse, which provide the good query performance, optimize hardware performance, and simplify the management of the data warehouse by reducing the volume of data to satisfy a query. Entity-relation modeling is used to create a single complex model, which proven effective in creating efficient online transaction processing systems. In this system, cubes are used to organize and summarize data for efficient analytical querying. In addition, an enterprise information system model has also been presented in this paper in order to optimize the utilization of operational data for use strategically. The proposed system is evaluated on the cube data for the Rajshahi and Khulna regions for ten years from 1994 to 2003. Experimental results indicate the effectiveness of the proposed OLAP based Decision Support System.

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OLAP-based Decision Support System for Business Data Analysis

This paper aims to introduce a design of an intelligent system (IS) to help students of industrial technical education to diagnose and fix automatic washing machine malfunctions (AWMM), With the huge development in the manufacture of home appliances and their components, there has been a merger between several areas such as electronics specialist, refrigeration and air conditioning specialist. (They are the two specializations entrusted with repairing home appliances in the Egyptian labor market) Which has created a huge gap between the knowledge and skills of students of these two specialties in industrial technical education (ITE) schools and labor market requires. So it became necessary to employ the technology of artificial intelligence (AI) to help these students to keep abreast of the tremendous developments taking place in the field of manufacturing various home appliances, by designing the proposed intelligent system (IS) to save time and effort needed to process the various malfunctions of the automatic washing machine. We noticed that skills of students are improved in dealing with malfunctions.

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Intelligent System for Diagnosing and Fixing Automatic Washing Machine Malfunctions for Industrial Technical Education in Egypt

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Quality Control in Automobile Manufacturing Industries

The traditional examination papers generally use manual marking, which is a very time-consuming and inefficient marking method. If teachers manually correct students' examination papers every time, not only the workload is heavy, but also due to the influence of subjective factors, they will not be able to objectively and impartially reflect the students' learning effect. If automatic scoring can be realized, it will greatly reduce the workload of teachers, improve the accuracy and objectiveness of scoring, and thus improve the quality of teaching. Therefore, solving the automatic scoring of examination papers is a key problem that needs to be solved urgently at present. In this paper, the BP neural network model in the deep learning technology is used to establish an automatic examination scoring system, which optimizes the information management performance of the system. 

Automatic Test Scoring System Based on Deep Learning Technology

As the specialization of cars is one of the specialties found in industrial technical education(ITE) schools and students suffer from many problems highlighted by the results of personal interviews with some experts and specialists in the field of repair and maintenance of cars as well as some teachers of ITE has become clear the need to design the proposed system to help students to improve their knowledge and then skills Which makes them able to join the labor market and keep abreast of the rapid changes and developments in the automotive industry and the complexity of their breakdowns. The proposed system was designed according to the basic stages of expert system; Problem IdentificationConceptualization-Formalization-Application ImplementationTesting. Knowledge base was put on the cloud computing so that it can be accessed at any time and from any place. The proposed system was applied to a sample of students including 53 students from the specialization of cars divided into two groups; (experimental and standard). The results were analyzed and processed statistically according to the actual application of the proposed system on the research sample. It was found that there were statistically significant differences at the level of (0.05) between the average scores of the students of the standard group (the traditional teaching style) and the experimental group in the knowledge and skills aspects of the experimental group, indicating the effective use of the proposed system and the need for ITE schools.

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An Expert System to Diagnose and Fix Common Car Breakdowns for Industrial Technical Education in Egypt

The current research aims to identify the effectiveness of a proposed application based on mobile educational techniques for the management of electronic tests. The sample consisted of a group of students of the fourth division of computer teacher preparation department in the Faculty of Specific Education in Damietta during the academic year 2018/2017) and the number (20).The results of the current research showed that There are statistically significant differences at level 0.05 between the average scores When pre and post applying the achievement test . The results indicated that There are positive trends among experimental group students (which study the network course using the proposed system) towards the use of the proposed system and there is the effectiveness of the proposed system to assess the learner and to get feedback and show the shortcomings of the learner that measure target at 0.05 level of significance.

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A Proposed Application based on Mobile Learning Techniques to Manage Electronic Tests

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Elsaeed Elsaeed Mohamed Abd Elrazek

Papers

An Expert System to Diagnose and Fix Common Car Breakdowns for Industrial Technical Education in Egypt

A Proposed Application based on Mobile Learning Techniques to Manage Electronic Tests

Automatic Exam Evaluation based on Brain Computer Interface

Intelligent System for Diagnosing and Fixing Automatic Washing Machine Malfunctions for Industrial Technical Education in Egypt