Journal of Software Engineering & Software Testing (ISSN: 2457-0516)

Journal of Software Engineering & Software Testing

The Journal of Software engineering & Software Testing deals with the application of engineering to software that includes documenting the requirements of the software through application of basic design principles. The journal also emplasizes to analyze and design alternatives keeping in mind the utility of the finished product and whether the final product meets its requirements. At the same The journal also emphasizes on the safety, reliability, cost-affectivity and functional aspects of the software.

Some of the topics covered under this journal (but not limited to them) are:

    • Mathematics
    • Chemistry
    • Basic Engineering
    • Computer Literacy
    • Physics Laboratory
    • Engineering Graphics
    • Biology for Engineering
    • Principles of Environmental Science
    • Material Science
    • Digital Computer Fundamentals
    • Computer Organization and Architecture
    • Data Structures and Algorithms
    • Software Engineering Principles
    • Object Oriented Programming
    • Microprocessors
    • Software Design
    • Computer Skills
    • Discrete Mathematics
    • Computer Networks
    • Industrial management and economics
    • Software quality management
    • Web technology

Vol 5, No 2 (2020): Personalize Recommendation Approach for Web Search in E-Learning

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Author: Sajid.M.Momin, Amol.B.Rajmane

Abstract: In the e-learning context, a recommender system is a software agent that tries to "intelligently" recommend actions to a learner based on previous learners' actions. These recommendation systems have been tried in e-commerce to entice purchasing of goods, but haven't been tried in e-learning. The majority of current web-based learning systems are closed learning environments where courses and learning materials are fixed and the only dynamic aspect is the organization of the material that can be adapted to allow a relatively individualized learning environment.


The proposed system is based on four modules: Web search Module, student Profiling Module, Behavioral Activity analyzer module, and recommendation module. The web search Module is a way of searching for anything that the user or student wants from the Google search engine. A student Profiling Module takes Students all Personal and Academic Information, and Behavioral Activity analyzer module is used to identify learners learning preferences and all activities which are done at the time of web surfing by students and a recommendation module which pre-processes data to create a suitable recommendation list and predicting the student interest domain. After the recommendation process, we calculate the Knowledge Point (KP) of a particular student based on KP value it categories the student into three levels 1. Beginner 2. Intermediate 3. Master. Several techniques, such as classification, clustering, and association rules, are used to improve personalization with filtering techniques to provide a recommendation and help learners improve their performance.


The e-learning field research has gained more and more attention thanks to the recent explosive use of the Internet. However, Web-based learning environments are becoming very popular. In a virtual classroom, educators provide text, multimedia and simulations, and moderate and animate discussions. Remote learners are encouraged to peruse the resources and participate in activities.

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