Iraqi Journal for Computers and Informatics

Blockchainis a new technology that provides services of immutability, trust, disintermediation, collaboration, transparency. Nowadays, the use of this new technology is mostly used for Bitcoin and other cryptocurrencies, but apart from this, blockchain technology improved the performance level of other areas of life i.e. Higher Education Institution (HEI) and stakeholders, certificate verification and many other domains. Students and educational institutions' important data are mostly shared via different networks. The data integrity, privacy and security are the major issues for these in the blockchain technology which cannot be avoided. This paper is a documented plan for to conduct or a protocol based on which a systematic literature review would be conducted focusingthe issues, challenges and major strengths of blockchain and its educational paradigms. The result of this review will be highly helpful for the new researchers to overcome the proposed issues and challenges, exploring educational paradigms in Blockchain, elaborate the major strengths helping the educational institutes in adapting process and increase the level of satisfaction. This study plans to explore some educational types with some issues and challenges such as scalability, immutability, and easyadaptation.Index Terms -Systematic Literature Review Protocol (SLRP), Higher Education Institution (HEI), Blockchain-Based Educational Paradigms (BCBEP).

The increasing use of the internet has created a vast amount of digital information and it is expanding extremely fast. Therefore, Information retrieval becomes a challenging task to fetch relevant information for users. The aim of this paper was to examine and evaluate the performance of the Information retrieval system through eight experiments to test all the features that can be used in a vector space model. These experiments were compared to show the best and the worst implemented features. The features are represented by applying (tf.idf, stop words, stemming), (tf.idf, No-stop words, stemming), (tf.idf, No-stop words, No-stemming), (tf.idf, stop words, No-stemming), (tf, stop words, stemming), (tf, No-stop words, stemming), (tf, No-stop words, No-stemming), (tf, stop words, No-stemming). Results showed that using stop words, stemming approach, and tf.idf improve the performance of the system. However, when tf was used without using stop words and stemming approaches the performance of the system is declined. In addition, results showed that stop words have a significant effect on the system while the stemming approach has no noticeable effect particularly with tf