Over the last several years, Massive Open Online Courses (MOOCs) have received significant coverage in the higher education literature. They are the most recent development in open online distance learning. Thus, the most challenging is designing an accurate method to evaluate and provide feedbacks, especially for open questions (especially Problem Situation), since the high number of learners. To tackle this problem, MOOCs use peer assessment techniques (known as peer grading) that suffer from a lack of credibility. In this paper, we present a new method for peer assessment in the Massive Open Online Courses, in order to improve the accuracy of grading results. Our proposition is divided into three (3) steps: clustering unit, assessment and treatment of the results. The clustering unit is the task of grouping learners with similar profiles. Clustering unit aims to group learners based on the parameters stored on learners' modeling within the MOOCs. After the clustering unit, the learners are required to grade a small number of their peers' tasks as part of their own task. Afterwards, the scores are dispatched for treatments where a synthesis is given for assessment. To assess the feasibility of the proposed peer assessment, we report here the results of the tests conducted on the developed prototype.
{"title":"Peer assessment in MOOCs based on learners' profiles clustering","authors":"Haddadi Lynda, Bouarab-Dahmani Farida, Berkane Tassadit, Lazib Samia","doi":"10.1109/ICITECH.2017.8080054","DOIUrl":"https://doi.org/10.1109/ICITECH.2017.8080054","url":null,"abstract":"Over the last several years, Massive Open Online Courses (MOOCs) have received significant coverage in the higher education literature. They are the most recent development in open online distance learning. Thus, the most challenging is designing an accurate method to evaluate and provide feedbacks, especially for open questions (especially Problem Situation), since the high number of learners. To tackle this problem, MOOCs use peer assessment techniques (known as peer grading) that suffer from a lack of credibility. In this paper, we present a new method for peer assessment in the Massive Open Online Courses, in order to improve the accuracy of grading results. Our proposition is divided into three (3) steps: clustering unit, assessment and treatment of the results. The clustering unit is the task of grouping learners with similar profiles. Clustering unit aims to group learners based on the parameters stored on learners' modeling within the MOOCs. After the clustering unit, the learners are required to grade a small number of their peers' tasks as part of their own task. Afterwards, the scores are dispatched for treatments where a synthesis is given for assessment. To assess the feasibility of the proposed peer assessment, we report here the results of the tests conducted on the developed prototype.","PeriodicalId":102480,"journal":{"name":"2017 8th International Conference on Information Technology (ICIT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122912391","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-05-17DOI: 10.1109/ICITECH.2017.8080008
C. Koçak, Kahraman Zaim
The use of real-time multimedia applications in IP networks is continuously increasing with the services provided by the evolving internet infrastructure. Providing Quality of Service (QoS) is important for service providers in terms of real-time voice and video services to meet users' expectations. For this reason, QoS parameters such as network latency, jitter and packet loss must be accurately and precisely measured. The widely used PING protocol for measuring the specified parameters do not give accurate and precise results at the desired level. In this study, it is proposed to use Two-Way Active Measurement Protocol (TWAMP) for measuring the QoS parameters of the IP network. TWAMP is the latest method to fully deliver performance metrics for IP network infrastructure. According to the active measurement method, round trip delay, jitter and packet loss parameters between two end nodes were measured with TWAMP and PING protocols and analyzed by comparing values. As a result of the study, it has been shown that TWAMP protocol recommended for multimedia communication is suitable for measuring service quality of IP Networks.
{"title":"Performance measurement of IP networks using Two-Way Active Measurement Protocol","authors":"C. Koçak, Kahraman Zaim","doi":"10.1109/ICITECH.2017.8080008","DOIUrl":"https://doi.org/10.1109/ICITECH.2017.8080008","url":null,"abstract":"The use of real-time multimedia applications in IP networks is continuously increasing with the services provided by the evolving internet infrastructure. Providing Quality of Service (QoS) is important for service providers in terms of real-time voice and video services to meet users' expectations. For this reason, QoS parameters such as network latency, jitter and packet loss must be accurately and precisely measured. The widely used PING protocol for measuring the specified parameters do not give accurate and precise results at the desired level. In this study, it is proposed to use Two-Way Active Measurement Protocol (TWAMP) for measuring the QoS parameters of the IP network. TWAMP is the latest method to fully deliver performance metrics for IP network infrastructure. According to the active measurement method, round trip delay, jitter and packet loss parameters between two end nodes were measured with TWAMP and PING protocols and analyzed by comparing values. As a result of the study, it has been shown that TWAMP protocol recommended for multimedia communication is suitable for measuring service quality of IP Networks.","PeriodicalId":102480,"journal":{"name":"2017 8th International Conference on Information Technology (ICIT)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128125937","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-05-17DOI: 10.1109/ICITECH.2017.8079929
M. Hassan, Mazen Sheikh Bashraheel
It is known that the number of colors that can be distinguished by human eye is much more than that of the grayscale levels and more information is contained in color image than what is contained in grayscale one. By studying the Structural Similarity Index (SSIM), it is found that it fails in estimating the quality of color images with color-related noises. Based on this, we develop an improved method which is called Color-based Structural Similarity. The proposed method was validated on the TID2013 image database and the experimental results show that the quality scores given by the proposed method are more consistent with HVS than the classical one.
{"title":"Color-based structural similarity image quality assessment","authors":"M. Hassan, Mazen Sheikh Bashraheel","doi":"10.1109/ICITECH.2017.8079929","DOIUrl":"https://doi.org/10.1109/ICITECH.2017.8079929","url":null,"abstract":"It is known that the number of colors that can be distinguished by human eye is much more than that of the grayscale levels and more information is contained in color image than what is contained in grayscale one. By studying the Structural Similarity Index (SSIM), it is found that it fails in estimating the quality of color images with color-related noises. Based on this, we develop an improved method which is called Color-based Structural Similarity. The proposed method was validated on the TID2013 image database and the experimental results show that the quality scores given by the proposed method are more consistent with HVS than the classical one.","PeriodicalId":102480,"journal":{"name":"2017 8th International Conference on Information Technology (ICIT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124707336","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-05-17DOI: 10.1109/ICITECH.2017.8079919
Khaled A. S. Abu Daqqa, Ashraf Y. A. Maghari, W. A. Sarraj
Algorithms used in data mining techniques are of great importance in the field of health care, especially in the case of getting patterns or models that are undiscovered in databases. In the area of health care, leukemia affects the blood status and can be discovered by using the Blood Cell Counter (CBC). This study aims to predict the leukemia existence by determining the relationships of blood properties and leukemia with gender, age, and health status of patients using data mining techniques. More than 4,000 patients were taken from a blood test laboratory from European Gaza Hospital at Gaza Strip. Three classification algorithms are identified for blood Cancer classification; k-nearest neighbor (k-NN), decision tree (DT) and Support Vector Machine (SVM). These three classifiers were implemented and studied thoroughly in terms of classification accuracy and F-Measure. From our experimental results, it was noticed that the decision-tree algorithm had the highest percentage of 77.30% compared with the other two techniques. In addition, the DT classifier obtains properties regarding outer attributes such as city (eastern regions) that are most vulnerable to leukemia.
{"title":"Prediction and diagnosis of leukemia using classification algorithms","authors":"Khaled A. S. Abu Daqqa, Ashraf Y. A. Maghari, W. A. Sarraj","doi":"10.1109/ICITECH.2017.8079919","DOIUrl":"https://doi.org/10.1109/ICITECH.2017.8079919","url":null,"abstract":"Algorithms used in data mining techniques are of great importance in the field of health care, especially in the case of getting patterns or models that are undiscovered in databases. In the area of health care, leukemia affects the blood status and can be discovered by using the Blood Cell Counter (CBC). This study aims to predict the leukemia existence by determining the relationships of blood properties and leukemia with gender, age, and health status of patients using data mining techniques. More than 4,000 patients were taken from a blood test laboratory from European Gaza Hospital at Gaza Strip. Three classification algorithms are identified for blood Cancer classification; k-nearest neighbor (k-NN), decision tree (DT) and Support Vector Machine (SVM). These three classifiers were implemented and studied thoroughly in terms of classification accuracy and F-Measure. From our experimental results, it was noticed that the decision-tree algorithm had the highest percentage of 77.30% compared with the other two techniques. In addition, the DT classifier obtains properties regarding outer attributes such as city (eastern regions) that are most vulnerable to leukemia.","PeriodicalId":102480,"journal":{"name":"2017 8th International Conference on Information Technology (ICIT)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129335356","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-05-17DOI: 10.1109/ICITECH.2017.8079969
Riyad Dhuny, N. Mohamudally, N. Nissanke
We propose caching mechanism in the form of a library named mysqlj capable of returning database results as an offline data file for further use by both server and client. The unique feature of this work & library is its transparency for developers and its versatility for use both at server and client level. The cache offloads application from querying database servers in the event valid data is available. Our tests shows a web server capable of serving 1.9 times more concurrent users than existing model. An RPI3 IoT device running our model is capable of handling 60 concurrent users/secs compared to initial value of 31. Our model advocates the idea of keeping HTML and queried data separately for further use by client browser and mobile applications. The work also contributes to existing knowledge by providing an insight on performance gain and advantages while working with HTML + data separation compared to traditional mixed one.
{"title":"Multi-level reusable static query cache for HTML5 service workers and offline data usage","authors":"Riyad Dhuny, N. Mohamudally, N. Nissanke","doi":"10.1109/ICITECH.2017.8079969","DOIUrl":"https://doi.org/10.1109/ICITECH.2017.8079969","url":null,"abstract":"We propose caching mechanism in the form of a library named mysqlj capable of returning database results as an offline data file for further use by both server and client. The unique feature of this work & library is its transparency for developers and its versatility for use both at server and client level. The cache offloads application from querying database servers in the event valid data is available. Our tests shows a web server capable of serving 1.9 times more concurrent users than existing model. An RPI3 IoT device running our model is capable of handling 60 concurrent users/secs compared to initial value of 31. Our model advocates the idea of keeping HTML and queried data separately for further use by client browser and mobile applications. The work also contributes to existing knowledge by providing an insight on performance gain and advantages while working with HTML + data separation compared to traditional mixed one.","PeriodicalId":102480,"journal":{"name":"2017 8th International Conference on Information Technology (ICIT)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127201655","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-05-17DOI: 10.1109/ICITECH.2017.8079912
M. Shehab, A. Khader, M. Al-Betar, L. Abualigah
The Cuckoo Search Algorithm (CSA) is a promising metaheuristic algorithm. It is applied to solve many problems in different fields. This paper proposes a new cuckoo search algorithm by combining the cuckoo search algorithm with the Hill Climbing method for solving the integer and minimax optimization problems. The proposed algorithm is named hybrid cuckoo search and hill climbing (CSAHC). CSAHC starts the search by applying the standard cuckoo search for the number of iterations then the best-obtained solution is passed to the hill climbing algorithm as an intensification process to accelerate the search and overcome the slow convergence of the standard cuckoo search algorithm. The proposed algorithm balances between the global exploration of the cuckoo search algorithm and the deep exploitation of the hill climbing method. The validation of the performance is determined by applying 13 benchmarks. The results of experimental simulations indicated that the CSAHC performs better than standard CSA.
{"title":"Hybridizing cuckoo search algorithm with hill climbing for numerical optimization problems","authors":"M. Shehab, A. Khader, M. Al-Betar, L. Abualigah","doi":"10.1109/ICITECH.2017.8079912","DOIUrl":"https://doi.org/10.1109/ICITECH.2017.8079912","url":null,"abstract":"The Cuckoo Search Algorithm (CSA) is a promising metaheuristic algorithm. It is applied to solve many problems in different fields. This paper proposes a new cuckoo search algorithm by combining the cuckoo search algorithm with the Hill Climbing method for solving the integer and minimax optimization problems. The proposed algorithm is named hybrid cuckoo search and hill climbing (CSAHC). CSAHC starts the search by applying the standard cuckoo search for the number of iterations then the best-obtained solution is passed to the hill climbing algorithm as an intensification process to accelerate the search and overcome the slow convergence of the standard cuckoo search algorithm. The proposed algorithm balances between the global exploration of the cuckoo search algorithm and the deep exploitation of the hill climbing method. The validation of the performance is determined by applying 13 benchmarks. The results of experimental simulations indicated that the CSAHC performs better than standard CSA.","PeriodicalId":102480,"journal":{"name":"2017 8th International Conference on Information Technology (ICIT)","volume":"25 8","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113967847","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-05-17DOI: 10.1109/ICITECH.2017.8079924
A. Moldagulova, R. Sulaiman
Nowadays the exponential growth of generation of textual documents and the emergent need to structure them increase the attention to the automated classification of documents into predefined categories. There is wide range of supervised learning algorithms that deal with text classification. This paper deals with an approach for building a machine learning system in R that uses K-Nearest Neighbors (KNN) method for the classification of textual documents. The experimental part of the research was done on collected textual documents from two sources: http://egov.kz and http://www.government.kz. The experiment was devoted to challenging thing of the KNN algorithm that to find the proper value of k which represents the number of neighbors.
{"title":"Using KNN algorithm for classification of textual documents","authors":"A. Moldagulova, R. Sulaiman","doi":"10.1109/ICITECH.2017.8079924","DOIUrl":"https://doi.org/10.1109/ICITECH.2017.8079924","url":null,"abstract":"Nowadays the exponential growth of generation of textual documents and the emergent need to structure them increase the attention to the automated classification of documents into predefined categories. There is wide range of supervised learning algorithms that deal with text classification. This paper deals with an approach for building a machine learning system in R that uses K-Nearest Neighbors (KNN) method for the classification of textual documents. The experimental part of the research was done on collected textual documents from two sources: http://egov.kz and http://www.government.kz. The experiment was devoted to challenging thing of the KNN algorithm that to find the proper value of k which represents the number of neighbors.","PeriodicalId":102480,"journal":{"name":"2017 8th International Conference on Information Technology (ICIT)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127713676","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-05-17DOI: 10.1109/ICITECH.2017.8079933
Suhaina binti Mohamed Zaki, R. Mohamad, S. A. Halim, Nor Bahiah Hj. Ahmad
The process of learning and teaching online learning has undergone many changes in line with technological developments. Education institutions have begun introducing new methods of learning this. However, it needs a huge amount of labor intensive to produce and maintain educational technologies due to its huge size (literacy, vocational education, school education, engineering and medical education) and huge variants (language, dialect). With the growing demand and at the same time would like to reduce the factor of cost, time and effort is long, then the need for an effective solution allowing rapid system development. A Software Product Line (SPL) approach is one of the best methods that can be used to develop an educational software family. The research contributes to the development of online learning SPL by studying issues in online learning SPL, identify appropriate pedagogical approach to online learning environment that is constructivism, and designing constructivist learning environment based on the theory of constructivism and design principles. In this paper, comparison between 10 VLE was tabulated against constructivist learning environment. The comparative evaluation is to discover commonalities and variabilities between online learning applications. The results should be useful as the process of domain analysis that is to document the commonalities and variabilities between SPL members. Hence, it can be used to enhance the feature model for online learning applications.
{"title":"Learning environment for software product lines online learning applications","authors":"Suhaina binti Mohamed Zaki, R. Mohamad, S. A. Halim, Nor Bahiah Hj. Ahmad","doi":"10.1109/ICITECH.2017.8079933","DOIUrl":"https://doi.org/10.1109/ICITECH.2017.8079933","url":null,"abstract":"The process of learning and teaching online learning has undergone many changes in line with technological developments. Education institutions have begun introducing new methods of learning this. However, it needs a huge amount of labor intensive to produce and maintain educational technologies due to its huge size (literacy, vocational education, school education, engineering and medical education) and huge variants (language, dialect). With the growing demand and at the same time would like to reduce the factor of cost, time and effort is long, then the need for an effective solution allowing rapid system development. A Software Product Line (SPL) approach is one of the best methods that can be used to develop an educational software family. The research contributes to the development of online learning SPL by studying issues in online learning SPL, identify appropriate pedagogical approach to online learning environment that is constructivism, and designing constructivist learning environment based on the theory of constructivism and design principles. In this paper, comparison between 10 VLE was tabulated against constructivist learning environment. The comparative evaluation is to discover commonalities and variabilities between online learning applications. The results should be useful as the process of domain analysis that is to document the commonalities and variabilities between SPL members. Hence, it can be used to enhance the feature model for online learning applications.","PeriodicalId":102480,"journal":{"name":"2017 8th International Conference on Information Technology (ICIT)","volume":"311 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131866655","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-05-17DOI: 10.1109/ICITECH.2017.8079993
M. Ibrahim
Providing a resiliency measure for communication networks is one of the challenges towards its Dynamic Security Assessment. This paper introduces a resiliency measure, called Level-of-Resilience (LoR) for communication networks, determined by examining: (i) the Level-of-Stability-Reduction (LoSr), as captured by percentage of “IP traffic dropped”, (ii) the eventual Level-of-Performance-Reduction (LoPr), as measured by percentage of reduction in application Quality-of-Service (QoS), namely, latency, and (iii) Recovery-Time (RT), which is the time system takes to detect and recover from an attack or a fault. This measure is illustrated by comparing resiliency level of two communication networks that serve the same traffic, but differ in their network topology, under two different attack scenarios.
{"title":"A resiliency measure for communication networks","authors":"M. Ibrahim","doi":"10.1109/ICITECH.2017.8079993","DOIUrl":"https://doi.org/10.1109/ICITECH.2017.8079993","url":null,"abstract":"Providing a resiliency measure for communication networks is one of the challenges towards its Dynamic Security Assessment. This paper introduces a resiliency measure, called Level-of-Resilience (LoR) for communication networks, determined by examining: (i) the Level-of-Stability-Reduction (LoSr), as captured by percentage of “IP traffic dropped”, (ii) the eventual Level-of-Performance-Reduction (LoPr), as measured by percentage of reduction in application Quality-of-Service (QoS), namely, latency, and (iii) Recovery-Time (RT), which is the time system takes to detect and recover from an attack or a fault. This measure is illustrated by comparing resiliency level of two communication networks that serve the same traffic, but differ in their network topology, under two different attack scenarios.","PeriodicalId":102480,"journal":{"name":"2017 8th International Conference on Information Technology (ICIT)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133647699","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-05-17DOI: 10.1109/ICITECH.2017.8079967
Ihsan A. Abu Amra, Ashraf Y. A. Maghari
Data mining techniques is rapidly increasing in the research of educational domains. Educational data mining aims to discover hidden knowledge and patterns about student performance. This paper proposes a student performance prediction model by applying two classification algorithms: KNN and Naïve Bayes on educational data set of secondary schools, collected from the ministry of education in Gaza Strip for 2015 year. The main objective of such classification may help the ministry of education to improve the performance due to early prediction of student performance. Teachers also can take the proper evaluation to improve student learning. The experimental results show that Naïve Bayes is better than KNN by receiving the highest accuracy value of 93.6%.
{"title":"Students performance prediction using KNN and Naïve Bayesian","authors":"Ihsan A. Abu Amra, Ashraf Y. A. Maghari","doi":"10.1109/ICITECH.2017.8079967","DOIUrl":"https://doi.org/10.1109/ICITECH.2017.8079967","url":null,"abstract":"Data mining techniques is rapidly increasing in the research of educational domains. Educational data mining aims to discover hidden knowledge and patterns about student performance. This paper proposes a student performance prediction model by applying two classification algorithms: KNN and Naïve Bayes on educational data set of secondary schools, collected from the ministry of education in Gaza Strip for 2015 year. The main objective of such classification may help the ministry of education to improve the performance due to early prediction of student performance. Teachers also can take the proper evaluation to improve student learning. The experimental results show that Naïve Bayes is better than KNN by receiving the highest accuracy value of 93.6%.","PeriodicalId":102480,"journal":{"name":"2017 8th International Conference on Information Technology (ICIT)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129145141","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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