A Recommender for Improving the Student Academic Performance

Goga, Maria; Kuyoro, Shade O.; Goga, Nicolae

doi:10.1016/j.sbspro.2015.02.296

Cited by 65 publications

(32 citation statements)

References 14 publications

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“…Maria Goga, Shade Kuyoro, Nicolae Goga (2015) used student data from Babcock University, Nigeria. On the basis of reviewed literature, they considered age, gender, parent's marital status, parent's qualification, parent's occupations, SSC score, HSC score, CGPA first year [19]. Maria Koutina and Katia Lida Kermanidis (2011) they tried to find out the best techniques for predicting the final grade of the postgraduate students of Ionian University Informatics, Greece.…”

Section: Important Factors Of Students Used For Predicting Student's mentioning

confidence: 99%

“…The most important personal attributes of the student like gender, age, interested in the study, admission type, Study Behaviour are taken into consideration [7,8,9,11,12,13,18,19,24]. The family attributes like parent's qualification, parent's occupation, family income, family status, Family Support for study are also taken as important for the academics prediction [7,9,15,19,24].…”

Section: Important Factors Of Students Used For Predicting Student's mentioning

confidence: 99%

“…The family attributes like parent's qualification, parent's occupation, family income, family status, Family Support for study are also taken as important for the academics prediction [7,9,15,19,24]. Whereas for academic attributes like high school grade, students' previous semester marks, class test grade, seminar performance, assignment performance, attendance in class and lab work, previous schools marks are taken into consideration [5,6,7,8,9,10,15,16,18,19,24] and for institutional attributes most the researcher are taken medium of teaching, accommodation type, infrastructure, water and toilet facilities, teaching methodology, transportation facilities into consideration [4,7,9,12,16,18,24].…”

Section: Important Factors Of Students Used For Predicting Student's mentioning

confidence: 99%

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Literature Survey on Student’s Performance Prediction in Education using Data Mining Techniques

Kumar¹,

Singh²,

Handa³

2017

IJEME

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One of the most challenging tasks in the education sector in India is to predict student's academic performance due to a huge volume of student data. In the Indian context, we don't have any existing system by which analyzing and monitoring can be done to check the progress and performance of the student mostly in Higher education system. Every institution has their own criteria for analyzing the performance of the students. The reason for this happing is due to the lack of study on existing prediction techniques and hence to find the best prediction methodology for predicting the student academics progress and performance. Another important reason is the lack in investigating the suitable factors which affect the academic performance and achievement of the student in particular course. So to deeply understand the problem, a detail literature survey on predicting student's performance using data mining techniques is proposed. The main objective of this article is to provide a great knowledge and understanding of different data mining techniques which have been used to predict the student progress and performance and hence how these prediction techniques help to find the most important student attribute for prediction. Actually, we want to improve the performance of the student in academic by using best data mining techniques. At last, it could also provide some benefits for faculties, students, educators and management of the institution.

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Section: Important Factors Of Students Used For Predicting Student's mentioning

confidence: 99%

Section: Important Factors Of Students Used For Predicting Student's mentioning

confidence: 99%

Section: Important Factors Of Students Used For Predicting Student's mentioning

confidence: 99%

See 1 more Smart Citation

Literature Survey on Student’s Performance Prediction in Education using Data Mining Techniques

Kumar¹,

Singh²,

Handa³

2017

IJEME

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“…According to M. Richardson et al GPA highlights the wealth of theoretical elaboration and empirical testing that has been devoted to understanding why some undergraduates perform better than others [10]. M. Gogaa et al aimed at designing a framework of intelligent recommender system, based on background factors, which can predict students" first year academic performance and recommend necessary actions for improvement [1].…”

Section: Student Performancementioning

confidence: 99%

“…For the good predictive accuracy there were few researches which used decision tree algorithms and data mining [8], [1] and [15]. The impact of extracurricular activities to the student studies performance were vital to making an own method to calculate extracurricular performance according to the most effective factors in this implemented system [5] and [9].…”

Section: Research Gapmentioning

confidence: 99%

Sisu Manthalawa: Guiding Students towards a Better Future

Thelis¹,

Jayatunge²,

Kumarapeli³

et al. 2016

IJCA

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Learning one"s own strengths and weaknesses is essential when making important life decisions; especially for students that are obliged to make decisions about what path they are to persuade leading them to a carrier path without regret. Today most of the students do not have a proper understanding of their own talents, abilities or how they can accomplish their future goals. The system mentioned in this research paper provides a solution by helping grade 10 and 11 local students to learn about their own strengths and weaknesses thus guiding them when making important decisions about what paths to follow in the future and what aspect they need to improve on. Students" past performances, logical thinking and other attributes were taken into consideration to provide an accurate and comprehensible output depicting their weaknesses and strengths. Moreover, the output was analysed and used to aid teachers when dividing student groups inside the classroom for cooperative group activities. An intelligent system driven by algorithms to support logical and cooperative grouping strategies that uses statistical analysis and output analysis along with an online quiz for students to learn their logical thinking skills were used to produce the expected output. Information about extracurricular activities were collected from a selected group of 50 students using a questionnaire that had being analysed by the research group. Patterns of students" scoring were analysed to predict the score the same student would gain in the future using data mining methods and tools. Sisu Manthalawa is a web application that can help the local students to make decisions thus helping them stride towards a better future.

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