Determination of Academic Performance and Academic Consistency by Fuzzy Logic

被引:0
|
作者
Salam, Shaikh Diya [1 ]
Paul, Pias [1 ]
Tabassum, Rehuma [1 ]
Mahmud, Ifaz [1 ]
Ullah, Md Ayat [1 ]
Rahman, Ashiqur [1 ]
Rahman, Rashedur M. [1 ]
机构
[1] North South Univ, Dept Elect Engn & Comp Sci, Plot 15,Block B, Dhaka 1229, Bangladesh
关键词
Fuzzy logic; Fuzzy inference system; Adaptive Neuro Fuzzy Inference System; k-means algorithm; Academic Performance; Academic Consistency; Factors;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Academic evaluation is becoming an increasingly popular area. In this work, we have developed a software tool using fuzzy logic to find out the academic performance and consistency of students. Traditionally, the academic performance had been measured by the result of a student. However, the new method developed in this work has taken several factors into consideration. The factors are the parameters that influence the academic performance and consistency of students. Such factors have been established by consulting students and data is obtained with the help of online surveys and face to face interviews with students of Electrical and Computer Engineering students from North South University, Dhaka, Bangladesh. Some of the factors that are considered: "Online Assistance", "Part-Time Job", "Number of courses", "Hours spent Studying etc. The data have been used to develop the tool for measuring the academic performance and consistency. The performance is measured with the Fuzzy Inference System (FIS), Adaptive Neuro Fuzzy Inference System (ANFIS). In case of obtaining the academic consistency, the data of different factors are used to generate the clusters using the k-means algorithm.
引用
收藏
页码:50 / 57
页数:8
相关论文
共 50 条
  • [31] Fuzzy-Clustering Embedded Regression for Predicting Student Academic Performance
    Li, Zhenpeng
    Shang, Changjing
    Shen, Qiang
    2016 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ-IEEE), 2016, : 344 - 351
  • [32] Improved Fuzzy Modelling to Predict the Academic Performance of Distance Education Students
    Yildiz, Osman
    Bal, Abdullah
    Gulsecen, Sevinc
    INTERNATIONAL REVIEW OF RESEARCH IN OPEN AND DISTRIBUTED LEARNING, 2013, 14 (05): : 144 - 165
  • [33] An algorithm based on fuzzy ordinal classification to predict students’ academic performance
    Juan C. Gámez-Granados
    Aurora Esteban
    Francisco J. Rodriguez-Lozano
    Amelia Zafra
    Applied Intelligence, 2023, 53 : 27537 - 27559
  • [34] Time Perspective, Intended Academic Engagement, and Academic Performance
    Barnett, Michael
    Melugin, Patrick
    Hernandez, Joseph
    CURRENT PSYCHOLOGY, 2020, 39 (02) : 761 - 767
  • [35] SELF-MADE ACADEMIC PREDICTIONS AND ACADEMIC PERFORMANCE
    BIGGS, DA
    ROTH, JD
    STRONG, SR
    MEASUREMENT AND EVALUATION IN GUIDANCE, 1970, 3 (02): : 81 - 85
  • [36] Academic Entitlement and Academic Performance in Graduating Pharmacy Students
    Jeffres, Meghan N.
    Barclay, Sean M.
    Stolte, Scott K.
    AMERICAN JOURNAL OF PHARMACEUTICAL EDUCATION, 2014, 78 (06)
  • [37] The Impacts of an Academic Intervention Based in Metacognition on Academic Performance
    Swanson, Holly J.
    Ojutiku, Adelola
    Dewsbury, Bryan
    TEACHING & LEARNING INQUIRY-THE ISSOTL JOURNAL, 2024, 12
  • [38] THE IMPACT OF THE USAGE OF ACADEMIC LIBRARY ON STUDENTS' ACADEMIC PERFORMANCE
    Yaseen, Maryam
    Bano, Sumera
    Arshad, Irfan
    Abbas, Qaisar
    Usman, Sohaib
    INTERNATIONAL JOURNAL OF EARLY CHILDHOOD SPECIAL EDUCATION, 2022, 14 (04) : 1101 - 1112
  • [39] Academic procrastination and academic performance: An initial basis for intervention
    Goroshit, Marina
    JOURNAL OF PREVENTION & INTERVENTION IN THE COMMUNITY, 2018, 46 (02) : 131 - 142
  • [40] THE IMPACT OF THE USAGE OF ACADEMIC LIBRARY ON STUDENTS' ACADEMIC PERFORMANCE
    Yaseen, Maryam
    Bano, Sumera
    Arshad, Irfan
    Assistant, Qaisar Abbas
    Usman, Sohaib
    INTERNATIONAL JOURNAL OF EARLY CHILDHOOD SPECIAL EDUCATION, 2022, 14 (02) : 7788 - 7804