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Incorporating statistical and neural network approaches for student course satisfaction analysis and prediction

หน่วยงาน Central Queensland University, Australia

รายละเอียด

ชื่อเรื่อง : Incorporating statistical and neural network approaches for student course satisfaction analysis and prediction
นักวิจัย : Guo, Wanwu.
คำค้น : Neural networks (Computer science) , Computer systems. , Expert systems (Computer science) , Applied research. , 890205 Information Processing Services (incl. Data Entry and Capture) , 080108 Neural, Evolutionary and Fuzzy Computation. , 080105 Expert Systems. , 080110 Simulation and Modelling. , Neural networks -- Multilayer perceptron -- Linear regression -- Student course satisfaction -- Nonlinear function approximation
หน่วยงาน : Central Queensland University, Australia
ผู้ร่วมงาน : -
ปีพิมพ์ : 2553
อ้างอิง : http://hdl.cqu.edu.au/10018/40622 , http://dx.doi.org/10.1016/j.eswa.2009.10.014 , cqu:5172
ที่มา : Guo, WW 2010, 'Incorporating statistical and neural network approaches for student course satisfaction analysis and prediction', Expert Systems with Applications, vol. 37, no. 4, pp.3358-3365.http://dx.doi.org/10.1016/j.eswa.2009.10.014 (viewed 12/2/10)
ความเชี่ยวชาญ : -
ความสัมพันธ์ : Expert systems with applications. Netherlands. : Elsevier, 2010. Vol. 37, issue 4 (April 2010), p. 3358-3365 8 pages Refereed 0957-4174 , ACQUIRE [electronic resource] : Central Queensland University Institutional Repository.
ขอบเขตของเนื้อหา : -
บทคัดย่อ/คำอธิบาย :

Student’s perception on course satisfaction through student surveys has become more influential in institutional operations because their experience in study may affect not only the prospective student’s decision in choosing the institution for their tertiary education, but also the retention of existing students. Student course satisfaction is a multivariate nonlinear problem. Neural network (NN) techniques have been successfully applied to approximating nonlinear functions in many disciplines, but there has been little information available in applying NN to the modelling of student course satisfaction. In this paper, based on the student survey results collected from 43 courses in 11 semesters from 2002 to 2007, statistical analysis and NN techniques are incorporated for establishing some dynamic models for analysing and predicting student course satisfaction. The factors identified from this process also allow new strategies to be drawn for improving course satisfaction in the future. This study shows that both the number of students (NS) enrolled to a course and the high distinction (HD) rate in final grading are the two most influential factors to student course satisfaction. The three-layer multilayer perceptron (MLP) models outperform the linear regressions in predicting student course satisfaction, with the best outcome being achieved by combining both NS and HD as the input to the networks.

บรรณานุกรม :
Guo, Wanwu. . (2553). Incorporating statistical and neural network approaches for student course satisfaction analysis and prediction.
    กรุงเทพมหานคร : Central Queensland University, Australia.
Guo, Wanwu. . 2553. "Incorporating statistical and neural network approaches for student course satisfaction analysis and prediction".
    กรุงเทพมหานคร : Central Queensland University, Australia.
Guo, Wanwu. . "Incorporating statistical and neural network approaches for student course satisfaction analysis and prediction."
    กรุงเทพมหานคร : Central Queensland University, Australia, 2553. Print.
Guo, Wanwu. . Incorporating statistical and neural network approaches for student course satisfaction analysis and prediction. กรุงเทพมหานคร : Central Queensland University, Australia; 2553.