Title :
Pretesting and data modeling for forecasting student success in computer science courses
Author :
Surkan, Alvin J.
Author_Institution :
Dept. of Comput. Sci. & Eng., Nebraska Univ., Lincoln, NE, USA
Abstract :
An experimental study in the design and use of questionnaires aims to capture salient information for predicting student success for computer science courses. Developing uniform and easy-to-use methods for collecting and processing information on student ability and preparation is the main objective. Such methods must be robust with respect to missing data. It should be influenced minimally by differences of cultural backgrounds and language proficiency.
Keywords :
computer science education; computer science courses; data modeling; information collection; information processing; missing data; pretesting; questionnaires design; questionnaires use; student ability; student success forecasting; Biological cells; Computer architecture; Computer networks; Computer science; Genetic algorithms; Optimization methods; Predictive models; Problem-solving; Robustness; Testing;
Conference_Titel :
Frontiers in Education Conference, 1999. FIE '99. 29th Annual
Conference_Location :
San Juan, Puerto Rico
Print_ISBN :
0-7803-5643-8
DOI :
10.1109/FIE.1999.839170
