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Measuring and Improving Student Performance in an Introductory Programming Course
Author(s) -
Raad A. Alturki
Publication year - 2016
Publication title -
informatics in education
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.53
H-Index - 19
eISSN - 2335-8971
pISSN - 1648-5831
DOI - 10.15388/infedu.2016.10
Subject(s) - mathematics education , computer science , competence (human resources) , grading (engineering) , affect (linguistics) , psychology , engineering , social psychology , civil engineering , communication
Students’ performances in introductory programming courses show large variation across students. There may be many reasons for these variations, such as methods of teaching, teacher competence in the subject, students’ coding backgrounds and abilities, students’ self-discipline, the teaching environment, and the resources available to students, all of which can affect student performance and outcomes. Our observations in teaching programming courses (at AlImam Muhammad Ibn Saud Islamic University in Riyadh) are that many students (up to 50% per course) drop out. There is a strong belief by many instructors that such a high dropout rate is due, at least in part, to students underestimating the effort needed to finish this course and not following instructions as recommended. This paper reviews the factors that affect student performance in an introductory programming course (CS1) and aims to discover correlations between various assessment methods, students’ participation and their final performance measured. It analyses mark distributions across various assessment methods to identify which assessment method best predicts final exam marks and overall marks, and gives recommendations for assessment in introductory programming courses.

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