Factors impacting novice code comprehension in a tutor for introductory computer science

EDM 2011 - Proceedings of the 4th International Conference on Educational Data Mining

Volumn , Issue , 2011, Pages 365-366

  Sudol Delyser, Leighann ^a   Steinhart, Jonathan ^b  

^a CARNEGIE MELLON UNIVERSITY   (United States)

^b Tutor Technologies   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BEST MODEL; CODE COMPREHENSION; EXPERIMENTAL CONDITIONS; INTRODUCTORY COMPUTER SCIENCE; MODEL SELECTION; STUDENT PERFORMANCE; STUDENT SUCCESS;

COMPUTER SCIENCE; DATA MINING;

TEACHING;

EID: 84857461209     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (3)

1. R. J. Barker and E. A. Unger. A predictor for success in an introductory programming class based upon abstract reasoning development. pages 154-158, 1983.
2. M. Lopez, J. Whalley, P. Robbins, and R. Lister. Relationships between reading, tracing and writing skills in introductory programming. In ICER '08: Proceeding of the Fourth international Workshop on Computing Education Research, pages 101-112, New York, NY, USA, 2008. ACM.
3. A. Venables, G. Tan, and R. Lister. A closer look at tracing, explaining and code writing skills in the novice programmer. In ICER '09: Proceedings of the fifth international workshop on Computing education research workshop, pages 117-128, New York, NY, USA, 2009. ACM.