TY  - JOUR
T1  - THE INVESTIGATION OF NOVICE PROGRAMMERS’ DEBUGGING BEHAVIORS TO INFORM INTELLIGENT E-LEARNING ENVIRONMENTS: A CASE STUDY
AU  - Türkmen, Gamze
AU  - Caner, Sonay
PY  - 2020
DA  - July
DO  - 10.17718/tojde.762039
JF  - Turkish Online Journal of Distance Education
JO  - TOJDE
PB  - Anadolu University
WT  - DergiPark
SN  - 1302-6488
SP  - 142
EP  - 155
VL  - 21
IS  - 3
LA  - en
AB  - This study aims to provide a comprehensive and in-depth investigation of the debugging process inprogramming teaching in terms of cognitive and metacognitive aspects, based on programming studentswho demonstrate low, medium, and high programming performance and to propose instructional strategiesfor scaffolding novice learners in an effective way. Data were collected from 41 novice programming studentsfrom C++ and Python programming language courses of the same instructor in the scope of case studymethodology, and data instruments included paper-based programming questions. The questions wereframed under three categories as questions’ difficulty levels (low, moderate and high), error types (syntaxand logic), and question types (if-else and while). As having three categories, a total of 12 different data(3x2x2) were taken from each student, which means 492 data rows were evaluated in the study. Chi-squaretest results revealed that while error detection and correction are significantly high in low difficulty levelquestions, error detection and error correction attempts for logic errors were substantially higher comparedto syntax errors. Further analysis conducted for paper-based markings that were used by students throughouttheir error detection, correction, and completion attempts. Chi-square test results revealed significantrelationships between marking availability and error types, as well as difficulty levels. Results were discussedfor both traditional learning and e-learning environments in terms of what kind of educational implicationsand strategies can be outlined by data for increasing the effectiveness of programming education for novicelearners.
KW  - Programming instruction
KW  - debugging
KW  - 
KW  - novice programmers
KW  - correlational study
KW  - intelligent e-learning environments
CR  - Liang, K., Zhang, Y., He, Y., Zhou, Y., Tan, W., & Li, X. (2017). Online behavior analysis-based student
profile for intelligent E-learning. Journal of Electrical and Computer Engineering, 2017.
UR  - https://doi.org/10.17718/tojde.762039
L1  - https://dergipark.org.tr/en/download/article-file/1181875
ER  -