Performing Tasks Can Improve Program Comprehension Mental Model of Novice
Program comprehension is challenging for many novice developers. Literature indicates that program comprehension is greatly influenced by the specific purpose of reading a program, i.e., the task. However, the task has often been used in research as a measure for program comprehension. Our study takes an inverse approach to investigate the effect of using the task as a facilitator to improve novice developers program comprehension. To measure the effect, our previously published program comprehension mental model of novice developers was utilized. In a sense, the study provides an empirical evaluation of our proposed model in terms of its ability to capture the novice developer’s mental model properly. The comprehensive experiment involved one hundred and seventy-eight (178) novice developers from three (3) universities and investigated the effect of six (6) tasks with difficulties ranked according to the cognitive categories of Revised Bloom Taxonomy. The results of the experiment confirmed that performing the tasks can improve program comprehension of novice developers. It demonstrated that different tasks improved different abstraction levels of the mental model and further indicated that higher cognitive category tasks improve program comprehension mental model at higher abstraction levels. The results also showed that the mental model we have proposed earlier is able to capture what novice developers know in response to the tasks they perform. The general implication of the study is that the tasks can be an effective tool for computing educators to incorporate program comprehension in programming courses, whereby these tasks need to be introduced in stages in the teaching of programming; starting initially from the lower cognitive categories’ tasks such as Recall and culminating at the higher cognitive categories’ tasks such as Modification by first taking into consideration the novices’ programming levels.
Wed 15 JulDisplayed time zone: (UTC) Coordinated Universal Time change
00:00 - 01:00 | Session 9: For DevelopersTool Demonstration / Research / ERA at ICPC Chair(s): Anderson Oliveira PUC-Rio | ||
00:00 12mPaper | An Empirical Study on Dynamic Typing Related Practices in Python Systems Research Zhifei Chen Nanjing University, Yanhui Li Department of Computer Science and Technology, Nanjing University, Bihuan Chen Fudan University, Wanwangying Ma Nanjing University, Lin Chen Nanjing University, Baowen Xu Nanjing University Media Attached | ||
00:12 12mPaper | Performing Tasks Can Improve Program Comprehension Mental Model of Novice Research Amal A. Shargabi Qassim University, Syed Ahmad Aljunid Universiti Teknologi MARA, Muthukkaruppan Annamalai Universiti Teknologi MARA, Abdullah Mohd Zin Universiti Kebangsaan Malaysia Media Attached | ||
00:24 12mPaper | SimplyHover: Improving Comprehension of else Statements Tool Demonstration Ahmad Jbara Computer and Cyber Sciences, Augusta University, Georgia, USA, Bar Ben Michael , Or Shacham , Omer Tavor Media Attached | ||
00:36 12mPaper | Combining biometric data with focused document types classifies a success of program comprehension ERA Toyomi Ishida Nara Institute of Science and Technology, Hidetake Uwano National Institute of Technology, Nara College, Japan, Yoshiharu Ikutani Nara Institute of Science and Technology Media Attached | ||
00:48 12mPaper | Program Comprehension in Virtual Reality ERA James Dominic Clemson University, Brock Tubre Clemson Universtiy, Jada Houser Clemson University, Charles Ritter Clemson University, Deborah Kunkel Clemson University, Paige Rodeghero Clemson University Media Attached |