Won the SIG-Computer and Internet Application in Education Best Paper Award at the 2019 AERA Conference

The paper titled "Block-Based Versus Text-Based Programming Environments on Novice Student Learning: A Meta-Analysis Study" won the best SIG-Computer and Internet Application in Education paper award at 2019 American Educational Research Association (AERA) conference. The paper was presented by Zhen Xu and Albert Ritzhaupt

Paper Title
Block-Based Versus Text-Based Programming Environments on Novice Student Learning: A Meta-Analysis Study

Abstract
The use of block-based programming environments is purported to be a good way to gently introduce computer programming to novice learners. This study examined the overall effect of block-based versus text-based programming environments on cognitive and affective student learning outcomes. Five academic databases were searched to identify literature meeting our inclusion criteria and resulted in 13 publications with 52 effect size comparisons on both cognitive and affective student learning outcomes. We found both effect size calculations were statistically insignificant using random effects models with a small effect size in favor of block-based programming environments on cognitive student learning outcomes, and a trivial effect size on affective student learning outcomes. Discussion of the findings and implications for further research are provided.

Authors
Zhen Xu, University of Florida
Albert D. Ritzhaupt, University of Florida
Fengchun Tian, Nanjing Xiaozhuang University
Karthikeyan Umapathy, University of North Florida

Conference & Location:
2019 American Educational Research Association (AERA), Toronto, Canada

Link to the conference program:
https://convention2.allacademic.com/one/aera/aera19/index.php?cmd=Online+Program+View+Paper&selected_paper_id=1436081&PHPSESSID=stln16gon24j8nbcuugc8ajtp1

Presented a paper on Meta-analysis on Pair vs Solo Programming at the 2017 ACM SIGCSE Symposium

Paper Title:
A Meta-Analysis of Pair-Programming in Computer Programming Courses: Implications for Educational Practice.

Abstract:
Several experiments on the effects of pair programming versus solo programming in the context of education have been reported in the research literature. We present a meta-analysis of these studies that accounted for 18 manuscripts with 49 separate effect sizes in the domains of programming assignments, exams, retention, and affective measures. In total, our sample accounts for N=3308 students either using pair programming as a treatment variable or using traditional solo programming in the context of a computing course. Our findings suggest positive results in favor of pair programming across all four of the domains. We provide a comprehensive review of our results, and discuss our findings.

Authors:
Karthikeyan Umapathy and Albert D. Ritzhaupt

Conference:
2017 ACM SIGCSE Technical Symposium, Seattle, WA, USA

Date:
March 9, 2017

Link to Presentation:
https://prezi.com/xm3fn3ctzm1k/a-meta-analysis-of-pair-programming-in-computer-programming/