-Arthur Lewis (alew525)

Contents Background and Introduction Overview of Popular Environments Empirical Studies Borland Delphi v/s SimplifIDE Gild v/s Eclipse BlueJ Eclipse and other IDEs Discussion

Introduction Programming is not easy for new comers to grasp Moreover, exposure to a professional development environment/IDE can be an added burden A number of pedagogical IDEs have been designed to address this issue

Overview of Popular Environments From current studies, BlueJ and DrJava are the most popular pedagogic environments Both have been designed for novice programmers picking up Java DrJava focused on providing a less “intimidating” interface as compared to Eclipse BlueJ focused on simplifying the learning of OO concepts via a visual interface

Overview of Popular Environments DrJava’s prominent feature is a read-eval-print (RELP) loop Intuitive testing and debugging capabilities also supported along with error detection However, no research done to test its effectiveness Empirical studies are a must to ascertain its actual impact with respect to learning

Overview of Popular Environments BlueJ had a visual interface designed to make OO concepts in Java easier for novices Another study compared the features of BlueJ with DrJava Main Window of the BlueJ Interface (Source: Kölling, M., Quig, B., Patterson, A., & Rosenberg, J. (2003). The BlueJ system and its pedagogy. Computer Science Education, 13(4), )

Overview of Popular Environments Other tools included Penumbra, DrScheme and Gild Penumbra was designed for Eclipse but never really took off DrScheme’s purpose was to simplify the functional programming language Scheme Researchers made claims which require empirical evidence to support validity Gild was made to create a “Student Perspective” for Eclipse

Borland Delphi v/s SimplifIDE Two related studies (part of the same work) compared a pedagogical environment (SimplifIDE) with a professional one (Borland Delphi) Studied 2 groups: treatment and control Took students academic abilities into account based on past performance by implicitly classifying them into two further categories

Borland Delphi v/s SimplifIDE One study focused on academic performance and programming behavior of students The other study took into account the perceived sense of learning derived by students Results: Weaker students benefited more from the pedagogical environment Improved programming behavior observed in weaker students Overall academic performance remained unaffected

Borland Delphi v/s SimplifIDE Categorizing the students into weak and strong categories was a crucial aspect of this study The sample size was adequately large and the study was conducted in a naturalistic environment Some students opted out Choice of pedagogical environments doesn’t affect academic performance

Gild v/s Eclipse Study considered metrics such as efficiency, effectiveness, understanding and satisfaction Hypothesized Gild will perform better than Eclipse Consisted of problems followed by a qualitative feedback to measure understanding and satisfaction Students preferred Gild over Eclipse

Gild v/s Eclipse Study sample was small (N=6) Participation was voluntary Some students were familiar with other IDE tools Students had trouble using some complex features of Eclipse such as a debugger Customizing Eclipse’s interface to help students would lower its standards as a professional IDE

Empirical Studies: BlueJ One study tested BlueJ in an academic setting An initial evaluation using a beta version Students were reported to have a higher passing rate as compared to previous years However, this was the first time Java was taught and BlueJ was being used Second evaluation evaluated students understanding of abstract OO concepts

Empirical Studies: BlueJ Students pursuing their second programming unit were asked to complete a survey Results were positive Study claimed students had a better comprehension of the study material More evidence is needed to support these claims

Empirical Studies: BlueJ Another study compared BlueJ with TextPad Sample populated comprised students of different disciplines Opting out wasn’t an option Course was taught in two sections, one using BlueJ and the other with TextPad Two different samples were used for each section

Empirical Studies: BlueJ Student performance was assessed BlueJ didn’t have a significant impact on student performance Students liked some features of the environment Sample size was small i.e. within the range Sample had students from non computing disciplines

Eclipse and Other Professional IDES Some researchers argue that Eclipse or other IDE tools are suited for classroom purposes However these studies had limitations: Small sample size Mental manipulation of students One of them did agree with the notion of academic performance being independent of the IDE

Discussion and Conclusion Most of the existing pedagogical environments support OO languages (preferably Java) More empirical analysis needed to ascertain their limitations and actual impact on learning An individual’s programming aptitude is strongly related to his/her analytical skills Tools may affect programming behaviors

Thank You!!!

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