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«A Paper Submitted to the Graduate Faculty of the North Dakota State University of Agriculture and Applied Science By Keith Stefan Abeyratne In ...»

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Total Grade: The final grade received by each subject included their grades on exams and programming exercises.

Exam Grades: The grades received on midterm and final exams.

3.2. STUDY SUBJECTS AND COURSE ASSIGNMENTS

The participating subjects in these study were 72 students enrolled in the CS1 Introductory Computer Programming at NDSU. Subjects in one of the sections of the course completed programming exercises in pairs, whereas subjects in the other section of the course completed programming exercises individually. The subjects in this study worked in pairs and individually throughout the semester and completed programming exercises related to variable assignment, evaluating conditions, string manipulation, looping, and other object oriented programming concepts during the semester.

Group A: The subjects were thirty-five undergraduate students enrolled in the CS1 course at NDSU.

Group B: The subjects were thirty-seven undergraduate students enrolled in the CS1 course at NDSU.

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Step 1: Subjects were assigned to two groups. In the experimental group (Group A), all subjects were paired with a partner to work on programming exercises early in the semester. The control group (group B) worked individually on programming assignments early in the semester.

Step 2: Subjects Work on Programming Exercises: In the Group A, all subjects worked on programming exercises with their assigned pairs for the duration of the first half of the semester, and then completed programming exercises individually during the second half the semester. In group B, all subjects worked on programming exercises individually for the duration of the first half of the semester, whereas the remaining section the subjects were paired and worked collaboratively on given programming assignments. This was done both to provide a control group, and to ensure that all subjects had the opportunity to use pair programming in the class.

Step 3: Evaluate the subjects on group A (who used pair programming) and group B (who worked individually) on their given programming assignments for the first half of the semester, based on the understanding basic programming concepts which was taught during the course.

Step 4: The study subjects will be redistributed so that subjects who started with pair programming will now be doing individual study and subjects who were studying individually will be now using pair programming.

Step 5:Subjects Work on Programming Exercises: In the Group A, all subjects worked on programming exercises individually for the rest of the semester, In group B, all subjects worked on programming exercises were now paired with another subject allowing them to work as pairs for the rest of the semester.

Step 6: Evaluate the subjects on group A (who used pair programming) and group B (who worked individually) on their given programming assignments for the first half of the semester, based on the understanding basic programming concepts which was taught during the course.

On the day prior to beginning the programming exercise, subjects were shown a ten minute video in class that described how to use pair programming effectively on their programming assignment [11]. The next day during their lab session, subjects in both groups worked on a programming exercise that was specifically designed by the instructor such that it should not take more than one lab period (fifty minutes) to complete. Subjects were given a programming exercise related to the topics that were being covered in class that week and were given two lab periods (with each lasting fifty minutes) and three days of out-of class time to complete the programming exercise. Subjects were only monitored while working on the exercise during the designated lab periods. Subjects worked with their assigned partner to complete the programming exercise.

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In the table 2, the allocation of students for each half of the semester is described. Thirty five students were paired initially in the semester to work in pair for the first half of the semester in which they worked of programming assignments with pairs. During the second half of the semester those 35 students worked individually on programming assignments. Thirty seven students worked individually during the first half of the semester and then paired with a partner to work on the second half of the semester.

3.4. DATA COLLECTION AND EVALUATION CRITERIA

Student performances on lab assignments and tests (including mid-term and final examinations) were analyzed to study the effects of the mental-model-based pairings on the students’ performance. The final course grades for subjects in the study were also analyzed so that we can determine the shift in student performance with related to the introduction of pair programming.

–  –  –

We analyzed the midterm and end-of the term examination marks for the subjects who used pair programming initially in the semester vs. subjects who started off studying individually. Some background on students’ performance on these tasks, students generally did very well on the all examinations. Average grades for students in Group A who were introduced to pair programming at the beginning was 51.11 and 43.28 for midterm and final exams, respectively. Average scores for students in Group B who worked individually initially and then introduced to the pair programming later was 54.94 and 46.81 for midterm and final exams, respectively. Figure 3, the average test scores are compared for each group.





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There is a non-significant increase in scores of students who used Pair Programming later in the semester in comparison to the students who used Pair Programming at the beginning of the semester. When you consider the midterm marks of Group A and Group B, the Group B subjects have performed better, and there is an increase of 3.83 for midterm which was not statistically significant. Similarly, there is a small increase of 3.52 for final scores of group B subjects when compared to group A subjects. Table 4 summarizes these results.

–  –  –

When comparing the final scores as listed in Table 3, even though the Group B subjects had performed better than the Group A subjects, both groups did poorly in final exams. We have compared each group’s midterm marks vs. the final marks. When considering Group A total of 7.8% drop in final grades compared to midterm grades. This is calculated by the difference between midterm marks and final marks in group A.

= − Difference between final/midterm marks is calculated as below.

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In group B this fall is about 8.1% drop in marks. The calculation of the drop in marks is as follows using the above formula 1.

This observation in final marks also validates previous research, which also concluded that pair programming does little to improve student learning and usually only in limited ways such as better grades on programming exercises [13] and generally does not extend to exams.

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Figure 4 shows a graphical representation of grades achieved by each group. Based on these results, Group A had a larger number of “A” a total of 3 students out of 37 students obtained a grade of A, whereas in Group B students’ performance is much higher than the Group A students performance.

–  –  –

The comparison of letter grades between the two groups are as follows, in Group A 9.6% students obtained a grade A as compared to the 2.9% of students in Group B that obtained a grade A. These results show that the total number of students who got a grade C or higher was 18 in Group A in comparison to 22 students in Group B. In Table 4 the grades that each group obtained are summarized

–  –  –

Results of the first pair and individual assessments initially indicated that there was a very small difference between pair and individual marks. A similar study by Radermacher [27, 30] also validates our finding in this study. The results from Radermacher et al.[2012] shows that students perceive pair programming as being beneficial and all of the subjects who used pair programming indicated that they would prefer using it again in the future as opposed to working individually. In addition pair programming is beneficial to student performance among students who may be struggling with the course. Research also indicates that pair programming allows a student pair to complete a given amount of work more quickly than individuals. [27]

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A major threat to validity deals with difficulties in being able to gather precise measurements of each student’s performance based on the time when pair programming was introduced. First, attendance was not taken during this course, so it is possible that whether or not subjects attended lectures had some influence in the overall scores of midterm and final by the subjects. The subjects of the experiments were mostly new to pair programming, and thus might perform worse because they were not adapted to the duration of short experiments, conduct so they may not have enough time to learn how to conduct pair programming well, as a result they could not improve statistically.

–  –  –

This presents an analysis of the data to provide answers to the hypothesis posed in Section 3.0.The data analyzed includes the subject’s the grade received on the marks obtained during midterm and final exam marks. Subjects’ pair performances on midterm and final exams and their individual performances on tests (including mid-term and final examinations) were analyzed to determine if the introducing pair programming at the beginning of the semester is more beneficial to the student than introducing it at a later stage.

The results from this study do not indicate that one group is significantly more effective than any other. There was not much difference between the exams scores in group A and Group B students. However results showed that students perceive pair programming as being beneficial and all of the subjects who used pair programming indicated that they would prefer using it again in the future as opposed to working individually Pair programming introduced at any time of the course was beneficial to students. It also shows that pair programming is beneficial to student performance among students who may be struggling with the course.

The results of this study provides support to encourage further studies, particularly to increase the number of data points in order to determine when is the best time to introduce pair programming. Also it is possible for students to perform well in the initial weeks of the course and then struggle with more difficult topics. When pair programming was introduced in later stages, students had a better knowledge on basic concepts in programming and were able to demonstrate those skills better. This would have resulted in better overall performance.

However, the results do not show a significant improvement when using Pair Programming later vs. earlier.

Although this study has provided some valuable insights, results should not be unconditionally generalized due to the small number of students who participated in this study. It is recommended that the study should be replicated and involve a larger sample of participant’s studies over a longer time period. More biographical information could also be useful for analysis of differences between male and female, different personality types, and age groups.

–  –  –

[1] L. Williams and R. Kessler, Pair Programming Illuminated: Addison-Wesley, 2003.

[2] L. Williams, R.R. Kessler, W. Cunningham, and R. Jeffries, Strengthening the case for pair programming, IEEE Software, 17(4), July – Aug. 2000, pages 19 – 25, 2000 [3] K. Beck, Extreme Programming Explained: Embrace Change: Addison-Wesley, 1999.

[4] P. Abrahamsson, J. Warsta, M. T. Siponen, and J. Ronkainen, “New Directions on Agile Methods: A Comparative Analysis,” International Conference on Software Engineering, 2003.

[5] B. F. Hanks, “Tool Support for Distributed Pair Programming,” Workshop on Distributed Pair Programming. Extreme Programming and Agile Methods - XP/Agile Universe, 2002.

[6] Domino, M. A., R. Webb Collins &Hevner, A.R. (2007). Controlled experimentation on adaptations of pair programming. Springer.

[7] J. Chong, T. Hurlbutt, The social dynamics of pair programming, ICSE 2007 29th International Conference on Software Engineering, IEEE Computer Society, 2007.

[8] C. McDowell, L. Werner, H.F. Bullock, J. Fernald, The effects of Pair-Programming on Performance in an Introductory Programming Course, Proceedings 33rd SIGCSE Technical Symposium on Computer Science Education, ACM Press, 2002.

[9] C. McDowell, L. Werner, H.F. Bullock, J. Fernald, The impact of pair programming on student performance perception and persistence, Proceedings 25th International Conference on Software Engineering, 3 – 10 May 2003, pages 602 – 607, 2003.

[10] C. McDowell, L. Werner, H.F. Bullock, J. Fernald, Pair programming improves student retention, confidence, and program quality, Communications of the ACM, Vol. 49, No.

8, pages 90-95, 2006.

[11] D. Wells. The rules of extreme programming, 1999.

[12] Klemm,W.R. (1994). Using a formal collaborative learning paradigm for veterinary medical education. Journal of Vertinary Medical Education, 21(1).

[13] C. McDowell, L. Werner, H.F. Bullock, J. Fernald, The effects of Pair-Programming on Performance in an Introductory Programming Course, Proceedings 33rd SIGCSE Technical Symposium on Computer Science education, ACM Press, 2002.



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