Is Pair Programming More Effective than Solo Programming for Secondary Education Novice Programmers?

California State University Monterey Bay (CSUMB) uses an outcomes-based delivery philosophy and focuses on measurable student learning. Because of the required outcome it was determined that the students needed more scaffolding or metacognitive support than is typically afforded in the introductory programming courses. The students were simply not capable of making the jump from simple programming concepts to being able to deliver a satisfactory completed portfolio piece. This paper reports on a study that investigated use of pair programming as a delivery methodology for an introductory Java programming course

High failure and drop-out rates from introductory programming courses continue to be of significant concern to computer science disciplines despite extensive research attempting to address the issue. In this study, we include the three entities of the didactic triangle, instructors, students and curriculum, to explore the learning difficulties that students encounter when studying introductory programming. We first explore students' perceptions of the barriers and affordances to learning programming. A survey is conducted with introductory programming students to get their feedback on the topics and associated learning resources in the introductory programming course. The instructors' perceptions are included by analyzing current teaching materials and assessment tools used in the course. As a result, an ADRI based approach is proposed to address the problems identified in the teaching and learning processes of an introductory programming course.

Problem solving skills are considered an integral part of grasping the precise concepts of the programming domain for novices in introductory programming (IP) courses. But these skills are mostly covered only in early lectures of such courses or are included in just a few early chapters of some relevant textbooks. Consequently, high failure and dropout rates are often reported in IP courses. In this study, we developed and introduced an application, called PROBSOL, which is designed to focus on, and enhance, novice programmers’ problem solving skills. Two versions of the application were developed, a web-based version and a mobile app. The applications were based on pseudo-code techniques. A survey was implemented to collect students’ feedback and semi-structured interviews were conducted to collect instructors’ opinion about the applications. Moreover, final exam grades over two semesters were compared to determine the impact of including the PROBSOL applications in the course. The results show that both students and instructors appreciated the applications and that their use supports students’ cognitive gains and engagement. Moreover, they promote students’ affective engagement in the IP course. The use of the applications improves novices’ programming understanding, logic capabilities and problem solving skills. However, students preferred the mobile version rather than the web-based version during the course. The comparison of students’ grades showed that the students’ achievements were improved and attrition rates were reduced after introducing the PROBSOL applications in the course.

This Systematic Literature Review (SLR) investigates the role of pair programming in higher education, focusing on its impact on students' learning outcomes, collaboration, and programming skill development. As programming courses become increasingly complex, the demand for effective teaching methods has led to the growing popularity of collaborative learning techniques, such as pair programming. However, questions remain regarding its scalability, adaptability, and long-term benefits in educational settings. A thorough search of academic publications from 2021 to 2024 was conducted to explore these issues using databases such as Scopus and Web of Science (WoS). The study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework, starting with 42 articles, of which 22 met the inclusion criteria for further analysis. Articles were excluded for irrelevance, mismatched titles, lack of empirical data, or unavailability of full texts. The review categorized its findings into three key themes: (1) Remote and distributed Pair Programming (RPP), (2) psychological and social dynamics, and (3) pedagogical approaches and tools. The results suggest pair programming enhances students' learning performance, particularly in introductory programming courses, by improving problem-solving skills and coding proficiency. However, challenges such as unequal participation and student resistance persist. The success of pair programming largely depends on proper implementation and teacher facilitation. While the review indicates that pair programming holds promise as an instructional strategy in higher education, it emphasizes the need for further research to assess its long-term impact and address its implementation challenges.

Students often find that learning to program is hard. Introductory programming courses have high drop-out rates and students do not learn to program well. This paper presents experiences from three educational institutions where introductory programming courses were improved by adopting Python as the first programming language and roles of variables as an aid in understanding program behavior. As a result of these changes, students were able to write working code from the very beginning, they found programming easy and interesting, they passed exams with good grades, and drop-out rates were low. Students became interested in programming and some of them even changed their personal study plan to include more of programming and computer science.

Computer programming is considered as a difficult area of study for novices. One of the reasons is the main focus of the curriculum presented in an introductory programming (IP) course which emphasizes more on the programming knowledge (syntax and semantic) of the programming language. This study introduced a new teaching curriculum in the IP course which focuses on different skills required by the novices. We compared the IP course materials based on the traditional and new approaches against five categories. The result shows that the new approach encourages both the programming knowledge and problem solving strategies, and promotes deep learning. Furthermore, it discourages programming shortcut (Problem statement → Code), and support three-step approach (Problem statement → Solution Plans → Code) in solving a problem statement. The new approach also promotes algorithmic thinking in the IP course by paying equal attention on the problem solving strategies.

This Research to Practice Full Paper analyzes the impact of using a problem-based learning (PBL) approach on student motivation and engagement in an introductory programming course (CS1). Learning programming is a difficult task, and CS1 courses have experienced high dropout and failure rates. Some authors associate this to students' lack of motivation and recommend the use of active learning methods to stimulate their motivation and engagement. Educators have been interested in using the PBL approach, an active instructional method based on problem solving, for its motivational potential. In this context, we surveyed students with the ARCS IMMS and UWES-S questionnaires to respectively measure their levels of motivation and engagement in a CS1 course. Results show that, on the categories of motivation, the PBL approach relates to students' attention and relevance. It also relates to confidence and satisfaction, either positively or negatively, depending on course planning. The approach, on the other hand, does not have much relation with the categories of engagement. Finally, we also found that there must be careful problem design and planning in order to positively relate to student motivation and engagement.

In our research, we have introduced and implemented a new software development method, testing before coding (TBC), to bring in the benefits of using software development lifecycle in computer programming and improved students program quality. TBC follows the basic concept of agile method (such as test-driven development, TDD) and makes students a "cultural shift" in developing their computer programs i.e., students must test their own codes and consider testing as an indispensable part of program development. Our method has been exercised in the introductory computer programming courses and has improved the students' programs quality at least 24%.

Progressive programming assignments were used in an introductory Java programming course where every assignment built on the previous one. The major goal was to help students learn difficult, abstract concepts. This technique allows students to concentrate on the current topic while building on their previous work. This also provides an incentive for students to keep up with their work. Students often feel that they can skip the current topic and pick up after it is over, but it is difficult to do this in a programming course because every new concept builds on the previous ones. This approach also has built-in scalability, which is difficult to achieve in introductory programming courses due to time constraints and the students limited knowledge. These assignments were given in a CS2-type course where the topics predominantly deal with abstract concepts. This paper discusses the assignments, goals, faculty observations, student comments, and results.

Usually, students face different difficulties when learning computer programming, this leads many of them to drop out of computing major, or continue with fear of programming assignments in subsequent courses. The main reason of these difficulties is inappropriate method used by students to study this subject. In this paper, we describe our experience of using e-journal to train students on self-regulated learning skills when studying computer programming. Although using this tool has many challenges, it proves its effectiveness in improving students' self-regulated learning skills, and consequently enhances students' performance in introductory computer programing course.

Program Visualization (PV) is an educational tool frequently used to assist users for understanding a program flow. However, despite its clear benefits, PV cannot be incorporated easily on Introductory Programming course. Several key properties such as student characteristics and behavior should be considered beforehand. This paper is intended to provide an empirical review about the impact of PV toward students of Introductory Programming course. For our case study, PythonTutor is selected as a sample of PVs due to its accessibility. It can be accessed anywhere and anytime through a web browser. Three conclusions are obtained based on our evaluation on data collected from a survey. Firstly, PV is quite effective to assist students for conducting several programming sub-tasks. Secondly, PV, at some extent, may help students to learn advanced topics on Introductory Programming course. Finally, despite the fact that several features should be incorporated to enhance understanding of students, PV is beneficial for learning Introductory Programming course, especially when it is frequently used.

Learning to program requires the development of multiple skills including critical thinking, problem-solving, as well as learning the syntax and semantics of the programming language. For novices, to acquire all these skills is considered a challenging and difficult task. They have to focus on both problem-solving strategies and the syntax and semantics of the programming language to acquire these skills. In this study, this article compares the current teaching and learning approach of an introductory programming (IP) course with the six categories of Bloom's taxonomy. The assurance of learning (AOL) process was incorporated in the IP course to assess students' learning outcomes on the basis of achiever (high, medium and low) and performance (very good, good enough and not good enough) categories. The results showed that the current teaching and learning approach of the IP course addressed all the six categories of Bloom's taxonomy. Most of the students (63%) fall under the medium achiever category. Moreover, 50% students learning outcomes come under ‘not good enough' performance category.

The introductory programming course (IPC) holds a special significance in computing disciplines as this course serves as a prerequisite for studying the higher level courses. Students generally face difficulties during their initial stages of learning how to program. Continuous efforts are being made to examine this course for identifying potential improvements. This article presents the review of the state-of-the-art research exploring various components of IPC by examining sixty-six articles published between 2014 and 2020 in well-reputed research venues. The results reveal that several useful methods have been proposed to support teaching and learning in IPC. Moreover, the research in IPC presented useful ways to conduct assessments, and also demonstrated different techniques to examine improvements in the IPC contents. In addition, a variety of tools are evaluated to support the related course processes. Apart from the aforementioned facets, this research explores other interesting dimensions of IPC, such as collaborative learning, cognitive assessments, and performance predictions. In addition to reviewing the recent advancements in IPC, this study proposes a new taxonomy of IPC research dimensions. Furthermore, based on the successful practices that are listed in the literature, some useful guidelines and advices for instructors have also been reported in this article. Lastly, this review presents some pertinent open research issues to highlight the future dimensions for IPC researchers.

This paper describes an action research for developing better algorithmic thinking in introductory programming courses. Enhancing algorithmic thinking and improving problem solving skills are the main objectives of such courses and are considered a significant success factor in future courses as well as future work achievements. Furthermore, failing to develop these skills, usually leads to failures in these introductory courses as well as the courses that follow. As part of this action research, that was performed during four semesters several course structures and learning tactics were examined. The evaluation methodology was simple and based only on the percentage of failing students. The success achieved was attributed to two main factors (1) using a visualization environment (Micro-world) for the whole duration of the course, which helped in understanding the more complex and abstract issues, and (2) using individual assignments that enforced better learning habits and development of individual algorithmic thinking. The paper describes the various attempts, as well as the final structure, that reduced the failing students by over 77%. This paper describes an action research for developing better algorithmic thinking in introductory programming courses. Enhancing algorithmic thinking and improving problem solving skills are the main objectives of such courses and are considered a significant success factor in future courses as well as future work achievements. Furthermore, failing to develop these skills, usually leads to failures in these introductory courses as well as the courses that follow. As part of this action research, that was performed during four semesters several course structures and learning tactics were examined. The evaluation methodology was simple and based only on the percentage of failing students. The success achieved was attributed to two main factors (1) using a visualization environment (Micro-world) for the whole duration of the course, which helped in understanding the more complex and abstract issues, and (2) using individual assignments that enforced better learning habits and development of individual algorithmic thinking. The paper describes the various attempts, as well as the final structure, that reduced the failing students by over 77%.

A core challenge in introductory programming courses during the freshmen year is getting students to understand how a static textual representation (source code) maps to a highly dynamic process (program execution). Most students nowadays are visual learners who learn programming concept better through web-based visual and interactive learning instead of learning from traditional black board lecturing styles. This presentation will report our experience with positive learning outcomes in teaching an introductory programming course in Python by using a dynamic visual programming development environment based on flow-charts (RAPTOR) and active learning with an interactive eBook (zyBook). In this study, eleven sections of COSC 111 were included over three semesters as control and experimental groups. Analysis showed a marginally significant difference (F (1,5) = 5.87; p = 0.060) between sections taught via the traditional method and sections taught with the proposed pedagogical innovation. We also found that there are statistically significant positive correlations in between uses of the interactive book (eBook) and performances of students in tests. To add to our understanding of what students were experiencing, we also administered a survey to students at the end of the course. Regarding learning styles and tools, survey result showed that the eBook was helpful in understanding programming concepts (71.5%), that the instant feedback that the online book provided was helpful (82.9%), that the class discussion and interaction were helpful (85.7%). Overall, it seems that the proposed pedagogical approaches have made a positive difference by increasing student motivation and engagement, and reducing failure rates.