Lecture Recordings, Viewing Habits, and Performance in 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.

Students in introductory programming courses struggle with how to turn a problem statement into code. We introduce a teaching technique, Seven Steps, that provides structure and guidance on how to approach a problem. The first four steps focus on devising an algorithm in English, then the remaining steps are to translate that algorithm to code, test the algorithm, and debug failed test cases. This approach not only gives students a way to solve problems, but also ideas for what to do if they get stuck during the process. Furthermore, it provides a way for instructors to work examples in class that focus on the process of devising the code - instructors can show how to come up with the code, rather than just showing an example. We describe our experience with this technique in several introductory programming courses - both in the classroom and online.

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

It is well-established that a sense of belonging is important for students' academic success. This is especially true for international students in introductory programming courses. In higher education, students' sense of belonging is closely associated with their interest in the subject and related career. This study explores the use of a narrative-based gamification approach to enhance students' sense of belonging in introductory programming courses. The gamified design was piloted with 32 Chinese students enrolled in a big data analytic course using Python at a British university. Results showed that the narrative-based gamified approach greatly improved students' sense of belonging in terms of peer relationships and related-ness to the subject, and increased their learning motivation, career interest, class engagement, and learning retention.

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.

Learning programming is a difficult task since programming requires new concepts in thinking and creative skills in problem solving. A number of learning tools and environments have been built to assist both teachers and students in introductory programming courses. In this study, we have established a classification for these tools. Tools are divided into four categories: A) integrated development interface; B) visualization; C) virtual learning environments; and D) systems for submitting, managing, and testing of exercises. The classification is based on a review of existing tools, both commercial and freely available. Guidelines for the selection of a suitable tool are discussed.

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.

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.

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.

Programming is a rewarding and yet demanding field in the ICT labormarket, but it is considered a challenging and difficult area of learning for significant numbers of novice programmers. As a result, high attrition rates from introductory programming (IP) courses are reported despite extensive research which attempts to address the issue. In this research, an action research methodology was used with three cycles to investigate and improve the teaching and learning process of the IP course. There were nine activities performed during the span of these three cycles. All three entities of the didactic triangle (student, instructor, and content) together with learning context were incorporated into the research design to understand the problem better and execute the proposed solution. The result shows that three cycles of the action research methodology helps in understanding and improving the students learning outcomes in the IP course. Moreover, the attrition rate was also reduced in the IP course.

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%.

The teaching and learning of programming are often considered a difficult topic for both teachers and students, due to its complexity and abstract nature. The traditional teaching approaches are unable to contribute substantially to the development of the necessary cognitive models by the students, producing high rates of failure and dropout in introductory programming courses. In the last 30 years, the scientific community has not stopped looking for new pedagogical approaches and teaching techniques in introductory computer programming courses. Various studies have shown that pair programming under appropriate conditions may create an environment conducive to learning, leading to an increase student interest in programming. In this paper, the author presents the results of a pilot teaching intervention. The sample was collected among first-grade students of a high school in Greece. The results showed that the pair programming is more efficient than the solo programming, both on facilitating and supporting students' learning and understanding of basic programming concepts, as well as on improving students' attitudes toward programming.

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.

We are engaged in the design of Grace, a new object-oriented open source programming language aimed at instructors and students in introductory programming courses. Grace aims to include features that have been found useful in software practice, while allowing multiple different teaching approaches without requiring that concepts be introduced to students before they are ready. While many aspects of Grace's design will be familiar to most object-oriented programmers, Grace cleanly separates the concepts of object, class, and type, and so Grace offers more options for creating objects than most other languages. We have written these patterns to explain how Grace programmers should go about creating objects.

Student retention in introductory programming courses remains a persistent challenge in higher education, with high failure and dropout rates impacting both learners and institutions. This article presents a novel, behavior-based approach to addressing this issue through Educational Data Mining (EDM) and a custom-built learning validation framework called AssessMe. Developed by the authors in collaboration with SmoothSoft Ltd., AssessMe is an advanced software tool that monitors the real-time development of programming assignments. It captures detailed behavioral data—including active coding time, code changes (added, modified, removed lines), and submission timelines—to generate learning indicators reflecting how students approach problem-solving tasks. Unlike traditional assessment methods that focus solely on final code correctness, AssessMe emphasizes the coding process, offering deeper insights into student engagement, effort, and learning strategies. This study focuses on Programming I and II courses within the Web & Mobile Computing program at RIT Croatia. The dataset includes 3,537 student submissions from the 2024/2025 academic year, covering homework, practicals, and in-class activities, all enriched with AssessMe indicators. We apply traditional machine learning models combined with the TSFRESH library to extract meaningful time-series features from students’ coding activity. This enables the identification of temporal learning patterns and supports early prediction of academic outcomes. Our models achieve over 93% accuracy in forecasting pass/fail status by the fifth week of a 15-week semester, demonstrating a strong correlation between AssessMe indicators and final grades. This behavior-based assessment approach enhances early intervention strategies and provides actionable insights for improving student retention and learning outcomes.