Using Peer Code Review to Support Pedagogy in an Introductory Computer Programming Course

Because the concept of program correctness is generally taught as an activity independent of the programming process, most introductory computer science (CS) students perceive it as unnecessary and even irrelevant. The concept of contracts, on the other hand, is generally taught as an integral part of the programming process. As such, most introductory CS students have little difficulty understanding the need to establish contracts via preconditions and postconditions. In order to improve teaching program correctness concepts, we implemented ProVIDE, an enhanced integrated development environment (IDE) for Java [7]. Pro VIDE supports a modified version of the "design by contract" methodology [13] that assists its student programmers in contract construction. Rather than asking for both a precondition and postcondition for each of his/her methods, ProVIDE asks the student to simply supply a postcondition. ProVIDE then helps the student construct the appropriate precondition by leading him/her through an axiomatic proof of the correctness of the method. Thus, the proof of correctness of the method is a side-effect of the student's need to construct an appropriate precondition.

The development of computational thinking skills is essential for information management, problem-solving, and understanding human behavior. Thus, the aim of the experience described here was to incorporate computational thinking practices to improve learning in a first Python programming course using programming tools such as PSeInt, CodingBat, and the turtle graphic library. A quasi-experimental methodological design was used in which the experimental and control groups are in different academic semesters. Exploratory mixed research was carried out. The control and experimental group consisted of 41 and 36 students, respectively. The results show that with the use of support programming tools, such as PSeInt, CodingBat, Python turtle graphic library, and the incorporation of computational thinking practices, the experimental group students obtained better learning results. It is concluded that student performance and motivation in university programming courses can be improved by using proper tools that help the understanding of programming concepts and the skills development related to computational thinking, such as abstraction and algorithmic thinking.

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.

The ability to solve problems is the key to developing software, and it is an ability that can be difficult to learn. Introductory Computer Science students are often taught syntax and semantics, along with simple problems designed to develop logical, structured thinking, but authentic problem-solving skills are rarely developed at these early stages. In this paper we describe an approach to introductory computer science education that addresses student engagement through integrating cooperative learning techniques and authentic problem solving processes throughout each aspect of the curriculum. Over a period of 4 years, the introductory computer science course at the University of Adelaide has been modified to support a cooperative learning style. A three-stage methodology has been implemented in place of traditional lectures to achieve this. The process focuses on observing the application of programming techniques, observing problem solving techniques and then applying cooperative problem solving exercises in the classroom. The results from this change in teaching methodology have been an increase in attendance rates at lectures and practical sessions as well as improved learning outcomes as measured by exam results. Student experience surveys show students have greater motivation for learning and believe they have a better understanding of concepts since the changes have occurred.

Computer programming skill is an essential skill for information technology and for some other natural science department students. However, teaching and learning computer programming ideas and skills has been recognized as a great challenge to both teachers and students. Therefore, the development of efficient learning strategies and environments for computer programming courses have become an important concept. This study is intended to recommend strategies for improving academic performance which can be used in teaching computer programming course effectively to undergraduate students in information technology related departments or informatics departments (including information Technology, computer science, and software engineering and information systems This concluded that there is a need for strategies for improving academic performance which requires planning and implementation to strengthen the motivation of the students to study, boost their academic performance, and uplift the quality of education in information technology departments. Finally, relevant and important workable recommendations have been suggested by the researcher.

Background and Context Peer code review activities provide well-documented benefits to students in programming courses. Students develop relevant skills through exposure to alternative coding solutions, producing and receiving feedback, and collaboration with peers. Despite these benefits, low student motivation has been identified as one of the challenges leading to poor engagement and substandard review quality. Objective This research investigates gamification as a technique for motivating students to generate high-quality reviews. Method We conduct a randomised controlled study, explore the nature and length of the feedback produced by students, and measure how students perceive the value of the feedback they receive and produce. We manually categorise students’ feedback into several categories adapted from a published taxonomy for student peer review. This categorisation indicates whether the feedback contains actionable advice and identifies strengths and weaknesses in the code. Findings We found that the quality of the feedback differed significantly between experimental and control conditions. Students in the experimental condition wrote longer comments and tended to produce more specific advice for their peers. Implications The findings can assist educators in understanding how the chosen game mechanics can be a potential strategy to motivate students to produce high-quality written feedback in peer code review activities.

Peer Code Review (PCR) is a proven pedagogical method for improving programming skills and collaboration. However, most gamified PCR systems emphasise reviewers while giving limited recognition to authors. This paper presents CODUAL, a conceptual dual-role gamified PCR framework that applies points, leaderboards, and badges for both roles. Using Likert-scale ratings and alignment-based rewards, CODUAL promotes balanced engagement and sustained effort. Grounded in Self-Determination Theory (SDT), it supports autonomy, competence, and relatedness to strengthen motivation. Future empirical evaluation, planned with undergraduate programming students at University Technical Malaysia Melaka (UTeM), will compare CODUAL with a non-gamified PCR platform using the Technology Acceptance Model (TAM) and BPNSFS.

Research was conducted to determine the effect of a constructivist learning environment upon field dependent (FD) and field independent (FI) students' achievement in an introductory computer programming course. Prior research in traditional environments had established a correlation between field dependence / independence (FD/I) and the design stage of programming. A correlational design was followed, using introductory computer science students in their first programming course. A pretest of BASIC programming ability was given to assess baseline proficiency. The Group Embedded Figures Test (GEFT) was given to assess each subject's measure of FD/I. A constructivist model for learning programming was implemented. Achievement tests in two of the stages of programming, design and coding were administered. As additional dependent variables, student construction of programming elements — the design (semantic) elements, and the language-specific coding (syntax) elements - were collected in a portfolio and examined for both qualitative and quantitative differences. No significant correlations were found between FD/I and the achievement scores of design and coding. No correlation was expected between FD/I and coding. There was no interaction between FD/I and design versus coding. The correlation between FD/I and the quantity of reconstructed programming elements was not significant. The correlation between FD/I and the quality of reconstructed programming elements was not significant. No interaction was found between FD/I and the quantity or quality of semantic versus syntactic elements. Stepwise multiple regression identified two predictors, for design, the predictor was the pretest. Coding was predicted by the quantity of syntactic programming elements. The principal finding of this research, in contrast to findings in traditional environments is that within this constructivist environment, the cognitive style of FD/I was not found to influence programming achievement.

Computer science provides an in-depth understanding of technical aspects of programming concepts, but if we want to understand how programming concepts evolve, how programmers think and talk about them and how they are used in practice, we need to consider a broader perspective that includes historical, philosophical and cognitive aspects. In this paper, we develop such broader understanding of monads, a programming concept that has an infamous formal definition, syntactic support in several programming languages and a reputation for being elegant and powerful, but also intimidating and difficult to grasp. This paper is not a monad tutorial. It will not tell you what a monad is. Instead, it helps you understand how computer scientists and programmers talk about monads and why they do so. To answer these questions, we review the history of monads in the context of programming and study the development through the perspectives of philosophy of science, philosophy of mathematics and cognitive sciences. More generally, we present a framework for understanding programming concepts that considers them at three levels: formal, metaphorical and implementation. We base such observations on established results about the scientific method and mathematical entities -- cognitive sciences suggest that the metaphors used when thinking about monads are more important than widely accepted, while philosophy of science explains how the research paradigm from which monads originate influences and restricts their use. Finally, we provide evidence for why a broader philosophical, sociological look at programming concepts should be of interest for programmers. It lets us understand programming concepts better and, fundamentally, choose more appropriate abstractions as illustrated in number of case studies that conclude the paper.

As one mainstream of current software development, Object-oriented programming has become one key course for undergraduate students in Computer Science. Since Object-oriented concepts are difficult to understand for students, small programming exercises are used to train and help the students, and the study performance is evaluated based on the quality of the submitted source code. The common practice of code assess-ment in programming courses is checking whether the submitted projects pass carefully-designed test cases. However, even some projects pass all test cases, they may have bad software design and do not use the knowledge of Object-oriented programming well, especially in the early stage of courses. Therefore, we propose an anomaly detection approach for early warning in Object-oriented programming courses, which can automatically find the abnormal application of Object-oriented knowledge. In our approach, we conduct static analysis on the code submitted by students. Typical Objected-oriented metrics are extracted, and students are divided into two groups by K-means clustering: being good at Object-objected knowledge or not, and finally detect anomalous students based on the distance from cluster centers. We evaluate our approach on the realistic data sets collected from our Object-oriented programming course, and experimental results show the effectiveness of our method.

At present, programming ability has always been a basic requirement for all college students in university education. Most major students will be required to take a programming course, but lack of programming ability is also a bottleneck commonly encountered by college students, even computer science students also have such confusion, how to improve their programming skills and understand programming thinking, which will be the focus of this article. This article uses creative design and project practice as a way to help students to accomplish problem discovery and problem solving by programming thinking. This can stimulate students' creative desire, understand the aim of programming and consciously integrate programming thinking into their own life, so as to exercise and improve their programming thinking ability. This paper applies the above ideas to the public elective course "iOS Mobile App Development" for college students, and proposes a set of thinking training methods from the project design, practice arrangement and competition incentives.

Aim/Purpose: The goal of this study was twofold: first, to examine how learners’ behavioral engagement types affect their final grades in an online programming course; and second, to explore which factors most strongly affect student performance in an online programming course and their connection to the types of cognitive engagement. Background: During the COVID-19 pandemic situation, information technology educational methods and teaching have been transforming rapidly into online or blended. In this situation, students learn course content through digital learning management systems (LMSs), and the behavioral data derived from students’ interactions with these digital systems is important for instructors and researchers. However, LMSs have some limitations. For computer science students, the traditional learning management system is not enough because the coding behavior cannot be analyzed. Through the OpenEdu platform, we collected log data from 217 undergraduates enrolled in a Python programming course offered by Feng Chia University in Taiwan in the spring semester of 2021. Methodology: We applied the evaluation framework of learning behavioral engagement conducted on a massive open online course (MOOC) platform and integrated it with the partial least squares structural equation modeling (PLS-SEM) approach. PLS-SEM is widely used in academic research and is appropriate for causal models and small sample sizes. Therefore, this kind of analysis is consistent with the purpose of our study. Contribution: In today’s fast-paced world of information technology, online learning is becoming an important form of learning around the world. Especially in computer science, programming courses teach many skills, such as problem-solving, teamwork, and creative thinking. Our study contributes to the understanding of how behavioral engagements in distance programming learning affect student achievement directly and through cognitive engagement. The results can serve as a reference for practitioners of distance programming education. Findings: Our results demonstrate that: (1) online time and video-watching constructs had significant effects on the self-assessment construct, self-assessment and video-watching constructs had significant effects on the final grade construct, and online document reading was not a significant factor in both self-assessments and final grades; (2) video watching had a most significant effect than other behavioral constructs in an online programming course; (3) cognitive engagement types are inextricably linked to the development of a behavioral engagement framework for online programming learning. The mediation analysis and the importance-performance map analysis supported the importance of cognitive engagement. Recommendations for Practitioners: (1) Online education platform developers and university policymakers should pay close attention to the development of self-assessment systems and design such systems based on students’ cognitive skills. (2) Instructors are advised to put substantial effort into the creation of videos for each course session and to actively promote students’ interest in the course material. Recommendation for Researchers: The empirical results reported in this study allow a better understanding of the connection between behavioral engagement and final achievement. However, there are still great challenges in trying to explore more kinds of engagement, like emotional or social engagement. It would be interesting to deepen the results obtained by integrating programming behavior like debugging and testing. Impact on Society: Online programming courses allow students to improve their coding skills and computer science background. Students’ behavioral engagement strongly affects their academic achievement, their ability to complete a course successfully, and the quality of the learning process. Our work can encourage more people who are different majors in society to learn coding in an online environment even not only computer science students. Moreover, the findings of this study can be recommendations for understanding students’ learning behavior and the development of distance programming learning. Future Research: We suggest for future studies: (1) include a wider range of participants, such as students enrolled in MOOCs environments; (2) include more log data items that can express various students’ behavior, depending on the reliability and validity of the research model; and (3) conduct more detailed studies of the effects of emotional engagement as well as additional aspects of students’ social engagement to elucidate the factors affecting students’ behavioral participation and performance more thoroughly.

This community service activity aims to improve digital literacy and 21st-century skills for school students in Blitar Village through basic programming (coding) training. Technology-based educational transformation is a crucial need to support the readiness of the younger generation to face the development of the digital era. The training was conducted over three sessions with a hands-on learning approach using basic materials on algorithms, programming logic, and an introduction to block-based visual programming languages. Participants consisted of 40 junior high and high school students selected based on their interest in information technology. Evaluation was carried out through pre- and post-tests and observations of participant engagement. The results of the activity showed a 45% increase in understanding of programming concepts and increased motivation to learn about digital technology. Students were also able to create simple projects such as interactive animations and mini-games. In addition to impacting student competency improvement, this activity also encouraged schools to begin integrating coding into extracurricular activities. Overall, this program succeeded in providing a meaningful learning experience and was the first step in the transformation of digital education in Blitar Village. This activity is expected to be sustainable through continued mentoring and collaboration with local educational institutions.

Student background undoubtedly influences the performance of students in computer science. The literature verily indicates that there are many key aspects of student background that influence students’ performance in a programming course. These include the socioeconomic status, demographic profile, types of gadgets students have, home possessions, and internet connectivity. This study aims to find answers to some pertinent questions related to different aspects of background and their association with computer science students’ performance. A questionnaire-based survey was used to collect data for analysis from a first-year computer programming course at a regional university in the South Pacific. This paper presents the students’ demographic and socioeconomic profiles and investigates their association with students’ performance. The results show that a student’s background is a significant factor in influencing their computing course performance.

The impact of Software Testing education on code reliability: An empirical assessment