Introductory programming: a systematic literature review

As computing becomes a mainstream discipline embedded in the school curriculum and acts as an enabler for an increasing range of academic disciplines in higher education, the literature on introductory programming is growing. Although there have been several reviews that focus on specific aspects of introductory programming, there has been no broad overview of the literature exploring recent trends across the breadth of introductory programming. This paper is the report of an ITiCSE working group that conducted a systematic review in order to gain an overview of the introductory programming literature. Partitioning the literature into papers addressing the student, teaching, the curriculum, and assessment, we explore trends, highlight advances in knowledge over the past 15 years, and indicate possible directions for future research

The role of social networks in students’ learning experiences

The aim of this research is to investigate the role of social networks in computer science education. The Internet shows great potential for enhancing collaboration between people and the role of social software has become increasingly relevant in recent years. This research focuses on analyzing the role that social networks play in students’ learning experiences. The construction of students’ social networks, the evolution of these networks, and their effects on the students’ learning experience in a university environment are examined

The impact of pair programming on students logical thinking : a case study on higher academic institution / Mahfudzah Othman … [et al.]

Pair Programming (PP) is a well-known agile software development technique that has been widely implemented in programming classes. Through PP, students are able to share knowledge and expertise that will contribute to better programming solutions. Nevertheless, how PP can help to improve students’ cognitive abilities has yet to be explored. Therefore, this study’s aim was to investigate the impacts of implementing Pair Programming (PP) on students’ logical thinking. Logical thinking is part of the cognitive ability claimed to be one of the crucial factors that determine the success or failure of novice programmers. To achieve this, 60 students who enrolled in Diploma in Computer Science programme in Universiti Teknologi MARA Perlis Branch, Malaysia, were asked to take the pre-test and post-test of Group Assessment Logical Thinking (GALT) Test in the beginning and at the end of the semester. These students were divided into two main groups; Control and Test in the Test Group, students with low logical ability will be paired with their high logical thinking friends. Meanwhile, in the Control Group, no pair programming or collaborative technique took place. Five programming tasks were assigned to both groups to solve either collaboratively or individually. The results obtained via paired sample t-tests statistical analysis shows significant improvements in students’ logical thinking with p-value <0.05 in the Test Grou

Online Programming Judge System (UOJ)

This research conducts a study to build an Online Programming Judge system with a mechanism to generate test cases automatically using Particle Swarm Optimization (PSO) algorithm. The system has the function to judge programming code by evaluating the output that the program produced. Based on the problem that it is time consuming for lecturers to manually compile, run and verify every student programs for judging. Moreover, they also need to define test cases for different programming exercises in order to judge student‘s code. The system is built on the purpose to assist lecturers in Universiti Teknologi PETRONAS in judging code submitted from students and generate test cases for every programming exercise automatically. It also helps UTP students practice and enhancing their programming skills. In this research, details of judging process are explored. Moreover, the mechanism of test cases generation using PSO algorithm is deeply analyzed. The study would focus on the primary structure of PSO and the proposed fitness function to calculate fitness value for each generated test case. There are comparisons between manual and automatic PSO test case generation results that would be conducted to evaluate the efficiency of the proposed method. Finally, conclusion of current results and recommendation for future development are also stated

Predicting and Interpreting Students Performance using Supervised Learning and Shapley Additive Explanations

abstract: Due to large data resources generated by online educational applications, Educational Data Mining (EDM) has improved learning effects in different ways: Students Visualization, Recommendations for students, Students Modeling, Grouping Students, etc. A lot of programming assignments have the features like automating submissions, examining the test cases to verify the correctness, but limited studies compared different statistical techniques with latest frameworks, and interpreted models in a unified approach. In this thesis, several data mining algorithms have been applied to analyze students’ code assignment submission data from a real classroom study. The goal of this work is to explore and predict students’ performances. Multiple machine learning models and the model accuracy were evaluated based on the Shapley Additive Explanation. The Cross-Validation shows the Gradient Boosting Decision Tree has the best precision 85.93% with average 82.90%. Features like Component grade, Due Date, Submission Times have higher impact than others. Baseline model received lower precision due to lack of non-linear fitting.Dissertation/ThesisMasters Thesis Computer Science 201

Jutge.org

Jutge.org is an open access educational online programming judge where students can try to solve more than 800 problems using 22 programming languages. The verdict of their solutions is computed using exhaustive test sets run under time, memory and security restrictions. By contrast to many popular online judges, Jutge.org is designed for students and instructors: On one hand, the problem repository is mainly aimed to beginners, with a clear organization and gradding. On the other hand, the system is designed as a virtual learning environment where instructors can administer their own courses, manage their roster of students and tutors, add problems, attach documents, create lists of problems, assignments, contests and exams. This paper presents Jutge.org and offers some case studies of courses using it.Postprint (published version

Analyzing User Comments On YouTube Coding Tutorial Videos

Video coding tutorials enable expert and novice programmers to visually observe real developers write, debug, and execute code. Previous research in this domain has focused on helping programmers find relevant content in coding tutorial videos as well as understanding the motivation and needs of content creators. In this thesis, we focus on the link connecting programmers creating coding videos with their audience. More specifically, we analyze user comments on YouTube coding tutorial videos. Our main objective is to help content creators to effectively understand the needs and concerns of their viewers, thus respond faster to these concerns and deliver higher-quality content. A dataset of 6000 comments sampled from 12 YouTube coding videos is used to conduct our analysis. Important user questions and concerns are then automatically classified and summarized. The results show that Support Vector Machines can detect useful viewers\u27 comments on coding videos with an average accuracy of 77%. The results also show that SumBasic, an extractive frequency-based summarization technique with redundancy control, can sufficiently capture the main concerns present in viewers\u27 comments

Canonical explorations of 'Tel' environments for computer programming

This paper applies a novel technique of canonical gradient analysis, pioneered in ecological sciences, with the aim of exploring student performance and behaviours (such as communication and collaboration) while undertaking formative and summative tasks in technology enhanced learning (TEL) environments for computer programming. The research emphasis is, therefore, on revealing complex patterns, trends, tacit communications and technology interactions associated with a particular type of learning environment, rather than the testing of discrete hypotheses. The study is based on observations of first year programming modules in BSc Computing and closely related joint-honours with software engineering, web and game development courses. This research extends earlier work, and evaluates the suitability of canonical approaches for exploring complex dimensional gradients represented by multivariate and technology-enhanced learning environments. The advancements represented here are: (1) an extended context, beyond the use of the ‘Ceebot’ learning platform, to include learning-achievement following advanced instruction using an industrystandard integrated development environment, or IDE, for engineering software; and (2) longitudinal comparison of consistency of findings across cohort years. Direct findings (from analyses based on code tests, module assessment and questionnaire surveys) reveal overall engagement with and high acceptance of collaborative working and of the TEL environments used, but an inconsistent relationship between deeply learned programming skills and module performance. The paper also discusses research findings in the contexts of established and emerging teaching practices for computer programming, as well as government policies and commercial requirements for improved capacity in computer-science related industries