Visual and textual programming languages: a systematic review of the literature

Aim/Purpose: The purpose of this study is to identify how Advanced level Mathematics and Mathematics course units offered at university level do impact on the academic performance of theoretical Computer Science course units. Background: In Sri Lankan state universities, students have been enrolled only from the Physical Science stream to do a degree program in Computer Science. In addition to that, universities have been offering some course units in Mathematics to provide the required mathematical maturity to Computer Science undergraduates. Despite of this it is observed that the failure rates in fundamental theoretical Computer Science course units are much higher than other course units offered in the general degree program every year. Methodology : Academic records comprised of all 459 undergraduates from three consecutive batches admitted to the degree program in Computer Science from a university were considered for this study. Contribution: This study helps academics in identifying suitable curricula for Mathematics course units to improve students’ performance in theoretical Computer Science courses. Findings: Advanced level Mathematics does not have any significant effect on the academic performance of theoretical Computer Science course units. Even though all Mathematics course units offered were significantly correlated with academic performance of every theoretical Computer Science course unit, only the Discrete Mathematics course unit highly impacted on the academic performance of all three theoretical Computer Science course units. Further this study indicates that the academic performance of female undergraduates is better than males in all theoretical Computer Science and Mathematics course units. Future Research: Identifying other critical success factors contributing to the students’ academic performance of the theoretical Computer Science through empirical studies

There is a growing demand for software developers who have experience writing parallel programs rather than just "parallelizing" sequential systems as computer hardware gets more and more parallel. In order to develop the skills of future software engineers, it is crucial to teach pupils parallelism in elementary computer science courses. We searched the Scopus database for articles on "teaching parallel and distributed computing" and "parallel programming," published in English between 2008 and 2019. 26 papers were included in the study after quality review. As a result, a lab course using the C++ programming language and MPI library serves as the primary teaching tool for parallel and distributed computing.

The pipeline of three introductory computer science courses at our university have low pass rates. As part of our efforts to improve the pass rates in these courses, we examine the students' mathematics preparation and their progress from one course to the next. We find that the minority of students who enter the university with good mathematics preparation are likely to succeed in our introductory computer science courses. For the majority of students, we suggest a series of interventions throughout the pipeline. Prior to taking Computer Science 1, students could gain more experience with problem solving during the Introduction to Computer Science and Introduction to Computer Engineering courses. We suggest adding precalculus as a prerequisite for Computer Science 2. For students who do not earn an A in Computer Science 2, we plan to examine whether taking a class in a second programming language before taking Computer Science 3 will improve performance in Computer Science 3. Our goal is to improve student learning and retention through these efforts, combined with continual innovation in the classroom.

ABSTRACTBackground and Context: The relationship between novices’ first programming language and their future achievement has drawn increasing interest owing to recent efforts to expand K–12 computing education. This article contributes to this topic by analyzing data from a retrospective study of more than 10,000 undergraduates enrolled in introductory computer science courses at 118 U.S. institutions of higher education.Objective: We explored the relationship between students’ first programming languages and both their final grades in an introductory computer science course and their attitudes about programming.Method: Multiple matching techniques compared those whose first language was graphical (e.g., Scratch), textual (e.g., Java), or absent prior to college.Findings: Having any prior programming experience had positive effects on both attitudes about programming and grades in introductory computer science courses. Importantly, students whose first language was graphical had higher grades than did students whose first language was textual, when the languages were introduced in or before early adolescent years.Implications: Learning any computer language is better than learning none. If programming is to be taught to students before early adolescence, it is advised to start with a graphical language. Future work should investigate the transition between different types of programming languages.

This paper presents a new programming language named SPARCL that has four major elements: it is a visual language, it is a logic programming language, it relies on sets to organize data, and it supports partitioning constraints on the contents of sets. It is a visual programming language in that the representation of the language depends extensively on non-textual graphics and the programming process relies on graphical manipulation of this representation. It is a logic programming language in that the underlying semantics of the language is the resolution of clauses of a Horn-like subset of first order predicate logic. It uses sets as the only method of combining terms to build complex terms. Finally, one may constrain a set's structure by specifying a partitioning into pairwise disjoint subsets.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

This paper describes our experiences using Active Learning in four first-year computer science and industrial engineering courses at the School of Engineering of the Universidad Católica de la Santísima Concepción, Chile. This work corresponds to the implementation stage of the curriculum reform using a CDIO-based approach currently underway at the School of Engineering. Before this reform, students had only one introductory course to their field of study, meeting one hour a week. After the reform, computer science students take an Introduction to Computer Science course and a Programming Laboratory. Similarly, the industrial engineering program now includes an Introduction to Industrial Engineering and an Engineering Communication course. These courses have been designed using CDIO standards 1, 4 and 8 as guidelines and have been formulated to include active learning in its many forms such as project-based learning, problem-based learning, case studies, small group discussions, oral presentations and reflective memos. The redesign impact was assessed via anonymous student surveys and reflective memos. Our results show improved student understanding of their professional endeavour and increased student motivation for their engineering programs. Student surveys registered high degrees of satisfaction with active learning techniques, working in teams, and receiving immediate feedback from instructors and peers.

This study investigated the relationships between computer science (CS) course effectiveness and academic performance in a Guangdong Province private school through an integrated environmental and social psychology framework, examining collaborative learning environment and technology environment perception as mediating mechanisms. A quantitative cross-sectional design surveyed several hundred Grade 4 international high school students enrolled in computer science courses at Guangdong Country Garden School during the 2024-2025 academic year. Results revealed that all five CS course effectiveness dimensions—hands-on experiences, real-world applications, collaborative learning, problem-solving abilities, and technology landscape readiness—demonstrated strong positive correlations with academic performance (r=.790-.879, p&lt;.01), with problem-solving abilities emerging as the strongest predictor (β=.342). Mediation analysis using Hayes' PROCESS macro with bootstrapping procedures confirmed that collaborative learning environment (14.7%-23.7% mediation) and technology environment perception (14.7%-23.9% mediation) functioned as significant partial mediators, with real-world applications showing strongest social-psychological mediation and hands-on experiences exhibiting strongest environmental mediation. Hierarchical regression demonstrated that environmental and social-psychological factors contributed unique variance beyond course effectiveness dimensions (ΔR²=.043, p&lt;.001). Findings provide empirical support for person-environment fit theories and social cognitive frameworks, highlighting the importance of optimizing both technological infrastructure and interpersonal climate for CS education effectiveness in private school contexts.

The number of computer science (CS) courses has been dramatically expanding in U.S. high schools (HS). In comparison with well-established courses in mathematics and science, little is known about how the decisions made by HS CS teachers regarding how and what to teach impact student performance later in introductory college CS courses. Drawing on a large sample of 2,871 introductory college CS students at 115 U.S. institutions who had taken a CS course in HS, we examined the topic coverage and prevailing instructional methods in the HS course and investigated how these experiences influenced student performance in college CS. Controlling for differences in student background, we find two predictors of higher grades in college CS: greater frequency of coding-related activities in HS (programming, debugging, studying algorithms) and lower frequency of “non-coding” computer use (e.g., data analysis, computer security). Interaction models revealed a more complex story. Coding-related activity more heavily benefited students who did not have coding help available at home. In the 28% of college CS courses in which instructors employed innovative pedagogies, students with higher ACT or SAT mathematics scores had a greater advantage than in traditionally taught courses. Finally, in the innovative college courses, students whose HS CS exams had typically included testing on vocabulary did worse than students whose exams had not included such tests.

The adoption of innovative online teaching tools in Computer Science (CS) courses provides opportunities for data-informed instruction as a regular teaching practice in CS classrooms. In this paper, we present a design study for an interactive visual analytics dashboard, called UserFlow, that supports feedback collection from teaching documents and assists instructors in interpreting feedback and acting on it in a timely manner. The design study is conducted with eight domain experts comprising of four teaching instructors, two learning analytics (LA) experts and two instructional designers. UserFlow offers a set of novel visualization designs for presenting the four interleaving aspects of document engagement (i.e., annotations, document traversal path, reading/focus time and student information). We evaluated UserFlow in an undergraduate computer science course with over 700 students. Our results demonstrate the usefulness and need for such a tool for CS educators to inform teaching approaches and courseware improvement.

Managing the graphical complexity of real-life programs expressed in visual programming languages is a great challenge in each visual programming environment. Besides general methods like displaying/layouting graphs and icons on different levels of abstraction or organizing multiple window environments, built-in language mechanisms which permit the structured and modular design of visual programs are essential to overcome this problem. We address these problems by discussing a concept for visual modules in a diagrammatic parallel language as well as a method to describe massive parallel programs consisting of hundreds of processes by means of a visual replication mechanism. >

This research shows an audience of fellow computer science teachers that there is benefit in testing college student's scientific reasoning skills and that the students increase their logical thinking skills in computer science classes when they are presented with real world problems, engaged in group activities, and given hands-on experiments.Students' scientific reasoning skills from several different computer science courses are analyzed and tested before and after taking the computer science course to measure their improvement in logical thinking. The higher order thinking skills test results are compared, and the overall class and individual student improvement between the classes that use different teaching strategies are analyzed. Also, the test results are compared with students' ability to perform adequately in a computer science course. This information is valuable to advisors when placing students in computer science courses.In the assessments of students' entering knowledge and evaluations of students' thinking improvement, the students' individual higher order thinking skills as well as their overall level of cognitive development are analyzed. Through the analysis of their individual skills and level of thinking, one can expand conclusions about the students' and teacher's performance over time.

Visual programming language research has evolved greatly since its early days. At first, attempts at visual programming mostly took the form of flowchart-like diagrams. But in recent years, a wide number of innovative approaches have been incorporated into visual languages, including object-oriented programming, form-based programming, programming by demonstration, and dataflow programming. Unfortunately, while many of these systems represent important ideas, only a few have been successful as complete visual programming languages. This tutorial explains why this is true, and describes ways in which the problem can be addressed. This tutorial explores the issues behind the successes and failures of earlier approaches from a design perspective. It identifies characteristics of successful visual programming languages, and explains how to design an object-oriented language that maintains those characteristics. It shows solutions to a number of problems by looking at existing visual programming languages, including Prograph.

: A general purpose visual programming language, based on object-oriented methodology, offers substantial Benefits of reusable code, shorter creation and maintenance time, faster overall understanding of the code, and reduced staff learning time. It should be an ideal fit for sites with long-lived code or very large bodies of code. The value of visual programming languages is well understood for very specific tasks; this report reviews the plan for research and design of a general purpose visual object-oriented programming language through nine steps, which includes general specifications for the preferred language and environment.

Supporting computer science and computer application courses requires spending many resources on specialized software. Courses, such as database concepts and applications, depend upon hands-on experience with software to help students understand important principles. Both the university computer labs and students need to install software for homework assignments. Problems include software availability, cost, installation, platform compatibility, and configuration. While academic licensing provides software to students at significantly lower prices, the price may still be too high for some students. Installation and configuration on client/student side may also be a problem. Further, IT departments face the challenge of installing, upgrading and patching the software in student labs.

The purpose of this study was to justify of the formation technique of representation of modeling methodology at computer science lessons. The necessity of studying computer modeling is that the current trends of strengthening of general education and worldview functions of computer science define the necessity of additional research of the problems relating to study of computer modeling bases within the basic course of computer science. Such necessity is caused by that “Mathematics and Computer Science” education range is a backbone line of the course. Consideration of modeling issues within computer science course is the basis of cogitative operations development called in pedagogies as methods of mental actions or intellectual abilities. But at schools and in pedagogical higher education institutions of Republic of Kazakhstan this section of computer science course is not considered properly. The issues related to a formation technique of basic concepts of modeling, and also usage of applied software environments for development and research of models except an Excel editor are not developed. Practically there are no techniques creating a broad view on concept of model, there is no methodically acceptable models’ typology. The research results indicate that when disclosing the material on themes about modeling stages the process is should be considered as cyclic, there is need of interpretation of models’ relevance concept, “undelivered”, “vital” tasks are should be considered, which fully reflect intersubject links.