Non-computer Science Research Articles

A Study on the Current State of Artificial Intelligence Based Coding Technologies and the Direction of Future Coding Education

Artificial Intelligence (AI) technology is used in a variety of fields because it can make inferences and plans through learning processes. In the field of coding technologies, AI has been introduced as a tool for personalized and customized education to provide new educational environments. Also, it can be used as a virtual assistant in coding operations for easier and more efficient coding. Currently, as coding education becomes mandatory around the world, students’ interest in programming is heightened. The purpose of coding education is to develop the ability to solve problems and fuse different academic fields through computational thinking and creative thinking to cultivate talented persons who can adapt well to the Fourth Industrial Revolution era. However, new non-computer science major students who take software-related subjects as compulsory liberal arts subjects at university came to experience many difficulties in these subjects, which they are experiencing for the first time. AI based coding technologies can be used to solve their difficulties and to increase the learning effect of non-computer majors who come across software for the first time. Therefore, this study examines the current state of AI based coding technologies and suggests the direction of future coding education.

A Phenomenographic Analysis of College Students’ Conceptions of and Approaches to Programming Learning: Insights From a Comparison of Computer Science and Non-Computer Science Contexts

Programming learning has become an essential literacy for computer science (CS) and non-CS students in the digital age. Researchers have addressed that students’ conceptions of learning influence their approaches to learning, and thus impact their learning outcomes. Therefore, we aimed to uncover students’ conceptions of programming learning (CoPL) and approaches to programming learning (APL), and analyzed the differences between CS and non-CS students. Phenomenographic analysis was adopted to analyze 31 college students (20 CS-related, and 11 not) from northern Taiwan. Results revealed six categories of CoPL hierarchically: 1. memorizing concepts, logic, and syntax, 2. computing and practicing programming writing, 3. expressing programmers’ ideas and relieving pressure, 4. applying and understanding, 5. increasing one’s knowledge and improving one’s competence, and 6. seeing in a new way. Four categories of APL were also found, namely: 1. copying from the textbook, teachers, or others, 2. rote memory, 3. multiple exploration attempts, and 4. online or offline community interactions. Furthermore, we found that most CS students held higher level CoPL (e.g., seeing in a new way) than non-CS students. However, compared with non-CS students, CS students adopted more surface approaches to learning programming, such as copying and rote memory. Implications are discussed.

User experiences using FLAME: A Case study modelling conflict in large enterprise system implementations

The complexity of systems now under consideration (be they biological, physical, chemical, social, etc), together with the technicalities of experimentation in the real-world and the non-linear nature of system dynamics, means that computational modelling is indispensible in the pursuit of furthering our understanding of complex systems. Agent-based modelling and simulation is rapidly increasing in its popularity, in part due to the increased appreciation of the paradigm by the non-computer science community, but also due to the increase in the usability, sophistication and number of modelling frameworks that use the approach. The Flexible Large-scale Agent-based Modelling Environment (FLAME) is a relatively recent addition to the list. FLAME was designed and developed from the outset to deal with massive simulations, and to ensure that the simulation code is portable across different scales of computing and across different operating systems. In this study, we report our experiences when using FLAME to model the development and propagation of conflict within large multi-partner enterprise system implementations, which acts as an example of a complex dynamical social system. We believe FLAME is an excellent choice for experienced modellers, who will be able to fully harness the capabilities that it has to offer, and also be competent in diagnosing and solving any limitations that are encountered. Conversely, because FLAME requires considerable development of instrumentation tools, along with development of statistical analysis scripts, we believe that it is not suitable for the novice modeller, who may be better suited to using a graphical user interface driven framework until their experience with modelling and competence in programming increases.

Barriers to Digital Literacy: Learning to Program

There are many challenges associated with teaching and learning computer programming for first year engineering students in non-computer based fields. This paper discusses barriers to acquiring the digital literacy needed to learn end-user programming, or programming as a tool to support activities in a non-computer science domain. The first barrier discussed is the gap in educational curriculum, where the first formal introduction to computer science and programming is found in pre-university preparatory courses. The second barrier is a lack of consensus in approaches to learning programming in online resources. A solution of integrating opportunities to use programming as a tool in existing course curriculum activities is proposed, as a way to improve programming accessibility and allow future engineers to use digital skills to innovate in non-computer based applications.

Case Study on Problem-based Programming Classes in Software Education for Non-Computer Science Majors

Case Study on Problem-based Programming Classes in Software Education for Non-Computer Science Majors

Enhanced Learning through Blended IC and DCN Strategies in C Programming for Non-Computer Science Students

Enhanced Learning through Blended IC and DCN Strategies in C Programming for Non-Computer Science Students

ACC_TEST: Hybrid Testing Techniques for MPI-Based Programs

Recently, MPI has become widely used in many scientific applications, including different non-computer science fields, for parallelizing their applications. An MPI programming model is used for supporting parallelism in several programming languages, including C, C++, and Fortran. MPI also supports integration with some programming models and has several implementations from different vendors, including open-source and commercial implementations. However, testing parallel programs is a difficult task, especially when using programming models with different behaviours and types of error based on the programming model type. In addition, the increased use of these programming models by non-computer science specialists can cause several errors due to lack of experience in programming, which needs to be considered when using any testing tools. We noticed that dynamic testing techniques have been used for testing the majority of MPI programs. The dynamic testing techniques detect errors by analyzing the source code during runtime, which will cause overheads, and this will affect the program's performance, especially when targeting massive parallel applications generating thousands or millions of threads. In this paper, we enhance ACC_TEST to have the ability to test MPI-based programs and detect runtime errors occurring with different types of MPI communications. We decided to use hybrid-testing techniques by combining both static and dynamic testing techniques to gain the benefit of each and reduce the cost.

Teaching basic of programming with the elements of Scratch - evaluation of VBA programming course for logistics students

Digital nations have become dependent on computer applications. One of the most important part of literacy in today's word are the basics of computer applications development and usage. Programming seems to be difficult to learn, therefore, several educational programming languages were developed, so that more people could develop the applications. Modern technologies mean that computer programming is not a skill reserved only for a small group of specialists. Programmers can become people of different ages and interests. The article addresses the problem of basic programming courses for non-computer science students. Its aim is to present the role of visual programming languages in encouraging university students to create algorithms and start programming. The research allows to conclude that Scratch makes introduction to programming more enjoyable, helps to concentrate on the problem and the business process. The comparative analysis showed also differences between groups of students.

ACC_TEST: Hybrid Testing Approach for OpenACC-Based Programs

In recent years, OpenACC has been used in many supercomputers and attracted many non-computer science specialists for parallelizing their programs in different scientific fields, including weather forecasting and simulations. OpenACC is a high-level programming model that supports parallelism and is easy to learn to use by adding high-level directives without considering too many low-level details. Testing parallel programs is a difficult task, made even harder if using programming models, especially if they have been badly programmed. If so, it will be challenging to detect their runtime errors as well as their causes, whether the error is from the user source code or from the programming model directives. Even when these errors are detected and the source code modified, we cannot guarantee that the errors have been corrected or are still hidden. There are many tools and studies that have investigated several programming models for identifying and detecting related errors. However, OpenACC has not been targeted clearly in any testing tool or previous studies, even though OpenACC has many benefits and features that could lead to increasing use in achieving parallel systems with less effort. In this paper, we enhance ACC_TEST with the ability to test OpenACC-based programs and detect runtime errors by using hybrid-testing techniques that enhance error coverage occurring in OpenACC as well as overheads and testing time.

Redesigning an Introductory Programming Course to Facilitate Effective Student Learning: A Case Study

Redesigning an Introductory Programming Course to Facilitate Effective Student Learning: A Case Study

Factor Analysis of Visual Literacy Influencing Diagram Understanding and Drawing in Computer Science Education

Recently, with the advent of the software-based society, many organizations have been providing software developing education, such as coding, to Computer Science majors and non-Computer Science majors. When implementing a program, teachers can let students draw a variety of diagrams, such as flowcharts, UML diagrams, and ERD diagrams ahead. As the importance of computational thinking is increasingly emphasized, abstracting algorithms into diagrams is considered an important educational element. In this paper, we examined the visual literacy and abstract/concrete way of thinking of novice programmers in order to analyze factors affecting the abstraction process of drawing diagrams, and how they influence students" ability to understand diagrams and ability to draw. If we understand what factors influence the abstraction process in this study, we can suggest educational alternatives for future strategies in which teachers will teach students.

How to Bring Computational Thinking Approach to The Non-Computer Science Student’s Class???

Computational Thinking (CT) skill is the ability to solve problems with computer thinking. In addition, CT can be seen as a structured and systematic approach that can be implemented in learning. This study aims to bring the computational thinking approach to the non-computer science student’s class and involved 35 undergraduate students of physics education in the computational physics course. The research method used was the mixed method sequential explanatory design (Creswell & Plano Clark, 2011), with the following design. Broadly speaking, the flow of the mixed method research method with an explanatory sequential design in this study includes the collection of quantitative data obtained from student self-evaluation instruments related to the understanding of the CT approach stage. The results showed that the Computational Thinking (CT) approach can be applied to non-computer science students in online learning which includes 6 stages of implementation and 6 stages of implementation. Other results indicate that this method can be used in improving student CT skills. Keywords: Computational thinking, physics, problem solving

A Study of the Effect of Modified Software Education Curricula on Non-Computer Science Majors

A Study of the Effect of Modified Software Education Curricula on Non-Computer Science Majors

Analyzing the impact of experiential pedagogy in teaching socio-cybersecurity

This paper presents results from efforts to integrate cybersecurity into social science courses, for the purposes of improving the cybersecurity awareness of non-computer science students. The inst...

Introducing students to computer science and programming using data analytics

Enthusiasm for learning computer science continues to grow as more non-computer science students are interested in creating computational solutions to the problems encountered in their respective f...

What happened to my application? Helping end users comprehend evolution through variation management

Context: Millions of end users are creating software applications. These end users typically do not have clear requirements in mind; instead, they debug their programs into existence and reuse their own or other persons’ code. These behaviors often result in the creation of numerous variants of programs. Current end-user programming environments do not provide support for managing such variants.Objective: We wish to understand the variant creation behavior of end user programmers. Based on this understanding we wish to develop an automated system to help end user programmers efficiently manage variants.Method: We conducted an on-line survey to understand when and how end-user programmers create program variants and how they manage them. Our 124 survey respondents were recruited via email from among non-computer science majors who had taken at least one course in the computer science department at our university; the respondents were involved in the Engineering, Sciences, Arts, and Management fields. Based on the results of this survey we identified a set of design requirements for providing variation management support for end users. We implemented variation management support in App Inventor – a drag and drop programming environment for creating mobile applications. Our support, AppInventorHelper, is meant to help end-user programmers visualize the provenance of and relationships among variants. We conducted a think-aloud study with 10 participants to evaluate the usability of AppInventorHelper. The participants were selected on a first-come, first-served basis from those who responded to our recruitment email sent to list-servers. They were all end users majoring in electrical engineering, mechanical engineering, or physics. None had formal training in software engineering methods, but all had some experience with visual programming languages.Results: Our (user study) results indicate that AppInventorHelper can help end users navigate through variants and find variants that could be utilized cost-effectively as examples or actual code upon which to build new applications. For example, in one of our empirical studies end users explored variants of a paint application in order to find a variant that could easily be extended to incorporate a new feature.Conclusions: Our survey results show that end users do indeed reuse program variants and suggest that understanding the differences between variants is important. Further, end users prefer running code and looking at outputs, accessing source code and meta information such as filenames, referring to the creation and update dates of programs, and having information on the authors of code. When selecting variants users prefer to look at their major features such as correctness, similarity and authorship information. End users rely primarily on memory to track changes. They seldom make use of online or configuration management tools. Hence, integrated domain-specific variation management tools like AppInventorHelper can significantly help improve users’ interactions with the system. A key contribution of our work is a set of design requirements for end-user programming environments that facilitate the management and understanding of the provenance of program variants.

Career aspirations, perceived instrumentality, and achievement in undergraduate computer science courses

This research investigated the relationships among undergraduate computer science students’ computer-science-related career aspirations, perceived instrumentality (PI) for computer science courses, and achievement in those courses. Specifically, the two studies examined (a) change in PI and career aspirations during a single semester, (b) the relationship between change in career aspirations and change in PI, and (c) the influence of career aspirations, PI, and change in career aspirations and PI on achievement in computer science courses. Findings from both studies revealed that students experienced a decrease in endogenous PI and career aspirations and an increase in exogenous PI during the semester. Study 1 showed that non-computer science majors experienced greater shifts in PI and career aspirations than computer science majors. Study 2 showed that the change in PI happened in parallel and was curvilinear, with more change happening in the first half of the semester than the second half. Both studies also showed that computer-science-related career aspirations were associated with PI, and that aspirations and PI had a stronger relationship with scores on a computer science knowledge test than with course grades. Implications and directions for future research are discussed.

The Game Making Framework for Collaborative Learning

Collaborative learning is a study group process that each member contributes their idea, information, experience, skill, and ability they have so it can be used on learning activity and improve members’ knowledge[1]. Digital game can become one of collaborative learning media that is not just for entertainment but also can be used as a unique and effective interactive learning media[2]. In conventional game making for collaborative learning, the research proves that it can improve excitement and contribution in learning activities[3]. But in game making, there are many technical issues for non-computer science students[3]. Based on many issues, designing framework is chosen to become a solution to help people in developing game as collaborative learning media by themselves. Because framework is a basic form of system [4], consist of various command, function, and benefit for developer in application development [5][6], so game making for collaborative learning is conducted again with support from framework designed by researcher. In order to know the effect from framework support in game making as collaborative learning media, this study is based on two subjects of non-computer science students and computer science students.

Guided Instruction of Introducing Computational Thinking to Non-Computer Science Education Major Pre-Service Teachers

Since ‘teaching coding’ or ‘programming’ classes for computational thinking (CT) education in K-12 are renowned around the world, a pre-service teachers’ readiness for integrating CT into their teaching subjects is important due to the fact that CT is considered to be another ‘R’ from algoRitm for 21st century literacy, in addition to the traditional 3R (Reading, Writhing, and Arithmetic) [2] and CT roles to other disciplines. With this rationale, we designed a guided instruction based CT course for pre- service teachers. We show the effectiveness of the program with respect to the teachers’ attitude toward combining CT into their teaching subjects, and mindset changes of learning computing connected with the career development of the teacher themselves. The research focused on the instructional methodology of teaching programing for non-Computer Science Education (CSE) majors who are not familiar with computer science for alleviating the cognitive load of first exposure to programming course under the CT concepts.

BlockPy: An Open Access Data-Science Environment for Introductory Programmers

Non-computer science majors often struggle to find relevance in traditional computing curricula that tend to emphasize abstract concepts, focus on nonpractical entertainment, or rely on decontextualized settings. BlockPy, a web-based, open access Python programming environment, supports introductory programmers in a data-science context through a dual block/text programming view. The web extra at https://youtu.be/RzaOPqOpMoM illustrates BlockPy features discussed in the article.