Non-computer Science Students Research Articles

A Comparative Analysis of Programming Language Preferences Among Computer Science and Non-Computer Science Students

In the face of the growing importance of programming skills across various fields, understanding student preferences for programming languages becomes crucial. This study delves into this very topic, examining which languages resonate most with computer science majors and students from non-computer science backgrounds. We don’t just identify the popular choices; we also explore the underlying reasons behind these preferences through surveys. The analysis reveals a fascinating interplay between factors like a student’s learning experience, their career aspirations, and even their interests, all of which influence their preference for specific programming languages. This newfound knowledge empowers us to refine programming education for a diverse student body, ensuring they’re well-equipped for the demands of the digital world. Our findings hold value for curriculum designers, educators, and industry professionals alike. By understanding the evolving demands and preferences of students, these stakeholders can craft more relevant and engaging programming education experiences. Ultimately, this fosters interdisciplinary collaboration in the digital age, a key element for success in today’s interconnected world. This research not only contributes to the growing body of knowledge on programming language preferences but also offers practical insights for the betterment of programming instruction and the promotion of collaboration across disciplines within the digital landscape.

Toward a new framework for teaching algorithmic literacy

PurposeResearch shows that postsecondary students are largely unaware of the impact of algorithms on their everyday lives. Also, most noncomputer science students are not being taught about algorithms as part of the regular curriculum. This exploratory, qualitative study aims to explore subject-matter experts’ insights and perceptions of the knowledge components, coping behaviors and pedagogical considerations to aid faculty in teaching algorithmic literacy to postsecondary students.Design/methodology/approachEleven semistructured interviews and one focus group were conducted with scholars and teachers of critical algorithm studies and related fields. A content analysis was manually performed on the transcripts using a mixture of deductive and inductive coding. Data analysis was aided by the coding software program Dedoose (2021) to determine frequency totals for occurrences of a code across all participants along with how many times specific participants mentioned a code. Then, findings were organized around the three themes of knowledge components, coping behaviors and pedagogy.FindingsThe findings suggested a set of 10 knowledge components that would contribute to students’ algorithmic literacy along with seven behaviors that students could use to help them better cope with algorithmic systems. A set of five teaching strategies also surfaced to help improve students’ algorithmic literacy.Originality/valueThis study contributes to improved pedagogy surrounding algorithmic literacy and validates existing multi-faceted conceptualizations and measurements of algorithmic literacy.

A Comparative Study of Computer Programming Challenges of Computing and Non-Computing First-Year Students

The learning of computer programming comes with unique difficulties that vary among students depending on their backgrounds, learning methods, and objectives. This paper investigates the programming challenges first-year students from non-computing at the North-West University, South Africa, and computing backgrounds at the University of Dschang, Cameroon face. A questionnaire-based data collection method is utilized and categorizes participants based on their gender, age, fields of study, prior experiences in mathematics, statistics, English, and programming languages, lab use/access, learning strategies, and material preferences. The aim is to identify and analyze the student's understanding of the basic programming concepts and the specific challenges met during introductory programming modules. Analysis of the collected data shows that while a considerable percentage of non-computing students have prior experience in mathematics and English, they lack familiarity with programming. Equally, while most computing students are proficient in spoken English, they face significant challenges in programming, mathematics, and written English. Notable difficulties are experienced in grasping concepts like recursion, arrays, error handling, and function/procedure methods. Moreover, a comparative study reveals that both groups of students encounter similar challenges, however, non-computing students’ difficulties are more than their computing counterparts. This paper, therefore, suggests designing teaching methods and learning materials to specifically meet the needs of non-computer science students, and enhance their understanding and proficiency in computer programming.

Design and Implementation of an Android GIS Data Collection Application for Students with Non-Programming Experience Using the MIT App Inventor: A Case Study on a Tick Data Collection APP

Learning programming can be a daunting task, especially for students without a programming background or non-computer science students. Most Geographic Information Science (GIS) experts and students come from a non-programming background and the development of applications has mostly been perceived to be a field for computer science students and has mostly been shunned by other non-programming students and courses. Compounded by the availability of Open-Source Data collection tools like the Open Data Kit (ODK), learning programming and android application development is often overlooked by Geo Spatial Scientists. Many studies have been done to identify a suitable application development kit to introduce application development to students in non-programming classes. MIT App inventor is a user-friendly drag-and-drop application development platform that is ideal for introducing application development to students with a non-programming background. In this paper, students doing an undergraduate honors degree in spatial sciences were introduced to the MIT App inventor for the development of a Geo-App capable of collecting spatial data that can be exported into a GIS system like Arc GIS, and QGIS after the data has been collected. The paper investigates the suitability of MIT App Inventor in the development of Geo-Spatial Applications. The application was developed for collaborative mapping of tick species for Mashonaland Central Province in Zimbabwe. The main purpose of the application developed is to act as a tool for veterinary extension workers under the Veterinary Services Department of Mashonaland Central Province allowing them to collect location information for tick monitoring. The application helps expansion workers to moreover outwardly communicate the circumstance at the tick controlling focuses such as plunge tanks by collaboratively making an outline and uploading multimedia records subsequently with an alternative of making calls straight to the veterinary call center in near real-time.

Top-Down Learning Pedagogy for Real Time Embedded System Design

Abstract : This paper presents an innovative pedagogical approach for average learners to implement projects by effectively fitting their knowledge in solving real-world problems. In particular, it concentrates on embedded systems and embedded signal processing as the current world is experiencing through digital era. Even though both courses are taught, only less numbers of students are opting for embedded projects due to fear of coding and lack of fitting their knowledge appropriately. The focus of this study is to make students to come out of fear by following top-down teaching learning methodology for the design and implementation of Electro Cardio Gram (ECG) data acquisition system. Accordingly, initial interest has been generated by taking the students to the hospital where doctors acquire ECG routinely for their patients and do Fast Fourier Transform (FFT) to observe the spectrum for diagnosis purpose. Every real time system uses high level language for implementation. However, noncomputer science students always found it difficult. In order to make the students to come out of fear, simple scripting language MATLAB was tried first. MATLAB coding demo was given to observe the waveforms and an exercise was made to correlate with actual workplace. After interest creation phase, the relationship has been established between the practical they did and the workplace instrument. In the final stage, their learning process was activated by applying inquiry-based (Masoodhu Banu et al. (2020)) learning. Once the quest for real time implementation was created, it was observed that the student's curiosity was increased enormously and was instituted to be effective coders in solving real time applications with more confidence Keywords: Top-Down learning, Bottom-up learning, ECG, Active learning, embedded system

Implementation of the gradual release of responsibility informed curriculum and pedagogy for teaching programming: Action research based on a course for sport science students

Non-computer science students typically find it challenging to learn programming and lack the motivation to learn it. We conducted a piece of action research to examine the impact of adopting the Gradual Release of Responsibility (GROR) approach as we taught programming to thirty-three sport science students in a Taiwanese university over two semesters. Learning self-efficacy, engagement, and burnout were assessed before and after the course. The results showed significant interaction effect between time (pre vs post) and groups (proactive vs apathetic) factors (F(1, 31) = 4.49, p = .042, ηp2 = 0.13) for self-efficacy. Implications of the findings were discussed.

Digital Tools Acceptance in Open Distance Learning (ODL) among Computer Science Students during COVID-19 Pandemic: A Comparative Study

Abstract: The present new norm driven by the COVID-19 pandemic has taught us to remain at home and carry our everyday activities. This pandemic has seriously made a radical shift to the Malaysian education sector as well. Educators instantly begin to adopt Open and Distance Learning (ODL). However, issues arise in courses that need a conventional setting. In ODL, students and lecturers rely on digital tools, social media, pre-recorded video, and video conference to assist the learning process. Nonetheless, there are some concerns about how successful digital tools are among students in an online learning environment, particularly among computer science students. Thus, a study is being conducted to compare the acceptance of digital tools among computer science (CS) and non-computer science (NoNCS) students by adapting the Technology Acceptance Model (TAM). A quantitative research method of convenient sampling was undertaken. Questionnaires were distributed through an online survey among UiTM Terengganu students at three campuses in Dungun, Bukit Besi and Kuala Terengganu. A sample of 367 students who responded from different diploma and degree programs was collected. Findings of the study revealed that all relationships in TAM are significant for both CS and NoNCS students, where both acquire positive perceived usefulness, attitude, and use intention. Thus, the acceptance of digital tools in ODL are justified. However, it appears that NoNCS students had a more positive attitude than CS students, contradicting the study's initial general assumption. More study is needed to discover why NoNCS students have a better attitude than CS students in the acceptance of digital tools during ODL.
 
 Keywords: Computer Science, COVID-19, Digital Tools, ODL, TAM

Students’ Assessments in Learning Programming based on Bloom’s Taxonomy

Learning a program is important for all students, not only students from the field of computer science but all fields. Programming languages are different from human communication languages as they have different structural forms. This makes it difficult for beginners especially for non-computer science students to understand the structure of programming languages. Therefore, to learn and understand the programming language more effectively, this article focuses on the important structure in learning a program from the initial stage to the advanced level suitable for non-computer science students. The objective of this article is to suggest important elements that can be assessed on these students which are to measure their understanding as they learn programming languages. The questions proposed to measure students' understanding were based on Bloom's Taxonomy, which covers six levels of understanding. It is hoped that this assessment proposal can act as a guideline for educators in fully focusing on important matters during the teaching and learning process.

A Study of Difficulties in Teaching and Learning Programming: A Systematic Literature Review

Teaching and learning (T&L) computer programming language especially for non-computer science students are challenging. The instructors are facing constraints or obstacles in making the students understand the programming concepts and able to create excellent programming skills to solve the real problem. Lack of logical, creative, and critical thinking among students leads to weaknesses in the implementation of problem-based learning (PBL). The entity of programming language problems such as instructors, students and programming language were examined and analyzed based on related previous studies or research that have been reported. The methodology of Structured Literature Review (SLR) was applied to explore the entities and help to measure the major contributing factors influencing the weaknesses of programming language understanding among students. Hence, SLR can guide researchers to find related information from the articles systematically and extensively in line with the objectives of the research framework.

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

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.

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

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...

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...

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.

Simulation Modeling of Lakes in Undergraduate and Graduate Classrooms Increases Comprehension of Climate Change Concepts and Experience with Computational Tools

Ecosystem modeling is a critically important tool for environmental scientists, yet is rarely taught in undergraduate and graduate classrooms. To address this gap, we developed a teaching module that exposes students to a suite of modeling skills and tools (including computer programming, numerical simulation modeling, and distributed computing) that students apply to study how lakes around the globe are experiencing the effects of climate change. In the module, students develop hypotheses about the effects of different climate scenarios on lakes and then test their hypotheses using hundreds of model simulations. We taught the module in a 4-hour workshop and found that participation in the module significantly increased both undergraduate and graduate students’ understanding about climate change effects on lakes. Moreover, participation in the module also significantly increased students’ perceived experience level in using different software, technologies, and modeling tools. By embedding modeling in an environmental science context, non-computer science students were able to successfully use and master technologies that they had previously never been exposed to. Overall, our findings suggest that modeling is a powerful tool for catalyzing student learning on the effects of climate change.

A CS unplugged activity for the online classroom

In this paper, we present a group, asynchronous problem solving exercise designed to introduce non-computer science students to a variety of concepts from artificial intelligence and operations research. The exercise is designed to be a Computer Science (CS) Unplugged activity suitable for the online classroom. CS Unplugged is a methodology for teaching CS concepts using hands-on interactive activities without using a computer. CS Unplugged activities are often used to introduce CS concepts to novices, such as elementary, middle, or high school students; but can also be effective at engaging the non-CS undergraduate student. By definition, CS Unplugged seems at odds with online education, as the participants in the exercise are necessarily using computers. We present an interactive activity motivated by CS Unplugged, but implemented within an asynchronous threaded discussion board. The activity is based on the well-known Bin Packing problem, and is specifically an extension of an existing active learning exercise known as Collective Bin Packing but adapted to the online classroom. The activity is designed for an undergraduate interdisciplinary course as part of a liberal arts curriculum.

Instructional Design and Learning Theory on the Development of C++ Programming Multimedia Content

This paper discusses on the possibility of taking advantage of the well-served Gagne's theory of learning and combining it with the benefits of instructional design. Such potent combination can surely be extended further with the integration of advance multimedia is undoubtedly helpful in today's education realm. The best off all these factors may have positive impact on the teaching and learning scenario. Hopefully it has an optimistic bearing on the study of computer programming for non-computer science students when an interactive multimedia application is developed based on Gagne's theory of learning.

Learning to Program with Personal Robots

One of the goals of using robots in introductory programming courses is to increase motivation among learners. There have been several types of robots that have been used extensively in the classroom to teach a variety of computer science concepts. A more recently introduced robot designed to teach programming to novice students is the Institute for Personal Robots in Education (IPRE) robot. The author chose to use this robot and study its motivational effects on non-computer science students in a CS0 course. The purpose of this study was to determine whether using the IPRE robots motivates students to learn programming in a CS0 course. After considering various motivational theories and instruments designed to measure motivation, the author used Keller’s Instructional Materials Motivation Survey to measure four components of motivation: attention, relevance, confidence, and satisfaction. Additional items were added to the survey, including a set of open-ended questions. The results of this study indicate that the use of these robots had a positive influence on participants’ attitudes towards learning to program in a CS0 course, but little or no effect on relevance, confidence, or satisfaction. Results also indicate that although gender and students interests may affect individual components of motivation, gender, technical self-perception, and interest in software development have no bearing on the overall motivational levels of students.

A data mining course for computer science and non-computer science students

A Data Mining course has been offered twice during the last two years at Missouri State University. The course is designed for both computer science and non-computer science majors with minor prere...