University Programming Course Research Articles

Extracting typing game keystroke patterns as potential indicators of programming aptitude

This study attempted to determine whether individuals possess programming aptitude solely based on keystroke information from typing games where participants type computer programs. The participants were students enrolled in university programming courses. The results indicated that using typing speed alone as an indicator achieved an accuracy of 0.71, while employing a custom machine learning model achieved an accuracy of 0.83. Additionally, it was found that individuals with programming aptitude tended to type the enter key relatively slower compared to other keys.

Convergent Education Platform and Performance Outcomes Research in the Integration of University Physics and Programming Courses

Convergent Education Platform and Performance Outcomes Research in the Integration of University Physics and Programming Courses

Evaluation of LLM Tools for Feedback Generation in a Course on Concurrent Programming

AbstractThe emergence of Large Language Models (LLMs) has marked a significant change in education. The appearance of these LLMs and their associated chatbots has yielded several advantages for both students and educators, including their use as teaching assistants for content creation or summarisation. This paper aims to evaluate the capacity of LLMs chatbots to provide feedback on student exercises in a university programming course. The complexity of the programming topic in this study (concurrency) makes the need for feedback to students even more important. The authors conducted an assessment of exercises submitted by students. Then, ChatGPT (from OpenAI) and Bard (from Google) were employed to evaluate each exercise, looking for typical concurrency errors, such as starvation, deadlocks, or race conditions. Compared to the ground-truth evaluations performed by expert teachers, it is possible to conclude that none of these two tools can accurately assess the exercises despite the generally positive reception of LLMs within the educational sector. All attempts result in an accuracy rate of 50%, meaning that both tools have limitations in their ability to evaluate these particular exercises effectively, specifically finding typical concurrency errors.

Effects of students’ perception on self-efficacy in programming courses at the tertiary institution

Programming is a difficult subject to learn and teach. When it comes to students learning basic programming information and skills, university-level introductory programming courses (Java, C++, Visual Basic, and Python) are critical. Students' achievement is negatively impacted by a negative attitude about programming. As a result, the study discovered the impact of students' perceptions in university computer programming courses. The study covered students studying Computer Science from the University of Ghana. A survey descriptive design with a quantitative technique was used in this investigation. The population of the study was 2,030 with 368 sample size. Purposive sampling was utilized to choose University of Ghana, Legon as the study's location. The study's participants were chosen using a stratified random sampling technique. Closed-ended questionnaire was used for data collection. The SPSS version 26 and PROCESS Macro were used to analyze the data. Respondents’ data were examined applying both inferential and descriptive statistics. The study revealed that students see programming as unfamiliar was the highest perception of programming to students. The study found that students see programming as easy with dedication was the lowest perception of programming to students. In conclusion, the significant impact of perception of students in Computer Programming account for 84% of the contribution of factors that influence self-efficacy.

Research on Construction and Practice of Precision Teaching Classroom for University Programming Courses

Facing the challenges of programming courses teaching in university, this study constructs a precision teaching classroom for programming courses that integrates precision teaching theory. Firstly, this paper analyzes the realization conditions for precision teaching in programming courses, then designs the implementation process of precision teaching including three teaching phases and five teaching links, and finally carried out teaching practice in C Language Programming course. The practice results showed that in the precision programming teaching classroom, teacher-student interactions were more frequent and students had higher programming learning efficiency than in ordinary programming teaching classroom. Compared with the control class, students in the experimental class were more capable of grasping programming knowledge and had better programming problem-solving abilities, and most of them were highly satisfied with teaching design of precision teaching classroom for C Language Programming. Precision programming teaching classroom constructed by this research provides a more optimized and effective teaching method for university programming teaching. On the other hand, this study provides a practical case for the integration and application of precision teaching theory and university curriculum teaching.

Classification of Program Texts Represented as Markov Chains with Biology-Inspired Algorithms-Enhanced Extreme Learning Machines

The massive nature of modern university programming courses increases the burden on academic workers. The Digital Teaching Assistant (DTA) system addresses this issue by automating unique programming exercise generation and checking, and provides means for analyzing programs received from students by the end of semester. In this paper, we propose a machine learning-based approach to the classification of student programs represented as Markov chains. The proposed approach enables real-time student submissions analysis in the DTA system. We compare the performance of different multi-class classification algorithms, such as support vector machine (SVM), the k nearest neighbors (KNN) algorithm, random forest (RF), and extreme learning machine (ELM). ELM is a single-hidden layer feedforward network (SLFN) learning scheme that drastically speeds up the SLFN training process. This is achieved by randomly initializing weights of connections among input and hidden neurons, and explicitly computing weights of connections among hidden and output neurons. The experimental results show that ELM is the most computationally efficient algorithm among the considered ones. In addition, we apply biology-inspired algorithms to ELM input weights fine-tuning in order to further improve the generalization capabilities of this algorithm. The obtained results show that ELMs fine-tuned with biology-inspired algorithms achieve the best accuracy on test data in most of the considered problems.

Incorporation of Computational Thinking Practices to Enhance Learning in a Programming Course

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.

Adaptive formative assessment system based on computerized adaptive testing and the learning memory cycle for personalized learning

Computerized adaptive testing (CAT) can effectively facilitate student assessment by dynamically selecting questions on the basis of learner knowledge and item difficulty. However, most CAT models are designed for one-time evaluation rather than improving learning through formative assessment. Since students cannot remember everything, encouraging them to repeatedly evaluate their knowledge state and identify their weaknesses is critical when developing an adaptive formative assessment system in real educational contexts. This study aims to achieve this goal by proposing an adaptive formative assessment system based on CAT and the learning memory cycle to enable the repeated evaluation of students' knowledge. The CAT model measures student knowledge and item difficulty, and the learning memory cycle component of the system accounts for students’ retention of information learned from each item. The proposed system was compared with an adaptive assessment system based on CAT only and a traditional nonadaptive assessment system. A 7-week experiment was conducted among students in a university programming course. The experimental results indicated that the students who used the proposed assessment system outperformed the students who used the other two systems in terms of learning performance and engagement in practice tests and reading materials. The present study provides insights for researchers who wish to develop formative assessment systems that can adaptively generate practice tests.

Research and Practice on the Blended Teaching Mode of Programming Courses Based on the Integration of Dual Theory and Practice

Blended teaching based on multiple online and offline modes has changed the way people learn in modern society. In view of the huge gap between theoretical teaching and practical programming in university computer programming courses, the content of theoretical and practical teaching has been reconstructed. The "five-in-one" course teaching support platform of teaching, learning, practice, evaluation, and interpretation explores a blended teaching mode that emphasizes both theory and practice, and innovates a multi-assessment system that highlights practical ability evaluation. better practical results.

Programación individual, por pares o colectiva: ¿cuál conviene utilizar en la universidad?

El objetivo de esta investigacion fue comparar la programacion individual, por pares y colectiva a traves de las percepciones de 24 estudiantes del curso universitario Programacion intermedia con Visual Basic.Net. Los participantes fueron expuestos a las tres modalidades de trabajo en el desarrollo de proyectos de software durante sesiones regulares de clase. El diseno de investigacion fue mixto explicativo secuencial. Para el componente cuantitativo se aplicaron cuestionarios, y para el apartado cualitativo se realizaron entrevistas. Los resultados mostraron que los alumnos prefieren la programacion por pares porque la perciben como un punto medio entre no programar con nadie y hacerlo con un grupo numeroso. Programar de manera individual puede provocarles estres y bloqueo intelectual, mientras que hacerlo con demasiadas personas al mismo tiempo les genera distraccion y desbalance de trabajo. Una limitacion del estudio es el tamano de la muestra; sin embargo, hace aportaciones cuantitativas y cualitativas a un area de conocimiento poco explorada en la literatura formal. Los hallazgos sugieren promover el trabajo por parejas en los cursos universitarios de programacion, pues se implementa con facilidad, con pocos recursos y buenos resultados.

Engagement in the course of programming in higher education through the use of gamification

Programming learning in college education is hard for students. Consequently, strategies are required to boost significant learning as well as sustained motivation during the delivery of the course. For this reason, the following investigation determines if the didactic strategy of gamification encourages engagement in a university level programming course. The article presents two interventions that took place during the period of January to April 2017 and January to April 2018 in a University of Mexico using the challenge-based gamification pedagogical strategy. This strategy supports the Werbach and Hunter methodology. The dynamics were emotional, social, and progressive and were conducted through challenge and opportunities mechanics. The components were points, badges, avatars, and a leaderboard. In both interventions, surveys were used to know the acceptance of the strategy on behalf of the students, and a meta-evaluation instrument was applied after the first intervention with the purpose of strengthening and improving the didactic strategy. The main conclusion of this work indicates that gamification in the classroom contributed to improve the engagement with the students to succeed in solving the challenges successfully; therefore, the pedagogical strategy under scrutiny can be applied to other subjects.

Software Server for Automatic Generation of Audio Lectures (uListenSrv)

<p class="Abstract">Facilitation of new methods for learning materials delivery and adoption of new learning experiences and practices in e-learning is always a challenge. Using synthesis of digital audio learning assets and learning objects as one of main sources for conducting learning is not new, but research on using audio lectures or combined audio with presentation lecture is not well investigated and adopted in traditional online learning environments. The main goal of current paper is to present requirements elicitation, software analysis, design, construction and testing of secure and reusable software architecture for production and delivery of learning resources with audio elements in university programming courses. Paper presents different architecture styles for designing the system and finish with presentation of development and usage of contemporary Software Server for Automatic Generation of Audio Lectures (uListenSrv). Main difference here is support of languages, not only in English, but not so popular languages, like Bulgarian language.</p>

Student-Generated Content Improves Online Learning of Programming

Quality learning content for online courses is difficult and time-consuming to create, and therefore students are increasingly employed to create learning content for use by their peers. Student-generated content however may be low quality and consequently of uncertain utility. The authors present a successful approach for improving online learning of programming through student-generated content – community tests that help other students in solving programming exercises. In their approach, the tests simplify student work on solving exercises, and the learning system can automatically provide focused help to each struggling student. They evaluated the proposed solution in an existing online learning system for programming in university programming courses. Results indicate that students used the proposed features often, and when examining the impact on learning performance, the active students showed improved performance compared to inactive students. Social awareness in online setting was evaluated using a questionnaire.

Big Five Personality in Online Learning and Games

Online learning gives promise of effective learning for masses. Personalized learning experiences tailored for individual needs and preferences of each student are key ingredients in making online learning successful. Current approaches to adaptive and personalized online learning use student's personality profile and preferred learning style to adapt learning content and activities in order to provide the best possible experience to each individual student. Research has shown that effects on different types of learning activities in various settings may be different. This study analyses how personality affects student's performance in an online learning environment for programming exercises and how the student's personality can be estimated unobtrusively using a casual online game. The data used to evaluate were collected from an online learning environment used in university programming courses over the course of several years. The activity indicators show significant correlations with overall academic results of students and particularly with personality traits.

Evaluation of topic-based adaptation and student modeling in QuizGuide

This paper presents an in-depth analysis of a nonconventional topic-based personalization approach for adaptive educational systems (AES) that we have explored for a number of years in the context of university programming courses. With this approach both student modeling and adaptation are based on coarse-grained knowledge units that we called topics. Our motivation for the topic-based personalization was to enhance AES transparency for both teachers and students by utilizing typical topic-based course structures as the foundation for designing all aspects of an AES from the domain model to the end-user interface. We illustrate the details of the topic-based personalization technology, with the help of the Web-based educational service QuizGuide--the first system to implement it. QuizGuide applies the topic-based personalization to guide students to the right learning material in the context of an undergraduate C programming course. While having a number of architectural and practical advantages, the suggested coarse-grained personalization approach deviates from the common practices toward knowledge modeling in AES. Therefore, we believe that several aspects of QuizGuide required a detailed evaluation--from modeling accuracy to the effectiveness of adaptation. The paper discusses how this new student modeling approach can be evaluated, and presents our attempts to evaluate it from multiple different prospects. The evaluation of QuizGuide across several consecutive semesters demonstrates that, although topics do not always support precise user modeling, they can provide a basis for successful personalization in AESs.

A Token Oriented Measurement Method of Source Code Similarity

In order to help teachers to identify plagiarism in student assignment submissions among students’ Source code quickly and accurately, this paper discusses a measurement method of Source code similarity. In the proposed algorithm, firstly, both of token oriented edit distance (TD) and token oriented length of longest common subsequence (TLCSLen) is calculated; secondly, considering the TD and TLCSLen, a similarity calculation formula is given to measure similarity of Source code; Thirdly, a dynamic and variable similarity threshold is set to determine whether there is plagiarism between Source codes, which ensure a relatively reasonable judgment of plagiarism. This method has been applied to the university's programming course work online submission system and online examination system. Practical application results show that this method can identify similar Source code timely, effectively and accurately.

A comparative analysis of different gender pair combinations in pair programming

Over the last decade, there has been a steady stream of pair programming studies. However, one significant area of pair programming that has not received its due attention is gender. Considering the fact that pair programming is one of the major human-centric software development paradigms, this is a gap that needs to be addressed. This empirical study conducted quantitative and qualitative analyses of different gender pair combinations within pair programming context. Using a pool of university programming course students as the experiment participants, the study examined three gender pair types: female–female, female–male, and male–male. The result revealed that there was no significant gender difference in the pair programming coding output. But there were significant differences in the levels of pair compatibility and communication between the same gender pair type: female–female and male–male, and the mixed gender pair type, female–male. The post-experiment comments provide additional insights and details about gender in pair interactions.

BLAKE: A language designed for Programming I

The process of comprehending a problem, strategically developing a solution and translating the solution into an algorithm is arguably the single most important series of skills acquired during the education of an undergraduate computer science or information technology major. With this in mind, much care should be taken when choosing a programming language to deploy in the first University programming course. BLAKE, Beginners Language for Acquiring Key programming Essentials, is designed specifically for use in a Programming I class. BLAKE aids in enforcing fundamental object-oriented practices while simultaneously facilitating the transition to subsequent programming languages. BLAKE's major features include; consistent parameter passing, single inheritance, non-redundant control structures, a simple development environment, and hardware independent data types. The syntax remains relatively small while still facilitating a straightforward transition to industry standard programming languages.

Learning teamwork skills in university programming courses

University courses about computer programming usually seek to provide students not only with technical knowledge, but also with the skills required to work in real-life software projects. Nowadays, the development of software applications requires the coordinated efforts of the members of one or more teams. Therefore, it is important for software professionals to master the sort of skills that assure the success of teamwork, such as communication, leadership, negotiation, or team management. However, these abilities are difficult to teach, one of the reasons being that they require true commitment from the students. However, today students are taking a more and more passive role in their own education, two of the more evident consequences being the increase in dropout rates and the decrease in marks obtained in exams. The NUCLEO e-learning framework has been designed to promote the effective acquisition of teamwork skills and, at the same time, to promote the more active participation of the students in their own learning process. NUCLEO adopts a socio-constructivist pedagogical approach that pursues the development of communities of practice for Problem Based Learning. Our research has rooted the design decisions of NUCLEO in the analysis of its socio-cultural environment with Activity Theory, which considers conflicts within groups as the impetus of their evolution and the forges of their environments. This paper presents the analysis of the main features of NUCLEO according to Activity Theory, as well as the experimental results obtained with the framework in three different case studies in university courses.

プログラミング初心者のソースプログラムの分析と傾向

The production of animations was made the subject of a university programming course in order to make students understand the process of program creation, and so that students could tackle programming with interest. In this paper, the formats and composition of the programs which students produced were investigated. As a result, it was found that there were a lot of problems related to such matters as how to use indent, how to apply comments and functions etc. for the format and the composition of the source codes.