Teaching programming is a complex process requiring learning to develop different skills. To minimize the challenges faced in the classroom, instructors have been adopting active methodologies in teaching computer programming. This article presents a Systematic Mapping Study (SMS) to identify and categorize the types of methodologies that instructors have adopted for teaching programming. We evaluated 3,850 papers published from 2000 to 2022. The results provide an overview and comprehensive view of active learning methodologies employed in teaching programming, technologies, programming languages, and the metrics used to observe student learning in this context. In the results, we identified thirty-seven different ALMs adopted by instructors. We realized that seventeen publications describe teaching approaches that combine more than one ALM, and the most reported methodologies in the studies are Flipped Classroom and Gamification-Based Learning. In addition, we are proposing an educational and collaborative tool called CollabProg, which summarizes the primary active learning methodologies identified in this SMS. CollabProg will assist instructors in selecting appropriate ALMs that align with their pedagogical requirements and teaching programming context.
In education, we have noticed a significant gap between the ability of students to program in an educational visual programming environment and the ability to write code in a professional programming environment. The aim of our research was to verify the methodology of transition from visual programming of mobile applications in MIT App Inventor 2 to textual programming in the Android Studio using the Java Bridge tool as a mediator of knowledge transfer. We have examined the extent, to which students will be able to independently program own mobile applications after completing the transition from visual to textual programming using the mediator. To evaluate the performance of students, we have analysed qualitative data from teaching during 1 school year and determined the degree of achievement of educational goals according to Bloom’s taxonomy. The results suggest that students in the secondary education can acquire advanced skills in programming mobile applications in a professional programming environment, when they have knowledge of visual programming in an educational programming environment, and a suitable mediator is used to transfer such knowledge into a new context.
This research examines the factors that influence the intention to use information technology in the classroom by primary school teachers based on the Unified Theory of Acceptance and Use of Technology and their technological predisposition. In particular, the relationship between teachers' innovativeness and their beliefs associated with the use of technology in the classroom was analyzed. To this end, 212 teachers from three provinces of Chile were surveyed. Data were analyzed using partial least squares statistical technique. Results indicate that performance expectancy, social influence, and facilitating conditions influence the intention to use information technology in the classroom. It was found that the intention to use construct is a determinant of the use of technology, which validates the robustness of the model in a context of primary education. In addition, it was validated that teachers' innovativeness determines their beliefs about the use of information technology in the classroom.
Although there is no universal agreement that students should learn programming, many countries have reached a consensus on the need to expose K-12 students to Computational Thinking (CT). When, what and how to teach CT in schools are open questions and we attempt to address them by examining how well students around the world solved problems in recent Bebras challenges. We collected and analyzed performance data on Bebras tasks from 115,400 students in grades 3-12 in seven countries. Our study provides further insight into a range of questions addressed in smaller-scale inquiries, in particular about the possible impact of schools systems and gender on students' success rate.
In addition to analyzing performance data of a large population, we have classified the considered tasks in terms of CT categories, which should account for the learning implications of the challenge. Algorithms and data representation dominate the challenge, accounting for 75-90% of the tasks, while other categories such as abstraction, parallelization and problem decomposition are sometimes represented by one or two questions at various age groups. This classification can be a starting point for using online Bebras tasks to support the effective learning of CT concepts in the classroom.
The paper analyses the problems in selecting and integrating tools for delivering basic programming knowledge at the university level. Discussion and analysis of teaching the programming disciplines, the main principles of study programme design, requirements for teaching tools, methods and corresponding languages is presented, based on literature overview and author`s experience. A pressure from labor market, students and other sources to emphasize practical skills over deeper, long-term programming concepts is described. A model of teaching introductory programming disciplines at a higher logical level, using C#, is presented as a summary of the accomplished analysis, and also taking into account the recommendations of the ACM (Association for Computing Machinery) association for typical teaching programs. Also, design principles for building introductory programming courses, aligned with such teaching approach, are presented. This model has already been trialed at Vytautas Magnus University.