This paper systematically explores how Large Language Models (LLMs) generate explanations of code examples of the type used in intro-to-programming courses. As we show, the nature of code explanations generated by LLMs varies considerably based on the wording of the prompt, the target code examples being explained, the programming language, the…

Background and Context: We explore the potential for understanding the processes involved in students' programming based on studying their behaviour and dialogue with each other and "conversations" with their programs. Objective: Our aim is to explore how a perspective of inquiry can be used as a point of departure for insights into how…

Integrating computational thinking (CT) into STEM disciplines requires secondary teachers to develop their pedagogical content knowledge of computing and content integration. Experienced teachers who choose to integrate CT in their secondary STEM courses may struggle in the same ways as novice teachers as they learn about programming and its…

This study examines modelling with machine learning. In the context of a yearlong data science course, the study explores how upper secondary students apply machine learning with Jupyter Notebooks and document the modelling process as a computational essay incorporating the different steps of the CRISP-DM cycle. The students' work is based on a…

This autoethnographic paper is part of a special issue trying to answer the question "How to design or choose languages for programming novices?" I will describe how my programming language Hedy was created, how the initial design goals were formed, how my perspectives on learning and teaching changed along the way, and how Hedy changed…

Is there a pattern in how students solve Parsons puzzles? Is there a difference between the puzzle-solving strategies of C++ and Java students? We used Markov transition matrix to answer these questions. We analyzed the solutions of introductory programming students solving Parsons puzzles involving if-else statements and while loops in C++ and…

Rough set theory (RST) was proposed by Zdzistaw Pawlak (Pawlak,1982) as a methodology for data analysis using the notion of discernibility of objects based on their attribute values. The main advantage of using RST approach is that it does not need additional assumptions--like data distribution in statistical analysis. Besides, it provides…

Data science is a highly interdisciplinary field that comprises various principles, methodologies, and guidelines for the analysis of data. The creation of appropriate curricula that use computational tools and teaching activities is necessary for building skills and knowledge in data science. However, much of the literature about data science…

In this paper, we propose a novel approach to combine domain modelling and student modelling techniques in a single, automated pipeline which does not require expert knowledge and can be used to predict future student performance. Domain modelling techniques map questions to concepts and student modelling techniques generate a mastery score for a…

The work of Niklaus Wirth, designer of the Pascal programming language, has led to the introduction of programming in schools in many countries often leading to a transformation in the way of thinking. In this article, we provide a retrospective analysis of the Lithuanian experience driven by Pascal and discuss the main ideas about teaching…

Simulation modeling is an effective tool for solving problems that cannot be explained analytically or when data cannot be collected. This is done by simulating the observed behavior of a problem under study using a computer program. In math education, this can develop knowledge and fundamental competencies of simulation modeling at a higher level…

Data science surrounds us in contexts as diverse as climate change, air pollution, route-finding, genomics, market manipulation, and movie recommendations. To open the "data-science-black-box" for lower secondary school students, we developed a data science teaching unit focusing on the analysis of environmental data, which we embedded…

Background and Context: Computational Thinking (CT) has been recently integrated into new and revised Digital Technologies content (DTC) in the Technology learning area of the New Zealand School Curriculum. Objective: To aid this change, this research examined how CT supports learning outcomes in both music and programming with the Sonic Pi…

The continuous technological development nowadays acts ancillary and supportively in student-centered learning, in both formal and informal education settings. Effective learning environments, such as the AppInventor software, could spark the students' interest and allow them to develop programming skills and strengthen their algorithmic…

Individual based models (IBMs) are up-to-date tools both in research and educational areas. Here we introduce an IBM built on NetLogo platform that simulates a top-down trophic cascade controlled by the pressure exerted by two model predators (web-building spiders and ground runner spiders) on a model pest (the olive fruit fly) within a…