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This empirical study investigates university teachers’ conceptions of the role of mathematics within science, technology, engineering, and mathematics (STEM) higher education disciplines, employing a phenomenographic approach to capture variation among perspectives of educators in chemistry, computer science, geoscience, and physics. Despite the significant reliance on mathematics across these disciplines, little is known about how educators conceptualise its role. Our study aims to contribute to this research by performing a phenomenographic analysis of semi-structured interviews with 16 teachers at a Swedish university. Through our analysis, we identified five hierarchically inclusive categories that represent increasingly sophisticated conceptions of the role of mathematics: as a computational tool, a language for communication, a key to understanding, an agent for development, and a philosophical foundation. These categories reflect both the instrumental and intrinsic roles that mathematics plays within other STEM disciplines, extending previous empirical findings that predominantly focus on students’ conceptions. We aim to raise awareness among educators, encouraging reflection on how their conceptions influence teaching and fostering a deliberate consideration of mathematics’ role in instruction. By understanding these varied conceptions, STEM educators can enhance instructional strategies and support student engagement with mathematics in a more meaningful way.

This full research paper investigates upper-secondary students programming skills. In 2021, an initialsurvey assessed the programming skills of first-year upper-secondary school students, focusing on their ability to solveproblems using block and text-based programming languages.The survey revealed significant differences between students withmandatory programming education (Group TECH) and thosewithout (Group SCI), with Group TECH outperforming GroupSCI across all categories.

The follow-up survey in 2024 evaluated the same cohort tomeasure longitudinal changes in their programming knowledgeand skills. The results showed marked improvements in GroupTECH’s performance, particularly in more complex program-ming tasks involving loops and embedded conditional statements,while Group SCI also showed progress, albeit to a lesser extent.The study found that students who engaged more frequently inprogramming activities outside of school demonstrated higheraverage scores.

Overall, students in the study entered upper-secondary mostlyprepared for programming topics mostly related to math likevariables and conditionals in block programming languages. Stu-dents that left upper-secondary, after introductory programming,were better prepared to understand loops and complex problemsin text.

This research-to-practice full paper discusses students' views on the role of generative artificial intelligence (GenAI) in their learning. The rapid integration of GenAI in educational settings has prompted significant interest in its implications for learning and academic integrity. This study investigates the adoption and impact of GenAI tools among computing students at a university, focusing on how they are utilized for educational purposes and their ethical implications. Semi-structured interviews with nine computing students were used to examine GenAI's specific use and timing. Additionally, it explores students' perceptions of the trustworthiness of GenAI outputs and identifies the students' ethical boundaries concerning its use in academic work. The findings reveal that while GenAI tools might enhance learning efficiency and provide substantial educational support, they raise significant ethical concerns, particularly regarding academic misconduct. The study highlights the need for educational strategies to navigate the challenges posed by GenAI technologies. Finally, three recommendations for computing education are outlined. This research contributes to the ongoing discourse on GenAI in education by describing the student's reflections on GenAI.

This Research-to-Practice WIP paper investigates how East Asian students studying in Sweden encounter various challenges. We discuss the discrepancy between our and previous findings and give recommendations. Background: Moving to and studying in a new country that is culturally different from their home country presents many challenges related to cultural differences to students. Intended outcomes: This research aims to offer insights into how East Asian students adapt their learning strategies in Sweden and suggest how the university can support their lives and studies. Research design: Six students were interviewed about their experiences studying in Sweden compared to studying at their home universities. Content analysis was performed to identify areas of interest. Findings: We report initial findings specifically related to academic and sociocultural issues.

This research work-in-progress paper presents findings related to upper secondary students’ understanding of programming concepts such as: (1) variable assignment, (2) if-statements, and (3) loops in Python and Scratch. In 2017, the Swedish education board added computer science curriculum to compulsory schooling. Students now entering upper secondary school are expected to have experience with programming. To find out how familiar first year upper secondary students are with programming, we assessed 172 students’ programming knowledge with a multiple choice questionnaire with block programming questions in Scratch and text programming questions in Python. Each question required students to read a program between 4-8 lines of code and correctly identify the output of the program. The questions included basic programming concepts such as: variable assignment, if-statements and loops. Additionally, we asked students to self-report their prior experiences with programming in terms of how many hours they had spent programming inside and outside of school, as well as if they had more experience with block or text programming. As expected, the students’ scores correlated positively with the amount of hours they self-reported to have spent programming inside and outside of school. In conclusion, we correlate students’ self-reported programming experience with their scores on the block and text sections and reason about these results based on teachers’ experience and research literature.

In this full research-to-practice paper we study novice programming students learning process in the computer laboratory. Working with laboratory assignments is an important component when students learn to program. Here the assignments are intended to help students consolidate theoretical understanding and simultaneously train practice. However, it has been observed that the learning outcome of such laboratory sessions often is unsatisfactory. In this article we ask the question "How do novice students go about learning in the computer laboratory?" We analyse empirical data on novice students working in pairs in the laboratory, which is common in a first programming course. The data consists of video films of students where they discuss and solve programming problems, screen captures of what the students typed during the same laboratory session, and stimulated recall interviews with the students after the laboratory session. In the analysis we use an approach inspired by phenomenography and variation theory. We specifically focus on typical stages in the learning process when students learn in the programming laboratory. In doing so we have identified successful and less successful learning paths, where variation can play different roles. The stages identified in students’ learning process are I. Students first need to become aware of a lack of clarity. In the data we have identified different ways in which this necessary awareness was trigged; II. If, and in that case how, they resolve the lack of clarity. In all the stages we found successful and less successful ways in which students’ handle the situations. We illustrate the stages and discuss how and why variation may play different roles in the different stages of students’ learning, specifically focusing of the unsuccessful learning paths. Lastly, we discuss what these findings can tell us about how programming labs could be designed to promote learning in terms of helping students to avoid the unsuccessful paths identified.

Student ‘copying’ is often considered negatively as thoughts of plagiarism come to mind. Previously, we investigated the ways that instructors expect to use copying and imitation positively in their teaching. In this paper, we follow up that study by focusing on the student perspective and explore the ways in which students see copying and imitating as positive tools in learning to program (both at an introductory level and through more advanced learning of algorithms, etc.).In a qualitative research study, using semi-structured interviews, students were asked about how they use copying positively - their goals when they copy, how they go about it, how they view the experience of copying, and results beyond simply fulfilling their immediate goals.When comparing student results with the previous study, it was noted that there is some level of agreement between instructors and students about how copying can be useful for learning to program. There is also some degree of mismatch between instructor and student views. Students did not report imitating instructors’ approaches to learning and sometimes were unsure about whether they were supposed to copy the materials that they were given. This leads to some teaching suggestions in terms of instructors being more explicit in their attitude to this type of ‘legitimate’ copying and imitation.

Knowledge of computer programming is increasingly important in society. Many countries have introduced programming into the school curriculum. Programming students’ learning has been studied from many perspectives, one being the importance of students working hands-on with programming problems. The explanations and underlying factors for this are however less researched.

In a controlled study with upper secondary school students (n=53) learning basic Java programming for three hours, we studied how factors like learning outcome, engagement, motivation, stress, and long-term memory are affected by hands-on and hands-off learning respectively. Students worked in pairs to solve programming problems. In each pair, one student was randomly selected to write the code hands-on, while the other student contributed hands-off. The roles did not switch during the session.

We used tests and questionnaires to assess the learning outcome and some other aspects of relevance for learning. Statistical analysis of the results showed that working hands-on reduced stress. There was no difference in knowledge gain immediately after the teaching, but the hands-on group did slightly better on a follow-up test one week later. The results are discussed in relation to research about, e.g., stress, long-term learning, and novices learning to program.