This poster reports a qualitative study investigating pre-service computer science teachers' perspectives on artificial intelligence (AI) education in a Teaching--Learning Lab. Twelve pre-service teachers designed and implemented AI learning activities with secondary school students in this out-of-school learning environment. Semi-structured interviews explored how pre-service teachers perceive the role of this setting for AI-related learning. The analysis reconstructs a preliminary category system capturing how they frame the potentials, challenges, and educational role of Teaching--Learning Labs for AI education.

In Germany, professional development (PD) programs are primarily organized by federal institutes, which have the resources to scale these programs, while universities face challenges such as limited long-term funding and staff turnover. Teacher trainers at federal institutes, typically subject matter experts (e.g., in mathematics), often lack AI knowledge and have expressed a need for AI-focused training. While universities tend to develop PD programs independently, there is little collaboration with federal initiatives. To bridge this gap, a collaborative project was initiated to create AI-related PD materials in partnership with teacher trainers. These materials are designed for piloting and dissemination by trainers and target teachers across multiple subjects, including vocational educators in fields like electrical engineering. This work-in-progress paper describes the development of a PD course structured around a Hybrid Learning Landscape (HLL) centred on AI. The HLL supports teachers in lesson planning, task differentiation, and the integration of AI tools, while providing foundational AI knowledge. The HLL content focuses on five core areas: (1) basic AI knowledge, (2) AI tools, (3) task differentiation, (4) quiz generation, and (5) additional AI-related PD resources. The preliminary findings on the collaboration align with related work and highlight the need to navigate the varying logics, interests, and expectations of the stakeholders involved. Networking meetings and exchange of ideas as well as continuous support seem relevant for a sustainable approach to AI PD.

With the increasing integration of artificial intelligence in education, the relationship between students' learning strategies and their engagement with AI chatbots are of interest. This exploratory study examines the relationships between learning strategies, epistemological beliefs, and motivational orientations concerning AI chatbot usage, as well as the actual usage patterns among students, which has been identified as a research gap. Some studies show that especially India has a high usage of ChatGPT and other countries e. g. Germany how low usage rates. Thus, we operationalized Indian student as so-called early adopters and German students as later users to compare the two subgroups. The study consists of$\mathbf{N = 1 3 5}$students from various disciplines across multiple German universities ($\mathrm{n}=91$; later users) and an Indian university ($\mathrm{n}=44$; early adopters). The findings indicate that students in subgroup 2 (Indian students) can be considered early adopters, utilizing AI chatbots more frequently and exhibiting less elaborated epistemological beliefs compared to later users. Early adopters perceive AI chatbots as a comprehensive source of knowledge. In contrast, later users reported less frequent use of AI chatbots. While no significant correlation was found between epistemological beliefs and learning strategies in relation to students' usage frequency, the differences in epistemological beliefs between the two subgroups suggest that frequent use of AI chatbots could potentially decrease students' epistemological sophistication and thus impact their learning strategies.

Many K-12 computer science (CS) education programs have started focusing on fostering Computational Thinking (CT) skills as early as kindergarten. While secondary-level CS education has been extensively studied, there is limited research on CT practices in early childhood education (ECE), particularly from the perspective of kindergarten teachers. Understanding how CT is taught by kindergarten teachers and how they rate the CT practices of students in preschool is essential for developing effective new curricula and professional development programs. Therefore, this study evaluates an eight-week CT intervention conducted by kindergarten teachers in naturalistic settings, addressing two critical research gaps: 1) the emphasis on CT practices rather than concepts, and 2) the perspectives of kindergarten teachers on CT activities. 109 preschool students (62 female, 43 male, 4 missing information) with the age of five or six years old from six kindergartens in Baden-Württemberg, Germany participated in the intervention. The overall evaluation using the TechCheck-K and the observation scale for CT unplugged activities (OSCTU) show significant improvements of students CT skills. I conclude by discussing the implications of these findings for the integration of CT in ECE. These insights contribute to bridging research and practice, offering a foundation for sustainable CT education initiatives for young learners.

Making and digital fabrication have been increasingly incorporated into computing education to attract female students, foster creativity, and promote design thinking through the hands-on creation of tangible products. While makerspaces and Making activities have been widely integrated into primary and secondary education, their application in early childhood education (ECE) remains limited. This work presents initial findings from a study exploring the integration of Making in ECE. A total of 49 preschool students participated in the intervention, with their future skills assessed using the Positive Technological Behaviour (PTB) rubric. Results indicate medium to high mean values across PTB dimensions, with the highest scores observed in students' choices of conduct and communication. Conversely, creativity and collaboration exhibited the lowest scores, prompting discussion on potential contributing factors. These findings offer valuable preliminary insights into the role of Making in ECE and lay the groundwork for further investigation in this emerging area.

This working group aims to develop a research-based AI concept inventory (AI CI) to assess the understanding of foundational AI concepts among non-experts. By identifying core concepts and common misconceptions through literature reviews, expert consultations, and iterative validation, the group will create a user-friendly assessment tool that can be used to capture snapshots of AI understanding, support benchmarking across contexts, and inform educational initiatives and policy. Designed for diverse non-expert audiences, including educators, students, and the general public, this tool can provide valuable insights into how AI knowledge evolves over time, contributing to the broader goal of promoting AI literacy in everyday contexts.

New (interdisciplinary) Computer Science (CS) subjects in K-12 education have been introduced in recent years. Most of them have educational plans derived from CS Frame-works such as the K-12 CS Framework. To some extent the educational plans have the same core topic areas: data and coding (including data compression and data structures), algorithms (in-volving variables and software projects), computers and networks (covering topics like logic tables and data transmission) and information society and data security (consisting of collection and processing of personal data and asymmetric encryption). Various Computer Science assessment tests such as the SCS1, MG-CSCI, PSIv1 and the Fairy Assessment have been developed for different age groups. These tests mostly include computational thinking, programming or topics that could be categorized in the first two core topic areas data and coding and algorithms. Hence, the research desideratum was to develop a test specifically for measuring the four core topic areas. These core topic areas are part of the educational plan of the new interdisciplinary subject IMP (Informatics, Mathematics, Physics) for secondary schools in Germany. The test was piloted with 156 (m = 117, f = 37, o = 2) 10th grade students, approximately aged 16 at the end of the lower secondary level. We used the Item-Response-Theory (IRT) to validate the test. This work in progress paper presents translated items and the psychometric evaluation of the piloted test. The contribution for both researchers and educators in the CS education research field is the set of items of the research-based CS test in the four core topic areas for 10th grade students that includes item sets for the areas computers and networks and information society and data security.

In Europe, both disciplinary and interdisciplinary approaches are employed in teaching Computer Science and other STEM subjects at the secondary level. In addition to acquiring disciplinary skills, students also have the opportunity to develop interdisciplinary skills, often referred to as 21st-century or future skills, that connect various STEM fields. However, there is limited knowledge about how students perceive interconnections between STEM fields after participating in one of the new interdisciplinary K-12 courses. Therefore, this study aims to assess, through open-ended questions, the perspectives of students enrolled in interdisciplinary subjects, specifically Informatics, Mathematics, and Physics (IMP), regarding the interconnections between these three subjects. A total of N = 371 (71% male, 26% female, 3% other; average age: M = 16.26, SD = 3.70 years) 10th-grade IMP students participated in the study. Open-ended questions about the interconnections of the three subjects involved were analyzed using qualitative content analysis according to Mayring. The findings reveal that students' perceptions of interconnections align with the educational objectives of the IMP curriculum. Interconnections were identified in various topics, including simulation and numerical analysis for all three subjects, cryptography and logic for computer science and mathematics, and electrical engineering for computer science and physics. This study contributes to the understanding of how students perceive interdisciplinary connections in STEM subjects. The results are discussed within the context of existing research in this article, highlighting the importance of fostering interdisciplinary skills in secondary education.

New interdisciplinary Computer Science (CS) sub-jects have been introduced in K-12 education worldwide in recent years, aiming to enhance students' interdisciplinary CS competencies. However, a persistent gender gap exists in various STEM jobs and subjects globally, with women being underrep-resented in these fields. Gender disparities manifest early in K-12 education, as female students are less likely to choose CS in higher grades. Numerous studies indicate lower motivation, interests, and self-concept among female students compared to their male counterparts. Some argue that interdisciplinary subjects have the potential to mitigate gender differences and attract a more diverse group of students. Therefore, the research objective was to investigate whether the new interdisciplinary STEM subject IMP (Informatics, Mathematics, Physics) could attract and retain more female students. N = 665 (male = 467, female = 176, other = 22) 10th grade students in Germany attending an interdisciplinary STEM subject called IMP were asked about their subject interests', motivation, self-concept, and vocational orientation. The results revealed no significant gender differences in vocational orientation. The hierarchical logistic regression analyses showed subject interest in CS and mathematics as significant predictors of the vocational orientation of IMP students. Gender was not a significant predictor in this study. The findings are discussed in the context of existing research and in terms of practical implications for schools.

The 21st-century skills and the 4 C's (communication, collaboration, critical thinking, and creativity) are currently the focal point of future education. An increasing number of programs addressing these crucial topics are being embedded in school curricula. However, knowledge about the effects of such programs is scarce. This work-in-progress study presents the initial results of students participating in a three-year STEM outreach program named DIGISTEM, spanning grades 10 to 12, within the context of digitization. A total of$N_{\mathbf{sum}}=218$students at the end of the 10th grade (around age 16) took part in the quasi-experimental study.$N_{\mathbf{digi}}=54$students (31 female, 22 male, 1 other) were enrolled in the DIGISTEM program, while$N_{\mathbf{CG}}=162$students (89 female, 62 male, 13 other) from the same school did not participate in the program. The assessed variables included subject knowledge in mathematics, physics, biology, and chemistry, subject interests, motivation in STEM lessons, vocational orientation, the use of digital media in learning contexts, and motivation through digital media in lessons. The results revealed significant differences between students in the program and the control group concerning the use of digital media in learning contexts, vocational orientation, motivation in STEM lessons, and STEM content knowledge. Further findings, such as how students use digital media and tablets for learning contexts, are explored. The findings are discussed in the context of existing research and in terms of practical implications for schools and STEM outreach support programs.