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.

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.

Global challenges like climate change emphasize the need for technological literacy in today's society. Additionally, as technologies such as artificial intelligence advance, data literacy becomes increasingly important. However, these competencies are often not systematically promoted in general education. This paper therefore explores the intersection of technology and engineering literacy with data literacy in the context of STEM education, focusing on the school subject Science and Technology (S&T) in Germany. It addresses the need for innovative educational approaches to integrate these competencies, using electric drive technology as an exemplary technical area. It proposes an interdisciplinary experiment to interconnect competency domains and aligns with facets of the International Technology and Engineering Educators Association's standards. To bridge the gap between educational plans and innovative concepts, this paper introduces a low-cost, 3D-printed electric motor test bench for K-12 students, promoting technology literacy and data literacy. This tool allows students to create their own product and use it for experiments, what should foster motivation and engagement. The test bench includes sensors for recording speed, torque, voltage, and current, facilitating the collection of motor characteristic curve data. These measurements are processed by a microcontroller and can be transferred to spreadsheet programs for analysis. Moreover, no-code or low-code data analysis tools like Orange3 extend the possibilities of data evaluation. The presented low-cost electric motor test bench is one example toward enhancing technology and data literacy in K-12 education. By linking established curricula with future-relevant competencies, it empowers students to engage with real-world challenges and develop essential skills for the future and adds value to the global dialogue on how to positively contribute to the advancement of engineering education.

International institutions, including the EU, have underscored the importance of fostering digitalization-related skills among students. The role of attitudes toward learning with digital technologies is pivotal in anticipating motivation and practical utilization within working contexts. Recent research revealed a deficiency in opportunities for students during their univer-sity education, specifically in dedicated courses or spaces for utilizing digital technologies. In response, pedagogical-didactic makerspaces for student training were implemented as part of a project initiative. This study examines the interplay of technology acceptance facets in makerspace engagement and digital learning intentions, utilizing regression models. Fifty-eight students have been involved so far. Utilizing a validated questionnaire based on the Unified Theory of Acceptance and Use of Technology (UTAUT), adapted with additional facets of user support and user training, the research investigates the technology acceptance of the given sample. Through hierarchical binary logistic regression, it was found that only effort expectancy significantly influenced the frequency of makerspace visits, emphasizing the role of user-friendliness in motivating students. The findings suggest that designing makerspace experiences with low complexity is useful for overcoming initial user-friendliness hurdles. Additionally, integrating makerspace visits into educational programs can enhance technology acceptance. Future research should assess specific makerspace use cases with a larger sample and investigate sample effects in relation to the academic disciplines.