arXiv subjects

Sebastian Becker-Genschow

Publications and source records attributed to Sebastian Becker-Genschow.

4 recordsLinked to original sources

arXiv2026

AI-supported data analysis boosts student motivation and reduces stress in physics education

The integration of artificial intelligence (AI) into education presents new opportunities for supporting learning processes. This study investigates the impact of AI-assisted versus traditional Excel-based data analysis on both learning outcomes and emotional-motivational responses in a physics education context. A custom GPT-based chatbot, ExperiMentor, was developed to support student teachers in analyzing experimental data from thread and spring pendulum experiments. Fifty student teachers were randomly assigned to either the AI or Excel group, with both groups completing identical tasks in a guided setting. Learning progress was measured using pre- and post-tests, while emotional and motivational variables were assessed through structured surveys. Both groups demonstrated significant learning gains, with no statistically significant differences found between them in terms of cognitive performance. However, the AI group reported substantially higher levels of engagement, enjoyment, and perceived method effectiveness compared to the Excel group. These findings suggest that interactive AI tools may enhance the affective dimensions of learning, even when cognitive outcomes remain comparable to traditional methods. The results underscore the importance of integrating AI not as a replacement for instructional design, but as a supportive element within pedagogical frameworks. Future research should explore long-term retention effects, the role of learner diversity, and comparisons with other forms of pedagogical support.

physics.ed-ph↗

arXiv2025

Teacher training in the age of AI: Impact on AI Literacy and Teachers' Attitudes

The rapid integration of artificial intelligence (AI) in education requires teachers to develop AI competencies while preparing students for a society influenced by AI. This study evaluates the impact of an online teacher training program on German in-service teachers' AI literacy, usage behaviors, and attitudes toward AI. A pre-post design study was conducted with teachers (N1 = 291 for AI literacy, N2 = 436 for attitude assessment) participating in the course. The program combined synchronous and asynchronous learning formats, including webinars, self-paced modules, and practical projects. The participants exhibited notable improvements across all domains: AI literacy scores increased significantly, and all attitude items regarding AI usage and integration demonstrated significant positive changes. Teachers reported increased confidence in AI integration. Structured teacher training programs effectively enhance AI literacy and foster positive attitudes toward AI in education.

cs.CY↗

arXiv2024

Building Bridges: AI Custom Chatbots as Mediators between Mathematics and Physics

This work explores the integration of AI custom chatbots in educational settings, with a particular focus on their applicability in the context of mathematics and physics. In view of the increasing deployment of AI tools such as ChatGPT in educational contexts, the present study examines their potential as personalized tutoring systems. The study assesses the impact of AI-generated learning materials on the learning experiences and performance of sixth-grade students, with a particular focus on proportional relationships in mathematical and physical contexts. The randomized controlled study with N = 214 students compared traditional textbook materials with explanations generated by a custom chatbot. The results demonstrated that while AI-generated materials had an indefinite impact on learning outcomes, they significantly enhanced positive-activating emotions, situational interest, and self-efficacy, while reducing intrinsic and extrinsic cognitive load. These findings underscore the potential of AI to transform educational practices by fostering a superior learning experience. However, further research is required to clarify its impact on learning performance and long-term learning outcomes. The study highlights the importance of careful integration and customization of AI tools to maximize their benefits in physics education.

physics.ed-ph↗

arXiv2024

A Systematic Review of Empirical Research on Graphing Numerical Data in K-12 STEM Education

Graphs are essential representations in the professions and education concerning the science, technology, engineering, and mathematics (STEM) disciplines. Beyond their academic relevance, graphs find extensive utility in everyday scenarios, ranging from news media to educational materials. This underscores the importance of people's being able to understand graphs. However, the ability to understand graphs is connected to the ability to create graphs. Therefore, in school education, particularly in STEM subjects, not only the understanding but also the skill of constructing graphs from numerical data is emphasized. Although constructing graphs is a skill that most people do not require in their everyday lives and professions, it is a well-established student activity that has been empirically studied several times. Therefore, since a synthesis of the research findings on this topic has not yet been conducted, a summary of the studies investigating graphing via various viewpoints and differing methods could be a valuable contribution. To provide an overview of the empirical literature on this important topic, our systematic review identifies how the construction of convention-based graphical representations of numerical data, referred to as graphing, has been studied in previous research, how effective graphing is, and which types of difficulties are encountered by students. Based on these aspects, we defined inclusion criteria that led to 50 peer-reviewed empirical studies on graphing in K-12 STEM education found in SCOPUS, ERIC, and PsychInfo. Graphing instruction seemed to be beneficial for student learning, not only improving graph construction but also graph interpretation skills. However, the students experienced various difficulties during graphing, both during graph construction and the interpretation and usage of data.

physics.ed-ph↗