This study aimed to investigate the impact of a data-driven teaching approach on students’ conceptual understanding of machine learning (ML). To this end, an exemplary intervention was designed and evaluated using a pre- and post-test design and a German-language Concept Inventory on Machine Learning. A total of 83 German ninth-grade students participated in the study. The results revealed significant learning gains related to data handling and the ML workflow. In contrast, conceptions about the inner workings of ML models largely persisted. The effectiveness of the intervention varied depending on context, with greater gains observed in the text generation domain than in facial recognition, highlighting challenges in cross-contextual transfer of understanding. A regression analysis showed no significant influence of students’ pre-instructional conceptions on learning outcomes. These findings demonstrate both the potential and the limitations of data-driven teaching approaches and emphasize the need for more explicit engagement with learners' misconceptions to foster deeper conceptual change.

Foreign perspectives help to advance and refine computer science (CS) education; however, existing international research frameworks for CS Education (CSE) in schools are mostly Western-centric. This paper aims to complement these findings with insights into CSE in a non-Western country, by isolating specific approaches in teaching CS. Due to the cooperation between the German and Japanese universities, to which the authors belong, an exchange about Japanese CS education was found to be particularly profitable. This paper seeks to establish this insight from two perspectives: the intended and enacted CS curriculum. Background research to the revised Japanese CS curriculum standard from 2018, governmental initiatives and studies of Japanese CS literacy provided a theoretical frame of Japanese CSE. To complement these findings, four interviews were conducted with Japanese CS teachers from different schools. Statements of this enacted Japanese CS curriculum were isolated and, in context with the background research, related to Western implementations. Therefore, this paper summarizes findings of Japanese CSE which differ from Western-centric approaches as learned concepts that are worth considering for enhancing future CSE. These include a holistic way to implement CS in elementary schools, a resource for extensive standards regarding social impacts of CS, and structures for integrated teacher training.

This contribution presents a case study on the extension of traditional approaches to blended learning in theoretical computer science at university level by incooperating modern multitouch tabletop displays for collaborative learning. The evaluated serious game about regular expressions provides a collaborative learning experience for groups of students and allows precise control of difficulty. It includes gamification elements and allows extensive analytics of learner activities. The didactical approach is evaluated in a case study with randomized test and control groups consisting of students in the same semester who had no curricular contact with the topic prior to the experiment. The test group consisting of 34 students tackled regular expressions by playing the learning game with minimal intervention by an educator. The control group consisting of 59 students had a lecture about the same contents as the learning game. To measure the success of the game regarding learning outcome, three tests were taken, a pre-test prior to and a post-test after the instructional phase. To compare the sustainability of both methods, a third test was taken two weeks later. The results are discussed regarding the learning outcomes on different levels of Anderson and Krathwohl’s revised version of Bloom’s taxonomy of educational objectives.