Software testing plays a critical role in the success of software development projects. As the complexity of software grows, the demand for qualified software testing specialists is rising. Despite this, a gap persists between the knowledge required in the industry and the competencies offered in academic curricula. To delve deeper into educational strategies, this study investigates the state of software testing education in German higher education by analyzing module manuals from 162 Universities and Universities of Applied Sciences manually, focusing on Information Systems, Computer Science, and Information and Media Technology-related study programs. We assess in 754 study programs the integration of teaching methods and competencies of 1.552 modules related to software testing. The research identifies variations in educational approaches and gaps between the instructional content and industry standards, e.g., the ISTQB Foundation Level. The findings emphasize the importance of aligning software testing education with industry standards and suggest incorporating practical, project-based learning to better prepare students for the professional demands of software testing. Therefore, based on teaching approaches from the module manuals, we provide recommendations to enhance the integration of software testing in curricula, focusing on the broader inclusion of ISTQB standards, practical exercises, and interdisciplinary teaching approaches. This study contributes to the ongoing discourse on improving software testing education and highlights areas for future research in academic and practical contexts.

Chatbots represent a promising approach to provide instructional content and facilitate active learning processes. However, there is a lack of knowledge as how to design chatbot interactions for active learning. In response to this knowledge gap, we conducted an experimental study (n = 164) comparing four modes for providing instructional content in chatbots, with varying demands for cognitive engagement. The four modes – passive, active, constructive, and interactive – were based on the ICAP framework of active learning. The learning content concerned identification of phishing emails and the four modes were distinguished by how the participants were invited to engage with the content during their chatbot interaction. The ICAP modes of higher cognitive engagement required participants to spend more time on the interaction and led to perceptions of higher subjective learning outcome. However, the effects of the different ICAP modes were not found to be significantly different in terms of user engagement, social presence, intention to use, or objective learning outcomes. The study represents an important first step towards understanding the design of chatbots for active learning.

Enrollment in online courses has sharply increased in higher education. Although online education can be scaled to large audiences, the lack of interaction between educators and learners is difficult to replace and remains a primary challenge in the field. Conversational agents may alleviate this problem by engaging in natural interaction and by scaffolding learners' understanding similarly to educators. However, whether this approach can also be used to enrich online video lectures has largely remained unknown. We developed Sara, a conversational agent that appears during an online video lecture. She provides scaffolds by voice and text when needed and includes a voice-based input mode. An evaluation with 182 learners in a 2 x 2 lab experiment demonstrated that Sara, compared to more traditional conversational agents, significantly improved learning in a programming task. This study highlights the importance of including scaffolding and voice-based conversational agents in online videos to improve meaningful learning.