Constructing Learning Together: The Social and Technological Conditions For Active Learning in STEM Education

This dissertation examined how active learning strategies can be effectively applied in higher STEM education. Active learning encourages student engagement, self-reflection, and deep learning, and often involves peer collaboration and digital tools. Because such strategies depend on both interpersonal dynamics and thoughtful technological design, four studies were conducted to explore how active learning can be successfully integrated into university STEM courses. Chapter 2 presents a case study on an online pre-lab module that enables biochemistry students to design their own experimental protocols. The study demonstrates that digital tools can strengthen instructional scaffolding in laboratory education. Data were collected through questionnaires, an interview with the course coordinator, and comparisons of report grades. Automated feedback and online teacher guidance helped students avoid errors and better understand the structure of experimental work. Report grades increased significantly compared to the previous year, possibly because the module also served as a digital lab journal, reducing cognitive load during lab work and supporting more coherent reasoning in final reports. Students expressed intrinsic motivation to use the module and felt it improved their understanding of the experiments. The course coordinator and lab supervisors confirmed this, although students stressed that interaction with lab supervisors remained essential. Chapter 3 presents a meta-analysis showing that technology-supported online peer feedback leads to better learning outcomes than traditional paper-based feedback. Although effect sizes were small to medium, the results indicate a clear positive impact. Asynchronous digital environments allow students to engage with the feedback process at their own pace, fostering more thoughtful, constructive comments. This can enhance intrinsic motivation through increased autonomy. Digital platforms also help instructors monitor the feedback process. A systematic review of student perspectives revealed that technology-supported feedback can boost extrinsic motivation, but students noted that asynchronous communication may limit dialogue and hinder clarification. Chapter 4 compares a structured online peer feedback tool with a traditional approach using a text editor and email. Using a quasi-experimental crossover design, students provided feedback on two assignments using both platforms. While final report grades did not differ significantly, the nature of the feedback did. Feedback written in the text editor included more global, revision-oriented comments, whereas feedback in the structured tool was more superficial. This difference may stem from the requirement to provide at least 20 comments in the tool, potentially increasing cognitive load and encouraging students to focus on easy-to-spot issues. Despite this, students preferred the structured tool for its usability and centralized interface. Some, however, appreciated that email allowed for more personal interaction. These findings show that platform design, such as required comment counts, feedback prompts, and anonymity settings, strongly influences the quality and experience of peer feedback. Chapter 5 examines how anonymous versus non-anonymous online peer feedback on students’ trust, psychological safety, and feedback quality when assessing professional competencies. The findings challenge the assumption that anonymity promotes safety or higher-quality feedback. Non-anonymous feedback resulted in longer, more balanced comments with both constructive suggestions and positive reinforcement. Anonymity appeared to reduce students’ sense of responsibility, leading to more superficial responses. Emotional distance created by anonymity may hinder meaningful engagement. Students who participated in a follow-up feedback dialogue benefited from opportunities to clarify comments and interpret facial expressions, which enhanced the perceived value of the feedback. The general discussion integrates findings from all studies and situates them in the broader literature. While online tools can support the structure and flexibility of active learning, their effectiveness depends not only on technology but also on the creation of a supportive, inclusive learning environment. Psychological safety, trust, and meaningful interaction, both online and face-to-face, remain essential components of successful active learning in STEM education.