Learning in the digital world requires not only technological skills for using digital tools but also ethical skills to critically reflect on (in)adequate digital media use and potential negative consequences. These skills are particularly crucial in professions dealing with public welfare and societal issues. Inter alia, those are teachers who educate the youth, legal professionals who judge (il)legal behavior regarding media, or computer scientists who bear responsibility when developing algorithms. Accordingly, higher education students studying teacher education, law studies, or computer science studies should develop ethical skills for the digital world. This study examined how higher education students perceive problematic media behaviors and which digital competences they regard relevant for ethical issues. In addition, the study investigated whether students of teacher education, law studies, and computer science studies differ in their perceptions. To this end, an online survey with N = 461 participating students was conducted. Study results indicated that higher education students perceived problematic media behaviors as such with posting inappropriate content identified as the most problematic. Furthermore, students considered several digital competences as relevant for ethical issues with protecting and acting safely as most relevant. In-depth analyses uncovered subject-specific differences with computer science students being most ethically savvy, albeit differences were only of small effect size. The study provides valuable insights into the intersection of digital competences, ethical considerations, and academic disciplines. In the future, longitudinal and training studies will help to understand how differences emerge and whether students of different study subjects benefit from digital ethics training.

Künstliche Intelligenz (KI) kann im Prozess der Leistungsbewertung assistieren und diesen transformieren. Besonders lohnend scheint eine KI-Assistenz bei der Bewertung von komplexem, geschriebenem Text. Jedoch ist der Einsatz von KI im Bewertungsprozess «hochriskant» (EU 2024) und bedarf umfangreicher Analysen. Die vorliegende Studie untersucht, inwiefern ChatGPT-4o die Auswertung und Interpretation von Lerntagebucheinträgen objektiv vornehmen kann. Dafür werden 757 Lerntagebucheinträge aus der geförderten Weiterbildung in Deutschland von Mensch und Maschine bewertet. Sowohl Mensch als auch Maschine erhalten hierzu Kriterien, nach denen die Bewertung vorzunehmen ist; ChatGPT-4o wird diesbezüglich mit einem Prompt unterstützt. Die Übereinstimmung der Bewertungen wird anhand der Masse Sensitivität und Spezifität gemessen. Die Ergebnisse zeigen, dass die Bewertungsvorschläge von ChatGPT-4o eine moderate bis hohe Übereinstimmung mit den menschlichen Bewertungen aufweisen; gleichzeitig neigt ChatGPT-4o jedoch zu einer optimistischen Bewertung der Lerntagebucheinträge. Die Ergebnisse weisen darauf hin, dass eine hybride Intelligenz, also eine Kombination der Stärken von Mensch und Maschine, gewinnbringend für Bewertungsprozesse sein kann. Künftig denkbar sind halbautomatisierte Bewertungsprozesse von Lerntagebucheinträgen, in denen die KI die Bewertung der Lerntagebucheinträge übernimmt und Lehrkräfte bei kritischen Fällen regulierend eingreifen. So könnte die Korrektureffizienz ohne bedeutende Qualitätsverluste gesteigert werden.

Learning diaries are reflective tools, often used as formative assessments in adult education with the aim to promote cognitive and metacognitive learning strategies. As grading of and feedback on learning diaries is effortful for teachers, artificial intelligence (AI) may assist teachers in evaluating learning diaries. A prerequisite is that AI's ratings show high accordance with the teachers' ratings. AI accuracy, measured via absolute accuracy and bias, is the focus of the current study with N = 540 learning diary entries focusing on learning strategies, seven teachers, and ChatGPT-4o. Findings revealed that AI evaluations align closely with teacher assessments, indicated by high overall accuracy and low bias. Interestingly, the accuracy varied based on the types of learning strategies assessed in the diaries. Additionally, individual teacher assessments influenced the alignment between human and AI evaluations, suggesting that teachers applied their profession-specific expertise to the assessment process while AI produced somewhat generic evaluations. Overall, the study results indicate that AI can enhance the efficiency of formative assessments while providing timely feedback to learners.

For successful learning, monitoring one's learning behavior and outcomes is essential. While both the use of monitoring strategies and monitoring judgment accuracy are regarded as indicators for metacognitive monitoring, their joint contribution to metacognitive monitoring and their interrelationship is unclear. The current study investigated how monitoring strategies and monitoring judgments (spontaneous as well as prompted judgments) change micro-genetically and influence each other reciprocally during an exam preparation phase. In this diary study, N = 273 higher education students completed knowledge tests and surveys on five consecutive days. Results indicated interindividual differences in dependence of prior performance and gender for the accuracy of prompted judgments but not for monitoring strategies or spontaneous judgments. Random intercept cross-lagged panel models revealed that higher quality monitoring strategies led to the spontaneous formation of monitoring judgments, while the quality of monitoring strategies and prompted judgment accuracy did not influence each other significantly.

Evidence syntheses, such as systematic reviews, aim to summarise the current state of research in a field, often using the publication language of a study as a criterion for inclusion or exclusion. However, this has serious implications for capturing evidence from a wider range of geographical areas, and the potential for linguistic bias. In order to explore this issue, a trilingual tertiary mapping review of 446 evidence syntheses within the field of educational technology (EdTech) and published in English, Spanish and German was undertaken, analysing the frequency of multi- and monolingual evidence syntheses, reasons for language choice by research teams, and the composition of research teams in multi- and monolingual evidence syntheses. Items were included if they were a form of evidence synthesis with an explicit method section, indexed within ERIC, Scopus, Web of Science, Dialnet, FIS-Bildung, or Google Scholar, education-related, and published between 1983 and May 2022. The results showed that only eight languages were considered in published syntheses, only five languages were used to construct search strings, most evidence syntheses included research published in English without explaining why, and multilingual research team composition did not predict multilingual evidence syntheses. The findings suggest the need to address publication languages not only as a formal criterion but as an integral aspect of methodological approach, influencing the content and scope of syntheses in educational research.

Synchronous online learning is situated in synchronous webinars, virtual classrooms, and videoconferences, in which students and teachers communicate live over the Internet across distant geographical locations. Shared virtual platforms with voice-over-IP technology and webcams are used to interact ubiquitously and synchronously in real-time. During the COVID-19 pandemic, the use of synchronous online learning environments in primary, secondary, higher, and continuous education has grown massively. In this chapter, we aim to identify design recommendations that help increase the effectiveness of synchronous online learning. First, we provide an overview of recent meta-analyses on the effectiveness of synchronous online learning compared to synchronous face-to-face and asynchronous online learning. Second, we use this empirical evidence to develop design principles that can guide teachers, trainers, and educators in designing effective synchronous online learning environments. Third, we discuss a research agenda for future studies on synchronous online learning, webinars, and videoconferences in education, and we reflect on some practical affordances, including the use of webcams and breakout rooms.