People increasingly use videos on the Web for learning, be it for daily tasks in formal or informal educational settings. To enhance this type of learning, scientists are continuously conducting experiments, proposing guidelines, analyzing data, and researching artificial intelligence methods for tool development. In this comprehensive review, we analyze 257 articles (using PRISMA guidelines) on video-based learning from a technological perspective for the period from 2016 to 2021. One of the aims is to identify video characteristics that support learning as explored by previous research. Based on our analysis, we suggest a taxonomy that organizes the video characteristics and contextual aspects into eight categories: (1) audio features, (2) visual features, (3) textual features, (4) instructor behavior, (5) learners’ activities (play, pause, etc.), (6) interactive features (quizzes, etc.), (7) production style, and (8) instructional design. Also, we identify four representative methodological approaches: (1) tool support of video-based learning, (2) controlled experiments, (3) data analysis studies, and (4) design guidelines for learning videos. We find that the most explored characteristics are textual features followed by visual features, learners’ activities, and interactive features. Tools that aid learning through videos frequently utilize text from transcripts, video frames, and images. The learner’s activity is heavily explored through log files in data analysis studies, and interactive features are frequently scrutinized in controlled experiments. As further contributions, we contrast research findings on how video characteristics affect learning effectiveness, report on tasks and technologies used to develop tools, and summarize design guideline trends to produce learning videos. Our findings provide actionable insights for the design of intelligent educational systems that better support video-based learning.

Zusammenfassung: Im vorliegenden Diskussionsbeitrag wird der Forschungsstand zu Unterrichtsqualität für verschiedene Fachdidaktiken – naturwissenschaftliche Fächer, Sport und Geschichte – vor dem Hintergrund der allgemeinen empirischen Unterrichtsforschung vergleichend diskutiert. Als Vergleichsgrundlage wurde ein Framework mit den sieben Dimensionen Auswahl und Thematisierung von Inhalten und Fachmethoden, kognitive Aktivierung, Unterstützung des Übens, formatives Assessment, Unterstützung des Lernens aller Schülerinnen und Schüler, sozio-emotionale Unterstützung und Klassenführung genutzt (Praetorius und Charalambous 2018). Es zeigte sich, dass die Fachspezifität von der fokussierten Ebene abhing: Während eine Ergänzung des Frameworks auf Ebene der sieben Dimensionen nicht notwendig erschien, waren auf der Ebene der Subdimensionen und insbesondere der diesen Subdimensionen zugeordneten beobachtbaren Indikatoren fachspezifische Anpassungen und Ergänzungen erforderlich. Der Beitrag schließt mit einer Diskussion zentraler Herausforderungen für zukünftige Forschung.

An experimental study investigated the effects of applying principles of the Universal Design for Learning (UDL). Focusing on epistemic beliefs (EBs) in inclusive science classes, we compared four groups who worked with learning environments based more or less on UDL principles and filled out an original version of a widely used EBs questionnaire or an adapted version using the Universal Design for Assessment (UDA). Based on measurement invariance analyses, a multiple indicator, and multiple cause (MIMIC) approach as well as multi-group panel models, the results do not support an outperformance of the extensive UDL environment. Moreover, the UDA-based questionnaire appears to be more adequately suited for detecting learning gains in an inclusive setting. The results emphasize how important it is to carefully adopt and introduce the UDL principles for learning and to care about test accessibility when conducting quantitative research in inclusive settings.

In modern science- and technology-based societies, competencies that allow citizens to reason scientifically play a key role for science- and technology-based careers as well as for democratic co-determination (e

Against the background of many studies focusing either on scientific reasoning or views on the nature of scientific inquiry (NOSI), the aim of this article is to present and empirically analyse a framework that associates these central science education constructs. Based on the idea of inquiry methods, the ScieNo-framework includes three scientific reasoning competencies (‘Scie’) and ten naïve and informed NOSI views (‘No’) that can be aligned on a theoretical level. We test this alignment using data from a quantitative cross-sectional study. In this study, internationally published instruments on scientific reasoning and NOSI views were administered in a sample of 802 students. We estimate structural equation models (SEM) that encompass correlations between scientific reasoning competencies and NOSI views. In order to control for effects of schooling in a second step, we included the grade level as a predictor into these models and checked whether the correlations were stable. The results confirm small to high positive and negative correlations between informed and naïve NOSI views and the scientific reasoning competencies that match the theory-based assumption. We interpret these as a first quantitative confirmation of the ScieNo-framework and open up further perspectives on usage of the framework for science education purposes and for future science education research.