Aligning lecture contents with learning objectives, as well as the integration of interactive elements, can increase the efficacy of video-based learning. However, their integration, i.e., the alignment of learning objectives with interactive elements, has not yet been systematically explored. Currently, integrating interactive elements is driven more by personal beliefs than evidence-based strategies. We address this research gap with a mixed-method study in the context of an information systems course. Based on the students’ subjective perception, we investigated the alignment between learning objectives and interactive element types, as well as the underlying rationale. Our results indicate that quizzes are most suitable for different purposes, annotations are never unsuitable but only needed on higher complexity levels, and navigation features are merely nice-to-have. The systematic understanding of interactive elements offers valuable guidance for educators and scholars, contributing to best practices in online education.

Crowdsourcing has emerged as a pivotal force driving innovation and problem-solving in today’s digital landscape. Yet, to sustain this momentum and meet the dynamic demands of the labor market, prioritizing learning opportunities within crowdsourcing is imperative. Current platforms face criticism for neglecting skill development, leaving it primarily the workers’ responsibility. This article delves into how crowdsourcing platforms can enhance support for workers’ learning. Through a structured literature review, we synthesize learning approaches within crowdwork literature in a conceptual mapping. We then practically apply theoretical findings to the successful platform “Kaggle”, examining how the platform supports data literacy learning. Through our investigations, we offer both theoretical insights and practical observations, aiming to catalyze further exploration and enhancement of learning opportunities within crowdwork.