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We propose a model of contextual facilitators for learning activities involving technology (in short: C♭-model) for both on-site and distance learning environments in higher education. The C♭-model aims at systematizing research on digital teaching and learning and offers a roadmap for future research to understand the complex dynamic of factors that lead to successful digital teaching and learning in higher education via suitable learning activities. First, we introduce students' learning outcomes as central benchmarks of teaching and learning with digital technologies in higher education. Second, we want to focus on a major proximal factor for students' learning outcomes and thus apply a learning activities perspective. Learning activities involving digital technologies reflect cognitive processes of students when using digital technologies and are causally connected with students' learning outcomes. Third, we highlight several contextual facilitators for learning activities involving technology in the C♭-model: learning opportunities that result from higher education teachers' instructional use of technology and students' self-arranged learning opportunities involving digital technologies. Apart from these proximal facilitators, we include more distal factors, namely, higher education teachers' knowledge, skills, and attitudes toward digital technology; higher education teachers' qualification; students' and teachers’ digital technology equipment; and institutional, organizational, and administrative factors.

The main aim of gamification, i.e. the implementation of game design elements in real-world contexts for non-gaming purposes, is to foster human motivation and performance in regard to a given activity. Previous research, although not entirely conclusive, generally supports the hypothesis underlying this aim. However, previous studies have often treated gamification as a generic construct, neglecting the fact that there are many different game design elements which can result in very diverse applications. Based on a self-determination theory framework, we present the results of a randomized controlled study that used an online simulation environment. We deliberately varied different configurations of game design elements, and analysed them in regard to their effect on the fulfilment of basic psychological needs. Our results show that badges, leaderboards, and performance graphs positively affect competence need satisfaction, as well as perceived task meaningfulness, while avatars, meaningful stories, and teammates affect experiences of social relatedness. Perceived decision freedom, however, could not be affected as intended. We interpret these findings as general support for our main hypothesis that gamification is not effective per se, but that specific game design elements have specific psychological effects. Consequences for further research, in particular the importance of treatment checks, are discussed. Motivational effects of gamification are analysed from an educational psychology perspective.Gamification is not effective per se, but different game design elements can trigger different motivational outcomes.A self-determination theory framework was used to study the effects of different configurations of game design elements.Competence and autonomy regarding task meaningfulness was affected by badges, leaderboards, and performance graphs.Social relatedness was positively influenced by avatars, a meaningful story, and teammates.

This study investigated the initiation of digitally supported learning activities and personal and institutional factors associated with them in different higher education courses, based on the C♭-model. The C♭-model is a theoretical framework that systematizes contextual factors, which influence students‘ learning activities as the most important facilitator of students’ learning success. Using a self-assessment instrument with anchored scenarios in a sample of 1625 higher education teachers, we were able to identify three levels at which higher education teachers initiated digital learning activities: a low level (powerpointers), a moderate level (clickerers), and a high level (digital pros). The findings also support the relevance of the contextual factors specified in the C♭-model for initiating a high level of digital learning activities, namely digitalization policy and commitment of university administration, institutional equipment, technical and educational support, self-assessed basic digital skills, and self-assessed technology-related teaching skills. All of these factors explain a substantial amount of variance in the level of initiated digital learning activities. We conclude that a comprehensive approach rather than isolated measures might contribute to successful teaching and learning in higher education.

This is the introductory article for the special issue “Technology-related knowledge, skills, and attitudes of pre- and in-service teachers”. It (1) specifies the concept of technology-related knowledge, skills, and attitudes (KSA) of teachers, (2) presents how these KSA are currently assessed, and (3) outlines ways of fostering them among pre- and in-service teachers. The eight articles in the special issue are structured accordingly, and we demonstrate how they contribute to knowledge in these three areas. Moreover, we show how the afterword to the special issue widens the perspective on technology integration by taking into account systems and cultures of practice. Due to their quantitative empirical nature, the eight articles investigate technology at the current state of the art. However, the potential of artificial intelligence has not yet been fully exploited in education. We provide an outlook on potential developments and their implications on teachers’ technology-related KSA. To this end, we introduce the concept of augmentation strategies., Highlights • Review of teachers' technology related knowledge, skills, and attitudes (KSA). • Three areas: specification, assessment, and ways of fostering. • Explanation of contribution of the eight articles in the special issue. • Outlook on KSA changes due to technological developments: artificial intelligence.

Instruments that assess teachers' skills and attitudes on the basis of a broad range of specific standards and demands for teaching with digital technologies are lacking to date. Based on the K19 framework, we validated the scenario-based instrument IN.K19 that simultaneously assesses technology-related teaching skills and attitudes via self-assessment. In our study with N = 90 teachers and student teachers with teaching experience, we demonstrate that the instrument has satisfactory factorial validity in our confirmatory factor analyses. To investigate its predictive validity, we examined the instruments' relationships with teachers' frequency of technology use in class and teachers' initiation of different types of student learning activities involving technology. Results from structural equation modelling show relationships between self-assessed skills in different phases of teaching with technology and the self-reported initiation of student learning activities involving overt actions (active, constructive, and interactive learning activities), supporting the predictive validity of our instrument. Positive attitudes towards technology-related teaching also exhibit positive relationships with the initiation of learning activities involving digital technologies, but more specifically learning activities that do not include observable actions by learners (passive learning activities). Thus, teachers' self-assessed technology-related skills rather than attitudes might contribute to facilitating learning activities crucial for students’ learning.