Smart products have received increasing attention from researchers and practitioners alike. One limitation of the existing literature, however, is that the term is often used as a blanket term and that there is no consensus on what a smart product actually is. Because different studies rely on differing conceptualizations, the current body of knowledge is scattered and lacks a uniform language and conceptual boundaries. Specifically, existing research has subsumed inherently different products under one collective term, has relied on a multitude of ad hoc criteria to define smart products or has conflated smart products with the services they render and/or the wider ecosystem, in which they operate. These developments limit the systematic advancement of the field and impede the integration of the smart product concept into related concepts such as the Internet of Things. To address these issues, this article provides an extensive analysis of the status quo of the field, with the goal of developing a common language and comprehensive conceptualization of smart products. First, existing studies on smart products were systematically reviewed across contributing disciplines and supplemented with a bibliometric analysis that allowed for a deeper understanding of the smart product concept within and across disciplines. This analysis revealed an initial set of 16 capability-based criteria that are currently applied to conceptualize smart products. Second, based on a systematic coding procedure, these criteria were synthesized and organized within a comprehensive framework delineating four distinct product archetypes for the digital age: (1) Digital, (2) Connected, (3) Responsive, and (4) Intelligent. Third, three major conceptual themes that arise from this framework are identified and possibilities for future research are pointed out. In sum, this work contributes to the literature by improving the understanding of smart products as an epistemic object and by laying the ground for more cumulative research endeavors. Practitioner Points • The analysis can be used to navigate in the areas of smart products and IoT as well as to leverage a firm's internal understanding of what smart products are and how smart products can be conceptualized as distinct archetypes. • The proposed framework can help to understand how physical and virtual components of a product have to be orchestrated to perform certain functions and services and which requirements need to be fulfilled to lift a product to a more advanced level. • Practitioners may use the framework to decompose value creation at the level of components and functions in order to develop an optimal architecture of a smart product's hardware and software as well as to derive effective pricing models.

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Aim/Purpose: This study aimed to explore whether students’ self-reported use of various learning strategies affected their perceptions on different course activities as well as their perceived performance in terms of both cognitive learning outcomes and general skills. Background: In a highly active learning environment that incorporates research into teaching, the effective use of various learning strategies is considered of high importance for the successful engagement of students. Yet, this line of research has mainly focused on individual learning. Shifting from individual to collaborative learning settings, the current study investigated whether students’ use of self-regulated learning, peer learning, and help seeking strategies influenced their perceptions on both the group activities and the respective outcomes. Methodology: At the beginning of the course, 81 first semester postgraduate students self-reported the level of use of self-regulated learning, peer learning, and help seeking strategies by filling in the respective subscales of the Motivated Strategies for Learning Questionnaire (MSLQ). Then, groups of 3 or 4 students were formed and instructed to create several learning artifacts of different types and conduct a peer-tutoring session, based on a topic assigned to them by the teacher. Additionally, the same groups conducted a research project of their own choice within course topics. Students’ final grade served as an indicator of their academic performance. At the end of the semester, students filled in a questionnaire eliciting their perceptions on the process and the outputs of the course activities. Finally, through statistical analysis of students’ responses to the questionnaires, the influence of learning strategies on students’ perceptions and their academic performance was examined. Contribution: Our findings contribute to the literature regarding the research-teaching nexus in higher education settings. More specifically, the study shows how students’ self-reported use of learning strategies affects students’ perceptions on the activities they were engaged in, their achievement of cognitive learning outcomes, and their skills development in a research-integrated course design. Findings: Students perceived differently the value of producing and studying learning artifacts. Students who scored higher in the self-regulated learning and peer learning subscales of MSLQ perceived their role as more active in the preparation of the presentation for the peer-tutoring session, which was the artifact that required higher level of interaction among the group members. Students’ final grades were influenced partially by their self-reported use of different learning strategies. Recommendations for Practitioners: Integrating research into teaching through the assignment of research-related tasks to students can promote students’ acquisition of domain knowledge and research skills. The merits of this approach can be further strengthened by having students working in groups and providing the outputs of their involvement in the research-related activities as learning material for their peers. Furthermore, students’ individual characteristics (e.g., use of learning strategies and preferences should be taken into account when designing course activities). Recommendation for Researchers: Researchers should continue to explore the way that various learning strategies influence different aspects of the learning process, especially in the achievement of cognitive learning outcomes and the development of general skills. Impact on Society: Creating learning environments that foster students’ active engagement with the course material and peer collaboration should be a vital goal of higher education institutes as it can improve students’ performance and promote the necessary skills for self-directed and autonomous learning, a key competence in the modern workplace. Future Research: In this study, both cognitive learning outcomes and general skills were assessed by students’ final grade. In a future study, distinguishing these different types of learning outcomes would allow us to examine in more detail the impact of students’ learning strategies and course activities on the accomplishment of cognitive learning outcomes and general skills.

The aim of the present study (n = 113) was to examine how (objective and subjective) information on peers' preparation, confidence, and past performance can support students in answering correctly in audience response systems (aka clickers). The result analysis shows that in the “challenging” questions, in which answers diverged, students who received additional information about peers' self‐reported preparation and/or confidence outperformed students who were only given the objective percentage with or without past performance feedback. In addition, students expressed a positive attitude towards the activity, commenting its usefulness in better understanding course material and identifying misconceptions.

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