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Abstract Background The literature asserts that science, technology, engineering, and mathematics (STEM) education needs to be authentic. Although models and modelling provide a basis from which to increase authenticity by bridging the STEM disciplines, the idea of authentic STEM education remains challenging to define. In response, the aim of this study is to identify consensus on significant elements of authentic STEM education through models and modelling. Views were gathered anonymously over three rounds of questions with an expert panel. Responses were subjected to a multimethod analysis that pursued identification, consensus, and stability in the panel’s revealed propositions and themes around authentic STEM education through modelling. Results The panel reached high consensus concerning the potential of STEM education to support learning across traditional subject borders through authentic problem solving. The panel also consented that modelling is indispensable for achieving real-world relevance in STEM education, and that model-based integrated STEM education approaches provide opportunities for authentic problem solving. Furthermore, results showed that integrating individual STEM subjects during teaching, in terms of including disciplinary knowledge and skills, requires specialised competence. Here, technology and engineering subjects tended to implicitly underpin communicated teaching activities aimed at STEM integration. Conclusions and implications The panellists stress that STEM disciplines should be taught collaboratively at the same time as they are not in favour of STEM as a subject of its own but rather as a cooperation that maintains the integrity of each individual subject. Many respondents mentioned integrated STEM projects that included modelling and engineering design, although they were not specifically labelled as engineering projects. Thus, real-world STEM education scenarios are often viewed as being primarily technology and engineering based. The panel responses also implicate a need for multiple definitions of authenticity for different educational levels because a great deal of uncertainty surrounding authenticity seems to originate from the concept implying different meanings for different STEM audiences. These international Delphi findings can potentially inform integrated STEM classroom interventions, teacher education development, educational resource and curriculum design.

Abstract Rapid developments in educational technology in higher education are intended to make learning more engaging and effective. At the same time, cognitive load theory stresses limitations of human cognitive architecture and urges educational developers to design learning tools that optimise learners’ mental capacities. In a 2-month study we investigated university students’ learning with an AI-enriched digital biology textbook that integrates a 5000-concept knowledge base and algorithms offering the possibility to ask questions and receive answers. The study aimed to shed more light on differences between three sub-types (intrinsic, germane and extraneous) of cognitive load and their relationship with learning gain, self-regulated learning and usability perception while students interacted with the AI-enriched book during an introductory biology course. We found that students displayed a beneficial learning pattern with germane cognitive load significantly higher than both intrinsic and extraneous loads showing that they were engaged in meaningful learning throughout the study. A significant correlation between germane load and accessing linked suggested questions available in the AI-book indicates that the book may support deep learning. Additionally, results showed that perceived non-optimal design, which deflects cognitive resources away from meaningful processing accompanied lower learning gains. Nevertheless, students reported substantially more favourable than unfavourable opinions of the AI-book. The findings provide new approaches for investigating cognitive load types in relation to learning with emerging digital tools in higher education. The findings also highlight the importance of optimally aligning educational technologies and human cognitive architecture.

Abstract This commentary expands the notion that models and modelling can be used as a basis to foster an integrated and authentic STEM education and STEM literacy. The aim is to synthesize key publications that document relationships between authenticity, models and modelling, and STEM education. The implications of the synthesis are as follows: authenticity must be viewed as a cornerstone of STEM literacy; models and modelling processes can bridge the gap between STEM disciplines through authentic practices; models and modelling should be used as a means to promote STEM literacy and the transfer of knowledge and skills between contexts, both in and out of the STEM disciplines; modelling activities can serve as a meaningful route toward authentic STEM education; teaching authentic modelling processes must be rooted in explicit and tested frameworks that are based on the practice of the STEM disciplines; and, authentic STEM education should be driven by developing interaction between STEM subjects in parallel with maintaining the integrity of each subject. If this vision is to be reinforced, it is of utmost importance that implementing any model-based authentic educational activities are underpinned by evidence-based frameworks and recommendations for teaching practice. It is therefore imperative that intended model-based pedagogies for STEM education classrooms are further researched, in order to contribute to an integrated STEM literacy.