Interdisciplinary Science Research Articles (Page 1)

Employability has become globally an explicit graduate outcome usually, although not without challenge, articulated as a set of graduate skills or capitals. It is therefore important to consider curriculum design and pedagogies that support these outcomes. Problem-based learning (PBL) is often cited as an effective pedagogy in this regard, particularly in education for the professions. Much less attention has been paid to pedagogies for employability in the pure sciences. Here we survey student perceptions of employability skills in an interdisciplinary science degree, taught by PBL, as they develop in the course of an undergraduate programme encompassing seven cohorts over five years. We present evidence that students’ beliefs in their acquisition of skills and their importance grows over the years of the degree. We emphasise the importance of conceptualising and embedding employability (as with the science content) as a developmental activity with multiple opportunities for systematic practice.

Basement membrane structure and function: Relating biology to mechanics.

This commentary explores the synergistic integration of Mongolian Mind-Body Interaction Therapy (MMBIT) with modern Systems Theory to offer a roadmap for advancing integrative psychosomatic care. By blending traditional Mongolian medical wisdom (Heyi/Xila/Badagan?triad) with interdisciplinary systems science, MMBIT provides a holistic framework for treating mind-body disorders through its Material-Energy-Information Triadic Interaction Model. This commentary highlights the theoretical foundations, clinical applications, and technological innovations of MMBIT, demonstrating its potential to transform integrative medicine and global healthcare practices.

The integration of data science into interdisciplinary research (IDR) has become a cornerstone in addressing complex global challenges, particularly in the digital era. In Vietnam, while there has been a growing recognition of data science's potential, its integration into interdisciplinary research remains in the nascent stages. This paper examines the current situation of interdisciplinary research with data science in Vietnamese universities, identifying key challenges and opportunities. The study highlights the importance of infrastructure development, human capital, and collaborative frameworks to promote data science across academic disciplines. It also provides strategic recommendations for fostering a data-driven research ecosystem, ensuring sustainable development and global competitiveness. The paper concludes by proposing actionable steps for Vietnam to establish itself as a leader in interdisciplinary data science research, contributing to solving pressing societal issues.

Abstract To foreground the role of mathematics in interdisciplinary STEM contexts, this study examined the kind of orchestrations embedded in the design that can elicit students’ covariational reasoning as they investigate scientific phenomena. The authors draw on data from three students, collected during two design experiments within a larger study in middle school classrooms, to discuss the forms of covariational reasoning that are possible and the specific orchestrations that might support them. This study contributes to the field by highlighting the pivotal role of questioning for eliciting different students’ forms of covariational reasoning in both mathematics education and interdisciplinary math and science education. The authors present an emerging design framework of covariational reasoning orchestrations, which consist of two forms of synergies in their design: between artifacts (digital simulation, table, and graph), and between artifacts and questioning. This framework can support researchers and designers to incorporate the study of covariational reasoning in interdisciplinary STEM contexts.

Abstract This five-year longitudinal study explores the potential influence of interdisciplinary science, technology, engineering, and mathematics (STEM) training on the development of innovation capacities among Ph.D. graduate students. Guided by Kegan’s (2009) constructive-developmental theory the research assesses how participation in an interdisciplinary program predicted the growth rate of student’s cognitive, social, and intrapersonal capabilities to innovate and develop contextually beneficial new ideas. The study uses a longitudinal design and hierarchical blocked regression using both a large control group with covariate-adjusted analyses and a smaller propensity score matched control group to evaluate these differential rates of innovation capacity development. Results demonstrate that five years of Ph.D. interdisciplinary training predicts an acceleration in the development of innovation capacities by well over one quarter of a standard deviation (β = .40-.41) – a very substantial increase. Stronger innovation capacities are observable in participating students’ creativity, proactivity, and teamwork across diverse fields. These findings highlight the potential of interdisciplinary STEM programs to meet modern scientific and industrial demands for innovative, adaptive researchers, while also underscoring challenges in scaling such programs within traditional academic structures. Implications for program design, student engagement, and the effectiveness of interdisciplinary approaches in higher education are discussed.

A guide to developing harmonized research workflows in a team science context.

Bringing new approaches to science teaching such as interdisciplinary, problem-based teaching into schools has proved a slow and difficult process. One of the means to bring about the change is through teacher education. This study is a qualitative study inspired by constructivist Grounded Theory which explores how four new teachers educated from programmes with an explicit focus on changing science teaching in schools, experience the transition from being a teacher student to being a teacher. The study found that new teachers were able to transfer approaches to science teaching from education to profession in the cases where 1) their teaching profile gave them the flexibility to plan interdisciplinary science teaching, 2) education and discourse in the schools aligned, 3) they were supported by management and 4) they experienced support in a community of practice with people they had studied with.

Safeguarding the blue lifeline: interdisciplinary science for sustainable rivers and watersheds

Fair and equal access to information is part of human rights and an important foundation for inclusive development. However, in practice, there are still significant gaps in access, especially for vulnerable groups such as people with disabilities, the elderly and remote communities. This research aims to examine how the principle of inclusivity is implemented in library services and examine the strategic role of library science in supporting access to information for all. This research uses a descriptive qualitative approach with data collection techniques in the form of in-depth interviews, observations, and document studies in several public libraries, schools, and universities in Indonesia. The results showed that most libraries have started to implement inclusive principles in physical aspects, such as providing accessibility for the disabled. However, the implementation of inclusive collections and information services is still limited. Librarians play an active role as literacy facilitators and social agents, but limited training and policy support hinder their effectiveness. Structural constraints such as lack of funding and low user participation are also major challenges. The discussion points to the importance of developing a more interdisciplinary library science and libraries as social justice institutions. This research recommends the need for systemic transformation through strengthening the capacity of librarians, participation-based policies, and integrating universal design principles and user needs-based services as a foundation in realizing inclusive and sustainable libraries.

Abstract This study explores how disciplinary identity construction in STEM (Science, Technology, Engineering and Math) graduate education can hinder the development of interdisciplinary scientists. While past research exploring interdisciplinary science often highlights knowledge incompatibilities as the primary obstacle hindering collaboration, our findings suggest that identity incompatibilities also contribute significantly to the ongoing challenges in interdisciplinary research. To examine the identity construction processes during graduate education, we extend research on disciplinary identity by linking it to existing research in organizational discourse and discursive identity. Through this discursive identity framework, we analyze a cohort of science graduate students—half of whom participate in an NSF-sponsored interdisciplinary training program—to illustrate how social-disciplinary pressures inadvertently discourage trainees from embracing interdisciplinary identities. As a result, these pressures limit the formation of robust interdisciplinary identities among emerging scientists. We conclude by discussing implications involving potential paths toward overcoming the insufficiencies of interdisciplinary discourses.

Biophysics is an interdisciplinary science that applies the theories and methods of physics to understand biological systems. It encompasses a wide range of topics, from the molecular mechanisms within cells to the physical properties of organisms and ecosystems. The goal of biophysics is to uncover the physical principles underlying the structure and function of biological molecules, cells, and cellular systems, providing a deeper understanding of life itself. The Institute of Biophysics, Czech Academy of Sciences (IBP) stands as a beacon of excellence in the field of biophysical research in the Czech Republic. This article delves into its history, structure, research areas, and major scientific achievements, highlighting the role of IBP in the global scientific community.

Despite the need to transform food systems to improve human and planetary health, the activities and actors of food systems remain largely intransigent to change. The Mandala research consortium offers a case study of how three methodological principles—interdisciplinary science, systems thinking and stakeholder collaboration—can be integrated to identify interventions with transformative potential in an urban food system. An existing conceptual framework was employed to interrogate the case study and reflect on the challenges and opportunities of its methods across two phases: (i) understanding the food system and identifying places to intervene; (ii) envisioning and prioritizing food system interventions. Ambitions to work across the breadth of the urban food system were supported by interdisciplinary science and stakeholder collaboration; tailoring the research process accommodated the epistemic, social, symbolic, spatial and temporal differences between stakeholders. A complex adaptive systems approach enabled identification of promising food system interventions. Nevertheless, challenges arose in every aspect of the work. A collaborative interdisciplinary systems approach to system transformation was articulated using a real-world example. While opportunities support the funding and design of research using a similar methodological approach, the documented challenges of adopting this approach may be overcome with practical solutions.This article is part of the theme issue ‘Transforming terrestrial food systems for human and planetary health’.

Albert Hirschman (1915–2012) was an economist known for his influential interdisciplinary social science models. In the 1950s, he developed the theory of unbalanced growth, which changed development theory. Hirschman argued that partial effects induced by targeted investments can have positive economic impacts on the development of national economies. In another behavioural model – exit and voice, he explains how dissatisfied individuals can react and how these reactions may affect the quality of output provided in both private and public goods. Hirschman's ideas have been incorporated into many concepts in the social sciences.

ABSTRACT This study aims to evaluate the interdisciplinary science teaching practices conducted in the context of socioscientific issues and pre-service science teachers’ opinions about the course. The participants (N = 59) are fourth-year students from two classes in the science teacher education program. In line with the purpose of the study, the case study design, one of the qualitative research designs, was preferred. The data collected using the ‘Interdisciplinary Science Teaching Levels Rubric’ and a ‘Semi-Structured Interview Form’ as data collection tools were analyzed. As a result of the implemented practices, it was determined that the pre-service teachers were generally able to carry out interdisciplinary science teaching in the context of socioscientific issues (SSIs) effectively. When the pre-service teachers’ opinions about the course were evaluated, the following themes were identified: the essential components of interdisciplinary science teaching, the contributions of SSIs to the interdisciplinary science teaching course, and suggestions for delivering the course more effectively. Based on the findings and the identified themes, various suggestions were made.

Our introductory essay to the Journal of Macromarketing special issue on futurology advances macromarketing as the discipline best positioned to facilitate humanity's preferred future. Framed by foundational assumptions about artificial intelligence, transhumanism, post-scarcity economies, and socio-ethical evolution, macromarketing must shift from predicting to inventing that future. The pertinent research-amenable problems are best resolved with future-oriented foresight tools such as scenario planning, causal layered analysis, backcasting, and immersive speculative design. Critical engagement with borrowed theories, rigorous scrutiny of underlying assumptions, contextual precision over broad generalizability, and prioritizing sustained human flourishing are vital to advancing an equitable, sustainable, inclusive, and meaningful future for all. Hence, we position macromarketing as a normative, interdisciplinary social science that can anticipate, shape, and ethically guide transformative technological and societal trajectories.

This article examines the growing prevalence and challenges of interdisciplinary data science education (IDSE) in higher education globally. We argue that while data science education has traditionally focused on statistical and computational skills, these emerging challenges require urgent attention as interdisciplinary data science becomes increasingly computational, intelligent, and expansive. Drawing on over 35 years of combined teaching experience across multiple European universities, we identify and analyze four critical areas facing IDSE classrooms, namely: interdisciplinarity; skills differences; decolonization; and ethics. By reflecting on these challenges, we emphasize the urgent need for data science educators to model conscious, critical, and reflexive interdisciplinary data science praxis in an increasingly data-dependent world. This is even more escalated by the fact of a fast-growing development of AI, ML, and political discussion on governance and impact of everyday life. The article concludes by advocating for an international community of data science educators across disciplines to address these challenges collectively.

Knowledge integration remains, paradoxically, both a key methodology and an elusive mystery in crossdisciplinary work such as interdisciplinary studies, team science, and transdisciplinary research. Many case studies have described compound events and iterations leading to remarkable integrative achievements. Even though a wealth of work on integration indicates that such achievements are common and desirable, there is no context-crossing approach to modeling how multiple integrations can connect to generate larger or more complex integrative results. There is thus an important need to develop an approach for unfolding integration that supports the full variety of integrative practices and theories. In the absence of such an approach, theorists and practitioners must either craft unique accounts for each case-which are difficult both to create and transfer-or reach general conclusions about what the smaller integrations have in common. This article draws upon and contributes to the philosophy of interdisciplinarity, proposing a new, structural approach to modeling connected integrations called integrative topologies. Each topology provides a model of connected integrations that can be customized for different situations instead of starting from scratch or abstracting away from intermediate integrations. First, the article develops simple rules for integrative pathways based on the input-process-output model of integration. Then, the weave, zipper, and chain topologies are introduced along with their hybrids. Next, the article illustrates how integrative topologies can make it easier to teach, plan, facilitate, describe, and evaluate complex combinations of expertise in crossdisciplinary work. The article concludes with areas for future philosophical research on knowledge integration.

This study examines the integration of social-scientific collaboration and local wisdom through bilingual learning to develop 21st-century competencies. This qualitative, descriptive phenomenological research was conducted with eighth-grade students at Muhammadiyah 1 Junior High School Kartasura. Data was collected via in-depth interviews, participant observation, and document analysis, validated through source and technique triangulation, as well as member checking. The results indicate that interdisciplinary integration Social Studies, Natural Sciences, Javanese Language, and English, combined with local wisdom and bilingual learning, significantly enhances students critical thinking, creativity, collaboration, character, and cultural identity. Project-based learning relevant to daily life and local culture fosters greater student engagement, confidence, and active participation. Phenomenological analysis reveals that students experience more meaningful and contextual learning, gaining a deeper understanding of social and cultural values, alongside increased pride and emotional attachment to their local culture. Students are able to connect academic concepts with real-life experiences, enhancing motivation and learning quality.

Abstract This critical review examines the transformative role of machine learning (ML) in revolutionizing thermoplastic recycling across mechanical, chemical, and biological pathways. As global plastic waste challenges intensify, sophisticated ML approaches are emerging as powerful tools to overcome traditional recycling limitations. Recent technological breakthroughs are systematically analyzed that leverage ML to optimize sorting precision, process efficiency, and quality assurance in recycled thermoplastics. The review presents a detailed analysis of feature engineering strategies that have proven most effective across diverse recycling applications. By identifying current implementation barriers and unexplored opportunities, a forward‐looking research agenda is established for ML integration that can accelerate progress toward a truly circular thermoplastic economy. This interdisciplinary perspective bridges materials science, computer science, and sustainability to provide actionable insights for researchers and industry practitioners.