Search for: All records

To pursue transdisciplinary education, bringing together different disciplinary perspectives is necessary. As two graduate researchers, in engineering technology and anthropology, on a National Science Foundation (NSF) Improving Undergraduate STEM Education research project, we want to embody and explore our role in the journey to pursue transdisciplinary education. Our familiarity with higher education as students, our different disciplinary backgrounds and lived experiences, and our training as an engineering technology educator and a social scientist contribute greatly to the advancement of understanding the project. Harnessing our combined expertise enables us to see collaborative co-teaching, group learning, and student engagement in new ways. Often transdisciplinary education research is approached from siloed disciplines or from a single perspective and not inclusive of graduate students' perspectives. We find ourselves working on a collaborative cross-college project between three different colleges, Business, Engineering Technology, and Liberal Arts, where faculty and students are co-teaching and co-learning in a series of design and innovation courses. A key element of this project is gathering and using stakeholder data from students, faculty, and administrators. Midway through our three-year project, the NSF project’s external reviewer highlighted the crucial value added of having graduate researchers looking at transforming higher education towards transdisciplinarity. With that in mind, we offer some guiding thoughts about collaborative research among graduate students and faculty from different academic disciplines. This includes tips on how we collaborated in coding, analysis, and data presentations. Using project examples, we will discuss how we used tools for collaboration such as NVivo Teams and Microsoft Teams; these platforms aided in contributing to the iterative research design of this project and research outputs. Our process was strengthened by active participation in project meetings with faculty, educational community events, and data review sessions to reach data consensus. We have noticed how transdisciplinarity can transform undergraduate learning and encourage cross-college faculty collaboration. We will reflect on the significance of collaboration at all levels of higher education. Furthermore, this experience has set us on the path to becoming transdisciplinary scholars ourselves. 

There have been numerous demands for enhancements in the way undergraduate learning occurs today, especially at a time when the value of higher education continues to be called into question (The Boyer 2030 Commission, 2022). One type of demand has been for the increased integration of subjects/disciplines around relevant issues/topics—with a more recent trend of seeking transdisciplinary learning experiences for students (Sheets, 2016; American Association for the Advancement of Science, 2019). Transdisciplinary learning can be viewed as the holistic way of working equally across disciplines to transcend their own disciplinary boundaries to form new conceptual understandings as well as develop new ways in which to address complex topics or challenges (Ertas, Maxwell, Rainey, & Tanik, 2003; Park & Son, 2010). This transdisciplinary approach can be important as humanity’s problems are not typically discipline specific and require the convergence of competencies to lead to innovative thinking across fields of study. However, higher education continues to be siloed which makes the authentic teaching of converging topics, such as innovation, human-technology interactions, climate concerns, or harnessing the data revolution, organizationally difficult (Birx, 2019; Serdyukov, 2017). For example, working across a university’s academic units to collaboratively teach, or co-teach, around topics of convergence are likely to be rejected by the university systems that have been built upon longstanding traditions. While disciplinary expertise is necessary and one of higher education’s strengths, the structures and academic rigidity that come along with the disciplinary silos can prevent modifications/improvements to the roles of academic units/disciplines that could better prepare students for the future of both work and learning. The balancing of disciplinary structure with transdisciplinary approaches to solving problems and learning is a challenge that must be persistently addressed. These institutional challenges will only continue to limit universities seeking toward scaling transdisciplinary programs and experimenting with novel ways to enhance the value of higher education for students and society. This then restricts innovations to teaching and also hinders the sharing of important practices across disciplines. To address these concerns, a National Science Foundation Improving Undergraduate STEM Education project team, which is the topic of this paper, has set the goal of developing/implementing/testing an authentically transdisciplinary, and scalable educational model in an effort to help guide the transformation of traditional undergraduate learning to span academics silos. This educational model, referred to as the Mission, Meaning, Making (M3) program, is specifically focused on teaching the crosscutting practices of innovation by a) implementing co-teaching and co-learning from faculty and students across different academic units/colleges as well as b) offering learning experiences spanning multiple semesters that immerse students in a community that can nourish both their learning and innovative ideas. As a collaborative initiative, the M3 program is designed to synergize key strengths of an institution’s engineering/technology, liberal arts, and business colleges/units to create a transformative undergraduate experience focused on the pursuit of innovation—one that reaches the broader campus community, regardless of students’ backgrounds or majors. Throughout the development of this model, research was conducted to help identify institutional barriers toward creating such a cross-college program at a research-intensive public university along with uncovering ways in which to address these barriers. While data can show how students value and enjoy transdisciplinary experiences, universities are not likely to be structured in a way to support these educational initiatives and they will face challenges throughout their lifespan. These challenges can result from administration turnover whereas mutual agreements across colleges may then vanish, continued disputes over academic territory, and challenges over resource allotments. Essentially, there may be little to no incentives for academic departments to engage in transdisciplinary programming within the existing structures of higher education. However, some insights and practices have emerged from this research project that can be useful in moving toward transdisciplinary learning around topics of convergence. Accordingly, the paper will highlight features of an educational model that spans disciplines along with the workarounds to current institutional barriers. This paper will also provide lessons learned related to 1) the potential pitfalls with educational programming becoming “un-disciplinary” rather than transdisciplinary, 2) ways in which to incentivize departments/faculty to engage in transdisciplinary efforts, and 3) new structures within higher education that can be used to help faculty/students/staff to more easily converge to increase access to learning across academic boundaries. 

When communication between teammates is limited to observations of each other’s actions, agents may need to improvise to stay coordinated. Unfortunately, current methods inadequately capture the uncertainty introduced by a lack of direct communication. This paper augments existing frameworks to introduce Simple Temporal Networks for Improvisational Teamwork (STN-IT) — a formulation that captures both the temporal dependencies and uncertainties between agents who need to coordinate, but lack reliable communication. We define the notion of strong controllability for STN-ITs, which establishes a static scheduling strategy for controllable agents that produces a consistent team schedule, as long as non-communicative teammates act within known problem constraints. We provide both an exact and approximate approach for finding strongly controllable schedules, empirically demonstrate the trade-offs between these two approaches on a benchmark of STN-ITs, and show analytically that the exact method is correct. In addition, we provide an empirical analysis of the exact and approximate approaches’ efficiency 

We report on an extension of a cross-cultural collaborative project between students and faculty at DePauw University in the United States and Shibaura Institute of Technology in Japan. The ongoing project uses cross-cultural teams to design and evaluate virtual companion robots for university students with the goal of gaining a deeper understanding of the role that kawaii (Japanese cuteness) plays in fostering positive human response to, and acceptance of, robots across cultures. Members of two cross-cultural teams designed virtual companion robots with specific kawaii attributes. Using these robots, we conducted the first phase of a two-phase user study to understand perceptions of these companion robots. The findings demonstrate that participants judge round companion robots to be more kawaii than angular ones and they also judge colorful robots to be more kawaii than greyscale robots. The phase one study identified pairs of robots that are the most appropriate candidates for conducting further investigations. The appropriateness of these pairs holds across male and female participates as well as across participants whose primary culture is American and those whose primary culture is Japanese. This work prepares us to perform a more detailed study across genders and cultures using both survey results and biosensors. In turn, this will inform our long-term goal of designing robots that are appealing across gender and culture.