Enabling Next-Generation HyFlex Field Laboratories through an Innovative Leaner-In-The-Loop Multi-Robot System

Many engineering and technology sectors, such as construction engineering and manufacturing, operate within an inherently complex and uncertain environment with dynamic operation conditions and potentially non-routine problems. To guarantee operational excellence, it is crucial to equip the workforce in these industries with advanced collaborative problem-solving (CPS) skills to collaboratively navigate challenges in the multifaceted working environment and develop innovative solutions.

In response to this urgent demand, this project intends to advance knowledge in both learning science and technology to study the effectiveness of emerging artificial intelligence (AI) and robotics technologies in supporting inclusive, scalable, and effective CPS skill development. To achieve this, this project will explore proof-of-concept innovative learning technologies to transform the conventional in-person field-based lab environments into Hybrid-Flexible (HyFlex) field-based lab environments accessible to extensive remote and residential student populations for CPS skill development.

The innovation of this project will revolutionize the existing fieldwork education and foster networked on-campus HyFlex field laboratories. Such a system would be akin to a "library of field labs with HyFlex mode,” enabling learners to access existing field-based labs established at different universities remotely or physically for fostering critical competencies in engineering and technology including CPS skills.

The success of this project will significantly contribute to the pressing need to promote diversity and inclusion and broaden participation in developing CPS skills. Additionally, this project will also significantly advance understanding of innovative-technology-enabled solutions that effectively promote diversity, equity, inclusion, and accessibility in STEM education.

The goal of this project is to develop new knowledge on the affordances of emerging generative AI (GAI)-enabled robot-mediated pedagogical technology called LILMR (Learner-In-the-Loop Multi-Robot system) for supporting scalable engagements of remote learners in innovative HyFlex field-based lab environments, facilitating effective development of CPS skills within a shared authentic experiential learning space with residential students. To achieve this goal, it is essential to answer three research questions (RQs).

RQ1: What technological affordances are essential for effectively supporting the development of CPS skills in a HyFlex field-based lab environment for both remote and residential learners? RQ2: What technological, pedagogical, and logistical supports are needed to foster an engaging HyFlex field-based lab environment and promote the development of CPS skills?

RQ3: How can the impact of emerging learning technologies on supporting the development of CPS skills for both remote and residential students in HyFlex field-based lab environments be assessed? To address these three RQs, the research team will establish a multidisciplinary research capacity and focus on three cohesive project objectives within a hybrid content-pedagogical-technological development space: 1) exploring an innovative GAI-enabled robot-mediated pedagogical technology and developing a LILMR system for enabling an inclusive HyFlex field-based lab environment for supporting the development of CPS skills.

The expected deliverables will include the initial identification of essential technological affordances, the initial design of the proposed LILMR system, and the associated technological, pedagogical, and logistical strategies; 2) interactively deploying and refining the proposed LILMR system in different HyFlex field-based lab contexts. The expected deliverables will include the formulation of a suitable assessment framework for evaluating the impact of the proposed LILMR system in supporting the development of CPS skills, the refinement of the core functionality components initially defined for the LILMR system, the understanding of the affordances of the LILMR system, and the optimization of the associated technological, pedagogical, and logistical support strategies; and 3) conducting pilot studies.

The expected deliverables will include the performance validation of the proposed LILMR system and associated technological, pedagogical, and logistical support strategies in supporting the development of CPS skills in fieldwork environments. Furthermore, the project’s results will be disseminated via courses, workshops, conferences, outreach, and collaborations.

This project is funded by the Research on Innovative Technologies for Enhanced Learning (RITEL) program that supports early-stage exploratory research in emerging technologies for teaching and learning.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.