The intersection of technology and education is creating new possibilities for learning, and at the forefront of this transformation is a project funded by the National Science Foundation (NSF). Dr. Abbas Rashidi, an Associate Professor in the Department of Civil & Environmental Engineering, is playing a key role in a $900,000 collaborative research initiative titled “An AI-Enhanced System to Integrate Unstructured Observations with Formal Engineering Education.”

Supplementing Learning with AI 

A joint effort with Stevens Institute of Technology and Mississippi State University, the project aims to bridge the gap between real-world observations and formal engineering education. Civil and construction engineering students often encounter various components—such as structural elements, materials, and equipment—in their everyday environments. These spontaneous observations have the potential to enhance learning, but without expert guidance, students may struggle to connect these real-world experiences with their academic knowledge.

Dr. Rashidi and his collaborators are addressing this challenge by developing an AI-driven mobile app designed to act as an on-demand educator. This application will allow students to use their smartphones to analyze and learn from construction projects they encounter in their daily lives or during site visits.

The app will use Enhanced Observation Guidance to directs students’ attention to key construction components and provide real-time explanations of what they’re seeing.
It will then link these observations to the students’ formal coursework and educational materials available on web-based platforms. Additionally, the app-to-web interface system will be able to generate detailed reports on students’ observations and performance, offering instructors valuable insights to tailor course activities.

Innovative Technology at Work 

The AI-enhanced learning system will be built on Activity Learning Theory, which emphasizes the role of sensory, mental, and physical activities in the learning process. Dr. Rashidi’s critical role in creating the platform will be the development of the novel hybrid image-audio processing system, which will integrate imagery and audio data to recognize and classify construction components with greater accuracy.

The innovative audio processing and signal source separation algorithms will eliminate the need for multiple microphones by enabling a single smartphone to capture and analyze audio signals from up to 100 feet away.

By harnessing the power of AI, this research involved in this project aims to provide students with a more interactive and effective learning experience, ultimately preparing them for the complexities of the modern engineering landscape.

Broad Implications for Education 

The impact of this AI-enhanced learning platform extends beyond construction engineering. While the initial focus is on this field, the methods and technologies developed can be adapted for use in other disciplines.

Specifically, researchers on this project are designing the app with accessibility in mind, featuring color palettes for users with color vision deficiency, subtitles and audio narrations to ensure an inclusive learning experience—foundations which will be key to the development of similar AI-driven education tools in other fields of study.

We look forward to seeing the transformative impact of this project and the continued contributions of Dr. Rashidi and his collaborators to the future of engineering education.