Grohs, J. R., & Shealy, T., & Maczka, D. K., & Hu, M., & Panneton, R., & Yang, X. (2017, June), Evaluating the Potential of fNIRS Neuroimaging to Study Engineering Problem Solving and Design  Paper presented at 2017 ASEE Annual Conference & Exposition, Columbus, Ohio. 10.18260/1-2--28305

\bibitem{asee_peer_28305}
  Grohs, J. R., \& Shealy, T., \& Maczka, D. K., \& Hu, M., \& Panneton, R., \& Yang, X. (2017, June), \emph{Evaluating the Potential of fNIRS Neuroimaging to Study Engineering Problem Solving and Design}
  Paper presented at 2017 ASEE Annual Conference \& Exposition, Columbus, Ohio.
  10.18260/1-2--28305

Jacob R. Grohs, Tripp Shealy, Darren K. Maczka, Mo Hu, Robin Panneton, and Xiao Yang.  "Evaluating the Potential of fNIRS Neuroimaging to Study Engineering Problem Solving and Design".  2017 ASEE Annual Conference & Exposition, Columbus, Ohio, 2017, June.  ASEE Conferences, 2017.  https://peer.asee.org/28305 Internet.  19 Apr, 2024

\bibitem{asee_peer_28305}
  Jacob R. Grohs, Tripp Shealy, Darren K. Maczka, Mo Hu, Robin Panneton, and Xiao Yang.
  "Evaluating the Potential of fNIRS Neuroimaging to Study Engineering Problem Solving and Design".
  \emph{2017 ASEE Annual Conference \& Exposition, Columbus, Ohio, 2017, June}.
  ASEE Conferences, 2017.
  https://peer.asee.org/28305 Internet.  19 Apr, 2024

@INPROCEEDINGS{asee_peer_28305
author = "Jacob R. Grohs, Tripp Shealy, Darren K. Maczka, Mo Hu, Robin Panneton, and Xiao Yang"
title = "Evaluating the Potential of fNIRS Neuroimaging to Study Engineering Problem Solving and Design"
booktitle = "2017 ASEE Annual Conference \& Exposition"
year = "2017"
month = "June"
address = "Columbus, Ohio"
publisher = "ASEE Conferences"
note = {https://peer.asee.org/28305}
number = {10.18260/1-2--28305}
}

TY  - CPAPER
AB  - This theory paper introduces functional Near Infrared Spectrometry (fNIRS) methods to the ASEE Educational Research and Methods (ERM) Division as a research method to augment engineering problem-solving and design studies.  As technology develops, we can ask and answer emergent research questions to meet National Science Foundation priorities to understand the brain, specifically in how “collective interactions between brain function and our physical and social environment enable complex behavior.”  With ERM researchers already pushing the boundaries of knowledge with teaching, learning, and practice of complex engineering skills, the field of engineering education is well poised to partner with cognitive scientists, developmental psychologists, and others to consider how neuroimaging can complement or supplement pressing research questions.  
Over the past few decades, advances in electroencephalography (EEG) and functional Magnetic Resonance Imaging (fMRI) technology have led to increasing interest in understanding complex neural processes of decision-making and problem solving under laboratory settings.  However, although EEG recording is convenient, its poor spatial resolution limits its capacity to determine neural substrates of complex behaviors that involve co-activation of multiple cortical regions. fMRI is very expensive to run and is generally uncomfortable for research participants and thus is not amenable to the lengthy cognitive processes involved in engineering problem-solving and design. Moreover, fMRI does not allow for the continuous assessment of brain activation due to its low temporal resolution. Of particular importance to educational research, body movements (e.g., writing, typing, and talking) produce significant artifacts that are difficult to control for in both EEG and fMRI methods.  In contrast, fNIRS has emerged as a novel potential method that is non-invasive and can be used comfortably while participants walk, talk, operate a computer, and otherwise perform the actions we commonly associate with educational settings. Although fNIRS lacks the high spatial resolution of fMRI and provides little information about non-cortical brain activity, fNIRS is sufficient to investigate the prefrontal cortex, the region that is associated with executive function (e.g., planning, problem solving). Taken together, these benefits make fNIRS particularly amenable to use in engineering education research as it allows for neuroimaging in more complex and realistic environments.
This paper will first review neuroimaging basics and relevant studies within engineering education with fMRI and EEG techniques (note: ASEE PEER Proceedings, JEE, IJEE search has no hits for fNIRS) in order to position fNIRS as an emergent relevant method for Engineering Education.  We will then discuss the specifics of fNIRS experimental design, data collection, data processing and analysis.  Analysis procedures involve both univariate and multivariate methods and both will be described along with the types of research questions each can answer (e.g., univariate analysis used to determine if specific tasks induce higher levels of activity).  As a demonstration, we will briefly explain how two ongoing projects by the authors are using different experimental designs and analysis to explore different topics: (1) cognitive load differences in engineering brainstorming unconstrained or with parameters and (2) neural correlates of insight and frustration while playing Rube Goldberg inspired puzzle game.        

AU  - Jacob R. Grohs
AU  - Tripp Shealy
AU  - Darren K. Maczka
AU  - Mo Hu
AU  - Robin Panneton
AU  - Xiao Yang
CY  - Columbus, Ohio
DA  - 2017/06/24
PB  - ASEE Conferences
TI  - Evaluating the Potential of fNIRS Neuroimaging to Study Engineering Problem Solving and Design
UR  - https://peer.asee.org/28305
DO  - 10.18260/1-2--28305
ER  -