The use of physiological tools to identify changes in affective responses for graduate students recently admitted into a scientific discipline

Idalis Villanueva, Adam Raikes, Nathan Ruben, Sydney Schaefer, Jacob Gunther

Research output: Contribution to journalArticle

2 Scopus citations


Over the past decade, underrepresentation of minority students in science, technology, engineering, and mathematics (STEM) at the undergraduate and graduate level have been reported. However, little is known about the internal and external factors/experiences causing students to decide to drop-out. This study considers the gateway experiences (B.S. to M.S.) that led six STEM college students to continue to pursue their master's degree. This paper will present a novel method to triangulate affective responses of participants as they recollect their college experiences. We will discuss the graduate student case studies by comparing gender. The information presented highlights interview summaries from the graduate students, physiological instrumentation data including: (1) wireless non-invasive wrist sensors to measure skin electrical conductance (electrodermal activity) as a trigger for emotional response, (2) wired pulse oximeters to non-invasively monitor an individual's heart rate, and (3) preliminary detection of heart rate using a custom-developed, non-invasive/non-contact video monitoring technology presented for the first time in this paper. Together, the findings present a unique method to assess emotional and decision-making responses of students. Through this work, we hope to develop future research strategies that are qualitatively and quantitatively based for the target population.

Original languageEnglish (US)
Article number7044316
JournalUnknown Journal
Issue numberFebruary
StatePublished - Feb 17 2015
Externally publishedYes



  • affective
  • decision-making
  • emotions
  • graduate students
  • non-contact
  • non-invasive
  • physiology
  • sensor
  • STEM

ASJC Scopus subject areas

  • Software
  • Education
  • Computer Science Applications

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