Exploring the link between task complexity and students' affective states during engineering laboratory activities

Qianyu Hu, Shruthi Bezawada, Allison Gray, Conrad Tucker, Timothy Brick

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations

Abstract

Assessment and feedback play an instrumental role in an individual's learning process. Continued assistance is required to help students learn better and faster. This need is especially prominent in engineering laboratories where students must perform a wide range of tasks using different machines. One approach to understanding how students feel towards using certain machines is to assess their affective states while they use these machines. Affective state can be defined as the state of feeling an emotion. The authors of this work hypothesize that there is a correlation between students' perceived affective states and task complexity. By adopting the Wood's complexity model, the authors propose to assess how the correlations of perceived affective states of students change while they perform tasks of different complexity. In this study, each student performs a "hard" and an "easy" task on the same machine. Each student is given the same tasks using the same materials. Knowledge gained from testing this hypothesis will provide a fundamental understanding of the tasks that negatively impact students' affective states and risk them potentially dropping out of STEM tracks, and the tasks that positively impact students' affective states and encourage them to engage in more STEM-related activities. A case study involving 22 students using a power saw machine is conducted. Perceived affective states and completion time were collected. It was found that task complexity has an effect on subjects' affective states. In addition, we observed some weak correlation between some of the perceived affective states and laboratory task performance. The distribution of correlation between affective states may change as the tasks change. With the knowledge of the relationship between task complexity and affective states, there is the potential to predict students' affective states before starting a given engineering task.

Original languageEnglish (US)
Title of host publication18th International Conference on Advanced Vehicle Technologies; 13th International Conference on Design Education; 9th Frontiers in Biomedical Devices
PublisherAmerican Society of Mechanical Engineers (ASME)
ISBN (Electronic)9780791850138
DOIs
StatePublished - 2016
EventASME 2016 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2016 - Charlotte, United States
Duration: Aug 21 2016Aug 24 2016

Publication series

NameProceedings of the ASME Design Engineering Technical Conference
Volume3

Other

OtherASME 2016 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2016
Country/TerritoryUnited States
CityCharlotte
Period8/21/168/24/16

All Science Journal Classification (ASJC) codes

  • Mechanical Engineering
  • Computer Graphics and Computer-Aided Design
  • Computer Science Applications
  • Modeling and Simulation

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