Free response evaluation via neural network for an IMathAS system

Nathanial Wiggins, Milton Smith

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

A fully interactive class with mixed reality and simulation learning should provide many free response types for students to learn beyond numerical answers and multiple choice. Essay and string responses in the IMathAS homework system have to be manually graded, making the free response questions difficult to generate instant feedback. The ability to write questions with automatic feedback during active lecture offer improvements to the current systems and provide an opportunity for critical thinking to occur. The following study provides framework for an interpretive neural network to be implemented into any IMathAS system. These responses can be in the form of equations, words and sentences, or pictures. Findings show that correctly trained networks using manually graded artifacts can be more than 90% accurate in providing feedback to a correct answer in student practice, allowing for lessons that guide students towards correct and well-phrased answers using their own words, and can even assign partial credit. The findings imply that Marzano's taxonomy level of analysis can be reached using the IMathAS system and that critical thinking methods can be directly applied for scoring. When integrated into the existing system, simulation-based or mixed reality homework can have free responses and the grades can be transferred via learning tool interoperability connection into the institutional learning management system for direct scoring in the gradebook.

Original languageEnglish
Title of host publication2019 22nd IEEE International Symposium on Measurement and Control in Robotics
Subtitle of host publicationRobotics for the Benefit of Humanity, ISMCR 2019
EditorsThomas L. Harman, Zafar Taqvi
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728148991
DOIs
StatePublished - Sep 2019
Event22nd IEEE International Symposium on Measurement and Control in Robotics, ISMCR 2019 - Houston, United States
Duration: Sep 19 2019Sep 21 2019

Publication series

Name2019 22nd IEEE International Symposium on Measurement and Control in Robotics: Robotics for the Benefit of Humanity, ISMCR 2019

Conference

Conference22nd IEEE International Symposium on Measurement and Control in Robotics, ISMCR 2019
CountryUnited States
CityHouston
Period09/19/1909/21/19

Keywords

  • critical thinking
  • mixed reality education application
  • neural networks
  • undergraduate education

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