Critical thinking in automated homework

dc.contributor.committeeChairDu, Dongping
dc.contributor.committeeMemberSmith, Milton
dc.contributor.committeeMemberBeruvides, Mario G.
dc.contributor.committeeMemberPeterson, Stephen
dc.contributor.committeeMemberBurns, James R.
dc.creatorWiggins, Nathanial David
dc.creator.orcid0000-0001-6102-0273 2020
dc.description.abstractBlending the digital world with the physical environment has long been a goal of science fiction. Two aspects of these science fiction elements to blend the digital world are holograms and intelligent response systems and are now possible through mixed reality headsets and machine learning. There is an ideal situation in academia that students have access to these technologies and that these systems integrate into existing learning management systems. Unfortunately, there are currently limited examples of these technologies in education and few are developed to integrate directly into the learning management systems of the academic institutions, leaving teachers to transfer grades manually various learning systems. The gap in knowledge is then the process to create and integrate activities that include mixed reality and machine learning or neural networks for student responses. The contribution of knowledge to education is the ability for teachers and instructional designers to produce new problem sets that go beyond the traditional numerical response or multiple choice into interactive manipulatives and free responses through implementation of these models. Implementation of materials should follow a scaffolding from basic repetition to knowledge utilization and have clearly identified language so that cognitive level is clear. Current homework systems often lack this ability or use Bloom’s Taxonomy. The old Bloom’s Taxonomy has been criticized for a lack of scaffolding infrastructure and has since integrated the Marzano’s Taxonomy scaffolding structure. There exists a lack of existing examples of Marzano’s Taxonomy as used in mixed reality, no surveys on the interest of using mixed reality in a community classroom, a lack of studies of the use of Marzano’s Taxonomy in community colleges, a lack of studies using neural networks to train the free responses of students, a lack of studies on the usage of 3D models integrated into educational lessons, and a lack of broader impacts studies as a result of Marzano’s infrastructure in STEM courses. These gaps in knowledge must be addressed before advanced implementation of embedded intelligent courses using situational learning techniques can be fully recognized. This work demonstrates the implementation of mixed reality and neural networks through learning tool interoperability connectors for integrated coursework with custom scaffolding. ISO standard and requirements along with internal and external validation of the tools are performed via testing and statistical analysis. Finally, future studies are presented with an opportunity for a full-scale implementation so that critical thinking can be directly measured and compared to existing metrics.
dc.description.abstractEmbargo status: Restricted until January 2022. To request access, click on the PDF link to the left.
dc.rights.availabilityRestricted until January 2022.
dc.subjectArtificial intelligence
dc.subjectNeural networks
dc.subjectKnowledge management
dc.titleCritical thinking in automated homework
local.embargo.terms2021-12-01 Engineering and Engineering Management Tech University of Philosophy


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