Dataset Information

A Randomised Control Trial and Comparative Analysis of Multi-Dimensional Learning Tools in Anatomy.

ABSTRACT: This article presents the results of a study that examined students' ability to retain what they have learned in an anatomy course after thirty days via using various learning tools for twenty minutes. Fifty-two second-year medical students were randomly assigned to three learning tools: text-only, three-dimension visualisation in a two-dimensional screen (3DM), or mixed reality (MR). An anatomy test lasting for twenty minutes measuring spatial and nominal knowledge was taken immediately after the learning intervention and another thirty days later. Psychometric tests were also used to measure participants' memory, reasoning and concentration abilities. Additionally, electroencephalogram data was captured to measure the participants' awakeness during the learning session. Results of this study showed that the MR group performed poorly in the nominal questions compared to the other groups; however, the MR group demonstrated higher retention in both the nominal and spatial type information for at least a month compared to the other groups. Furthermore, participants in the 3DM and MR groups reported increased engagement. The results of this study suggest that three-dimensional visualiser tools are likely to enhance learning in anatomy education. However, the study itself has several limitations; some include limited sample size and various threats to internal validity.

SUBMITTER: Wang C

PROVIDER: S-EPMC7145854 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

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A Randomised Control Trial and Comparative Analysis of Multi-Dimensional Learning Tools in Anatomy.

Wang Chris C Daniel Ben Kei BK Asil Mustafa M Khwaounjoo Prashanna P Cakmak Yusuf Ozgur YO

Scientific reports 20200409 1

This article presents the results of a study that examined students' ability to retain what they have learned in an anatomy course after thirty days via using various learning tools for twenty minutes. Fifty-two second-year medical students were randomly assigned to three learning tools: text-only, three-dimension visualisation in a two-dimensional screen (3DM), or mixed reality (MR). An anatomy test lasting for twenty minutes measuring spatial and nominal knowledge was taken immediately after t ...[more]

PMID: 32273563

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Project description:The diverse phenotypes of living organisms have been described for centuries, and though they may be digitized, they are not readily available in a computable form. Using over 100 morphological studies, the Phenoscape project has demonstrated that by annotating characters with community ontology terms, links between novel species anatomy and the genes that may underlie them can be made. But given the enormity of the legacy literature, how can this largely unexploited wealth of descriptive data be rendered amenable to large-scale computation? To identify the bottlenecks, we quantified the time involved in the major aspects of phenotype curation as we annotated characters from the vertebrate phylogenetic systematics literature. This involves attaching fully computable logical expressions consisting of ontology terms to the descriptions in character-by-taxon matrices. The workflow consists of: (i) data preparation, (ii) phenotype annotation, (iii) ontology development and (iv) curation team discussions and software development feedback. Our results showed that the completion of this work required two person-years by a team of two post-docs, a lead data curator, and students. Manual data preparation required close to 13% of the effort. This part in particular could be reduced substantially with better community data practices, such as depositing fully populated matrices in public repositories. Phenotype annotation required ∼40% of the effort. We are working to make this more efficient with Natural Language Processing tools. Ontology development (40%), however, remains a highly manual task requiring domain (anatomical) expertise and use of specialized software. The large overhead required for data preparation and ontology development contributed to a low annotation rate of approximately two characters per hour, compared with 14 characters per hour when activity was restricted to character annotation. Unlocking the potential of the vast stores of morphological descriptions requires better tools for efficiently processing natural language, and better community practices towards a born-digital morphology. Database URL: http://kb.phenoscape.org

Dataset Information

A Randomised Control Trial and Comparative Analysis of Multi-Dimensional Learning Tools in Anatomy.

Publications

A Randomised Control Trial and Comparative Analysis of Multi-Dimensional Learning Tools in Anatomy.

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