Husnu S. Narman, C. Berry, Alex Canfield, Logan Carpenter, Jeremy M Giese, Neil Loftus, Isabella Schrader
{"title":"Augmented Reality for Teaching Data Structures in Computer Science","authors":"Husnu S. Narman, C. Berry, Alex Canfield, Logan Carpenter, Jeremy M Giese, Neil Loftus, Isabella Schrader","doi":"10.1109/GHTC46280.2020.9342932","DOIUrl":null,"url":null,"abstract":"Data structures course is the most essential and critical course for computing-related majors. In this course, data structures, their main differences, and their usages are explained. However, for computer science students and especially students who do not have programming experiences, learning data structures can be challenging, and many students change their majors if they are not successful in this course. Given the importance of data structures, it is a pressing issue that we need to work to meet student needs and improve computer science education in this area. With technological developments, teaching strategies based on technology are also varying. The student performance is improved at various levels with these strategies. Also, accessing lower price smart devices with lower prices makes previously inaccessible technology, like Augmented Reality (AR), more readily available for students. Therefore, in this paper, we have developed a practice and learning environment for students based on AR and compared AR approach with standard and web-based animation approaches according to students’ comments. Results show that the AR approach not only helps students learn data structures better but is also found to be the most exciting approach. The results can help content-developers observe benefits of AR in computer science education.","PeriodicalId":314837,"journal":{"name":"2020 IEEE Global Humanitarian Technology Conference (GHTC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE Global Humanitarian Technology Conference (GHTC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GHTC46280.2020.9342932","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
Data structures course is the most essential and critical course for computing-related majors. In this course, data structures, their main differences, and their usages are explained. However, for computer science students and especially students who do not have programming experiences, learning data structures can be challenging, and many students change their majors if they are not successful in this course. Given the importance of data structures, it is a pressing issue that we need to work to meet student needs and improve computer science education in this area. With technological developments, teaching strategies based on technology are also varying. The student performance is improved at various levels with these strategies. Also, accessing lower price smart devices with lower prices makes previously inaccessible technology, like Augmented Reality (AR), more readily available for students. Therefore, in this paper, we have developed a practice and learning environment for students based on AR and compared AR approach with standard and web-based animation approaches according to students’ comments. Results show that the AR approach not only helps students learn data structures better but is also found to be the most exciting approach. The results can help content-developers observe benefits of AR in computer science education.