Small number enumeration processes of deaf or hard-of-hearing students: A study using eye tracking and artificial intelligence
Students who are deaf or hard-of-hearing (DHH) often show significant difficulties in learning mathematics. Previous studies have reported that students who are DHH lag several years behind in their mathematical development compared to hearing students. As possible reasons, limited learning opportun...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-08-01
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| Series: | Frontiers in Psychology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fpsyg.2022.909775/full |
| _version_ | 1798041835623415808 |
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| author | Maike Schindler Jan H. Doderer Anna L. Simon Erik Schaffernicht Achim J. Lilienthal Karolin Schäfer |
| author_facet | Maike Schindler Jan H. Doderer Anna L. Simon Erik Schaffernicht Achim J. Lilienthal Karolin Schäfer |
| author_sort | Maike Schindler |
| collection | DOAJ |
| description | Students who are deaf or hard-of-hearing (DHH) often show significant difficulties in learning mathematics. Previous studies have reported that students who are DHH lag several years behind in their mathematical development compared to hearing students. As possible reasons, limited learning opportunities due to a lesser incidental exposure to numerical ideas, delays in language and speech development, and further idiosyncratic difficulties of students who are DHH are discussed; however, early mathematical skills and their role in mathematical difficulties of students who are DHH are not explored sufficiently. In this study, we investigate whether students who are DHH differ from hearing students in their ability to enumerate small sets (1–9)—an ability that is associated with mathematical difficulties and their emergence. Based on a study with N = 63 who are DHH and N = 164 hearing students from third to fifth grade attempting 36 tasks, we used eye tracking, the recording of students' eye movements, to qualitatively investigate student enumeration processes. To reduce the effort of qualitative analysis of around 8,000 student enumeration processes (227 students x 36 tasks), we used Artificial Intelligence, in particular, a clustering algorithm, to identify student enumeration processes from the heatmaps of student gaze distributions. Based on the clustering, we found that gaze distributions of students who are DHH and students with normal hearing differed significantly on a group level, indicating differences in enumeration processes, with students who are DHH using advantageous processes (e.g., enumeration “at a glance”) more often than hearing students. The results indicate that students who are DHH do not lag behind in small number enumeration as compared to hearing students but, rather, appear to perform better than their hearing peers in small number enumeration processes, as well as when conceptual knowledge about the part-whole relationship is involved. Our study suggests that the mathematical difficulties of students who are DHH are not related to difficulties in the small number enumeration, which offers interesting perspectives for further research. |
| first_indexed | 2024-04-11T22:27:08Z |
| format | Article |
| id | doaj.art-105b4126caad45d38f5dfe0274c3c619 |
| institution | Directory Open Access Journal |
| issn | 1664-1078 |
| language | English |
| last_indexed | 2024-04-11T22:27:08Z |
| publishDate | 2022-08-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Psychology |
| spelling | doaj.art-105b4126caad45d38f5dfe0274c3c6192022-12-22T03:59:37ZengFrontiers Media S.A.Frontiers in Psychology1664-10782022-08-011310.3389/fpsyg.2022.909775909775Small number enumeration processes of deaf or hard-of-hearing students: A study using eye tracking and artificial intelligenceMaike Schindler0Jan H. Doderer1Anna L. Simon2Erik Schaffernicht3Achim J. Lilienthal4Karolin Schäfer5Department of Special Education and Rehabilitation, Faculty of Human Sciences, University of Cologne, Cologne, GermanyDepartment of Special Education and Rehabilitation, Faculty of Human Sciences, University of Cologne, Cologne, GermanyDepartment of Special Education and Rehabilitation, Faculty of Human Sciences, University of Cologne, Cologne, GermanySchool of Science and Technology, Örebro University, Örebro, SwedenSchool of Science and Technology, Örebro University, Örebro, SwedenDepartment of Special Education and Rehabilitation, Faculty of Human Sciences, University of Cologne, Cologne, GermanyStudents who are deaf or hard-of-hearing (DHH) often show significant difficulties in learning mathematics. Previous studies have reported that students who are DHH lag several years behind in their mathematical development compared to hearing students. As possible reasons, limited learning opportunities due to a lesser incidental exposure to numerical ideas, delays in language and speech development, and further idiosyncratic difficulties of students who are DHH are discussed; however, early mathematical skills and their role in mathematical difficulties of students who are DHH are not explored sufficiently. In this study, we investigate whether students who are DHH differ from hearing students in their ability to enumerate small sets (1–9)—an ability that is associated with mathematical difficulties and their emergence. Based on a study with N = 63 who are DHH and N = 164 hearing students from third to fifth grade attempting 36 tasks, we used eye tracking, the recording of students' eye movements, to qualitatively investigate student enumeration processes. To reduce the effort of qualitative analysis of around 8,000 student enumeration processes (227 students x 36 tasks), we used Artificial Intelligence, in particular, a clustering algorithm, to identify student enumeration processes from the heatmaps of student gaze distributions. Based on the clustering, we found that gaze distributions of students who are DHH and students with normal hearing differed significantly on a group level, indicating differences in enumeration processes, with students who are DHH using advantageous processes (e.g., enumeration “at a glance”) more often than hearing students. The results indicate that students who are DHH do not lag behind in small number enumeration as compared to hearing students but, rather, appear to perform better than their hearing peers in small number enumeration processes, as well as when conceptual knowledge about the part-whole relationship is involved. Our study suggests that the mathematical difficulties of students who are DHH are not related to difficulties in the small number enumeration, which offers interesting perspectives for further research.https://www.frontiersin.org/articles/10.3389/fpsyg.2022.909775/fullmathematics educationdeaf or hard-of-hearing studentsmathematical difficultiessmall number enumerationeye trackingArtificial Intelligence |
| spellingShingle | Maike Schindler Jan H. Doderer Anna L. Simon Erik Schaffernicht Achim J. Lilienthal Karolin Schäfer Small number enumeration processes of deaf or hard-of-hearing students: A study using eye tracking and artificial intelligence Frontiers in Psychology mathematics education deaf or hard-of-hearing students mathematical difficulties small number enumeration eye tracking Artificial Intelligence |
| title | Small number enumeration processes of deaf or hard-of-hearing students: A study using eye tracking and artificial intelligence |
| title_full | Small number enumeration processes of deaf or hard-of-hearing students: A study using eye tracking and artificial intelligence |
| title_fullStr | Small number enumeration processes of deaf or hard-of-hearing students: A study using eye tracking and artificial intelligence |
| title_full_unstemmed | Small number enumeration processes of deaf or hard-of-hearing students: A study using eye tracking and artificial intelligence |
| title_short | Small number enumeration processes of deaf or hard-of-hearing students: A study using eye tracking and artificial intelligence |
| title_sort | small number enumeration processes of deaf or hard of hearing students a study using eye tracking and artificial intelligence |
| topic | mathematics education deaf or hard-of-hearing students mathematical difficulties small number enumeration eye tracking Artificial Intelligence |
| url | https://www.frontiersin.org/articles/10.3389/fpsyg.2022.909775/full |
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