Small number enumeration processes of deaf or hard-of-hearing students: A study using eye tracking and artificial intelligence

Abstract

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.

Reflections on gaze data in statistics education

“…Another possibility is using heatmaps (middle [5]), here created through the Tobii software (see also Ref. [21]). Heatmaps have the advantage that they aggregate the gaze data but a disadvantage is that time and spatial information (eg, the order of the fixations or saccades) are thrown away.…”

“…Moreover, not every gaze is part of students' strategies (eg, [20]). Research is needed to reveal how specific gaze patterns relate to students' strategies for different topics (eg, [21]). In addition, data triangulation, for example through cued recall (retrospective reporting with students' own gazes as a cue), will be needed until clear patterns have been found for specific tasks and topics and in different communities.…”

SignMath: Enhancing Mathematical Skills for HearingImpaired Students through Interactive Sign Language Learning

“…The effects of interactive sign language learning on DHH students' mathematics abilities have been studied in a number of research projects. This research looked at the usefulness of interactive sign language activities, such as conversations, games, and hands-on manipulative exercises, in fostering mathematical comprehension and engagement [4] [12]. According to research interactive sign language learning improves mathematical reasoning, problemsolving skills, and collaboration capacities among hearingimpaired pupils.…”

“…It is recommended to include number patterns as much as possible when teaching mathematical concepts to primary school children. "Recent research has found that young children's ability to spot mathematical patterns can predict later mathematical achievement [12] The Process of teaching mathematics to primary school DHH children is quite challenging. It has been identified that they lag behind their sighted peers in mathematical skills [6].…”

“…Utilizing graphical visualization methods and encouraging activitybased learning supported by modern technology can be used as key techniques to minimize these communication barriers. [12] In addition, DHH students can be encouraged to self-learn by providing a user-friendly GUI (Graphical User Interface) associated with ASL and an appropriate E-learning environment. [3] Continuous support, attention, and guidance are essential in the learning process of deaf children.…”