Using Augmented Reality to Enhance Students’ Representational Fluency: The Case of Linear Functions

Abstract

Using multiple representations is advocated and emphasized in mathematics and science education. However, many students have difficulty connecting multiple representations of linear functions. Augmented Reality (AR) may affect these teaching and learning difficulties by offering dynamically linked representations. Inspired by this, our study aims to develop, implement, and evaluate an AR-based multi-representational learning environment (MRLE) with three representations of linear functions. The data were collected from 82 seventh graders from two high-performing classes in an urban area in China, through a pre-test, a post-questionnaire, and follow-up interviews. The results reveal that students were satisfied with the AR-based MRLE, which assisted in enhancing their understanding of the real-life, symbolic, and graphical representations and connections among them. Regarding students’ interactions with multiple representations, apparent differences in learning sequences and preferences existed among students in terms of their representational learning profile. In sum, learning in the AR-based MRLE is a complex interaction process between the mathematics content, forms of representations, digital features, and students’ representational learning profile.

EUCLIDA: 3D Augmented Reality Card for Learning Numeracy about Geometry

“…Augmented Reality transform two-dimensional images into threedimensional spatial geometry forms, thereby learners completely absorb mathematics materials [18]. This result approves that abstract mathematical content can be constructed into real objects with the help of technology [19], [20], [21]. The EUCLIDA also integrated with Augmented Reality can display the large object that is impossible to present in classroom and allow small objects to be performed [22].…”

Assessing the Influence of Augmented Reality in Mathematics Education: A Systematic Literature Review

“…The use of AR technology is beneficial for students through increased achievement (Moreno et al, 2021) and learning performance (Cabero-Almenara et al, 2021;Wangid et al, 2020;Wiliyanto et al, 2022). AR helps with knowledge construction (Amir et al, 2020a;Cahyono et al, 2020;Cai et al, 2019;Ibili & Billinghurst, 2019), develops thinking skills (Li et al, 2022) and supports learners to better understand the topic being studied (Cabero-Almenara et al, 2021;Moreno et al, 2021). http://ijlter.org/index.php/ijlter…”

“…Furthermore, the use of AR also demonstrates its potential in promoting student representational ability, described by Li et al (2022) as an AR-based multirepresentational learning environment (AR-based MRLE). AR-based MRLE promotes lower secondary school students' representational ability in linear function.…”

How Chinese Undergraduate Students’ Perceptions of Assessment for Learning Influence Their Responsibility for First-Year Mathematics Courses

“…Many countries and regions reported that students perform poorly in first-year mathematics courses, noting that unacceptably high failure rates in first-year mathematics courses have become a catalyst for many students to leave mathematics-intensive programs, delay progression from one academic level to the next, and drop out of university [7][8][9]. In China, the quality of first-year mathematics courses is also an issue under heated dispute, and factors such as students' learning approaches and attitudes, teachers' instructional methods, and the construction of institutional textbooks have been implicated in students' poor performance [10][11][12][13]. Moreover, in order to build a high-quality system in the Chinese mathematics education context, formative assessment (FA) and assessment for learning (AFL) have received more attention in China in recent years [14][15][16], but few studies have been based on systematic empirical approaches, especially on how students experience and feel about their mathematics teachers' FA and AFL practices.…”