ArticlePDF Available

Abstract

Augmented Reality Learning Experiences (ARLEs) for classrooms provide student-centered learning. In recent years, there has been an increase in HCI research on various handheld AR learning applications and the authoring tools to design them. However, there is a lack of studies exploring the design decisions required to create ARLEs, specific to the classroom context. To analyze the same, we conducted a design workshop with 32 participants forming 8 groups to investigate approaches for designing classroom-based ARLEs. Each group consisted of an AR developer, an interaction designer, an education researcher, and a middle-grade Math teacher. The groups designed ARLEs based on a given Mathematics topic for a classroom scenario. Though the groups used varied approaches for generating design prototypes, we observed similarities between their techniques. We report the key design approaches and decisions that were adopted by these groups. The findings are articulated through the lenses of content, context and design. Based on the analysis, we discuss the design approaches relevant for the novice designers while conceptualizing the design of a handheld ARLE for classrooms.
461
Approaches for Designing Handheld Augmented Reality
Learning Experiences for Mathematics Classrooms
PRATITI SARKAR, Indian Institute of Technology Bombay, India
JAYESH S. PILLAI, Indian Institute of Technology Bombay, India
Augmented Reality Learning Experiences (ARLEs) for classrooms provide student-centered learning. In recent
years, there has been an increase in HCI research on various handheld AR learning applications and the
authoring tools to design them. However, there is a lack of studies exploring the design decisions required
to create ARLEs, specic to the classroom context. To analyze the same, we conducted a design workshop
with 32 participants forming 8 groups to investigate approaches for designing classroom-based ARLEs. Each
group consisted of an AR developer, an interaction designer, an education researcher, and a middle-grade
Math teacher. The groups designed ARLEs based on a given Mathematics topic for a classroom scenario.
Though the groups used varied approaches for generating design prototypes, we observed similarities between
their techniques. We report the key design approaches and decisions that were adopted by these groups. The
ndings are articulated through the lenses of content, context and design. Based on the analysis, we discuss
the design approaches relevant for the novice designers while conceptualizing the design of a handheld ARLE
for classrooms.
CCS Concepts:
Human-centered computing Mixed / augmented reality
;
Ubiquitous and mobile
computing design and evaluation methods.
Additional Key Words and Phrases: augmented reality, learning experience, classroom experience, design
strategies, design decisions
ACM Reference Format:
Pratiti Sarkar and Jayesh S. Pillai. 2021. Approaches for Designing Handheld Augmented Reality Learning Expe-
riences for Mathematics Classrooms. Proc. ACM Hum.-Comput. Interact. 5, CSCW2, Article 461 (October 2021),
25 pages. https://doi.org/10.1145/3479605
1 INTRODUCTION
With the advent of technology, the classroom teaching method has evolved from the traditional
way of using chalk and blackboard to using interactive modes like smartboards [
41
,
73
], blended
learning platforms [
33
,
39
,
92
], interactive websites, applications, etc.,. However, these methods
continue to be instructor-mediated, where students tend to observe the actions of the teachers
and the resultant phenomena. Hence, it becomes dicult to assure the continuous attention of
all students throughout the class duration. To counter the same, teaching has been supported
with Activity Based Learning (ABL) that require creating multiple instances of the activity kits
or obtaining the related physical objects to explain a concept [
16
,
34
,
42
]. Though the approach
promotes hands-on learning, the limitation prevails in providing multiple physical objects for a
large class size while engaging all students together.
Authors’ addresses: Pratiti Sarkar, pratiti@iitb.ac.in, Indian Institute of Technology Bombay, Powai, Mumbai, Maharashtra,
India, 400076; Jayesh S. Pillai, Indian Institute of Technology Bombay, Powai, Mumbai, Maharashtra, India, jay@iitb.ac.in.
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee
provided that copies are not made or distributed for prot or commercial advantage and that copies bear this notice and the
full citation on the rst page. Copyrights for components of this work owned by others than the author(s) must be honored.
Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires
prior specic permission and/or a fee. Request permissions from permissions@acm.org.
©2021 Copyright held by the owner/author(s). Publication rights licensed to ACM.
2573-0142/2021/10-ART461 $15.00
https://doi.org/10.1145/3479605
Proc. ACM Hum.-Comput. Interact., Vol. 5, No. CSCW2, Article 461. Publication date: October 2021.
461:2 Pratiti Sarkar and Jayesh S. Pillai
Augmented Reality (AR) is one of the emerging technologies that can provide student-centered
learning when taught using handheld devices [
27
,
101
]. With its ability to superimpose computer-
generated virtual graphics onto the real world in real-time [
6
], the elds of Computer-Supported
Cooperative Work (CSCW) and Human-Computer Interaction (HCI) research have noted an exten-
sive range of studies on AR in education. Beyond interactivity, AR provides relative seamlessness
of digital objects within the real world leading to an immersive engagement for the students along
with enhanced learning [
8
,
46
,
84
]. Moreover, research has expanded towards providing the ability
for anyone to design an AR application using various AR authoring tools [64].
While the research on novel Augmented Reality Learning Experiences (ARLEs) and AR authoring
tools is growing, we lack insights into the design process involved which can guide novice designers
in creating such ARLEs. Here, by designers, we refer to anyone who is interested in designing AR
applications. The iterative process of creating a synergy between the content, pedagogy, technology,
and design is sparsely discussed. We especially lack the understanding of using appropriate design
strategies and decisions to develop ARLEs for the context of classrooms in eective ways [
5
,
93
].
This led us to explore the design requirements of AR for classrooms in its most accessible form of
handheld devices. Thus, encouraging the eortless design of such ARLEs for the novice designers,
the motivation of the work was to provide well-articulated design strategies and decisions in the
conceptualizing phases of the design process. As the literature lacks in specifying the details of the
relevant design approaches, it necessitated conducting a design workshop.
In this paper, we report the ndings of our design workshop conducted online with 32 participants,
divided into 8 groups. As we wanted to investigate the design strategies and decisions involved
in creating ARLEs, the co-design approach was followed [
80
] in the design workshop. This was
intended to bring together the teachers to collaborate with the designers, developers and researchers
in the designing process, taking into account the role of these actors in the implementation of an
educational technology in the education system. The participants had to design a handheld ARLE
based on a given Mathematics topic for a middle-grade classroom scenario. The study was conducted
with Indian participants who designed based on the school scenarios in the developing country
India where the use of tablets in the classrooms is prevalent and aordable [
67
,
79
,
81
,
98
]. Thus,
the AR glasses or head-mounted displays being expensive and less explored by the participants
themselves have not been investigated within the scope of the study. The paper thus qualitatively
analyzed the ways in which the participating groups designed the ARLEs, their decision-making,
and adoption of the design strategies. Though the authors in the existing works mention several
guidelines for AR in education in general, we have attempted towards providing specic ones for a
particular conceptualizing phase of the design process.
Our overall ndings indicate the various design decisions that are relevant for dening the
design strategies. These are relevant at the levels of dening the methods of interacting with the
AR application, teacher and student collaboration, and its execution in the classroom. The analysis
of insights led to the potential approaches for designing ARLEs. We further discuss the interplay
between our ndings and the existing notions of the design approaches while designing ARLEs
for classrooms. We posit this to be relevant for the novice designers (future HCI researchers, AR
designers, practitioners, and professionals) of ARLEs for classrooms with/without using any AR
authoring tool.
2 BACKGROUND
We looked into the existing research works to position our ndings in CSCW and HCI research.
The scope of our study included ARLEs for Mathematics at middle-school level. Hence, insights
were drawn from the intersection of existing ARLEs designed on dierent topics in Mathematics
Proc. ACM Hum.-Comput. Interact., Vol. 5, No. CSCW2, Article 461. Publication date: October 2021.
Approaches for Designing Handheld Augmented Reality Learning Experiences for Mathematics Classrooms 461:3
and the extent of design principles involved in designing such ARLEs, to articulate our contribution
in the design space for classroom based ARLEs.
2.1 The trends of ARLEs in Mathematics
The UNESCO IBE Glossary of curriculum-related terminology has dened learning experience
as “a wide variety of experiences across dierent contexts and settings which transform the
perceptions of the learner, facilitate conceptual understanding, yield emotional qualities, and
nurture the acquisition of knowledge, skills and attitudes” [
97
]. Emphasizing upon learners attaining
constructive meaning, the process of learning has been classied based on ve dimensions of
thinking: (1) positive attitudes and perceptions about learning, (2) thinking involved in acquiring
and integrating knowledge, (3) thinking involved in extending and rening knowledge, (4) thinking
involved in using knowledge meaningfully, and (5) productive habits of mind [
61
]. Building upon
these dimensions, the learning experience for learners has evolved over the years based on the
academic settings of teaching in classrooms [
13
,
44
], in outdoor environments [
37
,
74
,
100
] or
with self-paced learning at home [
18
,
60
]. In terms of the interactions, the dierences in learning
experiences have been studied and reported for the teacher-student interactions in the teacher-
mediated instructions, student-student interactions in student-centered learning, and student-
system interactions when educational technology in the learning setting comes into play [
44
,
63
,
83
].
To provide a satisfying learning experience, the state of concentration leading to absolute absorption
in an activity, known as ow, needs to be attained [
19
]. While operationalizing the learning
experience of a learner, it has been measured as “how much an individual learner engages in a
particular learning activity” [48]. To attain the same, the three cognitive states in learning i.e. the
ow experience, boredom, and anxiety or frustration are considered [
48
]. Thus, the smart learning
environments using technologies have used these parameters to witness the gain in learning
experiences of the learners using a technology as compared to traditional teaching methods [36].
One of the emerging technologies Augmented Reality (AR) tends to provide a discrete way to
interact with related information while integrating it with educational practices. Thus, Augmented
Reality Learning Experiences (ARLE) has been dened as “the learning experiences facilitated
by AR technology” [
84
]. This technology is considered valuable in education as it provides an
immersive and interactive experience to learners while engaging them in rich contextual learning
[
8
]. There are studies that indicate the positive motivation, knowledge construction and behaviour
patterns of students while collaboratively interacting with AR learning environments [
31
,
57
,
87
].
Pertaining to Mathematics in particular, AR is considered to be benecial in providing the ability to
manipulate and visualize augmented 3D objects in authentic contexts [
31
]. Thus, AR helps students
in learning abstract concepts which are otherwise dicult to understand [75].
Recognizing the benets of AR in visualizing 3D objects, a lot of explorations have been done in
teaching the topic of solid geometry to school students. For example, teaching geometry through
AR to middle-grade students has been reported to increase the students’ 3D thinking ability skills
[
47
], visualization skills [
89
], spatial ability [
56
], mental-rotation ability [
49
], learning performance,
and attitude [
58
]. For topics like volume and area, an interactive GeoAR book was designed for
students to explore the related formulae [
52
]. In AR Geometry Tutorial Systems (ARGTS), students
could calculate the volume and surface area of an object using nets and unit cubes and compare
the dierent volumes [
47
]. Though the prominence of AR is seen in learning concepts related
to 3D objects, studies have suggested that students can understand abstract concepts involving
gurative languages using AR [
12
]. The ability to visualize abstract concepts using AR has also
been explored in teaching the concepts of Fractions using augmented interactive number lines
[
50
,
71
], and “sorting unit fractions, mixed fractions, equivalent fractions with the area model,
and matching equivalent fractions” [
69
]. Similarly, the topic of probability has been taught using
Proc. ACM Hum.-Comput. Interact., Vol. 5, No. CSCW2, Article 461. Publication date: October 2021.
461:4 Pratiti Sarkar and Jayesh S. Pillai
AR and has been reported to have a positive impact on students’ understanding of concepts [
54
],
learning gains, attitude [14], and self-ecacy [15].
In the reported works, the AR application design and its eectiveness on learners’ learning
outcomes, engagement, collaboration, and motivation have been discussed extensively. For the
Cyberchase Shape Quest application, the authors have discussed the iterative evaluation cycles
in the design process of the Math AR application for elementary school students to learn 3D
Geometry [
77
]. The work primarily focused on the usability aspects to decide and rene the
application accordingly. However, the design decisions to create the synergy between student-
teacher interactions, the technology and the pedagogy have been barely discussed. Similarly, though
there have been discussions on the design of AR interactions and usability in the reported works,
the process of coming up with the application design has not been described in sucient detail,
making it dicult for the novice designers to understand the design requirements to begin with.
Thus, our study provides empirical insights for the novice designers on how one might approach
the design of ARLEs for classrooms related to the above Mathematics topics.
2.2 The design practice of ARLE for classrooms
To create AR applications, there are several development tools like ARKit [
72
], ARCore [
4
], and
Vuforia [
91
] that require programming knowledge. To ease user eort, several AR authoring tools
like ARtalet [
40
], 360proto [
65
], ProtoAR [
66
], DART [
59
] and SparkAR [
3
] have been developed.
These facilitate the designers in creating AR applications without the need for programming.
However, these authoring tools are designed to create specic predened tasks, which may not be
applicable to all instances [
5
]. To counter this, the Meta-AR-App was created to enable real-time
authoring for instructors and students, while promoting collaboration and interaction among peers
[
99
]. The authors of the Meta-AR-app however stated that the application worked in superimposing
sequential tasks involving the procedural actions to explain a certain phenomena.
To design AR learning tasks, in particular, using any SDK or authoring tool, one must consider
the design principles for AR in the context of education. The design principles involve fundamental
advice to create satisfactory and easy-to-use designs [
35
]. For example, the ARLEs are expected to
be designed in a way that give the learners a sense of challenge, fantasy, and raise their curiosity, to
ensure a satisfactory user experience for the learners [
25
]. Similarly, design principles for reduction
of orchestration load for teachers while teaching using AR in the classroom have been suggested
[
20
]. These design principles for providing pleasurable experiences to the users tend to leverage
the aordances of AR. While following these design principles it is imperative to make appropriate
design decisions to provide the rationale of the design, identify the design strategies to conform to
the decisions, and design methods to achieve the dened goal by implementing the strategies [
45
].
The design decisions help in providing the rationale of why an action was needed in the design
process. It was pointed out by [
8
] that due to the lack of educators’ proper understanding of the
technology and AR developers’ proper understanding of education, it is required to bring forth the
education and sound learning theory as part of the design decisions. Thus, to enhance the learning
outcomes, such thoughtful designs are required. While designing AR experiences, the simulations
and stories have been classied into four major categories: location, narrative, roles, and experience
mechanics [
26
]. Deciding on one of the factors can help in dening the basic structure of the AR
applications.
The design strategies help in dening how a decided action could be implemented. In one of the
studies, design guidelines for designing handheld AR in learning support were derived from existing
guidelines in dierent domains like tourism, navigation and games [
85
]. These guidelines included
presenting context-aware content, providing content controls, preempting technical diculties,
preserving intuitive icons and menus, and promoting social interactions. These guidelines were then
Proc. ACM Hum.-Comput. Interact., Vol. 5, No. CSCW2, Article 461. Publication date: October 2021.
Approaches for Designing Handheld Augmented Reality Learning Experiences for Mathematics Classrooms 461:5
applied to FlipPin application to teach new vocabularies in a real environment. Design strategies like
enabling exploration, promoting collaboration, and ensuring immersion have been synthesized from
varied literature on ARLEs [
84
]. Another study suggests design strategies like making contextual,
gamied, and student-driven ARLEs [62].
The design approaches help in dening the ways to implement a decided strategy in order to
achieve the dened learning outcome(s). In one of the works, the reported design stages of the
design process for creating AR applications were classied as: Task, Design Specication, Concept,
Preliminary Layout, Denitive Layout, and Product Documentation [
38
]. It was found that among
the dierent stages of the design process, the Concept, Preliminary Layout and Denitive Layout
stages of the design process are the areas currently most investigated while the Task, Product
Documentation, and Design Specication stages are least investigated. This emphasises on the
need to have a holistic and clearly outlined design process, highlighting the latter three stages.
The reported works emphasise generic implications for the design process, varying across the
lenses of the required characteristics. Also, professionals and practitioners nd AR/VR guidelines
to be scattered across the internet [
5
]. Overall, the literature on the holistic design process that
provides relevant design strategies and decisions for creating classroom-based ARLEs seems to be
sparse and dispersed.
In the context of educational interventions, co-design or co-creation has been dened as “a
highly-facilitated, team-based process in which teachers, researchers, and developers work together
in dened roles to design an educational innovation, realize the design in one or more prototypes,
and evaluate each prototype’s signicance for addressing a concrete educational need” [
80
]. Finding
it useful in school levels, co-design increases the teacher’s reections and ownership over the
technology in the classrooms [
80
] and helps in meeting the teachers’ goals of the curriculum [
95
].
While observations and interviews are adopted in user-centered design, the designer gains the
knowledge passively from theory and the users to enhance the understanding of the technology
and generate concept ideas [
82
]. In contrast, the collective creativity is brought forth while applying
co-design in the design process [
82
]. Considering its advantages, the co-design approach has been
adopted in AR learning to combine the actors’ expertise and contributions to create an AR book
[
1
], AR game-based learning [
96
], and AR vocational education and training applications [
7
]. Thus,
deriving the benets of this approach, our study was based on investigating the design strategies
and decisions through co-design in a design workshop.
Our ndings add to the knowledge body of the ARLE design process. We highlight the various
similarities and dierences with regards to the design strategies and decisions. Thus, we provide
empirical insights on the approaches adopted by the designers of an ARLE for the classroom,
ranging from content analysis to establishing the learning context in AR while designing an ARLE.
3 STUDY DESIGN
To investigate the design strategies and decisions involved in creating an ARLE for classrooms,
we conducted a design workshop with multiple groups, and focused on a qualitative method of
evaluation. The study addressed the following research question:
RQ: What are the approaches and decisions adopted by the designers to design an interactive classroom-
based ARLE?
3.1 Design Task
The aim of the study was to investigate the spectrum of approaches adopted by the designers of
an ARLE. Hence, the participants were asked to design a student-centered ARLE for a classroom.
To do so, they had to recreate a physical classroom scenario where the students could learn by
performing AR learning activities using tablets. The scope of the study involved a few topics from
Proc. ACM Hum.-Comput. Interact., Vol. 5, No. CSCW2, Article 461. Publication date: October 2021.
461:6 Pratiti Sarkar and Jayesh S. Pillai
the Mathematics syllabus for 6-8 grade students. These topics were chosen based on the suggestions
provided by Mathematics teachers during our earlier related studies [
86
,
87
,
90
]. The teachers
believed that these topics when taught using AR can help students understand and learn better.
Also, the chosen topics i.e. Fractions, Mensuration, Probability, and 3D Geometry, are commonly
explored in the literature of AR in education, as explained in Section 2 of the paper. Each topic was
randomly assigned to two groups, as shown in Table 1.
Table 1. The distribution of topics and groups
Topic Fractions Mensuration Probability 3D Geometry
Grade 6th 7th 8th 8th
Group G1 G8 G2 G4 G3 G5 G6 G7
During the session, each group was provided the textbook’s content of the assigned topic. The
groups were formed by random assignment of the participants. Similarly, the topics were randomly
assigned to each group. A list of user expectations of AR experience [
88
] in classrooms was also
provided, considering it to be a strong reference to spark the discussion. The participants could
assume that the students have access to the tablets in the classrooms. Each group was expected to
conceptualize an AR-based learning activity and document the ideation process of its use in the
classroom. Any assumption(s) beyond the ones mentioned by the authors had to be documented
by the participants. They were not expected to develop a working prototype and test it. Thus, we
conned our study to conceptualization of the ARLE.
3.2 Participants and Recruitment
With the approval from Institute Ethics Committee (IEC), an online design workshop was conducted
with eight groups of 32 participants (14 males, 18 females) from India. Each group consisted of four
participants - an AR developer, an interaction designer, an education researcher, and a middle-grade
Math teacher. With this group composition, we intended to get inputs about the aspects of learning
diculties and practices, learning sciences, and viable integration, design and implementation of
AR technology. Such a group composition was also formed in a previous study on collaborative
creation process (co-creation) to design and develop an AR application for Vocational Education and
Training [
7
]. The teachers were recruited through the mailing lists available online. The education
researchers and interaction designers were recruited through personal connections and snowball
sampling. The AR developers were recruited by advertising on public platforms. Their skills with AR
were veried using professional prole details available/provided online. The study was conducted
online because of the restrictive norms due to the pandemic.
The average ages of the teachers, education researchers, AR developers, and interaction designers
were 39, 29, 27, and 26 years respectively. Apart from the teachers, all other participants had
previously designed and/or developed an AR-related application. The education researchers, AR
developers, and interaction designers had on average 5, 4, and 3 years of work experience in their
respective designations. Moreover, these three categories of participants had on average 3 years of
experience in designing, developing and testing the self-created AR applications. The teachers on
average had 18 years of experience in teaching Math to middle-grade students. The teachers were
made familiar with the AR technology by sharing example videos that indicated the meaning and
the use of AR in education. These sample videos were classied as marker-based and markerless
handheld AR applications consisting of demonstrations in Mathematics and Science for learning
purposes. The participants were from varied geographical locations in India as the study aims at
Proc. ACM Hum.-Comput. Interact., Vol. 5, No. CSCW2, Article 461. Publication date: October 2021.
Approaches for Designing Handheld Augmented Reality Learning Experiences for Mathematics Classrooms 461:7
Table 2. Participant Demographics
Work Work
Group ID Gender Age Experience Group ID Gender Age Experience
(Years) (Years) (Years) (Years)
Math Teacher Education Researcher
G1 P1 F 52 14 G1 P2 M 28 5
G2 P5 F 29 10 G2 P6 M 29 6
G3 P9 F 37 16 G3 P10 F 25 3
G4 P13 M 32 28 G4 P14 M 30 7
G5 P17 M 45 23 G5 P18 F 33 3
G6 P21 F 40 19 G6 P22 M 35 2
G7 P25 M 38 16 G7 P26 M 27 8
G8 P29 F 39 18 G8 P30 F 27 6
AR Developer Interaction Designer
G1 P3 M 32 4 G1 P4 M 23 1
G2 P7 F 23 3 G2 P8 M 27 5
G3 P11 M 40 2 G3 P12 F 26 3
G4 P15 F 24 5 G4 P16 F 33 2
G5 P19 F 26 5 G5 P20 M 22 6
G6 P23 M 25 7 G6 P24 F 30 2
G7 P27 M 24 3 G7 P28 M 23 2
G8 P31 M 22 3 G8 P32 M 24 3
designing ARLE as per the present conditions of Indian classrooms. The details are presented in
Table 2.
3.3 Procedure
Before the study, informed consent was taken from all the participants and were apprised that
the session will be recorded. They were explained the context of the study and assured of the
anonymity of their data. A questionnaire was also shared to gather their demographic information
such as age, gender, designation, years of working experience, and familiarity with AR.
On the day of the study, all the participants of a group connected through the Zoom video
conferencing platform. Per day two groups participated where each session was scheduled for
approximately three hours. This time duration was chosen considering that shorter duration may
not lead to detailed concept generation and longer duration than this might be taxing for the
participants. Moreover, it was decided to not split the session across multiple days to avoid the
situation where participants might drop out of the study between sessions. An informal ice-breaker
session of 15 minutes was conducted at the beginning of the session, in which the researcher and
the participants rst introduced themselves. The participants were then asked to mention one thing
about the city they belonged to and their favourite food item, while the researcher was a silent
observer. This was intended to help the participants be vocal about their personal experiences and
to lower the social barriers. After 5 minutes, the researcher randomly asked a participant to mention
the two aspects of another random fellow participant. This was done till all four participants in the
group described the two aspects of each other once. The entire process made it comfortable for the
participants to interact with each other in the remaining session. In the next 10 minutes, the design
task was explained to them. The slides containing the design brief and the listed user expectations
Proc. ACM Hum.-Comput. Interact., Vol. 5, No. CSCW2, Article 461. Publication date: October 2021.
461:8 Pratiti Sarkar and Jayesh S. Pillai
Fig. 1. Group 1 ideating on the topic of Fractions populated their thoughts on the Miro board. The participants
of this group mentioned sample screens showing AR content representation, the types of AR examples
across dierent levels, the teacher intervention, and the approaches for onboarding, practice exercises and
gamification.
were then shared with the participants along with the chapter content from the middle school
textbook. The participants were asked to think aloud throughout the session on Zoom and note
their thoughts and ideas on the Miro board where each user had access to edit it. The researcher
additionally shared the screen on Zoom showing the Miro board for everyone to synchronously
see, discuss, and design as per the given brief. An instance of the same is shown in Fig. 1. At least
two participants were seen to be actively noting the thoughts and ideas on the sticky notes of the
Miro board. While discussing, the groups used the sticky notes to establish connections, added
sketches to explain the design concepts, and included low-delity mobile/tablet prototypes using
the templates of Miro to explain the user ow of the designed AR app solution. In the last 20 minutes
of the session, the participants presented their concepts, and briey discussed their decisions and
experience.
After the session, an anonymous feedback form was shared with the participants to know about
their overall experience, likes, dislikes, and suggestions (if any) for improving the session. The
participants were also encouraged to share any thoughts or ideas they may come across after the
session in the common group mail thread.
3.4 Pilot Study
A pilot study was conducted with one group of four participants. During the process it was found
that the usability of the initially chosen board was not that eective while documenting. Hence,
it was changed to Miro board for the rest of the study. Thus, the pilot study helped in verifying
the delivery of instructions, data collection tools, the duration of the study, and the method of
executing the designed protocol.
Proc. ACM Hum.-Comput. Interact., Vol. 5, No. CSCW2, Article 461. Publication date: October 2021.
Approaches for Designing Handheld Augmented Reality Learning Experiences for Mathematics Classrooms 461:9
3.5 Data Collection and Analysis
The study aimed to understand the design approaches, and decisions involved in designing an
ARLE for a given Math topic from the middle-grade textbook. The entire session was recorded
and analyzed using Atlas.ti software. An evaluation rubric partially adopted from STAR-ARLE [
24
]
was used to assess the extent of AR aordances incorporated for the classroom scenario explored
and the completeness of the concepts. Using the approach of inductive analysis [
94
], useful codes
were derived from the gathered data and anity diagrams were created to generate themes around
the research question. The unit of analysis in this study is the group. While the participants of a
group discussed, ideated and noted their thoughts, their decisions, methods, and techniques during
the design process were coded. The researchers began with open coding to come up with the
initial potential codes. Through iterative discussions, the codes were further grouped to obtain
higher-level codes in the axial coding phase. The coding process was iterative and proceeded in
stages. It was stopped when no new codes emerged. We encountered saturation after 6 studies out
of 8 leading to the reported results in the next section. The key themes emerging on grouping the
codes were of content,context and design, which have been discussed in detail in Section 4.
4 FINDINGS
We present our main ndings by describing the observations across groups. Overall, the Math teach-
ers were observed to be providing insights on the current teaching practices, learning diculties,
and the ways students would be engaged in performing the AR learning activities. The education
researchers contributed to aligning the techno-pedagogical aspect with the content creation while
considering the cognitive levels of the students. The interaction designers worked towards inte-
grating the aordances of AR technology and the learning activities. The AR developers suggested
the feasible implementations of the entire conceptualized system. Despite many dierences in
approaches between the groups, we found that most groups had some broader similar strategies of
solution design. To answer the RQ, we have synthesized these similarities to explain the strategies
and decisions for the ARLEs that have been designed by the participants. We organize our ndings
into three sections below. In the rst section we discuss the strategies that were considered to
translate the content of the textbook to an AR learning activity. The second section highlights the
ways of establishing the AR learning activities in the context of the classroom while involving the
two key stakeholders i.e. students and the teacher. The last section puts forward the elements of
consideration to design the low-delity prototypes for an AR learning activity to be performed
using a handheld device. The sections include supporting gures to clearly outline the dierent
deciding factors and strategies. One-way arrows depict the leading classication. Two-way arrows
reect the interdependence of the classications.
4.1 Content: Translating the Textbook Content to AR Activities
To bring the AR component to the textbook content, its appropriate analysis was done and the
strategies adopted for translation have been elaborated below.
4.1.1 Content Analysis. Across the groups, the idea generation began by scrutinizing the chapter
content to identify the key concepts. Additionally, the Math teacher’s insights guided a group
towards identifying the learning objectives and the learning diculties faced by the students. “Once
we have a proper understanding of what students should learn and understand, then we can develop
from there” (G2). The arguments were then based on selecting appropriate topics and examples. In
doing so, the participants were seen to be taking either of the three approaches as discussed below
and indicated in Fig. 2.
Proc. ACM Hum.-Comput. Interact., Vol. 5, No. CSCW2, Article 461. Publication date: October 2021.
461:10 Pratiti Sarkar and Jayesh S. Pillai
Fig. 2. Strategies to analyse the textbook content appropriate for AR translation
The rst approach involved content exploration and listing the examples in the chapter, especially
the ones that included real-life instances. The examples were then categorized in a way that can fall
under the categories in the list of user expectations of AR experience [
88
] in classrooms that was
provided as part of the design task. In the second method, the participants categorized the textbook
examples on the basis of the dimensions of cognitive levels as proposed in Bloom’s taxonomy
[
2
]. Functionalities of AR were then created based on the complexity of the examples. The third
approach involved categorizing the textbook’s chapter content on the basis of the types of contents
i.e. factual, conceptual, and procedural [
2
]. This was followed by identifying real-life instances
where examples are applicable for the categories obtained. These examples were either taken from
the textbook or introduced by the participants.
4.1.2 Translation to AR while integrating the technology. On identifying the possible relevant
examples, the arguments were based on accommodating the aordances of AR with suitable
tracking medium, to obtain the identied learning objective(s) as indicated in Fig. 3.
Suitable Aordances of AR. All the groups were observed to be discussing and deciding the
suitable aordances of AR while translating the chapter content to AR learning activities. These
aordances were mapped with the list of user expectations [1] to argue for a feasible and satisfactory
solution, where the intent was to answer “...what can AR do that cannot be is not achievable in real
life?” (G4). The following aordances of AR were thus considered by the groups:
Contextual Visualization: The discussions were around the realization of setting up the virtual
content in a specic context. For example, Group 8 suggested the cutting and merging of a
cylindrical 3D cake while creating the context of birthday celebration in the classroom, and
teaching the concepts related to fractions.
Proc. ACM Hum.-Comput. Interact., Vol. 5, No. CSCW2, Article 461. Publication date: October 2021.
Approaches for Designing Handheld Augmented Reality Learning Experiences for Mathematics Classrooms 461:11
Fig. 3. Strategies to translate the textbook content to AR learning activities
Perspective Exploration: Four groups considered that AR was essential as “...in this they are
able to move and see the dierent perspectives” (G6). Thus, it was emphasised that the activities
should be designed in a way that encourage students to visualize the dierent perspectives
of a 3D object which is otherwise dicult to explain in class. This aspect was seen to be
emphasised by the groups working on the topics of 3D Geometry and Mensuration, requiring
the need to observe the properties of the 3D shapes.
Situation Re-creation: Group 3 insisted upon re-creating and augmenting real-life scenarios
like calculating the probability of a mango falling o a tree on throwing stones. This would
help students to relate to and realize the application of the concept in real-life. For example,
Group 5 mentioned:
“To teach probability in the class, you [teacher] will not give them [students] coins, you will
not give them playing cards and you will not make them throw stones at the tree. All this is
what we can create in AR” (G5).
Location-Awareness: Taking inspiration from the popular AR game ‘Pokemon Go’ [
70
], two
groups suggested that within the classroom, the students can be asked to nd objects while
attaining a learning objective. For example, Group 1 suggested of nding the fractions in
dierent locations of the classroom to complete a shape. This was suggested to provide the
students a playful and engaging experience while learning.
Real-time Annotation: The groups ideating on the topics of Mensuration and 3D Geometry
considered that “...we cannot create glowing edges on real-life 3D objects” (G4). Thus, the ability
for the user to annotate on a virtual object in AR, in real-time would help to explain the
related concept better. The system-generated annotations such as indications to move in a
direction, swiping, slicing an object were proposed with the groups working on the topics of
Probability and Fractions.
Proc. ACM Hum.-Comput. Interact., Vol. 5, No. CSCW2, Article 461. Publication date: October 2021.
461:12 Pratiti Sarkar and Jayesh S. Pillai
Embodied Interaction(s): It was argued by three groups that “...AR gives the freedom to move
and look around” (G3). Thus, the aordance of full body movement, when implemented with
other 3D object manipulation tasks like swiping, slicing, rotation, etc., would give them a
hands-on and realistic experience while learning.
4.1.3 Type of AR Tracking. Three types of AR tracking were considered by the groups: marker-
based, markerless and location-based. Four groups considered marker-based AR which involves
scanning a marker i.e. an image or a physical object using the device’s camera which triggers the
overlaying of virtual graphics [
29
]: “Once these cross-section markers are being scanned, the 3D popup
appears and they have to classify which solid does it actually belong to” (G6). Three groups considered
markerless AR which gets triggered by scanning the surrounding environment, without using any
ducial marker [
11
]: “If we want to develop something that has a library, like you open up a side panel
or something, then markerless is a good option. You just scan a surface and it gets detected. You tap
on the option of a square or a rectangle. Then it pops up on the surface.” (G1). One group considered
location-based AR which uses the device’s GPS which allows placing the virtual objects in a certain
location [
29
]: “We can scatter the shapes as geo markers and then the students will nd the shapes
like a treasure hunt activity. They nd people having the 3D shape of the 2D shape that’s assigned to
them” (G2). For all the groups, the AR developers dominated the discussion on this aspect. They
guided the group members towards dening the suitable and feasible AR tracking medium for AR
learning activities based on their prior knowledge of a few existing AR applications and experience
in developing AR applications. For example, P15 mentioned: “There are apps with which we can
actually go and measure the distance or length from one surface to another.” (G4) Once determining
the suitable AR content representation, the levels, complexity, details and use of the AR application
were discussed.
4.1.4 Translation to AR while integrating learning. While integrating the aordances of AR with
the learning aspect, the depth and breadth of learning were considered. The depth was determined
in terms of dening how deep the concept is to be taught using AR and the breadth was dened by
the number of tasks for each level. The depth was dened by the levels of Bloom’s taxonomy [
2
].
For each concept, the number of tasks were dened by the growing complexity.
The overall pedagogical approach adopted by all the groups involved collaborative learning
process using the AR application. The teaching strategy that was adopted by the groups with the
topic of Probability (G3, G5) and 3D Geometry (G6, G7) was that of Predict, Observe and Explain
(POE) [
51
]. In this the students rst predict the answer for the given question in the AR space. The
demonstration is then carried by the students in AR where they perform a dened action on the
virtual 3D object. The predicted answers are then veried and the discussion with the peers and the
teacher take place to elaborate the targeted concept. The groups other than G3 and G7 proposed a
gamied way of learning to keep the students motivated throughout.
4.2 Context: Incorporating AR Activities in the Classroom
In the design process, appropriate learning delivery mode was considered. The current teaching
practice was discussed to understand the ways in which AR based scaold can be incorporated in
the curriculum. This decision was followed by the assumptions of the number of available devices
and possible group collaborations. The scenarios were then created in ways to enable exploration,
promote collaboration and ensure immersion [
84
]. Thus, deciding the group dynamics and the
instructional scaold played a vital role, which have been discussed below and indicated in Fig.4.
Proc. ACM Hum.-Comput. Interact., Vol. 5, No. CSCW2, Article 461. Publication date: October 2021.
Approaches for Designing Handheld Augmented Reality Learning Experiences for Mathematics Classrooms 461:13
Fig. 4. Strategies to integrate AR-based learning in the classroom
4.2.1 Students’ Group Dynamics. On outlining the relevant AR aordances for the chosen topic
and their representation, the students’ group composition and the ways of using the application in
the classroom were elaborated.
Students’ group composition. The groups were seen to be deciding the ideal collaborative structure
for the students to perform the AR learning activities in the classroom. Two types of collaborative
compositions were considered by the groups. Two groups ideated around forming a group of 4
students handling one tablet per group or per student. For example, Group 8 suggested:
“Let’s say there are four students. One of them can hold the device. And multiple tasks are
given so that each task is performed by one of the students and the others can instruct
them how to do it”.
The remaining groups insisted upon students performing the AR learning activities in dyads. In
doing so, the roles of the individuals were decided. For example, “One person is going to be the
navigator and other person is simply carrying the tab to scan” (G2),“...one student cuts the shape in AR
and the other one merges it back” (G7). The activities were designed in ways to let all the students of
a group be involved in performing the AR learning activities.
Mode of Execution. The groups suggested four dierent ways of using tablet-based AR in the
classroom. This decision was based on the type of AR learning activities that were conceptualized
for a given topic. For the rst three ways, it was assumed that there is access to only a certain
number of tablets for a class.
The rst way suggested by two groups included the use of a projector screen along with the
tablets. In this scenario, the students tend to work in groups with one tablet in each group. The
projector screen would be used to share the screens of all the tablets in use during and/or after an
AR learning activity. For example, G7 which was assigned the topic of 3D Geometry suggested:
“Your [teacher’s] view will be the Master View which will be projected and all students
will be viewing the same object in their tablets. Let’s say you are marking an edge on the
Proc. ACM Hum.-Comput. Interact., Vol. 5, No. CSCW2, Article 461. Publication date: October 2021.
461:14 Pratiti Sarkar and Jayesh S. Pillai
object, it will be shown to all the students. They can view it in dierent perspectives. If
they are marking on the edge of the object, that will be visible on your screen too.
This way indicated that the students will be able to simultaneously reect on their peers’ work and
approaches.
The second way of using AR in the classroom involved making multiple groups of students. Each
group is provided a tablet and every group gets a dierent AR learning activity of the same level.
The dierent groups of students can then compete to complete the task. As per the groups, with
this way the students will be focused on interacting with their group members in accomplishing
the assigned AR task.
The third way was the commonly proposed one. In this scenario, multiple groups would be
formed and each group would be provided a tablet. The same AR learning activity will be given
to each group. The students will work collaboratively within groups to perform the AR learning
activities, while the teacher would be the facilitator. The variation in the approaches of the groups
came while dening the depth and breadth of the AR learning activities.
The fourth way suggested by Group 3 was that each student is provided a tablet and they form
groups to perform an AR learning activity. They assumed that the number of tablets available
for a classroom is equal to the number of students in the class. In this, the action of one student
gets reected on the next student’s action in that group. For example, G3 depicted an example of
reinforcing probability and chance through the game of snakes and ladder. In this the students
would form small groups, where each student has a tablet. While playing snakes and ladder by
physically moving and climbing up and down based on the placement of the virtual boxes, ladders
and snakes on their augmented screens, they determine the probability of being bitten by a snake
or climbing the ladder, as shown in Fig.5.
Fig. 5. Group 3 suggesting the way to perform their designed AR activity
4.2.2 Instructional Scaolding. The participating groups ideated to determine the phases in which
the students would perform the AR learning activities in the classroom and the role of the teacher
at that time.
Phases of Scaold. Realizing the alignment of the AR activity sessions with the curriculum design,
another crucial aspect to decide was the phase of teaching in which the AR application will be
used by the students in the class. The rst method suggested by three groups involved using AR
learning activity to introduce the topic. For example, Group 5 discussed the approach of introducing
Proc. ACM Hum.-Comput. Interact., Vol. 5, No. CSCW2, Article 461. Publication date: October 2021.
Approaches for Designing Handheld Augmented Reality Learning Experiences for Mathematics Classrooms 461:15
the concepts of chance and probability while letting the students do hands-on activity of tossing
multiple 3D coins repeatedly as such a scenario is not possible in the physical classroom:
“When the teacher starts with this experiment, everyone has to swipe to toss the 3D coin
10 times... the rst pair of students share that they have got 5 tails, 3 heads and so on...
the 3D virtual Genie has magically given us this probability! While doing this they might
have deducted the formula already or after this. The teacher then uses the data of those
20 groups of students and she puts it all together. This would help the students see that
the probability tends to an ideal value when they talk of a large number of trials. And
here the teacher tells them that because you are not going to toss so many times whenever
you are doing anything, that is why we move from experimental probability to classical
probability and we talk about the formulae”.
The second and the most common method proposed was to explain the application of the taught
concept by giving contextual tasks. For example, once the types of 3D solids are explained to the
students, Group 7 working on 3D Geometry suggested that,
“We can have an activity in the app where we allow the students to merge and cut out
shapes from other shapes”.
The third method discussed by two groups was assessing the learning of the students as they
perform the multi-level AR learning activities. The exploration in the AR space could be done
through quizzes. The level and complexity of the quiz questions in the AR space was recommended
as per the levels of Bloom’s taxonomy [2].
Ways of Scaolding. The participating groups were observed to be discussing two ways of
scaolding in the dierent phases of teaching. The rst way suggested was to present the AR
learning activities as a learning module that supports both teaching and visualization. For example,
Group 2 stated: “We can have the nal application as a learning module which would have both
teaching, this is how it is done, these are the formulae, and the visualization. The other way proposed
was to have an additional instructional tool after a topic is completed.
The role and controls of the teacher. It was commonly suggested by the groups that the students
would learn through exploration and collaboration, while experiencing contextual visualization
in AR. The teacher as a facilitator can have the controls of monitoring the student actions as
“...otherwise when the kids will get the device, they will start going to every option, and play with the
app” (G5). Thus, the groups proposed that the teacher can control the AR application the following
ways:
Assign: The teachers can decide what type of AR learning activity to be performed on a
particular day in the classroom: “... like on day one we will measure, on day two we will explore”
(G2).
Monitor: The teachers will be able to monitor the actions of the dierent groups of students
while they perform the AR learning activities: “The teacher will have a record of what the
student is doing. She won’t be able to interfere in any actions because the student should have
that much freedom to interact with it” (G6). The teacher may help or guide any group if they
get stuck somewhere.
Unlock: If the AR learning activities have levels of tasks, the teacher can set the control of
unlocking the next level for the students whenever found appropriate.
Assess: The teachers can have a dashboard to receive the statistics based on the performance
of the students in the group: “Let’s say there are four teams. Team A nished its task in this
much of time. Probably some statistics on their performance can be given to the teacher so that
she can, later on, take her own time and analyze it, to evaluate their performances” (G8). The
Proc. ACM Hum.-Comput. Interact., Vol. 5, No. CSCW2, Article 461. Publication date: October 2021.
461:16 Pratiti Sarkar and Jayesh S. Pillai
Fig. 6. Strategies to design low-fidelity prototypes of AR learning activities
results obtained can be used as a formative evaluation of the students’ performance during
an AR session.
Overall, all the groups proposed to have a teacher’s side in the application where the teacher
is expected to “...have a dashboard, like a super controller of all the controls” (G7). Thus, with the
help of the controls “...the teacher will make sure that the students are using the app according to the
syllabus or the timeline of teaching” (G3).
4.3 Design: Creating the Prototype of AR Activity
Once the possible AR aordances and classroom execution were decided, it led to the following
design decisions regarding the design of the AR application and its learning activity for the given
topic (Fig.6):
4.3.1 Defining the virtual objects and the actions in AR space. To represent the concept in the AR
space, the groups dened certain virtual objects to be augmented and a related learning mechanism
as a result of a dened action. For example, to teach in AR the concept of representation of fractions
on a number line, Group 1 mentioned:
“...on the screen they can have the same part going on the number line, say from 0 to 1 as
a slider. If there is one 3D apple, and they have a 3D knife to control it the way they would
do in real-life, they cut the apple into four parts. And then they see the number line divided
into 4 parts. That could create a dynamic arranging of the number line representation as
they move the slider with actions on the real-life examples...
Thus, the groups provided examples in AR that were dicult to show using physical objects in the
classroom and/or required the students to do a certain action to understand the relevance of the
taught concept.
4.3.2 Defining the interactions. Considering the time duration of an activity and the intuitive nature
of the interaction, three types of interactions were commonly discussed. One of the interactions
was the ‘tap and snap’ interaction: “ Say there is a knife or a cutting plane in the app itself. When we
tap that, it should align at any angle. The cutting action will show the segmented part of the cube or
a complex shape” (G6). The other interaction was that of ‘swipe’ to initiate the animation of the
augmented 3D object: “There will be a coin which will be seen on the screen and the user can swipe
up to toss the coin. And then there can be dierent animations - as the coin will fall to the ground,
there will be a dropping sound” (G5). The third one involved the ability to ’annotate’ on the 3D
Proc. ACM Hum.-Comput. Interact., Vol. 5, No. CSCW2, Article 461. Publication date: October 2021.
Approaches for Designing Handheld Augmented Reality Learning Experiences for Mathematics Classrooms 461:17
object: “The students can mark and count the number of edges” (G7). All these ways involved the
embodied interaction with the ability to see the 3D object from all the sides by either rotating the
marker or physically moving with the handheld device in case of markerless or location-based
design solution.
4.3.3 Defining the gamification requirements. To keep the students motivated while learning in
a competitive and playful manner, six groups suggested to introduce gamication aspects using
two strategies. The rst way involves having time-based playful tasks in the AR space. Regardless
of the activity being performed as a game, the second way involved rewarding the students for
the actions they perform: “We can give them incentives. We just give some rewards, some points that
kids nd it [the activity] interesting... Say this is the rst level that you completed and then you get a
level 1 badge...” (G3). In earlier studies, game-based AR learning has been suggested to promote
fun, challenge and curiosity [
62
,
101
] among the students. The participating groups had similar
objectives while deciding the gamication aspect of the AR learning activities.
4.3.4 Defining the feedback mechanism. The groups worked on the ways of providing the feedback
to the students for their actions while they performed the AR learning activities. The discussion led
to providing feedback in two-folds. The rst way considered was to have a system-level feedback
using textual messages, color-highlights or a virtual pedagogical agent in the AR space. This should
help in indicating to the students about the mistakes done and the correction required. The second
way involved the teacher-level feedback to provide correct explanations when the students have
open-ended problems to solve, commit mistakes and/or get stuck.
4.3.5 Defining the UI elements. To show one example of leveraging the aordance of AR, the
representation of the content on the tablet/mobile screen was decided. This was followed by
detailing the components of the activity, the features of system feedback and dening the details of
the screens. As an example shown in Fig. 7, Group 5 designed the screens for teaching Probability.
They depicted the way to introduce the topic and one scenario of doing the assessment. In the
introduction to probability scenario, the students repetitively toss the virtual 3D coin in AR (the
way they would expect to do in real life) and the 3D character of Genie as a virtual pedagogical
agent mentions the probability of the occurrence of head or tail. In the assessment scenario, the
students spin the wheel and predict the probability of the occurrence of a particular number.
5 DISCUSSION
The design methods considered by the groups helped in dening the steps to be taken to implement
a decided strategy to achieve the dened learning outcome(s). In the process it was realized that the
groups faced several challenges as well. Initial tensions similar to the ones reported by Roschelle et.
al [
80
] were observed in our study, i.e. the teachers lacked ownership in the beginning. In their
study, the teachers were provided the experience of using the actual device in the classroom to
help them gain the clear sense of their role in the co-design process. In contrast to that, our study
design and group composition encouraged the active participation of the teacher, where the social
dynamics evolved over the session. The education researcher who had the knowledge and expertise
of the teaching strategies and the technology acted as a bridge in bringing together the thoughts of
the teachers and the AR designers and developers.
In terms of dening the design decisions, there were a lot of dependencies. However, the partici-
pants of a group dealt with these decisions by argumentation and elimination techniques. Thus,
our ndings synthesised the dierent design strategies and decisions that were adopted by the
participating groups. This was done by highlighting the rationale of a certain action, identifying
the ways to implement the decisions and dening the techniques of attaining the learning objective.
Proc. ACM Hum.-Comput. Interact., Vol. 5, No. CSCW2, Article 461. Publication date: October 2021.
461:18 Pratiti Sarkar and Jayesh S. Pillai
Fig. 7. Group 5 working on the topic of Probability designed the UI of the screen
We now reect upon our inferences from the ndings that can be supportive for future research
in CSCW and HCI. We discuss about what our ndings suggest using the lenses of design strate-
gies suggested by Santos et. al [
84
] for the novice designers to move towards the iterative design
approaches and decisions (as indicated in Fig. 8) for designing an ARLE for classrooms.
5.1 Towards Enabling Exploration
5.1.1 Appropriating for AR. Our analysis indicated that for content translation, the scanning and
classication of the content is required. This is then mapped with the expected learning outcomes
and accompanied by reecting on the learning diculties that students face in the usual teaching
practice. To enable exploration while bringing in the contextual dimension of learning [
12
], the
real-life examples from the textbook and the ones referred by the teacher in the classroom are
enumerated for the categorised content. This approach is in contrary to the reported approaches
where the students’ ways of problem solving in the physical classroom are initially analysed to
come up with the design of ARLEs [
77
,
99
]. However, such ARLEs are targeted towards a particular
skill to develop. In both the approaches, on outlining the key contents, the translation to AR to
enable exploration involves the ideation of the AR environment. This seems to be inuenced by the
choices of creating (1) a simulation, (2) a contextual representation, (3) a gamied world [
62
,
84
], (4)
Proc. ACM Hum.-Comput. Interact., Vol. 5, No. CSCW2, Article 461. Publication date: October 2021.
Approaches for Designing Handheld Augmented Reality Learning Experiences for Mathematics Classrooms 461:19
Fig. 8. The design approaches to create an ARLE for classrooms
a storytelling method, or (5) a mixed combination of these choices. As indicated in previous studies
[
20
,
62
,
84
], the context of the ARLEs must be set by situating instances from real-life scenarios to
guide in visualizing abstract concepts. Thus, the design decisions for the alternate representation in
AR are based on (1) the expectations of the users [
88
], (2) the designers’ prior experience of creating
AR applications and/or (3) the aordances of AR. The design solutions also indicated that the AR
representation must be kept simple and minimal [
20
] to restrict overwhelming visualizations for
the students.
5.1.2 Embracing AR Integrated Learning. After the elucidation of the group dynamics and appro-
priate AR world, it is required to dene how learning is to be delivered through it. As reected from
the ndings, learning using AR can be imparted in three possible stages: (1) to introduce the topic,
(2) to reinforce the taught concepts, and/or (3) to assess the learning. Further, from our observation
and as suggested by Wu et al. [
101
], the tasks can be designed to promote game-based learning,
problem-based learning or learning by design. This can lead to curiosity among the students while
they perform the AR learning activities [
62
]. The discussions also implied that the tasks can be
strategized to incorporate multiple levels to guide the students in attaining the dierent stages of
learning as per Bloom’s taxonomy [
2
]. Though the ndings did not target any skills such as spatial
thinking or critical thinking, we realize that learning may also be targeted at skill acquisition as
suggested in prior works [
49
,
77
,
99
,
101
]. This aspect was not considered by the participating
groups in our study for keeping it restricted to the textbook based examples and activities.
5.2 Towards promoting collaboration
5.2.1 Encouraging Collaborative Active Control for Students. To make it an engaging user-centered
experience [
68
] for the students, it was prominent from the analysis of the discussions that the
intention was to provide them active control for the designed activities. In doing so, the collaboration
of students played an important role [
84
]. The students can see the augmented virtual objects and
information along with their peers in the same space. As suggested by Sarkar et al. [
86
], this can
promote peer learning while being involved in the exploratory processes and embodied learning
[
76
]. It also helps students in building community through collaboration and competition [
27
]. The
group distribution and composition must be taken into consideration while dening the functions
of the AR learning activities. While active control of students are encouraged by the participating
groups, studies have suggested to have appropriate approval of students’ actions from the teachers
for a guided execution in the classroom [
20
,
24
,
99
]. The type of AR tracking, interaction and
complexity of the AR learning activity gets decided accordingly.
Proc. ACM Hum.-Comput. Interact., Vol. 5, No. CSCW2, Article 461. Publication date: October 2021.
461:20 Pratiti Sarkar and Jayesh S. Pillai
5.2.2 Ensuring Instructional Scaolding. While the students interact and learn with the AR con-
tent, informative feedback is required to make the status of the system obvious [
28
] and provide
response to validate their actions. It was suggested that the feedback can be provided by the
virtual pedagogical agents (for instance, mimicking a popular cartoon character) in the AR space
[
17
]. Moreover, badges and rewards can create a sense of competitiveness and motivation while
exploring the dierent levels within the activities [
23
]. However, if the students have doubts or
get stuck, the teachers are expected to be the facilitator in the process as suggested previously
[
32
]. Thus, it is required to determine the amount of scaolding required from the system and
teacher side. Our ndings on instructional scaolding aligned with the principles on reducing
orchestration load for teachers mentioned by Cuendet et al. [20]. The insights indicate that while
aligning to the regular teaching practice, the teachers play a key role in the entire experience. To
provide authority to the teachers while still keeping a student-centric experience and encourage the
two-way communication, the teachers can (1) assign the AR tasks, (2) monitor the students’ action
live, (3) unlock the levels, and/or (4) assess the performance of the students. Thus, the teachers
can be given the controls to initiate the process and monitor the actions and performance of the
students in their own tablets. Moreover, to use the ARLE eectively in the classroom lesson plans
in AR can be provided.
5.3 Towards Ensuring Immersion
On having the basic outline of the AR learning activities, the user interface (UI) and user experience
(UX) requirements of the application can be decided. Though the Miro board was used as a platform
in our study for the participants to articulate their designed solutions, the groups struggled in
showing the designs and depicting the degrees of freedom in the 3D space using the 2D screen
templates. The similar challenge has been reported by Krauß et. al [
53
] and Ashtari et. al [
5
].
Moreover, prototyping the interactions also comes up as a challenge [
22
,
53
]. To overcome the
barriers of prototyping and for clear articulation, the participants created a few classroom scenarios
to describe the use and implementation of the designed solutions. While scenarios have been seen
to be provoking creativity in design [
9
,
10
], a similar observation was noted in our study in the
context of creating and describing the classroom scenarios to provoke ideas. However, it was also
observed for one group that extreme hypothetical scenarios were created which went in all sorts
of directions. Though open-ended scenarios are encouraged for creating the caricatures of the
future [
9
], in this case the group struggled in reecting on their actions. Thus, to meet the UX
requirements of an AR app, we realized that staged reections are required in the conceptualizing
of solutions. Moreover, the considerations for why and how a particular prototype is intended to
support the design process while manifesting ideas to create the prototypes [55].
The immersiveness of the application can be enabled by letting the students rotate the augmented
3D objects, physically moving around them, and/or locating them in the classroom space. This
counts for appropriate virtual objects and the actions to be performed on them using the dened
interactions. The interactions in the AR learning activity must be intuitive for the students [
12
].
The cross-hair mode of interaction is another mode that has been previously studied with younger
students [
78
]. However, the study reported nger interactions to be more intuitive for the children.
Thus, the tap, swipe and annotate modes of interaction with the augmented 3D objects can be
easier for the students to respond to within the restrictive duration of the activities in the classroom.
At this stage it would be essential to refer to heuristics for evaluating the usability of of the AR
application [
21
,
30
]. On dening the low-delity prototypes through wireframing or mockups and
high-delity prototypes through multiple iterations of testing, the developmental frameworks [
43
]
or authoring tools can then be used to design the working prototypes.
Proc. ACM Hum.-Comput. Interact., Vol. 5, No. CSCW2, Article 461. Publication date: October 2021.
Approaches for Designing Handheld Augmented Reality Learning Experiences for Mathematics Classrooms 461:21
6 LIMITATIONS AND FUTURE WORK
In this study, the opinions, design, and settings of Indian classrooms have been considered. The
scope involves the design of ARLE in the subject of Mathematics. The emphasis of the study was
on the accessible mode of AR i.e. handheld AR and for the subject of Mathematics. However, the
analysis of the data made us realize that the results may be applicable for other subjects where
spatial thinking is required, the investigation of which is in the future scope of the work. Moreover,
the results may be applicable for other mediums of AR such as AR glasses and head-mounted
displays. Hence, one must be mindful while generalizing the ndings. The work also does not
evaluate the eectiveness of the designed solutions on learning gains.
For future work, geographically diverse groups and dierent subjects are to be considered. To
address this, we plan to conduct similar design workshops on a broader level with participants
from varied regions. Moreover, the design approaches and recommendations have been proposed
on the basis of the empirical insights from this study. The next phase of the study would involve
implementing them in the design of an AR application and validating the identied approaches
and decisions in the classroom scenarios.
7 CONCLUSION
With the extensive work of designing dierent types of ARLEs, there is sparse literature available
on the ways to approach the design of such environments. Our study was aimed at observing and
reporting the design approaches and decisions adopted by the designers involved in creating an
ARLE for classrooms. The ndings indicated the categories and inter-dependencies in the three
aspects of content, context and design of an ARLE. Our empirical ndings guided us towards
dening the design approaches for the novice designers that can be considered to design a handheld
ARLE for classrooms, ranging from content analysis to basic prototype design to incorporate the
design strategies of enabling exploration, promoting collaboration, and ensuring immersion [
84
].
Thus, for future CSCW and HCI research this work provides the direction towards a methodical
design process of handheld ARLEs for classrooms.
REFERENCES
[1]
Haifa Alhumaidan, Kathy Pui Ying Lo, and Andrew Selby. 2015. Co-design of augmented reality book for collaborative
learning experience in primary education. In 2015 SAI Intelligent Systems Conference (IntelliSys). IEEE, 427–430.
[2]
Lorin W Anderson, Benjamin Samuel Bloom, et al
.
2001. A taxonomy for learning, teaching, and assessing: A revision
of Bloom’s taxonomy of educational objectives. Longman,.
[3] Spark AR. [n.d.]. Become a creator. Retrieved September 14, 2020 from https://sparkar.facebook.com/ar-studio/
[4] ARCore. [n.d.]. ARCore overview. Retrieved September 14, 2020 from https://developers.google.com/ar/discover
[5]
Narges Ashtari, Andrea Bunt, Joanna McGrenere, Michael Nebeling, and Parmit K Chilana. 2020. Creating Augmented
and Virtual Reality Applications: Current Practices, Challenges, and Opportunities. In Proceedings of the 2020 CHI
Conference on Human Factors in Computing Systems. 1–13.
[6]
Ronald T Azuma. 1997. A survey of augmented reality. Presence: Teleoperators & Virtual Environments 6, 4 (1997),
355–385.
[7]
Jorge Bacca, Silvia Baldiris, Ramon Fabregat, Sabine Graf, et al
.
2015. Mobile augmented reality in vocational education
and training. Procedia Computer Science 75 (2015), 49–58.
[8] Mark Billinghurst and Andreas Duenser. 2012. Augmented reality in the classroom. Computer 45, 7 (2012), 56–63.
[9]
Susanne Bodker. 1999. Scenarios in user-centred design-setting the stage for reection and action. In Proceedings of
the 32nd Annual Hawaii International Conference on Systems Sciences. 1999. HICSS-32. Abstracts and CD-ROM of Full
Papers. IEEE, 11–pp.
[10]
Susanne Bodker and Ellen Christiansen. 1997. Scenarios as springboards in CSCW design. Social science, technical
systems, and cooperative work: Beyond the great divide (1997), 217–234.
[11]
Pedro Quelhas Brito and Jasmina Stoyanova. 2018. Marker versus markerless augmented reality. Which has more
impact on users? International Journal of Human–Computer Interaction 34, 9 (2018), 819–833.
Proc. ACM Hum.-Comput. Interact., Vol. 5, No. CSCW2, Article 461. Publication date: October 2021.
461:22 Pratiti Sarkar and Jayesh S. Pillai
[12]
Keith R Bujak, Iulian Radu, Richard Catrambone, Blair MacIntyre, Ruby Zheng, and Gary Golubski. 2013. A psy-
chological perspective on augmented reality in the mathematics classroom. Computers & Education 68 (2013),
536–544.
[13]
Alberto F Cabrera, Carol L Colbeck, and Patrick T Terenzini. 2001. Developing performance indicators for assessing
classroom teaching practices and student learning. Research in higher education 42, 3 (2001), 327–352.
[14]
Su Cai, Enrui Liu, Yang Shen, Changhao Liu, Shuhui Li, and Yihua Shen. 2020. Probability learning in mathematics
using augmented reality: impact on student’s learning gains and attitudes. Interactive Learning Environments 28, 5
(2020), 560–573.
[15]
Su Cai, Enrui Liu, Yang Yang, and Jyh-Chong Liang. 2019. Tablet-based AR technology: Impacts on students’
conceptions and approaches to learning mathematics according to their self-ecacy. British Journal of Educational
Technology 50, 1 (2019), 248–263.
[16]
Kira J Carbonneau and Scott C Marley. 2012. Activity-based learning strategies. The international guide to student
achievement (2012), 282–284.
[17]
Chih-Ming Chen and Yen-Nung Tsai. 2012. Interactive augmented reality system for enhancing library instruction in
elementary schools. Computers & Education 59, 2 (2012), 638–652.
[18]
Moon-Heum Cho and Michele L Heron. 2015. Self-regulated learning: the role of motivation, emotion, and use of
learning strategies in students’ learning experiences in a self-paced online mathematics course. Distance Education
36, 1 (2015), 80–99.
[19]
Mihaly Csikszentmihalyi and Mihaly Csikzentmihaly. 1990. Flow: The psychology of optimal experience. Vol. 1990.
Harper & Row New York.
[20]
Sébastien Cuendet, Quentin Bonnard, Son Do-Lenh, and Pierre Dillenbourg. 2013. Designing augmented reality for
the classroom. Computers & Education 68 (2013), 557–569.
[21]
Marcelo de Paiva Guimarães and Valéria Farinazzo Martins. 2014. A checklist to evaluate augmented reality applica-
tions. In 2014 XVI Symposium on Virtual and Augmented Reality. IEEE, 45–52.
[22]
Marco De Sá and Elizabeth Churchill. 2012. Mobile augmented reality: exploring design and prototyping techniques.
In Proceedings of the 14th international conference on Human-computer interaction with mobile devices and services.
221–230.
[23]
Lin Deng, Jing Tian, Christopher Cornwell, Victoria Phillips, Long Chen, and Amro Alsuwaida. 2019. Towards an
Augmented Reality-Based Mobile Math Learning Game System. In International Conference on Human-Computer
Interaction. Springer, 217–225.
[24]
Neven Drljević, Lung Hsiang Wong, and Ivica Botički. 2017. Where does my Augmented Reality Learning Experience
(ARLE) belong? A student and teacher perspective to positioning ARLEs. IEEE Transactions on Learning Technologies
10, 4 (2017), 419–435.
[25] Matt Dunleavy. 2014. Design principles for augmented reality learning. TechTrends 58, 1 (2014), 28–34.
[26]
Matt Dunleavy and Chris Dede. 2014. Augmented reality teaching and learning. Handbook of research on educational
communications and technology (2014), 735–745.
[27]
Matt Dunleavy, Chris Dede, and Rebecca Mitchell. 2009. Aordances and Limitations of Immersive Participatory
Augmented Reality Simulations for Teaching and Learning. Journal of Science Education and Technology 18, 1 (February
2009), 7–22.
[28]
Andreas Dünser, Raphaël Grasset, Hartmut Seichter, and Mark Billinghurst. 2007. Applying HCI principles to AR
systems design. (2007).
[29]
Amanda Edwards-Stewart, Tim Hoyt, and Greg Reger. 2016. Classifying dierent types of augmented reality
technology. Annual Review of CyberTherapy and Telemedicine 14 (2016), 199–202.
[30]
Tristan C Endsley, Kelly A Sprehn, Ryan M Brill, Kimberly J Ryan, Emily C Vincent, and James M Martin. 2017.
Augmented reality design heuristics: Designing for dynamic interactions. In Proceedings of the Human Factors and
Ergonomics Society Annual Meeting, Vol. 61. SAGE Publications Sage CA: Los Angeles, CA, 2100–2104.
[31]
Anne Estapa and Larysa Nadolny. 2015. The eect of an augmented reality enhanced mathematics lesson on student
achievement and motivation. Journal of STEM education 16, 3 (2015).
[32]
Min Fan, Alissa N Antle, and Jillian L Warren. 2020. Augmented reality for early language learning: A systematic review
of augmented reality application design, instructional strategies, and evaluation outcomes. Journal of Educational
Computing Research 58, 6 (2020), 1059–1100.
[33]
Minaz Fazal and Melanie Bryant. 2019. Blended learning in middle school math: The question of eectiveness. Journal
of Online Learning Research 5, 1 (2019), 49–64.
[34]
Azuka Benard Festus. 2013. Activity-based learning strategies in the mathematics classrooms. Journal of Education
and Practice 4, 13 (2013), 8–14.
[35]
Interaction Design Foundation. [n.d.]. Design Principles. Retrieved September 14, 2020 from https://www.interaction-
design.org/literature/topics/design-principles
Proc. ACM Hum.-Comput. Interact., Vol. 5, No. CSCW2, Article 461. Publication date: October 2021.
Approaches for Designing Handheld Augmented Reality Learning Experiences for Mathematics Classrooms 461:23
[36]
Bojun Gao, Q Wan, T Chang, and Ronghuai Huang. 2019. A framework of learning activity design for ow experience
in a smart learning environment. Foundations and trends in smart learning (2019), 5–14.
[37]
Ken Gilbertson, Timothy Bates, Alan Ewert, and Terry McLaughlin. 2006. Outdoor education: Methods and strategies.
Human Kinetics.
[38]
Lorenzo Giunta, Jamie O’Hare, James Gopsill, Elies Dekoninck, et al
.
2018. A review of augmented reality research
for design practice: looking to the future. DS 91: Proceedings of NordDesign 2018, Linköping, Sweden, 14th-17th August
2018 (2018).
[39]
Bayram Güzer and Hamit Caner. 2014. The past, present and future of blended learning: an in depth analysis of
literature. Procedia-social and behavioral sciences 116 (2014), 4596–4603.
[40]
Taejin Ha, Woontack Woo, Youngho Lee, Junhun Lee, Jeha Ryu, Hankyun Choi, and Kwanheng Lee. 2010. ARtalet:
tangible user interface based immersive augmented reality authoring tool for Digilog book. In 2010 International
Symposium on Ubiquitous Virtual Reality. IEEE, 40–43.
[41]
Khaled Hamdan, Nabeel Al-Qirim, and Mohammad Asmar. 2012. The eect of Smart Board on students behavior and
motivation. In 2012 International Conference on Innovations in Information Technology (IIT). IEEE, 162–166.
[42]
Prabha Hariharan and Tamil Nadu. 2011. Eectiveness of activity–based–learning methodology for elementary
school education. India: Coimbatore (2011).
[43]
Fabrício Herpich, Renan Luigi Martins Guarese, Liane Margarida Rockenbach Tarouco, et al
.
2017. A comparative
analysis of augmented reality frameworks aimed at the development of educational applications. Creative Education
8, 09 (2017), 1433.
[44]
Simon Hooper and Lloyd P Rieber. 1995. Teaching with technology. Teaching: Theory into practice 2013 (1995),
154–170.
[45]
V Hubka. 1983. Design tactics = methods + working principles for design engineers. Design Studies 4, 3 (1983),
188–195.
[46]
María-Blanca Ibáñez and Carlos Delgado-Kloos. 2018. Augmented reality for STEM learning: A systematic review.
Computers & Education 123 (2018), 109–123.
[47]
Emin İbili, Mevlüt Çat, Dmitry Resnyansky, Sami Şahin, and Mark Billinghurst. 2020. An assessment of geometry
teaching supported with augmented reality teaching materials to enhance students’ 3D geometry thinking skills.
International Journal of Mathematical Education in Science and Technology 51, 2 (2020), 224–246.
[48]
Norliza Katuk, Jieun Kim, and Hokyoung Ryu. 2013. Experience beyond knowledge: Pragmatic e-learning systems
design with learning experience. Computers in Human Behavior 29, 3 (2013), 747–758.
[49]
Navneet Kaur, Rumana Pathan, Ulfa Khwaja, Pratiti Sarkar, Balraj Rathod, and Sahana Murthy. 2018. GeoSolvAR:
Augmented reality based application for mental rotation. In 2018 IEEE Tenth International Conference on Technology
for Education (T4E). IEEE, 45–52.
[50]
Ioannis Kazanidis, George Palaigeorgiou, and Christos Bazinas. 2018. Dynamic interactive number lines for fraction
learning in a mixed reality environment. In 2018 South-Eastern European Design Automation, Computer Engineering,
Computer Networks and Society Media Conference (SEEDA_CECNSM). IEEE, 1–5.
[51]
Matthew Kearney. 2004. Classroom use of multimedia-supported predict–observe–explain tasks in a social construc-
tivist learning environment. Research in science education 34, 4 (2004), 427–453.
[52]
Tereza Gonçalves Kirner, Fernanda Maria Villela Reis, and Claudio Kirner. 2012. Development of an interactive book
with augmented reality for teaching and learning geometric shapes. In 7th Iberian Conference on Information Systems
and Technologies (CISTI 2012). IEEE, 1–6.
[53]
Veronika Krauß, Alexander Boden, Leif Oppermann, and René Reiners. 2021. Current practices, challenges, and
design implications for collaborative AR/VR application development. In Proceedings of the 2021 CHI Conference on
Human Factors in Computing Systems. 1–15.
[54]
S Li, Yihua Shen, Peiwen Wang, E Liu, and S Cai. 2016. A case study of teaching probability using augmented reality
in secondary school. In Proceedings of the 24th International Conference on Computers in Education. 340–344.
[55]
Youn-Kyung Lim, Erik Stolterman, and Josh Tenenberg. 2008. The anatomy of prototypes: Prototypes as lters,
prototypes as manifestations of design ideas. ACM Transactions on Computer-Human Interaction (TOCHI) 15, 2 (2008),
1–27.
[56]
Hao-Chiang Koong Lin, Mei-Chi Chen, and Chih-Kai Chang. 2015. Assessing the eectiveness of learning solid
geometry by using an augmented reality-assisted learning system. Interactive Learning Environments 23, 6 (2015),
799–810.
[57]
Tzung-Jin Lin, Henry Been-Lirn Duh, Nai Li, Hung-Yuan Wang, and Chin-Chung Tsai. 2013. An investigation
of learners’ collaborative knowledge construction performances and behavior patterns in an augmented reality
simulation system. Computers & Education 68 (2013), 314–321.
[58]
Enrui Liu, Yutan Li, Su Cai, and Xiaowen Li. 2018. The eect of augmented reality in solid geometry class on students’
learning performance and attitudes. In International Conference on Remote Engineering and Virtual Instrumentation.
Proc. ACM Hum.-Comput. Interact., Vol. 5, No. CSCW2, Article 461. Publication date: October 2021.
461:24 Pratiti Sarkar and Jayesh S. Pillai
Springer, 549–558.
[59]
Blair MacIntyre, Maribeth Gandy, Steven Dow, and Jay David Bolter. 2004. DART: a toolkit for rapid design exploration
of augmented reality experiences. In Proceedings of the 17th annual ACM symposium on User interface software and
technology. 197–206.
[60]
Emily Marshman, Seth DeVore, and Chandralekha Singh. 2020. Holistic framework to help students learn eectively
from research-validated self-paced learning tools. Physical Review Physics Education Research 16, 2 (2020), 020108.
[61] Robert J Marzano. 1992. A dierent kind of classroom: Teaching with dimensions of learning. ERIC.
[62]
Douglas Miller and Tonia Dousay. 2015. Implementing augmented reality in the classroom. Issues and Trends in
Educational Technology 3, 2 (2015).
[63] Michael G Moore. 1989. Three types of interaction. (1989).
[64]
Roberta Cabral Mota, Rafael Alves Roberto, and Veronica Teichrieb. 2015. [poster] authoring tools in augmented
reality: An analysis and classication of content design tools. In 2015 IEEE International Symposium on Mixed and
Augmented Reality. IEEE, 164–167.
[65]
Michael Nebeling and Katy Madier. 2019. 360proto: Making Interactive Virtual Reality & Augmented Reality Prototypes
from Paper. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems. 1–13.
[66]
Michael Nebeling, Janet Nebeling, Ao Yu, and Rob Rumble. 2018. Protoar: Rapid physical-digital prototyping of
mobile augmented reality applications. In Proceedings of the 2018 CHI Conference on Human Factors in Computing
Systems. 1–12.
[67]
Prema Nedungadi, Akshay Jayakumar, and Raghu Raman. 2014. Low cost tablet enhanced pedagogy for early grade
reading: Indian context. In 2014 IEEE Region 10 Humanitarian Technology Conference (R10 HTC). 35–39. https:
//doi.org/10.1109/R10-HTC.2014.7026322
[68]
Jean-Marie Normand, Myriam Servières, and Guillaume Moreau. 2012. A new typology of augmented reality
applications. In Proceedings of the 3rd Augmented Human International Conference. 1–8.
[69]
Duygu ÖZDEMİR and Bilal ÖZÇAKIR. 2019. An Analysis of The Eects of Augmented Reality Activities in Teaching
Fractions on 5th Grade Students’ Math Achievement and Attitudes. (2019).
[70]
Janne Paavilainen, Hannu Korhonen, Kati Alha, Jaakko Stenros, Elina Koskinen, and Frans Mayra. 2017. The Pokémon
GO experience: A location-based augmented reality mobile game goes mainstream. In Proceedings of the 2017 CHI
conference on human factors in computing systems. 2493–2498.
[71]
George Palaigeorgiou, Xristina Tsolopani, Soa Liakou, and Charalambos Lemonidis. 2018. Movable, Resizable
and Dynamic Number Lines for Fraction Learning in a Mixed Reality Environment. In International Conference on
Interactive Collaborative Learning. Springer, 118–129.
[72]
Ivan Permozer and Tihomir Orehovački. 2019. Utilizing Apple’s ARKit 2.0 for Augmented Reality Application
Development. In 2019 42nd International Convention on Information and Communication Technology, Electronics and
Microelectronics (MIPRO). IEEE, 1629–1634.
[73]
Elizabeth Lewis Pourciau. 2014. Teaching and learning with smart board technology in middle school classrooms.
(2014).
[74]
Simon Priest. 1986. Redening outdoor education: A matter of many relationships. The Journal of environmental
education 17, 3 (1986), 13–15.
[75]
Iulian Radu. 2014. Augmented reality in education: a meta-review and cross-media analysis. Personal and Ubiquitous
Computing 18, 6 (2014), 1533–1543.
[76]
Iulian Radu and Alissa Antle. 2017. Embodied learning mechanics and their relationship to usability of handheld
augmented reality. In 2017 IEEE Virtual Reality Workshop on K-12 Embodied Learning through Virtual & Augmented
Reality (KELVAR). IEEE, 1–5.
[77]
Iulian Radu, Ellen Doherty, Kristin DiQuollo, Betsy McCarthy, and Michelle Tiu. 2015. Cyberchase shape quest:
pushing geometry education boundaries with augmented reality. In Proceedings of the 14th international conference on
interaction design and children. 430–433.
[78]
Iulian Radu, Blair MacIntyre, and Stella Lourenco. 2016. Comparing Children’s Crosshair and Finger Interactions in
Handheld Augmented Reality: Relationships Between Usability and Child Development. In Proceedings of the The
15th International Conference on Interaction Design and Children. 288–298.
[79]
Raghu Raman, Hardik Vachhrajani, Avinash Shivdas, and Prema Nedungadi. 2014. Low cost tablets as disruptive
educational innovation: modeling its diusion within Indian K12 system. In 2014 IEEE Innovations in Technology
Conference. 1–5. https://doi.org/10.1109/InnoTek.2014.7137053
[80]
Jeremy Roschelle, William Penuel, and Nicole Shechtman. 2006. Co-design of innovations with teachers: Denition
and dynamics. (2006).
[81]
Mamta Roy, Regina Giraldo-Garcia, Anup Sam Mathew, Ursula Matias, and Indraneel Bommisetty. 2016. Emerging
Technologies for Face-to-face and online teachers: Use of Tablets. In EdMedia+ Innovate Learning. Association for the
Advancement of Computing in Education (AACE), 1814–1819.
Proc. ACM Hum.-Comput. Interact., Vol. 5, No. CSCW2, Article 461. Publication date: October 2021.
Approaches for Designing Handheld Augmented Reality Learning Experiences for Mathematics Classrooms 461:25
[82]
Elizabeth B-N Sanders and Pieter Jan Stappers. 2008. Co-creation and the new landscapes of design. Co-design 4, 1
(2008), 5–18.
[83] Judith Haymore Sandholtz et al. 1997. Teaching with technology: Creating student-centered classrooms. ERIC.
[84]
Marc Ericson C Santos, Angie Chen, Takafumi Taketomi, Goshiro Yamamoto, Jun Miyazaki, and Hirokazu Kato. 2013.
Augmented reality learning experiences: Survey of prototype design and evaluation. IEEE Transactions on learning
technologies 7, 1 (2013), 38–56.
[85]
Marc Ericson C Santos, Takafumi Taketomi, Goshiro Yamamoto, Ma Mercedes T Rodrigo, Christian Sandor, and
Hirokazu Kato. 2015. Toward guidelines for designing handheld augmented reality in learning support. In Proceedings
of the 23rd international conference on computers in education. china: Asia-pacic society for computers in education.
Citeseer.
[86]
Pratiti Sarkar, Kapil Kadam, and Jayesh S Pillai. 2019. Collaborative approaches to problem-solving on lines and
angles using augmented reality. In 2019 IEEE Tenth International Conference on Technology for Education (T4E). IEEE,
193–200.
[87]
Pratiti Sarkar, Kapil Kadam,and Jayesh S Pillai. 2020. Learners’ approaches, motivation and patterns of problem-solving
on lines and angles in geometry using augmented reality. Smart Learning Environments 7, 1 (2020), 1–23.
[88]
Pratiti Sarkar and Jayesh S Pillai. 2019. User Expectations of augmented reality experience in indian school education.
In Research into Design for a Connected World. Springer, 745–755.
[89]
Pratiti Sarkar, Jayesh S Pillai, and Ankita Gupta. 2018. ScholAR: a collaborative learning experience for rural schools
using Augmented Reality application. In 2018 IEEE Tenth International Conference on Technology for Education (T4E).
IEEE, 8–15.
[90]
Pratiti SARKAR, Prabodh SAKHARDANDE, Utsav OZAb, and Jayesh PILLAI. 2019. Study of Augmented Reality
Interaction Mediums (AIMs) towards Collaboratively Solving Open-Ended Problems. 1 (2019), 472–477.
[91]
Lamia Soussi, Zeena Spijkerman, and Slinger Jansen. 2016. A case study of the health of an augmented reality software
ecosystem: Vuforia. In International Conference of Software Business. Springer, 145–152.
[92] Heather Staker and Michael B Horn. 2012. Classifying K-12 blended learning. Innosight Institute (2012).
[93]
Patricia Steele, Cheryl Burleigh, Margaret Kroposki, Myrene Magabo, and Liston Bailey. 2020. Ethical Considerations
in Designing Virtual and Augmented Reality Products—Virtual and Augmented Reality Design With Students in
Mind: Designers’ Perceptions. Journal of Educational Technology Systems 49, 2 (2020), 219–238.
[94] David R Thomas. 2003. A general inductive approach for qualitative data analysis. (2003).
[95]
Mike Tissenbaum, Michelle Lui, and James D Slotta. 2012. Co-Designing Collaborative Smart Classroom Curriculum
for Secondary School Science. J. Univers. Comput. Sci. 18, 3 (2012), 327–352.
[96]
Hendrys Tobar-Muñoz, Silvia Baldiris, and Ramon Fabregat. 2016. Co design of augmented reality game-based
learning games with teachers using co-CreaARGBL method. In 2016 IEEE 16th International Conference on Advanced
Learning Technologies (ICALT). IEEE, 120–122.
[97] IBE UNESCO. 2013. UNESCO International Bureau of Education glossary of curriculum terminology.
[98]
Rekha Verma and Atul Razdan. 2019. Role of tablets as mood elevators in the perception towards green schools: An
exploratory research on the students of green schools in Gujarat. In Optimizing Millennial Consumer Engagement
With Mood Analysis. IGI Global, 69–97.
[99]
Ana Villanueva, Zhengzhe Zhu, Ziyi Liu, Kylie Peppler, Thomas Redick, and Karthik Ramani. 2020. Meta-AR-app: an
authoring platform for collaborative augmented reality in STEM classrooms. In Proceedings of the 2020 CHI conference
on human factors in computing systems. 1–14.
[100]
Brian Wattchow and Mike Brown. 2011. A pedagogy of place: Outdoor education for a changing world. Monash
University Publishing.
[101]
Hsin-Kai Wu, Silvia Wen-Yu Lee, Hsin-Yi Chang, and Jyh-Chong Liang. 2013. Current status, opportunities and
challenges of augmented reality in education. Computers & education 62 (2013), 41–49.
Received April 2021; accepted July 2021
Proc. ACM Hum.-Comput. Interact., Vol. 5, No. CSCW2, Article 461. Publication date: October 2021.
ResearchGate has not been able to resolve any citations for this publication.
Article
Full-text available
With limited time available in the classroom, e-learning tools can supplement in-class learning by providing opportunities for students to study and learn outside of class. Such tools can be especially helpful for students who lack adequate prior preparation. However, one critical issue is ensuring that students, especially those in need of additional help, engage with the tools as intended. Here we first discuss an empirical investigation in which students in a large algebra-based physics course were given opportunities to work through research-validated tutorials outside of class as self-study tools. Students were provided these optional tutorials after traditional instruction in relevant topics and were then given quizzes that included problems that were identical to the tutorial problems with regard to the physics principles involved but had different contexts. We find that students who worked through the tutorials as self-study tools struggled to transfer their learning to solve problems that used the same physics principles. On the other hand, students who worked on the tutorials in supervised, one-on-one situations performed significantly better than them. These empirical findings suggest that many introductory physics students may not engage effectively with self-paced learning tools unless they are provided additional incentives and support, e.g., to aid with self-regulation. Inspired by the empirical findings, we propose a holistic theoretical framework to help create learning environments in which students with diverse backgrounds are provided support to engage effectively with self-study tools.
Article
Full-text available
Developers and designers of virtual and augmented reality (VR/AR) products are expressing concerns regarding accountability for ethical design and use of VR/AR products in virtual learning environments. Within the field of education, more research is needed to determine how VR/AR designers make decisions regarding ethical issues, and particularly when integrating media into learning content. The purpose of the qualitative inquiry study was to interview designers/developers of VR/AR products regarding their perceptions of ethics in design and use of VR/AR products designed for educational purposes. Data collection was achieved through a sample of self-described instructional designers and developers from the Association for Educational Communications and Technology membership. Through qualitative inquiry with one-on-one interviews, designers shared their stories about their perceptions of ethics in the design and development of VR/AR products for educational purposes.
Article
Full-text available
Abstract There are several concepts in 2D Geometry that require understanding their application in the real practical world. However, in classrooms, such concepts are often taught without the analysis of the learners’ realization and interpretation of the existing concepts around them, in their surroundings. For this purpose, an Augmented Reality (AR) based module for the 7th and 8th grade syllabus has been designed to encourage the active participation of the learners in the classroom while learning the concept of Lines and Angles. It comprises three AR learning activities that enable the participants to recall, visualize, and identify the type of angle and then mark it by drawing on the augmented 3D house. Before conducting the main studies, a pilot study was conducted with 6 students of 8th grade. This helped in validating the data instruments, timing, and execution of the research study. The first study was conducted with 21 students of 8th grade where 12 participants performed the AR learning activities in dyads and 9 participants performed individually. Their perspectives, approaches, and motivation in performing the AR learning activities have been reported. Findings from the study showed that the majority i.e. 90.4% participants preferred to perform the AR learning activities in dyads than individually. Though the usability score was higher for the participants who performed the AR learning activities individually (M = 70.28) as compared to dyads (M = 65.23), there was no significant difference in the motivation scores between the participants of the two groups. In the second study, 28 students of 7th grade were divided into dyads and their behavior patterns of performing the AR learning activities have been reported. Using Lag Sequential Analysis, significant sequences were obtained based on the behaviors belonging to three categories of peer involvement, teacher prompts and AR interactions. It was found that the designed AR learning activities encouraged the participants to discuss the concepts with peers, enhanced their immersive experience as they together moved around and inside the house to find and identify the angles.
Conference Paper
Full-text available
Open-ended problem solving involves multiple approaches in solving a problem. This can help students to think divergently to relate and apply their classroom learnings in real-life examples. At the same time, through active collaboration, students get to exchange and enhance their knowledge, thus increasing productivity beyond that of an individual. The aim of our study was to develop a collaborative open-ended learning environment using Augmented Reality Interaction Mediums (AIMs) as scaffolds. We conducted a study in a classroom with 12 students of 7th grade who collaboratively used different AIMs to solve certain open-ended problems based on their Mathematics syllabus. We observed their interactions and performance with AIMs as compared to the controlled treatment for each task. Further, we evaluated the creativity through divergent thinking scores using the parameters of fluency, flexibility and originality, where the experimental groups using different AIMs had better creativity score (M=86.3) as compared to the control group (M=79). Thus, a collaborative open-ended approach using AIMs as scaffold can be explored further in improving creative problem solving.
Conference Paper
Augmented/Virtual Reality (AR/VR) is still a fragmented space to design for due to the rapidly evolving hardware, the interdisciplinarity of teams, and a lack of standards and best practices. We interviewed 26 professional AR/VR designers and developers to shed light on their tasks, approaches, tools, and challenges. Based on their work and the artifacts they generated, we found that AR/VR application creators fulfill four roles: concept developers, interaction designers , content authors, and technical developers. One person often incorporates multiple roles and faces a variety of challenges during the design process from the initial contextual analysis to the deployment. From analysis of their tool sets, methods, and artifacts, we describe critical key challenges. Finally, we discuss the importance of prototyping for the communication in AR/VR development teams and highlight design implications for future tools to create a more usable AR/VR tool chain. CCS CONCEPTS • Software and its engineering → Collaboration in software development; • Human-centered computing → Human computer interaction (HCI); Interaction techniques.
Chapter
A green school basically integrates nature into school (mainly through academics, operations, and student/teacher and community engagement) with incorporated natural substance to school educational module. The sole purpose of green schools is to inculcate healthy and nature friendly initiatives with integrated environmental course content in school curriculum. Research shows that environmental training and education might enhance a normal learner's classroom execution and diversified impact on individual's personality as environmental knowledge can make ordinary learners extraordinary. Green schools aim at decreasing the drop-out rate in schools by introducing environmental education as an interesting subject with aspects of learning by doing. Students of Class 6th, 7th, and 8th standard use tabs/tablets for submitting their assignments, tests, and quiz/assessment exams enabling them to be tech-savvy generation. This research will address this issue through a qualitative research and in-depth interviews of students of different green schools of Gujarat.
Article
In this article, we present a systematic review of literature on augmented reality (AR) supported for early language learning. We analyzed a total of 53 papers from 2010 to 2019 using qualitative analysis with complementary descriptive quantitative analysis. Our findings revealed three main AR learning activities: word spelling games, word knowledge activities, and location-based word activities. Our findings also uncovered five main design strategies: three-dimensional multimedia content, hands-on interaction with physical learning materials, gamification, spatial mappings, and location-based features. Several combinations of design and instructional strategies tended to be effective: Learning gains were enhanced by using three-dimensional multimedia with advanced organizers (presentation strategy) and/or using location-based content with learners’ self-exploration (discovery strategy); and motivation was enhanced by using game mechanisms with discovery strategy. We suggest that future designers of AR early language applications should move beyond these basic approaches and consider how unique benefits of AR may be applied to support key activities in early language learning while also considering how to support sociotechnical factors such as collaboration between teachers and learners and different learning contexts. We conclude with a discussion of future directions for research in this emerging space.