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Interactive Learning Environments
ISSN: 1049-4820 (Print) 1744-5191 (Online) Journal homepage: https://www.tandfonline.com/loi/nile20
Design implications for adaptive augmented
reality based interactive learning environment for improved concept comprehension in engineering paradigms
Deepti Prit Kaur, Archana Mantri & Ben Horan
To cite this article: Deepti Prit Kaur, Archana Mantri & Ben Horan (2019): Design implications for adaptive augmented reality based interactive learning environment for improved
concept comprehension in engineering paradigms, Interactive Learning Environments, DOI:
10.1080/10494820.2019.1674885
To link to this article: https://doi.org/10.1080/10494820.2019.1674885
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Design implications for adaptive augmented reality based interactive learning environment for improved concept comprehension in engineering paradigms
Deepti Prit Kaur a, Archana Mantriaand Ben Horanb
aChitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India;bSchool of Engineering, Deakin University, Geelong, Australia
ABSTRACT
Augmented reality (AR) has tremendous potential as a teaching and learning tool in engineering education to enhance students’ learning experience; it influences the students’ spatial ability for real-time visualization. Furthermore, this helps to attain better concept comprehension pertaining to improved understanding of the topics. The present study provides evidence by developing an AR learning environment (ARLE) suitable for complicated theoretical topics of electronics engineering, which otherwise cannot be demonstrated using practical experiments. The idea of using different design variants; such as mobile and table-top for adaptive AR is also implemented. For this, 60 undergraduate students of electronics and electrical engineering were introduced to the ARLE system, in two different case studies. The first case validates the efficacy of using AR for learning the concept of stability in linear control systems through a questionnaire based survey where students reported the ARLE as an effective learning system for theoretical topics. Second case study provides comparative analysis for usability of two design variants of the ARLE in terms of manipulability and comprehensibility. Finally, the design implications for developed ARLE are discussed, which may be helpful for other researchers in creating learning environments for different courses of engineering education.
ARTICLE HISTORY Received 7 January 2019 Accepted 20 September 2019 KEYWORDS
Adaptive augmented reality;
interactive learning; mobile AR; table-top AR; design implication; concept comprehension
1. Introduction
Researchers aim to improvise students’spatial and cognitive skills by incorporating new techniques to enhance the learning, motivation, and degree of satisfaction of students. Previous studies (Contero, Naya, Company, Saorín, & Conesa,2005;Ćukovićet al.,2013; Cukovic, Devedzic, Ghionea, Fiorentino, & Subburaj,2016; Gutiérrez, Navarro, & González,2011; Kozhevnikov & Thornton,2006) have shown a correlation between students’spatial skills and understanding of the complicated con- cepts of science, technology, and education, such as force and motion laws in physics and engineer- ing graphics. Spatial skills are one’s ability to visualize the concepts and analogies for understanding the fundamentals with minimum mental work. Many students cannot apply concepts in practical ways despite having appropriate theoretical knowledge because they might have less or different visualization for a particular topic or find it difficult to understand the content using traditional instruction methods. Therefore, focusing on methods that improve the concept comprehension of learners and bring each concept for them to nearly equal level while learning in a classroom are
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Supplemental data for this article can be accessed athttps://doi.org/10.1080/10494820.2019.1674885.
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important, even if they acquire different visualizations or spatial abilities. Education technology has ensured timely improvement in instructional practices, such as the use of the Internet, multimedia simulations, educational games, and immersive technologies, including augmented reality (AR) and virtual reality (VR). AR is a type of technology that has benefitted every area of education, whether in primary school (Efstathiou, Kyza, & Georgiou, 2018), K-12 education (Santos et al., 2014a; Wu, Hwang, Yang, & Chen, 2018), engineering (Chen, Liu, Cheng, & Huang, 2017), or medical education (Herron, 2016; Sutherland, Hashtrudi-Zaad, Sellens, Abolmaesumi, & Mousavi, 2013). Thefield of engineering education highlights the conceptual models and designs; particularly, thefield of electronics is considered even more abstract than any other discipline of engineering (Smith,2009), thereby requiring high spatial visualization in students. Using AR, a computer-gener- ated rich multimedia, can be amalgamated into real-world data (Azuma,1997) to enhance user per- ception of creating an influence on his spatial and cognitive skills (Martín-Gutiérrez et al., 2013;
Slijepcevic,2013). Although many researchers have used AR to improve the understanding of elec- tronics engineering students with regard to courses in fundamentals of basic electronics and embedded systems by allowing them to solve laboratory experiments through visualization (Anastas- sova et al.,2014; Odeh, Abu Shanab, Anabtawi, & Hodrob,2013), the need for conceptual understand- ing of theoretical topics using AR still remains unexplored. These topics/courses are neither demonstrated using laboratory experiments nor explained using simulations in CG space (here, CG space refers to Computer Generated imagery). Moreover, majority of the present systems that implement AR usefixed predefined methods (Drljević, Wong, & Botički,2017), which emphasize prac- tical approach and are notflexible as per user requirements, thereby affecting students with different spatial abilities. The primary purpose of this study is to answer the following research questions:
. Is there an available framework that uses AR as an instructional tool for teaching theoretical topics and useful for students in their concept building in engineering education?
. How effective is the performance of AR as a learning tool on the student motivation and satisfac- tion with use of technology when compared with other instructional treatments?
. Is there any difference in the usability of the AR based environment for different design approaches viz. Mobile and Table-top from learner’s perspective?
In this study, an adaptive AR-based dual approach (Ghouaiel, Cieutat, & Jessel,2014) is presented to improve the comprehension of students in thefield of control theory by developing an interactive learning environment in two different variants. The topic of stability analysis for linear control system has been chosen as an example for implementation using the designed AR learning environ- ment (ARLE). On the basis of the reviewed literature, AR implementation has never been considered for this topic; however, one study (Andujar, Mejías, & Márquez,2011) has mentioned the usefulness of their approach for control engineering and robotics. An adaptive ARLE is developed, considering theflexibility of system according to user requirements because learners can use either of the two approaches for common settings of the system. One approach is based on mobile AR, which uses a tablet or mobile phone as the display device for interactive augmented information and uses computer vision method in tracking real-time targets to provide user augmentation. Another method is a tabletop with afixed camera and vision tracking for real-time object targets where users can interact with the real environment and the augmented space simultaneously. This method uses a desktop/laptop screen to display the augmented information. In the present work, the AR system was validated using a group of 28 undergraduate students of electronics and electrical engineering by conducting a questionnaire- based survey tofind the determinants of using ARLE for concept comprehension and understanding control theory fundamentals. In this study, the developed system was validated through implemen- tation while emphasizing a user feedback with regard to student motivation, usability of ARLE, and satisfaction on the use of technology. The response thus obtained, was used for improvement in the existing system and two different variants with same user interface were designed suitable for mobile and table-top applications. These adaptive system was then presented to another set of
32 students from electronics and electrical engineering, and the two approaches were compared using manipulability and comprehensibility statements from the HARUS (Handheld Augmented Reality Usability Scale) given by Santos et al. (2014b). This study established the usability of both the design variants for different applications. The paper is organized as follows. Section 2 provides a background for the use of AR in education, training, and improvement of spatial skills for engineering students.
Section 3 provides the design parameters and implementation of ARLE. Section 4 presents the results of the survey for both the case studies and discussion on usability of different design variants of the ARLE. Finally, Section 5 concludes the study and discusses future works.
2. AR, education, and spatial ability: background
AR is a technology wherein overlaying of virtual data on a real identified scene is done using com- puters (Azuma,1997). This provides the user an access to additional meaningful rich and relevant multimedia which is available immediately (Bower, Howe, McCredie, Robinson, & Grover,2014). AR in educational paradigms provides a real-time learning experience, considering that the sense of being in the physical world is not removed from the user. Azuma (1997) reported that AR possesses three unique properties, that is, combines real and virtual worlds, interactive in real-time, and regis- tered in 3D. These properties make AR a viable tool in giving instructions because it is different from VR, where users are fully immersed in a synthetic environment (Milgram & Kishino,1994). In the lit- erature, thefield of AR reveals numerous constructs for consideration while discussing AR in edu- cational context. As reviewed from a recent paper (Chen et al.,2017), the use of AR in education has considerably increased since 2013, with various methods differing in cognitive process, user inter- action, tracking methods, classroom design and evaluation process, content development, and target users. The affordances (Santos et al.,2014a) of AR include real-world annotations and contextual and vision haptic visualization. These affordances or the actionable properties (Zhou, Duh, & Billinghurst, 2008) of AR enhance users’learning by affecting their motivation and support for cognitive process, spatial ability, and satisfaction for the use of technology, thereby further improving experiential and collaborative learning (Di Serio, Ibáñez, & Kloos,2013).Table 1presents few examples of using AR in educational paradigms, including review of studies for instrumentation, neuroscience, engineering drawing, construction and civil engineering, digital design, mechanical engineering, and optics.
The considerablefindings from the reviewed articles for last 10 years (2010–2019) are mentioned along with the AR treatment in education performed on a specific sample group.
The reviewed literature suggests that AR has been extensively used to address students’difficul- ties in learning various sciences and engineering concepts through interactive visualization. Labora- tory experimentation has been the main focus for the understanding and manipulation of electrical circuits (Ibáñez, Di Serio, Villarán-Molina, & Delgado-Kloos,2015; Noorasura & Sazilah,2011) and over- laying of 3D models to help understand mechanical and civil engineering concepts, such as engin- eering drawing (Camba & Contero, 2013; Gutierrez & Fernandez, 2014; Shirazi & Behzadan,2015).
Few studies have indicated the settings of remote laboratories that used AR (Andujar et al.,2011;
Mejías Borrero & Andújar Márquez,2012) for teaching the concepts of digital system design. A table- top AR approach called ARVita was presented (Dong, Behzadan, Chen, & Kamat,2013) for collabora- tive visualization of computer-generated models, which are useful for dynamic 3D simulated construction operations for engineering processes. As thefield of AR attracts new researchers, four undergraduate courses, namely, digital design, multimedia production, information system, and com- puter science, have been surveyed for their interest in the development of AR systems (Souza-Con- cilio & Pacheco,2013). The results showed considerable motivation and interest of participants in the development of AR systems in games and entertainmentfields. These studies aim to contribute new way of teaching practices to improve students’learning while keeping the realistic sensation alive for the users by incorporating AR in educational settings. AR-based training can aid students with low spatial ability to perform as good as those with high spatial ability. However, focus lacks on various investigating factors such as uses, advantages, limitations, effectiveness, challenges, features,
Table 1.Ten years of AR in educational paradigms.
Area/Topic of
implementation Sample AR treatment Findings Resource
Kinematics N= 40 (Secondary 3 students) Country = Singapore
AR for teaching and learning of Science by using software that was affordable, powerful and was locally developed in the University of Singapore.
Enhancement in the understanding of students for the concept of kinematics graphs.
Positive effect on students’learning and thus, their academic achievements.
IEEE ICETC (Jerry & Aaron, 2010)
Instrumentation N= 55 (first-year engineering students) Country = Malaysia
AR mobile learning for visualization and manipulation of basic circuit components
Reciprocal teaching applied to help students for improved comprehension of circuits
IEEE ICCSAE (Noorasura &
Sazilah,2011)
Digital systems N= 36 students and 10 teachers (first- and second-year of engineering) Country = Spain
An augmented remote laboratory for industrial and computer engineering students
Students interact with actual and augmented laboratories for practical experience
IEEE Transactions on Education (Andujar et al.,2011)
Industrial Engineering
N= 27 (first-year engineering students) Country = Spain
Use of an AR based exercise book, with embeddedfiducials.
Students were able to manipulate and interact with the virtual content for all exercises
Positive effect on spatial ability of students. An evaluation and satisfaction questionnaire was also submitted by the participants.
IEEE Frontiers in Education Conference (Contero, Gomis, Naya, Albert, & Martin- Gutierrez,2012)
Engineering
drawing N= 60 (first-year engineering students) Country = Texas, USA
AR incorporated to generate the content for graphics materials in engineering design
A desktop AR system, consisting of black and white markers; 3D models overlaid on marker detection
IEEE Frontiers in Education Conference (Camba & Contero, 2013)
Neuroscience education
N= 28 (graduate students from Stanford University) Country = California, USA
A tangible user interface using AR to explain the visual system of the human brain
The students learn about information processing in visual system using two different approaches, namely, Table to Text and Text to Table
IEEE Transactions on Learning Technologies (Schneider, Wallace, Blikstein, & Pea,2013)
Electronics Evaluation not done AR used to set up a remote engineering laboratory for teaching electronics
Live streaming of videos is performed from remote laboratories, and students can perform experiment from distant locations
International Journal of Online Engineering (Odeh et al.,2013)
Embedded systems
Evaluation not done A multisensory AR system for embedded electronics courses
A camera captures the video of a circuit board and displays it on a touch-screen, where the students can access specific board components and see relevant virtual content
ACSIS, Proceedings of the E2LP Workshop, 2014 (Anastassova et al., 2014)
Mechanical
engineering N= 47 (first-year students of mechanical engineering) Country = Spain
An augmented book called L-ELIRA is used as a marker for overlaying virtual models using AR to learn standard elements of mechanical engineering
An innovative AR system for students, in which effectiveness, efficiency, and satisfaction of using AR technology alongside traditional teaching is explored
International Journal of Engineering Education (Gutierrez & Fernandez, 2014)
Electrical fundamentals
N= 40 (ninth-grade students) Country = Spain
A simulation tool called AR-SaBEr is used to make the students discover the basic principles of electricity
Tool used on Android- based tablets, has activities to enhance student learning and motivation
IEEE Transactions on Education (Ibáñez et al., 2015)
Building design
and assembly N= 241 (students of civil,
An AR-based pedagogical tool to motivate the
Design and assembly of 3D models on mobile devices
Journal of Advances in Engineering Education
(Continued)
and affordances of AR in educational settings. Furthermore, the reviewed literature from Table 1 suggests that although few studies have been performed in the field of electronics (Anastassova et al., 2014; Odeh et al., 2013), their efficacy has not been validated. Thus, a tangible AR-based user interface is designed and implemented in the present study to address the issue of improving concept comprehension for engineering educational settings.
3. Design and implementation of ARLE
The development of an AR-based system depends on various design factors, including the inte- gration of software and hardware, with the AR system being capable of 3D registration, tracking, interaction, and display (Zhou et al., 2008). The identification of real environment, which is also called tracking, is the most important aspect of any AR system (Kaur & Mantri, 2015). Tracking in an AR environment can be performed with or without markers (fiducials). In the case of marker- based tracking, the AR system should be able to track or identify some predefined image/object targets to augment the real environment. In contrast, marker-less tracking involves the identification of certain features from the real environment to achieve augmentation.
The marker-based AR is chosen in the present study, where images in the form of markers can be detected using a device camera, and used as location for placement of the virtual data after being identified. The learning system has been designed on the spatial contiguity principle of multimedia learning (Mayer,2001), which states that learning of the students is better when corresponding words and pictures are presented on the display screen simultaneously. According to Do and Lee (2009) and Camba, Contero, and Herranz (2014), by using the markers like LEGO pieces, a user can interact with the real scene by changing the location of markers or simply by handling them. This feature adds an advantage to the use of AR for education by involving the learners to perform some task resulting in enhanced output providing them deeper insight into the learning materials. Usually markers are black and white, indicating 2-dimensional barcodes. But sometimes, if there are different colors and their contrast is not properly recognizable, it is not possible for a marker to be identified by a camera. To cater to such situation, the addition of Vumarks (image tracking feature of Vuforia) ensures the improved target identification.
The development of an AR system requires hardware (e.g. mobile/desktop/camera) and software [e.g. unity 3D/AR-SDK (such as Vuforia) and EasyAR/graphic generation tools (such as Autodesk
Table 1.Continued.
Area/Topic of
implementation Sample AR treatment Findings Resource
environmental, and construction engineering) Country = Florida, USA
students for learning abstract construction and civil engineering topics
for construction and civil engineering;
improvement in learning and collaborative skills
(Shirazi & Behzadan, 2015)
Refraction of light
N= 20 (10 randomly selected dyads) Country = Korea
AR-based environment for a science museum using game-based and non-game simulations
Visitors learn the propagation of incident and refracted light at boundary of physical media to explore the effect of different orders of AR simulations
IEEE Transactions on Learning Technologies (Oh, So, & Gaydos, 2018)
Sewing
Workshop N= 46
(Freshmen students) Location = Hong Kong
AR videos were used to provide to students for improved learning performance and satisfying learning experience in sewing tasks.
The students were able to have similar perception and took less time to perform the tasks through the use of AR videos in comparison to those who learnt using handouts.
Computers and Education, (Yip, Wong, Yick, Chan, & Wong, 2019)
Maya)]. In addition, interaction, registration, and display are important in the development of AR systems.Figure 1presents the key requirements in the development of an AR-based system.
While designing an AR-based system for educational settings, selection of an appropriate environ- ment can be made either from mobile/handheld or tabletop/desktop, thereby contributing towards interactive learning. An AR system developed for engineering drawing discusses and compares three approaches, namely, desktop and mobile AR and 3D viewer (Camba et al.,2014). The results of the study predicted that the use of mobile- or tablet-based approach is suitable for a better AR experi- ence with few participants opting for desktop-based AR. For an AR application, the hardware dictates the computing power, physical interface, and the type of display and input that can be accommo- dated (Santos et al., 2014a). Furthermore, software design is about maximizing the computing power of hardware, as well as managing content display and handling user inputs. The unique aspects of real-time tracking and 3D rendering are mostly achieved using open-source or commercial AR libraries, such as ARToolKit. To achieve tracking using computer vision, MATLAB can also be used with its computer vision toolbox. Moreover, Unity 3D tools are used to design AR-based applications.
The content-related issues involve instructional design, authoring tools, and content management tools. Instructional design is largely affected by the authoring tools available. Authoring tools are interfaces that allow a teacher to create a learning experience and select and load virtual information on a real environment. Content management tools are tools that handle the content from storage to delivery to the device. Examples of such tools include Vuforia database for virtual content storage and Maya 3D for virtual content creation. Table 2presents the various parameters considered for the development of present learning environment using AR, focussing on the design implications of present study with respect to hardware, software, and other factors, such as instructional design and content management. The implementation of designed framework has been conducted to improve students’learning through interactive visualization of the complex issues through incorpor- ating AR techniques for teaching electronics (Kaur, Mantri, & Horan,2018).
The design uses two different variants of Unity application, namely, mobile and tabletop, devel- oped to analyze the stability of linear control systems. The application aims to aid learners achieve similar perception for a particular concept even if they have different spatial visualization abilities.
Particularly, the pole-zero plot in the s-plane is utilized to obtain a decision on available cases as stable, unstable, or neutral system, according to the location of poles on the plot. The ARLE can be implemented for other topics of stability analysis of control systems in frequency domain using Nyquist plot, Polar plot, Bode plot etc. by including appropriate virtual content for specifically designed markers. Figure 2 presents the s-plane containing poles and zeroes, with two poles in the left half of the s-plane, which indicates that the system is a second-order stable system.
3.1. Mobile variant of ARLE
The mobile-based variant of ARLE has been implemented as an Android application (.apk) for mobile phones/tablets, with Vuforia used as an SDK to help in the tracking of image targets and in managing
Figure 1.Requirements of an AR system.
virtual content for augmentation. The addition of Vumarks (image tracking feature of Vuforia) ensures the improved target identification.Figure 3presents the s-plane graph with added Vumark as the marker or image target, a square with a length of side 11.5 cm.
User interface for interaction in virtual/augmented space of the system is provided in the form of virtual buttons with labeled specifications. It consists of system response waveforms and other system properties, such as oscillation frequency and system stability. A total of six different cases (three each for simple and complex pole systems) are added to the system database for stability analysis of linear control system. Furthermore,Figure 4shows one example in a system functional block diagram, where users can interact with the virtual information by clicking the graphical data to obtain details on the concept. For this application, the users must follow the steps shown in Figure 5.
Table 2.Design implications for present AR-based learning environment.
Design
factor Role
Parameters addressed
Present design
Mobile-based variant Tabletop-based variant Hardware To provide the physical interface,
input, and display of augmented information
Physical interface Mobile phone or tablet Tabletop with afixed camera for scene capturing Display Mobile/tablet screen for
showing the augmented information
Desktop/laptop screen for showing the augmented information
Input Through mobile/tablet
camera
Throughfixed camera and light-dependent sensors Real environment Static graphs in the form
of markers
Static graphs and movable poles in the form of markers
Software To maximize hardware computing power, manage the display of virtual content, and handle user inputs
Scripting and handling user inputs
Unity 3D gaming/
scripting tool for scene design
Unity 3D gaming/scripting tool
SDK Vuforia EasyAR
Tracking Vision based Vision based / Hybrid
Others To provide instructional design, authoring, and content management tools
Virtual content Static and dynamic waveforms, equations, and text messages
Dynamic waveforms, equations, and text messages
Interaction In augmented space only In real environment and in augmented space
Application Handheld Standalone desktop
Figure 2.Pole-zero plot for stable control system.
3.2. Table-top variant of ARLE
Conversely, the tabletop variant of the developed ARLE is in the form of an interactive workbench with a tangible user interface and implemented as a standalone Unity application for desktop/table- top environment (.exe). It uses EasyAR as the SDK to aid in the tracking of image targets and in mana- ging virtual contents for augmentation. During this study, it was found that Vuforia supports real-time tracking and application development for mobile platforms. EasyAR is selected over Vuforia to support the desktop version for the stand-alone application. This system uses the pole-zero plot in the s-plane as the marker and X-shaped movable targets as poles of the control system, thereby enabling the system to be interactive in real-time as well as in the augmented environment.
Figure 6 shows the trackable targets. Figure 7 shows the hardware associated with tabletop- variant ARLE.
The distance between camera and markers is nearly 65 cm, as thefixed focus works for 40 cm and beyond. The large and small markers (marker 1 and marker 2) are squares with a side length of 25 and 5 respectively. Furthermore, error handling is added for invalid cases and lost targets.Figure 8shows the functional block diagram of the application used in the case of a single-pole stable control system.
Figure 3.Marker used for mobile-based variant of ARLE.
Figure 4.Functional block diagram of mobile-variant ARLE using the case of a two-pole unstable control system as an example.
As shown inFigure 8, the augmented information contains a panel with user interface for system response wave, comment on stability and order of system; system equation; and specifications, such as pole location, oscillation frequency and period, damping ratio, and transfer function of the system.
The system is interactive in real-time given that the users can move the trackable objects on the red marked points on the graph, which serve as identifiable locations for the poles, and check the changes in system response. Furthermore, user interaction of the augmented space serves the
Figure 5.Steps for using the mobile-variant ARLE.
Camera to capture the real scene (installed facing downwards)
Display screen (shows real scene with augmented
information)
Tabletop with document (to be captured and augmented)
Figure 7.Hardware associated with tabletop- variant ARLE.
Figure 6.Trackable targets of tabletop-variant ARLE.
Figure 8.Implementation of ARLE for stable control system (single pole).
purpose of checking the system properties, which are displayed on the panel. To use this application, the steps are shown inFigure 9.
3.3. Implementation of ARLE in classroom settings
Figure 10presents the steps for ARLE implementation in a classroom whereasFigure 11gives the experimental class using the ARLE for both the variants viz. Table-top (Figure 11(a)) and mobile (Figure 11(b)).
The ARLE was implemented for two cases comprising of a sample with a total 60 of students. In both the cases, students were given appropriate prior knowledge of AR and the chosen concept before demonstrating the application. For case study 1, 28 undergraduate students gave response to the hands-on session in the form of a questionnaire based feedback and 32 students were part of case study 2. This study was conducted to evaluate the comparative difference between two different approaches developed for the ARLE viz. Mobile and Table-top.
4. Design challenges
For the mobile-variant ARLE, the augmented information is made dynamic and interactive by adding waveforms and user interface. However, the image targets (graphs for six different cases) are static in nature, containingfixed poles on the s-plane graph. Therefore, the system is not interactive in real- time. Moreover, no error handling is observed in this version of ARLE. Meanwhile, the table-top approach uses computer vision techniques to track the moving targets in the form of X-marked poles, which increases the usability of the system with regard to user interaction. The users can now interact with the real as well as the augmented information. While designing and implementing the ARLE, Vuforia is considered a good SDK (Software Development Kit) for developing mobile-based applications. However, for building a standalone desktop application, the SDK must be changed.
Therefore, EasyAR is selected for the development of tabletop-variant ARLE. A few hardware issues are observed, such as achieving perfect augmentation and the size of graph (real scene) and size of poles (marker). Selection of camera and adjustment of camera height (facing the graph) also play a vital role in the identification of target objects/images. Content-related issues involve the cre- ation of a virtual content (waveforms and equations) as an important aspect of system implemen- tation. N number of cases for pole location can be added using programming, and each case requires relevant virtual content. Targets are occasionally lost due to occlusions (whenever interrup- tion occurs between the camera and the identified target). Therefore, tracking techniques used for AR play a vital role in system performance. The present system uses the vision tracking approach to identify the markers. Another important factor is the lighting condition of the place where the system is installed. Moreover, adequate light is required for marker identification. However, excess lighting (such as sunlight covering the markers) creates undesirable results for augmentation.
5. Results and discussion
A questionnaire-based survey was conducted on undergraduate students to check the efficacy of the designed ARLE as a teaching-learning tool in educational settings. The vision tracking-based mobile and tabletop variants of the AR system were introduced to the undergraduate students of electronics and electrical Engineering, where 28 students took part in the analysis for case study 1. The question- naire comprised multiple-choice questions (with a response of“Very high”for rating 5 on a scale of 5) and written feedback from the students. The training session using ARLE and the feedback of partici- pants during this session lack any effect on students’final academic scores. The responses from the participants are presented inTable 3(Barata, Ribeiro Filho, & Nunes,2015). The response is presented for each question as number/percentage out of the total sample. The following observations have been obtained according to students’response.
Figure 9.Steps for using the tabletop-variant ARLE.
Adequacy:The results fromTable 3show that ARLE is highly adequate for the study of stability analysis of linear control systems, considering 100% of students responded a rating of 4 or 5.
Relevance:The procedure involving time-domain stability analysis of linear control system on a pole-zero plot is highly relevant to the concept in focus as felt by approximately 93% of the students who responded a rating of 4 or 5. However, 7% of the students still thought that only time-domain stability analysis has been presented in the ARLE. The stability analysis of any linear control system can be performed in time and frequency domains; thus, frequency-domain analysis is also implemented using AR in analyzing the stability of control systems.
Presentation and Usability: The virtual content generated for augmentation, such as graphs, equations, and modeled environment; is presented well, and a user friendly interactive interface is used for the ARLE. However, 32% of the students still felt that the usability of the learning environ- ment could be improved by modifying the design with regard to hardware and software, to make the target tracking accurate.
Understanding:Over 90% students opted for a response rating of 4 or 5 for the approach of using AR for improved understanding of concepts, approximately 7% of students still thought that multi- media and other simulations are better for the same goal.
Motivation:The students’level of motivation toward the use of AR-based approach to understand the control theory concept is very high with approximately 90% responded a rating of 4 or 5. However, 10% of students felt that they would be more motivated if the system was more illus- trated, with more graphics, more number of cases of poles location, and better accuracy of the system under design conditions.
Figure 10.Steps for ARLE implementation.
Figure 11.ARLE implementation for experimental class (a) Table-top variant (b) Mobile variant.
Satisfaction and Further Recommendation:Overall satisfaction toward the ARLE for control theory concepts is very high with over 95% rating of 4 or 5. Only 3.5% of sample wanted the system to be better in regard with the aforementioned parameters.
Table 4presents the mean score of students in response to the above mentioned questionnaire.
The case study 1 provided an insight into three aspects: (1) whether the augmented reality interests the students for their classroom environment, (2) how much do they feel motivated using technology such as augmented reality for learning in a classroom, and (3) what are the required modifications in the ARLE, so that it can be reliable enough for being used in classrooms for enhancing the student’s learning of a particular concept through improved visualization. Based on the student response, the changes were made in the ARLE, and case study 2 was implemented, where 32 students from elec- tronics and electrical engineering took part in rating the usability of the two different variants of ARLE on the basis of“HARUS”provided by Santos et al. (2014b). HARUS is Handheld Augmented Reality Usability Scale. It collects user’s opinion for several manipulability and comprehensibility factors per- taining to the AR environment.Table 5presents the manipulability (Q1 to Q5) and comprehensibility (Q6 to Q10) statements and user’s response for both the ARLE variants for these statements on a 5- point Likert scale (1 being lowest and 5 being highest).
The manipulability and comprehensibility statements are used tofind the usability of two different variants, viz. mobile and table-top, from student’s perspective. The mean scores of all the questions
Table 3.Questionnaire response of engineering participants for checking the efficacy of ARLE.
Question asked
Response (number/percentage forn= 28) Very high
#/%
High
#/%
Average
#/%
Low
#/%
Very low
#/%
1. Howadequateis the ARLE for teaching the stability analysis of the linear control system?
12/42.8 16/57.1 0/0 0/0 0/0
2. How much is therelevanceof the presented procedure to the concept in focus?
9/32.1 17/60.7 2/7.1 0/0 0/0
3. How well were the graphs, equations, and the modeled environment (virtual content used for augmentation)presentedin the procedure?
9/32.1 19/67.8 0/0 0/0 0/0
4. How high was your level ofmotivationtoward using the ARLE for analyzing the stability of the control system?
16/57.1 9/32.1 3/10.7 0/0 0/0 5. How highly would you rate theusabilityof the system
(userfriendliness of the interface, such as buttons, mouse and keyboard, and use of icons)
8/28.5 11/39.2 9/32.1 0/0 0/0
6. How well did the course with AR approach improve your understandingof the concept presented?
17/60.7 9/32.1 2/7.1 0/0 0/0 7. How likely would yourecommendthis AR approach to other
students?
17/60.7 10/35.7 1/3.5 0/0 0/0 8. Overall, howsatisfiedwere you with this approach to the topic? 15/53.5 12/42.8 1/3.5 0/0 0/0
Table 4.Mean score of student’s response to questionnaire on ARLE (case study 1).
Question Asked
Mean Score How adequate is the ARLE for teaching the stability analysis of the linear control system? 4.43 How much is the relevance of the presented procedure to the concept in focus? 4.25 How well were the graphs, equations, and the modeled environment (virtual content used for augmentation)
presented in the procedure?
4.32 How high was your level of motivation toward using the ARLE for analyzing the stability of the control system? 4.46 How highly would you rate the usability of the system (user friendliness of the interface, such as buttons, mouse and
keyboard, and use of icons)
3.96 How well did the course with AR approach improve your understanding of the concept presented? 4.54
How likely would you recommend this AR approach to other students? 4.57
Overall, how satisfied were you with this approach to the topic? 4.5
were calculated and compared, as given inTable 5. Both the variants were accepted by the learners as shown in the results of individual manipulability and comprehensibility statements given in Figures 12and13respectively.
However, the response of students shows that table-top approach scored better for Q1 (reverse question, discarded later for the case of table-top, as the students were not required to hold any device), Q4 and Q7 with better values of mean scores; related to user interaction and appropriate information on-screen. Whereas, the mobile variant had a slight edge over remaining test items in terms of information manipulation, ease of use, simple operation, required mental effort, speed of response and information consistency.
The freeform written feedback comprised of three questions: What did user like the most about the AR approach? What improvements are desired? What other topics do the students think are suit- able for being comprehended using the same approach? To answer thefirst question, nearly all of the students liked the new approach of understanding theoretical concepts. They described it as“inter- esting,” “exciting,”and“seamless.”The coding and animation used in the system development were considered by the students, and the technology of“AR”truly fascinated them. Students cited the ARLE as“interactive in real-time,” “better learning environment,” “better than cramming,”and“an addition to the traditional theoretical approach of learning and teaching.”Furthermore, the partici- pants mentioned that the developed ARLE is suitable for“practical visualization of concepts for better understanding.”The participants also mentioned that using AR could“make learning easy”for some of the complicated theoretical issues related to the course.
To answer the second question, participants suggested that the system to be“automated for detection of different number of poles”in the s-plane. Other improvements desired by the partici- pants were “sensitivity of markers” and “user friendliness of the interface” used for interaction.
Few points were mentioned by students considering the solution was either available or could not be feasible, such as the addition of a number of cases to the system for the stability of the control
Figure 12.Mean score for manipulability statements from the HARUS.
Table 5.Table-top vs mobile: manipulability and comprehensibility (case study 2).
Sr. No. Question Mobile AR Table-top AR
Q1 I found the device difficult to hold while operating the ARLE 2.28 –
Q2 I found it easy to manipulate information through the ARLE 3.94 3.78
Q3 I think the ARLE is easy to control 3.91 3.63
Q4 I think that the ARLE is interactive in Real-space as well as in Augmented-space 3.91 4.09
Q5 I think the operation of the ARLE is simple and uncomplicated 4.16 3.72
Q6 I think that interacting with the ARLE requires a lot of mental effort 2.22 2.37 Q7 I thought that the amount of information displayed onscreen was appropriate 3.50 3.78
Q8 I felt that the information display was responding fast enough 3.84 3.35
Q9 I thought that the information displayed onscreen was confusing 2.03 2.22
Q10 I thought that the information displayed onscreen was consistent 3.97 3.59
system and markerless tracking of the present ARLE. The addition of cases indicates increasing the number of identifiable locations of poles in the s-plane, which can be conducted by adding relevant virtual content and modifying the coding used for the ARLE. Therefore, N number of cases could be added to the present system to analyze the stability of linear control systems. The marker-less track- ing would not be an appropriate option for the present system because the markers were used as an interface between the user and the virtual data in this system, which would be an indoor application for education. Markerless tracking is suitable in outdoor application, thereby allowing users an access to virtual/augmented information anywhere and anytime.Table 6provides the feedback provided by the participants for each question in freeform in the same manner as it was written.
To answer the third question, the participants showed interest in visualizing and understanding the concepts of microprocessor and microcontrollers, communication systems, signal processing, electronic devices, and circuit design using the same approach, as well as in the frequency- domain stability analysis of control system. The overall response of the system was positive from the students’perspective. If the selection of relevant virtual content, relevant markers, and necessary changes in the code used for this system was conducted, then the application could be suitable for teaching/learning of other theoretical topics and would be useful in improving students’concept comprehension.
Figure 13.Mean score for comprehensibility statements from the HARUS.
Table 6.Response of engineering participants for freeform written feedback of ARLE session.
Question Written feedback
What did you like the best about the session? Visualization of theoretical topics; Practical visualization of concept for better understanding; Real-time hands on; Interesting; Exciting; Use of sensors for image identification; AR/VR; Better learning environment for theory topics; Back end coding/animation; Seamless recognition;
Easy for understanding of concepts; Better than cramming; Interactive;
Specification of each case of stability; New thing; Additional teaching/
learning of theoretical courses.
Please state the things you would want to see improved in future sessions.
Sensitivity of markers/image targets; Automated detection of single/
multiple poles in the s-plane; Tracking (detection of markers/image targets); User friendliness; More cases of stability with more illustration;
Markerless tracking.
Please mention other topics from your course that you would like to comprehend using AR/VR.
IC interfacing; Microprocessor and microcontrollers; Arduino circuits;
Communication; Programming languages, such as C/C++; Electrical signals; Expensive equipment; Chemistry; Analog communication system; Flipflops; Signals and systems, Digital signal processing; How to create AR/VR projects; Frequency-domain stability analysis of control systems involving Bode and polar plots; Shifting and scaling properties of signals; Network analysis and synthesis; Z-transform; Circuit design.
6. Conclusions and future scope
The use of an Augmented Reality Learning Environment (ARLE), which was developed and tested in the present study, is an adequate and relevant technique for teaching difficult theory concepts, where students’imagination/visualization is desired. The ARLE thus developed and implemented is adaptive, because the Unity 3D program using appropriate SDKs can be built as a mobile appli- cation as well as a stand-alone desktop application. It serves two purposes; students can chose the mobile variant and carry the app and associated markers anywhere anytime, and analyze the system properties using ARLE with interaction in the augmented space, making it a type of Mobile AR. Also, they can use a dedicated PC in classroom settings, with a fixed camera, display screen and associated markers, and analyze the system properties using ARLE with interaction in the real as well as the augmented space, making it a type of Desktop/Table-top AR. This ARLE has been designed while taking care of the principle of Contiguity used for multimedia learning (Mayer, 2001), emphasizing that students obtain better comprehension of the learning material, when corre- sponding text and pictures are provided to them simultaneously on the display screen. Hence, ARLE design consists of the following implications: First is the freedom to manipulate the virtual data and interact with the physical environment, resulting in improved understanding of the concepts from the students’perspective. The use of ARLE increases students’motivation and satisfaction on the use of technology. Another is its user-friendly interface and interaction with the system, which occurs in case of both the variants, namely, mobile and tabletop environment for the present study. The system designed for stability analysis of linear control system (simple and complex pole systems) is dynamic in terms of user interaction through addition of N number of cases by modifying the programming for mobile and desktop applications. The developed system supports error hand- ling for both variants of ARLE. However, usability of the learning environment would be improved in terms of hardware and software, if the target tracking becomes more accurate. To address this, the future work would involve the design of an updated version of the ARLE; which would include sensors along with the computer vision method for target tracking. This technique, called hybrid tracking, would ensure accurate marker detection, resulting in correct identification of the targets for a particular case. Moreover, the use of AR for visualization of more complicated topics from engin- eering courses, such as analysis of system stability in the frequency domain of the s-plane for control systems using Bode and Polar plots, communication systems, signal processing etc. would also be considered as future work. For the present study, participants’ response and feedback confirm that the developed ARLE is useful as an instructional tool for teaching theoretical topics and is an effective learning tool for students in their concept building in engineering education.
Disclosure statement
No potential conflict of interest was reported by the authors.
Notes on contributors
Deepti Prit Kauris an Assistant Professor at Chitkara Institute of Engineering and Technology, Punjab, India. Her research interests include Augmented Reality for Engineering Education, Computer Vision, Embedded Systems and Human-Com- puter Interaction.
Archana Mantriis Professor and Pro-Vice Chancellor at Chitkara Institute of Engineering and Technology, Punjab, India. In her current role, she oversees all research, innovation and Consultancy related aspects at Chitkara University Research and Innovation Network (CURIN). Her research interests include Augmented Reality, Innovation Management, and Ped- agogical Innovations.
Ben Horanis the Director of the CADET Virtual Reality (VR) Lab and the Head of the Bachelor of Mechatronics Engineering within the School of Engineering, Deakin University, Australia. His current research interests include haptic human robotic interaction, virtual and augmented reality, haptic device design.
ORCID
Deepti Prit Kaur http://orcid.org/0000-0003-2363-0753
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