Evaluation of learners’ attitude toward learning in ARIES augmented reality environments
Highlights
► We describe a system for building augmented reality learning environments. ► We examine factors affecting learners’ attitude to augmented reality environments. ► Learners can perform experiments on 3D virtual objects by hands-on experiences. ► Intention to use depends much more on perceived enjoyment than on usefulness. ► Interface style and ease of use have a weak influence on perceived enjoyment.
Introduction
The two most important social and economic processes occurring nowadays are: emerging electronic knowledge-based economy and transformation toward global information society. Therefore, creativity and innovation become more and more prominent determinants of the competitiveness on the labor market in the 21st century. This is a major challenge for education and teaching that needs to be addressed in the near future (Cellary, 2002). The aforementioned challenges require significant improvement of teaching methods, which will transform the role of learners from passive recipients of information to active participants in knowledge acquisition (Walczak, Wojciechowski, & Cellary, 2006).
In response to this need, an increasing interest in teaching based on the constructivist learning theory has taken place since the 90s of the 20th century (Wilson, 1996; Jonassen, 1999; Marshall, 1996). There are a wide variety of perspectives on what the term constructivism means (Piaget, 1973; Vygotsky, 1978; Bruner, 1996). In this paper, the constructivist learning is understood as an active process of constructing knowledge by the learner, in contrast to passive acquiring the information (Duffy & Cunningham, 1996).
According to the constructivist approach, a teacher is a facilitator of learning rather than a transmitter of knowledge (Chaille & Britain, 2002). There are a number of possible pedagogic activities implementing the constructivist principles, such as experimentation, conducting discussions, performing projects, etc. All these activities encourage learners to be active and to make their own discoveries, inferences, and conclusions. Deployment of constructivist principles in a classroom requires usage of interactive and dynamic learning environments, where the learners are able to modify appropriate elements, test ideas, and perform experiments (Roussou, 2004).
Learning based on performing experiments and further reflection on their results is the basis of the learning-by-doing paradigm (Schank, Berman, & Macperson, 1999). This paradigm implies that the best and the most natural way of learning how to do something is trying to do it. A learning strategy that implements the learning-by-doing approach is experiential learning (Kolb, 1984; Beard & Wilson, 2006). This strategy greatly increases understanding and retention of the learned material in comparison to the methods that solely involve listening, reading, or even viewing, as learners are usually intrinsically motivated to learn when they are actively engaged in the learning process (Yang, 2012).
A key determinant of the effectiveness of experiential learning is interactivity (Roussou, 2004). As far as learning content is concerned, the interactivity is defined as: “the extent to which users can participate in modifying the form and content of a mediated environment in real time” (Steuer, 1992, p. 14). In traditional learning, the highest level of interactivity can be achieved in teaching labs, where students are able to conduct experiments putting theoretical concepts into practice. However, there are serious limitations associated with the experiments performed in teaching labs, since they may require much space, expensive equipment, appropriate safety measures, and trained staff. These restrictions make the large scale dissemination of experiential learning in educational institutions practically impossible or economically unjustifiable (Jara, Candelas, Puente, & Torres, 2011). Without breaking down those barriers, experiential learning will remain of more theoretical rather than practical significance.
In this paper, we consider application of image-based augmented reality (AR), which is an extension of virtual reality (VR), to create learning environments enabling experiential learning. Virtual reality is defined as “a high-end user–computer interface that involves real time simulation and interactions through multiple sensorial channels. These sensorial modalities are visual, auditory, tactile, smell, and taste” (Burdea & Coiffet, 2003, p. 3). In this paper, we focus on two essential aspects of VR, namely three-dimensional (3D) visualization and interactivity. Such a VR interface is called a virtual environment (VE), which is a 3D digital model of a real, abstract, or imagined environment. Virtual environments potentially offer a much broader range of forms of interactivity than real environments. Users are able to freely navigate in a virtual environment, observe the environment from different perspectives, and interact with selected virtual objects. Virtual environments can be used to implement virtual laboratories in which users are able to perform experiments (Dalgarno, Bishop, Adlong, & Bedgood, 2009; Jeong, Park, Kim, Oh, & Yoo, 2011). However, to create a virtual environment offering a high level of credibility it is required to create a 3D model of an entire real environment, which is both time-consuming and expensive. The current state of the VR technology causes the separation of humans from the real world, requires the use of expensive equipment to display and manipulate virtual objects, and also offers an indirect non-intuitive user interface.
In comparison to virtual reality, which is aimed at immersing a user in a synthetic environment, augmented reality supplements the user’s perception of the real world by the addition of computer-generated content registered to real-world locations (Azuma, 1997). Augmented reality combines virtual reality with video processing and computer vision technologies (Parker, 1997; Davies, 2005). The AR technology enable merging virtual objects with the view of real objects, resulting in augmented reality environments. In augmented reality environments both virtual and real objects can co-exist and interact in real time (Milgram & Kishino, 1994).
The creation of AR environments requires design of virtual representation of a relatively small part of these environments. A significant part of AR environments consist of real objects, for which it is not necessary to create detailed 3D models, while offering the highest possible level of reality. In AR environments, users are able to interact with virtual objects in a direct and natural way by manipulating real objects without the need of sophisticated and expensive input devices (Wojciechowski, Walczak, White, & Cellary, 2004). Also, in contrast to virtual environments, in which users communicate in a mediated way via avatars, AR environments afford users direct face-to-face contact with each other.
AR environments offer better opportunity of learning-by-doing through physical movements in rich sensory spatial contexts (Dunleavy, Dede, & Mitchell, 2009). Therefore, users have an opportunity to perform experiments on virtual objects by hands-on experiences in their real environments. This feature of AR supports situated learning which means that learning should take place in the context in which it is going to be applied (Lave & Wenger, 1991). AR allows students to seamlessly combine learning environments with the real world in which they live and apply the knowledge and skills learned. AR environments with possible direct face-to-face interaction between learners foster the creation of communities of practice focused on the goal of gaining knowledge related to the presented content, since the learners are able to easily share gained information and experiences with the group (Lave & Wenger, 1991).
The main advantages of AR applications in the education domain are: activity of learners, cost and safety. AR environments allow learning content to be presented in meaningful and concrete ways including training of practical skills. They may play active roles in a wide range of learning activities within interactive educational scenarios developed in accordance with the learning-by-doing paradigm. The experience gained by learners during the learning process within an AR environment can be the basis for reflection and further group discussion in a classroom. The main aspects of learning afforded by AR environments are: spatial ability, practical skills, conceptual understanding, and inquiry-based activities (Cheng & Tsai, 2012).
Application of AR environments for teaching is followed by cost reduction due to replacing real expensive resources, such as laboratory equipment and supplies, with their virtual counterparts. A significant advantage of AR environments is safety, since unskilled learners may explore potentially dangerous situations without any risk of harm to themselves or damage to expensive equipment.
There are a number of possible applications of AR environments in education (Walczak et al., 2006). They can be used for teaching about objects and phenomena impossible to see by naked eye (e.g., molecular movements), simulation of potentially dangerous situations (e.g., chemical reactions), and visualization of abstract concepts (e.g., magnetic fields). In addition, the level of complexity of the presented phenomena can be reduced to allow the learners to easier gain knowledge about the underlying concepts. AR environments may be used in a wide spectrum of domains from natural sciences (e.g., chemistry, physics, biology, astronomy), through computer and information sciences, mathematics, engineering (e.g., mechanical, electrical, biomedical), to humanities (e.g., history, linguistics, anthropology).
This paper is organized as follows. In Section 2, basic concepts related to augmented reality environments are introduced, as well as an overview of applications of AR in education. In Section 3, an overview of the ARIES system is presented. In Section 4, the TAM-based research model and an application scenario of the ARIES system are described. This section also contains a description of the research study. In Section 5, the results of the system evaluation are presented. Finally, Section 6 concludes the paper.
Section snippets
Categories of augmented reality environments
Augmented reality is a broad concept, which applies to “technologies that combine the real and the virtual in any location-specific way, where both real and virtual information play significant roles” (Klopfer, 2008, p. 92). In general, AR systems are divided into location-based and image-based systems (Cheng & Tsai, 2012).
The location-based AR systems use the data about the position of mobile devices, determined by the Global Positioning System (GPS) or WiFi-based positioning systems. The
System design
In this section, a system for building AR learning environments, called ARIES, is presented. ARIES is an e-learning system which enables domain experts, i.e. teachers, to actively participate in the authoring process of interactive educational scenarios. The ARIES system has been built as an implementation of the Augmented Reality Environment Modeling (AREM) approach (Wojciechowski, 2012). The AREM approach enables teachers to design and create learning scenes for augmented reality environments.
Research model
The aim of the experiment was to evaluate the learner’s attitude toward experiential learning in AR environments. In the experiment we adopted the Technology Acceptance Model (TAM) that enables to explain the determinants that encourage system use (Davis, 1989; Davis, Bagozzi, & Warshaw, 1989). The TAM model is a widely used model in technology acceptance studies (Teo, 2009; Sun & Cheng, 2009). The basic TAM model is shown in Fig. 5.
In the TAM model, acceptance of a system is represented by
Descriptive statistics
The statements of the questionnaire and the descriptive statistics for each statement are presented in Table 1. All mean values are within a range of 3.93 and 4.62. The standard deviation range from 0.623 to 1.310.
To measure the internal consistency of statements a coefficient Cronbach alpha was calculated for the statements belonging to each construct specified in the research model. To consider the internal reliability of statements concerning the same construct as satisfactory Cronbach alpha
Conclusions
Following the empirical study, we found that perceived usefulness and perceived enjoyment had a similar effect on attitude toward using image-based AR environments. With regard to the intention to use of AR environments, perceived enjoyment was a much more significant factor than perceived usefulness. Therefore, the use of AR environments during lessons could provide extra motivation to learn for young students. Before performing the empirical study, we wondered whether the interface style
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