Virtual reality and perceived learning effectiveness in accounting studies: the mediating role of task-technology fit

Ratmono, Dwi; Sari, Ratna Candra; Warsono, Sony; Ubaidillah, Muhammad; Wibowo, Luqman Mulki Article Virtual reality and perceived learning effectiveness in accounting studies: the mediating role of task-technology fit Cogent Business & Management Provided in Cooperation with: Taylor & Francis Group Suggested Citation: Ratmono, Dwi; Sari, Ratna Candra; Warsono, Sony; Ubaidillah, Muhammad; Wibowo, Luqman Mulki (2024) : Virtual reality and perceived learning effectiveness in accounting studies: the mediating role of task-technology fit, Cogent Business & Management, ISSN 2331-1975, Taylor & Francis, Abingdon, Vol. 11, Iss. 1, pp. 1-18, https://doi.org/10.1080/23311975.2024.2316890 This Version is available at: https://hdl.handle.net/10419/326077 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/4.0/ Cogent Business & Management ISSN: 2331-1975 (Online) Journal homepage: www.tandfonline.com/journals/oabm20 Virtual reality and perceived learning effectiveness in accounting studies: the mediating role of task-technology fit Dwi Ratmono, Ratna Candra Sari, Sony Warsono, Muhammad Ubaidillah & Luqman Mulki Wibowo To cite this article: Dwi Ratmono, Ratna Candra Sari, Sony Warsono, Muhammad Ubaidillah & Luqman Mulki Wibowo (2024) Virtual reality and perceived learning effectiveness in accounting studies: the mediating role of task-technology fit, Cogent Business & Management, 11:1, 2316890, DOI: 10.1080/23311975.2024.2316890 To link to this article: https://doi.org/10.1080/23311975.2024.2316890 © 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. Published online: 26 Feb 2024. Submit your article to this journal Article views: 3182 View related articles View Crossmark data Citing articles: 7 View citing articles Full Terms & Conditions of access and use can be found at https://www.tandfonline.com/action/journalInformation?journalCode=oabm20 ACCOUNTING, CORPORATE GOVERNANCE & BUSINESS ETHICS | RESEARCH ARTIClE Cogent Business & ManageMent Virtual reality and perceived learning effectiveness in accounting studies: the mediating role of task-technology fit Dwi Ratmonoa , Ratna Candra Sarib , Sony Warsonoc, Muhammad Ubaidillahd and luqman Mulki Wibowod aDepartment of accounting, Faculty of economics and Business, universitas Diponegoro, semarang, indonesia; bDepartment of accounting education, Faculty of economics, universitas negeri Yogyakarta, Yogyakarta, indonesia; cDepartment of accounting, Faculty of economics and Business, universitas gadjah Mada, Yogyakarta, indonesia; daccountant Professional education Program, Faculty of economics and Business, universitas Diponegoro, semarang, indonesia ABSTRACT The use of virtual reality (VR) for the improvement of learning outcomes for accounting studies is an area in which the research is still limited. Technology-based accounting learning is very important because, currently, the accounting profession is very much affected by rapid technological change which means that it must adapt to remain relevant in the business world. This study aims to examine the role of the mediating effect of task-technology fit (TTF) on the relationship between the use of VR and learning outcomes for accounting studies. This research model states that the use of VR will be able to increase TTF, technology quality and accessibility, and then increase reflective thinking and reduce cognitive overload thereby increasing perceived learning effectiveness (PlE). The hypotheses derived from this model were tested empirically using survey data from 199 users of VR engaged in accounting studies. The data analysis uses partial least squares-structural equation modeling (PlS-SEM), and the results support the hypothesis that TTF mediates the relationship between VR use, learning behavior, and PlE. 1. Introduction In the current era known as the industry 4.0, there has been an acceleration of digitalization and information technology in business and government such as e-commerce and e-government. The COVID-19 pandemic also accelerated digitalization in various sectors. In these circumstances, various professions are currently facing the challenge of having to adapt to a very rapidly changing environment, especially in relation to technology. The accounting profession is also affected by technological change, so it must adapt to remain relevant in the future (Jackson et al., 2022; Tavares et al., 2023). One way to adapt is technology-based accounting learning (Tavares et al., 2023). This current digital transformation in the field of education has seen the development of e-learning which is a more flexible learning method without limitations of time, distance, and space (Umair et al., 2022; Zhang et al., 2017). The challenge for educators is to use technology to support the achievement of high learning outcomes. The educational community has been increasingly concerned about the effectiveness of technologies such as virtual learning environments (VlEs). One of the educational technologies for VlE is virtual reality (VR) (Jena, 2016; Jeon, 2023; Sari etal., 2023; Umair etal., 2022; Zhang etal., 2017). VR is a technology-based learning media that has interactive characteristics and high immersiveness, and it creates a sense of presence which means it can improve learning outcomes (Sari etal., 2023; Umair et al., 2022; Zhang etal., 2017). VR has been widely used in the educational sector because it has © 2024 the author(s). Published by informa uK Limited, trading as taylor & Francis group. CONTACT Dwi Ratmono [email protected] universitas Diponegoro, Jl. Prof. soedharto sH, tembalang, semarang 50275, Jawa tengah, indonesia https://doi.org/10.1080/23311975.2024.2316890 this is an open access article distributed under the terms of the Creative Commons attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. the terms on which this article has been published allow the posting of the accepted Manuscript in a repository by the author(s) or with their consent. ARTICLE HISTORY Received 27 October 2023 Revised 5 February 2024 Accepted 6 February 2024 REVIEWING EDITOR Collins Ntim; University of Southampton; United Kingdom of Great Britain and Northern Ireland KEYWORDS Virtual reality; tasktechnology fit; technology quality; technology accessibility; reflective thinking; cognitive overload; perceived learning effectiveness SUBJECTS Accounting; Accounting Education; Financial Accounting; I.T. Teaching 2 D. RATMONO ETAl. three main characteristics which are its advantages, namely, immersion, interaction, and imagination (Umair et al., 2022). Nowadays, VR has become an integral part of VlE. VR is a useful tool that brings people together from various parts of the world to engage and interact without geographical, social, and economic boundaries. VR technology creates an imaginary world that can transcend the boundaries found in traditional education. Instead of the traditional method of learning that involves listening to a lecture in a classroom, students can absorb words by using a headset and therefore have what feels like an authentic experience in a virtual space. The constructivism and game-based learning that VR provides can improve students’ learning capabilities when compared to the teaching and learning process offered by traditional pedagogy. VR can provide real-time visualization and interaction in a virtual world that can be a way to approach the real world (Chuan et al., 2008; Jeon, 2023). Users can wear three-dimensional (3D) glasses and feel as if they are floating in a projected world in which they can move freely (laver et al., 2015). VR makes it possible, in the learning process, to visualize and stimulate events that are not perceivable in real life; therefore, users can obtain perceived learning effectiveness (PlE) in the fields of architecture, medicine, computer science, construction, and business (Antonieta, 2014; Green et al., 2014; Griol et al., 2014; Kim & Choo, 2023; Sari etal., 2023; Umair etal., 2022; Zhang etal., 2017). Previous research has tested the effectiveness of VR in the learning process in various fields such as engineering (Alhalabi, 2016), the military, (Webster, 2016), robotic surgery (Bric et al., 2016; Francis etal., 2020), firefighting (Çakiroglu & Gökoglu, 2019), negotiation training (Ding etal., 2020), health-care training (Chow-White etal., 2017), ethics education (Sholihin etal., 2020), safety training (Pedram etal., 2020), construction design (Umair et al., 2022), business ethics (Sari et al., 2023) and marketing (Kim & Choo, 2023). However, empirical research on the use of VR in accounting studies is still very limited. This study expands previous research by analyzing the use of VR in improving learning outcomes in accounting. Studies on the use of technology in accounting studies are significant because, currently, the accounting profession must adapt to the process of technological evolution and transformation (Tavares etal., 2023). Education and training of individuals capable of adaptation in this era of digital transformation are necessary for the survival and sustainability of the accounting profession in the future (Tavares etal., 2023). One of the latest technological innovations in the accounting field is the use of VR to help accountants understand company financial reports better and faster (Al-Gnbri, 2022; Chukuwani, 2022; Egiyi, 2022; Zou, 2019). Egiyi (2022) shows that there are several benefits of VR in the accounting field, namely: (1) creation of financial statements, (2) accounting data visualization, (3) accounting education, recruitment and training, (4) virtual communication, networking and customer service, (5) corporate reporting, and (6) auditing. VR will make all accounting activities and preparation of financial reports more automatic in the future. VR will make tasks such as budgeting, invoicing, customer management, inventory, auditing of stock and others more efficient and effective. VR can enable accountants wherever they are to work remotely and can provide users with more efficient experiences such as team meetings, making presentations, training programs, and others. Furthermore, VR will enable accountants to check inventory in real time and with VR, it can reduce costs such as transportation costs because there is no longer a need to go directly to the field when you want to check inventory availability. In accounting learning, VR is used to understand accounting standards and systems in a real-life situation. One example of VR application in accounting learning is Top Education Institute (TOP) in collaboration with PwC Australia, developed to help students understand accounting concepts. The TOP application helps students in the process of learning accounting concepts in an interactive and fun way because they move from a standard classroom situation to a virtual store and apply these accounting principles in a real life. Although several previous studies have provided empirical evidence that users have more learning experiences with VR, there is still very little research that focuses on the mechanism of how VR can increase the PlE of users (Zhang etal., 2017). Most previous research focuses on user’s intention to use VR based on the technology acceptance model (TAM) theory. There is still very limited existing research analyzing how VR affects learning outcomes, especially PlE. Although several studies have described VR as improving learning outcomes when a task is designed well, few have based it on the task-technology fit (TTF) theory when developing research models. Zhang etal. (2017) have tested how the use of VR, according to TTF theory, can increase PlE in business analytics courses. They tested the role of the TTF variable as a moderator in the relationship between COGENT BUSINESS & MANAGEMENT 3 VR, technology quality and accessibility, reflective thinking, and PlE. However, empirical evidence does not support the hypothesis about the moderating effect of the TTF variable. This study extends the research of Zhang et al. (2017) by basing it on a mediation model, rather than a moderation one. In order to explain the mechanism or process of how independent/exogenous variables (use of VR) can influence dependent/endogenous variables (perceived learning effectiveness), it is more appropriate to use the mediation model than the moderation one (Hair et al., 2022; Hayes, 2022; Hayes & Rockwood, 2020). Apart from that, expansion was also carried out by adding the cognitive overload variable as one of the important learning behavior variables in research on learning (Buchner et al., 2022). 2. Literature review and hypothesis development 2.1. Task-technology fit theory The task-technology fit (TTF) theory has been used in empirical research to test the usefulness of technology in the work environment and education (Jung et al., 2023). TTF theory explains the level of conformity between the requirements of a person’s task and the ability of technology to support that person’s skills when performing the task (Dishaw et al., 2002). TTF theory is part of contingency theory which explains the usefulness of technologies (Jung etal., 2023). The right technology for a specific task can help individuals or organizations achieve their goals and improve performance. In addition, TTF theory is useful for understanding the technology-to-performance chain, focusing on the match between user task needs and the functionality provided by the technology (Howard & Rose, 2019). TTF theory complements the existing focus on utility in research on acceptance based on models such as the technology acceptance model (TAM) theory, in which the user’s attitude toward technology influences his or her choice (Klopping & McKinney, 2004). However, the user’s skill selection behavior does not always guarantee that task performance will improve (Jung et al., 2023). On the other hand, the use of the TTF model has been shown to improve personal and organizational task performance (Goodhue & Thompson, 1995; Jung etal., 2023). TTF theory shows the importance of decision-making and choosing appropriate information technology for different tasks. TTF theory has been used in previous research to explain the successful selection of information technology in various digital transformation contexts such as online educational content that ensures sustainable use (Wu et al., 2018), Internet of Things (IoT) network systems for disaster management (Sinha et al., 2019), learning about VR technology to increase its effects (Zhang etal., 2017), and decision support systems to improve the quality of decisions (Erskine etal., 2019). 2.2. Virtual reality (VR) VR is defined as "the sum of the hardware and software systems that seek to perfect an all-inclusive, sensory illusion of being present in another environment" (Biocca & Delaney, 1995; Radianti etal., 2020). VR has three core characteristics, namely interactivity, presence, and immersion (Radianti et al., 2020; Ryan, 2015; Walsh & Pawlowski, 2002). Interactivity is the degree to which a user can modify the VR environment in real time (Steuer, 1995). Presence is considered to be "the subjective experience of being in one place or environment, even when one is physically situated in another" (Witmer & Singer, 1998). According to a technological perspective, the term immersion means “the extent to which the computer displays are capable of delivering an inclusive, extensive, surrounding, and vivid illusion of reality’’ (Slater & Wilbur, 1997). More precisely, this includes the degree to which the physical reality is excluded, the range of sensory modalities, the width of the surrounding environment, and the resolution and accuracy of the display (Slater & Wilbur, 1997). The technological attributes of VR technology—such as the frame rate or the display resolution—consequently determine the degree of immersion that a user experiences (Bowman & McMahan, 2007). The main advantage of VR is that it can provide collaborative learning by emphasizing immersion, interaction, and communication. Immersion is a feeling of being physically present in a non-physical world. Interaction means that users can see a change in activity on the screen as a result of their input (e.g. a gesture) and respond to a new activity instantly and quickly. Imagination means that a VR environment triggers the human mind’s capacity to imagine in a creative sense, non-existent things. VR has 4 D. RATMONO ETAl. two important features, namely representational fidelity and immediacy of control. Representational fidelity is the degree of realism provided by the rendered 3D images and scenes (Dalgarno etal., 2002). It also refers to the connectedness and continuity of the stimuli experienced (Witmer & Singer 1998). Meanwhile, the immediacy of control refers to the ability to change the view position or direction, giving the impression of smooth movement through the environment, and the ability to pick up, examine, and manipulate objects within the virtual environment (Dalgarno et al., 2002). Previous research has documented that there has been an increase in the use of VR in the field of education and training because it can stimulate interactivity and motivation thereby increasing PlE (Egiyi, 2022; Garris et al. 2002; Ott & Tavella 2009; Radianti et al., 2020; Sari et al., 2023; Zhang et al., 2017). VR is able to help students explore computer-generated multimedia learning environments in real time. It can provide immersive learning environments in which learners are able to have an experience like real life where there is limited or no access to the real world (Freina & Ott, 2015; Radianti etal., 2020). One of the features of VR is that it’s capable of making learning environments highly immersive. Radianti et al. (2020) defined immersion as "the involvement of a user in a virtual environment during which his or her awareness of time and the real world often becomes disconnected, thus providing a sense of being in the task environment instead" (p. 2). The novelty of VR technology can bring excitement and fun to learning environments (Radianti et al., 2020). Previous studies have found that using new technology such as VR for learning can foster learners’ motivation in comparison to conventional learning materials. Jensen and Konradsen (2018) reviewed the use of immersive VR technologies, particularly for skill acquisition. They focused on immersion and presence and found that VR is useful for training cognitive skills that are related to spatial and visual knowledge, visual scanning, observational skills, psychomotor skills that involve head movement, and affective control of emotional response in stressful or difficult situations (Jensen & Konradsen, 2018). These findings are in line with other research that has also found that learning with VR can improve learning outcomes (Alhalabi, 2016). Zou (2019) argues that VR can help accountants in managing accounting systems and financial data and provide advice to top management for business development. VR is not only on its path to becoming a vital part of all businesses. It also provides a far-reaching and innovative experience to accounting education (Al-Gnbri, 2022; Chukuwani, 2022; Zou, 2019). In the context of accounting learning, Sari etal. (2023) have provided empirical evidence that VR can improve technology quality, technology accessibility, and self-efficacy. This research expands the research of Sari et al. (2023) with a more comprehensive model, namely by adding the variables task technology fit, reflective thinking, cognitive learning and perceived learning effectiveness. In order to address a specific gap in previous research, this study develops a mediation model to analyze the mechanism or process of how the use of VR can increase perceived learning effectiveness. This study argues that VR technology has representational fidelity and immediacy of control features that are easy to use, thereby increasing technology accessibility. In addition, these two features are appropriate technology so that users perceive them as quality (Dalgarno et al., 2002; Sari et al., 2023; Zhang etal., 2017; Zou, 2019). The use of user-friendly and high-quality VR further increases the match between technological capabilities and the needs for carrying out an assignment or TTF. VR technology has ease of use features (the same as the technology accessibility variable attribute) and usefulness (the technology quality variable attribute) which can increase suitability for the user’s task (Pedram et al., 2020). Furthermore, TTF can improve reflective thinking in the learning process which requires higher-order thinking skills, as it involves students’ capacity to think, react and decide rationally (Jena 2016; Sari etal., 2023; Zhang et al., 2017). In addition, TTF can reduce cognitive overload because the presentation of information in VR is easy to understand but comprehensive (Jena, 2016; Buchner etal., 2022). Increasing reflective thinking and reducing cognitive overload further contribute positively to learning effectiveness. 2.3. Hypothesis development 2.3.1. The influence of VR on technology quality and technology accessibility VR has features that include technology quality and technology accessibility (Salzman et al., 1999). Technology quality is described as “important,” “relevant,” “useful,” and “valuable,” so it is similar to COGENT BUSINESS & MANAGEMENT 5 “perceived usefulness” (Zhang et al., 2017). Meanwhile, technology accessibility is characterized by whether it is “convenient,” “controllable,” and “easy,” so it is the same as perceived ease of use. VR technology has been widely used in various fields including medicine, engineering, construction, business, education, and entertainment (Radianti et al., 2020; Sari et al., 2023; Zhang et al., 2017; Zou, 2019). The VR system is able to immerse users into a 3D virtual environment where they can interact in real time with virtual objects. With these features, VR technology can improve user performance in various fields (Radianti et al., 2020; Zhang et al., 2017). Shiratuddin and Sulbaran (2006) and Umair et al. (2022) found that VR can help study construction in courses such as engineering and building design. lawson etal. (2015) also found that VR enables better studies in physics. With two main features of VR, namely representational fidelity and immediacy of control, an appropriate set of learning tasks needs to be designed. With appropriate technology supporting their tasks in VR, learners will find the technology useful and easy to use (Dalgarno et al., 2002; Sari et al. 2023; Zhang et al., 2017). Thus, the use of VR can improve technology quality and technology accessibility. Based on TTF theory, VR technology may best be deployed to support individuals and facilitate the completion of tasks so that users perceive it as having good quality. An experimental study by Chapoulie (2014) focused on two types of VR interface, namely a six degrees of freedom (6DOF) joystick and finger-tracking systems. In the experiment, users found it easy to make manipulations and gestures. Chapoulie (2014) provided empirical evidence that VR is easy to use or meets the criteria for technology accessibility. Sari etal. (2023) have provided empirical evidence that the use of VR has a positive effect on technology quality and technology accessibility. Therefore, we hypothesize: H1: The use of virtual reality has a positive effect on technology quality. H2: The use of virtual reality has a positive effect on technology accessibility. 2.3.2. The influence of VR use on task-technology fit A new kind of information technology such as VR will only be used if its function supports the user’s tasks and can improve learning outcomes. Therefore, it is necessary to design an appropriate set of learning tasks with support for those tasks, such as VR, that users perceive as useful and easy to use (Dalgarno et al., 2002; Radianti et al., 2020; Zhang et al., 2017). The ability of an information system to support a task can be explained by the TTF model (Strong et al., 2006). TTF implies matching between the capabilities of the technology and the demands of the task (Goodhue & Thompson, 1995). There is an argument that in order for technology to have a positive impact on individual performance, the technology must fit the performance, system characteristics, and task characteristics in a TTF model (McGill&Klobas, 2009). Empirical evidence has shown that VR features have improved task-technology fit (Jung et al., 2023; Radianti et al., 2020; Zhang et al., 2017). H3: The use of virtual reality has a positive effect on task-technology fit. 2.3.3. The influence of task-technology fit on technology quality and technology accessibility According to TTF theory, if technology provides a good fit with the tasks, users should perceive the technology as being useful and easy to use to complete the task (Zhang etal., 2017). Zakaria and Daud (2014) argued that TTF is a predictor of technology quality. Previous studies have found that there is a significant positive relationship between TTF and technology quality (Dishaw et al., 2002; Zhang et al., 2017). Other empirical evidence has shown that technology quality is more dependent on the technology’s fit with the task than the workplace environment (Klopping & McKinney, 2004). In addition, Klopping and McKinney (2004) and Zhang etal. (2017) provided empirical evidence that TTF can increase technology accessibility. TTF will influence user beliefs about the consequences of use, namely technology quality and accessibility. H4: Task-technology fit has a positive effect on technology quality. H5: Task-technology fit has a positive effect on technology accessibility. 6 D. RATMONO ETAl. 2.3.4. The influence of technology quality, technology accessibility, and task-technology fit on reflective thinking and perceived learning effectiveness There is an argument that instructional implementation of technology, and not technology itself, determines learning outcomes (Webster & Hackley, 1997; Zhang etal., 2017). When the technology is right for solving learning tasks, it can encourage reflective thinking and reduce cognitive overload thereby increasing PlE. Reflection is an important factor for someone who wants to become an effective lifelong learner and an effective problem solver. Reflective thinking has characteristics including actively monitoring, evaluating, and modifying one’s thinking and comparing it to expert models, peers, and prior experience (Zhang et al., 2017). VR can offer several functions to support reflective thinking. There is a theoretical framework that good quality and easy-to-use technology can improve reflective thinking in four ways (Zhang et al., 2017): (a) process displays, showing learners explicitly what they are doing to solve a task or learn a concept; (b) process prompts, prompting students to explain and evaluate what they did before, during, or after problem-solving acts; (c) process models, focusing on the process that an expert would use in order to think about or solve specific problems; and (d) a forum for reflective social discourse, indicating that reflection can also be a social activity and can be influenced by a community. The literature states that technology quality and technology accessibility are antecedents of learning behavior such as reflective thinking which in turn has an impact on PlE (Radianti etal., 2020; Sari etal., 2023; Zhang et al., 2017). In using VR, PlE depends on the quality and accessibility of the technology used which is referred to as the model of technology-mediated learning (TMl) (Salzman etal., 1999; Sari et al., 2023; Sharda et al. 2004; Wan et al., 2007). The technology quality and technology accessibility in the VR feature are designed to influence learning behavior such as reflective thinking and cognitive overload. VR’s unique features alone are not enough to facilitate learning, thinking, and understanding. If the technology can support one or more of these four ways (Zhang etal., 2017), then reflective thinking can be improved. VR technology that has good quality and accessibility and is suited to what is needed to complete tasks will be able to improve reflective thinking (Jung et al., 2023; Radianti et al., 2020; Zhang et al., 2017). The main goal of the learning process is to gain knowledge and increase the capability to take effective action. However, in learning research, it is difficult to measure knowledge and capabilities; indeed, only actions and performance resulting from the learning process can be observed and measured (Alavi & leidner, 2001). Reflective thinking requires higher-order thinking skills as it involves students’ capacity to think, react, and decide rationally (Zhang et al., 2017). lee et al. (2010) provided empirical evidence showing that desktop VR can improve user’s reflective thinking and learning outcomes. Virtual learning environments (VlEs) with the use of VR can encourage reflection, accommodate student needs, increase self-confidence, improve readiness to learn, and improve academic performance (Jena, 2016). Empirical evidence shows that reflective thinking is predictive of PlE if the learning objectives are aligned closely to the assessment tasks (lee et al., 2010; Makransky & lilleholt, 2018; Sari et al., 2023; Zhang etal., 2017). Khalid etal. (2016) and Hsieh et al. (2014) provided empirical evidence showing that it is important for students to master reflective thinking skills, because it will help to improve their learning outcomes. H6: Technology quality has a positive effect on reflective thinking. H7: Technology accessibility has a positive effect on reflective thinking. H8: Task-technology fit has a positive effect on reflective thinking. H9: Reflective thinking has a positive effect on perceived learning effectiveness. 2.3.5. The influence of technology quality, technology accessibility, and task-technology fit on cognitive overload and perceived learning effectiveness Cognitive overload is a learning load where the amount or method of presenting information exceeds the carrying capacity of a person’s working memory (Buchner etal., 2022). According to TTF theory, it is important to consider cognitive overload when giving learning instructions. This is because the human cognitive architecture consists of a sensory register, a working memory with limited capacity, and a COGENT BUSINESS & MANAGEMENT 7 long-term memory with unlimited storage size (Sweller, 1988; Sweller etal., 1998, 2019). When compared to other technologies, VR seems to be less cognitively demanding and also leads to higher performance (Jena, 2016). Pedram et al. (2020) have provided empirical evidence that VR technology has ease of use features and usefulness which can make it suitable for the user’s tasks. These features can then reduce cognitive overload (Makransky etal., 2019). In a systematic review, Buchner etal. (2022) provided empirical evidence that the majority of previous studies report lower cognitive load with higher performance when compared to more traditional conditions such as display-based or paper-based instruction. H10: Technology quality has a negative effect on cognitive overload. H11: Technology accessibility has a negative effect on cognitive overload. H12: Task-technology fit has a negative effect on cognitive overload. H13: Cognitive overload has a negative effect on perceived learning effectiveness. Figure 1 presents the research model used in this research: 3. Research method 3.1. Data collection This study used a purposive sampling method to select VR experiment participants, namely accounting students who had studied Islamic accounting as criteria. Based on the criteria, there were 199 students who participated in this study. They were asked to complete an assignment including data extraction and analysis as well as a case study using VR. The average age of respondents is 20.27 years with a standard deviation of 2.04 years. There were 102 female respondents (51.25%) and 97 male respondents (48.75%). As many as 92.96% of respondents stated that they had no work experience. Based on experience using VR, the majority of respondents, namely 146 people (73.37%) stated that they had never used VR. Only 53 participants or 26.63% had experience using VR in learning. Based on the demographic data, it can be concluded that the characteristics of the respondent sample are relatively homogeneous. This study uses an Islamic/Sharia accounting learning experiment using virtual reality-based behavioral simulation (VR-BS) technology. The VR-BS method was developed in two stages: first, the development of VR-BS, in the context of sharia financial literacy; second, testing the effectiveness of VR-BS. The method used to develop the VR system was the waterfall stage model as used in previous VR research (Sari etal., 2023), which is described in Figure 2. There were five stages in its development which are described as follows: Figure 1. Research model. 14 D. RATMONO ETAl. Sony Warsono is a lecturer at the Accounting Department, Gadjah Mada University, Indonesia. He has published various papers in international journals with expertise in accounting information systems, accounting education, information technology systems and business ethics. Currently, he is the Head of the Accountant Professional Education Study Program, Universitas Gadjah Mada. Muhammad Ubaidillah is a student of Professional Accountant Education, Faculty of Economics and Business, Universitas Diponegoro. He is also a lecturer at the Vocational School, Universitas Diponegoro with expertise in accounting education, class instruction, financial reporting and Shariah accounting. Luqman Mulki Wibowo is a student of Professional Accountant Education, Faculty of Economics and Business, Diponegoro University. He has expertise as a consultant on accounting information systems, financial reporting and taxation. ORCID Dwi Ratmono http://orcid.org/0000-0002-0306-5622 Ratna Candra Sari http://orcid.org/0000-0002-3544-4168 Data availability statement The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. References Alavi, M., & leidner, D. E. (2001). 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Paper 12th annual International Conference of Education, Research and Innovation Dates: 11-13 November, 2019. https://doi.org/10.21125/ iceri.2019.2793 Appendix. Questionnaire Variables indicators Virtual reality 1. The realism of the 3D images motivates me to learn. 2. The smooth changes of images make learning more motivating and learning. 3. The realism of the 3D images helps to enhance my understanding. 4. The ability to change the view position of the 3D objects allows me to learn better. 5. The ability to change the view position of the 3D objects makes learning more motivating and interesting. 6. The ability to manipulate the objects (e.g: pick up, cut, change the size) within the virtual environment makes learning more motivating and interesting. 7. The ability to manipulate the objects in real time helps to enhance my understanding. technology quality 1. Using the virtual reality-based e-learning system will enhance my perceived learning effectiveness. 2. Using the virtual reality-based e-learning system will give me greater control over learning. 3. I will find the virtual reality-based e-learning system to be useful in my learning. 4. Using the virtual reality-based e-learning system will enable me to improve my performance in study. 5. Using the virtual reality-based e-learning system will enable me to increase my productivity in study. 6. Using the virtual reality-based e-learning system will make it easier to study. technology accessibility 1. Interacting with the virtual reality-based e-learning system will not require a lot of my mental effort. 2. I will find the virtual reality-based e-learning system to be ease to use. 3. My interaction with the virtual reality-based e-learning system will be clear and understandable. task-technology fit 1. I think that using e-learning with virtual reality will be well suited for the way I like to improve my achievement. 2. E-learning with virtual reality will be a good medium to provide the way I like to improve my achievement. 3. I think that using E-learning with virtual reality will be a good way to improve my achievement. Reflective thinking 1. I will be able to reflect on how I learn. 2. I will be able to link new knowledge with my previous knowledge and experiences when learning through virtual reality. 3. I will be able to become a better learner when learning through virtual reality. 4. I will be able to reflect on my own understanding when learning through virtual reality. 18 D. RATMONO ETAl. Variables indicators Cognitive overload 1. Using VR is boring 2. Interacting with VR-based teaching doesn’t require much mental effort on my part Perceived learning effectiveness 1. I will be more interested to learn the topics. 2. I will learn a lot of factual information in the topic. 3. I will gain a good understanding of the basic concepts of the materials. 4. I will learn to identify the main and important issues of the topics. 5. I will be interested and stimulated to learn more. 6. I will be able to summarize and conclude what I learn. 7. The learning activities will be meaningful. 8. What I learn, I can apply in real context. 9. With VR, this activity really increased my understanding of the formulas discussed 10. With VR, instructions and/or explanations during activities, are very unclear 11. With VR, instructions and/or explanations in learning are very ineffective 12. With VR, this activity really increased my understanding of the topics covered 13. With VR, this activity really increased my understanding of concepts and definitions