Introduction

Classroom management competency refers to the knowledge and skills that teachers must possess to effectively manage the learning environment, thus ensuring a positive and productive atmosphere that supports student engagement, learning, and development (Brandi et al. 2008). Skillful classroom management enables teachers to organize and manage students effectively, thus fostering a positive, safe, and conducive learning environment (Prameswari and Budiyanto 2017). However, many pre-service teachers, who have not yet started their teaching careers but are preparing through educational programs and practical experiences, struggle with selecting and implementing effective classroom management strategies to prevent or mitigate disruptive behaviors (Egeberg et al. 2021; Scott 2017). This inadequacy can be attributed to a lack of authentic practice opportunities in traditional pre-service teacher training approaches.

Although traditional methods like videos (Gold and Holodynski 2017), role plays (Imhof et al. 2016), and discussions (Mitchell et al. 2017) are utilized by teacher education institutions to simulate classroom situations, their effectiveness is limited. For example, the efficacy of simulation can be constrained by spatial limitations and the actors’ own imagination (Gopalakrishnan 2020). While these approaches provide theoretical knowledge, they do not sufficiently foster the practical skills that are required to meet diverse and realistic classroom challenges. The provision of situated learning experience is crucial (Kaufman and Ireland 2016). However, traditional methods have difficulties in creating environments where pre-service teachers can authentically practice. Today’s digital technologies, such as immersive virtual reality (IVR), offer new possibilities and can enhance the authenticity and immediacy of classroom simulations.

Recently, studies have been carried out in IVR under the application of HMD for a realistic experience to pre-service teachers in relation to understanding more about its implication in their work practice (Jensen and Konradsen 2018). Lugrin et al. (2016a), for instance, developed the IVR system, named Breaking Bad Behavior (BBB), which was able to create an immersive virtual classroom environment with semi-autonomous virtual students to provide guided practice in building classroom management skills. A study that incorporated BBB within teacher training programs reported that participants in the experimental group performed significantly better using the IVR system compared to using a video-based method (Seufert et al. 2022). However, other studies conducted later have offered some support for its potential benefits in classroom management training (Gopalakrishnan 2020; Huang et al. 2022b; McGarr 2020).

While existing IVR classroom management systems, such as BBB by Lugrin et al. (2016b) and TrainCM2 by Ye et al. (2019), have addressed the issue of how to train teachers to effectively deal with disruptive student behavior in a controlled setting, they have not responded adequately to the special challenges of large classroom settings, which are a key feature of the public school context serving the larger communities (Delamarre et al. 2021; Huang et al. 2021). Large classes typically fill space-maximizing seating configurations and require that teachers have developed high organizational and management skills. The potential limited applicability of current systems and research findings to these increased class sizes, which are often the result of budget constraints within public school districts, is a notable deficit in the field.

To address this gap, we have developed ClassMaster, an innovative immersive environment specifically designed for managing large classrooms. This pioneering system combines the strengths of existing systems and incorporates the distinctive characteristics of large class sizes. In this study, we explored the specific impact of a fully IVR classroom on the development of classroom management competency among pre-service teachers in a large class context. By focusing on this underexplored area, our research aims to contribute valuable insights to the field of teacher education and classroom management. To this end, we aimed to answer the following research questions:

  1. (1)

    How effective is IVR-based learning compared to video-based learning in improving classroom management competency among pre-service teachers?

  2. (2)

    What is the impact of IVR-based learning influence compared to video-based learning on pre-service teachers’ attitudes and self-efficacy?

  3. (3)

    What is the impact of IVR-based learning compared to video-based learning on pre-service teachers’ reflective behaviors?

  4. (4)

    What are the different benefits and challenges that pre-service teachers perceive in IVR-based learning and the video-based learning?

In the subsequent sections of this paper, we developed the ClassMaster system for training pre-service teachers’ classroom management competency. Additionally, we designed a quasi-experiment to compare the effects of IVR-based learning and video-based learning on the learning outcomes of pre-service teachers. Both groups of participants underwent pre-test, post-test, and delayed test to evaluate their respective outcomes.

Literature review

Classroom management and disruptive behavior

Classroom management refers to the strategies and techniques used by teachers to create a positive and productive learning environment (Emmer and Stough 2001). It involves establishing rules and expectations, managing student behaviors, and promoting student engagement and participation (Glock and Pit‐ten Cate 2021). By employing effective classroom management strategies, teachers can promote students’ engagement, academic achievement, and overall well-being (Tait-McCutcheon 2015). For teachers themselves, their classroom management skills have a direct impact on job satisfaction, teaching outcomes, and teacher-student relationships (İhtiyaroğlu 2018).

However, disruptive behavior, a commonplace and challenging facet of classroom management, can hinder the smooth functioning of the classroom (Reupert and Woodcock 2011). Disruptive behaviors encompass various actions, such as speaking out of turn, being off-task, displaying defiance or disrespect, and engaging in aggression or violence (Tulley and Chiu 1995). Furthermore, the consequences of disruptive behaviors can be detrimental to students’ academic performance, motivation, self-esteem, peer relationships, and mental health, as well as to teachers’ efficacy, job satisfaction, and retention (O’Neill and Stephenson 2012).

Many pre-service teachers often felt ill-equipped and unsupported when managing disruptive behaviors in their classrooms, because they had received insufficient training and guidance in this particular area (Zakaria et al. 2013). Moreover, pre-service teachers reported that disruptive behavior was their main concern and challenge during their practicum experiences in schools (Reupert and Woodcock 2011). Freeman et al. (2014) also identified a significant gap between effective classroom management practices and teacher training, with a minority of teacher preparation programs offering specific courses on classroom management. It is worth noting that in the realm of teacher education, there is a prevalent issue across many universities’ teacher education programs, namely, an imbalanced emphasis on theoretical aspects at the expense of practical training, which often takes a secondary role (Wang 2021). Consequently, pre-service teachers may excel in educational theory but encounter challenges when it comes to adeptly employing various teaching methods. This deficiency in practical skills can significantly extend their adaptation period when they embark on their teaching careers (Voon et al. 2019).

Therefore, there is a clear need for more effective and innovative methods to combine theory and practice in classroom management for pre-service teachers, thus enabling them to apply their knowledge effectively in real teaching settings.

Virtual reality for classroom management training

Pre-service teachers may encounter numerous challenges during teaching practicum (Deng et al. 2018). Therefore, prior simulated training becomes essential to equip them with the necessary skills and strategies to navigate these difficulties effectively. However, traditional training approaches may fall short of providing pre-service teachers with sufficient authentic and realistic opportunities to apply their knowledge and skills in diverse and complex situations (Aboomar et al. 2018; Tondeur et al. 2012). In recent years, virtual reality (VR) has gained widespread application in education (Reisoğlu et al. 2017), as researchers have investigated its potential as an alternative approach to enhance pre-service teacher education (Chen 2022).

The three types of VR according to the degree of immersion and interactivity include non-immersive VR, semi-immersive VR, and immersive VR (Merchant et al. 2014; Radianti et al. 2020). Non-immersive VR uses a computer screen for display and employs traditional interfaces like a keyboard and a mouse for interaction (Furht 2008). Examples would be desktop VR applications such as the Cook District school simulation (Girod and Girod 2006), ClassSim (Ferry et al. 2004), SimSchool (Christensen et al. 2011), and Second Life (Mahon et al. 2010). Semi-immersive VR is associated with the use of a large screen or projector, with the 3D virtual environment displayed on it. This environment is navigable by a tracking device, controller, or gesture-recognition system. Examples include the TLE TeachLivE™ simulation laboratory (Dawson and Lignugaris/Kraft 2017). Although in terms of pre-service teacher skills development, non-immersive and semi-immersive VR can have its potential benefits, products like these might not afford educators with the needed immersion and realism for it to become an authentic learning experience (Dieker et al. 2014; Glaser et al. 2023).

Through the use of VR headsets, IVR creates a sense of presence within the virtual environment by ignoring the real world, thereby delivering an intense level of graphical realism, interactivity, and immersion (Tussyadiah et al. 2018; Wu et al. 2020). IVR makes it possible to simulate behaviors and reactions that closely resemble reality and to overcome limits, for example, those resulting from the typing requirement and offscreen roleplay that are traditionally associated with non-immersive VR, which would enhance realism and flow in the learning experience (Hamilton et al. 2021). For its part, the BBB has been developed ad hoc as an IVR system for training in classroom management, while TrainCM2 incorporates several enhancements. BBB is a real-time 3D virtual simulation of a classroom with 24 semi-autonomous virtual students exhibiting disruptive behavior. It is designed as a supplementary tool for teacher seminars in primary and secondary schools. Meanwhile, TrainCM2 is an IVR training system that offers a training module consisting of five video clips that depict challenging behavior scenarios.

In summary, emerging learning technologies, particularly IVR, have shown promise in delivering practical experience at a reduced cost. This technology can simulate realistic behaviors and reactions, thereby improving the authenticity and flow of the learning experience.

The impacts of large class sizes on teachers

Accommodating the distinct needs of every student is considered a vital responsibility for educators (Klem and Connell 2004). Nonetheless, with the increase in class size, the complexity and number of occurrences within the classroom rise (Doyle 2006), hence challenging teachers to provide individualized attention (Blatchford and Russell 2019a) and maintain classroom order (Harfitt 2012). Large class sizes make it more difficult for teachers to provide individualized attention, feedback, and engagement with students.

Teachers often express that teaching in overcrowded classrooms, characterized by large class sizes, is a daunting and stressful task (Finn et al. 2003). This challenge holds particular significance for preservice teachers, who are more vulnerable to occupational stress owing to their limited teaching experience (Dicke et al. 2014; Harmsen et al. 2019). Consequently, class size is intuitively perceived as a significant source of stress for educators (Saloviita and Pakarinen 2021). In the absence of proficient classroom management, the challenge of large class sizes can magnify pre-existing achievement disparities among students and impede the development of positive teacher-student relationships (Blatchford and Russell 2019b). The enduring discourse on class size has predominantly centered around its correlations with student academic performance (Hattie 2005). Yet, the influence of class size on the dynamics of classroom interactions, particularly through the lens of educators, warrants attention (Blatchford et al. 2012). For instance, Huang and colleagues employed a standardized VR classroom setting to show that both the average heart rates and subjective stress levels of pre-service teachers significantly increased in scenarios involving larger class sizes (Huang et al. 2022a).

Immersive learning in virtual reality

The immersive nature of VR offers unique opportunities to create simulated environments that mimic real-world experiences, thus providing users with interactive and engaging learning environments. By transporting individuals into three-dimensional virtual worlds, VR can facilitate experiential learning, enabling users to actively participate in educational activities rather than passively consuming information (Conrad et al. 2024). This active engagement has been shown to enhance learning outcomes by promoting deeper understanding, retention, and transfer of knowledge (Dalgarno and Lee 2010; Gao et al. 2022).

Moreover, VR has proven to be relatively effective in the improvement of spatial memory and navigational capabilities. It has been established that spatial information provided by immersive virtual environments plays an instrumental role in enabling individuals to encode, store, and recall spatial information (Cadet & Chainay, 2020; Waller et al. 1998). An example is the use of VR-based simulations in the training of medical students for complex surgical procedures to enable them to practice such procedures in a safe and controlled environment (Seymour et al. 2002).

The potential of virtual reality does not limit itself to applications for learning and memory but also extends to emotional processes. A virtual environment with stereoscopic features will usually provoke heightened emotions, where the participants feel as if the reality is augmented (Baños et al. 2008). Such environments can be manipulatively designed to evoke certain emotional conditions and, therefore, become useful instruments in exposure therapy and the regulation of emotion. In fact, treatment of anxiety disorders, phobias, and PTSD has been quite successful through VR-based exposure therapy, since patients can be exposed to their fears in a safe, flexible environment (Parsons and Rizzo 2008). Additionally, VR intervention measures have been extended to improving emotional regulation capacities within clinical environments, in that the interventions help develop ways of managing stress and anxiety adaptively. (Freeman et al. 2017). This, however, may distract participants’ cognitive processing needed for learning, leading to heightened emotional arousal through excessive immersion that impairs performance on subsequent tests for learning outcomes (Parong and Mayer 2021).

The description of the training system

Overview

The ClassMaster training system is an innovative client-server IVR platform designed to enhance teacher training through a unified virtual environment. As depicted by Fig. 1, this system facilitates simultaneous interaction between a trainee teacher, who is immersed in a virtual classroom via an VR headset, and an instructor, who monitors and guides through a 2D graphical user interface. The system’s architecture comprises VR headset for the trainee and a computer for the instructor, interconnected through a networking framework called Photon Fusion. Two monitors are utilized: the HMD displays the trainee’s visual output, while the PC monitor serves as the instructor’s control interface, enabling real-time feedback and interaction. Notably, the virtual classroom accommodates 48 student avatars, simulating a large class size scenario. This configuration offers a comprehensive and convenient deployment solution for teacher training, bridging the gap between theoretical preparation and practical classroom experience.

Fig. 1: System structure.
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Top left: the instructor interacts with the system via a PC monitor displaying a 2D graphical user interface; top right: the trainee teacher, using a VR headset, is immersed in a virtual classroom; bottom left and right: the networking framework, Photon Fusion, connects the VR headset and the PC for real-time interaction.

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Trainee teacher-end

The trainee teacher-end is specifically designed to offer trainee teachers an immersive and interactive virtual classroom experience. The HMD shows the visuals seen by the trainee teachers wearing the VR headset (see Fig. 2). Similar to real-world classroom settings, the trainee teachers can move freely in the virtual classroom by walking around and interacting with the virtual students by asking questions or engaging in dialogue to intervene and resolve the issues. In addition, the system also provides teaching resources such as slides to support trainee teachers in delivering instructions to the virtual students, thereby simulating real teaching scenarios.

Fig. 2: Trainee teachers’ view within the virtual classroom.
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Top left: trainee teachers’ view from the door; top right: trainee teachers’ view from the teacher’s desk; bottom left: trainee teachers’ picking up the lesson plan; bottom right: trainee teachers’ questioning a student.

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Instructor-end

The instructor-end is specifically designed to offer a comprehensive control interface for the instructor (see Fig. 3). This interface, which is displayed on a PC monitor, provides the instructor with the ability to monitor the trainee’s actions, control the behaviors of virtual students, and deliver timely feedback. It features a GUI that offers a range of options and settings to manage the virtual classroom environment effectively, thus ensuring a seamless and intuitive user experience.

Fig. 3: View of the instructor.
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The instructor-end control interface displayed on a PC monitor. The GUI provides the instructor with a comprehensive view of the trainee’s actions and interactions.

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The control panels

The instructor-end control interface comprises two essential components: the Virtual Student Behavior Control panel and the Feedback to Trainee Teacher panel, as illustrated in Fig. 4. These panels serve dual functions, enabling instructors to manipulate the behaviors of virtual students and deliver targeted feedback to trainee teachers.

Fig. 4: The control panels.
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The Virtual Student Behavior Control panel enables instructors to manipulate virtual student behaviors. The Feedback to Trainee Teacher panel facilitates the delivery of tailored feedback to trainee teachers.

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With the Virtual Student Behavior Control panel, it is possible for the instructor to manipulate the behaviors of the virtual students. The instructor can navigate around the virtual classroom, change viewpoints, and turn some behaviors of the virtual students on or off using the arrow keys on the keyboard and the mouse wheel. If there are, the teacher can choose one of them by clicking on the student number at the top right of or right above the virtual student that corresponds to them. The teacher can then click on the buttons available to have the selected virtual student in one of these states: wander in class, fall asleep, use the cell phone, answer a question, interact with other students, or fight. The instructor can stop all the behaviors of the selected virtual student using the “Terminate Problem Behavior” button.

On the other hand, the Feedback to the Trainee Teacher panel has been designed to deliver relevant prompting and feedback to trainee teachers under the platform. It allows guiding instructors to give specific feedback in relation to the performance of trainees in managing the virtual classroom. All guidance and feedback are in line with the principles of scaffolding with intent to support trainee teachers’ learning at their respective optimum level of challenge (Wood et al. 1976). Further, feedback is given into the account of some positive and negative appraisals of the performance of the trainee teacher at present, along with the relevant suggestions to help them tackle specific problem behaviors presented by the virtual students. Positive feedback recognizes the trainee teachers’ reasonable and workable measures, while negative feedback clearly indicates the adjustments needed in the current strategies of the trainees. Meanwhile, the specific tips in the Feedback panel illustrate the guidance into diverse problem scenarios, empowering the trainee teachers with a finer capability to better their classroom management skills.

Modeling classroom settings and virtual students

The training system features a highly polished and well-modeled scene that closely simulates the layout and features of a full-size classroom. The use of Maya allows for a good amount of detailing in the creation of the desks, chairs, bookshelves, and other hard surface models that constitute the scene that is used within the virtual classroom. In addition, the virtual classroom’s layout mirrors the common horizontal and parallel arrangement of desks and chairs typically found in public school classrooms. To facilitate realistic classroom management training, the seating capacity is expanded to accommodate up to 48 virtual students, allowing trainee teachers to practice managing larger classes effectively. Moreover, the virtual students’ appearances are tailored by ZBrush to reflect Asian characteristics, including varying hair colors, skin tones, and facial details. Each virtual student has a unique personal appearance and a name tag to enable easy identification by trainee teachers.

Student behavior settings

In the ClassMaster training system, students’ behavior settings include both introverted and extroverted problem behaviors in the classroom, following Hinshaw’s classification (1992). Five specific problem scenarios are selected based on the most common behaviors observed in primary and secondary school classrooms. These scenarios include three introverted problem behaviors: dozing off, daydreaming, and using mobile phones, as well as two extroverted problem behaviors: whispering and fighting during class. Additionally, the system incorporates the common actions of students, like answering questions, sitting quietly, and writing. To control these behaviors, the system utilizes a character model representing 48 virtual students, each associated with an Animator component. By integrating user interface controls within the Unity development environment, instructors can easily manipulate and control the actions of the virtual students through simple interactions such as clicking a button.

Software and hardware

The training system was developed using Unity 2021.3.26f1 as the primary software platform, integrating both VR headset and traditional computing hardware. For the trainee teacher-end, a ByteDance PICO 4 headset was employed, featuring a Qualcomm Snapdragon XR2 Gen1 processor, 2160 × 2160 resolution per eye, 105° field of view, and 8GB RAM. The instructor-end was rendered on a high-performance PC equipped with an Intel i9-13900K 3.40 GHz CPU, 16 GB of RAM, and an NVIDIA® T400 Graphics card. To facilitate real-time interaction between the trainee teacher (client) and instructor (server) endpoints, Photon Fusion was implemented as the networking framework, ensuring robust and flexible multiplayer functionality.

Methods

Participants

The study involved 57 pre-service teachers (16 men and 41 women, aged 22 to 26 years old, with an average age of 23) from a teacher education institution in Jiangsu Province, China. These participants, drawn from educational technology majors across both undergraduate and graduate levels, were recruited through notices on the university’s bulletin boards and announcements on social media platforms. All the participants have already undertaken educational internships, and all have experience with both IVR and video-based learning.

Prior to their participation, informed consent was secured to guarantee their comprehensive understanding of the research’s objectives and their expected contributions. The study was approved by the institutional review board of the first author’s university. Ethical considerations were taken into account in the design, conduct, and reporting of the study.

This study employed a quasi-experimental design, randomly assigning the participants into two groups: the IVR group (n = 33) and the video group (n = 24). The video group received instruction through video-based learning, while the IVR group used the ClassMaster training system. Moreover, participants provided informed consent by signing a consent form before the experiment and received a nominal learning allowance as compensation for their participation in all learning and assessment activities after the experiment.

Learning materials

Introductory classroom management video

To establish a conceptual foundation for classroom management, a concise 10-min introductory video was developed. This video elucidates the core principles and philosophical underpinnings of effective classroom management, aiming to enhance educators’ foundational understanding. By focusing on these essential elements, the video provides a comprehensive introduction to the subject, preparing viewers for more in-depth exploration of classroom management techniques.

The ClassMaster training system

The ClassMaster training system was designed to train trainee teachers on how to manage problem behaviors in large classes, allowing both trainee teachers and instructors to log in. Once ready, participants (pre-service teachers) initiated the formal training by clicking the “Start Simulation” button in the system to commence the formal training. They were required to conduct simulated teaching sessions and address the problem behaviors of virtual students during the lesson. Whenever they encountered difficulties, the instructor provided specific feedback and guidance, with the training sessions averaging about 15 min in duration.

Problem behavior management video

We developed a 15-min instructional video addressing student problem behavior management. The video featured six scenarios mirroring those in the ClassMaster training system. Each scenario was followed by a designated reflection period for participants to consider potential solutions. Subsequently, the video presented corresponding management strategies, aiming to enhance participants’ understanding and mastery of effective classroom management techniques.

Procedure

The experiment consisted of four stages, as illustrated in Fig. 5.

Fig. 5: Flowchart of the experimental procedure.
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Overview of the four stages (Stage 1, Stage 2, Stage 3 and Stage 4) in the experiment.

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Stage 1: Before the experiment, participants were asked to undertake a classroom management competency test, alongside completing a questionnaire designed to assess their self-efficacy and attitudes pertaining to classroom management.

Stage 2: In the experiment, 57 participants were randomly assigned to either the IVR group or the video group. The experiment commenced with all participants, regardless of group allocation, viewing a 10-min introductory classroom management video. Following this, the participants in the IVR and video groups engaged with different learning materials, as shown in Fig. 6. Those in the IVR group used the ClassMaster training system for approximately 15 min, whereas the participants in the video group learned the 15-min video on problem behavior management.

Fig. 6: Training scenarios of the two groups.
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a The IVR group engaged with the ClassMaster training system; b the video group viewed the video on a PC monitor.

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Stage 3: Following the experiment, both groups took the classroom management test and fill out a reflective behavior questionnaire.

Stage 4: 20 days after the training, both groups completed the classroom management competency test, a questionnaire on self-efficacy and attitudes toward classroom management, and participated in semi-structured interviews.

Instruments

Classroom management competency test

When developing the questionnaire, we invited two experts with over ten years of experience in classroom management and teaching to formulate the questions. These questions described typical instances of student misbehavior, such as eating snacks and sleeping in class. Pre-service teachers were then asked to elaborate on their strategies for addressing these situations. These inquiries were presented at the pre-test, post-test, and delayed post-test stages. Clear scoring criteria and guidelines were established for each short-answer question. The final agreed-upon grading criteria are based on five aspects: (1) it fosters the physical and mental development of students, (2) it does not disrupt the order of the classroom or students’ learning, (3) it demonstrates respect for students, (4) it is feasible, and (5) the method allows for students to change or rectify their behavior. Each item is scored on a scale from 0 to 15 points.

Before formal implementation, the questionnaire underwent a pre-test to assess its comprehensibility and the appropriateness of question difficulty and scoring criteria. Two education management experts were invited to review the questionnaire, using agreed-upon scoring standards. The Spearman correlation coefficients for scoring before, after, and delayed after testing were 0.71, 0.81, and 0.85, respectively. These coefficients indicate significant consistency among assessors throughout the scoring process.

Classroom management self-efficacy questionnaire

The classroom management self-efficacy questionnaire (CMSEQ) was developed based on the CM/discipline subscale of the teacher efficacy questionnaire which was created by Emmer and Hickman (1991). Four items were chosen from this subscale to specifically measure classroom management and discipline. Participants were asked to rate their level of agreement with statements related to managing student behavior and focusing student attention on a 5-point Likert scale, with 1 indicating “strongly disagree” and 5 indicating “strongly agree”. Higher scores on the CMSEQ indicate a higher level of management self-efficacy. The internal consistency of the CMSEQ, as measured by Cronbach’s alpha (α), was found to be acceptable at 0.77.

Learning attitudes toward classroom management

The scale used in this study was adopted from the validated Learning Attitudes Scale developed by Hwang and Chang (2011). The attitude of the participants towards classroom management was obtained by selecting five items from the original scale. The latter were prompted to answer such statements as “I think learning classroom management is meaningful and worthwhile” on a 5-point Likert scale, where 1 corresponded to “strongly disagree” and 5 corresponded to “strongly agree”. Their responses had a Cronbach’s alpha value of 0.70.

Reflective thinking scale

Reflective thinking, which “helps a teacher evaluate his/her instructional decision” and allows the teacher to “further refine their practices, thus enhancing teaching effectiveness,” was measured using the three-item scale (Holmes et al. 2015; Jung 2012). The scale was adopted from Ai-Lim Lee et al. (2010) and was used to measure the tendency of participants to reflect on their experience in IVR-simulated teaching or watching teaching videos. It is on a 5-point Likert scale, ranging from 1 for “strongly disagree” to 5 for “strongly agree”. For the test, the Cronbach alpha value was 0.81.

Semi-structured interviews

Twenty days post-training, semi-structured online interviews were conducted to delve into the enduring effects of IVR classrooms and video learning on the participants’ classroom management competency. The interviews encompassed four specific inquiries: (1) Do you believe that the impact of this learning modality on your classroom management skills will be enduring? (2) In what aspects do you find this learning method most beneficial, and what are the most important things you have learned? (3) What have you learned the most from this experience? (4) Would you be interested in engaging in this form of learning in the future? The purpose of these interviews was to gather qualitative data from the participants, shedding light on the long-term implications of IVR and video-based learning on their pedagogical skills in classroom management.

Apparatus

The experiment was implemented in two hardware setups to support the video and IVR conditions separately. In the IVR condition, the client device used a ByteDance PICO 4 headset that ran a Qualcomm Snapdragon XR2 Gen1 processor with a resolution of 2160 × 2160 per eye and 105° field of view. The device also had 8 GB RAM. This headset was used with a high-performance server station, including an Intel i9-13900K 3.40 GHz CPU, 16 GB RAM, and an NVIDIA® T400 Graphics card, to support rendering and processing of the virtual environment without any lag. The video group setup was relatively simple: using a laptop PC equipped with an Intel i5-13500H CPU, the device had a 15.6-inch screen with a resolution of 1920 × 1080 pixels.

Data analysis

A mixed-methods design was employed in this study. All data were analyzed using SPSS software version 26.0. First, the normality of the data was assessed using the Shapiro-Wilk test, which indicated that only the post-test data for reflective thinking did not follow a normal distribution. Second, a one-way ANCOVA was conducted to compare the pre-test, post-test, and delayed test scores of the IVR group and the video group, with the pre-test scores as the covariate, and the post-test or delayed test scores as the dependent variable. The two groups (IVR group and video group) served as the independent variables. Third, a Mann–Whitney U test was performed to determine if there was a significant difference in reflective thinking between the IVR group and the video group.

In addition to the statistical analyses, interview data were analyzed and interpreted to explore learners’ training experiences and their perceptions of the ClassMaster training system. The interview data were transcribed verbatim in Mandarin and carefully evaluated by two researchers to identify key points and categorize them into overarching themes. Through iterative comparison of concepts, four categories were derived from the interview data. Selected representative comments have been translated into English and are described in the results section.

Results

Classroom management competency

The result (F = 2.013, p = 0.162 > 0.05) of Levene’s test for equality of variances showed no significant level, thus specifying that the assumption of homogeneity of variances in the groups was satisfied. One-way ANCOVA was then performed. As shown in Table 1, after excluding the effect of the pre-test scores, a significant difference was observed in the post-test scores of the two groups (F = 0.286, p = 0.595 > 0.05). The adjusted mean and standard deviation of the video group were 13.72 and 1.97, while those for the IVR group were 13.93 and 1.45. The effect size was small (η2 = 0.005). These results indicated that no statistically significant difference was observed in post-test scores of classroom management competency between the IVR group and the video group.

Table 1 Results of ANCOVA on classroom management competency.
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The result (F = 1.864, p = 0.178 > 0.05) of Levene’s test for equality of variances showed no significant level, thus specifying that the assumption of homogeneity of variances in the groups was satisfied. One-way ANCOVA was then performed. As shown in Table 2, after excluding the effect of the pre-test scores, a significant difference was observed in the delayed test scores of the two groups (F = 12.550, p = 0.001 < 0.01). The adjusted mean and standard deviation of the video group were 12.36 and 1.78, while those for the IVR group were 13.73 and 1.51. The results indicated that a substantial proportion of the variability in delayed test scores of classroom management competency could be attributed to the group variable, with a large effect size (η2 = 0.189).

Table 2 Results of ANCOVA on the delayed test of classroom management competency.
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Classroom management self-efficacy

The result (F = 0.004, p = 0.949 > 0.05) of Levene’s test for equality of variances showed no significant level, thus specifying that the assumption of homogeneity of variances in the groups was satisfied. One-way ANCOVA was then performed. As shown in Table 3, after excluding the effect of the pre-test scores, no significant difference was observed in the classroom management self-efficacy of the two groups (F = 1.340, p = 0.252 > 0.05). The adjusted mean and standard deviation of the video group were 3.75 and 0.43, while those for the IVR group were 3.86 and 0.39. The effect size was small (η2 = 0.024). No sufficient evidence was found to support the presence of a significant difference in delayed test scores for classroom management self-efficacy between the IVR group and the video group.

Table 3 Results of ANCOVA on the delayed test of classroom management self-efficacy.
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Learning attitudes toward classroom management

The result (F = 2.944, p = 0.092 > 0.05) of Levene’s test for equality of variances showed no significant level, thereby specifying that the assumption of homogeneity of variances in the groups was satisfied. One-way ANCOVA was then performed. As shown in Table 4, the IVR group exhibited a significantly higher attitude toward classroom management compared with the video group (F = 9.229, p = 0.004 < 0.01). The adjusted mean and standard deviation of the video group were 4.29 and 0.42, while those for the IVR group were 4.57 and 0.34. The results showed that the IVR classroom could better enhance students’ learning attitudes than videos, with a large effect size (η2 = 0.146).

Table 4 Results of ANCOVA on the delayed test of learning attitudes toward classroom management.
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Reflective thinking

As shown in Table 5, the difference in reflective thinking between the two groups was not statistically significant (U = 361.00, p = 0.564 > 0.05). The mean and standard deviation were 4.26 and 0.43 for the video group, and 4.14 and 0.66 for the IVR group, respectively. These results suggest that reflective thinking was comparable between the IVR group and the video group.

Table 5 Results of the Mann–Whitney U test on reflective thinking.
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Semi-structured interview

The interview results of the 57 interviewees are summarized in Table 6. The majority of participants held a positive attitude toward IVR classroom and appreciated the following top three benefits: “innovative and interesting”, “positive impact and enduring effects”, and “practical application and skill development”.

Table 6 Coding results for the interviews.
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In terms of “innovative and interesting” and “positive impact and enduring effects,” the majority of interviewees from the IVR group revealed that the realistic and immersive nature of the virtual environment left a strong impression on them, thereby enhancing their learning experience and making them recall the acquired knowledge more easily in real teaching situations. For instance, A1 mentioned, “The IVR classroom gave me more real teaching experience. The problem behaviors of students were random, which could also test my classroom management skills in teaching.” A20 stated, “Virtual class gave me a strong sense of experience. I felt like I was in a real class, and I could interact with students and the surrounding environment. This process had left a deep impression on me.” A21 also commented, “The creation of a virtual scene, compared with the blunt textbook, was more vivid!” In contrast, only a minority of participants in the video group felt that video-based learning had a sustained impact on their classroom management competency.

With regard to “practical application and skill development,” many participants from the IVR group pointed out that through practical exercises in the IVR classroom, they were able to apply their learning outcomes and deepen their understanding of classroom management. They believed that this experiential learning approach facilitated a better integration of knowledge and practice. For example, A3 mentioned, “I think through this simulation experience, I really learned the knowledge of classroom management, which would be translated into my future practical classroom management experience.” A6 also pointed out, “I could further test my understanding of classroom management by using immersive classrooms and through practice, and I could deepen my understanding of the knowledge as well.” However, participants from the video group generally believed that although teaching videos provided some good strategies and methods, the content of the videos was easily forgotten. For instance, B9 stated, “A significant effect immediately generated after watching the video, but after a period of time, I forgot most of the content.”

Regarding “other feedback,” a few participants expressed their hopes to promote the training methods that they used and provided relevant suggestions, such as extending the duration of the training or increasing the frequency of training sessions. They believed that these changes would allow more comprehensive learning and better retention of the knowledge and skills gained from the training.

As mentioned above, a predominant view emerged within the IVR group that immersive virtual classroom experiences exert a substantive and enduring effect on their classroom management competency. Participants broadly acknowledge the immersive nature of the IVR simulation as a catalyst for deeper learning, asserting that the authenticity and interactivity inherent to the medium fostered vivid retention of classroom management strategies. This heightened realism was frequently cited as instrumental in anchoring the knowledge gained, suggesting a potential for long-term influence on classroom management practices.

The interviews underlined the long-lasting effects and deep impressions most frequently cited by the participants in the IVR group. This is in line with research suggesting that immersive learning environments are likely to provoke enhanced emotional engagement and deeper processing of information, with the consequential contribution to the creation and maintenance of stronger memory (Grigorovici and Constantin 2004). The richness of the experiential and sensory stimulation from IVR promises that learning is likely to be even more compelling and interactive, not only facilitating immediate understanding but also promoting long-term retention through the anchoring of knowledge in memorable experiences (Schmidt et al. 2023).

In contrast to IVR, however, video-based learning is capable of presenting information in a lucid and vivid way that assists immediate understanding. However, it cannot offer the same immersiveness and interactivity as IVR. This might be a reason for the observed drop of retention over time with the participants in the video group. Video-based learning is passive, offering the learner no active participation or contextual immersion, which could result in lesser memory trace durability and hence make it difficult for the learners to recall information over long periods.

To conclude, while IVR and video-based learning both are effective to support short-term learning, the immersive and interactive nature of IVR supports a much more conducive setting for long-term retention and recall. This is further supported by interview data tending to underpin the innovativeness, realism, and immersion of IVR, factors that are directly related not only to immediate learning but also to knowledge retention over time.

Discussion

This study examined the effectiveness of the IVR training system in improving the classroom management ability, self-efficacy, attitude, and reflective thinking of preparatory teachers in large class teaching environments. Therefore, this research, in the quest to give an overall evaluation, compared findings obtained through the IVR system and those obtained through the micro-lesson video approach in the determination of the best method to enhance these crucial teaching skills.

For our first research question, the data revealed that both the IVR and video-based methods effectively improved the outcome learning immediately for classroom management competency. At the same time, the delayed post-test was significantly in favor of the IVR group, which indicates that over time the knowledge retention of classroom training supported a positive benefit from IVR. This aligns with previous research highlighting the benefits of immersive virtual environments for deeper learning and knowledge consolidation (Ekstrand et al. 2018; Menin et al. 2018; Parong and Mayer 2018). The increased motivation, engagement, and authenticity supported by the IVR simulation likely helped produce a deeper level of understanding and assimilation of the classroom management strategies in this condition, leading to improvements in long-term recall.

Related to our second research question, self-efficacy for classroom management was similar between the IVR and video conditions. This is in marked contrast to other findings that report an improved sense of classroom management in pre-service teachers exposed to immersive virtual environments (Huang et al. 2022b). Differences between the studies could be the different lengths and intensity of the intervention or the differences in sample characteristics, like their prior experience and cultural background. The relatively high levels of self-efficacy in both groups point to the training interventions having had a positive influence on the perceived competence of the participants in managing classroom dynamics.

The IVR group showed an advantage regarding attitude toward classroom management as well, with attitudinal perceptions much higher than those in the video group. The results suggest that a virtual environment, enhanced with abilities of interactivity and immersion, facilitated pre-service teachers in their perception and appreciation of effective classroom management strategies. This is consistent with prior research arguing that IVR learning can create more enjoyable and meaningful experiences, ultimately enhancing learners’ interest and satisfaction (Colegrove and Westergard 2021; Huang et al. 2022b).

Scores on the third research question, relating to reflective thinking, likewise did not significantly differ between the two groups; both the video and IVR groups showed comparable capacities for reflecting on what they have learned—that is, both learning modes provided opportunities for the trainees to look back on their learning experiences and transfer this knowledge to actual teaching. Although it is not statistically significant, the slightly higher mean score for reflective thinking in the IVR group showed a trend that participants experiencing the IVR classroom system could have greater reflective thinking ability. That is, the IVR classroom could foster reflective thinking ability by providing observation, practice, feedback, and evaluation during simulations of teaching.

The qualitative findings from the interviews on the fourth research question showed that most subjects of the IVR group appreciated the authenticity and interactivity of the virtual environment, which made them feel as if they were in a real classroom. In the case of a “positive impact and enduring effects,” participants in the IVR group had more experiences to write about than those in the video group. This seems to indicate that they had a deeper understanding after the immersive experience than those in the video group. Moreover, among the IVR group, the practical exercises held within the virtual classroom were found to help in achieving the learning outcome by developing their classroom management skills.

In conclusion, the integration of quantitative and qualitative findings suggests that the initial advantages of the IVR classroom system in developing classroom management competency will transition into stable and enduring effects over the medium to long term, particularly in terms of knowledge retention and positive attitudes. These findings contribute to the growing body of research on the effectiveness of immersive virtual environments for teacher education and professional development, strengthening the evidence that IVR simulations can provide a valuable complement to traditional video-based or lecture-based approaches. Further research is needed to explore the underlying mechanisms and contextual factors that influence the long-term impact of IVR training on pre-service teachers’ classroom management skills and overall professional development.

Conclusion

This study examined the comparative effectiveness of an IVR-based learning approach and a video-based learning approach in developing pre-service teachers’ classroom management competency, self-efficacy, attitudes, and reflective thinking in a large class context. The findings offer valuable insights into the potential of IVR to enhance pre-service teachers’ preparedness for real-world classroom challenges in large class settings, informing evidence-based teacher training and education.

Theoretical and practical implications

Notably, while the study observed no significant differences in classroom management self-efficacy and reflective thinking between the IVR and video groups, the nuanced advantages of IVR—rooted in its immersive and interactive capabilities—highlight the potential for a more profound engagement and understanding of classroom dynamics. From a theoretical perspective, these outcomes contribute to the evolving discourse on the pedagogical affordances of IVR in teacher education, challenging traditional paradigms and suggesting new pathways for embedding technological innovations in pedagogical strategies.

Practically, the implications of our research extend to curriculum designers and teacher educators, advocating for a judicious integration of IVR simulations to complement conventional training methodologies. The distinct benefits of IVR, as revealed through our study—particularly in terms of enduring effects on knowledge retention and the development of favorable attitudes towards classroom management—underscore the value of experiential learning environments that mimic the complexities of real-world teaching scenarios.

Furthermore, our findings call attention to the necessity of ongoing research and development to refine IVR platforms for optimal effectiveness in teacher training programs. As this study illuminates, the path toward fully leveraging the potential of IVR in education requires a collaborative effort among researchers, technologists, and educators to navigate the challenges and exploit the opportunities presented by this innovative teaching and learning tool.

In light of such insights, a role for full IVR can be noted beyond educational gadgetry; rather, it presents a transformation in bridging future educators with the dynamic demands of today’s classrooms. The present research therefore contributes considerably to the knowledge regarding how technology-enhanced learning environments can enrich teacher education and is laden with lessons both for theoretical exploration and practical application in the quest for the elevation of classroom management competencies among pre-service teachers.

Limitations and recommendations

Despite these promising findings, the study has some limitations. Over-reliance on self-report measures and interviews is one of the major limitations, which may fail to capture objective information that describes the actual behaviors and physiological responses of participants. Future research should consider incorporating physiological measurements to obtain more comprehensive data. Second, the study has not measured the classroom management competency of participants in the actual teaching setting; this needs to be part of future research and considered for direct observation and evaluation in authentic classroom contexts. Another limitation is the unequal number of participants concerning gender, as significantly more participants are women than men. This gender imbalance may affect the generalizability of the findings, and future research should have a better gender ratio so that the findings can apply to more diverse subjects.

The implications are so far-reaching, not just with respect to immediate educational output but also in holding promise for a bounteous future for IVR in teacher training programs—most specifically, in large class contexts. To open up further frontiers of the field, future studies are suggested on examining the long-run impacts of IVR learning, probing the underlying mechanism of its effectiveness, and assessing the application of this method in a variety of educational situations. In so doing, the limitations can be addressed to enrich our understanding of IVR in teacher education.