Simulator-mediated learning: enhancing accounting teaching-learning processes in higher education

Abstract

The literature has identified a significant dropout of students at the transition from high school to higher education, especially in areas related to mathematics. Therefore, new didactic tools have been identified to help teachers in the process of knowledge transfer, as simulators are an increasingly popular tool in their integration into educational environments. However, there is a lack of relevant research on the use of simulators in accounting education, which underlines the need for this study in a little explored area. For this reason, a study was conducted to analyze the impact perceived by university students in the city of Medellin on the use of a simulator to calculate the depreciation rate of assets. This was an exploratory study with a mixed approach, in which 45 students from a public university in the city participated. The results reflect the positive effects of the use of simulators in the classroom, such as consolidation of knowledge, agility in performing application exercises and better understanding of the content, allowing the conclusion that these technologies effectively mediate the teaching-learning processes in higher education. The study demonstrated the positive impact of simulator-mediated learning in higher education for the teaching of accounting subjects, with a high level of acceptance by students, increasing student motivation, content comprehension, and participatory behavior in the classroom. Although the study highlights the effectiveness of simulators as a teaching tool, it also indicates the need for further research on issues such as implementation costs and affective impact.

Keywords:

• Active learning
• mathematics teaching
• higher education
• educational assessment
• information technology

REVIEWING EDITOR:

• Shuyan Wang, The University of Southern Mississippi, United States

SUBJECTS:

• Technology in Education
• Higher Education
• Study of Higher Education

1. Introduction

Mathematics is a transversal teaching discipline at different educational levels: primary, secondary and higher education, which has led to the interest of the scientific community to understand in depth the factors that influence students’ motivation to study mathematics, revealing not only cognitive aspects, but also affective and intentional aspects of individuals. Studies have focused mainly on the processes of primary and secondary education, with interest in higher education emerging only in recent years (Fernández-Cézar et al., 2016; Krukowski et al., 2021).

However, there are learning disabilities that affect how a student cognitively receives and processes information, and students with this condition may have difficulty learning skills such as reading, writing, and arithmetic. High dropout rates from university mathematics studies have even been observed repeatedly, resulting in psychological and economic costs for individuals and society (Heusel et al., 2023; Ingkavara & Yasri, 2019). In Medellín, in mathematics, more than half of the students who took the state tests in 2022 did not have the basic and necessary competencies to perform adequately in higher education (Medellín Cómo vamos, 2023).

The transition from high school math to college math is a challenging process for many students, which is reflected in significant dropout rates during the first year of college (Geisler et al., 2023). Therefore, the literature has identified the need to improve outcomes in mathematics education using technology in active learning, considering the necessary conditions to achieve effective learning with the support of platforms (Lopez-Caudana et al., 2020).

Due to the importance of mathematics and the constant changes that the world is currently experiencing with the advent of the so-called ‘information and knowledge society’, training in this field has had to adapt to the emergence of new tools that allow effective pedagogical processes to be carried out through the incorporation of information and communication technologies (ICT) and that stimulate dynamic learning (Téliz, 2015; Thurm & Barzel, 2022)

Not surprisingly, given the emergence of these new technologies, a considerable number of spaces have been promoted to promote the teaching of the so-called hard sciences, becoming a complement to traditional teaching processes, and the incorporation of statistical and mathematical tools into curricula, through which it is possible for students to apply in practice what has been learned conceptually in classrooms (Alabdulaziz, 2021; Steegman et al., 2016).

Mathematics and various other disciplines and sub-disciplines of knowledge have had to reshape ICT-mediated teaching strategies, not only because of the current global dynamics, but also because of the need to train more competent and comprehensive professionals before entering the labor market. Consequently, various fields of knowledge, such as accounting, have also heeded the scientific literature in the face of the underlying demand to incorporate these new technologies in classrooms (Garcés et al., 2019), a position with which authors such as (Barreto-Carvajal et al., 2011) agree, i.e. there are benefits of adopting these technologies in the creation of cognitive and communicative capacities in future professionals in this field of administrative sciences (Ran et al., 2021).

It is necessary to explore and understand its dimensions, benefits, and specific applications in the context of mathematics, highlighting the innovation of ICT in modern education as a powerful approach that has received a positive response worldwide (Alotaibi & Kumar, 2019).

Thus, in a society where ICTs have already facilitated significant changes in the way people live, the challenge of the adoption of ICTs by institutions in the educational system is to address the ways in which the relationship with a digital era will occur, analyzing the existing policies and available technologies, as well as the pedagogical models and practices to be used in this new training scenario, which is becoming increasingly relevant (Pablos et al., 2019).

The use of simulators in the teaching of mathematics, particularly in fields such as accounting and finance, has proven highly beneficial. As (Trigo & Varajão, 2011) illustrate, these simulators allow students to apply concepts practically in realistic environments, providing them with the opportunity to become familiar with real regulations and practices that would otherwise be reserved for official use. In addition, recent research, such as that of Caballero et al. (2021), indicates that the use of simulators strengthens the development of specific competencies in finance and accounting, significantly improving the acquisition of skills needed in these fields. This methodology not only enriches the educational process, as evidenced by Antoniuk et al. (2021) with their business simulator focused on personal financial management competencies, but also allows personalized learning, promoting the active application of mathematical and accounting concepts in real contexts.

However, even though universities and educators have adopted various technological tools in the curriculum, it has been noted that the acceptance of these tools by students is not sufficient (Zogheib et al., 2015), which is necessary to measure the impact of new pedagogical proposals. However, there is a notable lack of studies related to the use of learning simulators in the field of accounting, and even fewer focus on the evaluation of students’ perceptions in this regard. In this context, the present study addresses the issue of the use of simulators in accounting education with the purpose of analyzing their application in the classroom, within the teaching-learning process, and determining the benefits derived from this practice. In addition, it is hypothesized that simulators can increase student motivation and encourage more active participation in the educational environment, thus maintaining their value as pedagogical tools.

Therefore, the aim of this manuscript is to present the results of a study conducted to answer the following question: What is the perception of university students in the city of Medellin on the use of simulators in mathematical competency training courses?

2. Theoretical foundation

In an increasingly globalized world, ICT has become an increasingly important tool and has gained greater influence in various aspects of life, such as education. In this field, it is necessary to adopt new strategies in the teaching practices used in classrooms that can be adapted to the current demands of technological tools. In this way, it is necessary to analyze the advantages and benefits that the integration of ICT can offer as a didactic resource and as a means of knowledge transfer (Gelves & Moreno, 2012).

In this sense, simulators in education are a mode of teaching whose main function is to help teachers in the process of transferring knowledge, which is why there is interest in integrating technology in teaching. These simulators are used in the classroom where students can interact with a model of some aspect of the real world, allowing them to manipulate parameters or input variables, execute or run models, and display results (Escamilla, 2000).

Their use as a useful tool in the teaching and learning process represents an approach both to concept formation and knowledge construction, and to the application of knowledge to contexts that are, for one reason or another, inaccessible to students. However, these simulators are not widely used in curricula related to mathematics and engineering to support the understanding of some basic concepts within these branches of knowledge (Contreras et al., 2010); this may be due to issues related to the technological infrastructure of educational centers, as well as the lack of knowledge about the practical applicability of these software programs within the respective subjects.

Mathematics is a clear example of a subject in which simulators can be integrated because students have different ways of acquiring knowledge and traditional teaching does not lead to the best student performance in this area. For this reason, it is necessary to include these tools in the learning process, providing students with an option in which they can transfer knowledge to the world around them, as this is a more effective way to introject the acquired knowledge (C.O.R.D., 2003).

The theory of mathematics in context encourages students to learn concepts as useful acquisitions and not as a complex matter, which supports the concept of integrating new strategies in the teaching process. Repeated cases of learning resistance to mathematical concepts and situations of analysis occur at all levels of education in professional careers. Thus, the contextual approach to mathematics is an opportunity for the application of simulators, since both aim to make students rethink their environment and focus their knowledge and professional skills in real situations using technology (Bravo-Bohórquez et al., 2016).

This has a relevant impact on the training of engineering professionals who use mathematics and basic sciences as a basis for developing their skills, especially when it is a determining factor for students to remain in an academic program, a matter that also affects the number of professionals trained and competent to face the needs and challenges of industry. Therefore, it is important that institutions adopt new strategies and teaching dynamics to face these types of challenges, venturing into the design of courses and the use of technological tools based on mathematical modeling as a viable way to train and take advantage of the new skills required by these professionals (Gallegos, 2017).

Some relevant examples are available for the American context, where a STEM (Science, Technology, Engineering and Mathematics) approach is applied through ‘Just in Time Teaching’ for first year engineering students (Klingbeil & Bourne, 2016), and for the European context, where soft skills are incorporated in engineering training with generic skills, where modeling and simulation of real phenomena can be included (Pedretti & Nazir, 2011).

Different software on the market, such as Excel and GeoGebra, can simulate different situations in different branches of engineering, finance and mathematics in general, allowing a better connection with the users through very agile and graphical means. In addition, MATLAB and R, programming languages with a focus on mathematics and statistics, allow users to create complex algorithms and perform estimations themselves (Celemín & Ángel, 2018).

Although this research topic has not been widely addressed, there are some experiences in which simulators have been used as teaching-learning tools, such as the use of ICT in virtual instrumentation for the development of physics laboratories used in engineering classes, where students can access the network in real time. These laboratories are developed considering the real limitations of these spaces and time, improving the availability of spaces with different schedules, and saving on operating costs (Macías, 2007).

In this regard, Virtual Mathematics Laboratories (Laboratorios Virtuales de Matemáticas, LVM) is a computer system with Internet access that integrates computer-aided engineering to solve different mathematical equations, graph them and obtain statistics, helping students understand how to improve their knowledge of concepts at their own pace with as many attempts as necessary, without any pressure, serving not only as a tool for engineering but also contributing to the teaching of basic sciences (Medina et al., 2011).

Another case applicable to the study of mathematics is the Logic.ly simulator, as it facilitates the understanding and application of theoretical content in the field of electronics; students agree that it is a useful, innovative, and efficient tool in the learning process, and therefore the integration of this type of practical teaching technology is recommended (Rueda & Silis, 2018). Another study (Contreras et al., 2010) showed that the use of simulators in the educational environment for basic science classes in an engineering department helped students understand mathematics, physics, and programming concepts because the tools allow students to participate in real and meaningful activities. However, teachers continue to implement a traditional program with little integration of these technological tools.

An example of the integration of this type of technology in Latin America has been developed by Gallegos (2017); a series of simulation tools and various technologies have been integrated for implementation in practice in engineering programs at Tecnológico de Monterrey, such as the use of sensors to model real situations with the application of differential equations in an experimental environment, making it possible to measure and model temperature, motion and voltage, apply real data, fit models and verify concepts (R. R. Gallegos & Rivera, 2015). Open-ended simulation software such as Tracker, MATLAB’s Simulink for control concepts (Silva, 2011), remote laboratories, and dynamic simulation software such as Vensim and Stella (Bourguet, 2005; Fisher, 2011) are also available.

In the study carried out by Canesco (2012), a simulator for the understanding and application of financial concepts focused on budgeting was developed, promoting it as a didactic tool that allows the integration of different scenarios and economic aspects; the simulator was designed to give more tools to teachers responsible for budgeting topics, so that they can integrate the concepts in a practical way.

This type of simulator can also be adapted to industrial and business profiles, such as the financial simulator for the development of SMEs, where there is a simulation model that allows the identification of trends within the system, making it possible to make projections of the financial system of SMEs (Méndez et al., 2009). This shows how it is possible to integrate knowledge, in this case financial and accounting knowledge, in real situations for the benefit of interested parties with the use of simulators, thus helping to make decisions that affect companies and their organizational management.

Finally, in general, simulators in the different scenarios allow the reproduction of real situations in academic environments, facilitating the strengthening of competencies of areas of study for both students and teachers in a controlled environment. The main advantages are learning through discovery and the promotion of creativity. Moreover, they are considered useful tools for saving money and time, since these programs can be used to process information, such as repetitive calculations, and in a certain way replace some laboratory practices and training equipment, and they can be advantageous when the facilities for developing practical activities are not available (Chavarro & Romero, 2009).

3. Materials and methods

In order to present the materials and methods considered in this research, the reader will be presented with 5 basic components, from which the following will be explained: (1) the focus and scope of the study, (2) the sample and selection criteria, (3) the guarantees and ethical considerations of the study, (4) the data collection and analysis techniques, (5) general elements to understand the way the case study was conducted.

3.1. Focus and scope of the study

An exploratory study was carried out through a mixed approach, the objective of which was to analyze the impact perceived by university students in the city of Medellín regarding the use of a simulator to calculate the slope of asset depreciation. The study included students in the technological and undergraduate cycles of a public higher education institution in the city in 2019.

3.2. Sample and selection criteria

A case analysis was proposed taking as a reference student at the Metropolitan Technological Institute of the city of Medellín, Colombia, who were enrolled in the subject ‘Accounting of funding sources’, which is taught in the Public Accounting and Technology in the Analysis of Costs and Budgets through the Department of Economic and Administrative Sciences of the mentioned institution.

Compared to the total number of students enrolled in the two reference groups 71 based on the institutional academic system 45 were able to participate which is equivalent to 63% of the base group of the case analysis. Eligibility for participation in the study was based on the following inclusion criteria: (i) voluntary and informed participation in the exercise; (ii) enrolled in the course ‘Accounting of funding sources’ and (iii) passed the ‘Differential calculus’ and ‘Accounting of resources’ classes, which are prerequisites of this course based on the programmed curricula. The exclusion criteria were students suffering from severe mental disorders that prevented their conscious participation in the study.

3.3. Guarantees and ethical considerations of the study

As applicable ethical considerations, the Declaration of Helsinki was taken as an international reference, which, although it pertains to the medical sciences to regulate ethical elements of studies (Osuna et al., 2016), is considered a necessary input for social science research in which human beings participate. Additionally, at the Colombian level, Resolution 8430 of 1993 was taken as a reference; this resolution regulates the administrative, technical and scientific procedures of investigations (Mateus et al., 2019).

To comply with this series of ethical guidelines, each student signed an informed consent form through which the objective of the study, scope, risks, benefits and data treatment were detailed, as well as the chain of custody of the instruments in which the information was collected, thus preserving confidentiality with regard to personal data and other information that could violate the anonymity under which each subject was guaranteed in this study.

3.4. Data collection and analysis techniques

Regarding tools for the collection of information, a questionnaire was designed using a Likert-type scale, through which basic aspects of the student’s experience with the use of the simulator were investigated from the perspective of perceived usefulness. In this sense, the scale has been considered from different theoretical approaches an important tool for the measurement of perception, as shown by the study of Gante et al. (2020), especially in the approach of qualitative variables as was the case of the study proposed here. (Gante et al., 2020).

In addition, in the second section of the instrument, a series of open questions were asked for more details on the general perception of the students about the simulator and on future expectations regarding this type of technology in their learning process.

Thus, once the information was collected, the data obtained in the first section of the document questions scored using a Likert scale were tabulated in Excel, creating frequency tables for later analysis. The second section open questions were selectively coded by the authors based on the central constituent categories of the questions asked, to later be used as elements of contrast with the data obtained in the quantitative component of the instrument; furthermore, the responses served as a complement in the analysis of the phenomenon studied.

Thus, with respect to the analysis of qualitative data collected in the study, the proposal developed by Taylor and Bogdan (1990, cited by Salgado, 2007) is taken into consideration, who state that, in order to provide greater consistency and systematicity to the qualitative data analysis process, it is possible to carry out its processing through three moments: data discovery, codification and relativization of the data. (Salgado Lévano, 2007)

Regarding the first moment, the authors refer to the discovery of the data, where the researchers carry out a permanent reading of the data collected -in this case, the answers obtained from the students to the questions asked-, and from this recurrent exercise (a repeated reading must be carried out and from different visions, in this case, of the research team) to identify the clues and main categories that can be traced in the exercise, contrasting which ones are part of the construct of questions and which ones emerge as novel elements or not initially considered in the exercise (Taylor and Bogdan, 1990, cited by Salgado Lévano, 2007).

Regarding the second moment, Taylor and Bogdan (1990, cited by Salgado Lévano, 2007) propose the coding of the data, where from the discovery phase the emerging categories are delimited and with greater recurrence from the contrast with the narratives of the participants; So that finally in the third moment these data can be relativized, that is, to recognize the possible factors that could have influenced the participants’ response -the context, who was nearby, among others-, thus generating conscious data on possible biases and thus achieving the sedimentation of the final categories that are accompanied through the fragments of the study participants in the results section, supporting the responses obtained with the first instrument under the Likert scale. (Salgado Lévano, 2007)

3.5. Generalities to understand the case study

Prior to the implementation of the study, the authors designed a simulator called ‘Simulator for Calculating the Slope of Asset Depreciation by Components’ in GeoGebra software, based on the first three stages of development detailed in Robinson and Robinson (2003): analysis of a real system, conceptual model, and computational model. In the first semester of 2019, the first three stages were implemented, and in the second semester, they were validated and adjusted, in addition to evaluating the impact on students in the classroom.

The first stage real system involves the characterization of the real system or problem reflected in this study, taking into account that the competence related to ‘Resource Accounting’ is based on the recognition and valuation of assets, and that the competence for ‘Differential Calculus’ is based on the resolution of problematic situations through the analytical tools of differential calculus, which is outlined in the microdesign of both courses, which, as previously mentioned, are prerequisites for the course in which the case analysis was carried out.

Although students learn to calculate depreciation by components in the Resource Accounting course, the way in which the content is usually dictated leads teachers to limit themselves to teaching concepts using data and formulas with replacement variables to determine the value of depreciation. However, by not comparing this value with the tools of differential calculus, it is not possible for students to visualize the geometric meaning of the slope and the extreme points with their coordinates for each line segment, showing how each component depreciates. Therefore, this project arises from the pedagogical interest of promoting the visualization, the relationship and the interaction of the students with the concepts, both in the linear depreciation by components and in the straight line with its slope, through a simulator that incorporates all the necessary concepts and graphics, so that the students can discuss the practical implications of the differences between slopes in an environment identical to the real one (Silva, 2011).

The second stage conceptual model involves the formalization of the behavior and dynamics of the system (Law & Kelton, 1991), where the construction and characterization of the real system is developed, showing the characteristics in a more detailed way that will allow students to follow a series of steps that are the guide for data entry in the simulator, thus starting the third stage computational model, which involves a coding process in which the conceptual model is converted into code. The conceptual model is translated into a simulation model according to the rules of the chosen system; for the case presented here, this process was carried out using GeoGebra software. The simulator has been uploaded to the website https://juandiana.com. Students could access the tool by clicking on ‘other projects’.

The following components are considered in the simulator:

1. The slope of a known line or line segment between P₁(x₁, y₁) and P₂(x₂, y₂) is given by the formula: $$m=\mathrm{\text{tan}}\hspace{0.17em}\mathrm{\theta }=\frac{\Delta y}{\Delta x}=\frac{y_2-y_1}{x_2-x_2}$$ $$\Delta y\to \mathit{\text{It means change in the ordinate axis}}$$ $$\Delta x\to \mathit{\text{It means change in the abscissa axis}}$$

2. The student is told what a line segment is, which is a component of the asset, and its depreciation is shown. The slope “m” of this line segment is negative. $$\mathit{\text{Slope\hspace{0.5em}}}“\mathrm{m}”=\frac{\Delta U.M.\left(\mathit{\text{change in Monetary Units}}\right)}{\Delta \mathit{\text{years}}\left(\mathit{\text{change in number of years}}\right)}=\frac{y_2-y_1}{x_2-x_1}$$ $$\mathrm{m}=\frac{\mathit{\text{Residual value of the asset}}-\mathit{\text{Initial asset value}}}{\mathit{\text{Final year of asset}}-\mathit{\text{Initial year of asset}}}=\frac{\mathit{\text{Negative result}}}{\mathit{\text{Positive result}}}=(-)$$ The slope “m” is negative, which means that the component is depreciating.

3. In Figure 1, show the book value of an asset component in period $x_3$ and how the coordinates of the book value point are found. $$P_3\left(x_3,y_3\right)=P_3\left(\mathit{\text{period}}\mathrm{ }{x}_3\mathrm{ }\mathit{\text{or year}}\mathrm{ }\mathrm{n},\mathit{\text{Book value in the period}}\mathrm{ }{x}_3\mathrm{ }\mathit{\text{or year}}“n”\right)$$ $$y_{3\mathrm{ }}=\mathit{\text{Engine value at the beginning of the period}}\mathrm{ }{y}_1‐\mathrm{m}\mathit{\text{of the segment}}\mathrm{ }{P}_1{P}_2\mathrm{ }x\mathrm{ }\mathit{\text{years elapsed between the initial year of the asset until the year for book value}}(x_3-x_1)$$

Figure 1. Outstanding of an asset and book value.

That is to say, $P_3\left(x_3,y_3\right)=P_3\left(\mathit{\text{period}}\mathrm{ }{x}_3,y_1-\left(\frac{y_2-y_1}{x_2-x_1}\right)\frac{U.M.}{\mathit{\text{year}}}.(x_3-x_1\right)y\mathit{\text{ear}})$

Figure 2 provides a view of the simulator being applied in a real exercise that is, the intended purpose for the reference course.

Figure 2. View of an application exercise to calculate the depreciation slope using the designed simulator. Source: Own elaboration.

3.6. Limitations

It is important to acknowledge several limitations of this study. First, the sample used was relatively small and limited to a single public university in Medellín, which may not be representative of the diversity of educational and cultural contexts in Colombia. In addition, the research focused on a specific topic, asset depreciation, and the results may not be generalizable to other areas of accounting or to different academic disciplines. The lack of comparisons with traditional teaching methods also limits the ability to draw definitive conclusions about the superiority of simulators in accounting education. Although the results are promising, additional and more extensive research is needed to fully understand the impact and implications of incorporating simulators into accounting education.

4. Results

A total of 45 students enrolled in ‘Accounting of funding sources’ participated in this study, of whom 27 were women (60%) and 18 were men (40%), with an average age of 20 years; the participants reported that they spent approximately 5 hours a day studying. Only 11-

24.4% of the students reported that they alternated their studies with work activities.

When inquiring about their knowledge regarding the existence of simulators, although 100% reported that they were familiar with them, only 37.7% had used such technology in training scenarios prior to the reference course. Table 1 presents the results of the quantitative instrument applied to analyse the impact perceived by the students when using the simulator to calculate the depreciation slope by components of an asset.

Table 1. Perceived impact of the use of a simulator for slope calculations.

	Neither					Do not
Item	Totally	Agree	agree	Disagree	Totally	know/n
	agree		nor	disagree	o disagree	answer
The simulator allows you to visualize differences between slope depreciation by component, i.e. the residual value, the increase in asset value and the useful life.	88.9%	11.1%	0%	0%	0%	0%
The simulator strengthens knowledge of depreciation by component with its mathematical interpretations.	74.9%	25.1%	0%	0%	0%	0%
The simulator helps in the completion, with greater agility, of exercises that involve calculating depreciation by component.	84.4%	15.6%	0%	0%	0%	0%
The simulator motivates you to seek more information on depreciation by component.	28.9%	57.8%	13.3%	0%	0%	0%
The simulator motivates you to learn.	60%	35.5%	4.5%	0%	0%	0%
The simulator allows you to participate more in the classroom.	42.3%	42.2%	13.3%	0%	0%	2.2%
The simulator helps you better understand the depreciation method with mathematical interpretations.	88.9%	11.1%	0%	0%	0%	0%
The simulator serves as a teaching and learning methodology.	80%	20%	0%	0%	0%	0%

Source: Own elaboration.

The results in Table 1 indicate a favorable impact regarding the use of the simulator for calculating the slope of asset depreciation by university students.

Regarding the first three components addressed, all the participants stated when compiling the responses of those in total agreement and in agreement that the simulator allows them to visualize the differences between the slope of depreciation by component, i.e. the residual value, the increase asset value, and the useful life. In addition, they reported that the tool allows them to consolidate their knowledge in this field with the respective mathematical interpretations, thus also allowing them to be more agile in solving exercises. The questions in Table 1 were divided into three categories: Understanding – Components of the Simulator, Motivational Part, Participatory Behavior in the Classroom.

Figure 3, titled ‘Category Comprehension – Simulator Components’, presents the outcomes derived from the survey conducted across the five measurement scales. This visual representation encapsulates the participants’ understanding of simulator components within distinct categories. The survey data not only contributes valuable insights into the participants’ comprehension but also serves as a comprehensive guide for evaluating the effectiveness of the simulator components in enhancing overall learning experiences.

Figure 3. Category comprehension – simulator components.

On a parallel note, Figure 4 takes center stage as it portrays the 'Motivational Category’ based on the survey findings. This graphical representation encapsulates the participants’ responses across the five measurement scales, shedding light on their perceptions and experiences related to motivational aspects within the simulated environment.

Figure 4. Motivational category.

Additionally, Figure 5 comes into focus with its title 'Category Participatory Behavior in the Classroom'. This figure encapsulates the outcomes derived from the survey responses across the five measurement scales, offering a visual depiction of participants’ engagement and behavior within the simulated classroom environment.

Figure 5. Category participatory behavior in the classroom.

With respect to this first component of the analysis, it is possible that its structure and the instruments used may generate some resonance with respect to its potency in terms of the objective set, including some concerns about having asked the perception questions directly to the students. However, it is important for the reader to consider that in the face of this possible objection, there are three central arguments for understanding this line of analysis. First, since this research is a wager from a mixed approach per se, the methodological approach gives the exercise a power that is valued in scientific terms, since, as (Hernández Sampieri & Mendoza Torres, 2018) point out, it is a route that integrates different data derived from quantitative and qualitative approaches in order to approach social phenomena in greater detail, deriving conclusions that can acquire greater depth through the interaction of data of different nature (Hernández Sampieri & Mendoza Torres, 2018).

Secondly, in the dynamics of the subject-object relationship of research in the social sciences, it is the subject who acquires a leading role, especially if we consider that the purpose of this study was to ‘analyze the perceived impact’; therefore, the starting point is the individual and his or her ability to perceive the world, interpret and explain through language, an issue already addressed by Guardián Fernández (2011). Thus, although methodologically there are proven ways to collect information on motivation or taste, the study appealed precisely to question the students, recognizing them as active and creative subjects of action (Guardián Fernández, 2011).

And third, it is necessary to consider that since the manuscript is a product derived from a case study, the proximity to the participants and being able to approach them directly through the experience constitutes a mechanism considered by the researchers to ensure improvement strategies for an exercise derived from a classroom experience, through which the student felt involved and with the confidence to openly express their motivation or not for the way of conducting the exercises of adopting the inverted classroom. Not surprisingly, as Martínez Carazo (2006) has pointed out, despite the criticisms that the case study has had, it is a valuable alternative for those exercises where it is desired to explore elements of human behavior, for example in studies in education and pedagogy (Martínez Carazo, 2006).

Some narratives collected from the students who participated in the study are presented, which allow us to confirm the results obtained from the quantitative analyses. Regarding this phase of the analysis, it is also important to point out other objections that may arise about the way in which the data were processed, especially since no software was used to process the qualitative data, which may constitute a narrative exposition. However, it is important to consider that although there are currently different software tools that speed up the work of analyzing and systematizing qualitative data, it is important to note that this research was carried out with public resources, which in the Colombian context are often limited in some fronts according to the prioritization of spending; Therefore, the use of this type of licenses is sometimes limited for use by researchers and teachers (depending on the cost of acquiring the license), so that processing through tools with less integrated technology is a significant barrier, but not a limitation to ensure the consistency and reliability of the data analyzed and its projection for the reader. Not surprisingly, as mentioned by Lancheros and Mora (2022), the situation inherited from the years of the COVID-19 pandemic has deepened the problems of financing higher education in Colombia, since the incorporation of an education mediated by digital tools forced to increase the cost of technological infrastructure that prioritized virtual training, thus diverting investment from other fronts (Lancheros & Mora, 2022).

Nevertheless, as mentioned in the Methodology section, the data presented is an exploratory approach, so the results presented here are a first approximation of a field that is still being explored, even in scenarios such as the Colombian one. However, their significance in qualitative terms is important, and as (Schettini & Cortazzo, 2015) point out, despite the flexibility of the approach, this does not detract from the possibility of verification and approximation to the phenomenon from other streams, through which similar results can be obtained under the state declared in the methodological route; likewise, as well mentioned by Coffey and Atkinson (2005; cited by Schettini & Cortazzo, 2015), ‘the contemporary popularity of qualitative research is largely due to its flexibility and the absence of methodological straitjackets’ (p. 64), so that, without compromising the methodological rigor of the exercise, the type of tools for data analysis can be made more flexible, which, according to the authors, justifies not using specialized software for this purpose (Schettini & Cortazzo, 2015).

In this sense, some contributions from the participants of the study can be found, which qualitatively give an account of their experience with the use of simulators in the classroom.

[…] classes go much faster (E-10).

[…] support from simulators better optimizes time and improves understanding of the subject in question (E-11).

[…] With the simulator, we can see the depreciation method in a clearer and easier way since we would know the values to be depreciated by components year by year (E-20).

When analyzing item 4, 5 and 6, although the great majority were in total agreement and agreement with the statements presented, a small group of similar expressions emerged in statistical terms, they have low representativeness when compared to the total obtained that deserve attention because they reveal indecision in the students and, therefore, reflect the future need for a more in-depth studies to determine their incidence and impact on perceived usefulness of simulators in the classroom.

For item 4 of the instrument (motivation to seek more information on the topic addressed asset depreciation curves), although 86.7% provided a favourable answer, 13.3% neither agreed nor disagreed with the statement, which could reveal, as already mentioned, a level of indecision in the participants and, therefore, a possible path to improving the efficacy of simulators in this field of study. Some statements support the findings.

[…] allows me to see everything more coherently and to be more up-to-date with respect to these platforms (E-43).

[…] the simulators help in the appropriation of knowledge; in addition, practise with simulators helps understanding the topics better (E-9).

Regarding item 5 (simulator as motivational tool in student learning), 95.5% fully agreed, leads to the inference that this tool is effective as a pedagogical strategy for teaching mathematics and related subjects. However, 4.5% of the participants neither agreed nor disagreed, reflecting indecision. Some interesting comments were presented that support the quantitative findings.

[…] being more didactic, it is more enjoyable, and the concepts can be understood very well (E-7).

Students are, for the most part, very visual. By implementing different modalities in class, such as this simulator, they pay more attention, and the subjects are more easily understood, illustrating the theory (E-12).

[…] it is more motivational for students than a theoretical class. The simulator helps make the theory more understandable (E-19).

[…] with simulators, we are able to open our mental panorama and to be able to live a little closer to the real world experience of work (simulated); currently, the methods of innovation are elementary for our learning (E-15).

Regarding item 6 (simulator generates greater student participation in class), although 84.5% of the respondents agreed with this statement, 13.3% did not agree or disagree, in addition to 2.2% who chose not to answer or did not know the answer. Although the differences are not highly statistically significant, it is necessary to deepen future studies on this particular issue so that if it is an issue that becomes more evident, alternatives can be explored that strengthen classroom participation exercises when simulators are used. The following are some testimonies regarding this issue:

[…] it is more interactive; it goes beyond just paying attention, if not seeing and doing the examples (E-18).

[…] it is much more playful, more visual, more innovative learning; it facilitates learning and entertains students more, motivating them to pay attention (E-23).

[…] they allow the class to be slightly more didactic, which helps and motivates us to pay attention and learn much more (E-26).

Regarding items 7 and 8, all the study participants totally agreed and agreed with the statements that using the simulator facilitates learning accounting issues such as asset depreciation and that the simulator is a useful tool for teaching-learning processes. The following statements support these findings:

[…] everything, especially that it helped me understand depreciation more easily, an issue where there were still gaps for me (E-19).

Support with simulators helps us to visualize the behaviour of the variables, which allows us to better analyse the information (E-28).

The simulator helps one get closer to the reality of how depreciation reduces the value of assets and its mathematical behaviour (E-37).

Simulators and technological advances in general, what they seek is to approach learning in a simpler and more playful way (E-44).

Although there were elements that were not incorporated in the quantitative section, the second section of the instrument collected information as previously mentioned in the methods section from open questions, making it possible to not only contrast the quantitative findings with the participants’ narratives but also to obtain important information from the students with regard to three categories: (i) the areas or courses in which they would recommend the use of simulators to mediate learning; (ii) the differences identified between traditional learning and learning mediated by the use of this type of technology; and (iii) other functions that they would like to find in this type of tool.

Regarding the courses or subjects in which the students might recommend the use of simulators, there is a clear relationship between mathematics and economics, such as microeconomics, macroeconomics, costs, financial mathematics, differential calculus and statistics. Some students referred to topics such as English and international business to a lesser extent.

Regarding the differences between traditional learning and that mediated by the use of simulators, the students made reference mainly to the ease of understanding the topics addressed, the practicality and applicability of the content in a course in which simulators are used compared to the way in which content is presented in traditional training:

Traditional learning is only theoretical, while with the simulator, you can see the practical and the real (E-3).

[…] with simulator-based learning you can have a better understanding of how things work (E-8).

Learning supported by simulators is more didactic, so it allows learning in a better, more visual way (E-22).

Finally, when exploring other types of functions that students would like to find with the use of simulators, financial field concepts were identified, such as loans and bank reconciliations, supply and demand curves, and topics related to financial risks. In addition, the students requested a more aesthetic interface from the design perspective which presents the authors with a window of opportunity to improve the similator as well as the possibility of bringing the simulator to mobile devices.

5. Discussion and conclusions

5.1. Contributions

Incorporating simulation processes in university training is a trend that is gaining strength because they allow students to develop skills that prepare them, through emulated environments, for their interaction with the environment for which they are being trained, acquiring knowledge through practical training exercises (Ledo et al., 2019).

The incorporation of simulation processes in university education is a trend that is gaining strength because it allows students to develop skills that prepare them, through emulated environments, for their interaction with the environment for which they are being trained, acquiring knowledge through practical training exercises (Ledo et al., 2019).

The results of the study presented here indicate a positive impact of the use of simulators for the calculation of depreciation of assets by university students, confirming the usefulness of the simulator to differentiate the applicable concepts in the field of knowledge in which the research is carried out, to teach public accounting content supported by mathematical tools and to support the consolidation of knowledge and solving mathematical exercises in a more practical way.

Some interesting contributions in the literature are similar to the results reported here, for example a study (Cárdenas et al., 2017) in Ecuador that analyzed the impact of a simulator in the field of financial management, identifying an average academic performance similar to the students who took the traditional course, called control group, but with a higher proportion of students with a score between 90 and 100 out of 100 possible points.

Similarly, in a study (Vargas, 2017) carried out at a university in the city of Bogotá (Colombia), the academic performance of university students was better with the use of simulators for the development of managerial competencies, undoubtedly due to an adequate consolidation of the acquired knowledge; in particular, these results converge with those reported in the results section of this article.

This study has yielded other relevant results related to the way in which the use of simulators stimulates students to seek additional information on the topics addressed, the intrinsic motivation for the learning process and the possibility of participating more in class, without forgetting, as noted in the previous section, that although the majority of students responded positively to these topics, there was some indecision regarding these postulates, thus constituting a window of opportunity for future studies.

5.2. Comparative studies

While other studies have been found in the literature that address the use of simulators in accounting education, the studies vary in their focus and scope. While the present study focuses on the impact perceived by university students in Medellin when using a specific simulator to calculate the depreciation rate of assets. Other studies focus on simulators designed for different purposes, such as the application of national tax laws in Portugal or the development of financial literacy. Moreover, they use different methodological approaches, from exploratory studies to pre-experimental designs, highlighting the diversity of approaches in research on the use of simulators in accounting and financial education.

For example (Trigo & Varajão, 2011), presented the VAT simulator designed for accounting students in Portugal, which replicates the official application that complies with national tax laws. However, since this application is exclusively reserved for official use, accounting students cannot use it for practice. Therefore, this solution offers the possibility to complete and submit the form through practice, highlighting the importance of implementing this type of tool in accounting education in a real context.

In recent studies (Caballero et al., 2021), argue that simulators are effective for the development of competencies, especially those related to the financial and accounting area, in the context of a formative approach based on the development of competencies. These authors highlight the positive impact of the use of the SIMDEF simulator in the learning of accounting among university students. Their research, carried out with a sample of 20 students in a pre-experimental design, concludes that the use of the simulator strengthens the acquisition of specific skills in the field of finance and accounting.

For their part (Antoniuk et al., 2021), developed an online business simulator focused on the development of personal financial management skills. This simulator incorporates the key features presented in several sections and uses machine learning elements to enhance its operation. Its usefulness extends to people with different levels of personal finance knowledge, including high school students in Ukraine, thus enriching the educational process in economics courses.

However, similarities have been found regarding the effectiveness of simulators as didactic tools in the teaching of accounting and finance, with a focus on the development of specific skills and competencies. Benefits such as knowledge consolidation, improved understanding of content and student motivation are highlighted. In addition, the studies underline the importance of the practical application of accounting and finance, either in real business contexts or in the management of personal finances using simulators.

There are elements congruent with the results of previous studies, for example, in Cárdenas et al. (2017), greater motivation was observed among students who used simulators to learn financial management, even dedicating additional time to the class to interact with the simulator and, consequently, better integrate the knowledge derived from it, in addition to improving their level of engagement in the classroom.

The work conducted by Duque and Del Moral Pérez (2020) showed that the use of these technological tools to mediate learning processes not only increased the participants’ interest in using simulators, but also in deepening the topics covered with them (i.e. economics), also revealing a greater preference on the part of the male population. In another study (Ratu & Erfan, 2017), the use of these tools by Indonesian students to study electrical circuits increased their motivation due to the interactivity provided by the simulators.

The use of a simulator for slope calculation helps to improve the understanding of the topics addressed and constitutes a suitable teaching-learning tool, while allowing students to perceive a differential value compared to the value derived from training processes under traditional schemes.

The above conclusion is confirmed by the positive effects that simulators have generated in the teaching of some disciplines, representing an important alternative to refine the applicability of knowledge by the student population in university classrooms, as has been the case in the medical sciences, among which medicine, dentistry and nursing stand out (Birt et al., 2018; Padilha et al., 2018; Roy et al., 2017).

A literature review (Salazar-Sánchez et al., 2019) identified the relevance of this issue in the field of healthcare organizations, as well as the progressive adoption of simulators in university curricula. However, the authors recognize the limitations that may exist due to the costs associated with this type of technological tools, a point with which (Renganayagalu et al., 2019) agrees based on the results of a study on the use of simulators for the maritime industry, stating that the greater the loyalty confidence in these instruments, the greater the demand for technology, thus increasing its cost.

The results of previous studies complement the findings presented here; for example, a systematic literature review (Vlachopoulos & Makri, 2017) found that simulators and games in higher education affect not only the cognitive aspects of students detailed in the study and in the theoretical contrasts made with other authors, but also the affective and behavioral components.

5.3. Practical implications

The findings presented here make a significant contribution to the field of knowledge, not only by serving as an exercise in validation and comparison with what has been explored in fields of study such as medical sciences, economics, administration, and marine industry, but also by offering perspectives for conducting future studies on issues such as the costs associated with incorporating simulators into training scenarios, their affective and emotional impact (which, although not addressed here, are reflected in the literature as important aspects of simulator implementation and thus related to the perceived impact on individuals), and the level of participation they can foster in students in the classroom.

Simulator mediated learning in higher education is not a new topic in the field of pedagogy. This has been demonstrated in the scientific literature with approaches from fields of study such as the medical sciences, where simulators have been widely tested for training and developing the skills of future health professionals. Other areas of interest include the marine industry, administration, and finance.

The results of this study indicated a positive impact of the use of simulators in the classroom for calculating the slope of asset depreciation by university students, with 95.84% of students in favor. The different components studied from the quantitative instrument were later validated in a qualitative approach obtained from the second part of the tool with which the data were collected.

Thus, from a cognitive perspective, the results obtained allow us to infer the impact of the simulator on the consolidation of knowledge in students, the performance of exercises in a more agile way, a better understanding of the content addressed in class and its usefulness as a mediation methodology in the teaching-learning process. At the behavioral level, the results of the study indicate that by incorporating these technologies in the classroom, students can study with a higher level of motivation and are empowered by the topics addressed wanting to learn more about the issues discussed in class and participatory behaviors in the development of the course were encouraged.

The implemented case study allows us to deduce a high degree of effectiveness in the use of simulators in the classroom for teaching topics related to accounting. The perceived support of mathematical tools confirmed the relevance of their inclusion in the curricula as an alternative that improves the performance of students and, therefore, their appropriation of knowledge in the training process as future professionals who will enter the job market.

Contrasting the quantitative data obtained with the narratives of the study participants collected in the second section through open-ended questions, more questions emerged, such as the (actual) effective participation gained by using a simulator in the classroom, the way in which students are motivated in the learning process and how this improves their appropriation of the acquired knowledge, leading them to learn more about the topics covered. Although statistically the answers to these questions were mostly positive, there were some cases in which indecision was generated in the students, indicating the need for further in-depth studies.

As indicated in the literature review for the study, future research could investigate issues such as the cost of implementing simulators in the classroom, which is higher for fields such as medical sciences due to the accuracy or reliability involved, as well as the impact of an affective dimension that their use may imply.

6. Conclusions

The study presented in this report examines the use of a simulator designed to calculate asset depreciation in the context of accounting education. This simulator was designed and developed using GeoGebra software. The development process was divided into three main phases: first, a thorough analysis of a real system was carried out, followed by the creation of a solid conceptual model, which served as the basis for the final phase, which consisted of the transformation of this conceptual model into a fully functional simulator.

The results of the study show a very positive impact derived from the use of the simulator in the teaching process. Not only did it contribute to a better understanding of the concepts related to asset depreciation, but it also allowed students to consolidate their knowledge in a more efficient and effective manner. Students expressed that the simulator provided them with a valuable tool to visualize and understand the differences in asset depreciation by component, including aspects such as residual value, asset appreciation, and useful life.

The students who participated in the study not only recognized the usefulness of the simulator, but also expressed great interest in seeing it used in math and business courses. This study underscores the proven effectiveness of simulators in accounting education. In addition to improving understanding of concepts, it demonstrates their ability to reinforce knowledge and motivate students.

However, it also raises issues that deserve future attention, such as the costs associated with implementing simulators in educational settings and the emotional and motivational effects that may result from their use. These areas hold promise for future research that explores the impact of simulators in education.

Ethical approval

All participants were provided with consents that highlight their voluntary participation, how the data will be used in the research and how their confidentially will be maintained during and after the study.

Consent to participate

Consents were obtained from the participants’ parents to maintain the ethical standards within this study.

Author contributions

At the culmination of this article, we present a statement outlining the individual contributions of each author. Diana Gaviria significantly contributed to the conception and design, providing invaluable insights into the conceptual framework. Juan Arango and Alejandro Valencia-Arias played key roles in the analysis and interpretation of the data, leveraging their technical acumen for seamless integration of simulation components. Lemy Bran-Piedrahita meticulously conducted data analysis, adding depth to the survey findings. Ángel Marcelo Rojas Coronel contributed substantially to the discussion on participatory behavior, offering thoughtful interpretations. Alejandra Romero Díaz dedicated efforts to exploring motivational aspects, enriching the overall narrative. All authors actively participated in the drafting and critical revision of the paper, ensuring intellectual content and methodological rigor. In unanimous agreement, all authors have approved the final version for publication, and each is committed to being accountable for all aspects of the work.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data that supper the findings of this study are available from the corresponding author, upon reasonable request

Additional information

Notes on contributors

Diana Gaviria

Diana Gaviria graduated with a Bachelor’s degree in Public Accounting from Jaime Isaza Cadavid Polytechnic, followed by a Specialization in Financial Management from Latin American Autonomous University, and a Master’s degree in Accounting from the University of Medellín. She specializes in interactive learning objects and is certified in International Financial Reporting (CertIFR) by the Association of Chartered Certified Accountants (ACCA). She currently holds a position as a lecturer at the Metropolitan Technological Institute (ITM) in Medellín.

Juan Arango

Juan Arango earned his degree in Civil Engineering from the National University of Colombia. He furthered his education with a Specialization in Didactics of Sciences from the Pontifical Bolivarian University and a Master’s degree in Education Teaching from the University of Manizales. With a wealth of experience, he has previously held full-time lecturing positions at ITM (2006-2014) and Lasallista University Corporation of Caldas (1984-2006), and currently serves as a part-time lecturer at ITM.

Alejandro Valencia-Arias

Alejandro Valencia-Arias holds a Ph.D. in Management Engineering from the National University of Colombia, a Master of Sciences degree in Computer Sciences, and a Bachelor of Engineering degree in Management Engineering. With over twelve years of experience in academia, he has contributed significantly to his field, publishing numerous books and articles. His research interests encompass entrepreneurship, simulation, marketing research, and e-learning.

Lemy Bran-Piedrahita

Lemy Bran Piedrahita is a Health Administrator from the Universidad de Antioquia, specializing in Management from the Fundación Universitaria CEIPA. He holds a Master’s degree in Government and Public Policy from the Universidad EAFIT and is currently pursuing a Ph.D. in Political and Legal Studies at the Universidad Pontificia Bolivariana. As a research professor at the Corporación Universitaria Americana and a lecturer at the Instituto Tecnológico Metropolitano ITM in Medellín, he focuses on government, political science, geopolitics, peace, and conflict studies.

Ángel Marcelo Rojas Coronel

Angel Marcelo Rojas Coronel serves as an Associate Professor at the School of Mechanical and Electrical Engineering at the University Señor de Sipán. He is also a Consultant in Energy Efficiency. He holds a Bachelor’s degree in Mechanical and Electrical Engineering from Lord of Sipán University, Peru, and a Master’s degree in Mechanical and Electrical Engineering Sciences, specializing in Energy, from Pedro Ruiz Gallo National University, Peru.

Alejandra Romero Díaz

Alejandra Romero Díaz holds a Bachelor’s degree in Education, a Master’s degree in Management and Quality Assurance in Higher Education, a Master’s degree in Education, and a Doctorate in Education. As an OECD researcher in Social Sciences and the Director of Degrees and Titles at the Institute for Education Quality at the University of San Martín de Porres, she oversees innovative projects in Social Sciences and teaches at various universities nationwide.