**3.4 Validity and reliability**

The theoretical model presented here was estimated by using the SPSS/AMOS 24 structural equation modelling program [99]. The measurement model (validity and


#### **Table 2.**

*Measurement instruments.*

**119**

**CR** 0.843 0.909 0.882 0.738 0.906 0.857 *Note 1: Diagonal represents the square root of the AVE.*

*Note 2: Outside the diagonal, we can observe the correlation between the constructs.*

**Table 3.** *Convergent and discriminant validity.*

0.667

0.842 *IWOM = Intention to Word-of-Mouth, SIN=Social Influence, RCG = Recognition, CUI=Continued Use Intention, ATT = Attitude, RCB = Reciprocal Benefits.*

0.793

0.651

0.553

0.687

0.735

**0.817**

0.763

0.902

0.634

0.544

0.519

0.615

**0.873**

0.526

0.891

0.436

0.525

0.402

**0.725**

0.718

0.867

0.418

0.662

**0.847**

0.769

0.909

0.750

**0.877**

0.641

0.833

**0,800**

IWOM

SIN RCG

CUI ATT RCB

**AVE**

α

**IWOM**

**SIN**

**RCG**

**CUI**

**ATR**

**RCB**

*Social Factors Influence on Accounting Students Attitude to Use Games Based Learning*

*DOI: http://dx.doi.org/10.5772/intechopen.95430*

#### *Social Factors Influence on Accounting Students Attitude to Use Games Based Learning DOI: http://dx.doi.org/10.5772/intechopen.95430*


**Table 3.**

*Convergent and discriminant validity.*

*The Role of Gamification in Software Development Lifecycle*

since they were allowed to play it outside school hours.

**Figure 2** the research model to test during this investigation.

**Constructs Authors** Social Influence (SIN) [22, 45, 96, 97] Recognition (RCG) [44, 46, 92, 98] Reciprocal Benefits (RCB) [43, 47, 49] Attitude (ATT) [22] Continued Use Intention (CUI) [49] Intention to Word-of-Mouth (IWOM) [50]

**3.3 Research model**

**3.4 Validity and reliability**

such as RCB, SIN, RCG, ATT, CUI, and IWOM that the user of an e-learning game experiences when operating it as a learning tool. All questionnaire items resulted from adapting previously validated scales used in other relevant scientific studies (**Table 2**). The attitude was measured using a combination of scales by several authors (Appendix 1). We translated and adapted these scales to the Portuguese language. The adaptation of scales did not involve many changes and enabling the application of the same scale. All the items were measured using a 7 point-Likert scale, varying between "Does not fully correspond" and "Fully Corresponds". The questionnaire was administered at the end of the semester, before the final evaluation, to all students who had played the game for at least six hours. It should be noted that the average game utilization rate in class was three sessions of two hours each; nevertheless, the total rate of the students' individual use was over 87,2%,

According to the literature review described in Section 2.3, we present in

The theoretical model presented here was estimated by using the SPSS/AMOS 24 structural equation modelling program [99]. The measurement model (validity and

**118**

**Figure 2.** *Research model.*

**Table 2.**

*Measurement instruments.*

reliability of the measures) was analyzed according to the literature, and several research hypotheses were tested to assess the meaning of the loads and coefficients of each path [100]. To evaluate convergent validity and reliability of the model, the Average Variance Extracted (AVE), the Composite Reliability (CR), and the Cronbach's Alpha (α) were analyzed, using only measurement items whose factor loads (AVE > 0,5; CR > 0,7; α > 0,7) were well within acceptable statistical parameters [100].

**Table 3** presents the different dimensions of the study that are related and whose correlation between the different constructs is strong. The dimensions IWOM, SIN, RCG, CUI, ATT, and RCB present significant correlations that demonstrate the ability that the different constructs must explain the results of the study. The closer to 1, the greater the ability to explain the influence of each construct in explaining the reality that is being studied. On the other hand, we found that the AVE values for each of the latent constructs are more significant than the highest square correlation with any other latent variable. Therefore, discriminant validity is established at the construct level.

The results presented in **Table 3** have sufficient convergent and discriminant validity to validate the results presented in which the Attitude to learn accounting using gamified resources is influenced by social factors.

## **4. Results**

The theoretical model presented here was estimated by using the SPSS/AMOS 26 structural equation modelling program [99]. The measurement model (validity and reliability of the measures) was analyzed according to the literature, and several research hypotheses were tested to assess the meaning of the loads and coefficients of each path [100]. To evaluate the model's convergent validity and reliability, the Average Variance Extracted (AVE), the Composite Reliability (CR), and the Cronbach's Alpha (α) were analyzed, using only measurement items whose factor loads (AVE > 0,5; CR > 0,7; α > 0,7) were well within acceptable statistical parameters [100]. In what concerns the measures that were used in this study, they are sufficiently valid and reliable (**Table 2**), and the sample that was obtained meets the criteria of structural equation analysis [101].

The research model tested (**Figure 3**) allowed us to verify that 67,6% of the ATT towards using GBL as a learning tool to teach management is explained by the RCB,

**121**

*Social Factors Influence on Accounting Students Attitude to Use Games Based Learning*

**Standard Error**

.638 .122 7.163 <0.001 Supported

**H1** RCB → ATT .100 .100 .813 <0.05 Supported **H2** SIN → ATT .081 .106 .944 <0.05 Supported **H3** RCG → ATT .161 .221 4.802 <0.001 Supported **H4** ATT → CUI .874 .112 5.669 <0.001 Supported

**t p-value Results**

**Coefficient**

SIN, and RCG dimensions. The model also explains 39,7% of the CUI and 50,5% of the IWOM. The direct paths tested were all statistically significant. We verified the effect of the RCB, SIN, and RCG dimensions on CUI and IWOM dimensions

In **Table 4**, we can see the structural results of the RCB, SIN, and RCG dimensions, which have direct and positive statistical significance on ATT, validating the formulated hypotheses (H1, H2, and H3). The ATT dimension has a positive, statistically significant, direct influence on CUI and IWOM, validating the hypoth-

The estimated results of the research model indicated that Reciprocal Benefits,

In what concerns ATT-mediated effects, some mediated relationships producing

In this article, we investigated how social factors influence the attitude of higher education students of Accounting towards using technological gamified resources as a learning method within these areas of knowledge. Using the theoretical background provided by the TBP [22], we tested how social factors like RCB [45];

statistically significant total effects were observed, such as: RCB → ATT → CUI (β = 0.10\*0.874 = 0.087, p < 0.001); RCB → ATT → IWOM (β = 0.10\*0.638 = 0.063, p < 0.001). Talking about indirect effect of SIN in CUI and IWOM results showed that SIN → ATT → CUI (β = 0.081\*0.874 = 0.070, p < 0.001); SIN → ATT → IWOM (β = 0.081\*0.638 = 0.051, p < 0,001). Finally we analysed indirect effect of RCG in CUI and IWOM of Accountigame users and we concluded that RCG → ATT → CUI (β = 0.161\*0.874 = 0.140, p < 0.001); RCG → ATT → IWOM

Social Influence, and Recognition Attitude, after using AccountinGame have a positive effect on Attitude. In the other side, Attitude has a positive effect in Continue Use Intention and Intention of Word of Mouth to use and advise the game like a learning tool. In its turn, the Attitude to study and learn after using the game also influenced the students. All relationship between dimensions was statistically significant, meaning that the fact that students are immersed with the use of the game to improve learning. Looking to the final results, we can start by saying: RCB has a positive impact on ATT(β = 0.10, p < 0.05); SIN has a positive impact on ATT(β = 0.081, p < 0.05) and RCG has a positive impact on ATT(β = 0.161, p < 0.001); Results confirmed and validated research hypotheses H1, H2 and H3. In the other side, ATT has a positive and statistically significant direct strong influence on CUI (β = 0.874, p < 0.001) and in IWOM(β = 0.638, p < 0.001) validating H4

*DOI: http://dx.doi.org/10.5772/intechopen.95430*

**Hypotheses Effect Regression** 

IWOM

mediated by the ATT dimension.

*Research hypotheses and statistical results.*

**H5** ATT →

and H5 od the research proposed model.

(β = 0.161\*0.638 = 0.102, p < 0.001).

**5. Discussion and conclusions**

eses (H4 and H5).

**Table 4.**

**Figure 3.** *Structural model results. \*\* p<0.05; \*\*\* p<0.001.*


*Social Factors Influence on Accounting Students Attitude to Use Games Based Learning DOI: http://dx.doi.org/10.5772/intechopen.95430*

#### **Table 4.**

*The Role of Gamification in Software Development Lifecycle*

eters [100].

**4. Results**

established at the construct level.

using gamified resources is influenced by social factors.

criteria of structural equation analysis [101].

*Structural model results. \*\* p<0.05; \*\*\* p<0.001.*

reliability of the measures) was analyzed according to the literature, and several research hypotheses were tested to assess the meaning of the loads and coefficients of each path [100]. To evaluate convergent validity and reliability of the model, the Average Variance Extracted (AVE), the Composite Reliability (CR), and the Cronbach's Alpha (α) were analyzed, using only measurement items whose factor loads (AVE > 0,5; CR > 0,7; α > 0,7) were well within acceptable statistical param-

**Table 3** presents the different dimensions of the study that are related and whose correlation between the different constructs is strong. The dimensions IWOM, SIN, RCG, CUI, ATT, and RCB present significant correlations that demonstrate the ability that the different constructs must explain the results of the study. The closer to 1, the greater the ability to explain the influence of each construct in explaining the reality that is being studied. On the other hand, we found that the AVE values for each of the latent constructs are more significant than the highest square correlation with any other latent variable. Therefore, discriminant validity is

The results presented in **Table 3** have sufficient convergent and discriminant validity to validate the results presented in which the Attitude to learn accounting

The theoretical model presented here was estimated by using the SPSS/AMOS 26 structural equation modelling program [99]. The measurement model (validity and reliability of the measures) was analyzed according to the literature, and several research hypotheses were tested to assess the meaning of the loads and coefficients of each path [100]. To evaluate the model's convergent validity and reliability, the Average Variance Extracted (AVE), the Composite Reliability (CR), and the Cronbach's Alpha (α) were analyzed, using only measurement items whose factor loads (AVE > 0,5; CR > 0,7; α > 0,7) were well within acceptable statistical parameters [100]. In what concerns the measures that were used in this study, they are sufficiently valid and reliable (**Table 2**), and the sample that was obtained meets the

The research model tested (**Figure 3**) allowed us to verify that 67,6% of the ATT towards using GBL as a learning tool to teach management is explained by the RCB,

**120**

**Figure 3.**

*Research hypotheses and statistical results.*

SIN, and RCG dimensions. The model also explains 39,7% of the CUI and 50,5% of the IWOM. The direct paths tested were all statistically significant. We verified the effect of the RCB, SIN, and RCG dimensions on CUI and IWOM dimensions mediated by the ATT dimension.

In **Table 4**, we can see the structural results of the RCB, SIN, and RCG dimensions, which have direct and positive statistical significance on ATT, validating the formulated hypotheses (H1, H2, and H3). The ATT dimension has a positive, statistically significant, direct influence on CUI and IWOM, validating the hypotheses (H4 and H5).

The estimated results of the research model indicated that Reciprocal Benefits, Social Influence, and Recognition Attitude, after using AccountinGame have a positive effect on Attitude. In the other side, Attitude has a positive effect in Continue Use Intention and Intention of Word of Mouth to use and advise the game like a learning tool. In its turn, the Attitude to study and learn after using the game also influenced the students. All relationship between dimensions was statistically significant, meaning that the fact that students are immersed with the use of the game to improve learning. Looking to the final results, we can start by saying: RCB has a positive impact on ATT(β = 0.10, p < 0.05); SIN has a positive impact on ATT(β = 0.081, p < 0.05) and RCG has a positive impact on ATT(β = 0.161, p < 0.001); Results confirmed and validated research hypotheses H1, H2 and H3. In the other side, ATT has a positive and statistically significant direct strong influence on CUI (β = 0.874, p < 0.001) and in IWOM(β = 0.638, p < 0.001) validating H4 and H5 od the research proposed model.

In what concerns ATT-mediated effects, some mediated relationships producing statistically significant total effects were observed, such as: RCB → ATT → CUI (β = 0.10\*0.874 = 0.087, p < 0.001); RCB → ATT → IWOM (β = 0.10\*0.638 = 0.063, p < 0.001). Talking about indirect effect of SIN in CUI and IWOM results showed that SIN → ATT → CUI (β = 0.081\*0.874 = 0.070, p < 0.001); SIN → ATT → IWOM (β = 0.081\*0.638 = 0.051, p < 0,001). Finally we analysed indirect effect of RCG in CUI and IWOM of Accountigame users and we concluded that RCG → ATT → CUI (β = 0.161\*0.874 = 0.140, p < 0.001); RCG → ATT → IWOM (β = 0.161\*0.638 = 0.102, p < 0.001).

#### **5. Discussion and conclusions**

In this article, we investigated how social factors influence the attitude of higher education students of Accounting towards using technological gamified resources as a learning method within these areas of knowledge. Using the theoretical background provided by the TBP [22], we tested how social factors like RCB [45];

C.-P. [48], SIN [22, 45, 61, 62, 97] and RCG [44, 45, 49] were predictors of ATT [61] towards using GBL and the influence of ATT in CUI [49] and IWOM [50].

We tried to understand how each factor influences HE students to increase the attitude towards using GBL as a complementary learning tool in one of the area of Management (Accounting) and if this construction of a positive attitude towards usage influences future intention to use and intention to recommend the tool to others. We tested if the students' behaviour after using GBL lead to the desire to continue using technology as a standard study tool. The results obtained indicate that the amount of recognition that users receive from others when using the resource directly and significantly affects the attitude towards GBL [57, 59]. Regarding the way other people (colleagues, family, friends) socially influence the use of this type of tools, we have verified that there is a statistically significant cause and effect relationship that corroborates previous research [22, 66, 69]. Concerning the benefits or usefulness resulting from using this type of technological resource, users are satisfied when the services are useful for learning, easy to use, and practical, previous corroborating research [45, 54, 57, 71]. The results also indicate that the ATT towards GBL service is a strong determinant of the CUI related to the future frequent use of the resource [47, 72, 76, 102], and IWOM, which is related to the intentions of recommending and saying positive things about the service used [50, 84, 103].

Previous studies have already tested the influence of social factors on ATT [42], as well as the influence of ATT on CUI and IWOM [104]; however, in this investigation, we used the TPB as the basic theory to test the influence of more social factors, simultaneously, on ATT and CUI and IWOM, based on the use of resources for the teaching of the area of knowledge management. Therefore, we seek to increase theoretical knowledge on this subject and to contribute to a better understanding of the influence of social factors on the continued use of the technology. After a minimum of six hours of use per student, the game used in this empirical study (Accountingame) allowed to test if the already mentioned social factors had direct effects on the attitude and if this dimension had a positive relation with the intention to continue using and recommending the service designed to support the teaching of Accounting in the context of Portuguese higher education.

The findings resulting from this research fill the gap in the literature regarding the effects of GBL in Accounting students, demonstrating that these areas of knowledge, like many others, can support the use of resources intended for this purpose.

The results of the present study, along with the findings previously achieved by other authors referenced in this study, indicate that the use of GBL has positive effects on attitude to learning, through intervention and because of several dominant social factors. In this regard, the validated hypotheses indicate that it is necessary to continue supporting the use of gamified technologies as a complementary teaching method for the acquisition of knowledge.

#### **6. Limitations and future research**

Future studies may investigate how social factors interfere with the attitudes of students towards using GBL, among other distinct areas of knowledge, noting that the results in these areas will be close to those obtained in the present investigation.

A study to compare the influence of social factors on the attitude towards GBL of students from different countries, in similar study fields, could also be carried out. An attempt to understand how social factors have more impact according to sociodemographic data variables such as gender, age, nationality, academic background, and

**123**

*Social Factors Influence on Accounting Students Attitude to Use Games Based Learning*

even family background could be carried out as well. Regarding family background, it would be useful to compare how Accounting students view GBL as a method of learning according to their family history, directly or indirectly related to these areas of knowledge. Future qualitative studies would be interesting to study the phenomenon from another perspective in the attempt to obtain other data resulting from an investigation, and this different methodology might bring other conclusions and

Regarding the limitations of the investigation, we denote the fact that the data are self-reported and can influence the results because users, when interested in a service, can become emotionally involved in the activities, which affects their

Regarding the collection instruments, although empirically and scientifically validated, they can be replaced by other relevant ones like structured or semistructured interviews. Scales are always liable to questioning and replacement by

The methodology of quantitative research itself and its generalization be limiting insofar as there are no two matching realities even when studying the same

**Question Constructs Authors** Using the game was important Attitude [22]

I will recommend the game to my friends Intention WOM [50]

I think the game is quite useful to learn Reciprocal Benefits [43, 47, 49]

Intention

[49]

Recognition [44, 46, 92, 98]

Social Influence [22, 45, 96, 97]

*DOI: http://dx.doi.org/10.5772/intechopen.95430*

reasonable opinion about the utilized resource.

others that may eventually have more statistically robust results.

I anticipate keeping using the game in the future Continue Use

I intend to use the game frequently, as I have done so far I anticipate using the game more frequently than less

I feel good when my achievements in the game are

I enjoy it when my colleagues understand my evolution

It is good to notice that other users follow my activities in the

The people who influence my attitudes would recommend

The people who I like would encourage me to use the game

I will recommend the game to people who ask my opinion

I will say positive things about the game so that other people

Using the game, I feel that I am learning in a more effective

My friend's thing it is a good idea to use the game

It is easier to start studying by using the game

other theoretical contributions.

phenomenon.

**Appendix 1**

frequently

game

acknowledged

using this game

about its usefulness

will use it

manner

throughout the game

Using the game was a good idea Using the game was positive

#### *Social Factors Influence on Accounting Students Attitude to Use Games Based Learning DOI: http://dx.doi.org/10.5772/intechopen.95430*

even family background could be carried out as well. Regarding family background, it would be useful to compare how Accounting students view GBL as a method of learning according to their family history, directly or indirectly related to these areas of knowledge. Future qualitative studies would be interesting to study the phenomenon from another perspective in the attempt to obtain other data resulting from an investigation, and this different methodology might bring other conclusions and other theoretical contributions.

Regarding the limitations of the investigation, we denote the fact that the data are self-reported and can influence the results because users, when interested in a service, can become emotionally involved in the activities, which affects their reasonable opinion about the utilized resource.

Regarding the collection instruments, although empirically and scientifically validated, they can be replaced by other relevant ones like structured or semistructured interviews. Scales are always liable to questioning and replacement by others that may eventually have more statistically robust results.

The methodology of quantitative research itself and its generalization be limiting insofar as there are no two matching realities even when studying the same phenomenon.
