A new model for evaluating the impact of ergonomic architectural design of gym,social network and digital knowledge on the desire of students for sport activities

Abstract

The sustainability issues in higher educational institutions have attracted an increasing level of attention from policymakers during the last decades. This is arguably due to the increased level of consciousness in society on sustainability issues; and the significant impacts of campus activities on both environment and communities. Also, digital technologies such as websites, online discussion forums, social media, content-sharing platforms, mobile apps, and wearable devices are now accessible for young people to learn about and promote their physical fitness and health. Therefore, in this paper, the impact of the ergonomic architectural design of gym, and social network on the desire of students for sports activities is investigated. A cross-sectional study was conducted with 500 students (275 girls and 225 boys; age 12–18 years), who responded to research questionnaires. The data were analyzed using PLS-SEM and Smart-PLS version 3.2. The obtained results showed the high strength of the proposed model. The outcomes also indicated that social network, digital knowledge and ergonomic architectural design of gym positively affect the desire of students for sports activities.

Keywords

Ergonomic architecture design of gym social network digital knowledge sports activities

My name is Fateme Moradi I was born on 20March 1980 in Shiraz, Iran. I am a faculty member of the department of general, school of Paramedical sciences, Shiraz University of Medical Sciences, shiraz, Iran, in the field of Persian language and literature.

I am a writer, poet, university professor, researcher and editor, and so far I have written dozens of ISI articles and scientific research and several poetries, literature and research books and edited dozens of scientific, literary and legal books. I have won many important scientific and literary awards of my country in Iran and I have been ranked first in bachelor’s, master’s and doctor’s degrees.

My favorite topics are classical and modern literature, culture, social sciences, linguistics, comparative literature of nations, psychology, history, and so on.

1 Introduction

Nowadays, sustainable development has progressively focused on the development of adaptive capabilities and creating prospects to maintain or achieve desirable social, economic and environmental systems for both the present and upcoming generations [1–2]. In addition, empowerment and public development are the backbones of economic development policies in many governments around the world. Lately, these concepts have become significant in health, environmental protection, criminal justice and anti-terrorism policies [3, 4]. Another hand, the lack of sufficient physical activity is considered as one of the most difficult health-related activities worldwide due to its strong association with the principal causes of mortality. Given that, the lifestyles of developed societies tend to be more and more inactive, therefore, sports activities become very important [5, 6]. Regular contribution to leisure sport provides opportunities for enhanced physical health, psychological well-being, and social functioning [7].

However, the process of learning and promoting the desire of students for sports activities are influenced by various factors, among these factors, social networks with their approval, encouragement, advice and guidance opportunities can provide a platform for the participation of individuals in sports activities. Based on Henderson and Ainsworth [8], social networks had an effect on perceptions and involvement in physical activity. A social network is an abstract structure which contains different relations between the individuals, such as common interests, friendships, and shared knowledge [9 –12]. Online social networks have gained important approval and are the most common sites on the Web [13, 14]. They are highly dynamic objects and they grow and alter rapidly through the addition of new connections [15, 16]. They play a major role as a medium for the spreading of ideas, information, and effect among their users [17]. Also, the social networking services disclose user’s real social connections and also enhance the growth by allowing them to share and communicate about ideas, events, activities, news, and interests in a much easier fashion [9 , 19].

In addition, digital knowledge and ergonomic architectural design of the gym may also address the desire of students for sports activities and the processes involved in learning. Digital technologies provide fast access to current knowledge; so, availability of Internet-connectivity and digital devices are necessary [20, 21]. Furthermore, ergonomic systems are concerned with understanding and optimizing the functioning of sports-related activities, including their organizational structures, policies, and processes [22]. One of the main features of human activity is the capability to alter the surrounding environment and the capability to make new structures. The appearance of such activity comprises many forms of building activity. The area which deals with adapting the whole of the material surroundings of man to their needs and capabilities is ergonomic [23]. Therefore, in this paper, the use of a social network, digital knowledge and ergonomic architectural design of the gym is considered as a key factor in improving the desire of students for sports activities. The main contributions of this paper are:

Providing a framework for assessing the impact of the ergonomic architectural design of gym, social network and digital knowledge on the desire of students for sports activities.

Highlighting the role of ergonomic architecture design in the desire of students for sports activities.

Helping to a better understanding of the role of social networks and digital knowledge as the tools for learning and encouraging the students, which can influence students’ sports activities.

The paper proceeds as follows. The next section presents the conceptual framework and research hypotheses. The third section presents the methodology study (participants, measures and data analysis). The fourth section presents the results and discussion. Finally, conclusions and further research are provided in the fifth section.

2 Related literature, conceptual framework, and hypotheses

In this section, we review the related research, the conceptual framework, and hypotheses.

2.1 Related literature

This section provides a brief summary of the most important research in the field of the ergonomic architectural design of gym, social network and digital knowledge and their influence on the desire of students for sports activities.

Rinaldi and Tosi [24] have examined smart technologies for physical activity as key factors in enhancing the quality of life and social inclusion. The results showed that use the strategies of human-centered design to identify innovative scenarios and solutions able the people to have a healthy life.

ERTAŞ [25] has examined the relationship between children, sports and agronomy in the architectural design process. They have proposed a model of child and sports relationship based on ergonomic factors affecting physical formation in the context of the study. With the developed model, the relationship between child and sports in the architectural design process for children’s sports facilities were introduced; the ergonomic arrangements for children were determined, and the factors affecting the design of children’s sports facilities and the essential principles were set forth.

Also, Mahedero, et al. [26] have investigated the effects of student skill level on knowledge, decision making, skill implementation and game performance in a mini-volleyball sports education season. The results showed that the game performance components of decision making and game playing attained important gains.

Furthermore, Brittin, et al. [27] have validated the associations between aspects of school environments and students’ physical activity. Research has provided physical activity design guidelines for school architecture. The design guidelines contain specific strategies in ten school design areas. Implementation of the guidelines is estimated to permit students to accept healthier physical activity behaviors.

Finally, Tessier, et al. [28] have tested the effects of a training program for newly qualified teachers on the teachers’ obvious behaviors and students’ psychological requirements satisfaction, self-determined motivation, and engagement in sport-based physical education. Results revealed that teachers managed to increase their teaching style in terms of all three dimensions. Also, students were receptive to these changes where by increasing their requirement satisfaction, self-determined motivation and engagement in the class are improved.

2.2 Research framework and hypotheses

Architecture has always reflected the variations taking place in the manner of the evolution of societies and socioeconomic requirements of human-environment at a specific stage of its development. In addition, ergonomic design deals with adapting the shape of the material settings to man’s requirements and aptitudes in the environment [23]. On the other hand, in recent years, the sport has become an important phenomenon for the development of a local context [29]. From the insights of numerous contemporary scholars on sustainability designs, it is proposed that sustainable sports growth is neither a state of the sports system to be improved or diminished, nor a static objective or target to be achieved [30]. Sports science includes not the only study of physical adaptations to training, nutrition, psychology, and biomechanics, but also how these diverse systems interact with one another [31, 32]. Therefore, the present section presents the conceptual model for assessing the impact of the ergonomic architectural design of gym, social network and digital knowledge on the desire of students for sports activities. Ten sub-indicators within three variables are provided where these variables are the ergonomic architectural design of gym, social network, and digital knowledge. In the ergonomic architectural design of gym variable, the sub-indicators are the color of educational spaces, Islamic architecture pattern and the use of the ergonomic tool. The communication, transfer of information, social learning and IoT services were identified in the social network variable. Finally, awareness, knowledge exchange and availability were identified in digital knowledge variable. This research develops such a framework including those variables which is shown in Fig. 1.

Fig.1

The proposed model.

Therefore, the following hypotheses will be examined:

H1: Ergonomic architectural design of the gym will positively influence the desire of students for sports activities.

H2: Social network will positively influence the desire of students for sports activities.

H3: Digital knowledge will positively influence the desire of students for sports activities.

3 Methodology

The measurement and structural models were tested using SEM. The component-based PLS approach was used to assess the psychometric properties of measurement scales and to test the research hypotheses [33]. PLS is a second generation data analysis technique which can exam not only the structural model but also the measurement model in a single analysis rather [34]. The rest of this section describes the participants and measurement model.

3.1 Participants

The population for this study consists of secondary schools’ students in Tehran of Iran. Participants were 500 students (275 girls and 225 boys; age 12–18 years). Stratified and simple random sampling techniques were used to select students, which formed the respondents for the study.

3.2 Measures

The study employed cross-sectional research design since data was gathered in a single point at a given time. In this study, the questions to measure the impact of the ergonomic architectural design of gym, social network and digital knowledge on the desire of students for sports activities were based on hypothetical considerations and the relevant aspects. A five-point Likert scale was used to ensure the high statistical variability among responses, which range from 1 (Strongly disagree), 2 (Disagree), 3 (Neutral), 4 (Agree), 5 (Strongly agree). SPSS was used for the initial screening of the data The data screening includes normality, and missing value of the data to ensure non-distortion of the analysis [35]. In addition, Partial Least Square (PLS) method was utilized as the data analytical tool in order to obtain a conclusion of causality between variables in the study, and the utilized PLS method aims to predict and develop theories [36].

3.3 Measurement model

SEM enables the concurrent examination of both the structural and measurement models [37]. PLS combines a factor analysis with linear regressions, and make only minimal assumptions, with the objective of variance explanation (high R-square) [38]. Furthermore, since PLS focuses on the prediction of data and is better suited for exploratory models, it is considered in this study [39, 40]. In the first step, we have confirmed the reflective type first-order constructs in one model and reported the indicator loadings, AVE, composite reliability and discriminant validity [41]. In the second step, we took the latent variable score from the first model and made a two-stage model. For the formative measurement model, we have reported the weights to validate the measurement model for formative constructs [42].

4 Results and discussion

This section tries to find the effect of the ergonomic architectural design of gym, social network and digital knowledge on the desire of students for sports activities. Next sub-sections describe the reliability and validity, validation of the structural model, the results of hypotheses testing, the goodness of Fit and discussion.

4.1 Reliability and validity

The reliability of the measures was inspected through the use of composite reliability and Cronbach’s alpha. In general, the minimum value of composite reliability is 0.7 [43], and the minimum value of Cronbach’s alpha is 0.7 [44, 45]. The values obtained for this index also presented acceptable reliability of structures (Table 1). The next criterion to evaluate the internal consistency of structures is the average variance extracted (AVE). The average variance extracted shows the amount of defined variance of latent variables by the observed related variables. Values greater than 0.5 are acceptable for this criterion [46]. According to the results from table (1), structures and their markers are of acceptable reliability. This indicates the reliability of the research tool used.

Table 1
Convergent reliability and validity of the measure

Variable AVE CR CA

Ergonomic architectural design of gym 0.654 0.903 0.864

Social network 0.612 0.885 0.838

Digital knowledge 0.501 0.833 0.758

The desire of students for sport activities 0.647 0.880 0.819

Variable	AVE	CR	CA
Ergonomic architectural design of gym	0.654	0.903	0.864
Social network	0.612	0.885	0.838
Digital knowledge	0.501	0.833	0.758
The desire of students for sport activities	0.647	0.880	0.819

Discriminant validity refers to the degree to which a set of items can differ a construct from another construct [47]. Table 2 indicates the correlation matrix in which the diagonal elements represents the square root of the average variance extracted of the latent constructs. The result of the correlation matrix indicated in Table 2 to guarantee that the discriminant validity is confirmed.

Table 2

Discriminant validity of the measurement model

Variable	Ergonomic architectural design of gym	Social network	Digital knowledge	The desire of students for sport activities
Ergonomic architectural design of the gym	0.809
Social network	0.471	0.782
Digital knowledge	0.416	0.340	0.708
The desire of students for sport activities	0.339	0.356	0.383	0.804

4.2 Validation of the structural model

Sang, et al. [48] suggested that the structural model indicates the causal relationships among constructs in the model (path coefficients and the R² value). Together, the R² and the path coefficients (beta and significance) show how well the data and hypothesized model are supported [49]. The range of R² is from 0 to 1; however, there is no standard criterion, and in general, the higher R², the higher the variance that can be explained [50, 51]. Figure 2 shows the results of the structural model from the PLS output. It demonstrates that three set of latent variables (ergonomic architectural design of gym (β= 0.30, p < 0.01), social network (β= 0.24, p < 0.01) and digital knowledge (β= 0.27, p < 0.01)) were expected to explain 55.7% of the variance in the dependent variable (the desire of students for sports activities). The results thus support every three hypotheses.

Fig.2

PLS results of the structural model.

4.3 Results of hypotheses

We wanted to test whether or not the ergonomic architectural design of gym, social network, and digital knowledge provide improved results in the desire of students for sports activities. T-value results in Fig. 3 indicate that the ergonomic architectural design of gym, social network, and digital knowledge yields better the desire of students for sports activities. The statistically significant loadings are at the 99.9% significance level. PLS performs an iterative set of factor analyses and applies a bootstrap approach to assess the significance (t values) of paths [52, 53]. As can be seen in Fig. 3, the standardized coefficient between the ergonomic architectural design of the gym and the desire of students for sports activities was 0.31 (t = 4.56, p < 0.001). H1, which stated that ergonomic architectural design of the gym had a positive influence on the desire of students for sports activities, was thus supported. The path coefficient between a social network and the desire of students for sports activities was 0.25 (t = 3.48, p < 0.001). Therefore, hypothesis H2 was statistically accepted. Furthermore, the path coefficient between digital knowledge and the desire of students for sports activities was 0.27 (t = 4.59, p < 0.001), which indicates that digital knowledge had a positive and significant influence on the desire of students for sports activities.

Fig.3

PLS results of the T-value.

4.4 Goodness of fit

Goodness of Fit (GOF) has been proposed to apply model performance in the measurement and the structural model [54]. The GOF index is calculated as the geometric mean of the average R² value: $GOF = \sqrt{\bar{AVE} \times \bar{R^{2}}}$ (1)

The GOF value is obtained: $GOF = \sqrt{0 . 776 * 0 . 557} = 0.657$ (2)

According to Wetzels, et al. [55], 0.1, 0.25 and 0.36 are the baseline values for GoF which mean small, medium and high, respectively. We obtained a GOF value of 0.66. Therefore, the structure of the proposed framework had a good fit with the data.

4.5 Discussion

Based on Table 3, the obtained results from path coefficient and the sample t-test implied that the desire of students for sports activities are positively and significantly influenced by the ergonomic architectural design of gym (β= 0.30, T-value = 4.56) where H1 was supported. In the ergonomic architectural design of gym, the sub-indicators are the color of educational spaces, Islamic architecture pattern and the use of the ergonomic tool. The desire of students for sports activities is also influenced by the social network which is proved to be positive and significant (β= 0.24, T-value = 3.48). H2 was supported accordingly. The communication, transfer of information, social learning and IoT services were identified in the social network. Also, β= 0.27, T-value = 4.59 is supported by H3 which proposed that the desire of students for sports activities and digital knowledge is positively related to each other. Finally, awareness, knowledge exchange and availability were identified in digital knowledge. The summary of the results obtained from the hypotheses tests and the model was presented in Table 3.

Table 3
PLS structural model results

Paths Path coefficients T-value Confirm or reject the hypothesis

H1 Ergonomic architectural design of gym → The desire of students for sport activities 0.30 4.56* Confirm

H2 Social network → The desire of students for sport activities 0.24 3.48* Confirm

H3 Digital knowledge → The desire of students for sport activities 0.27 4.59*** Confirm

	Paths	Path coefficients	T-value	Confirm or reject the hypothesis
H1	Ergonomic architectural design of gym → The desire of students for sport activities	0.30	4.56***	Confirm
H2	Social network → The desire of students for sport activities	0.24	3.48***	Confirm
H3	Digital knowledge → The desire of students for sport activities	0.27	4.59***	Confirm

^***p < 0.001.

5 Conclusions and further research

Sustainable sports development is an ideal and an important goal. Sports participation patterns around the world show this point and reflect an evolution of ideas, changing organizational forms, delivery systems, and performances. The outcomes of the recent study exhibit a positive relationship between the ergonomic architectural design of gym, social network and digital knowledge and the desire of students for sports activities. In this paper, related factors to the desire of students for sports activities in ergonomic architectural design of gym, social network, and digital knowledge have been investigated. A primary contribution of this work provides a model and framework for measuring the impact of the aforementioned variables on the desire of students for sports activities. The measurement of the impact of these variables on the desire of students for sports activities had been provided using three research hypotheses. This study found that the impact of the ergonomic architectural design of the gym is important to the desire of students for sports activities. The ergonomic architectural design of gym included the color educational spaces, Islamic architecture pattern and the use of the ergonomic tool. Furthermore, the finding showed that the effect of the social network variable (communication, transfer of information, social learning and IoT services) on the desire of students for sports activities is significant and positive. Another important finding is that digital knowledge is very important in the desire of students for sports activities. Digital knowledge includes the sub-indicators of awareness, knowledge exchange and availability. The results obtained from the study can be ordered as follows:

Converting sports spaces to safe and healthy places in order to encourage students to do sports by keeping them away from possible danger and injuries.

Designing an equipment in these spaces according to the skills and features of students and making the environment which is designed upon physical programs; thus, providing them with meaningful, useful and interesting activities that they are doing by letting them prove themselves and use their skills.

Presenting the basic speculative information for any space that requires sports facilities, child spaces and ergonomic regulations that are subjected to studio studies and education programs like architecture and interior architecture.

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A new model for evaluating the impact of ergonomic architectural design of gym,social network and digital knowledge on the desire of students for sport activities

Abstract

Keywords

1 Introduction

2 Related literature, conceptual framework, and hypotheses

2.1 Related literature

2.2 Research framework and hypotheses

3.1 Participants

3.2 Measures

3.3 Measurement model

4 Results and discussion

4.1 Reliability and validity

Table 1 Convergent reliability and validity of the measure Variable AVE CR CA Ergonomic architectural design of gym 0.654 0.903 0.864 Social network 0.612 0.885 0.838 Digital knowledge 0.501 0.833 0.758 The desire of students for sport activities 0.647 0.880 0.819

References

Table 1
Convergent reliability and validity of the measure

Variable AVE CR CA

Ergonomic architectural design of gym 0.654 0.903 0.864

Social network 0.612 0.885 0.838

Digital knowledge 0.501 0.833 0.758

The desire of students for sport activities 0.647 0.880 0.819