
==== Front
Heliyon
Heliyon
Heliyon
2405-8440
Elsevier

S2405-8440(24)13190-8
10.1016/j.heliyon.2024.e37159
e37159
Research Article
Predicting online learning experiences in sports education during the COVID-19 pandemic: Implications for pedagogical strategies
An Ran 1610483885@qq.com
a
Addas Abdullah a.addas@psau.edu.sa
bc
Rehman Nadia nadia_rehman@ciitwah.edu.pk
d
Rehman Shazia rehmanshazia.malik@gmail.com
ef⁎
a College of Finance and Economics, Zhengzhou University of Science and Technology, Zhengzhou, 450064, Henan, China
b Department of Civil Engineering, College of Engineering, Prince Sattam Bin Abdulaziz University, Al-Kharj, 11942, Saudi Arabia
c Landscape Architecture Department, Faculty of Architecture and Planning, King Abdulaziz University, P.O. Box 8 0210, Jeddah, 21589, Saudi Arabia
d Department of Mathematics, COMSATS University, Wah Campus, Islamabad, Pakistan
e Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China
f Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Hunan Medical Center for Mental Health, Changsha, 410011, Hunan, China
⁎ Corresponding author. Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China. rehmanshazia.malik@gmail.com
31 8 2024
15 9 2024
31 8 2024
10 17 e371592 3 2024
28 8 2024
28 8 2024
© 2024 The Authors
2024
https://creativecommons.org/licenses/by-nc/4.0/ This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
This research aims to assess the predictors that impact the online learning experiences (OLEs) of undergraduate sports students amid the Coronavirus Disease 2019 (COVID-19) outbreak utilizing the Community of Inquiry (CoI) framework. An online survey was employed using the cluster sampling method to systematically examine the associations among the variables related to the OLE of sports students. A sample size of 402 undergraduate sports students from two universities in China was chosen and surveyed. Exploratory factor analysis was conducted to assess the validity of the questionnaires and model adequacy. Finally, a multiple linear regression analysis was performed to explore the associations of the study constructs. The results revealed that open communication, social presence, design and organization, and facilitation possess significant potential in predicting students’ OLE. This demonstrates the paramountcy of transparent communication, directs focus towards the indispensability of fostering a sense of reception and admiration among sports students, and highlights educators' sway in shaping their students' holistic and positive educational encounters. The scalability of our study highlights its potential to contribute valuable insights for developing national-level policies and educational strategies for this demographic.

Keywords

Online learning experience
Undergraduate sports students
COVID-19
The community of inquiry (CoI) framework
Education
==== Body
pmc1 Introduction

The Coronavirus disease 2019 (COVID-19) outbreak has had a detrimental impact on the economies of several nations [1]. The impact of the pandemic on numerous multinational organizations, particularly within the education sector, is deemed unstoppable and unmanageable [2]. In response to the global crisis posed by the COVID-19 pandemic, governmental entities implemented urgent measures to address the situation, including issuing directives to close schools and educational establishments globally [3]. Consequently, to curb the consequences of the outbreak, several countries in the world have implemented nationwide closures of educational institutions, whereas others have opted for localized closure measures [4,5]. In light of the worldwide epidemic, various educational authorities in China have proposed replacing traditional classroom instruction with distance education. This proposal emphasizes the prevailing concerns and uncertainties surrounding the execution of this transition and its implications on student learning outcomes across diverse academic levels [6]. The educational sector in China has demonstrated the impact of macro ergonomic evaluations on academic performance, specifically with teaching methodologies and technology utilization by teachers and students. These assessments have influenced various aspects, such as learning styles and modes of acquiring knowledge [7]. Evaluating students' online learning aptitudes at this juncture is essential, given the absence of alternative educational avenues amidst the pandemic.

Due to the ongoing suspension of educational activities, there has been an observable surge in the population of school-aged children not currently attending formal schooling. A research investigation conducted in Ghana aimed to examine the impact of COVID-19 on the operational functions of educational institutions [8]. They identified several challenges encountered by students amidst the school closure prompted by the COVID-19 pandemic. These obstacles notably involve the limited capacity of students to effectively engage in remote learning from their residences, thereby exposing the inefficiencies associated with implementing online educational approaches. Several previous scholarly investigations have indicated that the transition to online learning negatively impacts students' learning capabilities [[9], [10], [11]]. This arises from the challenges they encounter while trying to adapt to this novel mode of education, their inadequate technical proficiency in handling technological devices, the absence of sufficient technological platforms for certain subjects, and the adverse consequences resulting from the sudden implementation of online learning [12,13].

Online learning, a recently emerged educational medium, presents various aspects that warrant further education research. In the study conducted by Thongsri et al. (2021) [14], the researchers aimed to investigate the correlation between certain variables. The study explored the adjustment process of higher education students in adapting to online education by employing the structural equation model (SEM) and machine learning techniques to examine and establish associations among self-directed learning, motivational learning, online communication, self-efficacy, and learner control. These determinants significantly influenced learner preparedness in the context of online learning. An empirical investigation in India revealed that many students do not possess the requisite electronic devices for engaging effectively in online learning [15]. The findings indicated that a portion of the student population lacks access to appropriate technological devices for optimal utilization of essential educational resources, while another segment faces inadequate internet connectivity. In virtual education, learners encounter the challenges of fatigue and isolation and recognize the pressing need for conducive learning environments. These studies are constrained by descriptive statistical methods and a narrow focus solely on school students. In another investigation carried out in New Zealand, the authors examined the various determinants that affect the process of technology acquisition in an educational setting [16]. The study's findings revealed that both individual factors and systemic variables impacted the acquisition and enhancement of technical literacy. In the United States, research conducted a thorough investigation into the determinants of learning, focusing on various factors such as alterations in physical and sensory capabilities, speed and temporal aspects, attitudes, cognitive aptitude and achievement, modifications in memory functioning, as well as changes in adaptability and psychological well-being [17]. This study concentrates on the elderly population. Another investigation revealed that several factors influence a nursing student's capacity for acquiring knowledge. These factors include the learning atmosphere, supportive services available to the student, attributes of the instructor, challenges encountered by the learner, and personal characteristics. It has been determined that the student's perspective impacts various parameters related to learning [20]. Ong et al. (2021) conducted a study during COVID-19 to examine various aspects of the outbreak [18]. The researchers examined the discernible attributes of online learning as preferred by students in senior high school. However, the study solely examined aspects of the delivery type, assigned tasks, assessment methods, virtual laboratory usage, interface layout, and delivery platform. Despite the existing body of research, there is currently a dearth of scholarly literature addressing the behavioral experiences of undergraduate sports students through online educational platforms.

The proposed work is justified on practical and social grounds, as it has the potential to contribute valuable insights into educational strategies. This, in turn, could significantly impact both the academic community and broader societal interests. We aim to address the pressing demand for efficient methods of virtual educational environments in response to unforeseen disruptions, such as the COVID-19 pandemic. Identifying potential determinants impacting the success of online learning outcomes can offer valuable insights for educators and curriculum developers in designing and implementing more efficacious online courses. It is of utmost importance for students studying sports to address the distinct challenges they encounter when translating practical skills into an online learning environment. This is crucial to ensure their academic advancement is seamless, particularly during global uncertainty. This study investigates the distinct challenges and educational needs of students pursuing sports education through online learning, a demographic that has received inadequate representation in existing literature. The research employs the Community of Inquiry (CoI) framework to analyze the complex interplay of teaching, social, and cognitive presence within sports education. This approach not only fills a substantial gap in the existing body of literature but also lays the groundwork for creating specialized pedagogical strategies tailored to the unique needs of this particular student demographic. Henceforth, the present work is guided by the following research objectives:• To investigate the influence of socio-demographic factors on the OLE of Chinese undergraduate sports students

• To assess the association between teaching presence, social presence, cognitive presence, and overall learning experience in an online educational context by employing the CoI framework

1.1 Theoretical and conceptual framework

The study employs the CoI model approach, introduced by Ong et al. (2023) [19], to analyze the OLE of Chinese undergraduate sports students. Although the fundamental CoI model remains intact, Fig. 1 contextualizes its components within our study group. The theoretical and conceptual framework draws upon established learning theories, including behaviorism, cognitivism, and social constructivism, as well as the CoI framework implemented by Ong et al. (2023) [19]. The implementation of the CoI framework was motivated by its status as a validated tool for evaluating educational experiences in the context of online learning [20]. The two methodologies were employed to establish a more refined framework for investigating the study's specific scenario, aiming to assess the determinants impacting the perceived OLE of university sports students in China. The theoretical framework modifies behaviorism, cognitivism, and social constructivism to yield interactive outcomes. Based on extant literature, the three factors of teaching presence, cognitive presence, and social presence have been identified as significant influences on the quality of online discussion experiences. The work conducted by Maddrell et al. (2020) [22] demonstrated that these components are instrumental in advancing higher-order cognitive skills in both students and educators. Consequently, we posit the following hypothesis:Hypothesis 1 (H1) Cognitive presence significantly influences the overall OLE of Chinese undergraduate sports students.

The cognitive presence facilitates meaningful learning by immersing students in the content, critically examining it, and incorporating new knowledge [21]. Previous studies, such as those conducted by Ong et al. (2023), have shown the beneficial effect of cognitive presence on OLE, indicating that increased cognitive involvement results in enhanced learning experiences. According to Garrison and Vaughan (2008) [22], cognitive presence is primarily aimed at facilitating students' development of the essential skills required to progress through the initial stages of learning. Anderson et al. (2001) [23] posited that the effectiveness of engaging in online discussions is contingent upon the development and incorporation of cognitive and social processes.

Hypothesis 2 (H2) Teaching presence significantly impacts the online learning environment of Chinese undergraduate sports students.

Effective teaching is essential for the organization and direction of the learning process and for providing explicit instructions, constructive feedback, and assistance [24]. A plethora of investigations have demonstrated that an effective teaching presence can significantly improve student satisfaction and academic achievement [[25], [26], [27]]. This hypothesis is based on the premise that carefully crafted and effectively guided instruction is crucial in enhancing learning.

Hypothesis 3 (H3) Social presence significantly affects the OLE of Chinese undergraduate sports students.

Social presence is crucial in creating a sense of community and belonging, essential for keeping students engaged and involved. Ong et al. (2023) [28] have shown that increased social interaction and connection result in fulfilling and successful online learning experiences. Likewise, Kreijins et al. (2014) [29] defined social presence as how students' participation and interaction influenced the online learning environment. The literature has also highlighted that these students must connect with other students, especially in a virtual context [28]. This would help them gain the confidence needed to participate in the interchange of ideas and perspectives. Cifuentes [30] proposed using technology and media to inspire students in online classes, considering their socio-emotional surroundings.

Hypothesis 4 (H4) Triggering events play a significant role in cognitive presence and facilitating knowledge acquisition and comprehension.

When certain events occur, they spark a process of thinking and learning in individuals, encouraging them to investigate and find solutions. The importance of these occurrences lies in their capacity to encourage thinking and the building of knowledge, as demonstrated by Ong et al. (2023) [28], Kurata et al. (2023) [31], and Sadaf et al. (2021) [32].

Hypothesis 5 (H5) The exploration process influences the facilitation of knowledge acquisition and comprehension through cognitive presence.

The exploration process encompasses learners' active pursuit of pertinent information and resources to address stimuli that prompt their inquiry [33]. This particular stage is crucial in enhancing comprehension and promoting cognitive engagement, as research on successful online learning methodologies emphasizes. The facilitation of exploration plays a crucial role in promoting higher-order cognitive processes and comprehension [33,33]. Implementing discussion strategies promoting exploration and inquiry has been shown to enhance cognitive presence and facilitate improved learning outcomes [34]. Additionally, the exploration process contributes to developing metacognitive skills, enabling learners to monitor and regulate their learning activities effectively, thereby improving their capacity to acquire and comprehend new knowledge [35,36]. Hence, it is imperative to engage in exploration as it plays a vital role in enabling the acquisition of knowledge and understanding through cognitive engagement within pedagogical settings.

Hypothesis 6 (H6) The resolution process influences the facilitation of knowledge acquisition and comprehension through cognitive presence.

The concept of resolution involves the application of newly acquired knowledge to address issues and incorporate this knowledge into the learning process [37]. The resolution process is crucial in attaining advanced cognitive outcomes, constituting a fundamental element of cognitive presence [33]. Research has indicated that attaining resolution is essential for facilitating profound learning and efficient integration of knowledge [38,39]. The resolution phase is conducive to a constructivist educational approach, wherein learners actively test and apply their knowledge, improving understanding and retention [20]. Akyol and Garrison (2011) [40] and Darabi et al. (2011) [34] suggest that promoting resolution can heighten cognitive presence and positively impact learning outcomes. Additionally, participation in problem-solving activities during the resolution process promotes the development of critical thinking skills and facilitates a deeper comprehension of the subject matter [41,42].

Hypothesis 7 (H7) The comprehension of subject matter through cognitive presence is contingent upon the level of understanding.

Comprehension denotes heightened cognitive engagement, wherein individuals amalgamate and internalize information [40]. Research has indicated that higher levels of cognitive presence can be attained through critical thinking and reflection, which are crucial for developing in-depth understanding and comprehensive comprehension [38,40]. Bloom's taxonomy classifies cognitive abilities ranging from fundamental knowledge to more advanced skills, emphasizing that the progression towards greater levels of comprehension entails transcending mere recollection to foster deeper understanding and application [43]. Meyer (2003) [44] and Richardson & Ice (2010) [37] suggest that using instructional approaches that encourage prolonged cognitive involvement and reflective thinking results in enhanced levels of comprehension and understanding. Moreover, adopting a constructivist approach underpinned by the CoI framework enhances cognitive presence and fosters heightened awareness [20].

Hypothesis 8 (H8) The acquisition of knowledge through perception and comprehension, along with cognitive presence, is contingent upon the level of knowledge construction.

The process of knowledge construction entails the development of novel conceptual frameworks and their incorporation into pre-existing cognitive structures [45,46]. The cognitive presence supports learners' acquisition and application of new knowledge. Wang and Kang (2006) [47] offered an elucidation of how knowledge construction fosters the processing, dissemination, and generation of information, elucidating how learners depend on available information to formulate concepts and derive meaning. On the contrary, Oztok (2014) [48] argues that knowledge creation is a collaborative and ongoing process rather than a static outcome. Ültanir (2012) [49] observed that individuals acquire knowledge and develop awareness through cognition, which depends on their perceptions and existing understanding. These results indicate that increased knowledge construction is critical in facilitating cognitive engagement and improving learning outcomes within online instructional settings.

Hypothesis 9 (H9) The efficient and effective utilization of available learning materials significantly influences cognitive presence.

Cognitive presence, defined as the mental, emotional, and physical preparedness of learners to engage in learning activities, is substantially impacted by the proficient and effective utilization of learning resources. Bandura's social cognitive theory posits that the availability of resources and their effective utilization contribute to enhancing self-efficacy, leading to improved cognitive preparedness [50]. Mayer (2002) [51] contends that meticulously crafted multimedia educational resources can enhance understanding and memory retention, equipping learners with the necessary skills to tackle more intricate cognitive tasks. Kahu et al. (2015) [52] and Pintrich & Groot (1990) [53] have highlighted the significance of students' access to and proficient utilization of learning resources, as they play a crucial role in enhancing student engagement and preparedness for learning. Moreover, research conducted by Azevedo & Cromley (2004) [54] and Anthony (2008) [55] indicates that implementing self-regulated learning strategies and well-designed instructional materials can decrease cognitive load and improve cognitive preparedness. Zimmerman's (2000) [56] research on self-regulation further emphasizes resource management's significance in learning, while Jeno et al.'s (2019) [57] work illustrates that proficient mobile learning tools lead to improved cognitive readiness and academic success. The findings presented in this study support the hypothesis that the proficient and successful utilization of educational resources is essential for augmenting cognitive preparedness in academic settings.

Hypothesis 10 (H10) Self-efficacy significantly influences cognitive presence by fostering confidence and a belief in the learner's abilities and expertise.

Self-efficacy, an individual's confidence in their ability to accomplish goals, is a significant factor in cognitive presence. Enhanced self-efficacy has been shown to increase learners' confidence and motivation, leading to more profound cognitive engagement [58,59]. Several empirical investigations have demonstrated the positive influence of elevated self-efficacy on students' levels of satisfaction, persistence, motivation, and adoption of effective learning strategies [[60], [61], [62]]. These outcomes indicate that promoting self-efficacy can improve cognitive presence through enhancing learners' confidence and engagement, ultimately resulting in more favorable learning outcomes.

Hypothesis 11 (H11) The design and organization of a curriculum significantly impact the teaching presence's capacity to construct a practical framework for presenting knowledge materials.

Designing and structuring the curriculum is essential in establishing a teaching presence, offering the necessary framework and coherence for successful teaching [46]. As demonstrated in prior investigations, a structured curriculum contributes to learning outcomes. Ong et al. (2023) [28] provided corroborating evidence that virtually administering laboratory sessions and instructional activities is perceived as challenging and not well received by the students. Prasetyo et al. (2021) [3] have also demonstrated that ease of use is critical in attaining student satisfaction with online learning systems.

Hypothesis 12 (H12) The facilitation of learning is a critical component of teaching presence, aiding in the active engagement of students in the educational process.

Facilitation encompasses guiding and supporting learners during the educational process, an essential component for promoting active engagement and participation [21]. Effective facilitation has been shown to strengthen the instructor's presence in the teaching process, leading to enhanced learning results [23,63]. It bolsters a constructivist approach to instruction, where learners effectively develop information through guided intuition [20]. Assistance also upgrades cognitive engagement and produces more profound learning results [40]. Successful help keeps up understudy engagement and builds community in online and mixed learning situations [64,65]. Hence, encouraging learning may be essential to educating nearness, supporting students' dynamic engagement, and guaranteeing effective instructive involvement.

Hypothesis 13 (H13) Learning communities play a critical role in cultivating a conducive environment for establishing an effective teaching presence in education.

Establishing a nurturing and stimulating learning environment requires the involvement of learning communities [66]. These communities let students connect, build relationships, and feel like they belong in the setting of online learning. Meaningful learning experiences depend on a practical teaching presence, encompassing the planning, directing, and supporting cognitive and social processes [63]. According to existing empirical evidence, effective teaching techniques are facilitated, and cognitive presence is enhanced by active engagement in learning communities—vital elements of teaching presence and a strong feeling of community foster student involvement and support instructional activities [20,64]. Incorporating online and in-person learning communities improves student engagement and boosts teachers' presence in mixed-learning environments [65]; therefore, they are essential for developing a successful teaching presence because they encourage student participation, teamwork, and community.

Hypothesis 14 (H14) The facilitation of open communication is a critical determinant of social presence, exerting a substantial influence on the exchange and cooperation of concepts within the realm of interpersonal interaction.

Effective and frequent communication is paramount in creating and sustaining a social presence within virtual learning settings [67]. The concept of social presence is characterized by the capacity of learners to convey themselves socially and emotionally within the CoI framework [21]. It is vital in facilitating significant interactions and establishing a sense of community. Research has indicated that social presence correlates with student satisfaction and perceived learning outcomes [68,69]. Open communication fosters uninhibited exchange and collaboration of ideas, thereby augmenting participation and involvement in online learning [21]. Additionally, promoting open communication enhances learning outcomes and self-efficacy by fostering a sense of connectivity and support among learners [70,71]. These results emphasize the significance of fostering transparent communication in establishing a vibrant and all-encompassing virtual learning setting where students can engage in productive collaboration and meaningful knowledge construction.

Hypothesis 15 (H15) The cohesiveness of a group is a critical component of social presence and plays a significant role in influencing its members' relationships and social integration.

Group cohesiveness, the degree of interconnectedness and mutual support among group members, plays a substantial role in shaping social presence and integration. Groups with strong cohesion positively impact social presence, improving learning outcomes [72]. The degree of a peer's contentment and satisfaction with other group members influences the social cohesiveness and unity of the group as a whole [73]. In response, facilitating collaborative learning, exchanging ideas, and interpersonal interaction among learners has been shown to simplify the learning process [29]. Enhanced student engagement and academic achievement are closely associated with the frequency and quality of student interactions [19,74].

Fig. 1 The community of inquiry (CoI) framework integrating new dimension [19].

Fig. 1

1.2 The present study

A plethora of research has been conducted on online learning; however, considerable gaps persist, particularly regarding the specific challenges undergraduate sports students encounter. The oversight of this aspect is of utmost importance as it has the potential to result in the design of support systems and teaching methods that do not adequately address the needs of all student populations. The current body of literature frequently provides generalized findings across various student populations, neglecting to address the specific educational and training needs unique to sports students. These students may have distinct engagement with online platforms due to their specialized requirements. Furthermore, there is a dearth of comprehensive analyses in the existing literature that seek to elucidate the interconnectedness of various factors influencing online learning outcomes and their predictive capacity on successful learning experiences, particularly in the context of the COVID-19 pandemic.

Furthermore, there is a dearth of longitudinal studies employing cross-lagged models to monitor and comprehend the directional effects among fundamental variables over an extended period, particularly within the realm of sports education amidst the conditions presented by a pandemic. Our research expands on the seminal work of Ong et al. (2023) [19], who employed deep learning neural network technology to examine primary school students' OLE using the CoI framework. Our study focuses on Chinese undergraduate sports students to investigate the connection between teaching presence, social presence, cognitive presence, and overall OLE, employing multiple regression analysis. This methodological change offers insights unique to sports education by broadening the CoI framework's applicability to a new demographic and educational setting and presenting an alternative analytical viewpoint.

2 Methods

2.1 Participants enrollment

A cross-sectional survey was carried out at two Chinese universities using a cluster sampling technique. The selection of these institutions was based on the distinctiveness of their sports programs, which serve as representative examples of comprehensive and competitive sports education environments within urban and semi-urban settings in China. Furthermore, these higher education institutions boast a substantial population of student-athletes, thereby contributing to a sizable and diverse sample that amplifies the statistical significance and broader applicability of our research findings within the context of sports education. Detailed information about the chosen universities, their sports programs/departments, and the implementation of online learning during the pandemic can be found in Supplementary File 1. The data were collected between April 2023 and June 2023 using a variety of social media platforms, ensuring we covered enough time to allow all participants a convenient opportunity to respond. The questionnaire was available 24 h a day to accommodate the diverse schedules of sports students, who often have irregular training and academic hours. The preliminary questionnaire was in the English language. The study materials were translated into Mandarin Chinese to accommodate the research participants in China. The translation process entailed the application of a conventional forward and backward translation approach to ensure the precision and suitability of the linguistic expressions utilized. Subsequently, the translated questionnaire underwent a pilot test with a limited sample of sports students to corroborate its linguistic and contextual fidelity. The first translation was done by experienced bilingual translators who were proficient in Mandarin and English. To ensure the translated version delivered the same things as the original, a different team unaware of the original questions performed a reverse translation. The discrepancies were addressed through collaborative discussions between the research team and professional translation experts. After completing the translation process, the questionnaire underwent pilot testing with a sample of 40 individuals from the intended target population. Feedback was obtained concerning the inquiries' clarity, relevancy, and cultural appropriateness, resulting in slight modifications before the ultimate implementation.

2.2 Sample size calculation

We performed a power analysis with G* power to calculate the sample size for our analysis. Based on a medium effect size of f2 = 0.15, α = 5 %, a power level of 0.80, and the six predictors, the preliminary estimation suggested a sample size of 120 individuals. To adjust for the clustering effect, with an intraclass correlation (ICC) of 0.01 and an average cluster size of 50, the design effect was computed to be 1.49 using formula 1+(50-1) *0.01, resulting in an adjusted sample size of approximately 179 participants. To further strengthen the credibility of our findings and enable a comprehensive subgroup analysis, we sought to have a final sampling size of 402 individuals, which significantly exceeded our estimated requirements.

The increased sample size facilitates more accurate estimations and enhanced applicability of the research outcomes to the broader population of athletic students.

2.3 Eligibility criteria

The survey targeted individuals who met two inclusion criteria: those above 18 and those enrolled as undergraduate sports students. Participants below the age of 18 and those who did not possess an undergraduate status were deemed ineligible for inclusion in this study. The questionnaires were excluded due to the presence of missing or incomplete information. Henceforth, a cumulative of 402 respondents were incorporated in the ultimate analysis.

2.4 Ethical consideration

The survey questionnaires were designed following the fundamental principles of anonymity and voluntary participation. All participants were duly informed about their right to make decisions regarding their participation in the study, emphasizing their freedom to decline or withdraw their involvement at any research stage. The ethical approval was granted by the Liaoning Normal University and adhered to the Declaration of Helsinki and its later amendments (P#2014/65X).

2.5 Research questionnaire

We adopted the questionnaire from the work of Ong et al. (2023) [19], which consisted of four primary sections (learning experience (dependent variable), cognitive presence, teaching presence, and social presence) and additional sub-domains evaluated on a 5-point Likert scale. This decision was made based on the robust validation and reliability of the primary instrument, which is consistent with our research aims. For a comprehensive understanding of the constructs and items utilized in the questionnaire, we direct readers to the work of Ong et al. (2023) [19]. Before the analysis, a pilot study was conducted to determine the validity of the study questionnaire (Supplementary File 2).

2.6 Statistical analysis

The statistical analyses were performed utilizing the SPSS software program with Version 27. Initially, preliminary analyses were conducted through exploratory factor analysis to evaluate the reliability and validity of the items and constructs. The model's fitness was evaluated by employing various statistical measures such as root-mean-squared error of approximation (RMSEA), standardized root-mean-squared residual (SRMR), comparative fit index (CFI), Tucker-Lewis index (TLI), and chi-square goodness-of-fit statistics. We proceeded with the analysis of the variables, examining them in terms of descriptive statistics and bivariate correlation. Prior to multiple linear regression analysis, we thoroughly verified several vital assumptions to ensure the validity of results, i.e., Durbin-Watson for independence of residuals, residual plots for homoscedasticity, Shapiro-Wilk test for assessing normality, and variance inflation factor for assessing multicollinearity. The analytical approach was chosen to enable the investigation of the combined impact of various independent variables on a singular dependent variable, specifically the OLEs of undergraduate sports students. Once all assumptions were met, we employed multiple linear regression analysis to ascertain the potential predictive factors of OLE determinants. All the significant level was set at p < 0.05.

3 Results

3.1 Reliability and validity analysis

A reliability assessment was performed on the measurement model, utilizing data obtained by administering questionnaires. The findings revealed that the Cronbach's alpha coefficients of all selected study constructs varied from 0.887 to 0.952, suggesting a satisfactory level of internal consistency.

In the subsequent phase of the study, the data was examined for its appropriateness in conducting exploratory factor analysis (Table 1). The Kaiser-Meyer-Olkin (KOM) sampling adequacy measure yielded a value of 0.935 (>0.700), indicative of the suitability of the data for conducting exploratory factor analysis. Furthermore, the significance level associated with Bartlett's sphericity test was determined to be significant (p < 0.001), further supporting the appropriateness of the data for factor analysis. The factor loading values for each item exceeded the minimum threshold criterion of 0.500, while the construct reliability (CR) values for each construct exceeded 0.700. The AVE values for each construct exceeded the prescribed threshold of 0.500, indicating favorable levels of reliability and validity within the scale.Table 1 Exploratory factor analysis results.

Table 1Construct	Code	Standardized factor loadings	Cronbach's α	CR (>0.7)	AVE (>0.5)	
Online learning experience	OLE-1	0.867	0.937	0.804	0.657	
OLE-2	0.812				
OLE-3	0.776				
OLE-4	0.785				
Cognitive performance	COGP-1	0.723	0.896	0.843	0.643	
COGP-2	0.849				
COGP-3	0.828				
Triggering events	TRE-1	0.823	0.901	0.838	0.633	
TRE-2	0.753				
TRE-3	0.810				
Exploration	EX-1	0.693	0.887	0.767	0.524	
EX-2	0.792				
EX-3	0.683				
Resolution	RES-1	0.856	0.923	0.889	0.728	
RES-2	0.874				
RES-3	0.828				
Level of understanding of content	LUC-1	0.833	0.936	0.900	0.643	
LUC-2	0.734				
LUC-3	0.766				
LUC-4	0.854				
LUC-5	0.817				
Level of constructing knowledge	LCK-1	0.778	0.952	0.913	0.635	
LCK-2	0.783				
LCK-3	0.813				
LCK-4	0.838				
LCK-5	0.794				
LCK-6	0.774				
Level of managing resources	LMR-1	0.793	0.911	0.853	0.592	
LMR-2	0.778				
LMR-3	0.758				
LMR-4	0.748				
Self-efficacy	SE-1	0.762	0.943	0.914	0.603	
SE-2	0.756				
SE-3	0.779				
SE-4	0.818				
SE-5	0.726				
SE-6	0.843				
SE-7	0.745				
Teaching presence	TP-1	0.816	0.904	0.846	0.647	
TP-2	0.832				
TP-3	0.763				
Design and organization	D&O-1	0.829	0.917	0.880	0.647	
D&O-2	0.817				
D&O-3	0.783				
D&O-4	0.788				
Facilitation	FCL-1	0.733	0.895	0.885	0.563	
FCL-2	0.755				
FCL-3	0.716				
FCL-4	0.773				
FCL-5	0.749				
FCL-6	0.774				
Learning Community	LCO-1	0.774	0.913	0.864	0.614	
LCO-2	0.825				
LCO-3	0.756				
LCO-4	0.778				
Social presence	SCP-1	0.845	0.896	0.884	0.717	
SCP-2	0.867				
SCP-3	0.828				
Open communication	OPC-1	0.889	0.907	0.885	0.721	
OPC-2	0.786				
OPC-3	0.869				
Group cohesion	GRC-1	0.799	0.893	0.865	0.682	
GRC-2	0.787				
GRC-3	0.888				
CR: Composite reliability, AVE: Average variance extracted.

3.2 Model fit analysis

The maximum likelihood method was employed to assess the model parameters. The evaluation of the overall adequacy of the model reveals that all of the indices satisfied the required testing standards. Hence, the model exhibited a strong fit, thus yielding satisfactory outcomes (Table 2).Table 2 Model fitness.

Table 2Indices	RMSEA	SRMR	CFI	TLI	χ2/df	
Estimate	0.063	0.054	0.945	0.932	1.76	
RMSEA: root mean squared error of approximation, SRMR: standardized root mean squared residual, CFI: comparative fit index, TLI: Tuckey-Lewis index.

3.3 Socio-demographics

Table 3 demonstrates the study participants' socio-demographic characteristics in the present survey. With 60.20 % of participants between the ages of 18–21 and 39.80 % between the ages of 22–25, the participants are primarily younger, demonstrating a statistically significant difference in the distribution of participants across these age categories. In addition, the study participants exhibit a moderate balance in gender representation, with 54.48 % identifying as male and 45.52 % identifying as female, yielding a statistically significant gender discrepancy (p-value <0.001). Moreover, study participants were predominantly from urban communities compared to rural (urban: 60.48 % vs. rural: 39.55). Likewise, more than half of the participants demonstrated an average annual family income of ≥50,000 RMB. The participants in the study are stratified by their level of undergraduate education, with the second year demonstrating the highest proportion of representation at 30.60 % and the first year exhibiting the lowest at 16.17 %. The graphical presentation of the basic demographics of the study constructs is presented in Fig. 2.Table 3 Socio-demographic characteristics of participants (n = 402).

Table 3Variable	Frequency (%)	p-value	
Age		<0.001	
 18-21	242 (60.20)		
 22-25	160 (39.80)		
Sex		<0.001	
 Male	219 (54.48)		
 Female	183 (45.52)		
Community		0.042	
 Rural	159 (39.55)		
 Urban	243 (60.48)		
Average annual family income (RMB)		0.036	
 <50,000	172 (42.79)		
 ≥50,000	230 (57.21)		
Year of undergraduate education		0.129	
 1st	65 (16.17)		
 2nd	123 (30.60)		
 3rd	116 (28.86)		
 4th	98 (24.38)		

Fig. 2 Demographic snapshot of the study constructs.

Fig. 2

3.4 Descriptive and bivariate correlational analysis of study constructs

The descriptive and bivariate correlation estimations were conducted for the study variables, and the outcomes are demonstrated in Table 4. We observed strong positive correlation between cognitive presence and teaching presence (r = 0.530, p < 0.001), cognitive presence and social presence (r = 0.459, p < 0.001), teaching presence and social presence (r = 0.433, p < 0.001), and teaching presence and learning experience (r = 0.504, p < 0.001). However, the correlation between cognitive presence and learning experience was positive but weaker (r = 0.217, p < 0.01).Table 4 Descriptive and bivariate correlational analysis.

Table 4		X‾±SD	1	2	3	4	
1	Cognitive presence	2.13 ± 0.78	–				
2	Teaching presence	3.42 ± 0.95	0.530***	–			
3	Social presence	2.78 ± 1.42	0.459***	0.433***	–		
4	Online Learning experience	2.34 ± 0.88	0.217**	0.504***	0.497***	–	
**p < 0.01, ***p < 0.001.

3.5 Multiple linear regression analysis

Table 5 presents the outcomes of the multiple linear regression analysis carried out to evaluate the influential aspect of students' OLE. The results displayed a robust, positive, and statistically significant correlation to open communication (β=0.278,p<0.001), social presence (β=0.231,p<0.001), design and organization (β=0.241,p<0.001), and facilitation (β=0.175,p<0.001). Furthermore, it should be noted that the variables of teaching presence (β=0.184,p=0.034), cognitive presence (β=0.110,p=0.02), level of understanding content (β=0.035,p−0.042), level of managing resources (β=0.049,p=0.021), level of constructing knowledge (β=0.043,p=0.034), and self-efficacy (β=0.037,p=0.137) exhibited positive associations, albeit with a relatively weak magnitude. In contrast, the remaining constructs exhibited a negligible correlation with the OLE of the participants in the study (Fig. 3).Table 5 Multiple linear regression analysis of the OLE of the participants.

Table 5	b (SE)	β	t	p-value	R2	F	
Cognitive presence	0.708 (0.255)	0.110	2.78	0.020	0.11	46.28***	
Triggering event	0.055 (0.139)	0.010	0.410	0.562			
Exploration	0.193 (0.205)	0.026	0.912	0.272			
Resolution	0.091 (0.133)	0.016	0.683	0.352			
Level of understanding of content	0.401 (0.225)	0.035	1.77	0.042			
Level of constructing knowledge	0.241 (0.169)	0.043	1.42	0.034			
Level of managing resources	0.160 (0.095)	0.049	1.65	0.021			
Self-efficacy	0.220 (0.175)	0.037	1.26	0.137			
Teaching presence	0.745 (0.245)	0.184	3.04	0.030	0.42	112.87***	
Design and organization	0.934 (0.118)	0.241	7.91	<0.001			
Facilitation	0.849 (0.143)	0.175	5.94	<0.001			
Learning Community	0.007 (0.116)	0.003	0.059	0.788			
Social presence	0.828 (0.101)	0.231	8.19	<0.001	0.30	78.23***	
Open communication	1.078 (0.121)	0.278	8.91	<0.001			
Group cohesion	0.025 (0.076)	0.013	0.367	0.547			
Note: Significant level was set at *p < 0.05, **p < 0.01, and ***p < 0.001.

Fig. 3 Theoretical framework.

Fig. 3

4 Discussion

The present study expands upon the foundational research of Ong et al. (2023) [19], who employed the CoI framework to assess primary school students' OLE by applying deep learning neural network methodology. However, our study demonstrates substantial discrepancies in contextual background and methodological approach. The primary aims of this study were two-fold: firstly, to examine the impact of socio-demographic variables on the OLE of undergraduate sports students in China, and secondly, to evaluate the association between teaching presence, social presence, cognitive presence, and overall learning experience within an online educational setting using the CoI framework through the application of multiple regression analysis. This transition expands the use of the CoI framework and provides novel perspectives relevant to sports education. The results of our study indicate that open communication, social presence, design & organization, and facilitation exhibit significant predictors of online learning environment. The findings of this study have significant practical implications for the design and implementation of targeted interventions aimed at enhancing the online learning experiences of sports students. These interventions can focus on improving critical factors identified in this study.

The results of the regression analysis indicated a significant relationship between cognitive presence and the OLE among sports students (supporting H1, with particular dimensions including the understanding of content (supporting H7), construction of knowledge (supporting H8), and management of resources (supporting H9) demonstrating significant contributions. Nevertheless, other dimensions of cognitive presence, such as self-efficacy (H10), resolution (H6), exploration (H5), and triggering events (H4), did not demonstrate discernible predictive power. The diverse findings indicate that some aspects of cognitive presence are essential for online learning environments, while others may hold less significance within this particular context. Cognitive presence refers to the ability of students to comprehend and engage with the content and deliberations of a given lesson or discussion [38]. This evidence demonstrates that the student has achieved sufficient comprehension of the course's fundamental and profoundly impactful concepts through engagement with the provided material and active involvement in class discussions.

The considerable influence of understanding content on OLE suggests that students with a greater understanding of the subject matter express enhanced learning experiences. Richardson and Ice (2010) [37] and Shea and Bidjerano (2009) [37] corroborate our findings, highlighting the significance of cognitive presence in improving learning experiences. One key challenge present-day online learning platforms encounter is students' capacity to maintain focus during lectures. Given the abundance of easily accessible distractions in the home environment, teachers must recognize that students may experience reduced concentration levels [75]. Likewise, the significant association of resource management and knowledge construction, two variables associated with cognitive presence, significantly impacts the perceived OLE. This passage elucidates that using learning resources effectively and efficiently is crucial in enhancing mental availability among students. Similarly, it can be inferred that acquiring knowledge through perception and comprehension, in conjunction with cognitive processes, is contingent upon the extent to which knowledge is constructed [76]. This implies that students can access supplementary resources on the course, should they desire additional information, and subsequently apply this newfound knowledge in practical situations. In education, the practical application of resources has been revealed to attain favorable learning outcomes when these resources foster and stimulate student learning. This notion is substantiated by a study that contended that material resources significantly influence students' academic achievement [77]. This influence is attributed to their ability to facilitate comprehending and assimilating abstract concepts and ideas while concurrently discouraging rote memorization.

The insignificant association observed in triggering events, exploration, and resolution may be attributed to the distinctive challenges and limitations introduced by the abrupt shift to online learning in response to the COVID-19 pandemic. Differences in student engagement and the distinctive characteristics of physical education, which often involve active and kinesthetic learning, may have influenced students' capacity for in-depth engagement during the initiation of events and exploratory phases. Prior research has demonstrated that practical disciplines such as sports education encounter unique challenges when transitioning to online formats, which may impact various aspects of the field [78,79]. These results diverge from the findings of Ong et al. (2023) [19], who highlighted these aspects significant in primary education by applying neural network analysis. The disparity underscores the flexibility and situational specificity of various analytical methodologies. The neural network analysis can capture intricate, non-linear relationships, while regression analysis provides comprehensive insights into linear relationships and is extensively advantageous in situations featuring transparent and interpretable variables. Adopting this methodology enabled the direct quantification of the impact of individual cognitive presence constructs on OLE in sports education, yielding valuable and practical implications for improving an online learning environment.

Previous research has underscored the significance of self-efficacy as an additional dimension that did not yield significant predictive power for OLE in our study population [80]. The disparity in our findings may be attributed to variations in student demographics and their previous exposure to online learning. Hodges et al. (2020) [80] demonstrated that varying degrees of familiarity with online learning can significantly impact individuals' perceptions of self-efficacy. These diverse outcomes of our study highlight the intricacy of online learning settings and the significance of contextual determinants. The importance of utilizing diverse methodological approaches in order to achieve a comprehensive understanding of educational phenomena is also underscored. Sun and Chen's (2016) [19] research determined that student satisfaction in online learning is complex and influenced by various contextual factors such as the course's nature and the interaction quality.

In addition, the findings of our analysis demonstrate a significant association between teaching presence and OLE, thus supporting H2 with the dimensions of design & organization (H11) and facilitation (H12), both emerged as significant predictors. These findings are consistent with previous research, such as Ong et al. (2023) [19], which highlighted the significance of well-organized course structure and proficient facilitation in improving students' OLE. The importance of teachers' competence in delivering clear lessons, task instructions, and deadlines within a framework of design & organization has been identified by students as crucial for fostering a positive learning environment [81,82]. The facilitation of educational activities that actively involve students, nurture higher-order cognitive abilities, and help and direction emerged as significant indicators within the context of pedagogy [83]. The findings, as mentioned earlier, are consistent with the research conducted by Garrison & Cleveland-Innes (2005) [66] and Shea et al. (2006) [24]. Educators ought to cultivate an inclusive and supportive classroom environment that fosters a sense of acceptance and encouragement, facilitating student engagement and active participation [24].

On the contrary, the dimension learning community did not produce statistically significant findings, thereby refuting H13. The observed outcome can be explained by the distinctive complications presented by the pandemic, which interjected disruptions to customary modes of community establishment and student engagement. Ong et al. (2023) [19] revealed that the learning community is pivotal in primary education. However, the specific context of sports education may necessitate alternative approaches to community building that were not adequately addressed online. Studies indicate that establishing a feeling of community within virtual educational settings presents more significant difficulties in applied fields such as sports education, where incorporating physical presence and direct engagement are essential components of the learning process [84,85]. Moreover, the abrupt shift to virtual learning may have impeded students' capacity to establish substantial relationships and partnerships, thereby affecting the perceived value of the academic community. Additional research is required to create customized approaches to cultivate a sense of community in online sports education, considering this student demographic's particular needs and dynamics.

10.13039/100014337 Furthermore , the findings indicated that social presence significantly impacts the OLE's overall quality, thus supporting H3. In particular, the dimension of open communication (H14) demonstrated a significant predictor in our study sample. This outcome corroborates the results of Ong et al. (2023) [19], Swan (2002) [86], Richardson (2001) [68], and Harastinski (2009) [87] that emphasize the significance of open communication in nurturing a feeling of connection and interaction among students within an online learning setting. Researchers have identified that promoting open communication can improve social interaction and learning outcomes [86,87]. The findings of these investigations illustrate the importance of open communication in creating a supportive and interactive learning environment that is vital for fostering student engagement and satisfaction. Likewise, Garrison et al. (1999) [21] utilized the CoI framework to demonstrate the importance of social presence in establishing a supportive learning environment and promoting meaningful interactions. Furthermore, a social presence contributes to establishing a communal ambiance [68], whereas the absence of social presence can engender misperceptions and apathy, impeding educational endeavors' efficacy [88]. One crucial aspect that presents difficulties in online learning is the limited time available for student interaction, which is only possible during designated lecture sessions [89]. Implementing online learning to create an atmosphere of inclusivity and validation for students, allocating sufficient time for effective communication, and fostering peer interaction is advocated.

On the contrary, the group cohesion dimension analysis did not yield a statistically significant outcome, thereby failing to support H15. The observed disparity could be attributed to the distinct dynamics characteristic of online sports education, in which physical presence and collaborative team activities are conventionally essential for promoting group unity. The transition to an online format amid the COVID-19 pandemic has potentially disrupted traditional approaches to fostering cohesion, reducing perceived group solidarity and collaboration among students [79]. As demonstrated by neural network analysis, Ong et al. (2023) [19] revealed that group cohesion is vital in primary education. However, it is essential to note that the context of sports education presents unique challenges and demands when fostering a cohesive group. Prior investigations indicated that virtual environments present challenges in achieving the same degree of interpersonal bonding and collaborative teamwork as in traditional face-to-face settings [79]. Moreover, the diverse levels of technological competence and access among students may have additionally impeded the formation of group cohesion in our research. Subsequent research endeavors should investigate methods for bolstering group unity within the context of online sports education, with a potential focus on integrating interactive and collaborative resources to mitigate the challenges stemming from the absence of physical proximity.

In conclusion, the present research work contributes to and broadens the CoI theoretical framework by centering on the distinct context of undergraduate sports students, a demographic that diverges substantially from the primary school students examined by Ong et al. (2023) [19]. While Ong et al. (2023) [19] utilized a deep learning neural network to analyze primary education, exploratory factor analysis and multiple linear regression offer a unique methodological approach better equipped to comprehend the intricate experiences of older students in a specialized field. The employment of multiple linear regression facilitated the identification of particular predictors associated with OLE within the context of sports education. This is of significant importance due to the unique pedagogical requirements and participation patterns prevalent in the field of sports education. The selection of this methodological approach is well substantiated in educational research due to its capacity to yield clear, readily interpretable findings concerning the impact of diverse factors on student achievement [90,91]. By applying conventional statistical methodologies, our study adds to the existing body of academic literature with a robust and comprehensible approach that can be reproduced and substantiated in analogous educational environments.

Furthermore, our study's emphasis on undergraduate sports students fills a research gap in the current literature. Previous research, such as the work of Ong et al. (2023) [19] other studies have predominantly focused on younger or general student populations [90,92]. The specificity of the OLE of sports students during the COVID-19 pandemic is crucial, as it presents distinct challenges and opportunities that have not been fully elucidated in studies involving other demographic groups. In conclusion, our study affirms the significance of the CoI framework in various educational settings and underscores the necessity of customizing methodological approaches to align with the distinct attributes of the study population. The dual contribution to theoretical and practical domains highlights the originality and importance of our research.

4.1 Theoretical contributions

The CoI paradigm has been extensively employed within the realm of educational practices. The advent of the COVID-19 pandemic precipitated the implementation of a novel mode of educational delivery wherein students were taught through online platforms. Several studies have employed the CoI framework; however, there is a paucity of research focusing on undergraduate sports education in an online environment. We sought to broaden the theoretical paradigm to identify the fundamental underlying variables that precede the three primary domains within the CoI paradigm. The study's results, following the CoI paradigm, can be utilized by educational institutions to enhance satisfaction among learners engaging in distance learning programs. This study may be a theoretical foundation for future researchers to explore and evaluate student satisfaction, academic performance, and educational experiences. This research may be utilized by government institutions and educational sectors to advocate for implementing a new educational standard focused on enhancing student satisfaction and experience.

4.2 Practical contributions

The global pandemic has profoundly impacted various educational programs, encompassing instructional delivery, assessment methodologies, extracurricular activities, and academic service initiatives. The impediments to adapting to the new pedagogical format, limited technical proficiency, inadequate technological infrastructure for non-technical subjects, and adverse ramifications stemming from the abrupt transition to remote instruction collectively impede students' comprehensive learning within the online educational paradigm. The results of this study underscore the significance of fostering transparent communication in both online and traditional modes of education. This indicates that students pursuing sports education may benefit from a positive academic experience within an online learning environment, particularly when afforded opportunities for open communication and collaboration with classmates. The outcomes also demonstrated the importance of social presence for students, clarifying why they think online communication is valuable for creating impressions without feeling uncomfortable. Proposing that students feel welcomed and appreciated for their individuality promotes a feeling of togetherness and a positive educational environment. Furthermore, the outcomes suggest that teachers significantly shape students' overall positive learning outcomes. A teacher's presence is necessary for guiding students and providing valuable feedback to inspire and improve their work. This research demonstrates that sports students in China have enhanced access to online learning, indicating that they continue gaining knowledge through the Internet. This research will also help educators and government departments improve online education systems.

4.3 Limitations

Despite the beneficial findings of the present investigation, it is essential to acknowledge and address several limitations and recommendations. Initially, the research findings were constrained using constructs from the online questionnaire. It is suggested that future researchers consider conducting a qualitative study that replicates the methodology of the present study. In addition, investigators can observe the interconnections of undergraduate sports students with their teachers and peers, focusing on the indicators outlined in the theoretical framework. Moreover, it is essential to acknowledge that the generalizability of the results may be limited due to the relatively small sample size and the focus on only two universities. This constraint underscores the necessity of prudence when generalizing our findings to larger demographic groups. Subsequent research endeavors should encompass a broader spectrum of educational settings and incorporate larger sample sizes to strengthen the validity and relevance of the research outcomes. Furthermore, cluster sampling was found to be effective in addressing logistical constraints and capturing internal diversity at the two universities. However, it should be noted that using this sampling method may restrict the generalizability of our study findings. This methodology operates under the assumption of uniformity within individual clusters and diversity between clusters, potentially failing to capture the full spectrum of online learning experiences among a more expansive demographic of sports students. At last, the primary focus of our study pertained to the theoretical aspects of online learning for students in the sports field, potentially neglecting the essential element of practical instruction. Subsequent studies should investigate the potential of digital platforms in effectively addressing the practical training requirements inherent in sports education.

5 Conclusion

In conclusion, it is imperative to emphasize the practical implications of our study findings. Improving comprehension of the dynamics of online learning in sports students can provide valuable insights for creating more efficacious educational platforms and instructional strategies. The present study, while situated within a particular context, offers initial data that may be relevant to diverse educational environments, thereby prompting additional research to authenticate and build upon our observations. The scalability of our study highlights its potential to contribute valuable insights for developing national-level policies and educational strategies.

Institutional review board statement

This study was approved by the review board of the Liaoning Normal University, China (P#2014/65X).

Informed consent statement

Informed consent was obtained from all subjects involved in this Study.

Funding

The authors extend their appreciation to 10.13039/100009392 Prince Sattam bin Abdulaziz University for funding this research work through the project number (PSAU/2024/01/921608 ).

Data availability statement

The raw data supporting the findings of this study are available in the supplementary materials.

CRediT authorship contribution statement

Ran An: Writing – review & editing, Writing – original draft, Visualization, Validation, Software, Methodology, Investigation, Formal analysis. Abdullah Addas: Writing – review & editing, Writing – original draft, Visualization, Validation, Supervision, Software, Project administration, Methodology, Investigation, Funding acquisition, Formal analysis. Nadia Rehman: Writing – review & editing, Writing – original draft, Visualization, Validation, Methodology, Formal analysis, Conceptualization. Shazia Rehman: Writing – review & editing, Writing – original draft, Visualization, Validation, Supervision, Methodology, Investigation, Funding acquisition, Formal analysis, Data curation, Conceptualization.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Appendix A Supplementary data

The following are the supplementary data to this article:Multimedia component 1

Multimedia component 1

Multimedia component 2

Multimedia component 2

Appendix A Supplementary data to this article can be found online at https://doi.org/10.1016/j.heliyon.2024.e37159.
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References

1 Kumar A. Impact of the COVID-19 pandemic on teaching and learning in health professional education: a mixed methods study protocol BMC Med. Educ. 21 1 2021 439 10.1186/s12909-021-02871-w 34412603
2 Abumalloh R.A. The impact of coronavirus pandemic (COVID-19) on education: the role of virtual and remote laboratories in education Technol. Soc. 67 Nov. 2021 101728 10.1016/j.techsoc.2021.101728
3 Prasetyo Y.T. Determining factors affecting acceptance of E-learning platforms during the COVID-19 pandemic: integrating extended technology acceptance model and DeLone & McLean IS success model Sustainability 13 15 2021 10.3390/su13158365
4 Hamid R. Sentryo I. Hasan S. Online learning and its problems in the Covid-19 emergency period J. Prima Edukasia 8 1 2020 86 95
5 Simamora R.M. De Fretes D. Purba E.D. Pasaribu D. Practices, challenges, and prospects of online learning during Covid-19 pandemic in higher education: lecturer perspectives Stud. Learn. Teach. 1 3 2020 185 208
6 Joaquin J.J.B. Biana H.T. Dacela M.A. The philippine higher education sector in the time of COVID-19 Frontiers in Education 5 2020 [Online]. Available: https://www.frontiersin.org/articles/10.3389/feduc.2020.576371
7 Gumasing M.J.J. Castro F.M.F. Determining ergonomic appraisal factors affecting the learning motivation and academic performance of students during online classes Sustainability 15 3 2023 10.3390/su15031970
8 Owusu-Fordjour C. Koomson C.K. Hanson D. The impact of Covid-19 on learning-the perspective of the Ghanaian student Eur. J. Educ. Stud. 7 2020
9 Adedoyin O.B. Soykan E. Covid-19 pandemic and online learning: the challenges and opportunities Interact. Learn. Environ. 31 2 2023 863 875
10 Heng K. Sol K. Online learning during COVID-19: key challenges and suggestions to enhance effectiveness Cambodian J. Educ. Res. 1 1 2021 3 16
11 Simamora R.M. The Challenges of online learning during the COVID-19 pandemic: an essay analysis of performing arts education students Stud. Learn. Teach. 1 2 2020 86 103
12 Camargo C.P. Tempski P.Z. Busnardo F.F. Martins M. de A. Gemperli R. Online learning and COVID-19: a meta-synthesis analysis Clinics 75 2020 e2286 33174948
13 Yan L. Whitelock‐Wainwright A. Guan Q. Wen G. Gašević D. Chen G. Students' experience of online learning during the COVID‐19 pandemic: a province‐wide survey study Br. J. Educ. Technol. 52 5 2021 2038 2057 34219755
14 Thongsri N. Chootong C. Tripak O. Piyawanitsatian P. Saengae R. Predicting the determinants of online learning adoption during the COVID-19 outbreak: a two-staged hybrid SEM-neural network approach Interact. Technol. Smart Educ. 18 3 2021 362 379
15 Priyadarshini A. Bhaumik R. E-readiness of senior school learners to online learning transition amid COVID-19 lockdown Asian J. Distance Educ. 15 1 2020 244 256
16 Mawson B. Factors affecting learning in technology in the early years at school Int. J. Technol. Des. Educ. 17 3 2007 253 269 10.1007/s10798-006-9001-5
17 Glass N. Internationalizing nursing: valuing the multiple places and spaces of nursing education The Journal of nursing education 45 10 Oct. 2006 387 388 10.3928/01484834-20061001-01 United States 17058692
18 Ong A.K.S. Students' preference analysis on online learning attributes in industrial engineering education during the COVID-19 pandemic: a conjoint analysis approach for sustainable industrial engineers Sustainability 13 15 2021 8339
19 Ong A.K.S. Cuales J.C. Custodio J.P.F. Gumasing E.Y.J. Pascual P.N.A. Gumasing M.J.J. Investigating preceding determinants affecting primary school students online learning experience utilizing deep learning neural network Sustainability 15 4 2023 3517
20 Swan K. Garrison D.R. Richardson J.C. A constructivist approach to online learning: the community of inquiry framework Information Technology and Constructivism in Higher Education: Progressive Learning Frameworks 2009 IGI global 43 57
21 Garrison D.R. Anderson T. Archer W. Critical inquiry in a text-based environment: computer conferencing in higher education Internet High Educ. 2 2–3 1999 87 105
22 Garrison D.R. Vaughan N.D. Blended Learning in Higher Education: Framework, Principles, and Guidelines 2008 John Wiley & Sons
23 Anderson T. Liam R. Garrison D.R. Archer W. “Assessing Teaching Presence in a Computer Conferencing Context,” 2001
24 Shea P. Li C.S. Pickett A. A study of teaching presence and student sense of learning community in fully online and web-enhanced college courses Internet High Educ. 9 3 2006 175 190
25 Kilis S. Yıldırım Z. “Posting Patterns of Students' Social Presence, Cognitive Presence, and Teaching Presence in Online Learning,” 2019
26 Zhang H. Lin L. Zhan Y. Ren Y. The impact of teaching presence on online engagement behaviors J. Educ. Comput. Res. 54 7 2016 887 900
27 Chakraborty M. Nafukho F.M. Strategies for virtual learning environments: focusing on teaching presence and teaching immediacy J. Online Learn. Res. Pract. 4 1 2015
28 Ong A.K.S. Prasetyo Y.T. Pinugu J.N.J. Chuenyindee T. Chin J. Nadlifatin R. Determining factors influencing students' future intentions to enroll in chemistry-related courses: integrating self-determination theory and theory of planned behavior Int. J. Sci. Educ. 44 4 2022 556 578
29 Kreijns K. Van Acker F. Vermeulen M. Van Buuren H. Community of inquiry: social presence revisited E-learning Digit. Media 11 1 2014 5 18
30 Cifuentes L. A Guide to Administering Distance Learning 2021 Brill
31 Kurata Y.B. Ong A.K.S. Joyosa J.J. Santos M.J.P.S. Predicting factors influencing perceived online learning experience among primary students utilizing structural equation modeling forest classifier approach Eur. Rev. Appl. Psychol. 73 5 2023 100868
32 Sadaf A. Wu T. Martin F. Cognitive presence in online learning: a systematic review of empirical research from 2000 to 2019 Comput. Educ. Open 2 2021 100050
33 Garrison D.R. Anderson T. Archer W. Critical thinking, cognitive presence, and computer conferencing in distance education Am. J. Dist. Educ. 15 1 Jan. 2001 7 23 10.1080/08923640109527071
34 Darabi A. Arrastia M.C. Nelson D.W. Cornille T. Liang X. Cognitive presence in asynchronous online learning: a comparison of four discussion strategies J. Comput. Assist. Learn. 27 3 2011 216 227
35 Akyol Z. Garrison D.R. Ozden M.Y. Online and blended communities of inquiry: exploring the developmental and perceptional differences Int. Rev. Res. Open Dist. Learn. 10 6 2009 65 83
36 Swan K. Shih L.F. On the nature and development of social presence in online course discussions J. Asynchronous Learn. networks 9 3 2005 115 136
37 Richardson J.C. Ice P. Investigating students' level of critical thinking across instructional strategies in online discussions Internet High Educ. 13 1–2 2010 52 59
38 Kanuka H. Garrison D.R. Cognitive presence in online learning J. Comput. High Educ. 15 2004 21 39
39 Garrison D.R. Ben Arbaugh J. Researching the community of inquiry framework: review, issues, and future directions Internet High Educ. 10 3 2007 157 172
40 Akyol Z. Garrison D.R. Understanding cognitive presence in an online and blended community of inquiry: assessing outcomes and processes for deep approaches to learning Br. J. Educ. Technol. 42 2 2011 233 250
41 Bangert-Drowns R.L. Bankert E. “Meta-Analysis of Effects of Explicit Instruction for Critical Thinking.,” 1990
42 Harasim L. Learning Theory and Online Technologies 2017 Routledge
43 Bs B. Taxonomy of educational objectives: the classification of educational goals Handbook; Cogn. domain 1 1956
44 Meyer K.A. Face-to-face versus threaded discussions: the role of time and higher-order thinking J. asynchronous Learn. networks 7 3 2003 55 65
45 Bangert-Drowns R.L. Pyke C. Teacher ratings of student engagement with educational software: an exploratory study Educ. Technol. Res. Dev. 50 2 2002 23 37
46 Kang M. Choi H. Park S. Developing a social presence scale for measuring students' involvement during e-learning process Educ. Technol. Int. 9 2 2008 1 15
47 Wang M. Kang M. Cybergogy for engaged learning: a framework for creating learner engagement through information and communication technology Engag. Learn. with Emerg. Technol. 2006 225 253
48 Oztok M. Towards understanding knowledge construction in online learning EdMedia+ Innovate Learning 2014 2087 2091
49 Ültanir E. An epistemological glance at the constructivist approach: constructivist learning in Dewey, Piaget, and Montessori Int. J. Instr. 5 2 2012
50 Bandura A. “Social foundations of thought and action,” Englewood Cliffs, NJ 1986 23–28 1986 2
51 Mayer R.E. Multimedia learning Psychology of Learning and Motivation vol. 41 2002 Elsevier 85 139
52 Kahu E. Stephens C. Leach L. Zepke N. Linking academic emotions and student engagement: mature-aged distance students' transition to university J. Furth. High. Educ. 39 4 2015 481 497
53 Pintrich P.R. V De Groot E. Motivational and self-regulated learning components of classroom academic performance J. Educ. Psychol. 82 1 1990 33
54 Azevedo R. Cromley J.G. Does training on self-regulated learning facilitate students' learning with hypermedia? J. Educ. Psychol. 96 3 2004 523
55 Anthony R. Jr. Cognitive load theory and the role of learner experience: an abbreviated review for educational practitioners AACE Rev. (Formerly AACE Journal) 16 4 2008 425 439
56 Zimmerman B.J. Attaining self-regulation: a social cognitive perspective Handbook of Self-Regulation 2000 Elsevier 13 39
57 Jeno L.M. Vandvik V. Eliassen S. Grytnes J.-A. Testing the novelty effect of an m-learning tool on internalization and achievement: a Self-Determination Theory approach Comput. Educ. 128 2019 398 413
58 Getenet S. Cantle R. Redmond P. Albion P. Students' digital technology attitude, literacy and self-efficacy and their effect on online learning engagement Int. J. Educ. Technol. High. Educ. 21 1 2024 3
59 Rehman S. Rehman E. Liu B. Potential correlation between self-compassion and bedtime procrastination: the mediating role of emotion regulation Psychol. Res. Behav. Manag. 16 null Dec. 2023 4709 4723 10.2147/PRBM.S431922 38024655
60 Levterova-Gadjalova D. Tsokov G. Self-efficacy among students in higher educational institutions during online learning self-efficacy among students in higher educational institutions during online learning Proc. CBU Soc. Sci. 2 2021 230 235
61 Bećirović S. Ahmetović E. Skopljak A. An examination of students online learning satisfaction, interaction, self-efficacy and self-regulated learning Bećirović S. Ahmetović E. Skopljak A. An Exam. Students Online Learn. Satisf. Interact. Self-Efficacy Self-Regulated Learn. Eur. J. Contemp. Educ vol. 11 2022 16 35 . 1,
62 Özüdoğru G. The effect of distance education on self-efficacy towards online technologies and motivation for online learning J. Learn. Teach. Digit. Age 7 1 2022 108 115
63 Shea P. Bidjerano T. Community of inquiry as a theoretical framework to foster ‘epistemic engagement’ and ‘cognitive presence’ in online education Comput. Educ. 52 3 2009 543 553
64 Rovai A.P. Building sense of community at a distance Int. Rev. Res. Open Dist. Learn. 3 1 2002 1 16
65 Vaughan N.D. A blended community of inquiry approach: linking student engagement and course redesign Internet High Educ. 13 1–2 2010 60 65
66 Garrison D.R. Cleveland-Innes M. Facilitating cognitive presence in online learning: interaction is not enough Am. J. Dist. Educ. 19 3 2005 133 148
67 Fiani I.D. Communication patterns of lecturers with tutors in distance learning Proceeding of the International Conference on Innovation in Open and Distance Learning vol. 3 2022
68 Richardson J.C. Examining Social Presence in Online Courses in Relation to Students' Perceived Learning and Satisfaction 2001 State University of New York at Albany
69 Gunawardena C.N. Zittle F.J. Social presence as a predictor of satisfaction within a computer‐mediated conferencing environment Am. J. Dist. Educ. 11 3 1997 8 26
70 Hostetter C. Community matters: social presence and learning outcomes J. Scholarsh. Teach. Learn. 13 1 2013 77 86
71 Shen D. Cho M.-H. Tsai C.-L. Marra R. Unpacking online learning experiences: online learning self-efficacy and learning satisfaction Internet High Educ. 19 2013 10 17
72 Yoon P. Leem J. The influence of social presence in online classes using virtual conferencing: relationships between group cohesion, group efficacy, and academic performance Sustainability 13 4 2021 1988
73 Bedir D. Agduman F. Bedir F. Erhan S.E. The mediator role of communication skill in the relationship between empathy, team cohesion, and competition performance in curlers Front. Psychol. 14 2023 1115402
74 Routman R. Writing essentials: raising expectations and results while simplifying teaching Educ. Rev. 2005
75 Gumasing M.J.J. Ong A.K.S. Bare M.A.D. User preference analysis of a sustainable workstation design for online classes: a conjoint analysis approach Sustainability 14 19 2022 12346
76 Good T.L. 21st Century Education: A Reference Handbook vol. 1 2008 Sage
77 Means B. Toyama Y. Murphy R. Bakia M. Jones K. “Evaluation of Evidence-Based Practices in Online Learning: A Meta-Analysis and Review of Online Learning Studies,” 2009
78 Bao W. COVID‐19 and online teaching in higher education: a case study of Peking University Hum. Behav. Emerg. Technol. 2 2 2020 113 115 32510042
79 Martin F. Bolliger D.U. Engagement matters: student perceptions on the importance of engagement strategies in the online learning environment Online Learn. 22 1 2018 205 222
80 Hodges C.B. Moore S. Lockee B.B. Trust T. Bond M.A. “The Difference between Emergency Remote Teaching and Online Learning,” 2020
81 Rapanta C. Botturi L. Goodyear P. Guàrdia L. Koole M. Online university teaching during and after the Covid-19 crisis: refocusing teacher presence and learning activity Postdigital Sci. Educ. 2 2020 923 945
82 Kuhfeld M. Soland J. Tarasawa B. Johnson A. Ruzek E. Lewis K. “How Is COVID-19 Affecting Student Learning?,” 2020
83 Wang Y. Stein D. Effects of online teaching presence on students' cognitive conflict and engagement Distance Educ. 42 4 2021 547 566
84 Jaggars S.S. Xu D. How do online course design features influence student performance? Comput. Educ. 95 2016 270 284
85 Martin F. Budhrani K. Wang C. Examining faculty perception of their readiness to teach online Online Learn. 23 3 2019 97 119
86 Swan K. Building learning communities in online courses: the importance of interaction Educ. Commun. Inf. 2 1 2002 23 49
87 Hrastinski S. A theory of online learning as online participation Comput. Educ. 52 1 2009 78 82
88 Kim J. Developing an instrument to measure social presence in distance higher education Br. J. Educ. Technol. 42 5 2011 763 777
89 Chen P.-S.D. Lambert A.D. Guidry K.R. Engaging online learners: the impact of Web-based learning technology on college student engagement Comput. Educ. 54 4 2010 1222 1232
90 Pillai R. Sivathanu B. An empirical study on the online learning experience of MOOCs: Indian students' perspective Int. J. Educ. Manag. 34 3 2020 586 609
91 Hair J.F. “Multivariate Data Analysis, 2009
92 Garrison D.R. Anderson T. Archer W. The first decade of the community of inquiry framework: a retrospective Internet High Educ. 13 1–2 2010 5 9
