Yoshiki B. Kurata,Ardvin Kester S. Ong,Jairus J. Joyosa,Makkie John Prince S. Santos
Predicting factors influencing perceived online learning experience among primary students utilizing structural equation modeling Forest Classifier approach Facteurs prédictifs influant sur l’expérience d’apprentissage en ligne perçue chez les élèves du primaire à l’aide de l’approche de modélisation par équations Forest Classifier
Online discussion experience,Distance learning,COVID-19,Community of Inquiry,Structural equation modeling,Expérience de discussion en ligne,Apprentissage à distance,COVID-19,Communauté d’enquête,Modélisation par équations
Introduction Amid the COVID-19 pandemic, the temporary closure of educational institutions led to the adoption of remote or online learning delivery. Challenges, especially for grade schools were evident. Objective This study aimed to identify factors affecting the perceived online discussion experience of Filipino primary students through distance learning in the National Capital Region, Philippines. Method Variables such as cognitive presence, teaching presence, social presence, and online discussion experience were investigated simultaneously by utilizing the structural equation modeling (SEM) and random forest classifier (RFC) approach. A total of 385 currently enrolled Filipino grade school student participants were surveyed. Results Results show that cognitive presence has the most significant impact on the perceived online discussion experience, followed by teaching presence, and social presence. This study is the first study that analyzed the online discussion experience among grade school students in online education in the Philippines considering SEM and RFC. It was seen that highly significant factors such as teaching presence, cognitive presence, social presence, triggering events, and exploration will lead to high and very high learning experience with grade school students. Conclusion The findings of this study would be significant for teachers, educational institutions, and government agencies to improve the online delivery of primary education in the country. In addition, this study presents a reliable model and results which can be extended and applied for academicians, educational institutions, and the education sector to develop ways in enhancing the online delivery of primary education worldwide.
Predicting factors influencing perceived online learning experience among primary students utilizing structural equation modeling Forest Classifier approach Facteurs prédictifs influant sur l’expérience d’apprentissage en ligne perçue chez les élèves du primaire à l’aide de l’approche de modélisation par équations Forest Classifier

Amid the COVID-19 pandemic, the temporary closure of educational institutions led to the adoption of remote or online learning delivery. Challenges, especially for grade schools were evident.

This study aimed to identify factors affecting the perceived online discussion experience of Filipino primary students through distance learning in the National Capital Region, Philippines.

Variables such as cognitive presence, teaching presence, social presence, and online discussion experience were investigated simultaneously by utilizing the structural equation modeling (SEM) and random forest classifier (RFC) approach. A total of 385 currently enrolled Filipino grade school student participants were surveyed.

Results show that cognitive presence has the most significant impact on the perceived online discussion experience, followed by teaching presence, and social presence. This study is the first study that analyzed the online discussion experience among grade school students in online education in the Philippines considering SEM and RFC. It was seen that highly significant factors such as teaching presence, cognitive presence, social presence, triggering events, and exploration will lead to high and very high learning experience with grade school students.

The findings of this study would be significant for teachers, educational institutions, and government agencies to improve the online delivery of primary education in the country. In addition, this study presents a reliable model and results which can be extended and applied for academicians, educational institutions, and the education sector to develop ways in enhancing the online delivery of primary education worldwide.

The novel coronavirus (COVID-19) has received significant attention as the government and the World Health Organization took several steps to control the spread of the virus by implementing quarantine protocols, travel restrictions, and temporary closure of educational institutions, which affected the delivery of classes among teachers and students. Due to the transmission of the virus, schools had to stop all traditional face-to-face learning activities and abruptly adapted to different kinds of online education (Ong, Prasetyo, Pinugu, et al., 2022). However, the implementation of online learning poses various risks, problems, and challenges that result in designing and implementing new ways of effective teaching and learning (Tria, 2020), especially in the Philippines. In the Philippines, the Department of Education (DepEd) adapted the online education setup through the implementation of the Basic Education Learning Continuity Plan (BE-LCP) (Department of Education, 2020). However, educational institutions in the country faced challenges in their implementation due to sudden changes in the applicable grading systems, assessments, and the appropriate feedback to students’ performance (Tria, 2020). (Cerezo et al., 2019) mentioned that a lack of face-to-face communication creates an impact on the students’ learning which leads to poor performance; however, a common problem with online classes occurs with conceptual topics, as several discussions require physical interactions for their complete understanding (Mishra et al., 2020). Meanwhile, Crook and Bligh (2016) pointed out that learning pursued in any other sense of an online environment is a systematic way of considering future learning opportunities that could become the critical learning platform for students to move forward. Maintaining motivation in an online course delivery poses another challenge that online learners face, and students who do not have independence and self-motivation have lower success rates than others (Savenye & Robinson, 2005). This in turn affects their online discussion experience. Despite the available literature regarding students’ learnability, very few studies have focused on the online discussion experiences of primary students using distance education. Peltier et al. (2007) mentioned optimizing the online discussion experience based on the value of mentoring, improvement of course structures, shifting responsibilities for teachers and students, and the importance of providing and developing course contents delivered by technology are connected. Meanwhile, Rodriguez et al. (2008) studied the improvement of online discussion experience based on the students’ perception in aiding teachers to design the ideal learning system in catering to the needs of learners. Similarly, in an e-learning context, Haverila (2011) examined the perceived learning results in terms of efficiency, quantity, and learning productivity. Finally, Gray and Diloreto (2016) studied the relationships between the structural organization of courses, learner interaction, student engagement, and teachers’ presence on student satisfaction and perceived learning. This study will give grade school teachers and students a compelling advantage in establishing online education structures that may guide the achievement of better online discussion experiences through structural equation modeling. However, recent studies for primary students during the COVID-19 pandemic were seen to be underexplored. Especially in the Philippines, studies have only dealt with e-learning in general, rather than specific education levels. Studies in the Philippines have dealt with e-learning, but focused more on intention and technology during the COVID-19 pandemic. Ong et al. (2021) focused on college students, master's degree, and PhD students, specifically those taking up industrial engineering with their preference on online learning. Their study considered the conjoint analysis approach to determine the different preference of the different education level. Their study suggested to utilize structural equation modeling (SEM) to determine the intention to utilize the online learning platform and correlate it to the results of the preference analysis. Thus, limiting their contribution to the preference of advanced education level. On the other hand, Prasetyo et al. (2021) considered the integration of Technology Acceptance Model and DeLone and McLean IS Success Model. Their study solely focused on the acceptance of senior high school students on the online learning platforms. Lastly, Ong, Prasetyo, Pinugu et al. (2022) considered the integration of self-determination theory and the Theory Of Planned Behavior in analyzing students’ future intention to enroll in chemistry-related courses despite the COVID-19 pandemic. Their study showed that affective behavior, attitude, autonomy, and competence were key factors. However, their study was limited to students in the senior high school level. Moreover, their study only considered utilizing SEM, which has several limitations due to the indirect effect and the non-linear relationship among latent variables (Fan et al., 2016). SEM is a modeling technique that involves factor and path analysis considered a mix of path analysis and factor analysis (Hair, 2010). Garrison et al., 2010a, Garrison et al., 2010b used SEM to explore the Community of Inquiry (CoI) framework to test the influence of teaching presence, social presence, and cognitive presence and their causal relationships based on the framework. In addition, Marks et al. (2005) utilized SEM and confirmatory factor analysis (CFA) to identify factors and evaluate primary relationships between the variables (e.g., learning, online instructor activities, student-to-student activities) for effective online learning. However, Duarte and Pinho (2019) suggested to integrate SEM with other tools to verify the results presented. This is in line with Woody (2011) who presented the challenges of utilizing SEM solely due to the mediating effects the latent variables have. To which, Chen et al. (2019) considered utilizing Random Forest Classifier to have higher accuracy of prediction for factors affecting human behavior-related studies. The purpose of this study is to identify factors affecting the perceived online discussion experiences of Filipino primary students through distance learning in the National Capital Region, Philippines consolidating the learning theories such as behaviorism, cognitivism, and social constructivism by utilizing the structural equation modeling (SEM) and random forest classifier (RFC) approach. This study is the first study that analyzes the online discussion experiences among grade school students in online education in the Philippines. The findings of this study would be significant for teachers, educational institutions, and government agencies to look for ways of improving the delivery of distance education in the country, as the online delivery of teaching is on its first run for most schools in the Philippines, offering primary education. By knowing the influential factors affecting primary students during online learning, the faculty members would be able to assess and develop approaches that would help enhance effective delivery. Finally, the model and constructs utilized in this study can be applied and extended among other grade school. The generalization may be applied in a specific country, which may also be utilized by other countries. In addition, the framework and findings may be applied and extended among other countries worldwide.

The Community of Inquiry (CoI) framework defines the critical essential components needed for a good online discussion experience (Fig. 1 ). The online discussion experience results from the overlapping interactions among the three identified predictors in the framework (i.e., cognitive presence, teaching presence, and social presence) (Garrison & Vaughan, 2008). This study extends the framework to identify the significant variables inherent in the experience of the online discussion of grade school students in online education. Fig. 2 shows the theoretical framework developed in this study. The learning theories of behaviorism, cognitivism, and social constructivism were integrated into the study, particularly in the CoI model framework to expound the currently available model for improving the students’ online discussion experience (Swan et al., 2009). The overall aim is to examine the factors influencing the perceived online discussion experience effectiveness among Filipino primary students in distant learning. The theoretical model adapts the three learning theories (i.e., behaviorism, cognitivism, and social constructivism) to form interactions. According to previous researches, online discussion experiences are affected by three elements such as teaching presence (behaviorism), cognitive presence (cognitivism), and social presence (social constructivism). These elements encourage higher-order thinking skills through the reflection and discourse of the students and teachers (Maddrell et al., 2020). Therefore, it was hypothesized that:H1Cognitive presence has a significant effect on online discussion experiences among grade school students Cognitive presence is the learners’ capability to create and verify meaning through reflection and discussion (Richardson et al., 2012, Redmond and Lock, 2006). Its primary focus is to help students develop the means of moving beyond the early stages of learning – to the stage where knowledge has meaning and where understanding and applying new concepts were practiced (Garrison & Vaughan, 2008). An excellent online discussion experience is the learners’ engagement in forming and using ideas in learning, like raising questions and presenting arguments on their ideas. Anderson et al. (2019) point out that a great online discussion experience is affected by the development and integration of both the cognitive and social processes to attain online discussion experiences relevant and educationally worthwhile. In addition, Murphy (2004) stated that teaching presence is critical in identifying roles and responsibilities of the instructors in the online environment such as the construction of effective learning content and how to implement it. Yalçın and Erden (2021) explained how having this increases children's problem-solving and creative-thinking skills. Thus, it was hypothesized that:H2Teaching presence has a significant effect on the online discussion experience among grade school students The social presence highlights the impact of learners’ participation and interaction towards the online learning environment (Kreijns et al., 2014). For these students to develop confidence in exchanging ideas and sharing opinions, it is evident to feel the bond with other students, especially in an online environment (Ong, Prasetyo, Pinugu, et al., 2022). The socio-emotional climate in online classes is considered media such as computers, videos, videos, and audiotapes (Richardson et al., 2012, Richardson & Swan, 2019). Ong, Prasetyo, Pinugu et al. (2022) explained how the involvement of other students in learning causes a significant influence towards their learning experience. To which, it was hypothesized that:H3Social presence has a significant effect on online discussion experience among grade

Based on Garrison et al. (2001) Practical Inquiry Model (PIM), variables such as triggering events, exploration, and resolution were considered three stages of higher-order learning, which are essential to comprehend and describe cognitive presence. PIM serves as a guide to representing the knowledge-building process (Schrire, 2004), and Sadaf and Olesova (2017) developed it further as a conceptualization tool for computer-mediated communication in online classes. Therefore, the following were hypothesized:H4Triggering events have a significant effect on cognitive presence's processing of knowledge and comprehension H5Exploration has a significant effect on cognitive presence's processing of knowledge and comprehension H6Resolution has a significant effect on cognitive presence's processing of knowledge and comprehension In addition, the studies of Kang et al. (2007) and Bangert-Drowns and Pyke (2002) indicated that understanding the content has a significant impact on cognitive presence. Moreover, it was further proven that committed learners who understand the contents are more deeply and are thoroughly involved with their learning activities intellectually (Bangert-Drowns & Pyke, 2002). In relation to this, Wang & Kang, 2006 explained how constructing knowledge promotes the processing of information, the dissemination of information, and the creation of knowledge, showing an indication that learners rely on the information available to construct meaning and ideas. Oztok (2012) stated that constructing knowledge is not a compiled outcome but rather a collaborative process. Ultanir (2012) mentioned that people's perceptions and knowledge make up what individuals may learn through awareness and cognition. Thus, it was hypothesized that:H7Level of understanding the content has a significant effect on cognitive presence to understand the topics taught H8The Level of constructing knowledge has a significant effect on the cognitive presence on learning through perception and understanding The process of establishing well-defined objectives and arranging the course content requires a high level of managing the learning resources that results in a good learning outcome Kang et al. (2007). As evident from the study of Woolfolk (2007), a classroom serves as multidimensional, time-sensitive, and filled with a variety of students and tasks. An effective and efficient strategy is required in such an environment in managing and distributing the learning resources equally to the learners. In support, Ong, Prasetyo, Pinugu et al. (2022) found that the management of laboratories and classes during online classes has been seen to be challenging, and are not easily acceptable by students. Moreover, Prasetyo et al. (2021) showed how the ease of use is one of the most significant factor to attain the satisfaction among students in using online learning platforms. Thus, it was hypothesized that:H9Level of managing the learning resources has a significant effect on cognitive presence through efficient and effective resource utilization Lin et al. (2015) investigated the impact of self-efficacy on online learning training. It has been determined that the learners’ motivation to make efforts would be significantly affected by the said claim. It was later supported by Wang & Shan (2018) and suggested that learners with distinct levels of self-efficacy show proportionality with efforts and persistence, leading to its likelihood to influence the learners’ degree of cognition. Ong, Prasetyo, Pinugu et al. (2022) showed how it is one of the contributing factors affecting intention to gain further knowledge by taking up chemistry-related courses in the future. Therefore, it was hypothesized that:H10Self-efficacy has a significant effect on cognitive presence to instill trust and belief in the learner's capabilities and knowledge Design and organization are deemed essential factors in the online learning environment. Teachers are responsible for planning and designing the courses to be pleasing for the students and enhance a participative environment. Khuana et al. (2017) emphasized that well-crafted and organized content for learning provides teachers with a birds-eye view of all the big pieces that must be included in the course for the students to understand. In addition, Ong et al. (2021) presented how the design and organization of contents and learning materials are one of the significant factors among preference of students in online learning. Thus, it was hypothesized that:H11Design and organization has a significant effect on teaching presence's ability to create a practical blueprint of knowledge content The facilitation of teachers in the learning environment is significant in how the students focus and learn more in their classes (Anderson et al., 2019). Meanwhile, Shea et al. (2006) mentioned that teachers should control the implementation of the course content and activities that will enable students to have a clearer understanding of the lessons. In relation, (Shea, 2019) noted that a well-designed learning environment is required to maximize good practice concepts, particularly in discussing the significance of learning collectively. To which, the teacher and students’ learning community possess a vital relationship through how teachers develop it (Rovai, 2002). Luppicini (2007) stated that the benefits of an online learning community development would make students’ development equally crucial to online learning success. Therefore, the following were hypothesized:H12Facilitation has a significant effect on a teaching presence's ability to engage and the students’ learning H13Learning community has a significant effect on teaching presence in forming an an environment full of learning Yoo and Alavi (2001) proposed that cohesive groups would have relations between friendly, pleasant, and personal, which is necessary to expand the social presence of communication interactions over a given mode of interaction. Bakar and Sheer (2013) mentioned that group cohesion is an element of the group members’ social integrity, which is evaluated depending on the group's attraction and satisfaction with each other. Subsequently, open communication impacts the learning process through the exchange of information, verbal and non-verbal interactions, and the sharing of thoughts which enhances the social aspect of the learners, thus making learning easier (Kreijns et al., 2014). Sedláček and Šeďova (2020) and Routman (2005) further added that as learners are actively involved in talking and interacting with their peers, they tend to participate and learn better. In essence, both Kreijns et al. (2014), Kurata et al. (2022) and Routman (2005) agreed that open communication is a key to social interaction, contributing to the overall online discussion experience. Therefore, it was hypothesized that:H14Group cohesion has a significant effect on the social presence that impacts the group's social integration and relationships with other members H15Open communication has a significant effect on social presence with how communication is used in sharing ideas and information Garrison et al. (2001) affirmed recognizing cognitive presence in attaining deep and meaningful learning, which leads to the interrelationship between cognitive presence and teaching presence, as teaching presence influences the completion of cognitive presence levels. Teaching presence is essential in learning outcomes and cognitive and social presence (Akyol & Garrison, 2008). According to (Garrison et al., 2001), teaching presence puts the elements of a culture of inquiry together to align with the intended learning outcomes, students’ needs, and skills, which suggests that teaching presence is related not only to cognitive but also to cognitive and to social presence. It shows great importance for a Community of Inquiry (CoI) as social presence emphasizes promoting engagement and the core principles of critical knowledge and higher-order thinking skills (Akyol & Garrison, 2008, Garrison et al., 2010a, Garrison et al., 2010b). To which, it was hypothesized that:H16Cognitive presence and social presence significantly affect one another as both factors show covariance H17Cognitive presence and teaching presence significantly affect one another as both factors show covariance H18Teaching presence and social presence significantly affect one another as both factors show covariance

A total of three hundred eighty-five (385) primary students from the Philippines were recruited and surveyed using purposive sampling during the COVID-19 pandemic. With the guidance of their parents and guardians, the study respondents ranged from 7 to 13 years old. The data was collected from November 2021–February 2022 through different social media platforms such as Facebook Groups and Viber Groups. The respondents considered are enrolled as grade school students across schools in the National Capital Region, Philippines. Meanwhile, the participants in the study reside in Valenzuela City (158), Marikina City (105), Quezon City (62), San Juan City (38), and Mandaluyong City (22) (Table 1 ). Hair (2010) have indicated how usual social science studies can have holistic generalizability with 250–300 respondents. To which, the collected dataset for this study could be said to represent the general public of primary students during online class setup.

A self-administered questionnaire based on the theoretical framework was devised to assess the factors influencing the perceived online discussion experience's effectiveness through distance education (Table 2 ). The adapted questionnaire comprised of four main sections: (1) cognitive presence, (2) teaching presence, (3) social presence, and (4) online discussion experience. The cognitive presence is composed of 7 latent variables triggering events, exploration, resolution, Level of understanding content, Level of constructing knowledge, Level of managing learning resources, and self-efficacy with integration as an indicator. Following which, the teaching presence consists of 3 latent variables: (1) design and organization, (2) facilitation, and (3) learning community with direct instruction as an indicator. In addition, the social presence contains two latent variables: open communication and group cohesion, while affective expression is an indicator. Lastly, the online discussion experience has no other latent variable. A total of 16 latent variables and 65 indicators were identified and supported by the references. A 5-point Likert scale was utilized for all indicator constructs using structural equation modeling. Prior to the distribution, a pilot test was done to validate the adapted questionnaire. The result garnered a Cronbach's alpha value of 0.835, which is considered as acceptable (Hair, 2010).

Structural equation modeling (SEM) is an advanced technique used as a multivariate statistical analysis that tests relationships of one or more measured variables and latent constructs (Abrahim, Mir, Suhara, Mohamed, & Sato, 2019, Kurata et al., 2022). After the collection of the data, SPSS AMOS 26 was used to run the model. Fig. 2 shows that the SEM constructs which has sixteen latent variables with one endogenous latent variable (online discussion experience) and fifteen exogenous latent variables (teaching presence, cognitive presence, social presence, and factors). The study of Lin et al. (2021) considered primary students’ motivation in learning artificial intelligence. With 14 hypotheses, it was seen how SEM was able to completely and simultaneously calculate the causal relationship among several latent variables. Al-Adwan et al. (2021) stated that theory-based hypotheses can be evaluated using SEM. Their study presented how implications from the findings based on the SEM results can be made based on the strength of relationships. Lastly, Gurer & Akkaya (2021) utilized SEM for evaluation of pedagogical beliefs on technology. Their study utilized an established framework such as the Technology Acceptance Model to evaluate conception on learning and teaching. This study considered the use of SEM to evaluate factors affecting online experience among primary students. Individual parameters were assessed using common fit indices after the model runs and following previous studies (Kozan, 2016, Kucuk & Richardson, 2019), the common fit indices are Normed Fit Index (NFI), Goodness Fit Index (GFI), Adjusted Goodness Fit Index (AGFI), Comparative Fit Index (CFI), and Root Mean Square Error of Approximation (RMSEA). A value greater than 0.80 for IFI, TLI, CFI, GFI, and AGFI shows that the model is a good fit (Gefen et al., 2000). Lastly, RMSEA with a value lower than 0.07 also offers a good model fit (Steiger, 2007).

RFC was employed to verify the significant factors affecting learning experience among students in the grade school level. Optimization was considered in this study for the best parameter. Different criterion (gini and entropy), splitter (random and best), training and testing ratios (60:40–90:10), and the tree depth (depth 4–7) were considered (Ong et al., 2022b, Ong et al., 2022c). Chen et al. (2019) explained how this machine learning algorithm is best suited as is presents a high degree of accuracy in predicting human behavior. To which, a total of 25,025 datasets were considered that underwent data cleaning. From the results, all constructs utilized in this study were significant using correlation analysis. A value greater than 0.20 coefficient and p-value less than 0.05 was seen (Yuduang et al., 2022). Thus, data aggregation and data normalization was done before running the RFC with Python 5.1. A total of 100 runs per combination was done for the whole optimization process.

Before testing for SEM, the data was run to check the normality. Utilizing the Shapiro–Wilk's Test, the resulting value was within the threshold of ±1.96 upon testing the skewness and kurtosis quotient. This indicates that the dataset utilized is normal. Fig. 3 shows the initial SEM for evaluating primary students’ perceived online discussion experience in the NCR. The figure shows that there are seven insignificant paths, triggering event → cognitive presence (β: 0.143, p = 0.001), level of constructing knowledge → cognitive presence (β: 0.206, p = 0.001), level of managing learning resources → cognitive presence (β: 0.337, p = 0.001), self-efficacy → cognitive presence (β: −0.126, p = 0.001), open communication → teaching presence (β: −0.598, p = 0.001), facilitation → teaching presence (β: 0.424, p = 0.001), and learning community → social presence (β: 0.390, p = 0.001). Thus, a modified SEM was done by removing these insignificant hypotheses. Modification of indices is also done to improve the model's fit based on previous studies (Prasetyo et al., 2020b, Prasetyo et al., 2020a, Kurata et al., 2022). Fig. 4 shows the final SEM model affecting the perceived online discussion experience effectiveness among Filipino grade school students in online education. The composite reliability table requires a value greater than or equal to 0.70 for the Cronbach's alpha and composite reliability. As for the model fit, the values of IFI, TLI, CFI, GFI, and AGFI are greater than 0.80. On the other hand, RMSEA is less than 0.07, which manifests that these results show that the conceptual model has a good fit after modifying indices. Initial data collected was tested to predict multicollinearity through the variance inflation factors (VIF). According to Montgomery & Runger (2019) and Ong et al. (2022b), multicollinearity can be an issue if the VIF has a value higher than 5. Since the highest value among the variance inflation factors is 3.553, we conclude that multicollinearity is not present in the data (Kurata & Matias, 2018). Results show that the initial model has a comparative fit index (CFI) value of 0.637 and a root mean square error of approximation (RMSEA) value of 0.083, indicating that the initial model requires modification. In constructing the final model, we removed the constructs and paths showing an initial factor loading of 0.5, which yielded CFI and RMSEA values of 0.836 and 0.042, respectively, indicating an excellent final model fit. As presented in Table 3 , the descriptive statistics of the different indicators to measure the factor loading (both initial and final), mean, standard deviation, variance, and Cronbach's alpha were obtained. As could be seen from the table, all Cronbach's alpha values were greater than the threshold, 0.70 (Hair, 2010, Ong et al., 2022). This posits that the items used to measure the different latent variables are considered to be highly acceptable and valid. Following the study of Podsakoff et al. (2003) common method bias using Harman's Single Factor Test produced a value of 17.237%, which indicates no CMB. Podsakoff et al. (2003) explained how CMB should have a threshold of 50%, wherein this study presented value within the threshold, lower than 50%. Table 4, Table 5 represent the values of the final SEM. It could be seen that all values are greater than the threshold, 0.70 for both the Cronbach's alpha and Composite Reliability (Hair, 2010). In addition, Fornell and Larcker (1981) indicated that the average variance extracted could be acceptable as long as the distribution of Composite Reliability exceeded 0.6. To further validate the findings, Table 5 represents the model fit, which are greater than the minimum high threshold set. Thus, it could be deduced that values for the latent variables and the final model are acceptable and can represent the measurement intended for the study.

Presented in Table 6 is the optimum result of RFC from Depth 5. This was utilized since this depth presented the combination with highest average accuracy and 0.00 standard deviation. Running the Analysis of Variance, no significant difference was seen among the results. To which, this was considered with the highest average accuracy for 90:10 training testing ratio considering gini and best. With 96% accuracy, the optimum decision tree from RFC is presented in Fig. 5 . From the tree, it could be seen that the parent node considered TP (X1) that will consider COG (X0). With values less than or equal to 1.881, it will consider X0, X1, and SP (X2) which will lead to very high learning experience among grade school students. If the second node was not satisfied, it will consider X2, which will lead to high learning experience among grade school students. For the right COG leaf node, it will consider values less than or equal to 0.123. If this was satisfied, it will consider X1 and EX (X4), which will lead to high learning experience. Otherwise, it will consider X2, which will lead to very high learning experience among grade school students. If the COG leaf node is not satisfied, it will consider X2 with values less than or equal to −0.163. Satisfying this will lead to high learning experience among grade school students considering TE (X3), otherwise it will consider X0, which will lead to very high learning experience among grade school students. Thus, it could be deduced that TP, COG, SP, TE, and EX are highly significant factors that affects learning experience.

Around half of the world's children are reported to be enrolled in schools that are still closed (UNICEF, 2022). Overall, a generation's education has been significantly impacted. However, one of the few positive results of this experience is the opportunity to reconsider how digital technology may be used in schools to progress the student's learning and experiences with it. With the COVID-19 pandemic, the Philippines immediately deployed virtual education over the last two years, which tells us little about how institutions should approach adopting online learning for their students into their educational system. This study aimed to provide the driving factors that significantly contribute to a great online learning experience of grade school students with the integration of the Community of Inquiry framework. The factors assessed with the utilization of Structural Equation Modelling (SEM) and Random Forest Classifier (RFC) are: cognitive presence, social presence, teaching presence, triggering event, exploration, resolution, level of understanding content, level of constructing knowledge, level of managing resources, self-efficacy, group cohesion, open communication, design and organization, facilitation, and learning community. As the first study to look at the goal of preparing Filipino grade school students for virtual classes, it unavoidably offers a better way to give a better online learning experience. From the SEM results, different factors such as cognitive presence (COG), group cohesion (GC), exploration (EX), facilitation (F), level of understanding (U), open communication (OC), design and organization (DO), and self-efficacy (SE) were significant. With the use of RFC, it was evident that teaching presence (TP), COG, social presence (SP), triggering events (TE), and EX are highly significant factors that affects learning experience. The results of RFC is in line with the explanation of Woody (2011) which presented that mediating factors can cause the insignificance of the latent variables. Moreover, Duarte and Pinho (2019) suggested to utilize other tools to highlight the results presented in SEM. Thus, factors such as TE were seen to be significant with RFC and not with SEM due to the indirect effect present (Fan et al., 2016). COG was seen to have the highest significant direct effect on Learning Experience (ODE) with SEM and was significant with RFC. The indications predated children's ability to autonomously propose questions, develop explanations, solve difficulties, and comprehend fundamental and significant teachings. When teachers and institutions put students’ intellectual abilities to the test, they are more likely to examine and think about how to respond. The relationship between the students’ online class provides lessons and goals in the construction of knowledge (Darabi et al., 2010). In accordance to this result, researchers see better online learning strategies like initially structured threads, role assignments, and debates can develop the thinking (Brooks and Jeong, 2006, De Wever et al., 2010). Our claim on how important COG on ODE is supported by research that states that students who are presented with opportunities, which involve the use of cognitive processes create and translate ideas into actual solutions with an efficient use of learning resources (Blumenfeld et al., 2005). Moreover, teachers incorporating both Cognitivism and Social Constructivist approaches may develop structured conversations and problem-based learning projects, including discovery learning through critical thinking exercises (Palloff and Pratt, 2005). Second, GC was seen to have a significant effect on SP. The indicators showed how important children maintain confidence in their peers despite opposing views, accepts other perspectives, and develop a sense of collaboration. This emphasizes the necessity of engaging with and developing good relationships with their peers, since this will lead to increased interaction. Students gain trust in others as a result of these encounters, which aids their learning. Yoon and Leem (2021) back up the claim that SP will have a favorable impact by reinforcing GC. Previous studies have shown that trust and unity improve group performance in online learning, while more research on how to explicitly develop trust and unity is needed (Paul et al., 2016, Furumo and Pearson, 2006). With a stronger social connection, students are more satisfied in working with one another, leading to more collaborations and interactions to better understand and maximize their online learning experience (Bulu, 2012). Third, F is another factor that significantly affects TP. The indicators showed that children find it beneficial to have an instructor who can identify important course topics on which they agree and disagree, clarify, and guide them in understanding their lessons, engage their students in discussions, give them tasks to apply what they have learned, encourage them to explore important concepts, and reinforce a sense of community among them. This means that when an instructor creates events, forums, and activities that keep students engaged and ready to learn, they are more inclined to understand their lessons (Prasetyo et al., 2021). This also implies that effective use of learning resources has a favorable impact on instructors’ instructional presence (Ong et al., 2021). Students expect their teachers to actively organize nonbiased discussions, keep everyone engaged and on track, and encourage everyone to participate in meaningful ways (Hosler & Arend, 2012). Fourth, EX is seen to have a significant effect on cognitive presence (CP) in both SEM and RFC. The indications predated children's utilization of information to explore problems, find solutions, and find discussions that would give a different perspective to it. This means that students’ efficient utilization of information in determining problems and solving it, increases their cognitive abilities and pushes them to come up with different ways to understand it. Exploring for more information include researching further courses, attending forums, and engaging in different discussions challenges the students to think outside of the box which results to new learnings (Yildiz and Guler Yildiz, 2021). Students who are supported and stimulated to explore in pursuit to further their education are more inclined to use cognition critically and to look at things in a more multidisciplinary manner (Sadaf & Olesova, 2017). Exploration is essential in education, especially for young children because it leads to awareness of different aspects of the courses (Schrire, 2004). Fifth, U is seen to have a significant effect on CP. The indicators preceded the children's ability to comprehend through the contents of the courses they desired, the contents of the courses they expected, the ability to demonstrate their comprehension through diagrams and charts, organize their learnings, and describe what they learned in class. This means that a student's level of comprehension of their classroom lessons reflects how well they employ their cognitive capacities. Students are more likely to broaden their knowledge and improve their thinking skills when they grasp what they have learned. Goldman (2012) mentioned that students must be able to understand and be advanced in doing studies. They must be capable of making smart decision that is based on what they analyze and evaluate. Aside from that, they should comprehend how lessons function, their purposes, and their analytical framework Goldman (2012). Sixth, OC significantly affects SP. Children's capacity to talk comfortably with their classmates online, participate in course discussions, and interact with other course participants are all preceded by the indicators. This means that students who are at ease discussing and connecting with their peers are more likely to do so online. This also reflects how well students interact with one another while they are learning. Open communication impacts the learning process through the exchange of information, verbal and non-verbal interactions, and the sharing of thoughts which enhances the social aspect of the learners, thus making learning easier (Kreijns et al., 2014). Sedláček and Šeďova (2020) and Routman (2005) further added that as learners are actively involved in talking and interacting with their peers, they tend to participate and learn better. In essence, both Kreijns et al. (2014) and Routman (2005) agreed that open communication is a key to social interaction, which contributes to the overall learning experience. Seventh, DO has a significant effect on TP. The indicators showed the teacher's ability to discuss relevant themes, develop class learning goals, present a participatory class activity, and communicate crucial dates for class activities. This means that in the online learning environment, design, and organization are crucial factors since educators are responsible for planning and structuring course content that is appealing to students and encourages participation. Moreover, it was mentioned that an organized and well-structured design of curriculum helps promote students’ learning (Reed, 2015), which is observed on how teachers cope and construct ways for students to learn in online classes. In addition, it is also evident that TP has a significant effect on CP for both SEM and RFC. The indications demonstrated the instructor's capacity to address relevant issues with students, assist students in understanding their strengths and shortcomings in relation to the course's objectives, and provide feedback on student learning. This means that the effectiveness with which the instructor teaches the courses determines the student's ability to think and learn. It also emphasizes the importance of the instructor's role in assisting students in improving their cognitive capacity. In addition, Murphy (2004) stated that teaching presence is critical in the identification of roles and responsibilities of the instructors in the online environment such as the construction of effective learning content and how it should be implemented. Moreover, SE has a significant effect on CP. The indicators presented the student's capacity to do well in class, absorb course materials despite technical difficulties, learn independently, perform well in self-paced online courses, and continue learning despite distractions. Students who perceive they can learn and think for themselves are more likely to acquire a high level of thinking. Learning with confidence demonstrates students’ eagerness to learn, which encourages them to think more critically (Ong, Prasetyo, Pinugu, et al. 2022). This is also supported by Wang and Shan (2018) who suggested that learners with distinct levels of SE show proportionality with efforts and persistence, leading to its likelihood to influence the learners’ degree of cognition. Lastly, SP has a significant effect on Cognitive Presence CP for both SEM and RFC. The indicators showed student's capacity to have a sense of belonging in the class, convey feelings toward their classmates, and work together to learn effectively. This suggests that students’ thinking improves as a result of socializing and connecting with other course participants. “Two heads are better than one,” as the old adage goes, perfectly describes how students who connect with their classmates think critically and are inspired to engage in intellectual activity. Previous study by Kehrwald (2008) supports that reinforcing the necessary meaning of SP in active and engaging learning activities in an online learning environment is important as it brings a common understanding to develop the learners’ experiences. Overall, it can be determined that institutions and teachers must evaluate a variety of factors, particularly the ones listed above in order to construct a suitable approach for improving the online learning experience of Philippine grade school students. These important components are required for the online education setup to be successful at this level.

By incorporating the Community of Inquiry framework into the online education setup, the aim was to uncover components that positively reinforce the online learning experience of grade school students. The findings pave the way for future studies to connect other methodologies and frameworks, such as the integrated framework utilized in this study in order to improve online learning at various educational levels. Every level necessitates a unique technique to optimizing their educational system in an online setting. Different aspects that can affect their online learning experience, such as nationality, age, and accessibility, can also be included to our theory. The applied theory considered in the framework presented an acceptable fit, which indicates that it could holistically measure learning experience of students during online learning. The framework therefore could be applied and extended among related studies worldwide.

The findings of this study will aid various institutions, educators, parents, and students in determining the best way for accepting and adapting online learning in the new normal. The online learning experiences of Philippine grade school students would improve as a result of this research, indicating that pupils are still learning in an online setting. It will assist institutions, educators, and parents in determining the best approach and methods for properly implementing course materials to their pupils. It would be best to consider Teaching Presence, Cognitive Presence, Social Presence, Triggering Events, and Exploration among learning experience with grade school students. These highly significant factors would greatly affect learning experience of grade school students, which may be applicable also in different countries.

Despite the evident and significant findings provided in this study, several limitations were still considered. First, due to the COVID-19 pandemic, this study considered an online survey. It is recommended that interviews may be conducted to better analyze the learning experience of grade school students with parents and teachers. This will obtain more information and even additional factors that were not considered in this study. Second, this study utilized SEM and RFC only. Other machine learning algorithm such as neural networks could be employed to predict factors affecting learning experience among grade school students. Lastly, no separation of public and public school students were considered in this study. In the Philippines, there is a difference in delivery among different universities. To which, it is suggested to consider clustering by particle swarm optimization and fuzzy c-means to elaborate on the different factors affecting online learning experience.

The COVID-19 pandemic led every country to implement quarantine protocols, and travel restrictions, including the closure of educational institutions, which ceased all face-to-face learning activities and abruptly adapted to various forms of remote or online learning delivery. At present, academicians, educational institutions, and the education sector of the government are looking for ways of improving the delivery of distance education, as the online delivery of teaching is on its first run for most schools in the Philippines offering primary education. The purpose of this study is to identify factors affecting the perceived learning experience effectiveness of Filipino grade school students through distance learning in Metro Manila, Philippines. The learning theories such as Behaviorism, Cognitivism, and Social Constructivism were integrated in the model of community of inquiry and proved to be beneficial in determining factors affecting online learning experiences of the Filipino grade school students. Factors were analyzed simultaneously through the structural equation modeling (SEM) and random forest classifier (RFC) approach and showed that cognitive presence, social presence, teaching presence, group cohesion, facilitation, exploration, level of understanding content, open communication, design and organization, and self-efficacy have positive significant effects on the perceived learning experience effectiveness of Filipino grade school students. Moreover, it was seen that highly significant factors such as teaching presence, cognitive presence, social presence, triggering events, and exploration will lead to high and very high learning experience with grade school students. This study presents a reliable model and results for academicians, educational institutions, and the education sector of the government to develop ways in enhancing the online delivery of primary education in the country. In addition, this study can be an opportunity for further studies to be done about perceived effectiveness of online education among higher education students who implement the same teaching and learning delivery worldwide.

The authors declare that they have no competing interest.