Pa ge 1 Pa ge 17 1 American Journal of Arts and Human Science (AJAHS) The Mediating Role of Transactional Distance on the Relationship between Course Satisfaction and Student Persistence Earl John D. Ares1*, Angel Hane A. Cavales1, Narwesa I. Hasan1, Mylyn L. Doren1 Volume 3 Issue 3, Year 2024 ISSN: 2832-451X (Online) DOI: https://doi.org/10.54536/ajahs.v3i3.3123 https://journals.e-palli.com/home/index.php/ajahs Article Information ABSTRACT Received: June 17, 2024 Accepted: July 21, 2024 Published: July 25, 2024 In the context of education, which is asynchronous and synchronous online learning, students’ persistence is of concern in most educational institutions. Several studies reveal many factors that influence students’ persistence. One of them is course satisfaction but hardly any research about the effect of psychological space of learners on students’ persistence. Thus, this study aimed to determine the mediating effect of transactional distance on the relationship between course satisfaction and student persistence. The study employed a descriptive-causal method of research and used an adaptive questionnaire that was contextualized by the researchers, and was participated by 239 senior high school students (grade 11 and grade 12) at the University of Mindanao Digos College; utilized stratified random sampling. The results of the study showed that the students are satisfied with their online course experience and thus students are highly likely to persist. Results also reveal that the transactional distance is low. Moreover, it also showed course satisfaction and student persistence are significantly related. However, after the insertion of transactional distance, the direct path unveiled insignificance while the indirect path revealed significant effect. Hence, the mediation analysis disclosed that transactional distance fully mediates the relationship between course satisfaction and student persistence. The paper provides evidence that in asynchronous and synchronous online learning, satisfaction should not solely be the focus in attaining students’ “intent-to-persist” but must also consider the perceived transactional distance of learners. Keywords Course Satisfaction, Student Persistence, Transactional Distance, Mediating Effect, Mediation Analysis 1 Department of Teacher Education, University of Mindanao, Digos, Philippines * Corresponding author’s email: aresearl15@gmail.com INTRODUCTION Inevitably, when the topic is all about transactional distance, the gist is distance education, which is the state of our education today - asynchronous and synchronous online distance learning, where concerns are very apparent. Several studies have identified variables affecting dropout rates in online and distance learning (Kauffman, 2015; Croxton, 2014; Adamopoulos, 2013; Park & Choi, 2009; Willging & Johnson, 2009; Selim, 2007). Nevertheless, it has been shown time and time again that one very intuitive and straightforward variable, satisfaction, is positively correlated with persistence in online distance learning (Lee & Choi, 2013; Joo et al., 2013; Joo et al., 2011; Schreiner, 2009; Park & Choi, 2009; Levy, 2007). According to some experts, the attrition rate for online learning could be as high as 75% (Croxton, 2014). This was particularly prominent in Massive Open Online Courses (MOOCs) where completion of the course could be as poor as 6.5 percent (Jordan, 2014). Carr (2000) argues that the persistence rate is often 10-20% lower in distance education programs than in traditional settings. Moreover, Rutter (2016) states that students’ persistence with online courses is lesser than the normal face-to-face classes. From the report of Gabriel Lalu in Inquirer.net as of June 18, 2020, according to Samahan ng Progresibong Kabataan (Spark), after the Department of Education (DepEd) opened its online enrollment procedures in early June, only 10.5 million of the 27.2 million students in the primary and secondary education systems have enrolled. Conversely, the study of Markle (2015) stated that course satisfaction is not only the predictor of students’ persistence but must also consider the psychological distance. Transactional distance values are unique student satisfaction indicators, which reflect learning and persistence (Paul et al., 2015). Transactional distance influences students’ satisfaction and persistence, and it is viewed as a significant matter of conversation (Steinman, 2007). Transactional distance is the perceived psychological and cognitive distance between students and educators; the higher the transactional distance the higher the autonomy of learners (Moore, 1993). Now, according to Oregon, McCoy, and Carmon-Johnson (2018), this learners’ autonomy or lack of interactivity has been one of the reasons for persistence degradation. Since a correlation has been identified between highly satisfied students and persistence in a program (Horzum, 2015), examining transactional distance and improvements that enhance student satisfaction in an online classroom will bring apparent advantages for students’ persistence. Hence, from strong empirical grounds, transactional distance might contribute to the relationship between course satisfaction and student persistence. In this new normal, asynchronous and synchronous online distance learning dominate, and we researchers have been inspired to discover the mediating role of transactional distance Pa ge 17 2 https://journals.e-palli.com/home/index.php/ajahs Am. J. Arts Hum. Sci. 3(3) 171-179, 2024 on the relationship between course satisfaction and student persistence that has not yet been discovered by recent studies. We aimed to discover how mediating variable specifies the association that occurs between independent and dependent variables, that will eventually contribute to our education, on how psychological distance affects learners consequently formulating certain actions addressing attrition. This study is deeply anchored with Michael Moore’s (1972) Transactional Distance Theory. The transaction occurs in distance education in a setting consisting of students and teachers separated by a geographical distance from each other resulting in an effect on their satisfaction and persistence in education. A psychological and communication space exists because of this separation (Moore, 1972). Moore further pointed out that possible misunderstandings caused by the transactional distance between the learning environment and the learner may occur even in-room setting, which also influences students’ satisfaction and intent to persist (Moore, 1993). Psychological and contact space is referred to as transactional distance by Moore. Moore coined the term and developed the basic principle of transactional distance (Moore, 1972). The Moore model involves an interrelated set of variables: dialogue, structure, and autonomy of learners (Moore, 1972). The use of ‘dialogue’ connotes experiences with constructive characteristics. The dialog can be called purposeful, positive interactions that are respected by all parties in a relationship. Moore states in particular that “the nature of the medium of communication directly affects the extent and quality of dialogue between teachers and learners” (Hills & Keegan, 1994). A Learning Management System (LMS) framework also determines the means of communication leveraged for an online course. In an online course, the structure is a qualitative variable, as is dialogue, which is primarily dependent on the communication media being used throughout the course. The greater the structure and the lower the dialogue, the greater the distance between teachers and learners from the transaction (Moore, 1972). The last variable considered by Moore was the learner’s autonomy. The theory of Moore effectively combined two different pedagogical traditions: the humanistic tradition and the tradition of behavior (Moore, 1972). While humanism gave value to interpersonal, unstructured dialogue from the field of counseling, a systematic design of instruction gave more value to the behaviorist tradition (Moore, 1972). Such systematic teaching was underpinned by behavioral goals controlled almost entirely by the teacher. He questioned the de facto behaviorist model of education in the early 1970s by incorporating learner autonomy as a central variable of his model (Hills & Keegan, 1994). At a time before the emergence of the Internet (or even widespread use of personal computers), Moore’s theory was developed and as such, required improvements that accounted for the shift in learning and communication provided new technologies. This study sought to determine the mediating role of transactional distance on the relationship between course satisfaction and student persistence. Specifically, this research aimed to examine the following: (1) Determine the level of course satisfaction with the learning experiences of senior high school students; (2) Determine the level of student persistence in terms of academic Integration, social Integration, supportive services Satisfaction, degree commitment, institutional commitment; and academic conscientiousness; (3) Determine the level of perceived Transactional Distance in terms of transactional distance between students and content, transactional distance between students, transactional distance between students and teacher, and transactional distance between students and technology; (4) Determine if there is any significant relationship between course satisfaction and student persistence; and determine if transactional distance significantly mediate the relationship between course satisfaction and student persistence. METHODOLOGY The researchers employed quantitative research: descriptive causal design. According to Jefferys (2021), descriptive and causal research addresses various questions. Descriptive studies are mainly designed to clarify what is happening or what is existing. On the other hand, causal research is used to determine if the importance of other variables is caused or affected by one or more variables. Descriptive research aims to describe a population, situation, or phenomenon in an accurate and systematic way (Languita et al., 2023). And was utilized to describe the respondents’ level of perceived course satisfaction, student persistence, and transactional distance. On the other hand, causal research is concerned with measuring and testing the indirect effect, as a function of the mediator, on the dependent variable; a mediator is a variable that influences the relationship between an outcome and a predictor. In this study, causal design is utilized by the researchers to determine how transactional distance influenced the relationship between course satisfaction and student persistence through the lens of senior high school students. The participants of this study are Senior High School (SHS) students at UM Digos College. These are students, Grade 11 and Grade 12 students who were officially enrolled in the school year 2020-2021. To quantify the level of course satisfaction, student persistence, and transactional distance, the researchers adapted questionnaires from different authors where contents were validated by experts. It contains three parts: the first part determines the course satisfaction, the second part is student persistence, and the last part is for transactional distance. For the independent variable, the statements of the questionnaire were from the “Development of Online Course Satisfaction Scale” of Bayrak, Fatma, Tibi, Moanes, Altun, and Arif (2020). Pa ge 17 3 https://journals.e-palli.com/home/index.php/ajahs Am. J. Arts Hum. Sci. 3(3) 171-179, 2024 Moreover, the instruments for measuring students’ Course Satisfaction is a Five-point Likert scale format in which respondents will select the most appropriate answer from response options ranging from (5) Strongly agree, (4) Agree, (3) Neutral, (2) Disagree, and (1) Strongly disagree. For the dependent variable, some statements of the questionnaire from “The College Persistence Questionnaire: Development and Validation of an Instrument That Predicts Student Attrition” adapted from Davidson, Beck, and Milligan, (2009) were modified (from “college” to “senior high school”; the statements were changed to declarative form). Furthermore, the instrument for measuring Student Persistence is a Five- point Likert scale in a “favorability scale” format in which respondents will select the most appropriate answer from response options ranging from (5) Very favorable, (4) Somewhat favorable, (3) Neutral, (2) Somewhat unfavorable, and (1) Very unfavorable. Lastly, for the mediating variable, the questionnaire from “Technology Matters - The Impact of Transactional Distance on Satisfaction in Online Learning” adapted from Weidlich and Bastiaens (2018) was also modified (from “Moodle” changed to “Quipper”; items in “satisfaction with the learning experience” were removed). Additionally, the instrument of Transactional Distance is a 5-point Likert scale format which respondents will select the most appropriate answer from response options ranging from (5) Strongly disagree, (4) Disagree, (3) Neutral, (2) Agree, and (1) Strongly agree. To obtain a result that is valid and reliable, the following statistical tools were being used. All interpretation was based on the 0.05 level of significance. Mean. This is utilized to get the average perception of respondents for each variable of the study (Alegado et al. 2024; Zalsos & Corpuz, 2024). In addition, this is utilized to describe the level of the respondents’ course satisfaction, the level of student persistence in terms of academic integration, social integration, supportive services satisfaction, degree commitment, institutional commitment, and academic conscientiousness, and the level of perceived transactional distance in terms of transactional distance between students and content, the transactional distance between students, the transactional distance between students and teacher, and the transactional distance between students and technology. Pearson r. This determines the significant relationship between the variables (Diquito et al., 2024). and Structural Equations Modeling (SEM). This is utilized to determine the mediating effect of transactional distance on the relationship between course satisfaction and student persistence. RESULTS AND DISCUSSION Level of Course Satisfaction among SHS Students Table 1 presents the overall level of Course satisfaction of senior high school students. As disclosed in the table, respondents obtained a mean rating of high course satisfaction (͞x= 3.80, SD= 0.54). This means that the students are satisfied. Bage (2018) and Diez . (2021) stated that students are highly satisfied when the online courses have clear structures, interactive instructors, healthy and supportive learning environmentt al. (2021) stated that students are highly satisfied when online courses have clear structures, interactive instructors, and healthy and supportive learning environments. This is congruent to the study of Cole, Shelley, & Swartz (2014), who surveyed a total of 553 cases and found that the significant reason why students are highly satisfied with online learning is convenience, and the main reason for dissatisfaction is the lack of learner-teacher and learner-learner interactions. Apparently, even in the state of asynchronous and synchronous online distance learning, students are still satisfied because of the timely update of their instructors, the accommodating ambiance provided by the educational institution, fast-paced interactivity with peers, and the simplicity and flexibility of the learning interface. Also, because of the convenience experienced by students where they can participate in the class anywhere they want and answer the tasks anytime. The three domains of transactional distance (student-content, student-student, and student-teacher) were found to have a significant relationship with students’ perceived satisfaction that the three predictors accounted for 31.6 percent of the variance in student satisfaction (Mbwesa, 2014). This implies that students who experienced portability and great interaction with his/ her peers and teacher are highly satisfied with their online learning environment. Furthermore, Bolliger and Halupa (2012) cited by Yalcin (2017) stated that course satisfaction and technological anxiety have a negative relationship; their anxiety in using technology is because of incompetence in using the tool. Students who have low levels of technological anxiety have significantly higher satisfaction than those students with high technological anxiety (Yalcin, 2017). This implies that if students are more likely used to utilizing the technology there are probably satisfied in the online learning context. Table 1: Level of Course Satisfaction with the Learning Experiences of SHS Students in UMDC (n=239) Course Satisfaction Mean SD Overall Mean 3.8 0.54 Level of Student Persistence among SHS Students Table 2 shows the level of Student Persistence among senior high school students. As disclosed in the table, respondents obtained a mean rating of high student persistence (͞x= 3.66, SD= 0.44) which was verbally described as high. This means that the students are likely to persist even in a state of asynchronous and synchronous online distance learning. The result of this study is very contrary to the study of Sorensen and Donovan (2017) which they stated that, unlike traditional education, online courses in an educational institution resulted in lower persistence rates. Pa ge 17 4 https://journals.e-palli.com/home/index.php/ajahs Am. J. Arts Hum. Sci. 3(3) 171-179, 2024 Academic Integration An indicator of student persistence got the mean rating of 3.58 (SD=0.44) which was verbally described as high. This implies that the senior high school students in UMDC will likely persist because of their academic connection. As stated by Woosley and Shepler (2011) cited by Toliao (2017) that according to many studies academic integration is as important as social integration, and it is key for the academic performance of underprepared students, boosting their chances of persistence and degree completion. Social Integration An indicator of student persistence got the mean rating of 3.71 (SD=0.62) which was verbally described as high. This implies that the senior high school students in UMDC will likely persist because of their commendable social camaraderie in the online learning environment. According to Inkelas, Daver, Vogt, and Leonard (2007) cited by Glenn (2017) that peer participation is another form of social integration that benefits first-generation college students; students are encouraged to join student groups, which also gives them a greater sense of campus belonging and decreases feelings of isolation, thus instilling a sense of connection to the school that promotes retention and persistence. are having a hard time increasing students’ satisfaction so that students’ persistence as well is apparent, this can only be attained if there exists quality student support. Degree Commitment An indicator of student persistence got the mean rating of 4.17 (SD=0.73) which was verbally described as high. This implies that the senior high school students in UMDC will likely persist to finish their strand. Since there is a connection between high levels of satisfaction and persistence in a degree program (Weidlich and Bastiaens, 2018), exploring changes to the online classroom that increase student satisfaction will benefit students, teachers, and the institutions they attend. Students must have the mindset of completing their degree so that persistence will follow (Holzweiss, Joyner, Fuller, Henderson, & Young (2014) cited by Sweetland, 2015). Institutional Commitment An indicator of student persistence got the mean rating of 3.81 (SD=0.68) which was verbally described as high. This implies that the senior high school students in UMDC are likely to persist in their commitment to the institution. According to Lucey (2018), a higher level of commitment in institutions than in typical classrooms in online learning. It implies that online learning is critical to their institutions’ success, while also expressing concern that online learners are less likely to succeed and persist in an academic institution (Dexter, 2015). Academic Conscientiousness An indicator of student persistence got the mean rating of 2.84 (SD=0.97) which was verbally described as moderate. This implies that the senior high school students in UMDC are moderately eager to thoroughly do well in academics. Brown (2015) claims that there is a connection between academic conscientiousness and college persistence. In contrast, the research Gregg (2021) found that conscientiousness has no statistically significant relationship with organizational engagement or help and satisfaction. Level of Transactional Distance among SHS Students Table 3 shows the level of the perceived Transactional Distance among senior high school students in UMDC. As disclosed in the table, respondents obtained a mean rating of low transactional distance (͞x= 3.78, SD= 0.48). This means that the students perceived low transactional distance. Table 2: Level of Student Persistence of SHS of Students in UMDC (n=239) Indicators Mean SD Academic Integration 3.58 0.44 Social Integration 3.71 0.62 Supportive Services Satisfaction 3.84 0.63 Degree Commitment 4.17 0.73 Institutional Commitment 3.81 0.68 Academic Conscientiousness 2.84 0.97 Overall 3.66 O.44 Supportive Services Satisfaction An indicator of student persistence got the mean rating of 3.84 (SD=0.63) which was verbally described as high. This implies that the senior high school students in UMDC will likely persist because they perceived commendable satisfaction in the support of the school in services. Such supportive services will affect student retention and the overall evaluation of an academic institution (Jones (2011) cited by Emmanuel-Frenel, 2017). Additionally, Culp (2014) stated that universities Table 3: Level of Perceived Transactional Distance of SHS Students in UMDC (n=239) TDSC TDSS TDST TDSTECH Overall Mean Mean 3.91 3.81 3.64 3.75 3.78 SD 0.59 0.67 0.57 0.53 0.48 Pa ge 17 5 https://journals.e-palli.com/home/index.php/ajahs Am. J. Arts Hum. Sci. 3(3) 171-179, 2024 Transactional Distance between Students and Content (TDSC) An indicator of transactional distance got the mean rating of 3.91 (SD=0.59) which was verbally described as low. This implies that senior high school students in UMDC are more engaged with the online learning content. According to Chou, Peng, and Chang (2010) cited by Alotibi (2018) found out that in Learning Management Systems, learner-content interaction has the lowest percentage in an online learning interactive function. Moreover, Huang, Chandra, DePaolo, Cribbs, and Simmons (2015) stated that learner and content interaction is closely related to learner and interface interaction that the flexibility of LMS’s contributes to the connection of the learners and the contents. Transactional Distance between Students (TDSS) An indicator of transactional distance got the mean rating of 3.81 (SD=0.67) which was verbally described as low. This implies that the senior high school students in UMDC have great connections and interactions with each other. As the study of Ali (2018) stated that in an online learning environment, there are numerous advantages to students’ quality of interactions with other students, for example, the student acquires knowledge through collaborative inquiry with other students. Students’ motivation and participation, perceived learning, course and instructor satisfaction, and retention in online courses have all been shown to be impacted by the social presence of students with each other (Richardson, Besser, Koehler, Lim, & Strait, 2016). Transactional Distance between Students and Teacher An indicator of transactional distance got the mean rating of 3.64 (SD=0.57) which was verbally described as low. This implies that the senior high school students in UMDC perceived low psychological space between them and their teachers in the online learning environment. According to Hollis (2016), student-faculty interactions are widely acknowledged to have a positive impact on students’ cognitive advancement, satisfaction, and development of educational institutions. In the result findings of Ali (2018) and Acuña (2021) stated that for students in online courses, there is a moderate to a strong positive relationship between student-faculty interaction and student satisfaction. Increases in student-faculty interaction were moderate to strongly correlated with increases in student satisfaction for students in online courses, according to his findings. This is contrary to the findings of Peterson (2019) which resulted in TDST (transactional distance between students and teacher) as insignificant with a p-value of 0.521. Transactional Distance between Students and Technology An indicator of transactional distance got the mean rating of 3.75 (SD=0.53) which was verbally described as low. This implies the senior high school students in UMDC are very connected and engaged to the LMS’s specifically to the ‘Quipper’, they perceived low transactional distance in utilizing such interface. As stated by Horzum (2015) that testing the effects of technology (interface) will significantly affect transactional distance and online course satisfaction of students. Additionally, literacy of the interface used in online learning will help in minimizing the high attrition rate and level of isolation of learners (Burns & Gillepie, 2018; Keefer, 2015). Significant Relationship between Course Satisfaction and Student Persistence Table 4 shows the correlation analysis between Course Satisfaction and Student Persistence of senior high school in UMDC. It was revealed that there is statistical evidence showing a significant relationship between two variables with a p-value of 0.001 and a beta coefficient of 0.05. Table 4: Direct effects of Course Satisfaction to Student Persistence Unstandardized Standard Error Standardized t p CS to SP 0.05 0.05 0.06 1.07 < .001 CS for course satisfaction, SP for Students Persistence This implies that a unit increase in Course Satisfaction there is a 0.05 increase in Student Persistence. The result is similar to the study of Lim and Kim (2013) cited by Weidlich and Bastiaens (2018). Moreover, Mbwesa (2014) studied the relationship between transactional distance and students’ satisfaction and stated student-content, student-student, student-teacher transactional distance were investigated as predictors of perceived learner satisfaction. However, Richardson, Besser, Koehler, Lim, & Strait (2016) argued that the amount of social presence mediates student satisfaction and persistence. Social presence, defined as the ability to perceive others in an online environment and the degree of emotional and social engagement, has been shown to influence course and instructor satisfaction, and online course persistence (Gutirrez-Santiuste, Rodriguez- Sabiote, & Gallego-Arrufat, 2015). Additionally, Markle (2015) also stated that course satisfaction is not only the predictor of students’ persistence in an online learning environment. This implies that even some authors suggest a significant relationship, but many authors as well stated inconsistencies and must take into consideration of the social and emotional presence in learning context (Mehri & Izadpanah, 2017; Poquet, Kovanović, de Vries, Hennis, Joksimović, Gašević, & Dawson, 2018) which is related to the theory of transactional presence (Shin, 2003). Pa ge 17 6 https://journals.e-palli.com/home/index.php/ajahs Am. J. Arts Hum. Sci. 3(3) 171-179, 2024 Mediation Analysis Including Change in SHS Students’ Perceived Student Persistence from Course Satisfaction, and Taking Their Perceived Transactional Distance as a Mediator Variable The table shows the path coefficient among course satisfaction, student persistence, and transactional distance. The path coefficient of the total effect is 0.42. The direct effect is 0.05 which is the impact of course satisfaction to student persistence. This is similar to the study of Dhungana (2015) that satisfaction with e-learning is a predictive indicator for learners intending to continue learning online (persistence). Further, the indirect effect is 0.37 which is the impact of course satisfaction to student persistence when bridged or mediated by transactional distance. Increased student satisfaction is linked to student engagement in online courses (Martin & Bolliger, 2018), and students who are engaged in the learning environment are more persistent (Ali & Smith, 2015). Table 5: Results from the mediation analysis including change in perceived students’ persistence from course satisfaction, and transactional distance as a mediator variable 95% Confidence Interval Estimate Std. Error z-value p Lower Upper Direct Effects 0.05 0.05 1.08 0.28 -0.04 0.14 Indirect Effects 0.37 0.04 8.98 < .001 0.29 0.46 Total Effects 0.42 0.05 9.28 < .001 0.34 0.51 It was disclosed the test of transactional distance as a mediator to the relationship between course satisfaction and student persistence. Previous table showed the significant relationship between course satisfaction and student persistence (p=0.001), however, after the insertion of the transactional distance it revealed: the direct path showed a positive effect result but not significant (p=0.28); the indirect path of the mediation analysis showed significance with a p-value of 0.001. Hence, transactional distance fully mediates the relationship between course satisfaction and student persistence. This implies that student persistence could only be influenced by course satisfaction if there exist transactional distance in between, that in an online educational realm, course satisfaction should not solely be the consideration in attaining the “intent-to-persist” of students. But the emphasis on transactional distance plays a critical role in linking the two variables. This conforms to the argument of Peterson (2019) that the focus on transactional distance will improve the level of students’ satisfaction and persistence. Which is according to Moore (1993), transactional distance influences the process and results of teaching namely satisfaction and persistence (Weidlich and Bastiaens, 2018). Conversely, since social presence is related to transactional distance (Horzum, 2015), the findings of Pattison (2017) revealed no significant bivariate relationship between social presence and students’ satisfaction and persistence. Figure 1: Mediating effect model of Transactional Distance between the Relationship of Course Satisfaction and Student CONCLUSION Based on the aforementioned findings, the researchers concluded that the senior high school students at UM Digos College are satisfied, likely to persist, and perceive low transactional distance. Furthermore, the result of the study of The Mediating Role of Transactional Distance on the Relationship between Course Satisfaction and Student Persistence indicates the following: Course satisfaction has Pa ge 17 7 https://journals.e-palli.com/home/index.php/ajahs Am. J. Arts Hum. Sci. 3(3) 171-179, 2024 a significant relationship with student persistence. However, after the insertion of the mediator (transactional distance), the direct effect is not significant. Meanwhile, the indirect path showed significant results; hence, full mediation of transactional distance on the relationship between course satisfaction and student persistence is evident. REFERENCES Adamopoulos, P. (2013). What makes a great mooc? An interdisciplinary analysis of student retention in online courses. 34th International Conference on Information Systems: ICIS 2013. Retrieved from http://pages.stern. nyu.edu/~padamopo/What%20makes%20a%20 great%20MOOC.pdf Acuña, A. R., Aman, F. A. R., Apas, P. D. D., & Diquito, T. J. A. (2021). Exploring Students’ Attitudes Towards Online-based Learning System in the n]New normal: an Exploratory Factor Analysis. European Journal of Education Studies, 8(11). https://doi.org/10.46827/ ejes.v8i11.3964 Alegado, C., Guinto, R. D., Beldeniza, F. R., & Culajara, C. L. (2024). Sleep Hygiene Practices and Mood States: A Quantitative Analysis. American Journal of Arts and Human Science, 3(2), 72–81. https://doi.org/10.54536/ ajahs.v3i2.2786 Ali, A., & Smith, D. (2015). Comparing social isolation effects on students attrition in online versus face-to-face courses in computer literacy. Issues in Informing Science and Information Technology, 12, 11-20. Retrieved from http:// iisit.org/Vol12/IISITv12p011-020Ali1784.pdf Ali, M. N. (2018). A correlational study of types of interactions and student satisfaction in online community college mathematics Englor information technology courses. Retrieved from: https://eric. ed.gov/?id=ED599450 Bage, L. (2018). Satisfaction with online learning options in the insurance industry: Does mindfulness play a role (Order No. 10823433). Available from ProQuest Central. (2099202217). Retrieved from https://www. proquest.com/dissertations-theses/satisfaction-with- online-learning-options/docview/2099202217/se- 2?accountid=31259 Bayrak, Fatma & Tibi, Moanes & Altun, Arif. (2020). Development Of Online Course Satisfaction Scale. Turkish Online Journal of Distance Education. 21. 110- 123. https://doi.org/10.17718/tojde.803378. Bolliger, D. U., & Halupa, C. (2012). Student perceptions of satisfaction and anxiety in an online doctoral program. Distance Education, 33(1), 81–98. http:// dx.doi.org/10.1080/01587919.2012.667961 Brown, Lisa (2015). Self-efficacy and perceptions of first- year American Indian college students: A quantitative study. University of Phoenix, ProQuest Dissertations Publishing, 2015. 3727499. Burns, E. M., & Gillespie, C. W. (2018). A phenomenological study of attrition from a doctoral cohort program: Changes in feelings of autonomy and relatedness in the dissertation stage. International Journal of Doctoral Studies, 13, 517–537. https://doi. org/10.28945/4158 Carr, S. (2000). As distance education comes of age, the challenge of keeping its students. The Chronicle of Higher Education, 23, A1. Cole, M. T., Shelley, D. J., & Swartz, L. B. (2014). Online instruction, e-learning, and student satisfaction: A three year study. The International Review of Research in Open and Distributed Learning, 15(6). Croxton, R. A. (2014). The role of interactivity in student satisfaction and persistence in online learning. Journal of Online Learning and Teaching, 10, 314-324. Retrieved from http://jolt.merlot.org/ Culp, M. M. (2014). Adult learners: Who they are, why they matter, and what they need to succeed. In M. M. Culp & G. J. Dungy (Eds.), Increasing Adult Learner Persistence and Completion Rates: A Guide for Student Affairs Leaders and Practitioners (pp. 1-23). Washington, DC: NASPA – Student Affairs Administrators in Higher Education. Davidson, W. B., Beck, H. P., & Milligan, M. (2009). The college persistence questionnaire: Development and validation of an instrument that predicts student attrition. Journal of College Student Development, 50(4), 373-390. Retrieved from https://www.proquest. com/scholarly-journals/college-persistence- questionnaire-development/docview/195185998/se- 2?accountid=31259 Dexter, Paul D. (2015). The influence of engagement upon success and persistence of online undergraduates. University of Southern Maine. ProQuest Dissertations Publishing, 2015. 3723157. Diez, J. J., Ebro, E. M., Dequito, R. J. C., & Diquito, T. J. A. (2021). Uncovering Learners’ Experiences to New Normal Education: Implications of Asynchronous Instruction in GE 5: Science, Technology, and Society Course Teaching. European Journal of Education Studies, 8(10). https://doi.org/10.46827/ejes.v8i10.3937 Diquito, T. J. A., Acuña, A. R., Garcia, J. R., & Laganson, J. B. C. (2024). Analysis of Students’ Climate Change Learning Using the Affective Domain of Learning. Revista De Gestão Social E Ambiental, 18(6), e05908. https://doi.org/10.24857/rgsa.v18n6-075 Emmanuel-Frenel, R. (2017). A study of the relationship between distance learners’ perception of the value of student support services and a sense of belonging in the university’s learning community (Order No. 10622513). Available from ProQuest Central. (1955191539). Retrieved from https://www.proquest. com/dissertations-theses/study-relationship- between-distance-learners/docview/1955191539/se- 2?accountid=31259 Glenn, D. M. (2017). Persisting through college: The academic and social integration of first-generation college students of color participating in a student engagement program (Order No. 10278433). Available from ProQuest Central. (1898694806). Retrieved from https://www.proquest.com/dissertations- Pa ge 17 8 https://journals.e-palli.com/home/index.php/ajahs Am. J. Arts Hum. Sci. 3(3) 171-179, 2024 theses/persisting-through-college-academic-social/ docview/1898694806/se-2?accountid=31259 Gutirrez-Santiuste, E., Rodriguez-Sabiote, C., & Gallego- Arrufat, M. J. (2015). Cognitive presence through social and teaching presence in communities of inquiry: A correlational-predictive study. Australasian Journal of Educational Technology, 31(3), 349–362. https://doi.org/10.14742/ajet.v0i0.1666 Hills, P., & Keegan, D. (1994). Theoretical principles of distance education. British Journal of Educational Studies, 42(4), 411. https://doi.org/10.2307/312168 Hollis, L. P. (2016). The importance of professor civility in a computer-based open-access environment for a minority-serving institution. In The Coercive Community College: Bullying and its Costly Impact on the Mission to Serve Underrepresented Populations. Emerald Group Publishing Limited, pp. 65-82. Horzum, M. B. (2015). Interaction, structure, social presence, and satisfaction in online learning. Eurasia Journal of Mathematics, Science and Technology Education, 11(3), 505–512. https://doi.org/10.12973/ eurasia.2014.1324a Huang, X., Chandra, A., DePaolo, C., Cribbs, J., & Simmons, L. (2015). Measuring Transactional Distance in Web- Based Learning Environments: An Initial Instrument Development. Open Learning, 30(2), 106–126. Inkelas, K. K., Daver, Z. E., Vogt, K.E., & Leonard, J. B. (2007). Living-learning programs and first-generation college students’ academic and social transition to college. Research in Higher Education, 48(4), 403-444. doi:10.1007/s11162-006-9031-6 Jefferys, Adam. (2021, January 17). Distinguishing Between Descriptive & Causal Studies. sciencing.com. Retrieved from https://sciencing.com/distinguishing-between- descriptive-causal-studies-12752444.html Joo, Y. J., Lim, K. Y., & Kim, E. K. (2011). Online university students’ satisfaction and persistence: Examining perceived level of presence, usefulness and ease of use as predictors in a structural model. Computers & Education, 57(2), 1654-1664. Joo, Y. J., Lim, K. Y., & Kim, J. (2013). Locus of control, self-efficacy, and task value as predictors of learning outcome in an online university context. Computers & Education, 62, 149-158. Jordan, K. (2014). Initial trends in enrolment and completion of massive open online courses. The International Review of Research in Open and Distributed Learning, 15(1). https://doi.org/10.19173/irrodl. v15i1.1651 Kauffman, H. (2015). A review of predictive factors of student success in and satisfaction with online learning. Research in Learning Technology, 23. Keefer, J. M. (2015). Experiencing doctoral liminality as a conceptual threshold and how supervisors can use it. Innovations in Education and Teaching International, 52(1), 17–28. https://doi.org/10.1080/14703297.2014.981 839 Languita, J. M. S., Ligtas, J. B., Baron, D. C., & Diquito, T. J. A. (2023). Preferred Style of Teaching and Learning by College Students in the New Normal. American Journal of Multidisciplinary Research and Innovation, 2(1), 74–82. https://doi.org/10.54536/ajmri.v2i1.1209 Lee, Y., & Choi, J. (2013). A structural equation model of predictors of online learning retention. The Internet and Higher Education, 16, 36-42. Levy, Y. (2007). Comparing dropouts and persistence in e-learning courses. Computers & Education, 48(2), 185- 204. Lucey, K. (2018). The effect of motivation on student persistence in online higher education: A phenomenological study of how adult learners experience motivation in a web-based distance learning environment (Doctoral dissertation, Duquesne University). ProQuest Dissertations Publishing. (Accession No. 10750789). Markle, G. (2015). Factors influencing persistence among nontraditional university students. Adult Education Quarterly, 65(3), 267-285. Martin, F., & Bolliger, D. U. (2018). Engagement matters: Student perceptions on the importance of engagement strategies in the online learning environment. Online Learning, 22(1), 205-222. https://doi.org/10.24059/ olj.v22i1.1092 Mbwesa, J. K. (2014). Transactional Distance as a Predictor of Perceived Learner Satisfaction in Distance Learning Courses: A Case Study of Bachelor of Education Arts Program, University of Nairobi, Kenya. Journal of Education and Training Studies, 2(2), 176–188. Mehri, S., & Izadpanah, S. (2017). The effect of computer- mediated communication tools in online setting on Iranian efl learners’ teaching, social and cognitive existence. Journal of Language Teaching and Research, 8(5), 978. https://doi.org/10.17507/jltr.0805.20 Moore, M. G. (1972). Learner autonomy: The second dimension of independent learning. Convergence, 5(2), 76–88. https://doi.org/10.1093/elt/ccs044 Moore, M. G. (1989). Editorial: Three types of interaction. American Journal of Distance Education, 3(2), 1-6. Moore, M. G. (1993). Theory of transactional distance. Theoretical principles of distance education, 1, 22-38. Oregon, E., McCoy, L., & Carmon-Johnson, L. (2018). Case analysis: Exploring the application of using rich media technologies and social presence to decrease attrition in an online graduate program. Journal of Educators Online, 15(2). https://doi.org/10.9743/ jeo.2018.15.2.7 Park, J. H., & Choi, H. J. (2009). Factors influencing adult learners’ decision to drop out or persist in online learning. Educational Technology & Society, 12(4), 207- 217. Pattison, A. B. (2017). An exploratory study of the relationship between faculty social presence and online graduate student achievement, satisfaction, and persistence (Order No. 10259040). Available from ProQuest Central. (1874562951). Retrieved from https://www.proquest.com/dissertations-theses/ Pa ge 17 9 https://journals.e-palli.com/home/index.php/ajahs Am. J. Arts Hum. Sci. 3(3) 171-179, 2024 exploratory-study-relationship-between-faculty/ docview/1874562951/se-2?accountid=31259 Paul, R. C., Swart, W., Zhang, A. M., & MacLeod, K. R. (2015). Revisiting Zhang’s scale of transactional distance: Refinement and validation using structural equation modeling. Distance Education, 36(3), 364-382. Peterson, E. R. (2019). Effect of videoconferencing on online doctoral students’ transactional distance, student satisfaction, and intent-to-persist (Order No. 27547859). Available from ProQuest Central. (2334771440). Poquet, O., Kovanović, V., de Vries, P., Hennis, T., Joksimović, S., Gašević, D., & Dawson, S. (2018). Social presence in massive open online courses. International Review of Research in Open and Distance Learning, 19(3), 43–68. https://doi.org/10.19173/ irrodl.v19i3.3370 Richardson, J. C., Besser, E., Koehler, A., Lim, J. E., & Strait, M. (2016). Instructors’ perceptions of instructor presence in online learning environments. International Review of Research in Open and Distance Learning, 17(4). https://doi.org/10.19173/irrodl. v17i4.2330 Rutter, K. (2016). Student satisfaction and persistence in online courses: Implications for instructional design. Available at: https://www.researchgate.net. Schreiner, L. A. (2009). Linking student satisfaction and retention. Coralville, IA: Noel-Levitz. Retrieved from https://cmsro.uwstout.edu/admin/provost/upload/ LinkingStudentSatis0809.pdf Selim, H. M. (2007). Critical success factors for e-learning acceptance: Confirmatory factor models. Computers & Education, 49(2), 396-413. Shin, N. (2003). Transactional presence as a critical predictor of success in distance learning. Distance Education, 24 (November 2014), 69–86. https://doi. org/10.1080/01587910303048 Sorensen, C., & Donovan, J. (2017). An examination of factors that impact the retention of online students at a for-profit university. Online Learning, 21(3), 206-221. doi:10.24059/olj.v21i3.935 Steinman, D. (2007).Educational experiences and the online student. TechTrends, 51(5), 46-52, 2007 Sweetland, Lascelle A. (2015). Online Degree Programs’ Impact on Student Motivation : Factors That Influence South Florida Online Master’s Degree Students’ Motivation. St. Thomas University, ProQuest Dissertations Publishing, 2015. 10105861. Toliao, P. S. (2017). Underprepared, first-year college student experiences with academic integration (Order No. 10743564). Available from ProQuest Central. (2014374911). Retrieved from https://www. proquest.com/dissertations-theses/underprepared- first-year-college-student/docview/2014374911/se- 2?accountid=31259 Weidlich, J., & Bastiaens, T. J. (2018). Technology matters – the impact of transactional distance on satisfaction in online distance learning. International Review of Research in Open and Distributed Learning, 19(3) Willging, P. A., & Johnson, S. D. (2009). Factors that influence students’ decision to dropout of online courses. Journal of Asynchronous Learning Networks, 13(3), 115-127. Yalcin, Y. (2017). Online learners’ satisfaction: Investigating the structural relationships among self- regulation, self-efficacy, task value, learning design, and perceived learning (Order No. 10637957). Available from ProQuest Central. (2018825524). Zalsos, E., & Corpuz, G. G. (2024). Academic Management and Instructional Practices of Higher Education Institutions in Lanao Del Norte: Basis for Faculty Development Plan. American Journal of Arts and Human Science, 3(2), 19–38. https://doi. org/10.54536/ajahs.v3i2.2649