Predictors of Students’ Academic Performance in Online Learning

Predictors of Students’ Academic Performance in Online Learning

Mia B. Villanueva, Jazel G. Leyson, Joel V. Cocolan, April Farrell M. Relacion

Faculty of the College of Education Misamis University Ozamiz City

DOI: https://dx.doi.org/10.47772/IJRISS.2024.8110136

Received: 30 October 2024; Accepted: 05 November 2024; Published: 10 December 2024

ABSTRACT

Online learning is using the Internet to provide educational information, resources, and assistance to students, allowing meaningful interaction and supporting knowledge creation. This study used the descriptive-correlational research design to determine the predictors of students’ academic performance in online learning at the College of Education of Misamis University, Ozamiz City. Stratified random sampling was used to get the 124 education students who served as respondents. An adopted instrument in the Factors that Affect Students’ Academic Performance in Online Learning questionnaire from Gopal and Mushtaq (2020) consisting of 28 statements was used as the research instrument. This tool consists of 4 categories: Study Habits, Teacher Skills and Efforts, Accessibility, and Parental Involvement. Results showed that the perceived factors influencing students’ academic performance in online learning regarding study habits, teacher skills and efforts, accessibility, and parental involvement were high. Students have average performance in online learning based on their general weighted average in the first semester of the school year 2021-2022. Study habits and accessibility were significantly correlated with academic performance. The predictors of students’ academic performance in online learning were study habits and accessibility. Students with good study habits and internet connectivity will likely achieve and maintain good grades in their online learning. If internet access is not widely available in rural areas, teachers give extensions to pass requirements without deducting more significant points.

Keywords: predictors, performance, online learning, accessibility

INTRODUCTION

Online education is a phenomenon that has been around for a while. Its origins can be found in distance learning and the development of digital technologies that enable lectures, virtual classes, and other educational materials and activities to be provided effectively and reliably over the Internet. Advances in online learning management systems (LMSs) and instructional platforms, in addition to the persistent need for cost-effective, top-notch education, there is a growing demand for accessibility to students who either cannot or would rather avoid relocating or commuting to a traditional college campus., have established online instruction as a thriving and competitive alternative to conventional campus-based instruction (Wang et al., 2020).

Online education also provides a broader range of curriculum options. Students who study in a conventional classroom must either take courses at colleges within driving distance or relocate. Web-based learning, on the other hand, provides students with electronic access to various colleges and course options (Salcedo, 2019). As a result, students who previously had access to only a few institutions in their surrounding vicinity may now access several colleges worldwide from a single, convenient place. Students who usually do not engage in class can now express their ideas and concerns through online instruction. Quieter students may feel more comfortable participating in class conversation without being identified or criticized because they are not in a classroom setting. As a result, average class scores may rise (Driscoll et al., 2020). Online learning is critical to the long-term growth of institutions, reporting that the increase in demand for online courses or programs is more significant than that for face-to-face courses. Online learning offers an enhanced level of student-to-student and student-to-instructor accessibility throughout the day, depending upon the instructor’s guidelines (e.g., contact times). Online learning, as opposed to classroom training, allows students to interact with the instructor, and students are not restricted by space or time. They can enhance their learning prospects from any location, irrespective of their residence, work hours, or time.

Over the past three centuries, distance learning in the United States has developed into what is now called “online learning” through important delivery mechanisms that reflect the tools available at the time: the postal system, radio and television, and interactive technologies. Typical learning takes place in a classroom environment with students interacting with their teachers face to face. As a result of the ever-expanding influence of technology, the globe has experienced enormous changes in the landscape of education since the 1990s. One such trend is the acceptance of online learning across many learning contexts, whether formal or informal, academic or non-academic, domestic or remote. We started to see schools, instructors, and students adopting e-learning tools that allow teachers to conduct interactive instruction, effortlessly exchange materials, and enhance student collaboration and involvement (Garcia et al., 2018). Even though the educational world has long recognized the usefulness of online learning data th,e hurdles in its implementation continue to accumulate (Barrot, 2020)

The current situation is unusual in that it can exacerbate the difficulties encountered during online learning because of movement limits and health measures (Gonzales et al., 2020; Kapasia et al., 2020). Given the current situation, acquiring a more detailed knowledge of students’ online learning experiences during the COVID-19 epidemic is critical. Many studies have focused on students’ mental health, home learning, self-regulation, virtual learning environments, and overall learning experience (Singh et al., 2020).

Student performance throughout COVID-19 has improved compared to a cohort from the previous year. The benefits of online learning during the pandemic may have been facilitated, according to some data. Gonzalez et al. (2020) examined student performance and discovered a considerable improvement in the online and face-to-face test scores when pupils were confined owing to COVID-19. Despite the possibility of objectively measured performance improvements, there needs to be more data regarding how online learning and COVID-19 measures (stay-at-home) have impacted the learning process from the students’ perspectives (Aguilera-Hermida, 2020).

The assessment of students’ experiences and academic performance within the new learning platform is imperative. Academic performance serves as a pivotal indicator of the quality of education. Analyzing the impact of online learning is crucial for evaluating curriculum adjustments and comprehending students’ academic progress. To identify areas for enhancement, assess the effectiveness of instruction, and recognize the strengths of the online learning environment, it is equally important to gauge the satisfaction levels of students. It has been observed that students’ satisfaction is intricately linked to their performance, motivation, retention, program completion rates, and overall outcomes, emerging as a critical element in ensuring educational quality (Oducado & Estoque, 2021).

In line with our topic, four factors affect students’ performance in online learning. These are study habits, teacher skills and efforts, accessibility, and parental involvement. The new home-based online learning mode has put new obligations on university students; on the other hand, the question of how to increase the learning impact has prompted fresh thinking among professors. This research extends the four aspects of online learning: a sense of effort, a sense of control, a sense of involvement, and a sense of environment, by conducting in-depth exploration from the perspective of students’ self-efficacy (Wladis et al., 2018).

Students’ experiences and academic performance in the new learning platform need evaluation. The student’s academic performance is a crucial indicator of quality education. Examining the impact of online learning for evaluating curriculum adjustments is essential to understanding students’ academic progress. In order to identify the areas for improvement, evaluate the effectiveness of the instruction, and identify the strengths of the online learning environment, it is also necessary to understand how satisfied the students are with it. Students’ pleasure was discovered to be linked to their performance, motivation, retention, program completion rates, and results, becoming a crucial element of educational quality assurance (Oducado & Estoque, 2021).

In line with our topic, four factors affect students’ performance in online learning. These are study habits, teacher skills and efforts, accessibility, and parental involvement. The new home-based online learning mode has put new obligations on university students; on the other hand, the question of how to increase the learning impact has prompted fresh thinking among professors. This research extends the four aspects of online learning: a sense of effort, a sense of control, a sense of involvement, and a sense of environment, by conducting in-depth exploration from the perspective of students’ self-efficacy (Wladis et al., 2018).

As online learning places all control into the hands of online learners, they must take it upon themselves to plan, organize, monitor, self-reflect, and evaluate their learning processes. Online learners must be independent and autonomous, as the essence of successful online learning is self-direction and self-management (Ejubovic & Puška, 2019). Students’ self-respect, creativity, and conviction in academic progress have always affected academic performance. Poor performance influences students’ future uncertainty about outcomes such as higher grades. Thus, a student’s academic performance is a subject in the spotlight for educators (Mushtaq & Khan, 2019).

The quality of instructors with high fanaticism for student learning positively impacts their satisfaction. The way instructors conduct online discussions stands out as a crucial determinant of student satisfaction, significantly impacting the overall educational process. Satisfaction among faculty is recognized as a key element in the quality of online courses. A study was undertaken to pinpoint and validate factors influencing online faculty satisfaction at a small research university. The aim was to develop and validate an instrument capable of measuring perceived faculty satisfaction within the online learning environment. Attitudes held by instructors, students, course administrators, and course designers collectively shape the quality of a remote education program. This research identifies elements that impede these efforts, hindering the participation of certain groups in this educational medium. The study will assess and appraise the attitudes of students, instructors, administrators, and designers regarding online education, recognizing their substantial impact on the quality of distance education programs (Richardson & Swan, 2017).

Students and teachers have expressed several concerns about online classes, which are reflected in the data. For starters, this is their first time connecting with an online class. Thus, they are having difficulty adapting to this trend, as going from a traditional classroom to computer-based instruction in a virtual classroom changes their learning and teaching experience completely. Second, most students stay home during the shutdown in various parts of the country since internet facilities are still few in rural regions. As a result, students use mobile internet, which disrupts online connectivity owing to poor internet signal. Aside from that, internet access in our country still needs to be more affordable. Finally, there are some technological obstacles, such as a need for literacy when using a computer or a smartphone. Furthermore, students and teachers must download programs such as Zoom, FoxFi, Audioboo, and others.

Limited knowledge and the time constraints for online connectivity can lead to challenges with certain applications. According to Khanna and Prasad (2020), a significant portion of the population encounters internet issues and lacks the expertise to address technological problems. The use of technology is contributing to a knowledge gap among people. It is essential for students and educational institutions to collaborate in addressing these issues that hinder the progress of academic life. Alam (2020) emphasizes the need for a comprehensive and robust plan to overcome these challenges and enhance our educational endeavors. Parental involvement is one of the determinants of the student’s academic success. According to previous results, students are passive in learning in-home isolation compared to their academic achievement. They will likely have more free time, develop irregular sleeping patterns, and eat unhealthy foods. These adverse effects on pupils are likely to develop during lengthy periods of quarantine, which will undoubtedly affect their academic performance (Wang et al., 2020). According to Sprang and Silman (2018), psychological illnesses that are neglected during quarantine are more stressful than those that are not. The results of a study of 506 parents revealed that the pandemic had a significant impact on their children’s mental health. Various forms of parental participation can benefit or harm a child’s capacity to thrive in high school and college. Parents had a significant influence on their children since they were the ones who introduced them to the outside world, including academics. The term “parental engagement” refers to a parent’s level of interest in their child’s education and life.

Prospective students want to get a good education without giving up time with their families, employment, or travel expenses. Instead of being required to be in a given area at a specific time, online educational students can speak with instructors, address classmates, study materials, and complete tasks from any Internet-connected location (Richardson & Swan, 2017). This kind of flexibility provides students with much-needed mobility, which makes the educational process more appealing. Lundberg et al. (2018) suggest that a student might opt for an online course or pursue an entirely online-based degree program due to the flexibility they offer in terms of study hours. For instance, a working student could participate in virtual classes and access instructional films and streaming lecture videos outside of their working hours.

According to Wallace and Hentgens (2017), poor treatment of children, such as physical abuse, screaming, and other punishments, has a detrimental influence on their academic performance and outputs. On the other hand, students who have active parental involvement in their education are more likely to be motivated and succeed. Making school more exciting and fulfilling in a short period for these students, such as through peer-to-peer learning, hands-on projects, and experiences, may be more effective. The study on parent engagement in schools focused on the home background in terms of features of school involvement activities and then followed up to see if it had any effect on academic achievement. As a result, it contributes to their children’s willingness and motivation (Park & Holloway, 2017).

Furthermore, supervising students’ academic work may enhance their anxieties about their image but not their academic achievement. School accomplishment is influenced directly and positively by parents’ expectations and children’s performance and indirectly and adversely by parents’ participation in tasks and orientation to goals and objectives. Similarly, parent-delivered compensatory education for children at risk of educational failure: improving academic and self-regulatory skills revealed that significant increases in parental involvement and expectations were translated into mediated intervention gains in child literacy skills and academic results. As a result, it advised that parents’ opinions about their kid’s academic potential and their methods of behavioral support for the child should be considered.

Critical linkages include school-based participation, family educational aspirations, teenagers’ cumulative high school grades, and academic accomplishments (Benner, 2017). The study’s findings revealed a substantial beneficial association between parental participation in education and students’ academic achievement. As previously said, parents should lead in encouraging and supporting their children’s accomplishments and objectives.

With the wide use of technology in today’s environment, we should not be concerned about which is better in delivering instruction. Our primary goal should be determining whether students learned and enhanced their learning experiences. The researcher conducted this study to explore the variables that contributed to the success of online learning and students’ academic performance. If none, then the researcher would like to study more about what is going wrong and how they can enhance the learning instruction that contributed to the success or failures of students’ academic performance in online learning.

This research will significantly benefit teachers regarding their critical role with their students. That no classes would be jeopardized in the event of a disaster and that they could be resumed without interruption. They must equip themselves with technical literacy to do their everyday responsibilities, which may influence the quality of future societal leaders. The project aims to strengthen teacher-student cooperation to accomplish outcome-based education, which will ultimately decide the students’ level of achievement and the school’s success. This can serve as an initial reference for upcoming researchers interested in conducting studies to delve deeper into the concept, aiming to expand the existing literature and address any gaps. The employed research design may offer valuable insights for shaping their studies.

Review of Related Literature and Studies

The COVID-19 outbreak has compelled millions of students to shift to home-based learning. While learning from home has a long history, primarily in the context of informal education, it has now become a new normal for students. Education Task (2020) notes that many university students find comfort in studying at home, where they have everything at their disposal without leaving their seats. However, the transition to formal education from home poses significant challenges for educators, learners, and parents, particularly in developing countries where technology’s accessibility, availability, and use in education are not widespread. Beyond the financial aspects of online education, various factors like network issues, unreliable power supply, distractions, limited digital skills, inaccessibility, and availability problems can hinder a seamless home-based study experience. Additionally, challenges include the time required to learn new technologies for remote learning and disturbances from internal or external noises originating from neighbors and neighborhoods (Onyema et al., 2020). As studies on the implementation of online learning during COVID-19 have progressed, two general patterns have emerged so far.

Initially, evaluate online learning courses from a normative perspective, encompassing user perceptions, implementation, and the technology platforms utilized. The second trend concerns evaluation, including the factors influencing students’ online learning performance (Yudiawan et al., 2021).

As the prevalence of online education continues to grow, many educational institutions are exploring effective ways to deliver course content to online learners. This study utilizes data from the National Survey of Student Engagement to investigate the impact of online courses on student engagement. Through the analysis of ordinary least squares regression models, considering relevant student and institutional characteristics, the findings reveal significant relationships between online courses and student engagement for both first-year students and seniors.

The results indicate that students enrolled in more extensive online courses are more likely to engage in quantitative reasoning. However, they are less inclined to participate in collaborative learning, student-faculty interactions, and discussions with diverse peers compared to their counterparts in traditional classrooms. Additionally, students with a higher number of online courses reported less exposure to effective teaching practices and lower-quality interactions. The relationship between engagement indicators and the percentage of online classes suggests that while an online environment may benefit certain types of engagement, it may hinder others. The study emphasizes the importance of considering these findings in the design of online course content and encourages institutions to promote various strategies for fostering student engagement across different delivery formats (Gillett-Swan, 2017).

Nevertheless, questions persist about the preparedness, design, and effectiveness of e-learning, especially in developing countries like India, where technical constraints such as device suitability and limited bandwidth pose significant challenges. A study focusing on agricultural students’ perceptions and preferences toward online learning in India reveals that a majority of respondents are willing to opt for online classes during the pandemic. The preference for smartphone use and recorded classes with quizzes for improved learning effectiveness was prominent, although challenges related to broadband connectivity in rural areas were acknowledged (Muthuprasad et al., 2021).

Researchers have explored various factors influencing students’ performance and learning outcomes in the online learning environment. Some models include student satisfaction and academic achievement as mediating variables, emphasizing the need to investigate factors affecting these aspects in online courses. For example, Choi’s conceptual model considers learner, external, internal, and outcome factors, encompassing variables such as age, gender, educational level, motivation, external encouragement, financial support, and internal factors like social integration and technology usability (Hee-Jun, 2021).

Concerning participation in online asynchronous discussions, several studies have examined factors falling into categories such as attributes of asynchronous online discussion, facilitator roles, and discussion activity design. Additional factors influencing online learner participation include technology and interface characteristics, content area experience, student roles, instructional tasks, and information overload (Yukselturk, 2017).

Amid the shift to online learning prompted by the COVID-19 pandemic, educational institutions are grappling with the challenge of maintaining teaching continuity. However, the quality of learning is intricately tied to digital access and efficiency. The online learning environment differs significantly from traditional classrooms in terms of learner motivation, satisfaction, and interaction (Bignoux & Sund, 2018). The abrupt transition to online learning underscored organizational agility, with institutions primarily focusing on transferring educational content to the digital realm rather than refining online teaching and delivery methods (Wu, 2020). This shift also highlighted resource limitations and social inequalities, affecting students’ ability to engage in digital learning (Zhong, 2020). Instructor interaction and concerns about online course content have become primary considerations, with email serving as the primary mode of communication, albeit with response time challenges (Zhong, 2020).

Students’ academic performance in most universities has become an object of inquiry by researchers nowadays. Education, trainers, and researchers have long been interested in identifying characteristics that substantially impact student performance. These variables are both external and internal. External factors contribute to students’ external environment that is beyond their control, whereas internal factors are primarily student-related. The former includes home, school, and teacher-related factors, while the latter includes personal factors and study habits (Alshammari et al., 2017). According to (Maheshwari, 2021), three essential aspects influence students’ online learning experiences: a comfortable and quiet learning environment, teachers’ support, and the learning platform’s ease of use. There are a variety of other aspects that can influence a learner’s learning experience and desire to study online. Researchers have recognized that home, personal, and teacher-related factors contribute to a student’s academic performance.

Based on a BEAN survey conducted among undergraduate and postgraduate students in Vietnam who engaged in online learning during the pandemic. The internet’s stability and speed were cited as the most critical factors influencing students’ online learning experiences (B and Company, 2020). A global report by UNESCO in 2020 reveals that nearly 826 million students, who were unable to attend classrooms, lack access to a household computer. Additionally, approximately 706 million students have no access to the internet in their homes.

Economically disadvantaged students, particularly those residing in rural areas of our country, will be marginalized by this, hindering their access to essential technology. Another previous studies (Kuama & Intharaksa, 2016) there are two suggestions for further research: first, the main challenges in online learning are technical and individual problems that students face; assisting students in overcoming these two challenges would increase satisfaction with the new mode of learning and promote online learning motivation. Addressing technological challenges necessitates a sufficient Internet connection and round-the-clock accessibility to Internet connectivity. One challenge that some students residing in rural areas and the region still need to improve is a better internet connection. For example, if a professor is giving a live broadcast and our connection or signal could be better, the lecturer’s delivery of material would inevitably lag, preventing students from receiving it to its full potential (Simamora, 2020).

Even though most schools rapidly began to provide some form of virtual education (Hamilton et al., 2020), there have been concerns about the effects of online learning on students’ performance (Malkus, 2020). Why do students struggle more in fully online courses? Practitioners and scholars increasingly acknowledge two crucial challenges to successful online learning: the requirement of higher-level self-directed learning skills and more significant difficulties in enabling effective human interactions. On top of these challenges, individual differences in technology literacy and unequal access to computers and the internet may also hinder some students’ online learning effectiveness (Xu, 2019).

Low-income students, in particular, express concerns that the transition to online learning may lead to unequal effects for them. They worry that their limited financial resources could result in less access to online resources, further exacerbating the challenges posed by the loss of in-person instruction (Horowitz, 2020). Home-related factors still have an extensive effect on students’ academic performance. The term “home” spans a wide variety of concepts. However, in this study, home-related factors are persons and things present in the student’s home that influence their academic achievement to a lesser or greater degree. These include the student’s parents, elders, siblings, communication devices, financial capability, and educational opportunities (Alshammari et al., 2017).

According to (Zahra et al., 2020), online classes during COVID are expensive. Parents should provide social support at home so children are comfortable learning. Social support generally refers to the function or effect that significant others, such as family members, friends, and relatives, can have. The capacity and awareness of the condition that children experience, ranging from lifestyle, is heavily influenced by parental education. The involvement of children’s learning assistance, nutritional intake, and influence on parental economic status can affect student’s academic performance (Pajarianto, 2020).

The interaction between students and teachers is shaped by technology, and the design of the learning environment can significantly impact learning outcomes (Gonzalez et al., 2020). When comparing the current study to previous research, previous research looked at the elements that influence student happiness in a traditional schooling setting. On the other hand, the current study was done during India’s shutdown era to uncover the key aspects that influence students’ happiness with online courses. The study also looked into the relationship between student satisfaction and academic achievement. According to the findings of this study, the quality of the instructor or teacher-related factors is the most crucial element influencing student academic performance in online classrooms. This requires a high level of efficiency from the lecturer, as they must comprehend students’ psychology to teach the course material effectively. The teacher’s proficiency influences the satisfaction and performance of students in delivering the course information (Gopal et al., 2021).

Instead of traditional teaching, the responsibility of an instructor in an online environment is to inspire, advise, and invoke critical thinking in students with autonomy and accountability. Being a good educator and having reliable technological tools are essential in online classrooms.

Effective facilitation and the establishment of social presence, primarily driven by the instructor, play pivotal roles in determining the quality of online learning. The instructor’s knowledge and facilitation in online classes have a positive impact on students’ perceived learning outcomes (Baber, 2020). Additionally, fostering communication between teachers and students through informal channels such as instant messages, online chat groups, audio calls, and private video calls alongside formal channels like online platforms and email is crucial. Instructors are also encouraged to motivate students to engage and study more by offering various incentives (Alawamleh et al., 2020).

Research underscores the significance of building rapport and promoting collaboration between students and instructors in an interactive online learning environment (Martin & Bolliger, 2018). According to (Abuhassna et al., 2020), another important thing to remember is that it might be something other than technology that causes this type of change in learners’ achievement. It is the educational method used in the teaching and learning process. Most important of all is teacher training. Quality of education online requires instructors trained in online teaching to create student satisfaction and higher academic achievement.

Moreover, (Markova et al., 2017) found some controversies in how students evaluate the effectiveness of their distance learning compared to other education patterns.

Despite being positively motivated to pursue online courses, students encounter various challenges in distance learning. These challenges include difficulties in self-organization, a perceived lack of control on the instructor’s part, ineffective interaction, and a sense of isolation, all contributing to reduced satisfaction with the online learning experience. These findings support the argument that successful and effective distance learning necessitates significant attention and commitment from faculty. The faculty’s role is evident in the design and delivery of instruction, as well as their incorporation of relevant course content, emphasizing student support, interaction, and assessment techniques. These factors are deemed critical for the success of distance learning (Duque et al., 2018).

According to (Selvaraj et al., 2021), online learning can affect student’s performance because some students cannot adapt comfortably to the shift of education to online mode and directly suffer from mental or physical discomfort. These include headaches, strain in the eyes due to longer time spent in front of computers, backache, lack of motivation to teach, anxiety, and stress. The rapid adoption of online or remote learning during the pandemic has led to heightened anxiety and various affective states among educators and learners. Additionally, environmental factors, including lighting, noise, and temperature levels, can impact academic achievement. Variables such as students’ desk/table and chair designs, the technical devices they use for studying (tablet, mobile phone, computer), and the duration of interaction with this furniture and equipment can also play a crucial role. Poor ergonomic design may result in physical discomfort in areas such as the back, neck, arms, and wrists, potentially increasing mental workload and leading to stress, anxiety, and headaches, particularly in children (Vargas et al., 2020).

Krashen (as cited in Russell, 2020) notes that heightened anxiety and stress levels can act as filters, hindering the internalization of linguistic input. Piaget (as cited in Duque et al., 2018) similarly emphasizes the significant impact of affective factors on the cognitive process. Mental health issues emerge as a major obstacle to academic success, influencing motivation, concentration, and social interactions, all crucial components for student success in higher education (Son et al., 2020). Positive emotions correlate with improved performance, while negative emotions can have adverse effects (Duque et al., 2018). Motz et al. (2021) discovered that increased effort in online classes does not necessarily translate to better grades and learning outcomes, underscoring the need for adjustments in online learning processes (Karalis, 2020). Elements like decreased motivation, delayed feedback, and feelings of isolation due to the absence of physical presence can pose obstacles in the learning process (Coman et al., 2020).

Student engagement, defined as an individual’s interest and enthusiasm for school, plays a pivotal role in influencing academic performance and behavior (Alalwan, 2019). Social interactions online contribute significantly to student satisfaction and better results, as demonstrated by the study. The social dimension enables students to establish interactions and gather information from peers, motivating the use of communication tools in the online environment and enhancing social interaction (Cidral et al., 2018). Future research directions may explore various data-mining and analytics techniques for detecting and predicting at-risk students, evaluating the efficacy of student and faculty support programs, and identifying strategies to encourage struggling students to adopt effective learning behaviors (Muljana & Luo, 2019).

Theoretical Framework

This study was anchored on Herbert J. Walberg’s theory of educational productivity (1981).

Walberg’s theory (1981) concerns the factors in learning that impact a student’s academic achievement. It is a study of academic achievement in which Walberg uses a range of methodologies to identify the factors that influence a student’s academic performance. In his theories, he identified 11 influential categories of variables, eight of which are influenced by social-emotional factors: classroom management, parental support, student-teacher interactions, social-behavioral qualities, motivational-effective attributes, the peer group, school culture, and classroom climate. Distant background influences could have been more influential. According to the Walberg research evaluation, student learning characteristics were identified as the collection of variables with the highest potential for alteration, which may have a significant and beneficial effect on student outcomes. According to the Walberg large-scale causal modeling research, nine key educational productivity elements were hypothesized to operate a complicated network of relationships to account for school learning. Furthermore, some student characteristics had an indirect effect.

For a student’s educational production to be consistent in creativity and good results, their mental health must be considered. According to the Walberg theory of educational productivity, socio-emotional effects are critical to a student’s educational development. This theory is based on several reviews of past research on how a student’s mental health and learning environment can influence their academic success. Walberg, 2004). In order to facilitate academic achievement, Walberg emphasized the importance of motivational orientations, self-regulated learning mechanisms, and social/interpersonal talents.

According to the study, students who gained confidence and self-awareness in their learning capacities got more motivated to create educational goals and organization learning tactics in SEL (Social et al.) programs and performed very well in academic studies. They used this theory to identify problems affecting students’ academic performance. The academic performance of a student is influenced by various socio-economic factors. These include the presence of a trained teacher in school, the teacher-student ratio, class attendance, the student’s gender, family income, the educational background of both the mother and father, and the proximity of the school (Amitava Raychaudhuri, 2004). This theory explores academic achievement, wherein Walberg uses various methods to identify the factors that affect a student’s academic performance.

Walberg formulated his theory by analyzing various theorists and incorporating insights from over 3000 studies. Initially postulated in 1981, Walberg’s theory, as outlined by Reynolds and Walberg in 1992, posits that the psychological characteristics of individual students and their immediate psychological environments play a crucial role in shaping educational outcomes. Walberg’s theory emphasizes several key variables that significantly influence student outcomes. These variables include student ability/prior achievement, motivation, age/developmental level, the quantity and quality of instruction, classroom climate, home environment, peer group, and exposure to mass media outside of school (Walberg et al., 1986).

Conceptual Framework

Student engagement refers to an individual’s level of interest and enthusiasm for school, and it has a direct impact on academic performance and behavior (Alalwan, 2019). Our study focuses on the factors influencing students’ academic performance, which is critical to the research and often determines a student’s ultimate position in society. In our study of the factors affecting students’ academic performance in online learning, we suggest a framework that includes four factors: study habits, teacher skills and efforts, accessibility, and parental Involvement.

Study habits are integral to a student’s daily routine, reflecting their perseverance and endeavors to enhance academic performance. They significantly contribute to developing capacities for knowledge and perception, illustrating an individual’s eagerness to learn, the extent of their determination, and the depth of their aspirations.

Teacher skills and efforts encompass various aspects, including the effectiveness of how teachers deliberately discuss specific topics. This can be influenced by factors such as course design, capacity utilization, and content delivery. Teacher skills also extend to technology use, teaching style, interaction with students, strategies for capturing students’ attention, fostering contact between students and faculty, promoting collaborative learning, providing prompt feedback, and implementing active learning methods.

Accessibility refers to students’ access to electronic devices, Wi-Fi, and computer literacy resources. Internet access plays a crucial role in students’ academic outcomes, enabling them to participate in online classes. It opens doors to a wealth of information, educational resources, and opportunities for learning, enhancing the overall online learning experience.

Parental involvement refers to the active participation of parents in regular, two-way, and meaningful communication related to their child’s academic learning and other school activities. The interest and encouragement parents show in their child’s education can significantly impact the child’s attitude toward school, classroom behavior, self-esteem, absenteeism, and motivation. While some schools actively promote healthy parental involvement, parents may sometimes hesitate to engage with their children’s education.

Several factors inside and outside the school influence the quality of students’ academic performance. However, our study only focused on some factors that affect students’ academic performance in online learning. The critical aspect for educators is to educate their students effectively so that they can show quality performance in their academics. To achieve this objective, educators must understand the factors that may contribute to students’ academic success.

Figure 1. Schematic Diagram of the Study

Objectives of the Study

This study will determine the factors that affect student’s academic performance in online learning among Education student at Misamis University, Ozamiz City during the Second Semester, School Year 2021-2022. The specific objectives of the study were to:

1. Determine the level of the perceived factors influencing students’ academic performance in online learning as to study habits, teacher skills and efforts, accessibility, and parental involvement.
2. Determine the academic performance of Education students.
3. Explore the relationship between the perceived factors and the academic performance of the students in online learning.
4. Identify the predictors of academic performance in online learning.

METHODS

Research Design

The descriptive-correlational research design was used in the study. Descriptive research aims to accurately and systematically describe a population, situation, or phenomenon. Descriptive research design can use various research methods to investigate one or more variables (McCombes, 2019). Descriptive statistics will be reported, and correlations between variables will be explored with parametric and nonparametric measures (Efthymiou, 2017). A correlation refers to a relationship between two variables. Correlations can be strong or weak and positive or negative. Sometimes, there is no correlation (Cherry, 2020). Descriptive and correlational designs are focused on describing and examining the relationships of variables in a natural setting (Baker, 2017). This design was used to determine the underlying predictors of students’ academic performance in online learning.

Research Setting

The study was conducted in the tertiary school of Misamis University during the second semester of the 2021-2022 school year. Specifically, the College of Education students of Misamis University are involved in selecting respondents. Misamis University was a recipient of awards by the Philippine Association of Colleges and Universities (PACUCOA) as the “First Bachelor of Secondary Education Program in Region X to have been granted LEVEL III REACCREDITED STATUS in 2013”, as having the most significant number of accredited programs for two consecutive years.

Research Respondents

The respondents of the study were the College of Education students of Misamis University. A total of 124 student-respondents were considered as samples from the population of 252. They were selected through a stratified sampling technique.

Research Instruments

The following instrument was used in this study:

Factors that Affect Students’ Academic Performance in Online Learning. This tool consists of 4 categories: Study Habits, Teacher Skills and Efforts, Accessibility, and Parental Involvement. A total of 28 statements describes the activities of students, teachers, and family that affects the academic performance of students in online learning.

In interpreting the level of factors affecting student’s academic performance, the following scales were used:

   Continuum                                              Responses                                          Interpretation

    5 – Always                                                 4.21-5.00                                  Very High

    4 – Often                                                    3.41-4.20                                   High

    3 – Sometimes                                           2.61-3.40                                   Average

    2 – Rarely                                                  1.81-2.60                                   Low

    1 – Never                                                   1.00-1.80                                  Very Low

Student’s Academic Performance. The performance of the students was based on the General Weighted Average during the First Semester, School Year 2021-2022. In interpreting the students’ academic performance, the University grading interpretation was used.

Grade Point Average                      Interpretation

1.0-1.20                                               Very Superior

1.21-1.40                                               Superior

1.41-1.60                                               Above Average

 1.61-1.80                                               Average

1.81-3.0                                                 Passing

5.0                                                          Failure

Data Collection

The researchers secured a Sample Letter of Request and Informed Consent Form from the secretary of the College of Education. Approval of the Dean of the College of Education of Misamis University was sought to conduct the study. Then, the research instrument was distributed to the students at the College of Education through a survey, and safety protocols were observed in conducting this study.

Ethical Consideration

Protection of the integrity of research participants and informants is a fundamental ethical norm in research, including in special-needs education studies. This norm focuses on protection against various forms of risk involved in participation in research and the protection of the identity of participants, including concerns for preventing stigmatization of populations or groups. Ethical considerations were observed before and during the data gathering. The respondents were asked for their consent to participate, and they had the right to withdraw their participation in the research. The confidentiality of the information supplied by the respondents was respected.

Data Analysis

The following statistical tools were used in the study:

Mean and Standard Deviation. These were utilized in determining the predictors of students’ academic performance in online learning.

Pearson’s (r) Product Moment Correlation Coefficient. This was used in exploring the relationship between the predictors and the student’s academic performance in online learning.

Regression Analysis. This was used in determining the predictors of students’ academic performance in online learning.

RESULTS AND DISCUSSION

Factors that Affect Student’s Academic Performance in Online Learning

Table 1 shows that overall, there is a high (M=4.01; SD=0.52) level of the perceived factors influencing students’ academic performance in online learning. Among the four dimensions, study habits obtained the highest mean (M=4.15; SD=0.53), followed by teacher skills and efforts (M=4.09; SD=0.35), and then followed by parental involvement (M=4,06; SD=0.60) and accessibility (M=3.72; SD=0.59). These imply that students are actively engaged in their online classes, demonstrated the willingness to establish a good relationship with their teachers, developed a good relationship with their parents at home, and experienced a lack of internet connectivity and enough gadgets to be used in their online learning.

Generally, the education students exhibited high engagement in all the factors that affect their academic performance in online learning, as evidenced by the overall results in Table 1. This indicates that the students religiously attended their online classes, actively participated in the discussion, and clarified things they did not understand during their synchronous meetings. The top barriers students encountered during the online portion of the semester were connected to Wi-Fi quality and finding a quiet space. As a result, students use mobile internet, which disrupts online connectivity owing to poor internet signal. Aside from that, internet access in our country still needs to be more affordable. The interaction between students and teachers is also mediated by technology, and the design of the learning environment can influence learning outcomes.

The effective delivery of course content by the teacher plays a crucial role in influencing student satisfaction and performance. A teacher’s ability to convey information accurately and engage students can significantly impact their overall learning experience and academic outcomes. The global pandemic prompted governments to implement a widespread shift to online learning for colleges and universities. This transition was a response to the challenges posed by the pandemic, requiring educational institutions to adapt to remote and digital modes of instruction to ensure the safety of students and educators Despite all the challenges, students tend to cope with the situations and accept the new learning method. Students still managed their time well to pass their requirements on time. From most students’ perspectives, internet connectivity does not hinder them from continuing their studies online. They established a good relationship with their teachers as well as their parents. This kind of relationship helps them to be motivated in their online classes (Hodges et al.et al., 2020).

The data presented in Table 1 imply a high level of engagement in all factors that affect students’ academic performance in online learning. Students rely on their personal study habits on how they will accept and improve their academic performance in online learning. Teachers also have a significant impact on the way students develop their academic performance. The school must continue to provide an internet data plan every month for the students to continue accessing their online platforms, noting that there are also students in rural areas where Wi-Fi is not evident.

Table 1 Level of the Perceived Factors Influencing Students’ Academic Performance in Online Learning (n=124)

Note. Perceived Factors Scale: 4.21-5.00 (Very High); 3.41-4.20 (High); 2.61-3.40 (Average); 1.81-2.60 (Low); 1.00-1.80 (Very Low)

Academic Performance of Education Students

Table 2 reveals the academic performance of education students in terms of their final grades in the second semester of the school year 2021-2022. Most of the students obtained grades that did not meet expectations, having a percentage of 38.65 percent. 8.06 percent of the respondents received an Outstanding performance, 25 percent received Very Satisfactorily, and 16. Ninety-four percent were satisfactory, while 19.45 percent were reasonably satisfactory. With an overall mean of M=1.65, the academic performance of education students is classified as reasonably satisfactory. This implies that most respondents struggle to cope with their academic performance in online learning.

Generally, students performed exceptionally well in their online classes during the second semester of the school year 2021-2022. However, some students need help balancing their studies, especially since this is their first time encountering online classes. This indicates that students have acquired a deep understanding of the topic. However, a hindrance affects their performance, like the loss of stable internet connectivity, which significantly impacts the success of their online performances. Students have different situations and privileges. Some students experience depression and anxiety, a lack of gadgets to use, and even experiences family problems. Based on the first table presented, these factors strongly influence the students’ performance in online learning.

The delivery of college courses online, particularly with synchronous technologies, has seen a significant rise. Educators are actively seeking suitable learning environments that cater to the diverse needs of students. A recent report from Michigan State University’s Quello Center highlights the impact of slow internet connections or limited access in rural areas on students’ academic progress. The data indicates that a substantial number of respondents require assistance with online learning, particularly concerning internet connectivity.

The findings suggest that students lacking internet access or relying solely on a cell phone for connectivity tend to perform half a grade point lower than their counterparts with faster access. This performance gap can have long-lasting repercussions. Furthermore, students without high-speed internet at home are less likely to plan on attending a college or university. For students residing in rural areas attending online classes, challenges related to accessibility significantly affect their academic performance.

Conversely, students with internet access demonstrate substantially higher digital skills, which strongly correlate with performance on standardized tests. This group of students is more likely to excel in online learning due to their enhanced accessibility to internet connections (Johannes, 2020).

It’s crucial to recognize that students’ academic performance is not inherently predetermined or fixed. Instead, it can be influenced by the learning environment they are in. In a positive learning environment, students tend to be more motivated, engaged, and demonstrate higher overall learning abilities. On the contrary, adverse learning environments can make students feel uncomfortable, confused, unsupported, and hesitant to make mistakes, potentially resulting in academic challenges and failures. The impact of the learning environment underscores the significance of creating supportive and encouraging educational settings to foster positive academic outcomes for students.

Table 2 Academic Performance of Education Students (n=124)

Performance Scale: 1.00-1.20 (Very Superior); 1.21-1.40 (Superior); 1.41-1.60 (Above Average); 1.61-1.80 (Average); 1.81 and above (Passing)

Relationship between Perceived Factors and the Academic Performance of the Students in Online Learning

Table 3 reveals the test of the relationship between the perceived factors and the student’sstudents’ academic performance in online learning. A highly significant relationship exists between study habits and academic performance (r=0.33; p=0.00) and accessibility and academic performance (r=0.23; p=0.01). Moreover, there is a significant relationship between parental involvement and academic performance (r=0.22; p=0.02). This suggests that students’ acceptance of online classes, accessibility of internet connections and gadgets, and how their parents are involved in their online classes are directly associated with their academic performance in online learning.

The data tells us that there is a statistically significant association between the accessibility and academic performance of students.

In conclusion, students in higher education extensively rely on the Internet to access relevant information and materials for completing assignments or projects. The findings suggest that the lack of internet access significantly impacts the academic performance of education students, leading to lower grades and overall diminished performance in school. The accessibility and availability of the internet play a pivotal role in shaping the educational outcomes of students. This underscores the importance of addressing issues related to internet access to provide essential support for students in reaching their academic potential. Ensuring equitable access to the internet is vital for creating an inclusive and conducive learning environment, allowing students to fully engage with educational resources and opportunities, thereby fostering academic success and achievement.

Most earlier research on using Internet technology for learning in modern educational settings in developing nations has focused on how it affects academic achievement, communication, and general educational goals. Internet connection is an issue and challenge not only for the students but also for teachers and the institution. Another related matter in this study is the availability of learning tools or devices that are equally important. Although we are in an era where technological instruments and apparatuses are within reach, some still need one. Suppose students need more access to the Internet and need more gadgets to use it. In that case, it means that they cannot pass their online requirements on time and even cannot join their synchronous meetings because of the slow internet connectivity. It means that if they need more access to the Internet, they are expected to gate low performance in their online learning. (Tarimo & Kavishe, 2017).

Study habits encompass individual behaviors related to studying and are a combination of study methods and skills. These habits involve behaviors and skills that can enhance motivation and transform the study process into an effective one, ultimately leading to increased learning. The presented data establishes a direct association between study habits and students’ academic performance.

Given the significance of study habits as a predictor of academic performance, it is advisable to assess and consider students’ study habits upon entry into university. Providing specific training to help students learn or modify their study habits can contribute to enhancing their academic achievements. Research at a global level has consistently demonstrated the impact of study habits on academic performance.

In the context of medical education, students face a substantial volume of challenging information that requires effective organization and learning. Developing and applying study skills become crucial in such situations. Evidence suggests that learners lacking adequate information about study strategies may struggle to achieve effective and stable learning, leading to a negative impact on their academic performance (Jafari, 2019).

Another factor is parental involvement directly associated with students’ academic performance in online learning.

Enhancing communication between parents and teachers has a positive impact on students, fostering increased motivation to learn and resulting in improved grades. This improved communication also contributes to positive changes in student behavior within the classroom. When parents and teachers engage in more frequent and effective communication, students experience heightened motivation in their classes, leading to improvements in their self-esteem and attitudes toward learning. The collaboration between parents and teachers, therefore, plays a crucial role in creating a supportive and motivating educational environment for students.

Academic success in children has regularly been proven to be favorably correlated with parental involvement in their early schooling. Mainly, children with parents who are more involved in their education perform better academically than kids who are less involved. Researchers and policymakers who have incorporated measures targeted at boosting parent involvement into more general educational policy initiatives have noticed the impact of parental involvement on academic success. A child’s academic success is steady mainly after early primary school, consistent with the findings about the significance of early academic success (Topor et al., 2017).

Findings in Table 3 imply that students’ academic performance in online learning is directly associated with factors like study habits, accessibility, and parental involvement. This is to conclude that it is essential to understand better all of the predictors that affect students’ academic performance so we can quickly assess the students’ outcomes.

Table 3 Test of Relationship between Perceived Factors and the Academic Performance of the Students in Online Learning

Note: p˂0.01 (Highly Significant; p˂0.05 (Significant); p˃0.05 (Not Significant)

Predictors of Academic Performance in Online Learning

Table 4 implies the predictors of students’ academic performance in online learning. Multiple regression analysis was used to test if study habits and accessibility significantly predict students’ academic performance in online learning. The regression result shows that two predictors explained 14%% of the variance (R2=13.97%, F=0.32 df=0.11, p<0.01) or the extent of the student’s academic performance in online learning. It was revealed that study habits are the highest of the predictor variables, followed by accessibility. The finding shows that 14 percent of the student’s academic performance in online learning is explained by two predictors: study habits and accessibility. Moreover, it indicates that other factors outside of the predictors mentioned can further explain the students’ academic learning performance in online learning. Hence, it is one of the limitations of this study.

As the results showed, study habits obtained the highest of the predictors that affect students’ performance. Study habits act as another variable connected with distance learners’ performances. Study habits reflect students’ usual act of studying and also call forth and serve to direct the learner’s cognitive processes during learning. Study habits include various activities: time management, setting appropriate goals, choosing an appropriate study environment, using appropriate note-taking strategies, choosing main ideas, and organization. The habitual practices used to help one study and learn can help them achieve excellent academic performance in online learning. Good study habits can help achieve and maintain good grades.

Study habits play a significant role in the development of knowledge and perceptual capacities. They serve as a guide, indicating the extent to which a person is willing to learn, how ambitious they are in terms of educational achievements, and the level of success they aim to attain. Throughout life, one’s study habits can influence decisions related to the depth of learning, the pursuit of goals, and the determination of future earning potential. In essence, study habits become a crucial factor in shaping an individual’s educational and professional trajectoryTherefore, it is assumed that study habits are correlated with scholastic or academic achievement (Rabia et al., 2017). Therefore, achievement in any form of academic activity is based on study, interpretation, and application. Everyone has different study habits. Often, students perform poorly in school simply because they need good study habits.

In many cases, students need help knowing where to begin. Those high school students who succeed exceptionally well usually study alone and follow a study technique that has been worked out for them and incorporates desirable procedures.

Good health, ample sleep, regular exercise, and a nutritious diet are crucial factors contributing to achieving positive study outcomes. Creating favorable study conditions involves ensuring adequate lighting, maintaining comfortable temperatures, controlling humidity, adopting proper posture, creating optimal physical surroundings, and minimizing emotional disturbances. The interplay between physical well-being and a conducive study environment significantly influences one’s ability to focus, retain information, and perform effectively in academic pursuits (Julius & Evans, 2017).

Another predictor of student’s academic performance in online learning is accessibility. Accessibility means providing flexibility to accommodate each user’s needs and preferences.

Indeed, the Internet has become an indispensable tool in contemporary society, serving as a vital means for accessing information, facilitating communication with others, and supporting a wide range of daily activities. Its pervasive influence has transformed how individuals interact, learn, work, and engage with the world around them. The Internet is also beneficial in terms of online learning. Students attend their synchronous meetings online with the use of gadgets and internet connectivity. Passing requirements, quizzes, and projects are online. If students have proper gadgets and Wi-Fi, it is easier to comply with all their requirements on time.

Due to the growth and spread of cheaper and more user-friendly computer technology and software (e.g., smartphones, portable computers, Microsoft Word, etc.), students’ use of the Internet has increased dramatically. The Internet allows students to widen their academic performance and experience, access important information, and communicate with others within the academic community. Students’ academic attainment depends on their capacity to comprehend, read, and communicate at high levels using Internet technologies. By providing Internet access and enhancing its usage in schools, a chance to improve student’s learning knowledge through access to the vast amount of information that is accessible on the Internet is granted. Since Internet services depend on the power supply as the devices used to provide the services need the power to operate, it is therefore very vital that good infrastructure should be present to enhance Internet services provision, particularly in rural areas where there is insufficient or ultimately no power supply as it will increasingly spread the use of and access to online information (Tarimo. & Kavishe, 2017).

The findings in Table 4 imply that students will likely achieve and maintain good grades in their online learning when they have good study habits. Accessibility to an internet connection has a significant impact on the academic performance of students in online learning.

Table 4 Predictor of Students’ Academic Performance in Online Learning

Dependent Variable: Study Habits and Accessibility

General Weighted Average = 2.921 – 0.2061 A. Study Habits – 0.1114 C. Accessibility

SUMMARY, FINDINGS, CONCLUSIONS, AND RECOMMENDATIONS

Summary

This study explored the predictors of students’ academic performance in online learning. It was participated by 124 Education students selected through stratified sampling technique from the College of Education of Misamis University. The descriptive-correlational design was used to gather all pertinent data and information needed. It utilized the Factors that Affect Student’s Academic Performance in Online Learning questionnaire as the research instrument. Also, the study used the Mean, Standard Deviation, Pearson product-moment correlation coefficient, and Regression analysis as statistical tools.

Findings

The following were the salient findings of the study:

1. The level of perceived factors influencing students’ academic performance in online learning regarding study habits, teacher skills and efforts, accessibility, and parental involvement was high.
2. Students have average performance in online learning based on their general weighted average in the first semester of the school year 2021-2022.
3. Study habits and accessibility were significantly correlated with academic performance.
4. The predictors of students’ academic performance in online learning were study habits and accessibility.

Conclusion

Based on the indicated findings, the following conclusions were drawn:

1. Students demonstrated a high level of engagement in all of the predictors that affect students’ academic performance in online learning, whether negatively or positively.
2. Most of the students experienced difficulty adapting to the new mode of learning in a way that most of the respondents’ grades obtained average scores during the first semester of the school year 2021-2022.
3. Despite all the predictors mentioned, study habits and accessibility significantly impact the academic performance of students in online learning, which implies that how students adapt to the new way of learning and their accessibility to internet connection is very important in terms of their academic performance.
4. Students with good study habits and internet connectivity will likely achieve and maintain good grades in their online learning.

Recommendations

This study revealed education students’ perspectives on the factors that influence students’ academic performance in online learning. Thus, the following recommendations are at this moment presented:

1. Teachers maintain their performance to educate students and help them cope with the predictors that hurt students in online learning through developing positive relationships to assist one another in fulfilling their roles and responsibilities.
2. The teacher implements a discussion about mental health as it affects study habits, active class participation, and hard work.
3. If internet access is not widely available in rural areas, teachers give extensions to pass requirements without deducting more significant points.
4. A similar study must be conducted on a larger group of subjects to determine if the same findings will be established.

REFERENCES

1. Abu Saa, A., Al-Emran, M., & Shaalan, K. (2019). Mining student information system records to predict students’ academic performance. In International conference on advanced machine learning technologies and applications (pp. 229–239). Berlin: Springer.
2. Abuhassna, H., Al-Rahmi, W. M., Yahya, N., Zakaria, M. A. Z. M., Kosnin, A. B. M., & Darwish, M. (2020). Development of a new model on utilizing online learning platforms to improve students’ academic achievements and satisfaction. International Journal of Educational Technology in Higher Education, 17(1), 1–23. https://doi.org/10.1186/S41239- 020-00216-Z
3. Aguilera-Hermida, A. P. (2020). College students’ use and acceptance of emergency online learning due to COVID-19. International Journal of Educational Research Open, 1, 100011.
4. Alam, A. (2020). Challenges and possibilities of online education during Covid-19.
5. Alawamleh, M., Al-Twait, L. M., & Al-Saht, G. R. (2020). The effect of online learning on communication between instructors and students during Covid-19 pandemic. Asian Education and Development Studies.
6. Alea, L. A., Fabrea, M. F., Roldan, R. D. A., & Farooqi, A. Z. (2020). Teachers’ Covid-19 Awareness, distance learning education experiences and perceptions towards institutional readiness and challenges. International Journal of Learning, Teaching and Educational Research, 19(6), 127-144.
7. Alshammari, F., Saguban, R., Pasay-an, E., Altheban, A., & Al-Shammari, L. (2017). Factors affecting the academic performance of student nurses: A cross-sectional study. Journal of Nursing Education and Practice, 8(1), 60.
8. B and Company. (2020). Retrieved from http://b-company.jp/en/online-education-en/. Accessed 17 Oct 2020.
9. Baber, H. (2020). Determinants of students’ perceived learning outcome and satisfaction in online learning during the pandemic of COVID-19. Journal of Education and E-Learning Research, 7(3), 285-292.
10. Bettinger, E. P., Fox, L., Loeb, S., & Taylor, E. S. (2017). Virtual classrooms: How online college courses affect student success. American Economic Review, 107(9), 2855-75.
11. Bickle, M. C., Rucker, R. D., & Burnsed, K. A. (2019). Online learning: Examination of attributes that promote student satisfaction. Online Journal of Distance Learning Administration, 22(1), 1-8.
12. Bignoux, S., & Sund, K., J (2018). Tutoring executive online: What drives perceived quality? Behavior and Information Technology, 37(7), 703 713.
13. Cidral, W. A., Oliveira, T., Di Felice, M., & Aparicio, M. (2018). E-learning success determinants: Brazilian empirical study. Computers & Education, 122, 273–290.
14. Coman, C., Țîru, L. G., Meseșan-Schmitz, L., Stanciu, C., & Bularca, M. C. (2020). Online teaching and learning in higher education during the coronavirus pandemic: Students’ perspective. Sustainability, 12(24), 10367.
15. Duque, R., Isotani, S., Rodriguez, C. L., Lyra, K. T., Jaques, P. A., & Bittencourt, I. I. (2018). Affective states in computersupported collaborative learning: Studying the past to drive the future. Computers & Education, 120, 29–50. https://doi.org/10.1016/J.COMPEDU.2018.01.015
16. Duque, , Isotani, S., Rodriguez, C. L., Lyra, K. T., Jaques, P. A., & Bittencourt, I. I. (2018). Affective states in computersupported collaborative learning: Studying the past to drive the future. Computers & Education, 120, 29–50. https://doi.org/10.1016/J.COMPEDU.2018.01.015
17. Ejubovic, A., & Puška, A. (2019). Impact of Self-Regulated Learning on Academic Performance and Satisfaction of Students in the Online Environment. Knowledge Management & E-Learning, 11(3), 345-363.
18. Gillett-Swan, (2017). The challenges of online learning: Supporting and engaging the isolated learner. Journal of Learning Design, 10(1), 20-30.
19. Gonzalez, T., de la Rubia, M., Hincz, K., Lopez, M.C., .Subirats, L., Fort, S. et al. (2020, 20). Influence of COVID-19 confinement in students’ performance in higher education. https://doi.org/10.35542/osf.io/9zuac
20. Gopal, R., Singh, V., & Aggarwal, A. (2021). Impact of online classes on the satisfaction and performance of students during the pandemic period of COVID 19. Education and Information Technologies, 26(6), 6923-6947.
21. Hamilton, L.S., Grant, D., Kaufman, J.H., Diliberti, M., Schwartz, H.L., Hunter, G.P., Messan Setodji, C., Young, C.J., 2020. COVID-19 and the state of K–12 schools: Results and technical documentation from the spring 2020 American educator panels COVID-19 surveys. RAND Research Report.
22. Hee-Jun, C. (2021). Factors affecting learners’ academic success in online liberal arts courses offered by a traditional korean university. Sustainability, 13(16), 9175. doi:http://dx.doi.org/10.3390/su13169175
23. Hodges, C., Moore, S., Lockee, B., Trust, T., & Bond, A. (2020). The difference between emergency remote teaching and online learning. Educause Review.
24. Horowitz, 2020. Lower-income Parents Most Concerned about their Children Falling behind Amid COVID-19 School Closures https://en.unesco.org/covid19/educationresponse/ [Accessed 8 September 2020]..
25. Julius, , & Evans, A. S. (2015). Study of the relationship between study habits and academic achievement of students: a case of spicer higher secondary school, India. International Journal of Educational Administration and Policy Studies, 7(7), 134-141.
26. Karalis, T. (2020). Planning and evaluation during educational disruption: lessons learned from Covid-19 pandemic for treatment of emergencies in education. European Journal of Education Studies, 7(4), 125-142. http://doi.org/10.5281/zenodo.3789022
27. Kaware, S. S., Gupta, M. K., & Gupta, A. K. (2021). Mobile Phone Educational Applications: Their Importance in Academic Learning During Covid 19 Pandemic. International Journal of Early Childhood Special Education, 13(2).
28. Khanna, D., & Prasad, A. (2020, October). Problems faced by students and teachers during online education due to COVID-19 and how to resolve them. In 2020 6th International Conference on Education and Technology (ICET) (pp. 32-35). IEEE.
29. Maheshwari, G. (2021). Factors affecting students’ intentions to undertake online learning: an empirical study in Vietnam. Education and Information Technologies, 26(6), 6629-6649.
30. Malkus, N., 2020. School districts’ remote-learning plans may widen student achievement gap. EducationNext.
31. Markova, T., Glazkova, I., & Zaborova, E. (2017). Quality issues of online distance learning. Procedia-Social and Behavioral Sciences, 237, 685-691.
32. 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.
33. Motz, B., Quick, J., Schroeder, N., Zook, J., & Gunkel, M. (2019). The validity and utility of activity logs as a measure of student engagement. In S. Hsiao, J. Cunningham, K. McCarthy, & G. Lynch (Eds.), LAK19 Conference: 9th International Conference on Learning Analytics & Knowledge. (pp. 300-309). Association for Computing Machinery. https://doi.org/10.1145/3303772.3303789
34. Muljana, P. S., & Luo, T. (2019). Factors contributing to student retention in online learning and recommended strategies for improvement: A systematic literature review. Journal of Information Technology Education: Research, 18.
35. Mushtaq, I., & Khan, S. N. (2012). Factors affecting students’ academic performance. Global journal of management and business research, 12(9), 17-22.
36. Muthuprasad, T., Aiswarya, S., Aditya, K. S., & Jha, G. K. (2021). Students’ perception and preference for online education in India during COVID-19 pandemic. Social Sciences & Humanities Open, 3(1), 100101.
37. Alalwan, W. M. Al-Rahmi, O. Alfarraj, A. Alzahrani, N. Yahaya and A. M. Al-Rahmi, “Integrated Three Theories to Develop a Model of Factors Affecting Students’ Academic Performance in Higher Education,” in IEEE Access, vol. 7, pp. 98725-98742, 2019, doi: 10.1109/ACCESS.2019.2928142.
38. Oducado, R. M., & Estoque, H. (2021). Online learning in nursing education during the COVID-19 pandemic: Stress, satisfaction, and academic performance. Journal of Nursing Practice, 4(2), 143-153.
39. Onyema, E. M., Eucheria, N. C., Obafemi, F. A., Sen, S., Atonye, F. G., Sharma, A., & Alsayed, A. O. (2020). Impact of Coronavirus pandemic on education. Journal of Education and Practice, 11(13), 108-121.
40. Pajarianto, D. (2020). Study from home in the middle of the COVID-19 pandemic: analysis of religiosity, teacher, and parents support against academic stress.
41. Pajarianto, D. (2020). Study from home in the middle of the COVID-19 pandemic: analysis of religiosity, teacher, and parents support against academic stress.
42. Pei, L., & Wu, H. (2019). Does online learning work better than offline learning in undergraduate medical education? A systematic review and meta-analysis. Medical education online, 24(1), 1666538.
43. Realyvásquez-Vargas, A., Maldonado-Macías, A. A., Arredondo-Soto, K., Baez-Lopez, Y., Carrillo-Gutiérrez, T., & Hernández-Escobedo, G. (2020). The impact of environmental factors on academic performance of university students taking online classes during the COVID-19 pandemic in mexico. Sustainability, 12(21), 9194. doi:http://dx.doi.org/10.3390/su12219194
44. Russell, V. (2020). Language anxiety and the online learner. Foreign Language Annals, 5 3(2), 1-15. https://doi.org/10.1111/flan.12461
45. Selvaraj, A., Radhin, V., Nithin, K. A., Benson, N., & Mathew, A. J. (2021). Effect of pandemic based online education on teaching and learning system. International Journal of Educational Development, 85, 102444.
46. Simamora, R. M. (2020). The Challenges of online learning during the COVID-19 pandemic: An essay analysis of performing arts education students. Studies in Learning and Teaching, 1(2), 86-103.
47. Son, C., Hegde, S., Smith, A., Wang, X., & Sasangohar, F. (2020). Effects of COVID-19 on college students’ mental health in the United States: Interview survey study. Journal of medical internet research, 22(9), e21279.
48. Topor DR, Keane SP, Shelton TL, Calkins SD. Parent involvement and student academic performance: a multiple mediational analysis. J Prev Interv Community. 2010;38(3):183-97. doi: 10.1080/10852352.2010.486297. PMID: 20603757; PMCID: PMC3020099.
49. UNESCO, 2020. Education: From Disruption to Recovery [online] Available at:
50. Wu, Z. (2020). How a top Chinese university is responding to coronavirus. Retrieved from World Economic Forum: https://www.weforum.org/agenda/2020/03/coronavirus-china-the-challenges-ofonline-learning-for-universities/
51. Xu, D., & Xu, Y. (2019). The Promises and Limits of Online Higher Education: Understanding How Distance Education Affects Access, Cost, and Quality. American Enterprise Institute.
52. Yudiawan, A., Sunarso, B., & Sari, F. (2021). Successful Online Learning Factors in COVID-19 Era: Study of Islamic Higher Education in West Papua, Indonesia. International Journal of Evaluation and Research in Education, 10(1), 193-201.
53. YUKSELTURK, E. (2017). An investigation of factors affecting student participation level in an online discussion forum. TOJET : The Turkish Online Journal of Educational Technology, 9(2) Retrieved from https://www.proquest.com/scholarly-journals/investigation-factors-affecting-student/docview/ 1288355554/se-2?accountid=149218
54. Zayet, S., Lepiller, Q., Zahra, H., Royer, P. Y., Toko, L., Gendrin, V., & Klopfenstein, T. (2020). Clinical features of COVID-19 and influenza: a comparative study on Nord Franche-Comte cluster. Microbes and infection, 22(9), 481-488.
55. Zhong, R. (2020, March 17). The coronavirus exposes education’s digital divide. Retrieved from The New York Times: https://www.nytimes.com/2020/03/17/technology/china-schools-coronavirus.htm

APPENDIX A

Questionnaire on

Factors That Affect Students’ Academic Performance in Online Learning

(Adapted from Gopal and Mushtaq, 2020)

Instructions: Below are the factors that affect students’ academic performance in online learning.  Please indicate how these factors affect your academic performance. Please indicate your response by checking the column based on the following scale:

                             5         –       Always           2          –          Seldom

                             4         –       Often              1          –          Never

                             3         –       Sometimes