Students’ perception of online learning amidst the Covid-19 pandemic: A study of junior, senior high school and college students in a remote area

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Abstract

Background: The COVID-19 pandemic has brought about many changes in all sectors of life, especially in the field of education. These changes aim to make the learning process more effective in the pandemic environment. However, it can be challenging, as some students do not give positive responses to these changes, especially those in remote areas. This article aims to identify and report students' perceptions about the effectiveness of online learning during the COVID-19 pandemic in the remote North Tapanuli region of Indonesia.
Methods: In this study, data were obtained using an online survey involving 30 students from three levels of education, namely junior high school, senior high school, and college. They are students who the teacher appoints as class administrators; through them, the teacher communicates about everything—learning activities. So compared to his other friends, they know more about the implementation of online learning during the covid 19 pandemic. In addition, schools in remote areas have fewer students than schools in big cities. So we conclude that this research is considered representative with thirty students as the sample. The data gathered from the survey were analyzed using quantitative descriptive methods.
Results: Results show that online learning is considered less effective by students in remote areas; this happens because communication networks and infrastructure do not adequately support them to follow online learning.
Conclusion: Teachers need to evaluate how to teach as well as re-design models and approaches to be applied in learning. This can be achieved by adjusting to the student’s current situation to generate interest and willingness to learn online.

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Keywords

students' perception, online learning, COVID-19 pandemic

Corresponding Author(s) Senida Harefa (senida.harefa@gmail.com)
Grace Lamudur Arta Sihombing (graceshbg@gmail.com) Corresponding authors: Senida Harefa, Grace Lamudur Arta Sihombing Competing interests: No competing interests were disclosed.

Grant information: Institut Agama Kristen Negeri Tarutung 025-05.2.552755/2020
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Copyright: © 2022 Harefa S and Sihombing GLA. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

How to cite: Harefa S and Sihombing GLA. Students’ perception of online learning amidst the Covid-19 pandemic: A study of junior, senior high school and college students in a remote area [version 2; peer review: 2 approved] . F1000Research 2022, 10:867 (https://doi.org/10.12688/f1000research.52152.2) First published: 27 Aug 2021, 10:867 (https://doi.org/10.12688/f1000research.52152.1) Latest published: 14 Feb 2022, 10:867 (https://doi.org/10.12688/f1000research.52152.2)

Revised Amendments from Version 1

Differences between the old version and the new version of the article:
Abstract : we have added an explanation of the characteristics of the sample in this study. In this study, data were obtained using an online survey involving 30 students from three levels of education, namely junior high school, senior high school, and college. They are students who are appointed by the teacher as class administrators, which acts as a regulator of the class, connecting students and teachers field of study, and through them every teacher to communicate to all the learning activities, such as setting the learning time, record the attendance of students in the classroom, and also reports on student assignments in one class, submitted to the subject teacher through them. They are the ones who know a lot about the implementation of learning during the COVID 19 pandemic, compared to other friends. Schools and students in remote areas are few, not as many as schools and students in big cities, so we conclude that the thirty samples are considered representative of the sample in this study.
Introduction, the author summarizes what was found in the study of students during the pandemic
Literature : The author also adds some literature reviews, to support the research questions discussed in this study.
Results; research results in tabular form, most of which we have deleted, by switching to an explanation of research results.
Discussion: we have added an explanation of the four themes studied, Then added an explanation of the implications that can be drawn from the research findings.
Conclusion: we have also added an explanation to the conclusion, and rearrange the sentence without changing the previous meaning.

Differences between the old version and the new version of the article:
Abstract : we have added an explanation of the characteristics of the sample in this study. In this study, data were obtained using an online survey involving 30 students from three levels of education, namely junior high school, senior high school, and college. They are students who are appointed by the teacher as class administrators, which acts as a regulator of the class, connecting students and teachers field of study, and through them every teacher to communicate to all the learning activities, such as setting the learning time, record the attendance of students in the classroom, and also reports on student assignments in one class, submitted to the subject teacher through them. They are the ones who know a lot about the implementation of learning during the COVID 19 pandemic, compared to other friends. Schools and students in remote areas are few, not as many as schools and students in big cities, so we conclude that the thirty samples are considered representative of the sample in this study.
Introduction, the author summarizes what was found in the study of students during the pandemic
Literature : The author also adds some literature reviews, to support the research questions discussed in this study.
Results; research results in tabular form, most of which we have deleted, by switching to an explanation of research results.
Discussion: we have added an explanation of the four themes studied, Then added an explanation of the implications that can be drawn from the research findings.
Conclusion: we have also added an explanation to the conclusion, and rearrange the sentence without changing the previous meaning.

Introduction

The COVID-19 pandemic has had a major impact on various aspects of peoples’ lives, namely in the economic, socio-cultural, and educational aspects. It is a global problem affecting educational institutions. Since the start of this pandemic, it has caused shock and disruption to students. The pandemic has forced schools to close and lessons that were carried out face-to-face have shifted to the online world. The use of the Internet and many other significant technologies to create materials for educational purposes, educational distribution, and program management constitute online learning (Fry, 2001). All educators are asked to make a transition, due to the closure of school buildings. There is no other choice but to apply online learning; even though many feel unprepared during this transitional period, students must adjust themselves while trying to build meaning amid various challenges related to the pandemic. Even though learning is carried out online, it is hoped that learning outcomes will remain maximal. There is some evidence that online learning can lead to higher student success (Kurucay & Inan, 2017). A great amount of evidence indicates that there is no substantial difference in the efficacy of well-designed online learning relative to well-designed face-to-face learning (Clark, 2007).

However, the reality is not as expected since not all students respond positively to the implementation of online learning. Today, the majority of colleges and universities still face virtual learning difficulties (Talidong & Toquero, 2020). For example, not all educators and students can use e-learning applications, especially those in remote areas. They feel that they are not optimal in learning. During online learning, they deal with several obstacles such as more assignments that make them feel burdened. This happens since teachers or lecturers in charge assign them two or three tasks for every lesson. Additionally, network connection disturbance in rural areas affects their attendance of online learning. Online learning also influences the students’ motivation in doing assignments. Therefore, the objectives of online learning goals are not always achieved effectively. Students who succeed in learning are those who are active and always follow the learning. Parents of students also confirmed that their children were too lazy to learn online. Most of them show unsatisfactory results. For example, performance in learning is decreased compared to face-to-face learning, Some students quit school and do not continue their education. This situation gives a bad picture of the learning attitudes of students.

In Anna Ya Ni’s it is suggested that the use of the video chat software Zoom has the greatest potential to improve classes in order to meet student concerns. Zoom is one of the most frequently used applications in online learning to replace conventional face-to-face classes (Ni, Wart, Medina, Collins, Kimberly, & Pei, 2020). It turns out that technology is used as a tool or media in learning which cannot replace face-to-face interactions between teachers and students (Miller, 2020). The obstacles of online learning in rural areas encourage researchers to conduct this research. Therefore, the objective of this research is to identify the students’ perception of the effectiveness of online learning. The researchers wanted to gain a deep and detailed understanding of students' online learning experiences, Based on the support they gained during the learning process and satisfaction with the learning facilities used. The findings of our research, both strengths and weaknesses, will be valuable inputs for institutions to improve the quality of distance learning by adjusting to the needs and conditions of students in remote areas.

Literature

The development of information and communication technology at this time provides many benefits for human life, so the mastery of such technology is no longer an option but has become a necessity. Through the existence of Internet networks, the use of technology in the educational environment has opened new avenues for educators; face-to-face learning has been transformed into e-learning or online learning (Bernard et al., 2009). In addition to other electronic media, such as CD-ROM, satellite, and television, some experts classify e-learning as ‘education delivered via the Internet’, while online education is described as ‘education delivered only via the Internet or web-based media’ (Lee, 2017). When used interchangeably, online education or e-learning is commonly defined as bridging the space between teachers and students through the use of web-based technology (Ryan & Young, 2015).

The presence of the Internet facilitates human work in many ways, especially in the field of education. The current learning process requires teachers and students to use technology. However, not all students can accept and adapt to these changes. The acceptance of changes in the learning process differs among students. This can be influenced by age, thinking ability, and students’ interest in technology. Students of all ages seem to react differently to the practice of online learning, with older students showing greater appreciation. There are still major variations in how learners view their online interactions during learning (Koohang, Paliszkiewicz, Nord, & Ramim, 2014). There are also concerns about the online learning environment’s efficacy (Hashem, 2011).

Students’motivation in taking online learning can be assessed by how they participate in ongoing learning. Participation in online learning requires three dimensions, namely cognitive participation, emotional participation, and behavioral participation (Fredricks, Blumenfeld, & Paris, 2004). These three dimensions are explained as follows: (1) Cognitive participation is the cognitive effort of a student to acquire skills in the online learning process. (2) Emotional participation is described as students’ positive emotions towards teachers, peers, and online learning. (3) Behavioral participation is participation that is manifested by activities that pay attention to learning when studying online (Jung & Jeongmin, 2018).

Motivation is generated through effective learning. Effective online learning requires effective instructional design and procedures based on the concept of a good education. It will positively impact the instructions if the plan is correct. For example, designing learning must consider the method, flexibility of time, student involvement in activities, and presentation of material (Simonson et al., 2015; Barberà et al., 2016). Variations in teachers' teaching style and their expertise in using technology in interacting with students also significantly affect the Motivation and results of e-learning (Ozkan & Koseler, 2009). Several studies on using technology can change the learning experience and improve student performance, such as posting videos after class and using social media platforms such as Facebook, YouTube, and other e-learning tools. The effect on perceived satisfaction and effectiveness online is when teachers have sufficient and up-to-date knowledge in their area of expertise (Early & Murphy, 2009). The increasing use of technology in online learning benefits students, but the main concern is unstable internet connections in remote areas, not providing comfort in learning (Kulal & Nayak, 2020). Based on the description above, we developed a research instrument from the aspects: Teachers’ methods of online learning, Students’ convenience in online education, Motivation to learn online, and The effectiveness of online learning, to gain a detailed understanding of students’ experiences of online learning during COVID 19.

Methods

An online-based questionnaire study was conducted in a remote area, North Tapanuli, Indonesia. The main objectives of this study were as follows:

Ethics

This research project was approved by the Research Ethics Committee. Ethical Approval Involving Human Respondent from tertiary education (Approval number: 1437.1/Ikn.01/TL.01/09/2020), from junior high school education (Approval number: 086/SMP-SM/IX/2020), and senior high school education, (Approval number: 422.1/063/SMA N 1TRT/2020). Written informed consent from all subjects involved was obtained for participation in the study and subsequent publication.

Data collection

Primary data was collected through an online survey (see Table 1). The survey included 20 items on a four-point Likert scale, from 1 (disagree), 2 (neutral), 3 (agree), 4 (strongly agree). The survey was conducted for over a week. Students were asked to participate in a web-based survey. Of the 75 students surveyed, only 30 students submitted their answers to the online survey, namely 10 students from junior high school education, 10 students from senior high school education and 10 undergraduate students from tertiary education. They are students who are appointed by the teacher as class administrators, which acts as a regulator of the class, connecting students and teachers field of study, and through them every teacher to communicate to all the learning activities, such as setting the learning time, record the attendance of students in the classroom, and also reports on student assignments in one class, submitted to the subject teacher through them. They are the ones who know a lot about the implementation of learning during the Covid 19 pandemic, compared to other friends. Schools and students in remote areas are few, not as many as schools and students in big cities, so we conclude that the thirty samples are considered representative of the sample in this study. In this case, gender demography is an important factor to be analyzed.

Table 1. Frequency of respondent statistics.

No Item 1 2 3 4 N Score Mean % Category
Teacher’s methods in online learning
1 Obtain and find out the teaching materials/learning materials delivered by the teacher/lecturer when studying online. Good 0 0 11 19 30 109 3.63 90.83% Effective
2 Understanding of the material presented by the teacher/lecturer when studying online studied 1 5 18 6 30 89 2.97 74.17% Less effective
3 Can re-describe the material that has been online by the teacher/lecturer on time 2 4 17 7 30 89 2.97 74.17% Less effective
4 Responding to questions that appear in discussion forums of subject matter provided by the teacher/lecturer during online learning 3 5 21 1 30 80 2.67 66.67% Less effective
5 Apply the subject matter delivered by the teacher/lecturer in everyday life 4 5 16 5 30 82 2.73 68.33% Less effective
Students’ convenience in online learning
6 Can communicate smoothly with the teacher/lecturer during online learning 1 2 15 12 30 98 3.27 81.67% Less effective
7 Can ask directly to the teacher/lecturer when I don’t understand the subject matter during online learning 0 3 18 9 30 96 3.20 80.00% Less effective
8 Always get a good response from the teacher/lecturer during online learning 4 3 16 7 30 86 2.87 71.67% Less effective
9 Enjoy doing assignments given by the teacher/lecturer on online learning 4 7 16 3 30 78 2.60 65.00% Less effective
10 Feel comfortable because the teacher/lecturer always understands the obstacles experienced when learning online (for example network barriers and data packets) 1 9 15 5 30 84 2.80 70.00% Less effective
11 Active in following class discussion forums created by the teacher/lecturer during online learning 1 8 16 5 30 85 2.83 70.83% Less effective
Learning Motivation in online learning
12 Always on camera during online learning 2 7 17 4 30 83 2.77 69.17% Less effective
13 Pay attention when teacher/lecturer provides learning explanations during online learning 1 4 22 3 30 87 2.90 72.50% Less effective
14 Participate in discussion group study assignments formed by the teacher/lecturer 2 6 17 5 30 85 2.83 70.83% Less effective
15 Submit assignments given by the teacher/lecturer on time 1 3 16 10 30 95 3.17 79.17% Less effective
16 Learn guidelines about learning online from the internet 1 12 15 3 30 81 2.70 67.50% Less effective
17 Sit calmly during online learning in front of the laptop/cellphone until the time set by the school/teacher/lecturer elapses 0 5 22 3 30 88 2.93 73.33% Less effective
Effective online learning
18 Likes online learning rather than face-to-face learning 0 9 16 5 30 86 2.87 71.67% Less effective
19 The interaction of online teaching and learning is better than face-to-face learning 3 9 15 3 30 78 2.60 65.00% Less effective
20 Online learning facilities always support, both in terms of equipment (for example mobile/laptop) or network. 0 7 14 9 30 92 3.07 76.67% Less effective
Mean 72.96% Less effective

Instrument

Data in this study were collected through the use of questionnaires. Questionnaires consisted of four indicators; 1) Teachers’ methods of online learning; 2) Students’ convenience in online learning; 3) Motivation to learn online; 4) The effectiveness of online learning. Then the indicators were translated into 20 questionnaire items (Table 1).

Statistical analysis

Data were collected, coded, checked for completeness and input into SPSS Version 25 IBM (SPSS Statistics, RRID:SCR_019096). R is an open-source alternative software that can also be used to do the same analysis. Descriptive statistics (frequency, percentage, mean and standard deviation) were used to describe variables. One-way analysis of variance (ANOVA) was used to determine differences in perceptual scores about learning online for junior high school, senior high school, and college students. In all experiments in this report, we applied an alpha level of. 05.

Results

20 questionnaires, which were elaborated on 4 indicators, were used to survey students' experiences in online learning. Based on the results of the calculation of the data obtained, the value of each questionnaire indicator was as follows: The teacher’s method in online learning (score = 89.8; average = 2,992; percentage = 74.83%), student comfort in online learning (score = 87.83; average = 2,928; percentage = 73.19%), learning motivation in online learning (score = 86.5; average = 2.883; percentage = 72.08%), effective online learning (score = 85.33; average = 2.846; percentage =71, 11%). After being calculated, the average percentage score = 72.96%. So, based on the hypothesis H1: p ≥ 85% (effective), H0: p ≤ 85% (less effective) indicates that students’ perceptions towards online learning in remote areas are less effective. The shortcomings are related to Teachers' methods of online learning; Students' convenience in online learning; Motivation to learn online; The effectiveness of online learning. The four indicators must be improved so that students' motivation, performance, and achievement in education can increase optimally (Table 1).

Using the One Way ANOVA test, the researchers aim to figure out the difference in the percentage of perceptions between the three groups of students. The conditions that must be met to process data in a One-way ANOVA test are the data must be normally distributed, and the variance must be homogeneous. After our data were processed, the normality test met the first of these requirements, namely, a significance value of.103 > 0.05 (Shapiro-Wilk) thus the data was declared to be normally distributed.

The second step is to test the homogeneity. Results of the homogeneity of variance test obtained a significance value of.093 > 0.05. Thus, we can be confident that our data distribution was homogeneous.

The output in the descriptive section shows the average value of students’ perceptions about online learning: student at junior high school (mean) = 58.10, student at senior high school (mean) = 55.30 and college student (mean) = 61.70. The highest score stating that online learning is less effective than face-to-face learning is that of college students, n = 30, 95% confidence interval for mean, total min = 48 and max = 73.

The mean scores of each group are different in number, even though the difference is not significant. Meaning that students from the three groups have learning experiences that are not much different in online learning, junior high school, senior high school and college students.

Table 2. Descriptive statistics for variables.

Descriptives
Perception
N Mean Std. deviation Std. error 95% confidence interval for mean Min Max
Lower bound Upper bound
Junior high school 10 58.10 3,814 1206 55.37 60.83 48 61
Senior high school 10 55.30 2,710 .857 53.36 57.24 51 61
College 10 61.70 5,982 1892 57.42 65.98 54 73
Total 30 58.37 5,000 .913 56.50 60.23 48 73

Then, the authors conducted a follow-up ANOVA test using Duncan’s test to determine the perceived significance value between junior high school with senior high school students and senior high school with college students. Duncan’s test results have two subsets, namely in the first subset, the significance value was 0.077 > 0.005 of senior and junior high school students’ perceptions, meaning that their perceptions about online learning are not significantly different. In the second subset, the significance value was 0.165 > 0.05 of senior high school and college students’ perceptions, meaning that their perceptions about online learning were also not significantly different. So, the results of Duncan’s test concluded that there was no significant difference between students’ perceptions of online learning, meaning that they had the same perception (Table 3).

Table 3. Advanced test of ANOVA (perception of Duncan about student perception).

Perception of Duncan
Education level N Subset for alpha = 0.05
1 2
Junior high school 10 55.30
Senior high school 10 58.10 58.10
College 10 61.70
Significant .077 .165

The means of groups in homogeneous subsets are displayed.

Uses harmonic mean sample size = 10,000.

In this study, more male students answered that online learning was less effective than female students. The result of data calculation showed that the frequency of male students’ answers was 66.7%, while the frequency of female students’ answers was 33.3%.

Discussion

The overall mean score obtained in this study p = 72,96% thus (H0:72, 96% ≤ 85%) indicates that students’ perception of online learning in remote areas is that it is less effective than face-to-face learning. The resulting score needs to be improved for the achievement of learning objectives. To enable teaching activities to be carried out at an adequate level, the constraints to be considered are:

Conclusions

The COVID-19 pandemic presents an extraordinary situation worldwide, this situation affects the implementation of learning in schools. Face-to-face teaching and learning interactions turn to the online world. The online learning method's challenges are practical activities that emphasize that effective learning requires designs and procedures based on appropriate education; teachers should not burden students with continuous assignments. Research shows that the failure of students to continue their education online in some cases due to the increased workload caused students to drop out of school (Park & Choi, 2009). To achieve higher levels of academic success, teachers must ensure there is a complete curricular plan that is tailored to goals, avoiding a large number of student burdens that are practically impossible to meet (Oliveira & Magalhães, 2020).

So, educators are expected to redesign implementing procedures for online learning so that students can still learn as much as possible. From the teacher's side, it is hoped that teachers will improve methods of teaching, by designing models and other approaches to provide variation in learning in order to raise students’ interest and willingness to learn online. Furthermore, each institution needs to prepare well for designing interesting learning media, and designing modules that are more flexible, making adjustments such that students adapt to changes in the teaching, learning and assessment, both face-to-face and online (Ansari et al., 2021), And blended learning is an effective teaching model amid pandemics to improve motivation, achievement, and learning performance. However, this is also a call for the government to improve internet networks and infrastructure in remote areas, in order to facilitate online education. The results of this research provide additional insight to all those involved in the implementation of education. However, further research is needed to obtain a more complete explanation.

Data availability

Underlying data

This project contains the following underlying data.

Data are available under the terms of the Creative Commons Zero “No rights reserved” data waiver (CC0 1.0 Public domain dedication).

References

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VERSION 2 PUBLISHED 27 Aug 2021

1 Faculty of Religious Education, Christian Education Management, Institut Agama Kristen Negeri Tarutung, Tarutung, Sumatera Utara, 22758, Indonesia

Senida Harefa
Roles: Conceptualization, Formal Analysis, Methodology, Writing – Original Draft Preparation, Writing – Review & Editing

Grace Lamudur Arta Sihombing
Roles: Conceptualization, Writing – Original Draft Preparation, Writing – Review & Editing

No competing interests were disclosed.

Institut Agama Kristen Negeri Tarutung 025-05.2.552755/2020
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.