Students’ Attitude towards Online Learning: Its Impact to Students’
Problem-Solving Ability
Ariel M. Berico
Don Carlos Polytechnic College, Philippines Arnel S. Travero*
University of Science and Technology of Southern Philippines-Claveria, Philippines [email protected]*
Article Info Abstract
Article History
Received:
21 April 2023
This study assessed the relationship of attitude towards online learning on the problem-solving ability of 2nd year Bachelor of Elementary Education (BEED) students of Don Carlos Polytechnic College. It aimed to describe the level of students’ attitude toward online learning; ascertain the problem-solving ability of the students; correlate students’ problem-solving ability with the attitude toward online learning; and identify which component of attitude towards online learning best impacts and predicts students’
problem-solving ability. A descriptive-correlational research design was used in this study. Mean, correlation and regression analyses were employed. Students were found to have positive attitude towards online learning; however, their problem-solving ability is still very poor. Moreover, there was a significant relationship on students’ attitude towards online learning, specifically on ease-ness in using online learning, on students’ problem-solving ability.
Further, it was revealed that problem-solving ability is predicted by ease-ness in using online learning. Nevertheless, due to the limited scope of this work, the authors felt that there is a need for more extensive research particularly in the effectiveness of online learning to arrive at conclusions that would be more valid, and applicable to a larger student population.
Accepted:
18 June 2023
Keywords: Ease- ness in using online learning, Effectiveness of online learning, Interest in computer and adoption to online learning, Problem Solving Ability
Introduction
As the instruction shifted to online classes or modular, mathematics teaching becomes hard because they need to explain various processes in systematic way for learners to understand both concept and content by displaying the mathematical concepts, problems, and process steps of the solutions (Karal et al., 2013). Here, systematic means a way that problems should be accompanied with figures or illustration to enrich students’ imagination of the problem and logically arranged and presented. Milligan and Littlejohn (2016) demonstrated that students new to online learning had higher rates of reaching goals and persisting to overcome challenges when teacher reinforced organizational skills, goal setting, and orientation to the classroom, and provided consistent academic support.
In fact, the students’ mathematical performance in the Philippines fared worst among 58 countries in an assessment for mathematics in Grade 4 students. Referring to that statement, mathematics performance should be a major concern for teachers. According to Mullis et al.
(2020), Trends in International Mathematics Science Study (TIMSS) 2019 international results in Mathematics placed Philippines at the last rank out of 58 countries. The mentioned study also revealed that only one (1) percent of the Filipino students can apply conceptual understanding to solve problems.
Now, with the advent of virtual modality students' attitudes regarding online learning must also be evaluated, considering that this type of learning does not require students to travel across time zones or locations. At first glance, this type of learning appears to be beneficial to students because they can learn whenever and wherever they choose. Learners can access up-to-date and appropriate instructional materials via the Internet (Songkram et al., 2015) Students’
attitudes are also affected via the excellence and easiness of using course of online learning, usability of online learning, and students’ level and skills in computer (Aixia, 2011). Their computer experiences, which consists apparent self-use, gratification and effectiveness and application of online learning play a dominant role (Liaw, 2011).
Based on observation and interview there are also complains on teachers’ inability to give attention towards their students. Cases like questions post by the students via online classroom are not addressed immediately if not at all. This could be a reason why students are not intrinsically motivated to learn math. This supports that the instructional supervision during this trying time is apparently important that teachers should meet the present challenges of instruction by being consciously aware and connected to their students and their communities, as well as their own inner struggles (Haberlin, 2020). Teachers should be patient as they meditate on how to continually improve instructional outcomes for all students (Mette, 2020).
Furthermore, the success of students in problem solving ability is known to be dependent on their learning in algebraic concepts (Sugiarte & Retnawati, 2019). Students who are weak in algebra are most likely to fail in related areas (Jupri & Drijvers, 2016). Knowing that, George Polya’s problem solving technique is a technique that is studied today and even before and where most of the studies about problem solving is anchored (Yushau et al., 2020). It was used as a guide in adapting problem-solving questions that will contain algebraic concepts.
With these problems, the present study aimed to (1) describe the level of students’ attitude toward online learning in terms of interest in computer, effectiveness of online learning, and ease-ness on the use of online learning; (2) ascertain the problem-solving abilities of the students when classified as understanding the problem, devising a plan, carrying out the plan, and looking back; (3) correlate students’ problem-solving ability with the attitude toward online learning; and (4) identify which component of attitude towards online learning best impacts and predicts students’ problem-solving ability.
Method
Research Design
Descriptive-correlational research design was employed in the study. This design is considered appropriate since the present study investigated student’s attitude toward online learning, and problem-solving ability and show the relationships between these variables and to tell whether or not attitude towards online learning predicts students’ problem-solving ability.
Research Locale and Respondents
The study was conducted at Don Carlos Polytechnic College, a Community College run by the Local Government Unit (LGU) of Don Carlos, Bukidnon, Philippines. Respondents of the study were the 433 second year BEED students who were enrolled in the course Mathematics in the Modern World in the academic year 2021-2022. These BEED students will be the ones to teach the elementary learners in the future; hence, their ability in mathematics, particularly in problem-solving, will be extremely beneficial to students' success in solving math problems, which has been a challenge since then.
Research Instruments
The researchers used survey questionnaires to measure attitude toward online learning, and problem-solving ability. The attitude towards online learning questionnaire with three themes in which theme 1 (Interest in computer and adoption of online learning) contains 7 questions, theme 2 (Effectiveness of online learning) contains 10 questions, and theme 3 (Ease-ness in using online) learning contains 6 questions which was adopted from the study of Ullah et al.
(2017). The questionnaire has a Cronbach’s alpha of 0.7. To measure the given questionnaire, the 5-point Likert scale key below was used. It has positive and negative statement and ranges from 5 to 1 describing from strongly agree, agree, undecided, disagree, and strongly disagree which implies further as highly positive, positive, neutral, negative, and highly negative, respectively. Reverse scoring procedure was applied for negative statements. High score represents high positive attitude.
The problem-solving questionnaire is a thirty-five-item multiple choice questionnaire adopted from the study of Asparin (2012) which was designed from the student’s textbook in Elementary Algebra. It contains three stems: the Stem A and Stem B composed of twelve (12) questions each and eleven (11) questions for Stem C that represents Polya’s problem solving steps.
Scoring Procedure
The participants’ responses on the attitude towards online learning questionnaire will be scored using a scale. The scoring procedure is shown on Table 1.
Table 1. Scoring Procedure
Rating Scale Qualitative Description Interpretation
5 4.50-5.00 Strongly agree Highly positive
4 3.50-4.49 Agree Positive
3 2.50-3.49 Uncertain Neutral
2 1.50-2.49 Disagree Negative
1 1.00-1.49 Strongly disagree Highly Negative
Data Analysis
To present the students’ scores in attitude towards online learning and problem-solving ability, descriptive statistics, specifically mean, was used. Moreover, the study utilized Pearson product moment correlation to determine the relationship of attitude toward online learning
and problem-solving ability. To determine the predictor of student’s problem-solving ability linear regression analysis was carried out.
Results and Discussion
Attitude Towards Online Learning
Students’ attitude towards online learning is shown in the literature to have an effect to students’ mathematics achievement and performance. The present study adapts themes given by Ullah et al. (2017) which are Interest in Computer and Adoption to Online Learning, Effectiveness of online learning and Ease-ness in using online learning. The mean scores of the students in these themes are presented in Tables 1, 2 and 3, respectively.
Table 1. Mean scores of students’ interest in computer and adoption to online learning
Indicators Mean Qualitative
Description
Interpretation 1. Slow computer and poor internet connections
discouraged to use online learning.
1.73 Disagree Negative 2. It is difficult to understand online learning
without getting acquainted with appropriate guidance.
1.97 Disagree Negative
3. It is difficult to favor online learning on regular basis due to least face to face interaction among students and teachers.
1.98 Disagree Negative
4. Online learning is often avoided as it promotes social isolation.
2.45 Disagree Negative 5. Using online learning makes learning
interesting.
3.08 Uncertain Neutral 6. Online learning highly motivates the students
for taking advance courses.
3.26 Uncertain Neutral 7. As a useful program suggested for peers to
utilize online learning for online learning materials.
3.78 Agree Positive
Over-all Mean 3.71 Agree Positive
Table 1 shows that the over-all mean score of 3.71 which means that students show positive interest in computer and adoption to online learning. Also shown in the table is the indicator
“slow computer, and poor internet connections discouraged to use online learning” got the lowest mean score of 1.73, followed by the indicator “it is difficult to understand online learning without getting acquainted with appropriate guidance” with a mean score of 1.97. It means that students disagreed to these indicators. This further means that despite of the challenges of internet connectivity, students did not believe that it will discourage them to adopt online learning which shows that they are still positive towards online learning. This is because most of the students nowadays excel at technology-based communication and independent learning and prefer to take the exam online because of the possibility to take open-book exams in online, though sometimes they are required to visit either the campus or on approved site for proctored test (Why choose online learning: overview for prospective students, 2021).
Apparently, this type of learning appears to be beneficial to students because they can learn whenever and wherever they choose and can access up-to-date and appropriate instructional
materials via the Internet. A positive over-all mean indicated that students believed online learning can be a great help in utilizing online learning materials. Despite of their uncertainties when it comes to their motivation in taking advance courses, they still favor online learning even when it means least face to face interaction.
According to Al-Fahad (2009; as cited by Ullah et al., 2017), this further means that students are not negative on the implementation of online learning. Many students prefer online learning because of its flexibility and self-directed nature, it is ideal for them especially to those who have excellent time management and written communication skills because they can access advanced learning opportunities (PR Newswire, 2020). Furthermore, the study of Peytcheva- Forsyth et al., (2018) presented that students’ have stated positive attitudes towards online distance learning, which implies that they are more likely to accept it well as a mode of education. It can be concluded that the poor internet connections and online support by the teacher (Struyven et al. as cited by Ismaili 2021) did not affect their demonstration of willingness towards online learning.
Table 2. Mean scores on effectiveness of online learning
Indicators Mean Qualitative
Description
Interpretation 1. Students and teachers’ interaction is weak
through online learning.
2.18 Disagree Negative 2. Several problems were created by online
learning rather than its solution.
2.47 Disagree Negative 3. Access to education increases through online
learning.
3.26 Uncertain Neutral 4. Online learning offers maximum engagement
of students.
3.30 Uncertain Neutral 5. Productivity of students can be enhanced
through online learning to strengthen educational concepts.
3.31 Uncertain Neutral
6. Quality of teaching and learning can be increased through Online learning because it integrates various types of media.
3.32 Uncertain Neutral
7. Online learning ensures the effectiveness for presenting the work in class.
3.34 Uncertain Neutral 8. Online learning ensures the effectiveness in
terms of coping up with missed lectures.
3.58 Agree Positive
9. Online learning is economic in terms of time for students and teachers.
3.59 Agree Positive
10. The usability and expertise in computer ensure the effectiveness in computer mediated learning.
3.61 Agree Positive
Over-all Mean 3.47 Uncertain Neutral
Table 2 shows that the over-all mean score of the effectiveness of online learning is 3.47, which indicates that BEED students cannot decide whether online learning is indeed effective. The reason why students are uncertain on the effectiveness of online learning is because they are not sure of the effectiveness of presenting their work online probably because most students lack gadgets to use for online. They do not also see the effectiveness of integrating of various
types of media in learning because they have not explored the full potential of the gadgets since they do not own one or if they have, it cannot handle some of the applications which are beneficial in online learning, given that not all gadgets have the same capacity.
The students cannot also say that it enhances their productivity and that they are actively engaged in learning. This is otherwise true based on observation. Students are expected to do the schoolwork and at the same time they also need to help with household chores most of the time, if not the entire day. The negative attitudes of students towards online learning were identified with low level of computer skills, technological anxiety, and computer hardware problems, as well as poor study skills, low motivation, and an inability to work independently (Ullah et al., 2017). Being uncertain on its accessibility to provide education, student engagement, strengthening educational ideas and the efficiency of work presentation, students’
positive attitude towards online learning on its effectiveness in terms of coping up with missed lectures, its economic advantages and usability are still worthy to note.
The result of the study contradicts to the study of Yang (2006; as cited by Ullah et al., 2017) which found positive attitudes of students toward online learning because of the feasibility and new ways of learning. It also contradicts to the study of Kirkwood (2003; as cited by Ullah et al., 2017) which showed strongly positive student’s attitude regarding the application of multimedia technologies in online learning.
Table 3. Mean scores on ease-ness in using online learning
Indicators Mean Qualitative
Description
Interpretation 1. Learning of courses through online portal is
difficult.
2.13 Disagree Negative 2. It is easy to read from print learning materials
instead of electronic medium or internet.
2.32 Disagree Negative 3. Acquisition of significant information is
difficult through using internet.
2.41 Disagree Negative 4. Use of online learning is easier and better than
using books/journals in the library.
3.07 Uncertain Neutral 5. It is easy to become skillful at using online
learning system.
3.17 Uncertain Neutral 6. For searching online educational resources, the
web is often student friendly.
3.78 Agree Positive
Over-all Mean 3.52 Agree Positive
Table 3 shows that the over-all mean score of students’ ease-ness in using online learning is 3.52, which means that most of the students are positive towards it. The result is greatly influenced by the students’ perception that learning through online portal is not difficult.
Students also believed that it is not hard to look for educational resources online especially in mathematics. Students equipped with digital literacy which is the ability to navigate, evaluate, and communicate information online or in a digital format through digital technologies will have a positive learning attitude in mathematics. Thus, digital literacy can increase the level of learning attitude of students towards Mathematics (Alag et al., 2021). It is also crucial to note that this study also reported that students prefer to use digital resources compared to printed ones. This is because digital resources are readily accessible any time which makes it more convenient (Songkram et al., 2015) than bringing hardbound material.
The table also presents that students are uncertain whether the “Use of online learning is easier and better than using books/journals in the library” which has a mean of 3.07. This means, that students are more into convenient learning. They prefer materials that are easily accessible and not limited to any one place or time. Finding examples is also easy and different types of online calculator are available online, which can be of great help especially if you want to validate the answer to a given problem. The result of the study is in line with the findings of Songkram et al. (2015). Accordingly, despite the limitations of online learning at first, students gain greatly from the autonomy and flexibility it provides.
Summary of mean scores of students’ attitude toward online learning
Table 4. Summary of mean scores of students’ attitude toward online learning
Indicators Mean Qualitative
Description
Interpretation Interest in computer and adoption to online learning 3.71 Agree Positive
Effectiveness of online learning 3.47 Uncertain Neutral
Ease-ness in using online learning 3.52 Agree Positive
Over-all mean 3.56 Agree Positive
Table 4 shows that among the three (3) indicators, the indicator “Interest in computer and adoption to online learning” has the highest mean of 3.71 followed by the indicator “Ease-ness in using online learning” which has a mean score of 3.52 and lastly the indicator “Effectiveness of online learning” has the lowest mean score of 3.47. The over-all mean score of students’
attitudes toward online learning is 3.56 which can be interpreted as positive. This means that the 2nd year BEED students of Don Carlos Polytechnic College, Don Carlos, Bukidnon had positive attitude towards online learning with an overall mean score of 3.56.
The results of this study showed that generally, the students are positive in the implementation of online learning. However, problems such as poor internet connectivity and peer influences hindered the flow of the teaching-learning process. With these concerns regarding online learning, schools should develop a consistent strategy for implementing it, namely, providing a solid internet connection to teachers and collaborating with other stakeholders to support learners' requirements in engaging in online classes.
The result confirms the study of Al-Fahad (2009; as cited by Ullah et al., 2017) which stated that students extensively accepted online learning because it makes it easy for them to search, gain and work independently on learning materials and resources.
Problem Solving Ability
Table 5. Mean scores of students’ problem-solving ability
Indicators Mean Percentage Qualitative Description
Understanding the problem 46.86 Very poor
Looking back 37.50 Very poor
Devising a plan 26.74 Very poor
Carrying out the plan 22.22 Very poor
Over-all mean 46.86 Very poor
Legend:
Score Qualitative Description
87.51-100 Very Good
75.01-87.50 Good
62.51-75.00 Fair
50.01-62.50 Poor
50.00 and below Very Poor
George Polya’s problem solving technique is the most used techniques that is studied today and even before is proven effective by the study of Yushau et al (2020). It is where most of the studies about problem solving is anchored. The said technique uses four-step process for problem-solving namely, understand the problem, devise a plan, carry out the plan and look back.
Table 5 shows the mean scores of students’ problem-solving ability. Understanding the problem has a mean percentage of 46.86; devising a plan has 26.74; carrying out the plan has 22.22; and looking back has 37.5. All of these steps have a qualitative description of very poor.
This result is consistent to the study of Asparin (2012) which showed that the students’ ability to understand the problem, devise a plan, carry out a plan and looking back were all very poor.
This revealed that it means that they don’t have the mathematical skills to solve the problem even with the problem situations. Students’ inability to translate mathematical words to mathematical symbols usually causes their failure to solve the problem (ibid). To address this problem, students have to read the problems carefully for them to easily understand it. They need to restate the problem such that it will be easier to solve (ibid).
Correlation and Regression Analysis of the Variables Involved
Table 6. Correlation of students’ problem-solving ability with their attitude toward online learning
Indicators Coefficient of Correlation (r) Probability
Interest in computer -.078 .053
Effectiveness of online learning .035 .232
Ease-ness in using online learning -.125 .005*
As portrayed in Table 6, among the three components on attitude towards online learning, ease- ness is found to have a significant relationship with problem solving ability.
Table 7: Regression analysis showing the extent of influence of predictor variables on problem solving ability
Indicators
Unstandardized Coefficients
Standardized Coefficients
t Sig.
B Std. Error Beta
(Constant) 15.406 1.979 7.785 .000*
Interest -.110 .090 -.066 -1.215 .225
Effectiveness .102 .054 .099 1.884 .060
Ease-ness -.229 .094 -.128 -2.432 .015*
R = 0.157 R2 = 0.025 F = 3.606 Sig 0.013
From Table 7, the linear regression equation in predicting problem solving ability is given by the equation 𝑦̂ = 𝟏𝟓. 𝟒𝟏 − 𝟎. 𝟐𝟑 𝑥1 where 𝑦̂ = problem solving and 𝑥1 = ease-ness. This
model is fit with 0.013. Moreover, from the table, it can be gleamed that ease-ness best impacts and predicts students’ problem-solving ability.
Despite the limitation of online learning, it provides convenience to learning, allowing the students gain autonomy and flexibility (Songkram et al., 2015). Students accept online learning since it easy for them to search on learning materials and work independently (Al-Fahad, 2009;
as cited by Ullah et al., 2017). Learning through online portal with ease-ness in navigating the portal shows students’ digital literacy. This leads to them having positive learning attitude towards mathematics; thereby, making digital literacy a key factor that increases students’
positive attitude towards Math (Alag, et al., 2021). This positive attitude in turn impacts their problem-solving ability.
Conclusion
Based on the results of the survey, the following conclusions were drawn. First, the level of students’ attitude toward online learning in terms of interest, and ease-ness is positive while it is neutral in terms of effectiveness. However, the over-all students’ attitudes toward online learning is positive. Second, students’ level of problem-solving ability is very poor in terms of understanding the problem, devising a plan, carrying out a plan, and looking back. Clearly, students’ problem-solving ability is very poor. Moreover, there is a significant relationship on students’ attitude towards online learning, specifically on ease-ness in using online learning on students’ problem-solving ability. Lastly, it was shown that ease-ness in using online learning impacts and predicts students’ problem-solving ability.
Recommendations
The results and findings of the survey led to some recommendations for further research and action. First, teacher may use strategies such as blended learning which is already proven effective in teaching mathematics to engage students’ positive attitudes towards online learning. However, due to the limited scope of this work, the author felt that there is need for more extensive research particularly in the effectiveness of online learning to arrive at conclusions that would be more valid, and applicable to a larger student population. Second, curriculum planners and teachers may consider using a problem-based learning model in formulating teaching materials in the form of a student activity sheet that can be utilized for effective learning in mathematics. Furthermore, another thorough research could be done like the study where face-to-face survey can be considered and conducted. Since the outbreak of COVID-19 limits the data gathering of the study into online survey form only, this face-to-face survey may lead to more plausible results which will possibly identify more interesting and significant recommendations.
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Authors Information
Ariel M. Berico
Don Carlos Polytechnic College Don Carlos, Bukidnon
Contact:
E-mail Address: [email protected]
Arnel S. Travero
University of Science and Technology of Southern Philippines-Claveria
Claveria, Misamis Oriental [email protected]
Biography of the First Author
Ariel M. Berico graduated Master of Science in Mathematics Education from Central Mindanao University and is currently taking a PhD in Mathematics Education in University of Science Mindanao. Mr. Berico is a topnotcher of the Licensure Examination for Teachers in 2017. His research interests include Mathematical Modelling and Mathematics Education. As of this writing, he serves as an Instructor and Senior High School in-charge of Don Carlos Polytechnic College.
Biography of the Second Author
Arnel S. Travero is a graduate of Master of Science in Teaching Mathematics from University of Science and Technology of Southern Philippines (USTP). His research interests include Educational studies, Social Science researches and Classroom-Based Action Researches. He is currently working as a Mathematics instructor at USTP- Claveria.
