International Journal of Education and Pedagogy (IJEAP) eISSN: 2682-8464 | Vol. 4 No. 3 [September 2022]
Journal website: http://myjms.mohe.gov.my/index.php/ijeap
WHAT MATTERS THE UPPER SECONDARY SCHOOL STUDENTS IN LEARNING MATHEMATICS-RELATED SUBJECTS DURING THE COVID-19 PANDEMIC ERA?
Chee Loong Lee1, Yoke Chin Kuah2, Wai Kwan Lau3, Nurullashkeen Mohd Anis4 and Chooi Yi Wei5*
1 2 3 5 Faculty Business and Finance, University Tunku Abdul Rahman, Kampar, MALAYSIA
4 Faculty of Arts and Social Science, University Tunku Abdul Rahman, Kampar, MALAYSIA
*Corresponding author: [email protected]
Article Information:
Article history:
Received date : 18 July 2022 Revised date : 25 August 2022 Accepted date : 1 September 2022 Published date : 10 September 2022
To cite this document:
Lee, C. L., Kuah, Y. C., Lau, W. K., Mohd Anis, N., & Wei, C. Y. (2022).
WHAT MATTERS THE UPPER
SECONDARY SCHOOL STUDENTS IN LEARNING MATHEMATICS-
RELATED SUBJECTS DURING THE COVID-19 PANDEMIC ERA?.
International Journal of Education and Pedagogy, 4(3), 154-164.
Abstract: Traditional face-to-face teaching and learning mode was stopped during COVID-19; online teaching and learning is the only feasible mode to continue schooling.
However, it is a sudden and new challenge for students, especially for mathematics-related subjects that involve the mass of calculation and hands-on practices. This study takes the first step in carrying out a preliminary needs analysis to identify the needs of students in learning mathematics- related subjects online. The respondents of this study comprised 431 Malaysian upper secondary students. The findings reported that learning support is the most significant factor affecting students’ learning of mathematics-related subjects, while math anxiety was the minor factor. Thus, educators and policymakers should improve learning support to promote smooth and polished online learning in mathematics-related subjects.
Keywords: Upper secondary school; Online learning;
Mathematics-related subjects; COVID-19 Pandemic.
1. Introduction
Since end of 2019 until present, the world has been affected by the Coronavirus (COVID-19) spread and World Health Organization has declared this scenario as pandemic. The whole world is suffering from the COVID-19 pandemic and Malaysia is no exception. Therefore, Malaysia Government announced Movement Control Order (MCO) in March 2020 in order to minimize transmission of this virus and break the chain of the COVID-19 infection. This unexpected situation has a significant impact on education sector in Malaysia. Although the schools and learning institutions have been closed due to MCO, yet the teaching and learning process is still on going.
In order to resume learning process for students, education institutions start Online Teaching and Learning (OTL) mode. It has been more than a year since the implementation of OTL with Home- based Teaching & Learning1.0 implemented fully online in March 2020 and Home-based Teaching
& Learning 2.0 in November 2020 with various learning methods apart from online method. The Education Ministry announced that the OTL sessions would continue after taking the current Covid- 19 situation into account. It is a new normal in teaching and learning and is deemed as an effective model to create more flexible educational practices in the future. Whether learning has taken place during the OTL or not has been the concern of parents, students and of course the educators. This is due to the problems and challenges faced such as internet connectivity, availability of IT gadgets, delivery of lesson, classroom management and readiness of students and educators.
The main issue here is the unknown requirement that is demanded from the educators and students;
what is really needed from the students in their learning? The answer for this question may enlighten their direction in this journey of OTL and to ensure that learning does take place. It could also function as a suggestion for the improvement of OTL. The study may assist the teachers in ensuring teaching does happen which will ensure that learning takes place. This study will look at the OTL of mathematics-related subjects in secondary schools in Malaysia. Questionnaires were distributed to upper secondary students in Malaysia via Google Forms and collected 431 responses. The study aims to investigate the need analysis of five factors that affect OTL namely, teaching practices, platform/facilities, learning support, Maths’ anxiety and self-confidence. This new data and novel findings would contribute to finding the gaps of implementation of OTL and hence, provide solutions to the gap such as creating a module to address the issue.
This study is organized as follows. Section 2 reviews the literature related to the factors that affect OTL performance. Section 3 describes the data and discusses the methodology. Section 4 discusses the results. Finally, the last section presents a conclusion.
2. Literature Review
The effects of the COVID-19 pandemic have affected all educational activities in Malaysia. Web- based and online learning platforms have exploded in popularity because of the lack of other options.
Online learning, on the other hand, has several drawbacks. As the key measure of online learning preparedness, students must have access to technology (Rasheed et al., 2020). Meanwhile, Favale et al. (2020) discovered that poor internet access was the primary factor affecting students’ online learning behavior at an Italian institution. Instructors may require extra time to create successful material delivery since students will more likely face adapting and technical difficulties (AJ &
Vijayalakshmi, 2019). Besides, interaction is an important component of effective online learning, as it has a favorable influence on learning (Ha & Im, 2020). Thus, instructors must use online electronic communication systems that allow for teacher-student engagement (Kamal et al., 2020). According to Boelens et al. (2017), successful designs and digital education emphasize student-driven learning and interactivity. Interaction serves both social and cognitive purposes.
Blended learning is crucial for open and remote education, especially when the pandemic spreads. A good instructional design is also required for a smooth transition to online learning, ensuring that students do not fall behind in their studies (Volungevičienė et al., 2020). As a result, educators and instructors must stay current on learning and tool theories in order to meet the demands of their students. Hence, online cloud-based solutions like Google Drive and Zoom Cloud Meeting are now vital to accommodate a varied and geographically dispersed group of learners from across the world (Kamal et al., 2020). In addition, numerous learning and teaching techniques were also implemented, including live video conferences (Microsoft Teams, Zoom, Youtube), pre-recorded lecture films (Youtube), and social media (Telegram, Whatsapp, Facebook) (Kamal et al., 2020). Perienen (2020) studies teachers’ perspectives by adopting ICT in teaching mathematics and finds that students understand the subject more appropriately and effectively when technology is integrated. Cullen et al. (2020) also point out that using technology into mathematics classes boost learning. Borge &
Mercier (2019) discovered that adopting numerous tactics to assist students in discussing, participating, sharing and contributing is much more crucial when they are not in touch physically.
During the Covid-19 pandemic, most physical classes shifted to online classes suddenly. It was found that school management and teacher lack readiness for online classes and providing learning support to students (Martin et al., 2019). Kelly (2014) points out that learning support is vital to letting students not to feel alone and building up confidence in their school and teachers. More recent attention to learning support has focused on the online learning support roles (OLSR); according to Nacu et al. (2018), teachers play as encouragers and instructors; they provide formal assessments such as grades, ratings, and badges to encourage students to study hard. They teach, monitor, and guide students to think and understand the related concept and skills. Next, students make friends and support together and form learning brokers that connect each other with various learning opportunities. Finally, parents are the resource provider and learning promoters. They prepare study spaces, devices, and guides for their children to support online learning. Redmond et al. (2018) suggest that learning support is the critical competency of online teaching and learning. Together, these studies indicate that learning support from teachers, students, and parents is a vital factor in online learning.
Stress and anxiety have been identified as significant challenges in teaching math-related subjects (Bradstreet, 1996). The feeling of fear, tension, and apprehension when learning and doing math exercises cab be described as math anxiety (Ashcraft, 2002). Pizzie and Kraemer (2017) replenished that math anxiety is one type of phobia that creates behavioral disengagement bias when exposed to math stimuli. Although Dowker et al. (2016) argue that a person without any math anxiety can be poor at math, it is well known that math anxiety has a negative influence on math achievement (Ma, 1999; Skagerlund et al., 2019). It is because math learning is highly dependent on working memory (Lefevre et al., 2005; Lemaire et al., 1996), and the math anxiety erodes the working memory that controls, regulates, and maintains relevant information in math learning (Engle, 2002; Miyake &
Shah, 2005). Furthermore, the online burden, such as connection problems and weak interactions with teachers and friends, has made matters worse, Ramirez et al. (2018) argue that online burden amplifies the math anxiety and affects a person’s ability to learn math. In all the studies reviewed here, math anxiety is a significant challenge in teaching and learning math-related subjects, especially in online classes.
Self-confidence is a vital feature in overcoming stress and anxiety in learning, especially in math- related subjects requiring a high working memory level. Self-confidence is the capability to understand own weaknesses and limitations and react appropriately to overcome these (Hendrian et al., 2018; Jerald & Me, 2020). Students with self-confidence enjoy showing off, daring to appear in front of the class, telling stories, and answering questions (Han et al., 2015; Hendriana et al., 2018;
Kavenuke et al., 2020). Ardianti et al. (2021) claim that self-confidence is not an innate ability. It requires support from family members, friends, instructors, and the environment. Training students to expoxe themselves and dare to ask can be done through group activities. Letting the students to discuss and present together can reduce their anxiety and foster self-confidence (Hendriana et al., 2018; PharmD et al., 2020). Moreover, instructors should provide positive words and feedback to ensure students do not feel inferior to others and can be more confident (Muppudathi, 2014; Pandey
& Kurian, 2016). These studies indicate that self-confidence is critical for students to learn effectively.
3. Methodology
This quantitative study aims to conduct a preliminary needs analysis learning mathematics related subject among Malaysian upper secondary school students. The contexts to be researched include teaching practice, facilities, learning support, math anxiety and self-confidence.
3.1 Population and Sample Size
The upper secondary school students of Form 4 and Form 6 are those involved in learning mathematical related subjects such as Mathematics, Additional Mathematics, Physics, Engineering, Science, Accounting, Economics. Quota sampling technique will be employed to select the respondents based on 5 regions in Malaysia namely Northern, Central, East Coast, South and East Malaysia.
3.2 Questionnaire Development
A total of 32 items ranged in 5-likert scale has been developed through the review of relevant past studies. The questionnaire developed in English language and translated into Malay and Chinese language to cater the respondents from public secondary school, Chinese independent High School and International Schools in Malaysia. Questionnaire has undergone expert validation by 2 academicians from curriculum and assessment area and education field. Thereafter, pilot test has been performed among 33 respondents from few secondary schools of public secondary school, Chinese independent High School and International Schools. Reliability test measured by Cronbach Alpha value indicated 0.879. Hence, all the items in the questionnaire have fulfilled the rules of thumb of reliability analysis and the same questionnaire is being employed for the actual data collection.
3.3 Data Collection and Data Analysis
Questionnaire has been sent out via Google form link to the respondents during the period of complying with social distancing and strict restriction of entering the school in person. The survey link available in three languages (English, Bahasa Malaysia and Chinese) distributed to respondents via various method such as WhatsApp and snowball method from one to another. A total of 431 set data has been successfully collected within 2 months. The data obtained has been transferred to Statistical package for Social Science (SPSS) version 25 for statistical analysis of respondent’s profile, score mean and standard deviation. The statistical results will be discussed in the next subtopic.
4. Results and Discussion
Respondent’s profile is presented in Table 1 as follows. There were 431 responses being reported descriptively. Respondents involved in this study are from all states of Malaysia. Majority of the students from the East Coast region (Pahang, Terengganu and Kelantan) n = 156, 36.20%, followed by the respondents from Central region (Selangor, WP Kuala Lumpur, and WP Putrajaya) n = 108, 25.06%. A total of 250 female (58%) respondents and balance of 181 male (42%) respondents.
Majority respondents are the Form 4’s students (n = 356, 82.6%) and the remaining of 75 respondents (17.4%) are the Form 6 students. Majority of the schools are located at urban area (n = 318, 73.78%) such as city and town area with strong (n = 144, 33.41%) and average speed (n = 262, 60.79%) of internet connection. Rural areas include small town in the area located far from town mainly in Sabah and Sarawak with poor internet connection as well. Respondents are mostly Chinese (n= 280, 64.97%) followed by Malay (n = 95, 22.04%) and others (n = 49, 11.37%) which consists of Bajau, Iban and Kadazan from East Malaysia. Most of the respondents are from public secondary schools (government subsidized school) (n = 393, 91.18%) and 38 respondents (8.82%) are from private secondary school namely Chinese Independent High Schools and international schools In Malaysia.
Table 1: Respondents Profile
Item Description Frequency Percentage
Region North 41 9.51
Central 108 25.06
South 52 12.06
East Coast 156 36.20
East Malaysia 74 17.17
TOTAL 431 100
Gender Male 181 42.0
Female 250 58.0
TOTAL 431 100
Level of Study
Form 4 356 82.6
Form 6 75 17.4
TOTAL 431 100
School’s location
Urban 318 73.78
Sub-urban 34 7.89
Rural 79 18.33
TOTAL 431 100
Speed of internet connection
Strong 144 33.41
Average 262 60.79
Poor 25 5.8
TOTAL 431 100
Ethnicity Malay 95 22.04
Chinese 280 64.97
Indian 7 1.62
Other 49 11.37
TOTAL 431 100
Type of school
Public secondary school
393 91.18
Private secondary school
38 8.82
TOTAL 431 100
Source: Developed for research
As shown in Table 2, there are 5 constructs being examined to determine the upper secondary school student’s need towards learning mathematics related subjects during pandemic era. The constructs namely teaching practice (TP), facilities (F), learning support (LS), math anxiety (MA) and self- confidence (SC). Learning support (LS) is found to be most significant concern for the students (μ = 4.1213, SD = .7460) learning mathematics related subjects such as accounting, science, economics, mathematics, and additional mathematics. Next, teaching practice (TP) (μ = 3.9791, SD = .8196) employed by their teachers for the lesson and class activities during the class as the secondary concerned element to the students. Meanwhile, math anxiety (MA) is found to be the least (μ = 3.3067, SD = 1.0106) concerned factor to the students. This indicates that majority students are with positive feeling towards learning mathematics related subjects.
Table 2: Mean and Standard Deviation Based on Constructs
Source: Developed for research
Table 3 illustrates the mean and standard deviation for each item under the constructs respectively.
Construct N Mean (μ) Standard Deviation
(SD)
Teaching practice (TP) 431 3.9791 .8196
Facilities (F) 431 3.9451 .8507
Learning Support (LS) 431 4.1213 .7460
Math Anxiety (MA) 431 3.3067 1.0106
Self-confidence (SC) 431 3.6187 .8114
Teaching practice (TP). Majority respondents agreed that their teacher provides adequate teaching material for online mathematics related subject (Item TP4) ( μ = 4.17, SD = .976) followed by their teacher is updated with technologies in teaching (item TP 2) ( μ = 4.17, SD = .976). However, the students claimed that their teacher are not really into educational games during the teaching of mathematics related subject (item TP 6) ( μ = 3.59, SD = 1.278).
Facilities (F). Majority students can read their teacher's writing on online platform (item F3) such as Google Meet and Zoom. These online platforms have been widely used during the emergency remote learning due to MCO implemented by government. Throughout these 2 years of online learning period, the teachers have applied various online features such as screen sharing, video conferencing, chat, whiteboard, and file sharing features on the online platform (item F5) for better communication with the students ( μ = 4.12, SD = 1.019).
Learning support (LS). Majority parents provide devices (laptop and smart phone) (item LS6) ( μ = 4.30, SD = .936). The parents also provide a comfortable learning environment for their children to learn from home (item LS7) ( μ = 4.16, SD = 1.022). Meanwhile, students feel comfortable communicating with their friends via online platform and device without meeting their friends in person (item LS1) ( μ = 4.19, SD = 1.023).
Math anxiety (MA). Less than 25% of the students have bouts of unexplained crying when being given a lot of difficult mathematics questions that must be submitted the next day (item MA5) ( μ = 2.82, SD = 1.518). This indicates that students are able to cope with their online learning in mathematics related subject regardless of the learning environment during pandemic era.
Self-confidence (SC). Approximately 65% of the students are dare to express their opinions during group discussion via online platform (item SC1) ( μ = 3.86, SD = 1.111). However, they are not comfortable turning on the camera during online classes (item SC4). Hence the mean of the said item at low score relative to other items under the construct of self-confidence ( μ = 2.94, SD = 1.414).
Table 3: Mean and Standard Deviation Based on Items
Construct Code Items Mean (μ) Standard
Deviation (SD) Teaching practice
(TP)
TP1 My teacher uses mathematics software to teach me.
3.99 1.078
TP2 My teacher is updated with technologies in teaching.
4.09 .969
TP3 My teacher uses audio, video, text, simulations to enhance my learning ability.
3.97 1.059
TP4 My teacher provides adequate teaching material for online mathematics related subject.
4.17 .976
TP5 My teacher uses various methods to make me participate during online mathematics related subject.
4.00 1.055
TP6 My teacher applies educational games 3.59 1.278
to teach mathematics related subject.
TP7 My teacher is able to ensure smooth learning process.
4.04 1.012
Facilities (F) F1 I am able to access the recorded videos for online classes anytime.
3.85 1.183
F2 I am able to access online learning platform (Google meet & Zoom) anywhere.
3.91 1.203
F3 I am able to read my teacher's writing on online platform.
4.12 1.019
F4 My teacher uses online statistical software (graphing and calculation) to teach mathematic related subject.
3.83 1.186
F5 My teacher uses online features (such as screen sharing, video conferencing, chat, whiteboard, and file sharing features) for better communication.
4.12 1.019
F6 I feel comfortable attending online classes.
3.85 1.157
Learning Support (LS)
LS1 I feel at ease communicating with my friends.
4.19 1.023
LS2 I am able to obtain full cooperation with my friends during group discussions.
4.11 1.005
LS3 My teacher provides clear explanations of homework to me.
4.00 1.066
LS4 Immediate feedback from my teacher motivates me to do more practices with the course material.
4.01 1.073
LS5 My teacher shares various useful online links as additional learning materials.
4.09 1.018
LS6 My parents provide devices (laptop and smart phone) to support my learning.
4.30 .936
LS7 My parents provide comfortable environment for my study at home.
4.16 1.022
Math Anxiety (MA)
MA1 I feel nervous a day before mathematics test.
3.75 1.299
MA2 I feel tired having to complete homework on my own.
3.49 1.339
MA3 I struggle to concentrate on mathematics lessons.
3.16 1.410
MA4 I feel uneasy when the teacher announces a mathematics quiz.
3.33 1.302
MA5 I have bouts of unexplained crying when being given a lot of difficult mathematic questions that must be submitted the next day.
2.82 1.518
MA6 I feel that lack of explanation creates 3.32 1.285
confusion in understanding mathematics concept.
Self-confidence (SC)
SC1 I dare to express my opinions during group discussion.
3.86 1.111
SC2 I volunteer to work on assignments or questions on the online learning platform
3.71 1.150
SC3 I am able to provide strong arguments to defend my opinion or answer.
3.76 1.076
SC4 I felt comfortable turning on the camera during online classes.
2.94 1.414
SC5 I am able to try new things to learn mathematics related subject.
3.81 1.045
SC6 I spend less time studying when there is no homework assigned to me.
3.73 1.178
Source: Developed for research
5. Conclusion
The global disruption by Coronavirus disease (COVID-19 caused by a newly discovered coronavirus (Word Health Organization, 2020) has severely affected the economy sector of very nation in this world, including the higher education sector. To resume learning process for students, education institutions start Online Teaching and Learning (OTL) mode. The objective of this study is conducting a preliminary needs analysis learning mathematics related subject among Malaysian upper secondary school (form 4 and form 6) students. The contexts to be researched include teaching practice, facilities, learning support, math anxiety and self-confidence. Mathematical related subjects such as Mathematics, Additional Mathematic, Physic, Engineering, Science, Accounting, Economics. A total of 431 responses were collected and statistical analysis of respondents’ profiles, score mean, and standard deviation has been used for identifying the needs of students in studying math-related subjects in online mode. Major findings are learning support is the most significant factor affected student’s learning mathematics, while math anxiety (MA) is found to be the least significant factor.
However, the finding from the studies also support that majority of student have positive feeling toward learning during MCO pandemic period.
References
AJ, S. L., & Vijayalakshmi, M. (2019). How Cloud Frameworks Support Blended Learning Environments. In Emerging Techniques and Applications for Blended Learning in K-20 Classrooms (pp. (pp. 114-136)). IGI Global.
Ardianti, S. D., Wanabuliandari, S., & Wijayanti, E. (2021). Need Analysis of “Si Eco” Ethno- Confidence Game for Slow Learner Students. Jurnal Ilmiah Sekolah Dasar, 5(3).
Ashcraft, M. H. (2002). Math anxiety: Personal, educational, and cognitive consequences. Current directions in psychological science, 11(5), 181-185.
Boelens, R., De Wever, B., & Voet, M. (2017). Four key challenges to the design of blended learning:
A systematic literature review. Educational Research Review, 22, 1–18.
Borge, M., & Mercier, E. (2019). Towards a micro-ecological approach to CSCL. International Journal of Computer-Supported Collaborative Learning, 14(2), 219–235.
Bradstreet, T. E. (1996). Teaching introductory statistics courses so that nonstatisticians experience statistical reasoning. The American Statistician, 50(1), 69-78.
Cullen, C. J., Hertel, J. T., & Nickels, M. (2020). The Roles of Technology in Mathematics Education.
Educational Forum, 84(2), 166–178.
Dowker, A., Sarkar, A., & Looi, C. Y. (2016). Mathematics anxiety: What have we learned in 60 years? Frontiers in psychology, 7, 508.
Engle, R. W. (2002). Working memory capacity as executive attention. Current Directions in Psychological Science, 11(1), 19–23.
Favale, T., Soro, F., Trevisan, M., Drago, I., & Mellia, M. (2020). Campus traffic and e-Learning during COVID-19 pandemic. Computer Networks, 176.
Ha, Y., & Im, H. (2020). The role of an interactive visual learning tool and its personalizability in online learning: Flow experience. Online Learning Journal, 24(1), 205–226.
Han, J.-S., Baek, H. C., & Jeong, A.-S. (2015). The Effects of Psychiatric Nursing Simulation on Anxiety and Self-confidence about Clinical Placement of Nursing Students. Journal of the Korea AcademiaIndustrial Cooperation Society, 16(11), 7812–7819.
Hendriana, H., Johanto, T., & Sumarmo, U. (2018). The role of problem-based learning to improve students’ mathematical problem-solving ability and self confidence. Journal on Mathematics Education, 9(2), 291–299.
Jerald, M., & Me, V. H. (2020). Number of Friends in School and the Level of Self-Confidence of the Students. International Journal of Research -Granthaalayah, 8(1), 277–286.
Kamal, A. A., Shaipullah, N. M., Truna, L., Sabri, M., & Junaini, S. N. (2020). Transitioning to online learning during COVID-19 Pandemic: Case study of a Pre-University Centre in Malaysia.
International Journal of Advanced Computer Science and Applications, 11(6), 217–223.
Kavenuke, P. S., Kinyota, M., & Kayombo, J. J. (2020). The critical thinking skills of prospective teachers: Investigating their systematicity, self-confidence and scepticism. Thinking Skills and Creativity, 37,100677. .
Kelly, R. (2014, May 30). Faculty Focus. Retrieved from Five Things Online Students Want from Faculty: https://www.facultyfocus.com/articles/online-education/online-students-want-from- faculty/
LeFevre, J. A., DeStefano, D., Coleman, B., & Shanahan, T. (n.d.). Mathematical cognition and working memory. In The Handbook of Mathematical Cognition. New York: Psychology Press.
Lemaire, P. (1996). The role of working memory resources in simple cognitive arithmetic. European Journal of Cognitive Psychology, 8(1), 73-104.
Ma, X. (1999). A meta-analysis of the relationship between anxiety toward mathematics and achievement in mathematics. Journal for research in mathematics education, 30(5), 520-540.
Martin, F., Budhrani, K., & Wang, C. (2019). Examining faculty perception of their readiness to teach online. Online Learning, 23(3), 97-119.
Miyake, A., & Shah, P. (1999). Models of working memory: Mechanisms of active maintenance and executive control. New York: Cambridge University Press.
Muppudathi, G. (2014). Role of Teachers on Helping Slow Learners to Bring Out Their Hidden Skills.
International Journal of Scientific Research, 3(2277), 98–99.
Nacu, D., Martin, C. K., & Pinkard, N. (2018). Designing for 21st century learning online: A heuristic method to enable educator learning support roles. Educational Technology Research and Development, 66(4), 1029–1049.
Pandey, S., & Kurian, B. J. (2016). Role o f Teacher ’ s : Helping Slow Learners to Bring out Hidden Skills. Journal of Research & Method in Education, 6(6), 23–26.
Perienen, A. (2020). Frameworks for ICT Integration in Mathematics Education - A Teacher’s Perspective. Eurasia Journal of Mathematics, Science and Technology Education, 16(6), 1–12.
PharmD, V. K., McAuley, J., & PharmD, M. M. (2020). Naloxone counseling: Confidence and attitudes of student pharmacists after a volunteer syringe exchange experience. Currents in Pharmacy Teaching and Learning, 12(4).
Pizzie, R. G., & Kraemer, D. J. (2017). Avoiding math on a rapid timescale: Emotional responsivity and anxious attention in math anxiety. Brain and cognition, 118, 100-107.
Ramirez, G., Shaw, S. T., & Maloney, E. A. (2018). Math anxiety: Past research, promising interventions, and a new interpretation framework. Educational Psychologist, 53(3), 145-164.
Rasheed, R. A., Kamsin, A., & Abdullah, N. A. (2020). Challenges in the online component of blended learning: A systematic review. Computers and Education, 144, 103701.
Redmond, P., Abawi, L. A., Brown, A., Henderson, R., & Heffernan, A. (2018). An online engagement framework for higher education. Online learning, 22(1), 183-204.
Skagerlund, K., Östergren, R., Västfjäll, D., & Träff, U. (2019). How does mathematics anxiety impair mathematical abilities? Investigating the link between math anxiety, working memory, and number processing. PloS one, 14(1), e0211283.
Volungevičienė, A., & Teresevičienė, M. &. (2020). When is open and online learning relevant for curriculum change in higher education? Digital and network society perspective. Electronic Journal of E-Learning, 18(1), 88–101.