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Article

Short-Term and Long-Term Effects of COVID-19 and Remote Learning: Experiences of Parents Supporting Children with Mathematical Learning Disabilities in Israel

by
Sarit Ashkenazi
1,* and
Sonia Hassoun
2
1
Learning Disabilities, The Seymour Fox School of Education, The Hebrew University of Jerusalem, Jerusalem 9190501, Israel
2
The Department of Special Education, Oranim Academic College of Education, Kiriat Tivon 36006, Israel
*
Author to whom correspondence should be addressed.
Educ. Sci. 2024, 14(9), 995; https://doi.org/10.3390/educsci14090995
Submission received: 13 June 2024 / Revised: 27 August 2024 / Accepted: 7 September 2024 / Published: 10 September 2024
(This article belongs to the Topic Advances in Online and Distance Learning)
Browse Figure
Review Reports Versions Notes

Abstract

:
Background: Over the last three years, many studies have explored the effect of pandemic closures on learning. However, in Israel, the perspectives of parents on the short- and long-term effects of the lockdowns on students with mathematical learning disabilities (MD), have rarely been examined. Method: To fill this gap, MD (n = 33) or typically developing (n = 50) children were selected. They were in the 1st and 2nd grades during the closures, and we tested them and their surroundings, two years later. Results and Conclusions: First, according to the parent’s survey, children with MD had physical conditions similar to the TD group, the two groups had similar stable connections to the internet, computer, and a quiet environment. However, MD children (1) needed more help and (2) had a harder time concentrating during virtual math classes compared to TD children. Moreover, the coronavirus closures resulted in a greater learning gap in the MD children compared to the TD children. We found positive associations between difficulties reported by the parents and actual weakness in performances in complex multiplication and division and verbal working memory.

1. Introduction

The coronavirus pandemic has led to drastic changes around the world generally, and in Israel specifically [1,2,3]. Schools were closed during the lockdown in the spring of 2020 in almost every country in the world. In Israel, the education system was closed from 2020 to 2021 between 11.5 to 24 weeks [4]. Even today, during the Gaza War in Israel, many children and young people are still involved in distance learning. Distance learning has become a common solution to every situation where children cannot participate in in-class learning. Hence, understanding the perspectives of parents about the short- and long-term effects of closure and distance learning on young children with mathematical learning disabilities is very important from both educational and social perspectives. This question is particularly important for children who were in the 1st and 2nd grades during 2020 and needed to learn the basics of arithmetic during the closures. This age range is unique because (1) the mathematical curriculum in the 1st and 2nd grades is the building block for subsequent, more complex mathematical knowledge [5,6]. The mathematical curriculum in the 1st and 2nd grades includes the learning of addition and subtraction and the understanding of multidigit numerals, areas in which children with mathematical disabilities have large weakness [7,8,9]. (2) Children as young as the 1st and 2nd grades cannot perform distance learning independently, due to difficulties in operating computers by themselves and concentrating throughout a full class period.
Questions about the cognitive effects of school closures on children with and without learning disabilities have already been tested around the world [10]. Kuhfeld et al. [11] compared mathematical performance before and after closures in the USA and found that both 3rd- and 4th-grader’s mathematical performances decreased by 9 percentile points after closure as compared to before closure. Maldonado and De Witte [12] looked at the effect of 7-week closures in Belgium and found a 0.19 standard deviation decrease in the test scores achieved in mathematics. A meta-analysis that combined 12 studies regarding learning loss during closures found that most of the studies reported varying degrees of learning loss [13]. However, the results were highly heterogeneous. One of the explanations for this great heterogeneity in the effect of closures is individual differences, such as the presence of learning disabilities [14,15,16]. Participants with learning disabilities are likely to be more heavily affected by closures than their typically developing peers [14,15,16,17].
Independent of the Corona lockdown, multiple studies have tested the effect of remote online learning on participants with learning disabilities and have found mixed results [3,17,18,19]. On the one hand, the advantage of online learning for participants with learning disabilities is free access to the course lectures and materials [19]. Moreover, online learning increases parents’ awareness of the course materials, which is beneficial, especially for students with learning disabilities [18]. On the other hand, previous studies have mentioned a few points that can interfere with online learning by students with learning disabilities [3,17]. Specifically, the online learning of students with learning disabilities requires substantial parental involvement, which might be a challenge for some of parents [17]. Moreover, students with learning disabilities need to use the support network of schools more than students without learning disabilities. Hence, online learning disconnects students from school support networks, affecting mostly students with learning disabilities [3].
Even in traditional learning environments, students with learning disabilities require considerable parental help. As children with learning disabilities experience academic deficiencies, parents need to supervise their children’s academic activities [20]. Parents of children with learning disabilities lack social support from teachers and schools [21]. They often need to create educational interventions for their child to overcome learning gaps in school.

1.1. Mathematical Disability (MD)

Many children and adults have difficulties in learning mathematics and arithmetic. Mathematical disability (MD) or developmental dyscalculia is characterized as a severe disorder of numerical and mathematical abilities in children of normal intelligence who do not have other cognitive impairments [9]. Most studies agree on a prevalence rate of 5–6% for developmental dyscalculia among school-age children [22,23,24,25,26]. MD is more common, with an expected prevalence of 25% to 35% in the population [22,23,27,28]. Therefore, in the current group, our definition would be MD.
MD has ramifications beyond schooling and can affect many aspects of everyday life [29,30]. For example, unemployment rates are higher among adults with learning disabilities [31,32]. Children with MD experience multiple weaknesses in basic numerical skills, including the inability to retrieve simple arithmetical facts [33]. Moreover, MD has been associated with weaknesses in basic numerical abilities such as symbolic or non-symbolic comparisons or deficits in general cognitive abilities such as (1) working memory [34,35], (2) inhibition abilities [36], and (3) processing speed [36].

1.2. Environmental Perspectives on Distance Learning during COVID-19

A few previous studies have explored parents’ and teachers’ perspectives on distance learning during the COVID-19 pandemic [37,38,39,40,41]. Stites et al. [41] examined parents’ perspectives in the US and found that parents were more involved in literacy-based activities than in mathematics activities. Additionally, the surveyed parents stated that time was a significant factor in helping their children with distance learning and expressed a preference for activities that did not require a lot of time. Later, Godwin et al. [38] investigated the viewpoints of parents and teachers regarding remote learning for elementary school children during the pandemic. Teachers reported that the amount of virtual instruction was less than in-person instruction and that children were more off-task. In addition, parents reported that fewer than half of the children completed online lessons independently. Furthermore, parents reported that children preferred in-person learning over online learning. Other studies investigated the perspectives of parents of children in special education and found that these children were unable to participate in virtual learning without significant adult support. Parents often had other responsibilities and were unable to provide their children with assistance during virtual learning [39,40].
One of the main challenges during the lockdown was due to parents’ inability to cope with the load and their loss of hope in helping children; this challenge varied according to the severity of the disability, with severe disabilities posing the greatest challenge [42]. Another challenge that was previously raised regarding the support of parents for online learning is the involvement of parents at home during remote learning. The level of parental involvement in distance learning was found to be modulated by two factors: (1) student requests and (2) parents’ understanding of technology [43]. In a study examining students in special education, parents reported that their children were unable to participate in virtual learning without significant adult support [40]. Similar results were also found in typically developing children. It was reported that parents tried to support their children, but this support primarily was related to the use digital technologies, which means that children whose parents do not use digital technologies may be at greater risk developing larger educational gaps [44].
A study that was conducted in Saudi Arabia aimed at investigating parents’ perspectives about the effect of the COVID-19 pandemic on children with or without learning disabilities. The results demonstrated that the COVID-19 pandemic has had serious psychological effects on children with or without disabilities. However, from the social and academic aspects, the impacts of the pandemic were generally moderate and were not different between children with or without learning disability [44].

1.3. The Present Study

It has been documented that in most countries, the effect of the coronavirus pandemic has led to significant universal learning loss. However, in Israel, the multiple perspectives of parents on the short- and long-term effects of the lockdowns on students and classes with students with learning disabilities have rarely been examined [37,38,39,40,41]. In this study, we selected children from schools in the North District of Israel who were in the 1st and 2nd grade during the closures and examined those children 2 years later during their 3rd and 4th grades. Children who were in the 1st and 2nd grades during the closures are a unique population because they were in their initial stages of learning arithmetic and were too young to fully participate in remote online learning. We selected a group of typically developing children (TD) and a group of MD. Children assigned to the MD group had severe difficulties in mathematics according to their teachers and according to curriculum-based tests that were designed by the Ministry of Education in Israel. In addition to their performances on multiple mathematical and domain-general tasks, we collected online surveys from their parents.
Whilst most of the studies described above focused on the national lockdown period, little is known about parental views on remote learning during the lockdown. The parents of all the participants signed informed consent forms for participation in the experiment. The study was approved both by the ethics committee of the Education Ministry and the School of Education at the Hebrew University.
We aimed to ascertain the impact of the COVID-19 pandemic on the learning process of children with mathematical learning disabilities in Israel, from the parents’ point of view, with a focus on experiences of school closures. To achieve this goal, the following research questions were formulated: (1) How do parents of children with learning disabilities perceive the impact of school closures on their children’s abilities to learn math later on, and are there differences in the perceptions of parents of children with or without learning disabilities? (2) Are parents’ perceptions about difficulties during the lockdowns associated with specific subject matter in the mathematical abilities of their child? (3) Are parents’ perceptions of difficulties during the lockdowns related to specific domain-general abilities associated with their child’s learning?
We hypothesize that parents’ perceptions of difficulties during the lockdown will be more severe in children diagnosed with MD than in TD. Moreover, based on previous studies in which parents of children with learning disabilities reported that they need more help than parents of typically developing children [17], we expect that parents of MD children will report that they need more help than parents of TD children. Moreover, based on our previous findings for the same population in which we found that MD children have more meaningful weaknesses in multiplication than in addition, we hypothesize that perceived difficulties related to the closures will be associated with real performances in multiplication.

2. Methods

The present study employs a survey design to assess parental perspectives on the impact of school closures in Israel resulting from the COVID-19 pandemic. Data was collected between October and December 2022–2023 following ethical approval by the Ethics Committee of the host higher educational institution. All data was anonymous, and informed consent was obtained from respondents before initiating the survey. Table 1 presents all survey items and average responses by groups. The current set of data was part of a bigger data set on the effect of COVID-19 closures and remote learning on multiple cognitive tasks. These effects will be reported in further studies.

2.1. Participants

In the first step, we asked elementary school teachers from regular classes in the Northern District of Israel to select a group of children from the 3rd or 4th grade with MD based on (1) teacher assessments of having severe difficulties in mathematics and (2) achievement in mathematical curriculum-based tests in Israel (lowest 20%). The mathematical curriculum-based test was administered to all children in Israel during these years. Children who met these two criteria were assigned to the MD group. We also asked the same elementary school teachers to provide us with an additional group of children with average or above-average math performance. This group was defined as TD.
Eighty-three children in the 3rd and 4th grades were selected from 7 schools in the Northern District of Israel. Of these, 34 were in the 3rd grade, and 16 were males (mean age = 8.64, S.D. = 0.53), while 46 were in the 4th grade, and 21 were males (mean age = 9.83, S.D. = 0.51). Of the children in the 3rd grade, 17 were TD and 20 were MD; in the 4th grade, 16 were TD, and 30 were defined as MD. Two of the MD group participants did not complete all the tests and were excluded. One of the participants in the MD group quit during the experiment due to difficulties.

2.2. Tools

Since MD is associated with weakness in multiple domain-general and domain-specific factors, we examined multiple domain-general and domain-specific tasks and their associations to reported difficulties by the parents.

2.2.1. Domain-General and Domain-Specific General Tasks

Math Fluency Test

Participants started with addition and then continued on to the multiplication subtest. At total of 81 simple multiplication (e.g., 2 × 3) and 81 simple addition (e.g., 6 + 39) problems were presented on a sheet of paper with operands between 1 to 9, including twins. The test was administered to all participants together.

KeyMath III Test

Mathematical abilities were assessed using KeyMath subtests: numeration, mental computation and estimation, addition and subtraction, and multiplication and division [45]. We chose KeyMath due to its comprehensive inclusion of several mathematics subtests and the fact that our laboratory had translated it into Hebrew for previous studies [46]. In addition, since it is a standardized measure, it has high reliability (median subtest-retest reliability 0.88 [45]. The reliability between the subscales for the participants in the current study was very high (Cronbach’s alpha = 0.90). The items of each subtest were arranged in order of difficulty. The experimenter moved on to the next subscale after four consecutive errors or when they reached the end of the subscale. Numeration, mental computation, and estimation were conducted orally, with each item presented on the KeyMath easel, while addition and subtraction and multiplication and division were assessed using paper and pencil tests.
The numeration subtest included 49 questions related to numerical understanding (place value, magnitude, number sense, decimals, fractions, percentages, exponents, integers, multiples, and factors). Mental computation and estimation, addition and subtraction, and multiplication and division are all part of the KeyMath area operations. The mental computation subtest included 40 items related to mental computation of whole and rational numbers, mental computation chains, and estimation of whole and rational numbers. The addition and subtraction subtest included 35 items, and the multiplication and division subtest included 31 items. Both subtests ranged from basic operations with integers to algebra. All of the KeyMath subtests were given a raw score, the number of correct answers in addition to a standardized score according to class level.

2.2.2. Non-Standardized Basic Numerical Tasks

Simple Operations RTs

Simple addition (e.g., 2 + 7), multiplication (e.g., 2 × 7), and sub-traction (e.g., 7 − 2) operations were shown to the participants on the screen, and the participants were instructed to give a vocal response to the operation. RTs of the correct trial served as the dependent variable.

Comparison of Symbolic Numerals

Two digits between 1 and 9 were presented on the screen in two sizes, and the participants were instructed to ignore the physical size and select the larger digit by pressing a key. Numerical distance (1 and 4) and physical size resulting in 3 congruity conditions (congruent (e.g., 1 3), natural (e.g., 1 3), and incongruent (e.g., 1 3) were manipulated; the dependent measure was average RTs for correct trials. A typical trial started with a fixation cross for 500 ms, followed by appearance of the digits until the response, and ended with a blank screen for 500 ms.

Comparison of Non-Symbolic Numerals

Participants were presented with dots, ranging in number between 5 and 24, of various sizes; the participants had to indicate, by a key press, the side on which there were more dots while ignoring the dots’ physical sizes. A typical trial started with a fixation cross for 300 ms, followed by a blank screen for 500 ms and the appearance of dots until the response, and ended with a blank screen for 1500 ms.

2.2.3. Domain General Abilities

Vocabulary

Twenty-three words were presented to each child verbally; and the child was instructed to say what the meaning of this word is. Every meaning was assigned a score between 0 to 2.

Visuospatial Short-Term and Working Memory

A computerized version of the Corsi block test was used to measure each participant’s spatial working memory span. Nine blue squares (2 cm × 2 cm) were unevenly distributed over a 16 cm × 16 cm quadrant on a computer screen. The positions of the squares were fixed. Each trial began with the presentation of nine blue squares, and then a random sequence of squares was lit up in yellow at a rate of one square per second. The squares remained on the screen for 500 ms after the sequence was completed. Then a black screen was presented for 15 s. Finally, the nine blue squares were presented again and the participant had to reproduce by mouse click the sequence in which the squares had lit up, either in the same order (working memory) or in reverse order (central executive). (Task from the Psychology Experiment Building Language—PEBL https://pebl.sourceforge.net/ accessed on 1 January 2022).

Verbal Short-Term and Working Memory

A computerized version of the digit span test was used to measure the participants’ phonological span. In each trial, a sequence of numbers was auditorily presented to each participant. The participants were asked to repeat the sequence numbers in the same order (working memory) or reverse order (central executive). Trials started with a sequence of two numbers and increased in difficulty with each successive trial. In contrast to the phonological span test, which involves the use of non-numerical stimuli (letters), the present task used digits.

Inhibition

A row of 5 fishes were presented on the screen and the participants had to indicate by a keypress whether the central fish was pointing to the left or the right while ignoring the fishes on the sides. In the congruent condition, all the fishes were pointing in the same direction, while in the incongruent condition, the central fish was pointing in the opposite direction to the fishes on the sides. A typical trial started with a fixation cross for 500 ms, followed by the appearance of digits until the response, and ended with a blank screen for 500 ms.

Processing Speed

In this task, participants were presented with a number between 1 and 9 matched with 9 abstract symbols (e.g., the number 1 was matched to a certain abstract symbol). The matched numbers and symbols were shown on the screen for the whole experiment. During the experiment, participants were shown a pair of a number and a symbol and had to indicate, by a key press, whether the symbol matched the number or not.

Raven

Children were shown 37 trials with a pattern with a missing part. The children were asked to select the part that was missing from a few options. The dependent variable was accuracy.

Parent’s Survey

The influence of remote learning during the Corona period included 14 items. The survey was sent online, with the following general instructions for the parents: “Your child was in his first or second grade during the Corona period. Try to remember the closure time two years ago, when your child performed virtual learning. Try to answer the questions as exactly as possible. For every item, please decide which ranking best describes the remote learning period during the closure. Please answer with a score between 1 and 5, with 1 indicating ‘not at all’, and 5 indicating ‘very much’. Please mark only one answer. Please work fast, but relate to every item separately”. The individual items are presented in Table 1.

3. Results

3.1. Preliminary Analysis

Reliability Analysis. The questionnaire included 14 items. In order to test the reliability of the test, we calculated Cronbach’s Alpha. For all of the 14 items, Cronbach’s Alpha was rather low (0.38). In order to increase Cronbach’s Alpha, we first omitted Q2, Q4, and Q12, which resulted in a Cronbach’s Alpha of 0.58; then we omitted Q7, resulting in a Cronbach’s Alpha of 0.63. Next, we omitted Q10 and Q11 to achieve a Cronbach’s Alpha of 0.71. This was followed by omission of Q9 and Q13, which yielded a Cronbach’s Alpha of 0.82. Then only 6 items were left: Q1, Q3, Q5, Q6, Q8 and Q14.
Factor Analysis. Exploratory factor analysis (EFA) was performed on the correlation matrix in order to identify underlying dimensions (factors) as measured by 6 items comprising the Parent’s survey for which the influence of remote learning during the Corona period was found to be highly reliable. We used the principal axis factoring method. The results indicated a single factor with an Eigenvalue greater than 1 that explained 52.61% of the variance with direct Oblimin. The results are presented in Table 1. The model fit indices obtained through EFA for the one-factor were: χ2/df = 10.46, Kaiser- Meyer-Olkin measure of sampling adequacy = 0.77, Bartlett’s test of sphericity p = 0.001. Thus, the one-factor model was acceptable (Table 2).

3.2. Main Analysis

Group Comparison of Responses. In the current analysis, we included a typically developing (TD) group, which according to their teacher had average school achievement, and a mathematical difficulty group (MD), which according to their teachers and curriculum-based measurements had severe difficulties in arithmetic. A three-way repeated measures ANOVA was conducted on the responses, with item numbers (1–14) as the within-participants factor and grade (3 or 4) or group (MD or TD) as the between-participants factor. The effect of item number was significant F(13, 962) = 16.44, partial µ2 = 0.182, p = 0.001. The interaction between group and item was also significant F(13, 962) = 4.157, partial µ2 = 0.053, p = 0.001. Accordingly, we tested between-group differences for each item. The results are summarized at Table 1. First, for to Q1, whose effect size was medium, parents of children from the MD group reported that they had a harder time following virtual classes compared to parents of children from the TD group. Second, for Q5, whose effect size was medium, parents of children from the MD group reported that they had a harder time concentrating in virtual math classes compared to parents of children from the TD group. Third, for Q8, whose effect size was large, parents of children from the MD group reported that they had a harder time performing virtual learning tasks without help, compared to parents of children from the TD group. Fourth, for Q14, whose effect size was medium, parents of children from the MD group reported that the Corona closure resulted in larger learning gaps compared to parents of children from the TD group.
Responses by Group for the subset of 6 reliable Items. A three-way repeated measures ANOVA was conducted on responses, with item numbers (1, 3, 5, 6, 8, 14) as the within-participants factor and grade (3 or 4) or group (MD or TD) as the between-participants factor. The effect of item was significant F(5, 385) = 7.81, partial µ2 = 0.09, p = 0.001. The interaction between group and item was also significant F(5, 385) = 4.897, partial µ2 = 0.06, p = 0.001. The results are summarized in Table 3. All of the questions that showed significant group differences were included in the current analysis; hence, we did not analyze the group by item interaction (see the previous section).
Correlation Analysis between Responses, Domain-General, and Mathematical Abilities. We conducted correlation analyses questionnaire responses that showed significant group differences and domain-general or domain-specific factors. First, we tested the relations between general abilities and average score in the items that showed significant group differences in the previous analysis. The scores for Q1 were recoded as opposite scores (a response of 1 was coded as 5, a response of 2 was coded as 4, a response of 4 was coded as 2, and a response of 5 was coded as 1), and then the opposite scores for Q1 were averaged together with those for Q5, Q8, and Q14 (see Table 1). Table 4 presents the correlations between these scores and general abilities. Table 5 presents the correlations between these scores and numerical and mathematical abilities. It was found that only verbal working memory was negatively associated with responses in the questionnaire, r(62) = −0.43, p < 0.001. Moreover, it was found that after Bonferroni correction, only KeyMath multiplication and division was negatively associated with responses in the questionnaire, r(62) = −0.35, p < 0.01 (see Figure 1).

4. Discussion

The main goal of the present study was to test the perspectives of parents of students with mathematical learning disabilities regarding the short and long-term effects of coronavirus closure. Many novel aspects can be found in the current study. First, we looked at a population of students with MD identified according to teacher assessments and curriculum-based tests. Second, we correlated parents’ perspective with the actual performances of children in mathematical tasks as well as cognitive factors. Third, we used children who were in the 1st and 2nd grades during the closures. These children were in the initial stages of acquiring basic mathematical abilities.
In a meta-analysis, Zierer [13] found that most of the studies reported learning gaps to various degrees, although the size of the effect varied dramatically among studies due to individual characteristics of the learners or socioeconomic status. For example, the learning gap was very severe for students from less-educated households who experienced a 60% greater loss to the general population [47]. Similarly, studies from all over the world found that learning gaps were greater for students with learning disabilities compared to the general population [17]. In line with the investigators’ view about learning gaps, for children and especially children with learning disabilities, most parents, with a small preference for the parents of MD children, believe that the coronavirus closure had a negative effect on the learning of their child. Both groups of parents reported that their children had a harder time being part of virtual classes compared to regular classes, and both groups reported that it was not so hard to find the right symbols on the keyboard during class. The findings regarding the symbols is very surprising due to the fact that the children were very young and because the technological barriers of the parents was reported to be a big challenge in previous studies [43].
However, in line with our expectations, parents of the MD group reported (1) that their children needed more help from others to perform the online tasks; (2) That they had a harder time concentrating during online math classes, and (3) that the Corona time resulted in greater learning gaps compared to TD parents. Specifically, 75.8% of the parents of children from the MD group and 55.1% of the parents of children from the TD group strongly agreed (gave an answer of 4 or 5) with the item “The Corona period resulted in significant learning gaps among the students”. This finding is not consistent with the findings of a study on a large sample of children from Saudi Arabia indicating that the impacts of the pandemic on academic performance were mild and were not different between children with and without learning disability [44].
Effective online learning requires physical conditions such as (1) a stable internet connection, (2) an available computer, and (3) a quiet environment [48]. The Program for International Student Assessment (PISA) is an international assessment that measures 15-year-old students’ reading, mathematics, and science literacy [48]. Pisa (2018) compared these physical online learning conditions during the coronavirus closures across countries. According to the report, Israeli learners had relatively good physical conditions during the coronavirus closure. The specific results reported were as follows. (1) According to the Pisa 2018, 90% of the students in disadvantaged schools, and over 95% of the students in advantaged schools reported that they had a quiet place to study (gave an answer of 4 or 5). In our sample, only 50% of the TD and 42.5% of the MD parents reported that their child always had a quiet and isolated environment during online learning. (2) According to Pisa 2018, 90% of students in disadvantaged schools and over 95% of students in advantaged schools reported that they had an internet connection. In our sample, only 74% of the TD and 69.6% of the MD parents reported that their child had a stable connection to the internet during online classes. (3) According to Pisa 2018, 90% of the students in disadvantaged schools and over 98% of the students in advantaged schools reported that they had access to a computer for schoolwork. In our sample, only 70% of the TD and 72.8% of the MD parents reported that their child always had a computer available for learning. These findings demonstrate that students in the MD and TD groups had similar environments and materials conducive to online learning. However, our results indicated worse physical conditions across the board in our sample compared to the results of Pisa 2018. Please note that our sample was much younger than the students sampled in Pisa 2018, which included only 15-year-old students [48].
One of the main aims of the present study was to look at the different experiences of children with or without learning disabilities with respect to online and remote learning during the coronavirus closure. One of the differences was related to the independence of learners. Our two groups were children who were in the 1st or 2nd grades during the coronavirus closure, and accordingly had minimal technical knowledge, and required extensive help from families. However, in line with previous studies, 72% of the parents of children from the MD group and only 37% of the parents of children from the TD group strongly agreed (gave an answer of 4 or 5) with the item “The student had a hard time performing the online task by his/herself and without help from others”. Schuck and Lambert [17] previously reported that the online learning of students with learning disabilities requires great parental involvement, which might be a challenge to some of the parents. Moreover, in line with the greater general difficulties of MD students with mathematical learning in class or remotely, we discovered that MD children had a harder time keeping track or concentrating during virtual classes than TD children.
An additional question of the study was whether parents’ perspectives about the child’s weaknesses were related to their child’s actual mathematical abilities or general cognitive mechanisms that are the basis of mathematical abilities. The results indicated that subjective parents’ reports of weakness in the survey were positively related to their child’s actual weakness in complex multiplication and division as tested by KeyMath III standardized tasks and to their child’s weakness in verbal working memory.
In a recent study [49], we looked at the long-term and short-term effects of the Corona lockdown on retrieval of arithmetical facts in the same age group as in the present study. We looked at the short-term effects by examining students’ knowledge of addition facts that were learned shortly before the lockdown, and multiplication facts that were learned after the Corona lockdown. As expected, with regard to addition facts, participants that experienced the Corona lockdown showed reduced performance compared to participants who learned the facts before the Corona lockdown. However, with regard to multiplication facts, typically developing children who learned multiplication facts post-Corona lockdown showed better performance than children who learned the facts before the Corona lockdown. Children with mathematical learning disabilities showed weaknesses in both addition and multiplication, with more severe deficits in multiplication. While TD children improved in multiplication compared to pre-Corona, for MD children, this was their biggest gap. The present result is consistent with previous results indicating that multiplication facts are very sensitive to the effect of Corona lockdowns. Additionally, we discovered that verbal working memory of individual abilities was the only domain-general factor associated with reported weakness. Verbal working memory is one of the building blocks of complex multiplication and division [50,51,52,53]. For example, Bulk et al. [53] discovered that verbal working memory (digits backward) was a significant predictor of mathematical abilities at the beginning of elementary school. A meta-analysis [54] found that complex mathematical tasks had the strongest correlation with working memory. In a recent study, Chen et al. [55] examined the associations between multiple mathematical tasks, including complex calculations, and working memory tasks in children. They discovered that verbal working memory, but not visuospatial working memory, had a unique contribution to complex subtraction, multi-step computation, and number series. Hence, it comes as no surprise that the perceived difficulties of children during the Corona period were associated with both complex calculations and verbal working memory deficits.

Educational Implications

The study highlights how the pandemic exacerbated learning gaps, particularly for children with mathematical learning disabilities. Recognizing these gaps is crucial for developing targeted interventions and support systems to ensure that all students, especially those with additional learning needs, receive the support necessary to succeed.
The findings show that children with MD faced significant challenges during virtual learning, such as requiring more help and having trouble concentrating. Understanding these challenges allows educators to adapt their teaching strategies and provide additional support tailored to the needs of MD students, both in virtual and in-person settings.

5. Conclusions

The main aim of the present study was to examine the perspectives of parents of children with mathematical learning disabilities about the short and long-term effects of the coronavirus closures on the learning process of mathematics. We used a population of students who were in the 1st and 2nd grades during the closures and investigated them and their surroundings two years later. Children with MD had physical conditions similar to children in the TD group: the two groups had stable connections to the internet, computers, and quiet environments. However, the MD children (1) needed more help and (2) had a harder time concentrating during virtual math classes compared to TD children. Moreover, the coronavirus closures resulted in a greater learning gaps for the MD children compared to the TD children. We found positive associations between difficulties reported by the parents and real weakness in performances in complex multiplication and division and verbal working memory.

Author Contributions

Conceptualization, S.A. and S.H.; methodology, S.A.; software, S.A.; validation, S.A.; formal analysis, S.A.; investigation, S.H.; resources, S.A.; data curation, S.A.; writing—original draft preparation, S.A.; writing—review and editing, S.A.; visualization, S.A.; supervision, S.A.; project administration, S.H.; funding acquisition, S.A. All authors have read and agreed to the published version of the manuscript.

Funding

This research received funding from the Ministry of education in Israel. Grant number 45/9.2022.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki, and approved by the Institutional Ethics Committee of school of education in the Hebrew university on the November 2021. Approval code 1411Y2021.

Informed Consent Statement

Informed consent was obtained from all the parents of the subjects involved in the study.

Data Availability Statement

The data will be available upon request from the corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Shahar, G.; Aharonson-Daniel, L.; Greenberg, D.; Shalev, H.; Malone, P.S.; Tendler, A.; Grotto, I.; Davidovitch, N. Changes in General and Virus-Specific Anxiety during the Spread of COVID-19 in Israel: A 7-Wave Longitudinal Study. Am. J. Epidemiol. 2022, 191, 49–62. [Google Scholar] [CrossRef] [PubMed]
  2. Kaufman-Shriqui, V.; Navarro, D.A.; Raz, O.; Boaz, M. Dietary changes and anxiety during the coronavirus pandemic: A multinational survey. Eur. J. Clin. Nutr. 2022, 76, 84–92. [Google Scholar] [CrossRef] [PubMed]
  3. Lee, J. Mental health effects of school closures during COVID-19. Lancet Child Adolesc. Health 2020, 4, 421. [Google Scholar] [CrossRef] [PubMed]
  4. Buonsenso, D.; Roland, D.; De Rose, C.; Vásquez-Hoyos, P.; Ramly, B.; Chakakala-Chaziya, J.N.; Alasdair, M.; Sebastián, G.-D. Schools closures during the COVID-19 pandemic: A catastrophic global situation. Pediatr. Infect. Dis. J. 2021, 40, e146–e150. [Google Scholar] [CrossRef] [PubMed]
  5. Siegler, R.S. Magnitude knowledge: The common core of numerical development. Dev. Sci. 2016, 19, 341–361. [Google Scholar] [CrossRef]
  6. Haverty, L. The Importance of Basic Number Knowledge to Advanced Mathematical Problem-Solving; Carnegie Mellon University: Pittsburgh, PA, USA, 1999. [Google Scholar]
  7. Szűcs, D. Chapter 11—Subtypes and Comorbidity in Mathematical Learning Disabilities: Multidimensional Study of Verbal and Visual Memory Processes Is Key to Understanding, in Progress in Brain Research; Marinella, C., Wim, F., Eds.; Elsevier: Amsterdam, The Netherlands, 2016; pp. 277–304. [Google Scholar]
  8. Henik, A.; Rubinsten, O.; Ashkenazi, S. The “where” and “what” in developmental dyscalculia. Clin. Neuropsychol. 2011, 25, 989–1008. [Google Scholar] [CrossRef]
  9. Butterworth, B.; Varma, S.; Laurillard, D. Dyscalculia: From brain to education. Science 2011, 332, 1049–1053. [Google Scholar] [CrossRef]
  10. Colvin, M.; Reesman, J.; Glen, T. The impact of COVID-19 related educational disruption on children and adolescents: An interim data summary and commentary on ten considerations for neuropsychological practice. Clin. Neuropsychol. 2022, 36, 45–71. [Google Scholar] [CrossRef]
  11. Kuhfeld, M.; Soland, J.; Lewis, K.; Ruzek, E.; Johnson, A. The COVID-19 school year: Learning and recovery across 2020–2021. Aera Open 2022, 8, 23328584221099306. [Google Scholar] [CrossRef]
  12. Maldonado, J.; De Witte, K. The effect of school closures on standardised student test outcomes. Br. Educ. Res. J. 2022, 48, 49–94. [Google Scholar] [CrossRef]
  13. Zierer, K. Effects of pandemic-related school closures on pupils’ performance and learning in selected countries: A rapid review. Educ. Sci. 2021, 11, 252. [Google Scholar] [CrossRef]
  14. Petretto, D.; Carta, S.M.; Cataudella, S.; Masala, I.; Mascia, M.L.; Penna, M.P.; Piras, P.; Pistis, I.; Masala, C. The Use of Distance Learning and E-learning in Students with Learning Disabilities: A Review on the Effects and some Hint of Analysis on the Use during COVID-19 Outbreak. Clin. Pract. Epidemiol. Ment. Health CP EMH 2021, 17, 92. [Google Scholar] [CrossRef] [PubMed]
  15. Kadarisma, G.; Juandi, D. Mathematics Learning for Students with Special Needs during the COVID-19 Pandemic. In Journal of Physics: Conference Series; IOP Publishing: Bristol, UK, 2021. [Google Scholar]
  16. Poletti, M. Hey teachers! Do not leave them kids alone! Envisioning schools during and after the coronavirus (COVID-19) pandemic. Trends Neurosci. Educ. 2020, 20, 100140. [Google Scholar] [CrossRef] [PubMed]
  17. Schuck, R.K.; Lambert, R. “Am I doing enough?” Special educators’ experiences with emergency remote teaching in Spring 2020. Educ. Sci. 2020, 10, 320. [Google Scholar] [CrossRef]
  18. Sorensen, T. Special Education in Idaho Virtual Schools: An Analysis of the Efficacy of Service Delivery; Northwest Nazarene University: Nampa, ID, USA, 2019; p. 236. [Google Scholar]
  19. Serianni, B.A.; Coy, K. Doing the math: Supporting students with disabilities in online courses. Teach. Except. Child. 2014, 46, 102–109. [Google Scholar] [CrossRef]
  20. Finardi, G.; Paleari, F.G.; Fincham, F. Parenting a child with learning disabilities: Mothers’ self-forgiveness, well-being, and parental behaviors. J. Child Fam. Stud. 2022, 31, 2454–2471. [Google Scholar] [CrossRef]
  21. Dyson, L. Children with Learning Disabilities Within the Family Context: A Comparison with Siblings in Global Self–Concept, Academic Self–Perception, and Social Competence. Learn. Disabil. Res. Pract. 2003, 18, 1–9. [Google Scholar] [CrossRef]
  22. Geary, D.C. A componential analysis of an early learning deficit in mathematics. J. Exp. Child Psychol. 1990, 49, 363–383. [Google Scholar] [CrossRef]
  23. Geary, D.C. Mathematics and Learning Disabilities. J. Learn. Disabil. 2004, 37, 4–15. [Google Scholar] [CrossRef]
  24. Geary, D.C.; Hoard, M.K.; Byrd-Craven, J.; Nugent, L.; Numtee, C. Cognitive mechanisms underlying achievement deficits in children with mathematical learning disability. Child Dev. 2007, 78, 1343–1359. [Google Scholar] [CrossRef]
  25. Geary, D.; Hoard, M.K.; Nugent, L.; Byrd-Craven, J. Development of Number Line Representations in Children With Mathematical Learning Disability. Dev. Neuropsychol. 2008, 33, 277–299. [Google Scholar] [CrossRef] [PubMed]
  26. Rotzer, S.; Loenneker, T.; Kucian, K.; Martin, E.; Klaver, P.; von Aster, M. Dysfunctional neural network of spatial working memory contributes to developmental dyscalculia. Neuropsychologia 2009, 47, 2859–2865. [Google Scholar] [CrossRef] [PubMed]
  27. Geary, D.C.; Brown, S.C.; Samaranayake, V.A. Cognitive addition: A short longitudinal study of strategy choice and speed-of-processing differences in normal and mathematically disabled children. Dev. Psychol. 1991, 27, 787–797. [Google Scholar] [CrossRef]
  28. Geary, D.C.; Hamson, C.O.; Hoard, M.K. Numerical and arithmetical cognition: A longitudinal study of process and concept deficits in children with learning disability. J. Exp. Child Psychol. 2000, 77, 236–263. [Google Scholar] [CrossRef]
  29. Parsons, S.; Bynner, J. Numeracy and employment. Educ. Train. 1997, 39, 43–51. [Google Scholar] [CrossRef]
  30. Bruine de Bruin, W.; Slovic, P. Low numeracy is associated with poor financial well-being around the world. PLoS ONE 2021, 16, e0260378. [Google Scholar] [CrossRef]
  31. Gerber, P.J.; Ginsberg, R.; Reiff, H.B. Identifying alterable patterns in employment success for highly successful adults with learning disabilities. J. Learn. Disabil. 1992, 25, 475–487. [Google Scholar] [CrossRef]
  32. Gerber, P.J. The impact of learning disabilities on adulthood: A review of the evidenced-based literature for research and practice in adult education. J. Learn. Disabil. 2012, 45, 31–46. [Google Scholar] [CrossRef]
  33. Rotem, A.; Henik, A. Multiplication facts and number sense in children with mathematics learning disabilities and typical achievers. Cogn. Dev. 2020, 54, 100866. [Google Scholar] [CrossRef]
  34. Ashkenazi, S.; Mark-Zigdon, N.; Henik, A. Do subitizing deficits in developmental dyscalculia involve pattern recognition weakness? Dev. Sci. 2013, 16, 35–46. [Google Scholar] [CrossRef]
  35. Silverman, S.; Ashkenazi, S. The differential relationship between visual and spatial working memory in children’s mathematics performance. Trends Neurosci. Educ. 2022, 29, 100188. [Google Scholar] [CrossRef] [PubMed]
  36. Ashkenazi, S.; Blum-Cahana, I.Y. The role of inhibition and speed of processing in mathematics. Appl. Cogn. Psychol. 2023, 37, 111–124. [Google Scholar] [CrossRef]
  37. Jubran, S.M.; Al Fayez, M.Q.; Abueita, J.D. Teachers’ Perspectives of the Sudden Shift towards Online Learning: Challenges and Future Lessons. J. Lang. Teach. Res. 2023, 14, 239–248. [Google Scholar] [CrossRef]
  38. Godwin, K.; Kaur, F.; Sonnenschein, S. Teaching and Learning during a Global Pandemic: Perspectives from Elementary School Teachers and Parents. Educ. Sci. 2023, 13, 426. [Google Scholar] [CrossRef]
  39. Sonnenschein, S.; Stites, M.L.; Grossman, J.A.; Galczyk, S.H. “It Just Does Not Work”: Parents’ Views about Distance Learning for Young Children with Special Needs. In The Impact of COVID-19 on Early Childhood Education and Care: International Perspectives, Challenges, and Responses; Springer: Berlin/Heidelberg, Germany, 2022; pp. 253–273. [Google Scholar]
  40. Sonnenschein, S.; Stites, M.L.; Grossman, J.A.; Galczyk, S.H. “This will likely affect his entire life”: Parents’ views of special education services during COVID-19. Int. J. Educ. Res. 2022, 112, 101941. [Google Scholar] [CrossRef]
  41. Stites, M.; Sonneschein, S.; Galczyk, S. Preschool parents’ views of distance learning during COVID-19. Early Educ. Dev. 2021, 32, 923–939. [Google Scholar] [CrossRef]
  42. Rababah, A.; Khlaifat, D.; Abdelfattah, F.; Busaad, Y.; Alqaryouti, I.; AlAwamleh, A. The impact of COVID-19 on parents of children with disability: Educational needs and challenges. Int. J. Instr. 2022, 15, 701–722. [Google Scholar] [CrossRef]
  43. Herwin, H.; Dahalan, S. Technological integration factors in parental involvement during distance learning. Int. J. Inf. Educ. Technol. 2022, 12, 637–642. [Google Scholar] [CrossRef]
  44. Daniela, L.; Rubene, Z.; Rūdolfa, A. Parents’ perspectives on remote learning in the pandemic context. Sustainability 2021, 13, 3640. [Google Scholar] [CrossRef]
  45. Connolly, A.J. KeyMath-3 Diagnostic Assessment; Pearson: London, UK, 1998. [Google Scholar]
  46. Silverman, S.; Ashkenazi, S. The Unique Role of Spatial Working Memory for Mathematics Performance. J. Numer. Cogn. 2022, 8, 226–243. [Google Scholar] [CrossRef]
  47. Engzell, P.; Frey, A.; Verhagen, M.D. Learning loss due to school closures during the COVID-19 pandemic. Proc. Natl. Acad. Sci. USA 2021, 118, e2022376118. [Google Scholar] [CrossRef] [PubMed]
  48. Organisation for Economic Co-Operation and Development. Learning Remotely When Schools Close: How Well Are Students and Schools Prepared? Insights from PISA; OECD Publishing: Paris, France, 2020. [Google Scholar]
  49. Ashkenazi, S.; Hasson, S. Dissociations between short and long-term effects of Corona closures: The case of math fluency. Cognitive Dev. Under review.
  50. Liang, Z.; Dong, P.; Zhou, Y.; Feng, S.; Zhang, Q. Whether verbal and visuospatial working memory play different roles in pupil’s mathematical abilities. Br. J. Educ. Psychol. 2022, 92, e12454. [Google Scholar] [CrossRef] [PubMed]
  51. Caviola, S.; Colling, L.J.; Mammarella, I.C.; Szűcs, D. Predictors of mathematics in primary school: Magnitude comparison, verbal and spatial working memory measures. Dev. Sci. 2020, 23, e12957. [Google Scholar] [CrossRef] [PubMed]
  52. Allen, K.; Giofrè, D.; Higgins, S.; Adams, J. Working memory predictors of written mathematics in 7- to 8-year-old children. Q. J. Exp. Psychol. 2020, 73, 239–248. [Google Scholar] [CrossRef] [PubMed]
  53. Bull, R.; Espy, K.A.; Wiebe, S.A. Short-term memory, working memory, and executive functioning in preschoolers: Longitudinal predictors of mathematical achievement at age 7 years. Dev. Neuropsychol. 2008, 33, 205–228. [Google Scholar] [CrossRef]
  54. Friso-Van den Bos, I.; van der Ven, S.H.; Kroesbergen, E.H.; van Luit, J.E. Working memory and mathematics in primary school children: A meta-analysis. Educ. Res. Rev. 2013, 10, 29–44. [Google Scholar] [CrossRef]
  55. Chen, C.; Liu, P.; Lu, S.; Li, S.; Zhang, C.; Zhou, X. Verbal but not visual-spatial working memory contributes to complex arithmetic calculation. Br. J. Dev. Psychol. 2023, 41, 385–399. [Google Scholar] [CrossRef]
Education 14 00995 g001
Figure 1. Correlations between responses for items that showed significant differences between MD and TD groups and verbal working memory score (A) or complex multiplication and division as measured by the KeyMath score (B). The result showed significant and positive correlation between parents’ reports and actual weakness in complex calculation and verbal working memory. ** p < 0.05, *** p < 0.01.
Figure 1. Correlations between responses for items that showed significant differences between MD and TD groups and verbal working memory score (A) or complex multiplication and division as measured by the KeyMath score (B). The result showed significant and positive correlation between parents’ reports and actual weakness in complex calculation and verbal working memory. ** p < 0.05, *** p < 0.01.
Education 14 00995 g001
Table 1. Results of all survey questions for all groups.
Table 1. Results of all survey questions for all groups.
The Translated Question TD (n = 50)MD (n = 33)
MeanSDMeanSDp
Q1The student was able to keep track of what was going on during class3.5811.0933.0911.090.004 *
Q2The student was able to understand the teacher 3.5011.0933.2400.870.25
Q3It was harder for the student to study in a virtual compared to a frontal class3.2611.1233.8511.290.06
Q4 Digit learning aids, including short movies, helped the student understand the subject matter 3.6511.1233.3800.980.25
Q5It was hard for the student to concentrate during virtual math class3.0611.2333.8211.130.006 **
Q6It was hard for the student to find symbols on the keyboard 2.5111.1833.0611.410.07
Q7The student performed the tasks that were given to him/her on time3.8811.2433.4211.090.09
Q8The student had a hard time performing the online task by himself and without help from others2.9511.2644.0011.060.001 **
Q9The student always had a quiet and isolated environment during online learning3.3811.2633.2711.350.71
Q10The student always had the computer available for learning 4.0411.2144.1511.180.68
Q11The student left the online lesson only when it ended 4.3300.7744.1511.230.43
Q12The student used a mobile phone instead of the computer during learning 2.1611.3511.9411.340.47
Q13The student had a stable connection to the interment during online classes3.9000.9533.9411.200.87
Q14The Corona period resulted in significant learning gaps for the student3.5110.9744.1511.260.02 *
* p < 0.05, ** p < 0.01. Bold font indicates significant difference between groups after Bonferroni correction.
Table 2. Results from the factor analysis after reliability analysis.
Table 2. Results from the factor analysis after reliability analysis.
Factor 1 Loading (52.61%)
Q30.80
Q80.80
Q50.73
Q60.72
Q140.67
Q1−0.66
Table 3. Results of the items identified by reliability analysis.
Table 3. Results of the items identified by reliability analysis.
TD (n = 50) MD (n = 33) pCohen’s d
MeanSDMean SD
Q13.581.013.091.100.04 *−0.47
Q33.261.433.851.280.06
Q53.061.253.821.130.006 **0.64
Q62.511.213.061.430.07
Q80.951.264.001.060.001 **0.90
Q140.511.344.151.030.02 *0.54
* p < 0.05, ** p < 0.01. Bold font indicates significant difference between groups after Bonferroni correction.
Table 4. Correlations between average scores for questions that showed group differences and general abilities.
Table 4. Correlations between average scores for questions that showed group differences and general abilities.
TestCorrelationSignificant
Vocabulary−0.010.92
Visuospatial short-term memory0.050.97
Visuospatial working memory−0.050.72
Verbal short-term memory−0.010.95
Verbal working memory−0.430.001
Inhibition0.130.25
Processing speed0.120.38
Revan−0.190.13
Note. Bold font indicates significance after Bonferroni correction (p < 0.006).
Table 5. Correlations between average scores for questions that show group differences and numerical and mathematical abilities.
Table 5. Correlations between average scores for questions that show group differences and numerical and mathematical abilities.
TestCorrelationSig
Numerical fluency (number of correctly solved addition and multiplication in 2 min)−0.170.17
Simple operation (accuracy)−0.290.02 *
Comparison symbolic (RT) −0.100.44
Comparison non-symbolic (RT)0.100.43
KeyMath addition and subtraction (number of correctly solved)−0.260.04 *
KeyMath multiplication and division (number of correctly solved)−0.350.004 **
KeyMath estimation (number of correctly solved)−0.290.02 *
KeyMath numeration (number of correctly solved)−0.290.02 *
Note. * p < 0.05, ** p < 0.01. Bold font indicates significance after Bonferroni correction (p < 0.006).
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Ashkenazi, S.; Hassoun, S. Short-Term and Long-Term Effects of COVID-19 and Remote Learning: Experiences of Parents Supporting Children with Mathematical Learning Disabilities in Israel. Educ. Sci. 2024, 14, 995. https://doi.org/10.3390/educsci14090995

AMA Style

Ashkenazi S, Hassoun S. Short-Term and Long-Term Effects of COVID-19 and Remote Learning: Experiences of Parents Supporting Children with Mathematical Learning Disabilities in Israel. Education Sciences. 2024; 14(9):995. https://doi.org/10.3390/educsci14090995

Chicago/Turabian Style

Ashkenazi, Sarit, and Sonia Hassoun. 2024. "Short-Term and Long-Term Effects of COVID-19 and Remote Learning: Experiences of Parents Supporting Children with Mathematical Learning Disabilities in Israel" Education Sciences 14, no. 9: 995. https://doi.org/10.3390/educsci14090995

APA Style

Ashkenazi, S., & Hassoun, S. (2024). Short-Term and Long-Term Effects of COVID-19 and Remote Learning: Experiences of Parents Supporting Children with Mathematical Learning Disabilities in Israel. Education Sciences, 14(9), 995. https://doi.org/10.3390/educsci14090995

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