Research Article Volume 6 Issue 5
Social Administration, Democritus University of Thrace, Greece
Correspondence: Despoina Kaltsidou, Social administration, Democritus University of Thrace, Amygdaleona, Kavala, Greece
Received: October 02, 2022 | Published: October 14, 2022
Citation: Kaltsidou D. New technologies and students with learning difficulties. Sociol Int J. 2022;6(5):273-278. DOI: 10.15406/sij.2022.06.00299
New Technologies have become a part of the wider lifestyle and over the years, in the future, they will probably continue to be an important part of our lives. The use of computers and the Internet appears to be able to improve people's daily lives, the quality of their work, their market prospects, while facilitating communications and access to information (National Research Council 1999). Also, using computers may help students gain experience with technology. Many questions have arisen in relation to the use of New Technologies in learning. Much research focuses on investigating the impact of ICT on student achievement while few have focused on children with special learning needs.
The purpose of the research is to investigate whether and to what extent students with special learning difficulties perform better with the use of new technologies compared to the traditional learning method. The results of the research, which was carried out on a sample of 232 Kindergarten and First Primary students, showed that children with special learning difficulties adapt easily to this new learning environment and that they perform better compared to the traditional teaching method.
Keywords: new technologies, learning disabilities, traditional methods
ICT, information communication technologies; LD, learning disabilities
In the modern society of technological developments the various means of technology are increasingly entering both everyday life and education. In this context, ICT plays an important role in the school. They are a valuable assistant in the pedagogical and teaching work of all teachers and in achieving the cognitive and social goals, which determined during the planning of teaching.1,2 In education, ICT can support all subjects and contribute to exploratory and collaborative learning, communication and in the development of students' critical thinking and creativity. All students, especially students with learning disabilities, are likely to benefit in such a teaching context, where personalized - adapted is promoted teaching at each student's ability level and in a work environment pleasant and creative.
The lesson becomes interesting as the students interact with software and develop creativity and criticism them thinking by discovering knowledge through information seeking also they actively participate in work groups, without feeling disadvantaged against them their classmates, depending on their individual abilities and skill level.3,4 The aim of this study is to examine if with the use of new technologies children with learning disabilities perform better than with traditional teaching.
Literature review
According to Adam and Tatnall,5 the use of I.C.T has a beneficial effect on the education of children with learning difficulties. It achieves this both by improving children's self-esteem, by providing the means by which they can achieve something they consider worthwhile, and by facilitating the acquisition of useful life skills. The I.C.T proved to help pedagogically, and create a pathway for the transition from school to work or further studies for students with learning difficulties.6 With the use of New Technologies, the nature of the teaching subject does not change, but it has the ability to integrate and enrich several areas from the field of study or the curriculum. Blackhurst7 described “how concepts related to the use of technology in education have evolved with particular emphasis on their implications for people with learning disabilities (LD)” (p. 175).
Henniger8 described computers as important tools in the teaching and learning of everyday subject areas. Ryba, Sleby and Nolan9 pointed out that providing 'relevant learning technology' actually showed respect for the personal needs, wishes and interests of children with special needs. The computer can be used as a learning tool that improves their quality of life. However, doing so requires adaptations to minimize these children's difficulties in working on computer tasks. Ryba, Sleby and Nolan9 stated that "adaptations that allow full access to computers (for example, laser scanning, alternative keyboards, and voice recognition) allow students with special needs to demonstrate their potential" (p. 82).
Some of the benefits of using New Technologies include promoting academic success for students with learning disabilities in the areas of writing, mathematics, spelling, reading and comprehension, enhancing their organizational skills, and, most importantly, encouraging them in their social inclusion in society.10 Students with learning disabilities, using visual tools, find new means to express language and represent their thinking in words.11
Therefore, the use of New Technologies helps to achieve the fundamental goals of co-education, such as fostering a sense of belonging to the group, sharing activities with exclusive results and providing a balanced education experience.12 Technology helps increase the regularity of successful task completion, and plays an important role in improving the motivation of students with learning disabilities.13
Research methodology
The target population of the research was children from Kindegarten and Primary full day schools, from the region of Eastern Macedonia and Trace in Greece. The students that were enrolled in kindergarten were 104 and from Primary school were 128. Furthermore, primary school students that had two classes of first grade were chosen to participate in this research. The first group was control group , and the second was the experimental group. As control group it is called the group that uses traditional methods first and proceeds to new technology methods, whereas experimental groups are vice versa. In order to be able to apply this research, the researcher had to obtain the consent of the Ministry of Education, the children's parents and the principals of the kindergarten schools. The researcher administrated the book form of the CPM to each child individually, following the standard administration procedure that was prescribed by Raven, Raven and Court14 without setting time limit.14,15 The children's personal data were kept anonymous by the researcher. Prior to administrating the book form of CPM, the kindergarten and Primary school teachers were asked to provide the researcher the names in alphabetic order, reversing the order of the code in order for no one to be able to know the personal characteristics of the children that participated in the research. The second step concerned kindergarten teachers and school units chosen by the researcher based on the curriculum of the kindergarten. The subject that was chosen and implemented in all the kindergartens was traffic education. As far as the primary school is concerned the subject that was taught to the students was subtraction and the children were divided in two classes of first grade. After the completion of the first week, the researcher gave the teachers a form that had three columns. The first column was the codes that the researcher had given to the students, the second was the grades that the teachers would give to the children based on their performance using the traditional teaching method. The rates were from 1 to 10 (where one was the lowest and 10 the highest). The children had to answer correctly to the five questions that he/she had been asked. The third column was the grades given to the children using new technology methods (the highest grade was 10).
On the other hand for primary school children after the completion of traditional teaching took a test about subtraction were 1 was the lowest grade and 5 was the highest. In order to examine their performance in new technologies the children took a test on the computer concerning subtraction. The researcher had given the teachers software created by the Ministry of Education, allowing all the teachers to download and use the web site that the Ministry had implemented in order to make their lesson more interesting.
Learning disabilities
The sample of 553 children of the first grade of A1 class in primary school, shows that 13.0% of students have learning difficulties, from the 532 students of Α2 10.6% of the students have learning difficulties while from the total sample of 1183 kindergarten students only the 8.8% presents some kind of learning difficulty (Table 1).
|
Learning disabilities % |
Α1 Grade |
13.00% |
Α2 Grade |
10.6 |
Kindrgarten |
8.80% |
Table 1 Percentage of learning disabilities
The most frequent problem presented by primary school children of groups A1 and A2 is dyslexia (62.5%), followed by distraction (25.0%) and, finally, speech problems (12.5%) (Table 2).
Category |
Percentage % |
Dyslexia |
6250.00% |
Dissociation of attention |
25 |
Speech problem |
1250.00% |
Table 2 Learning disabilities
The most frequent problem of kindergarten children is distraction (29.8%), followed by autism (20.2%), speech disorders and immaturity (17.3%), and mental retardation (7.7%) (Table 3).
Category |
Percentage % |
Distraction |
2980.00% |
Immaturity |
17.3 |
Autism |
2020.00% |
Table 3 Learning disabilities
ICT and learning difficulties in class A1 of primary school
The learning difficulties of A1 Primary students appear with small differences in boys and girls. Thus, girls show a higher percentage in dyslexia, while boys in distraction, with speech problems being equally distributed (Table 4).
Gender |
Dyslexia |
Distraction |
Speech problem |
Total |
Boy |
60.00% |
27.50% |
12.50% |
100.00% |
Girl |
65.60% |
22.00% |
12.40% |
100.00% |
Table 4 Class and gender for primary A1
The largest percentage of students with learning disabilities belong to the category of "normal intelligence", while in the categories of "low intelligence" and "high intelligence", the proportion is about the same (Table 5).
Intelligence |
Percentage` % |
Low |
23.6 |
Normal |
54.2 |
High |
22.2 |
Total |
100 |
Table 5 Intelligence for Α1 of primary school
No significant difference is observed in the ratio of boys and girls with regard to the different levels of intelligence, which is also documented by the χ2 test of independence, where the value of the statistic χ2=0.262 is not statistically significant (sig=0.877> 0.05), and therefore the gender and intelligence group variables are independent (Tables 6&7).
|
|
|
Low intelligence |
Normal intelligence |
High intelligence |
Total |
Gender |
Boy |
Frequency |
10 |
21 |
8 |
39 |
% line |
25.60% |
53.80% |
20.50% |
100.00% |
||
% column |
58.80% |
53.80% |
50.00% |
54.20% |
||
% Total |
13.90% |
29.20% |
11.10% |
54.20% |
||
Girl |
Frequncy |
7 |
18 |
8 |
33 |
|
% line |
21.20% |
54.50% |
24.20% |
100.00% |
||
% Column |
41.20% |
46.20% |
50.00% |
45.80% |
||
% Total |
9.70% |
25.00% |
11.10% |
45.80% |
||
Total |
Frequence |
17 |
39 |
16 |
72 |
|
% line |
23.60% |
54.20% |
22.20% |
100.00% |
||
% Column |
100.00% |
100.00% |
100.00% |
100.00% |
||
|
|
% Total |
23.60% |
54.20% |
22.20% |
100.00% |
Table 6 χ2test for class Α1of primary school
|
Value |
df |
Sig |
Pearson Chi-Square |
0.262a |
2 |
0.877 |
Likelihood ratio |
0.263 |
2 |
0.877 |
N of Valid cases |
72 |
||
a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 7.33. |
Table 7 χ2test for gender and intelligence categories – class Α1of primary school
The average performance of all the children of section A1, using ICT is very satisfactory (4.62) and the variability is 18.55%. Specifically, typically developing children have an average score of 4.67, and children with learning disabilities have an average score of 4.28 (Table 8).
Total of students |
Typical development |
Learning difficulties |
|
Average |
4.62 |
4.67 |
4.28 |
Median |
5 |
5 |
5 |
Mode |
5 |
5 |
5 |
Standard deviation |
0.857 |
0.847 |
0.922 |
Table 8 Performance of students A1class of primary school
In a test carried out to determine whether the performance of students with software differs by gender, no statistically significant differences emerged, as the value of the F statistic is non-significant (sig=0.329>0.05) (Table 9). In particular, in performance with software, girls (mean value 4.39) are ahead of boys (mean value 4.18).
Methods |
F |
Sig |
New Technologies |
0.965 |
0.329 |
Table 9 Analysis of variance by gender and performance – class Α1
Children with dyslexia (mean value 4.49), followed by those with speech problems (mean value 4.11), and, finally, children with distraction (mean value 3.83) show the highest performance in the use of New Technologies (Table 10).
Category |
Mean |
Standard deviation |
Dyslexia |
4.49 |
0.726 |
Distraction |
3.83 |
1.248 |
Speech problem |
4.11 |
0.781 |
Table 10 Performances in ICT by Category – class Α1
In A2 Elementary students, dyslexia and distraction appear as more frequent problems in boys, while a higher percentage is observed in girls with a speech problem (Table 11).
Gender |
Dyslexia |
Distraction |
Speech problem |
Total |
Boy |
67.60% |
26.50% |
5.90% |
100.00% |
Girl |
54.50% |
22.70% |
22.70% |
100.00% |
Table 11 Category and gender for class Α2 of primary school
The largest percentage of students with learning difficulties belongs to the category of "normal intelligence", while the category of "low intelligence" lags significantly behind the corresponding "high intelligence" (Table 12).
Intelligence |
Percentage% |
Low |
12.5 |
Normal |
58.9 |
High |
28.6 |
Total |
100 |
Table 12 Intelligence for Α2 class
No significant difference is observed in the ratio of boys and girls with regard to the different levels of intelligence which is also documented by the x2 test of independence, where the value of the statistic x2=5.091 is not statistically significant (sig=0.078>0.05), and , therefore, the gender and intelligence group variables are independent, however, the results are not particularly reliable as 33.3% (>20%) of the cells have an expected frequency of less than 5 (Tables 13&14).
|
|
|
Level of intelligence |
|
|
|
|
|
|
Low intelligence |
Normal intelligence |
High intelligence |
Total |
Gender |
Boy |
Frequency |
7 |
18 |
10 |
35 |
% line |
20.00% |
51.40% |
28.60% |
100.00% |
||
% Column |
100.00% |
54.50% |
62.50% |
62.50% |
||
% Total |
12.50% |
32.10% |
17.90% |
62.50% |
||
Girl |
Frequency |
0 |
15 |
6 |
21 |
|
% line |
0.00% |
71.40% |
28.60% |
100.00% |
||
% Column |
0.00% |
45.50% |
37.50% |
37.50% |
||
% Total |
0.00% |
26.80% |
10.70% |
37.50% |
||
Total |
Frequency |
7 |
33 |
16 |
56 |
|
% line |
12.50% |
58.90% |
28.60% |
100.00% |
||
% Column |
100.00% |
100.00% |
100.00% |
100.00% |
||
|
|
% Total |
12.50% |
58.90% |
28.60% |
100.00% |
Table 13 χ2test for class Α2
|
Value |
df |
Sig |
PearsonChi-Square |
5.091a |
2 |
0.078 |
Likelihood ratio |
7.45 |
2 |
0.024 |
N of Valid cases |
56 |
|
|
a. 2 cells (33.3%) have expected count less than 5. The minimum expected count is 2.63. |
Table 14 χ2test gender and level of intelligence – class Α2 of primary school
The performance of all the children in section A2 is very satisfactory (4.92), and the variability is about 8%. In particular, children with typical development have an average performance of 4.94, and children with learning difficulties have an average performance of 4.57 (Table 15 ).
|
Students in total |
Normal development |
Learning disabilities |
Mean |
4.92 |
4.94 |
4.57 |
Median |
5 |
5 |
5 |
Mode |
5 |
5 |
5 |
Standard deviation |
0.39 |
0.294 |
0.805 |
Table 15 4z5RwSsu52UbET7nJUhPoWqCKrVZCH4PMX6qucpWr2m6
In a test that was carried out to determine whether the performance of students with software differs in terms of gender, no statistically significant differences emerged, as the value of the F statistic is non-significant (sig=0.498>0.05) (Table 16). In particular, in performance with software, girls (mean value 4.67) are ahead of boys (mean value 4.51).
Methods |
F |
Sig |
New technologies |
0.465 |
0.498 |
Table 16 Analysis of variation in terms of gender and performance – class A2 of primary school
Children with dyslexia (mean value 4.63), followed by children with speech problems (mean value 4.57), and children with distraction (mean value 4.43) show the highest performance in the use of New Technologies (Table 17).
Category |
Mean |
Standard deviation |
Dyslexia |
4.63 |
0.77 |
Distraction |
4.43 |
0.937 |
Speech problem |
4.57 |
0.786 |
Table 17 Amplitude in mill volts of the Lead-1 of electrocardiography in sheep
*Significant (P≤0.05); NSNot significant (P>0.05)
A fairly significant difference is observed in the performance of children with learning difficulties in section A2 (mean value 4.57) compared to children in section A1 (mean value 4.28), while it is noteworthy that the variability in both sections is quite significant (17.6% in section A2 and 21.5% in section A1).
ICT and learning disabilities in Kindergarten students
In toddlers, the most common problem is distraction (29.8%), followed by autism (20.2%), speech disorders and immaturity (17.3%), and mental retardation (7.7%) (Table 18).
Category |
Frequence |
Percentage % |
Distraction |
31 |
29.8 |
Immaturity |
18 |
17.3 |
Autism |
21 |
20.2 |
Mental dysfunction |
8 |
7.7 |
Speech disorders |
18 |
17.3 |
Psychomotor immaturity |
2 |
1.9 |
Pervasive development |
2 |
1.9 |
Language problem |
4 |
3.8 |
Total |
104 |
100 |
Table 18 Learning disabilities of kindergarten students
Attention deficit disorder is about equally common in boys and girls (29.3% vs. 30.4%), immaturity is more common in boys (30.7%) than girls (13.0%), and autism (22.4%) against 17.4%), while on the contrary mental retardation in girls is more frequent (8.7%) compared to boys (6.9%). The same happens with speech disorders, where girls present more often (23.9%) than boys (12.1%) (Table 19).
Category |
Boy% |
Girl % |
Total% |
Distraction |
29.3 |
30.4 |
29.8 |
Immaturity |
20.7 |
13 |
17.3 |
Autism |
22.4 |
17.4 |
20.2 |
Mental dysfunction |
6.9 |
8.7 |
7.7 |
Speech disorders |
12.1 |
23.9 |
17.3 |
Psychomotor immaturity |
3.4 |
0 |
1.9 |
Diffuse growth |
3.4 |
0 |
1.9 |
Language problem |
1.7 |
6.5 |
3.8 |
Total |
100 |
100 |
100.00% |
Table 19 Category and gender of Kindergarten
The largest percentage of kindergarten students with learning difficulties belongs to the category of "normal intelligence", while in the category of "low intelligence" a slight superiority is observed in relation to "high intelligence" (Table 20).
Intelligence |
Percentage % |
Low |
20.8 |
Normal |
63.2 |
High |
16 |
Total |
100 |
Table 20 Intelligence of kindergarten students
789No significant difference is observed in the ratio of boys and girls regarding the different levels of intelligence, which is also documented by the χ2 test of independence, where the value of the χ2=0.201 statistic is not statistically significant (sig=0.904> 0.05), and therefore the variables gender and intelligence groups are independent (Tables 21&22).
|
|
|
Level of intelligence |
|
|
|
|
|
|
Low Intelligence |
Normal Intelligence |
High Intelligence |
Total |
Gender |
Boy |
Frequency |
12 |
39 |
9 |
60 |
% line |
20.00% |
65.00% |
15.00% |
100.00% |
||
% Column |
54.50% |
58.20% |
52.90% |
56.60% |
||
% Total |
11.30% |
36.80% |
8.50% |
56.60% |
||
Girl |
Frequency |
10 |
28 |
8 |
46 |
|
% line |
21.70% |
60.90% |
17.40% |
100.00% |
||
% Column |
45.50% |
41.80% |
47.10% |
43.40% |
||
% Total |
9.40% |
26.40% |
7.50% |
43.40% |
||
Total |
Frequency |
22 |
67 |
17 |
106 |
|
% line |
20.80% |
63.20% |
16.00% |
100.00% |
||
% Column |
100.00% |
100.00% |
100.00% |
100.00% |
||
|
|
% Total |
20.80% |
63.20% |
16.00% |
100.00% |
Table 21 χ2 test for kindergarten students
|
df |
Sig |
PearsonChi-Square |
2 |
0.904 |
Likelihood ratio |
2 |
0.905 |
N of Valid cases |
|
|
a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 7.38. |
Table 22 χ2test gender and intelligence level – kindergarten students
The performance of all kindergarten students with the use of software is satisfactory (mean value 8.30) and slightly better than the corresponding one without software (mean value 8.13) (Table 23). This difference is statistically significant, as the t-test for equality of means of the two dependent samples gave a value of t=4.198 with sig=0.000<0.01.
|
With ICT |
Without ICT |
Mean |
8.3 |
8.13 |
Median |
9 |
8 |
Mode |
10 |
10 |
Standard deviation |
1.56 |
1.77 |
Table 23 Performance of kindergarten students
In a test that was carried out to determine whether the performance of toddlers with software differs by gender, no statistically significant differences emerged, as the value of the F statistic is non-significant (sig=0.091>0.05) (Table 24). In particular, boys lead with an average value of 7.15 compared to an average value of 6.52 for girls.
Methods |
F |
Sig |
New technologies |
2.911 |
0.091 |
Table 24 Analysis of variance by gender and performance – kindergarten students
|
With ICT |
Without ICT |
Normal development |
8.45 |
8.3 |
With learning disabilities |
6.87 |
6.28 |
F |
106.759 |
137.251 |
Sig |
0 |
0 |
Table 25 Performance of kindergarten students with and without learning disabilities
The results of the research come in full agreement with research by Adam and Tatnall,5 where it was found that the I.C.T they improve learning and equip children with sufficient skills to enable them to enter the workforce or go on to further studies. Also, it is mentioned that the adoption of I.C.T in the classroom significantly facilitates children with learning difficulties, both in the development of skills and academic knowledge. The literature also provides examples of the performance of students with learning disabilities who perform poorly in courses not supported by New Technologies. Research on the use of ICT with students with learning difficulties, have been carried out by Blackmore et al, Florian and Hegarty, Williams, Jamali and Nicholas, Adam and Tatnall,5 and others. In any case, these studies found that the use of I.C.T with students with learning disabilities have had varying beneficial effects. In addition except improving their grades, the children also gained interest in their studies and confidence in their abilities. The use of technology promotes a sense of belonging, and encourages interactive participation in regular education classes for students with learning disabilities.
None.
The author declares that they have no direct or indirect conflicts.
None.
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