{'fraction_non_alphanumeric': 0.04221499920723006, 'fraction_numerical': 0.022356112256223245, 'mean_word_length': 5.318307037315302, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
A Systematic Review on the Use of Technology in Learning Disabilities  Ankara University Faculty of Educational Sciences Journal of Special Education

This paper is a systematic literature review of research studies on using technology to support individuals with Learning Disabilities (LD). The purpose is to determine (1) demographic and methodological characteristics of the articles focusing on the use of technology in LD, (2) skills that need improvement and technological tool to develop these skills (3) the effects of technological tools on the performances of students with LD and (4) students’ perceptions toward learning with technology. A systematic literature review covering 55 articles were examined. Results showed that the majority of articles were published between 1995 and 2018. Furthermore, multiple baseline designs were preferred in most of the studies, and they sampled elementary school students. The review also revealed essential skills that need improvement and the technological tools utilized to enhance these skills. Results showed that technological tools positively affect students' performances, and students' perceptions toward implemented technology were generally positive.


Learning Disabilities
According to the World Health Organization's records in 2015, 15% of the world population has some disabilities. Likewise, the records of the Turkish Statistical Institute in 2002 (Türkiye İstatistik Kurumu, 2002) showed that 12.29% of the population live with different types of disabilities. These people have different needs and characteristics (Brodin, 2010). Special education is a field aiming to provide education services to students with disabilities to overcome their difficulties (Vaughn & Linan-Thompson, 2003).
Although there are many types of disabilities in which special education is interested, learning disabilities (LD) appear to be the most common one (U.S. Department of Education, 2016). According to the American Psychiatric Association (APA, 2013), LD can be defined as a type of disorder related to difficulties in reading, writing, and mathematics. Ministry of Turkish National Education (MoNE) (Milli Eğitim Bakanlığı, 2010) describes individuals with learning disabilities as ones who need special attention and help to overcome difficulties related to reading, writing, and mathematics. APA (2013) explained that there are three main types of LD, which are dyslexia, dyscalculia, and dysgraphia. MoNE (2010) highlighted the difficulty of individuals with LD in reading, writing, and mathematics, but there is no further categorization for children diagnosed with LD (Çakıroğlu, 2017).
Dyslexia results in problems related to reading comprehension, reading fluency, and reading accuracy (APA, 2013). Moreover, dyslexia can also cause phonological issues such as word recognition, decoding, and spelling (Lyon, Shaywitz, & Shaywitz, 2003;Shaywitz & Shaywitz, 2005). Dysgraphia is the second most common learning disability. It is a disorder related to writing difficulties (National Association of Special Education Teachers [NASET], 2005) such as grammar, organization of the written text, punctuation (APA, 2013) and vocabulary knowledge, and text structure (Topbaş, 1997). Last but not least, Dyscalculia is a disorder that influences mathematical abilities. It is frequently comorbid with dyslexia (Price & Ansari, 2013) and impedes the acquisition of mathematical skills such as number sense, mathematical reasoning, and arithmetic facts (APA, 2013).

Use of Technology for Overcoming Learning Disabilities
There are many studies conducted to determine the effects of technology on students. Special education also keeps pace with technological enhancements from which it gets benefits. Some studies highlight the use of technology in special education. For example, Drigas and Ioannidou (2013) emphasized that the use of technology has the potential to provide benefits to both typically developing students and those with disabilities. King-Sears and Evmenova (2007) underlined that technology could promote learning for students with and without disabilities. Furthermore, studies emphasized the importance of integration of technology into special education (Chang, Chen, & Huang, 2011;Lin, Chen, Wu, & Yeh, 2008) and the value of technology to improve the academic success of students with learning disabilities (Blackhurst, 2005).
Technology use in special education is prevalent, and different types of technologies have been used to meet the diverse needs of people with special needs, eliminate the problems they encounter and make them more independent and competent. Technologies aiming to facilitate the lives of these people have changed over time. To illustrate, visually impaired people have been using standard walking sticks. Now with the enhancements in the technology, these sticks are equipped with GPS function, and they are more helpful for disabled people to find their ways (Çoklar, Ergenekon, & Odabaşı, 2018). In other words, the main idea of using technology is to increase the competency and independence of disabled people by supporting them in a way they need. Thus, the use of technologies for this aim evolved and ameliorated the negative impacts of disabilities. Beard, Carpenter, and Johnston (2011) categorized the technologies used for individuals with disabilities as low-tech, mid-tech, and high-tech based on their usability, development, and practicality. Firstly, post-it's, highlighter, adapted pencil, paper, scissors, and velcro are listed under low tech technologies. These are the customary form of technology, and they can be found in many classrooms. Secondly, mid-tech technologies cover tools such as audiobooks, software predicting words, wheelchairs, and translation software. Technologies in this category are not as common as a low-tech group. Thirdly, a high-tech group consists of a computer, mobile devices such as tablet PCs, text-to-speech and speech to text programs, smart boards, and artificial intelligence applications. These are the intense form of technology (Çoklar et al., 2018). In learning disability studies, many technologies categorized as high-tech were preferred in recent years. For example, different types of text-tospeech, speech recognition programs were generally preferred for enhancing reading/writing-related skills (Ciullo, Falcomata, Pfannenstiel, & Billingsley, 2015;White & Robertson, 2015). Moreover, many studies utilized software running on computers and mobile devices to handle challenges related to learning disabilities (Seo & Woo, 2010;Shin & Bryant, 2017;Silver-Pacuilla, 2006).
The use of technology can provide many opportunities, such as offering more chances to do practice (Butterworth & Laurillard, 2010;Kaur, Koval, & Chaney, 2017;Zhang, 2000) and getting immediate feedback without anyone's help (Mohammed & Kanpolat, 2010). Moreover, technology can support students to have control over their learning process (Jones, Issroff, & Scanlon, 2006). In addition to these, technology can create individualized and flexible learning environments (Galatis & White, 2013), which are essential for students with disabilities in terms of meeting their diverse needs (Brodin, 2010).
Although studies emphasize the use of technology in special education and the potential benefits of technology use, it is essential to examine demographic and methodological characteristics of the studies; skills that need improvement and technological tools used for developing these skills. It is also important to designate the possible effects of technology use on performances of students with LD and students' perceptions toward the use of technology in a systematic way. For that reason, the following research questions were addressed: 1. What are the demographic and methodological characteristics of the articles focusing on the use of technology in LD?
2. What are the skills that need improvement and technological tools used to develop these skills?
3. What are the effects of technology on the performances of students with LD?
4. What are students' perceptions of the use of technology?

Method
The purpose of this study is to explore demographic and methodological characteristics of the articles focusing on the use of technology in LD, skills and technological tools, effects of technological tools on students' performances, and students' perceptions toward the use of technology. A systematic literature review method was used to achieve this aim. The systematic review had three stages, which were, (a) searching, (b) study selection, and (c) analysis.

Searching Stage
Four databases were scanned: Web of Science, Academic Search Complete (ASC), Education Resources Information Center (ERIC), and Education Source. These databases were preferred because they are common reference tools used by researchers. Moreover, they provide access to educational literature and resources including peer-reviewed and full-text articles. Before scanning the databases, initial research was done to determine common keywords used in this field of study. The specified keywords were utilized to proceed with a systematic scan. The keywords were "Learning Disabilities," "Specific Learning Disabilities," "Learning Difficulties," "Computer Assisted Instruction," "Technology," and "Assistive Technology." These keywords were chosen by considering the initial literature search. In addition, the Boolean search was used in the process. The keywords were combined using AND/ OR operations. (("Learning Disabilities" OR "Specific Learning disabilities" OR "Learning Difficulties") AND ("Computer Assisted Instruction" OR "Technology" OR "Assistive Technology").
In the searching stage of the review, dyscalculia, dyslexia, and dysgraphia were not used as keywords because the keywords of the study were determined through an initial literature search. Although these terms used in the searching stage, the articles were examined and categorized according to difficulties in reading, writing, and mathematics as defined by APA (2013) and MoNE (2010).
This literature search was limited to the articles published in peer-reviewed journals. Furthermore, the study was restricted to full-text articles written in English. In addition, no date limitation was applied to see the progress of the use of technology in LD over the years until June 2018.

Study Selection Stage
After searching the databases above with the specified keywords, 699 articles were found in total. After removing exact duplicates, 521 articles remained. The abstracts of the articles were examined to determine whether they met the inclusion criteria. Among the found articles, 249 were either not empiric or research-based. The articles excluded were reviews, overviews, analysis, synthesis, and reports. The remaining 216 articles were empiric studies. However, some of these studies were excluded as they either did not include students with learning disabilities or not hold the aim of developing skills related to reading, writing, and mathematics.
Following these procedures, 55 studies remained and examined. A list of inclusion and exclusion criteria were presented in the following:

Inclusion criteria:
 The article was published in a peer-reviewed journal.
 The study was empiric research in the area of education.
 Students with learning disabilities were the leading participant group.
 Articles were related to technology used for developing skills in reading, writing, and mathematics.

Exclusion criteria:
 Articles were reviews, overviews, analysis, synthesis, or reports.
 Articles presented models about how to use assistive technology in LD.
 Articles aimed to determine which assistive technology special education students or teachers preferred.

Analysis Stage
The remaining articles were analyzed under four titles. Firstly, the demographic and methodological characteristics of the studies were determined. The demographic information of the articles was obtained through their publication year and the journal in which they were published. The methodological characteristics involved information regarding research design, participants, and data collection tools. The participants were classified as elementary school students, middle school students, high school students, university students, frostig school students, which is a school for children with learning disabilities, and doctoral students. Secondly, skills that need improvement, and technological tools to enhance those skills were designated. Thirdly, studies were analyzed by considering the effects of technology on the skills that need improvement. Lastly, results were presented according to student perceptions of the technology use.
In the analysis stage, the first author examined all the articles according to the main titles explained above and created a table. A doctorate student who is experienced in terms of coding and technology use in special education was involved in the study voluntarily. The first author and the doctorate student discussed the main titles and coded two articles together. The doctorate student was asked to review and code 32% of the articles (N = 18) himself. Following the coding, the results were compared and discussed. A substantial agreement percentage (namely, 95.1%) was found between researchers as the reliability coefficient formula was applied (Miles & Huberman, 1994). However, there were some disagreements. Two researchers made some changes to the coding table to resolve 4.9% disagreements.

Results
In the result part, there are four main parts: Demographic and methodological characteristics, skills and technological tools, effects of technological tools, and students' perceptions. In the result part, the total number of the skills may exceed the total number of the articles because some of the studies focused more than one skill at a time as shown in the Table 1.

Demographic and Methodological Characteristics of the Articles
The articles were published between 1995 and 2017. No date restriction was applied in the inclusion of the studies. As shown in Table 1, the oldest article was published in 1985, while the most recent was in 2017. More than half of the articles (N = 29) were published after 2012. Many of the articles were published in 2014 (N = 9) and in 2012 (N = 7). Moreover, Table 1 showed that Learning Disability Quarterly (N = 8), Journal of Special Education Technology (N = 7), Remedial and Special Education (N = 5), Journal of Learning Disabilities (N = 5), Learning Disabilities: A Multidisciplinary Journal (N = 2) and Education and Treatment of Children (N = 2) were the journals that published more articles than others.
In addition to these, the majority of the journals were indexed either in Social Science Citation Index As for the methodological characteristics, information about research methods, participants, and data collection tools were provided. Various methodology types including both qualitative and quantitative were preferred. As shown in Table 1, most of the studies (N = 16) used multiple baseline designs as a research method. Experimental research (N = 6), case study (N = 5), single-subject designs (N = 4), and pretest-posttest designs were among other research methods utilized in the studies. More than half of the articles (N = 32) were experimental even if they had weak designs.
It can be seen in Table 1 that articles included different participant profiles. Most of the reviewed articles (N = 26) involved elementary school students, 13 of them covered high school students, 7 of them included middle school students, six of them covered university students, two of them involved Frostig school students and one of the studies included doctoral student as participants. The students involved in the studies were diagnosed with learning disabilities based on the discrepancy between IQ and academic achievement. These students followed individualized education plans (IEPs) or special education programmes. Interviews, observations, achievement tests, surveys, questionnaires, field notes, artifacts (students' written and visual products) and video/audio recordings were among the data collection tools. Interviews, questionnaires, and surveys were used to identify the perceptions of the students and teachers (Belson, Hartmann, & Sherman, 2013;Dimitriadi, 2001;Hall, Cohen, Vue, & Ganley, 2015;Klemes, Epstein, Zuker, Grinberg, & Ilovitch, 2006;Nordness, Haverkost, & Volberding, 2011;. The achievement tests such as paper-pencil tests, reading comprehension tests, mathematic problem solving subtest of SAT, Woodcock-Johnson III (WJ-III) Writing Fluency subtest were implemented to explore how the use of technology affected the student performances on the focused skills Leh & Jitendra, 2013;Satsangi & Bouck, 2015;Seo & Bryant, 2012;Stultz, 2013;White & Robertson, 2015).

Skills that Need Improvement and Technological Tools
In this part, the articles that focused on the skills and technological tools to develop these skills were presented. The skills were grouped according to the difficulty areas mentioned in the definitions of the learning disabilities in Table 1. Even though the articles specified the name of the technologies they used, the Table 1 did not include technological tools to avoid providing company names. However, some examples were presented below. It is important to note that the total number of skills exceeded the total number of articles because some of the articles studied more than one skill at a time. Table 1 showed that most of the articles (N = 28) were conducted to enhance reading-related skills. Reading comprehension (N = 14), reading fluency (N = 5), vocabulary knowledge (N = 3), spelling (N = 3), literacy (N = 2), reading rate (N = 2), acquisition of sight words (N = 1), oral presentations (N = 1), reading aloud (N = 1) and word recognition (N = 1) were the skills that were investigated in the reviewed articles. The review results highlighted that articles focusing on reading-related skills preferred text-to-speech (TTS) (i.e., "Natural Reader  Moreover, Table 1 presented that 12 articles investigated the effects of technology use on the writing skills of the students with LD. In these articles, planning and writing persuasive essays (N = 3), written expression (N = 3), authoring (N = 2), fundamental writing (N = 1), dictation (N = 1), note taking (N = 1), word prediction (N = 1), and narrative writing (N = 1) were the skills that were examined. In addition to text-to-speech and speech recognition tools, technologies like computer-based graphic organizers (Evmenova et al., 2016) and electronic pens (Belson et al., 2013) were preferred to enhance writing-related skills. The graphic organizers were used to help students with LD to organize their thoughts, and the electronic pens were used to make the writing process easy.
Furthermore, three of the studies focused on reading and writing skills together instead of a single skill. In these studies, vocabulary acquisition (N = 1), letter and sound identification (N = 1), and information problem solving (N = 1) were the skills that were examined.
The results of the current study showed that most of the articles (N = 50) used software to improve the skills mentioned before. However, five of the studies used mobile applications (Corkett & Benevides, 2016;Nordness et al., 2011;Papadima-Sophocleous & Charalambous, 2014;Skiada et al., 2014;.

Effects of the Technology Use on Students' Performances Related to Reading, Writing and Mathematics
The articles were reviewed to identify how the use of technology affected the student performances related to reading, writing, and mathematics. The review process showed that the majority of the studies resulted in improvement, either statistically significant (N = 14) or insignificant (N = 36). However, 7 of the articles did not result in any improvement. Fourteen of the studies presented a significant improvement in skills related to mathematics, reading, and writing. The area-specific skills included problem-solving (Twyman & Tindal, 2006;Xin et al., 2017), notetaking (Belson et al., 2013), planning and writing persuasive essay (Englert et al., 2005), written expression (Corkett & Benevides, 2016), information problem solving (Curcic, 2011), reading fluency (White & Robertson, 2015), reading comprehension and spelling (Hall et al., 2015;Higgins & Raskind, 2000;Raskind & Higgins, 1999 A total of 36 articles resulted in statistically insignificant improvement in reading, writing, and math. First of all 14 of the articles covered skills related to reading (Ciullo et al. 2015;Cullen, et al., 2014;Cullen, et al., 2013;Dolan, et al., 2005;Keyes et al., 2016;Klemes et al., 2006;Papadima-Sophocleous & Charalambous, 2014;Regan et al., 2014;Scheeler et al., 2010;Silver-Pacuilla, 2006;Wade et al., 2010;White & Robertson, 2015).

Student Perceptions Toward the Use of Technology
More than half of the articles (N = 30) aimed to identify students' perceptions of the use of technology. Interviews, observations, and surveys were utilized in this realm. Table 2  Among these studies, it was reported by the students that technology use was helpful for them (Belson et al., 2013;Dolan et al., 2005;Evmenova et al., 2016;Hall et al., 2015;Shin & Bryant, 2017) and working with technology was fun  and easy to use (Belson et. al., 2013;Evmenova et. al., 2016). It was also stated that they enjoyed using technology (Gentry & Lindsey, 2008;Klemes et al., 2006;Nordness et al., 2011;Satsangi & Bouck, 2015; and technology increased their motivation White & Robertson, 2015).
Although their perceptions were positive in general, three of these studies revealed that participants did not prefer working with technology (Corkett & Benevides, 2016;Higgins & Raskind, 2000;Satsangi et al., 2016). The students preferred working with their teachers while they were using technology. In other words, they wanted their teachers to be part of the technology-enhanced learning process.

Discussion and Conclusion
The review revealed that the oldest article was published in 1985, and more than half of the studies (N = 29) were published after 2012. Thus, it may indicate that there is a growing interest in terms of the use of technology with learning disabilities (LD). Moreover, the most common characteristics were utilizing multiple baseline designs, working with elementary students, using interviews, observations, achievement tests, surveys, and questionnaires as data collection tools in the reviewed studies. Since the majority of the articles focused on the skills related to reading, including elementary school students is an obvious result. Therefore, the skills that need improvement may determine the target group.
The reviewed articles used different types of technologies to achieve their aims. Text-to-speech and speech recognition tools were preferred to enhance skills related to reading. Graphic organizers and digital pens were used along with the speech recognition and text-to-speech tools to improve writing-related skills. As for the mathematical skills, manipulatives and flash applications took the stage. When the results are examined, it can be said that difficulty area, which are reading, writing and math directed the type of technology to be used.
In addition to these, many of the articles used computer-based software to improve skills. However, a few of the articles published in recent years used mobile applications (Corkett & Benevides, 2016;Papadima-Sophocleous & Charalambous, 2014;Skiada et al., 2014). As far as the increased popularity of mobile learning and education is concerned, it may be said that more studies will integrate mobile technologies into special education too. In addition to mobile technologies, many new high technologies such as augmented reality will have a place in special education. Although keeping pace with the enhancements in the technology may positively support special education; applicability, usability, and practicality of the technologies should be examined before integrating them.
Furthermore, the review revealed that most of the articles showed positive improvements, whether statistically significant or not, in the skills related to reading, writing, and mathematics. In some of the studies, no improvements were recorded. When these studies were examined, the problems were related to the technology, lack of teacher-led instruction, and research design. In these studies, the technology did not meet the needs of the students Satsangi et al., 2016) as the technology did not provide self-control over the learning environment and had a limited function because of free limited version. Moreover, the results were affected by insufficient teacher-led instruction (Stetter & Hughes, 2011) because the age of the participant group was not big enough to work alone (Regan et al., 2014). It may be said that the technology use may be planned along with the teacher-led instruction by taking participant profile into account. Moreover, the applicability, usability, and practicality of the tool need to be investigated to receive a higher benefit.