case study on student with learning disabilities

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Open Access

Peer-reviewed

Research Article

A comparative case study of the accommodation of students with disabilities in online and in-person degree programs

Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Validation, Visualization, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliation Center for Education Through Exploration, School of Earth and Space Exploration, Arizona State University, Tempe, Arizona, United States of America

Roles Data curation, Validation, Writing – review & editing

Affiliation Student Accessibility and Inclusive Learning Services, Educational Outreach and Student Services, Arizona State University, Tempe, Arizona, United States of America

Roles Validation, Writing – review & editing

Affiliation Sheridan Center for Teaching and Learning, Brown University, Providence, Rhode Island, United States of America

Roles Conceptualization, Funding acquisition, Writing – review & editing

Affiliations Center for Education Through Exploration, School of Earth and Space Exploration, Arizona State University, Tempe, Arizona, United States of America, School of Molecular Sciences, Arizona State University, Tempe, Arizona, United States of America

Roles Conceptualization, Funding acquisition, Project administration, Writing – review & editing

Affiliation School of Life Sciences, Arizona State University, Tempe, Arizona, United States of America

Affiliation School of Social and Family Dynamics, The College of Liberal Arts and Sciences, Arizona State University, Tempe, Arizona, United States of America

Roles Conceptualization, Funding acquisition, Investigation, Project administration, Supervision, Validation, Writing – review & editing

Affiliations School of Life Sciences, Arizona State University, Tempe, Arizona, United States of America, Research for Inclusive STEM Education Center, Arizona State University, Tempe, Arizona, United States of America

• Chris Mead, 
• Chad Price, 
• Logan E. Gin, 
• Ariel D. Anbar, 
• James P. Collins, 
• Paul LePore, 
• Sara E. Brownell

• Published: October 12, 2023
• https://doi.org/10.1371/journal.pone.0288748
• Peer Review
• Reader Comments

Fully online degree programs are an increasingly important part of the higher education ecosystem. Among the many challenges raised by the growth of fully online courses and degree programs is the question: Are institutions providing online students with disabilities accommodations that are comparable to those provided to students in traditional in-person degree programs? To explore this question, we compared students in a fully online biology degree program to students in the equivalent in-person degree program at a large research university. For each group, we assessed the frequency with which students register with the disability resource center, the range of specific accommodations provided, and course grades. Results show that students in the in-person program were nearly 30% more likely to be enrolled with the disability resource center, and that students in the online program were offered a narrower range of accommodations. However, in relative terms (i.e., compared to students without disabilities in their degree program), online students with disabilities perform better than in-person students with disabilities.

Citation: Mead C, Price C, Gin LE, Anbar AD, Collins JP, LePore P, et al. (2023) A comparative case study of the accommodation of students with disabilities in online and in-person degree programs. PLoS ONE 18(10): e0288748. https://doi.org/10.1371/journal.pone.0288748

Editor: Jolanta Maj, Wrocław University of Science and Technology, POLAND

Received: April 6, 2023; Accepted: June 23, 2023; Published: October 12, 2023

Copyright: © 2023 Mead et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: The data analyzed in this study describe students' individual disability statuses. They also include enough demographic information to make re-identification of individuals possible. For these reasons, it is not possible to publicly release the raw data. Qualified researchers may request access through https://uoia.asu.edu/contact .

Funding: This work was supported by grant #GT11046 from the Howard Hughes Medical Institute ( www.hhmi.org ), awarded to JPC, SEB, PL, and ADA and grant #2012998 and #1644236 from the National Science Foundation ( www.nsf.gov ), awarded to SEB. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

1. Introduction

Legal requirements institutionalized the provision of learning accommodations for students with disabilities in American colleges and universities [ 1 – 3 ]. Within this context, a disability is defined as “a physical or mental impairment that substantially limits one or more major life activities, a record of such impairment, or being regarded as having such an impairment” [ 1 , 3 ]. Accommodations are an adjustment to a course or degree requirements made to allow a student with a disability to have equal access to that course or degree and, by definition, are intended to ensure that students with disabilities have educational experiences as equivalent as possible to students without disabilities. However, as Gin et al. [ 4 ] discuss, contemporary higher education has changed dramatically since these statutes were enacted. Notably, because university structures that provide disability accommodations predate the availability and growth of both online courses and fully online degree programs, common accommodations provided are specific to the obstacles to learning that students might face when attending in-person courses. Therefore, in-person accommodations may not be as well suited to addressing the needs of online students with disabilities.

Online education offers some inherent accommodations relative to in-person settings, particularly when viewed through the historical lens of disability accommodation [e.g., 5]. For example, students do not need to physically move across campus to get to class, rendering some accommodations related to mobility moot. Similarly, pre-recorded lectures or video conference-based instruction easily allow for pausing, repeated viewing, or playback at different speeds. These can be seen as “built in” accommodations for students with certain conditions such as ADHD. Asynchronous instruction gives students greater time flexibility for completing their work, which can be helpful for students with chronic health conditions who may have frequent doctor appointments or flare ups.

At the same time, the modality of teaching online may present novel challenges and, thus, the need to consider how to adapt common accommodations or create new accommodations to best support fully online students. For example, test-taking accommodations, such as reduced distraction environments in a room on campus, cannot be provided for students who are physically situated across the world. Depending on students’ living situations, a quiet testing environment may not be available. The issue of video-monitored exam proctoring has been increasingly debated during the COVID-19 pandemic [e.g., 6 – 8 ], with some work suggesting that it may exacerbate student mental health struggles [ 9 – 11 ].

Thus, it is an open question whether the inherent accommodations of the online modality allow students with disabilities to learn and succeed academically or if the range of accommodations offered to online students is, indeed, narrower and if this in turn hinders the performance of online students with disabilities. Please note that we chose to use “person-first language” (e.g., students with disabilities) in this article, although we do recognize that this choice is not universally preferred [ 9 ].

1.1. Access to disability accommodations for online students

A pair of recent studies gives some insight into the challenges faced by online students with disabilities. Gin et al. [ 9 ] interviewed students with disabilities in courses that were rapidly shifted to an online format in response to the COVID-19 pandemic. Gin et al. [ 4 ] conducted a follow-up survey a year later to test if students with disabilities were being provided adequate accommodations online after instructors had more time to be comfortable teaching online. In both studies the authors found that students with disabilities faced obstacles to receiving the disability accommodations to which they were legally entitled. Early on in the pandemic, students with disabilities were often completely forgotten about and their standard accommodations were often not enacted. A year later, students with disabilities were receiving their accommodations, but often these accommodations were not meeting their needs, both in the new modes of instruction and because of the changing needs of students due to the pandemic. Collectively, these studies highlight that students with disabilities currently are not being adequately supported in many online environments.

These studies brought important issues to light and, through the interviews and open-ended survey questions, allowed students with disabilities to reveal barriers associated with online learning in their own words. However, both studies are limited in that they only capture the experiences of those students who chose to participate in the studies. By examining administrative data, the present study will build on Gin et al. [ 4 , 9 ] and explore the experiences of all registered students with the Disability Resource Center at a single institution.

1.2. Academic performance of students with disabilities

To our knowledge, there are no prior studies that examine the academic performance of postsecondary students with disabilities in fully-online degree programs. In research exploring traditional in-person postsecondary settings, Kimball et al. [ 12 ] studied both persistence and academic achievement of students with disabilities. Although many results point to lower persistence, Kimball et al. argue that the evidence is not conclusive, owing generally to the use of correlational data. Similarly, Fichten et al.’s [ 13 ] review of existing evidence finds mixed conclusions, with studies finding equivalent persistence [ 14 ], albeit with longer time to graduation [ 15 , 16 ], or less persistence [ 17 , 18 ]. Looking at academic achievement, studies often examine the success of students with specific types of disabilities. For example, Dong & Lucas [ 19 ] examined academic performance of students across majors with a range of disabilities and, importantly, studied the performance of students who did and did not register for campus disability services. These authors found the students with disabilities—whether psychological, cognitive, or physical disabilities—were less likely to persist than students who reported no disability. They also found that students with psychological or cognitive disabilities who requested accommodations were more likely to be in good academic standing, although this relationship was not found for students with physical disabilities. Interestingly, Lee [ 20 ] found that STEM majors with disabilities received significantly fewer accommodations than non-STEM majors.

Although research has shown many specific disability accommodations to have a positive impact on student success, these results are not universal. A recent randomized controlled study examined the value of accommodations for students with ADHD or learning disabilities in which students were allowed to complete tests in a separate, reduced-distraction environment [ 21 ]. Their results show that not only did the separate testing room not improve test performance, but that students with ADHD or learning disabilities performed worse in the separate testing room compared to students in the classroom. Using the Beginning Postsecondary Students Longitudinal Study (BPS:04/06) data set, Mamiseishvili & Koch [ 22 ] studied factors that predicted first- to second-year persistence among students with disabilities, including specific accommodations. Analyzed in isolation, they found that classroom note-taking accommodation was significantly related to increased persistence and that alternative exam formats and additional time were not significant. However, these did not rise to the level of inclusion in the authors’ final regression model. In a single-university study modeling cumulative GPA, Kim & Lee [ 23 ] found that including specific disability accommodations added only a small amount of explanatory power to their regression model. Newman et al. [ 24 ] looked more broadly and examined the effect on the persistence of students with disabilities of the use of resources that are available to all students regardless of disability status, such as tutoring and writing or study centers. Their results show that accessing only these universally available resources led to significantly higher persistence, whereas accessing only disability-related support had no effect on persistence. Notably, Newman et al. relied on data from the National Longitudinal Transition Study-2, a nationally representative study, and, thus, included students with disabilities who choose not to disclose this information to their college or university [ 25 ].

1.3. The present study

We examine administrative data from students in both an in-person and a fully online biology degree program at a large, public research university. Our focus on a science degree program follows from the substantial body of work, particularly in recent years, showing failures in achieving diversity, equity, and inclusion in the sciences and engineering [e.g., 26 – 28 ] and our own prior work examining course grade equity for women, racial and ethnic minorities, low-income, and first generation to college students in online biology [ 29 , 30 ]. Thus, against this backdrop, we consider whether students with disabilities in an online biology degree program are afforded an equitable experience both relative to their online peers without disabilities and relative to in-person degree students. In this study we pose the following research questions:

RQ1: Do in-person and fully online students differ in either the frequency of reported disabilities or the frequencies of receiving specific accommodations?

RQ2: Do students with disabilities compared to students without disabilities differ in academic performance between in-person and fully online degree programs?

2.1. Description of population and data sources

We collected three types of student data:

• Academic data: individual course grades, overall grade point average,
• Demographic data: student gender, race/ethnicity, college generation status, and Pell Grant eligibility (an indicator of socioeconomic status), and
• Disability data: categorical disability type and specific accommodations requested by course.

All students were enrolled in the Biological Sciences degree program. This degree is offered both in-person and in a fully online mode, but both modes are housed in the same academic unit and were designed to be identical in their curriculum structure. We included course enrollments from Fall 2014–Fall 2019 for the in-person program and Fall 2017–2019 for the online program (Note that the online degree program began in Fall 2017, but grew rapidly in enrollment, eventually surpassing in-person enrollment). The end point was chosen to avoid the confounding effects of the COVID-19 pandemic, which necessitated a shift to remote instruction for all students beginning midway through the Spring 2020 semester. We do wish to acknowledge the effects the pandemic has had on students with disabilities; please see Gin et al. [ 4 , 9 ] for examinations of those effects. In order to make our findings more general and to avoid undue influence from unique circumstances that can emerge in smaller courses, we limited our analysis to the large, required courses that are the focus of the first two years of the degree program. These include the two-course introductory biology sequence, genetics, evolution, a two-semester introductory chemistry series, two organic chemistry courses, and introductory physics. Most of these courses include a laboratory component. These are also the same set of courses analyzed in a previous study, the focus of which was course grade equity in online courses with respect to gender, race/ethnicity, household income, and college generation status [ 29 ].

Data regarding student disability status and the specific accommodation requests are stored separately from ordinary academic and demographic data. For this reason and to ensure there was no possibility that personally identifying information related to disability status was revealed, we took steps to ensure that the identifiable disability data were handled only by staff members within the Disability Resource Center (DRC). Note that we will use the DRC abbreviation as a generic term, but such organizations may also be called a Disability Services Office, Student Accessibility Center, among other names. The lead author compiled the academic and demographic data based on the selection criteria described above. These data were then sent to the office in charge of approving and coordinating disability accommodations who performed a match to their internal database, de-identified the data, and returned the new dataset to the lead author for analysis. Details of this process were reviewed and approved by the Arizona State University institutional review board (IRB, protocol #9105). Consent was not obtained because the data were analyzed anonymously.

Prior research on the subject of disability accommodations has argued for the importance of including and prioritizing the perspectives of students with disabilities themselves [ 31 ]. The present study relies on de-identified administrative data. It would not be possible to conduct such a broad survey of the types of accommodations sought and the course grades earned by students with disabilities in these degree programs. Nonetheless, it is important to acknowledge that the administrative data do not capture the full depth and range of the academic experiences of these students and that since we are only analyzing students who are registered with the DRC, we are only examining the experiences of students who have the resources and support to have achieved a diagnosis.

2.2. Description of analyses

We calculated descriptive statistics for the student demographic variables, students’ disability status, disability type, and the frequencies of disability accommodations that were received. The categories used for disability type are the same used in Gin et al. [ 4 , 9 , 31 ]. Following the procedure of our prior studies [ 29 , 30 ], we used a linear mixed effects regression to estimate the effect of student disability status on course grades, adjusting for the effects of prior academic performance (GPA in other courses, abbreviated as GPAO, [ 27 ]), whether the student earned fewer than 30 credit hours, gender, race/ethnicity, age, college generation status, and socioeconomic status (fixed effects) and including random effects for each student and class section. GPAO was a continuous variable on a 0–4.33 (A+) scale. Age was treated as a categorical variable (18–25 and over 25 years of age). These categories distinguish the more “traditional” aged (18–25 years old) students from older students and are also of roughly equal sizes among the online program students. The remaining fixed effects were analyzed as binary variables: fewer than 30 credit hours or not, binary gender (female, male), race/ethnicity (BLNP [Black, Latine, Native American, or Pacific Islander], White or Asian), college generation status (first-generation, continuing-generation), socioeconomic status (Pell eligible, non-Pell eligible). We also used logistic regression to estimate the effects on DRC registration of degree program modality (online or in-person) and possible interaction effects between modality and gender, race/ethnicity, college generation status, and socioeconomic status. For model selections, we employed both forward selection (starting with a minimal model and adding predictors stepwise) and backwards elimination (starting with a full model that consisted of all of the above predictors and removing predictors stepwise) [ 32 ].

Note that, in contrast to Mead et al. [ 29 ], we did not fully exclude students with missing demographic data or students who received “withdraw” grades in a course. Because the focus of the present study goes beyond just grades analysis, there was no need reduce our analytical power by excluding these data when analyzing DRC enrollment or the types of accommodations given. However, for regressions involving grades or demographics, we excluded any course enrollments where the student received a “withdraw” grade and we excluded students with missing demographics data.

2.3. Positionality statement

Our research team consists of both women and men as well as first generation college graduates and individuals who received Pell grants as students. Some of us are members of the LGBTQ+ community and some of us identify as having depression. Most of us have served as instructors of courses who have worked directly with the DRC to provide students with disabilities with accommodations. One of us has received accommodations for a disability through the DRC as an undergraduate and graduate student.

3.1. Population demographics

The total population included 5586 students, 2908 from the in-person degree program and 2678 from the online degree program ( Table 1 ). Women were a majority in both groups, although substantially more so in the online program (74% vs. 59%). About a third of students in both programs were BLNP. Just under half of the in-person students were Pell eligible, while somewhat more than half were Pell eligible among the online program students. Similarly, the percentage of first-generation students was also higher online (43% vs. 33%). In summary, although the two populations are similar, the online program has slightly more representation of each of the four historically marginalized groups (consistent with our own prior work, [ 29 ]). Another important demographic consideration is student age, which also differs substantially between the in-person and online populations. The median age for in-person students in our dataset is 19 as compared to 25 in the online population.

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https://doi.org/10.1371/journal.pone.0288748.t001

Table 2 shows the percentage of students in each program who are registered with the DRC. With 8% of in-person students and 4.7% of online students registered for a disability accommodation, this is well below published estimates for the overall proportion of students with a disability (19.4%; [ 33 ]). However, previous research also finds that only about a third of students with disabilities disclose this information to their school [ 25 ], which would put the two populations in our study near to the prior estimates. Full demographic details for the students with any disability accommodation may be found in S1 Table . Table 2 also shows the percentages of students whose listed “primary” disability falls within either learning disability (including ADD/ADHD; see [ 9 ] for a discussion of this categorization) or mental health/psychological disability. These are the most common disability types in our data set, which is consistent with prior analysis [ 34 ]. Students in both groups were registered with other disabilities types, including, Acquired Brain Injury, Chronic health condition, Hearing loss, Neurological, Physical disability, and Visual loss, but each of these categories had fewer than 20 individual students and our research protocol prohibits us from presenting results for subgroups smaller than this size. It is also important to note that the personal experiences of individuals, even with the same type of disability, are unique [ 35 , 36 ]. Thus, we caution against making generalizations concerning all individuals who share a disability type or specific disability.

https://doi.org/10.1371/journal.pone.0288748.t002

Finding 1: DRC enrollment is significantly lower among online program students

There are two important dimensions to this research question: differential access to (or use of) disability support services and a differential range of services provided. To examine the first dimension of this, we used logistic regression to determine whether students in the online or in-person modalities were equally likely to be registered with the university DRC. To test for possible differences within these populations, we performed additional regressions that included student demographics and interactions between the degree program type and each of gender, race/ethnicity, Pell grant eligibility, college generation status, age, and whether the student has fewer than 30 credit hours.

Overall, we find significant differences in DRC enrollment associated with degree program mode (in-person or fully online). Specifically, in-person program students are nearly 30% more likely to be enrolled with the DRC ( Table 3 ). Regarding demographics, we will first consider a main effects model to examine how the demographic effects differ by degree program mode. We will then add a series of interaction terms to see whether these demographic effects vary in their impact for in-person and online students. In the main effects model ( S2 Table ), we find that women are much more likely to be registered with the DRC as are students older than traditional college age. Pell eligible students are slightly more likely to be registered while first-generation students are somewhat less likely to be registered. No significant differences exist in the main effects model with respect to race/ethnicity or credit hours earned.

https://doi.org/10.1371/journal.pone.0288748.t003

Considering the full model with degree program modality interaction effects ( Table 4 ), we see that women are more likely to be registered in both programs, but that this effect is stronger for in-person students. In contrast to the main effects model, we see that BLNP is significant when the program interaction effects are considered. BLNP students in the online program are more likely than white or Asian students to be registered with the DRC, but in the in-person program BLNP students are slightly less likely to be registered. There are also similar, but smaller differences with respect to college generation status, with first generation students in the in-person program being significantly less likely to be registered than first generation students in the online program. For online students, having fewer than 30 credit hours is a negative predictor of DRC registration; this is not the case in-person. No significant interactions with program modality were found for student age or Pell eligibility.

https://doi.org/10.1371/journal.pone.0288748.t004

Finding 2: Online degree program students with disabilities are given access to a narrower range of accommodations

Table 5 presents an overall summary, for common accommodation categories, of the frequency at which they are received by students in both the in-person and online program courses. A complete list of accommodation types is provided in S3 Table . There are several accommodation “types” that are much less common for online students than in-person students. These include:

• “Reduced Distraction” environment for testing
• Flexible attendance
• Peer notetaking services
• Audio recording

https://doi.org/10.1371/journal.pone.0288748.t005

The impact of these varies in severity. Depending on the nature of the online course, “audio recording” and “flexible attendance” may be irrelevant in the majority of cases. However, both “reduced distraction environment” and “peer notetaking services” are accommodations that can reasonably be seen as addressing needs that are common to both in-person and online learning. A previous nationwide study found notetaking to be the third most common accommodation with 26% of students surveyed reporting receiving this kind of support [ 18 ]. It is important to state that the notetaking accommodation here refers to a peer notetaker, i.e., a fellow classmate who is compensated to share their own notes with the student receiving the accommodation. Thus, while dictation software or other technology solutions have some overlap with the intended benefits of the peer notetaking services accommodation, those tools are not entirely equivalent.

Conversely, we see that some accommodations are somewhat more common in the online group. These include Assistive Technology and PDF with Recognized Text (i.e., ensuring that PDF documents are compatible with screen readers). These accommodations are understandably important in the computer-based learning environment of the online program. We found that extra time on exams is the most common accommodation in both modalities and flexible assignment deadlines is the second and fourth most common for online and in-person, respectively, but in both cases, the percentages of students receiving these accommodations are higher in the online modality.

Finding 3: The relative performance of students with disabilities in the online program exceeds that of the in-person program

Our regression model finds a significant interaction effect between disability status (i.e., a student requesting a disability accommodation for a particular course) and learning modality. Specifically, in-person students with disabilities earn grades 0.19 grade units lower than their peers as compared to students in the online degree program ( Fig 1 , Table 6 ). The overall grade effect associated with disability accommodation was positive, but non-significant. This model also finds significant effects associated with demographics categories and online program status. Similar demographic findings from a closely related student population were described in [ 29 ]. Recognizing Finding 1—significant demographic and program modality differences in DRC enrollment—we explored the addition of interactions between these factors and the disability status term, but none of these interactions were statistically significant.

Whereas having a disability was not associated with an overall grade difference, the results do show a significant interaction effect between disability status and modality.

https://doi.org/10.1371/journal.pone.0288748.g001

https://doi.org/10.1371/journal.pone.0288748.t006

We explored possible interaction effects involving specific types of disabilities using the same categories as in Table 6 . The learning disability and mental health/psychological disability categories represent a large majority of students in this population (see Table 2 ). Our modeling showed students in each of these categories to have similar patterns of course performance to our initial regression model (i.e., to have a negative grade effect associated with the in-person degree program). See S4 Table for details. The small number of students with other types of disabilities limited our ability to detect possible interaction effects associated with any of those disability types.

4. Discussion

Regarding our first research question, our results show that systematic differences exist between the two modalities of degree programs studied, with students in the online program being less likely to enroll with the DRC or request disability accommodations. There are also notable differences in the demographic effects by modality, such as online BLNP students being more likely to have a disability accommodation and online students with fewer than 30 credit hours being less likely to have any accommodation. The online students are also offered a narrower range of disability accommodations. With respect to our second question, we find that the relative academic performance of students with disabilities to students without disabilities differs between the online and in-person degree programs. In relative terms (i.e., compared to students without disabilities in their degree program), online students with disabilities perform better than in-person students with disabilities.

The differences in the types of accommodations provided online as compared to in-person reflect a combination of accommodations that are impractical/impossible to provide to a distributed and remote population of students and accommodations that are inherently unnecessary online. This is very much the pattern we anticipated, and it highlights the inherent advantages and disadvantages of online learning for students with disabilities. However, the differential rates of registration and requests for accommodations with the university DRC across both modality and student demographics raise questions about whether all students are being made aware of and given access to these resources. Our findings are consistent with the issues raised in Gin et al. [ 4 ] and Terras et al. [ 37 ], both in the specific lack of access to distraction-free testing and peer notetaking services for online students and in the overall lower rates of DRC registration among the online students studied.

Our findings with respect to the demographic predictors of DRC enrollment contribute to a somewhat varied set of previous findings. The largest demographic effect we observed was that of gender, in which women were much more likely to be registered for an accommodation. This sits in contrast to Henderson [ 38 ], Wagner et al. [ 39 ], and Newman et al. [ 25 ] which present evidence of the opposite trend. However, the U.S. Department of Education reported gender parity with respect to disability status among undergraduates and found that women were more likely to report a disability among postbaccalaureate students [ 33 ]. It is important to note that our study population has a high population of women, owing in part to the discipline of the program studied (biology) and in part to the fact that the online program enrolls proportionately more women [ 29 ]. As additional studies are performed involving online programs, it will be interesting to see how these demographic effects compare to results from in-person programs.

It goes beyond our data to make claims about whether the underlying rate of disabilities differs systematically between the in-person and online degree programs. However, if we assume that this rate of disability is constant, then our data point to systematic differences between these two degree programs across one or more of a number of factors related to how students with disabilities approach these programs. This may include students’ awareness of these university services or of their personal eligibility for receiving them. It may include students’ perceived value of the available accommodations or their willingness to request accommodations. Lastly, the differences in usage may stem from perceived and real differences in the need for accommodation in the in-person versus online programs, even for students with very similar personal circumstances. We expand upon each of these possibilities in the following paragraphs.

4.1. Awareness

It is possible that the online program students are less well-informed about the availability of support through the DRC [e.g., 9 , 40 ]. This could follow from a lack of informal sharing of information that is more likely to occur in in-person learning environments. Supporting this explanation is the fact that for online students, having fewer than 30 credit hours was predictive of less DRC enrollment, whereas this was not the case among in-person students. This suggests that, despite the university’s many lines of communication to its online program students, including traditional academic advisors and “success coaches” who provide support to online students for things like time management and career exploration, many students early in their college journey may not receive the support that they may require and be entitled to.

4.2. Eligibility

Complicating this subject is the question of which students are considered eligible to receive accommodations. In addition to the structural issues addressed in the Gin et al. studies, prior research has highlighted the “documentation disconnect”, in which a student was deemed eligible for a disability accommodation at the K–12 level, but, due to more stringent requirements for documentation of disability, was not found to be eligible for the same accommodation at the college level [ 41 , 42 ]. Sparks & Lovett [ 43 ] also conclude that the breadth of methods for diagnosing a learning-disabled student has led to a situation in which there is substantial overlap in the academic performance of “learning disabled” and “non-learning disabled” students. The literature calls attention to ways that a student may have an expectation of receiving a disability accommodation, but not be eligible in practice. Some of these factors may be exacerbated in the case of fully online degree programs. For example, the documentation disconnect described previously occurs in part because different laws mandate disability accommodation in K–12 than in higher education and in part because standards for K–12 disability status vary by state. Given that online undergraduate programs are often marketed toward out-of-state students, the fraction of these ineligible students may be greater in an online program as compared to the traditional in-person degree programs at the same university. In addition, given that our prior work showed that the online program attracted relatively more students from lower socioeconomic status backgrounds [ 29 ], it is possible that online students with disabilities are, on average, less able than the in-person degree students to obtain the medical diagnoses necessary to demonstrate their eligibility.

Assuming that online students with disabilities are aware of their support options and, bearing in mind our results showing the limited range of accommodations that are commonly received ( Table 5 ), it is possible that some students are making an informed choice to not ask for accommodations. That is to say that these students may believe that the accommodations that are made available to them do not effectively address their needs. We have no evidence that speaks directly to this possibility. However, in considering more indirect evidence, Gin et al. [ 4 , 9 ] found that some students with disabilities struggled to be granted the kind of support they felt was justified during the emergency shift to online learning during the COVID-19 pandemic. There is also the question of a perceived stigma associated with requesting accommodations, so students must see these accommodations as having a value that exceeds the effort required to obtain them and any negative consequences (e.g., judgement or bias against them) they may associate with them.

4.4. Willingness to request

Numerous previous studies highlight the important possibility of students who choose not to address or report their disabilities [ 5 , 12 , 25 , 44 ]. This may be even more true in online courses and programs where students will have fewer and more limited interactions with their peers or with faculty members. The limited nature of these interactions makes it easier, and perhaps more appealing, to keep one’s disability status private. It also removes opportunities for students to learn about the types of accommodations available or the potential value of those resources. Similarly, it may be more difficult for online instructors (or student peers) to recognize instances where a student may benefit from disability services. Therefore, the mediated nature of an online degree program expands the concept of a “hidden disability”, providing many students with disabilities the choice whether or not to disclose their disability status to others. In an in-person setting, a hidden disability might be a mental health condition, but in an asynchronous online setting, this category could include deafness, physical disabilities, or chronic health conditions, many of which would be readily apparent in-person. Thus, students not registering with the DRC could be a conscious decision not to reveal their disability to others, and the nature of online learning gives students in those degree programs more autonomy regarding this decision.

Looking at results from both Tables 5 and 6 , a final possibility is that the differences in the frequencies of requested accommodations follow from the inherent accommodations provided by the online learning modality. Put simply, perhaps students online need fewer accommodations because of the asynchronous flexible nature of the learning environment. Consider peer notetaking services, for example, which our results show to be a relatively common accommodation in-person, but not available to online students. It may be the case that some students who would have requested this kind of accommodation for a synchronous, in-person class do not see it as necessary for an asynchronous, online delivery where they can freely pause, rewind, or rewatch lectures at their convenience. Alternatively, perhaps our results are driven by a self-selection effect in which students with disabilities preferentially enroll in the online degree program knowing that they will not need to request disability accommodations. This kind of strategic enrollment would imply a high level of effective self-determination, something that prior work has shown to be associated with academic success [ 45 ]. Therefore, if such behavior is widespread, then our observed grade differences reflect a combination of the inherent affordances of the online modality and the presence of students with the skills of self-determination that help them to be successful.

Prior research is mixed on whether online courses are seen as preferable by students with disabilities, with much of the difference coming from how attentive a given institution or instructor has been to accessibility [ 12 , 46 , 47 ]. The present study does not examine instructional practices or technology use at the level of individual courses, but strategies for effective and accessible online learning have been reviewed elsewhere [e.g., 48 ] and could be the basis for future research expanding on our work.

This study relied on administrative data because these data provide a complete summary of the university’s available DRC services and students’ use of these services. However, our work cannot speak directly to the students’ perspective in requesting, declining to request, or receiving DRC services, nor can it speak to factors related to the self-determination of these students. The latter is one of the more widely studied constructs for both predicting success of students with disabilities and for designing support programs to promote success [e.g., 49 – 52 ]. Future work is needed to explore whether our findings reflect an underlying difference in the level of self-determination between students in in-person and online degree programs or, perhaps, that the skills associated with self-determination (self-advocacy, goal setting, etc.) must be applied differently in online settings.

We conclude this section by reiterating that our regression results with respect to course grades suggest that students with disabilities who are registered with the DRC in the online degree program have an equal or better opportunity to succeed as their in-person counterparts. Therefore, we tentatively conclude that online students with disabilities can be well-supported in that modality. However, we do underscore that our interpretation of the grade results is complicated by the fact that we can only analyze students who were officially eligible for and proactively chose to request support from the campus DRC, thus it may be the case that our finding with respect to grades is biased by a selection for the most well-informed students with disabilities. Or, relatedly, that online students with disabilities that are registered with the DRC are the more privileged group of students with disabilities, so the grade advantage that we see online is simply because the more privileged group of students with disabilities are represented in the dataset.

4.6. Limitations

Although we believe this work is an important first step in closing a gap in the existing understanding of disability accommodations in online learning environments, we also wish to highlight some limitations. First, there are reasons to predict that some students with disabilities might be more likely to prefer an online degree program. This could lead the population of students with disabilities online to be systematically stronger academically and more motivated to succeed. Testing this possibility would require an indicator of prior academic performance, such as high school GPA or standardized test scores, but these data are not uniformly collected at admission to the online degree program that we studied, thus we are unable to rule it out. Second, the overall percentage of students with disabilities is smaller in the online program than the in-person one. If there exist substantial numbers of online students who could benefit from disability accommodation, but who are not registered to receive them, this could have biased our comparison of online to in-person grades by disability accommodation status.

Although we explored the possible differential effects among students with different types of disabilities and found no such differences, it bears repeating that our primary results aggregate all students with any disability. It goes without saying that the nature of the barriers to academic achievement experienced by a student with reduced mobility and those experienced by a student with a learning disability are very different. The same is true within these broad categories of disability. Critically, we also cannot assume that an in-person student and an online student with the same type of disability will have the same barriers to academic success. It is also important to note that the personal experiences of individuals, even with the same type of disability, are unique [ 35 , 36 ]. Thus, we caution against making generalizations concerning all individuals who share a disability type or specific disability and acknowledge that our aggregated analyses may conceal important variability.

The other notable limitation is the use of administrative data. Although these data did allow us to examine research questions that are troublesome for survey and interview research-based approaches, the administrative data do not capture a complete picture of any one student’s experience. This is particularly true when studying students with disabilities, each of whom must be categorized within an existing category for disability type (and other demographic characteristics).

5. Conclusion

The use of online learning will certainly continue to grow among institutions of higher education. It is, therefore, essential that these institutions examine and continuously monitor how their existing disability accommodations align with the needs of students in online courses and fully online degree programs. Previous survey- and interview-based research has found that students with disabilities in online courses feel less well supported and encounter more obstacles to receiving accommodations [ 4 , 9 , 37 ]. In our study, administrative data from a fully online degree program suggests that this kind of unequal accommodation persists. While our analysis of course grades indicates that the affordances of online learning for students with disabilities may outweigh any disadvantages caused by the gaps in accommodation, there remains an obligation for administrators and faculty to ensure that students are equitably supported across both in-person and online programs. In particular, if the types of accommodations offered predate the online program, there may be gaps either due to the appropriateness of those accommodations for fully online courses or due to the practical realities of providing those accommodations to remote students. Although the details of disability accommodations will vary, we hope that the present study will offer a starting point for self-study at any institution with new or existing online degree programs and that our results will inspire these institutions to look for ways to better support their online students with disabilities.

Supporting information

S1 table. student with disability’s demographics by modality..

https://doi.org/10.1371/journal.pone.0288748.s001

S2 Table. Difference in DRC enrollment by student demographics.

https://doi.org/10.1371/journal.pone.0288748.s002

S3 Table. Complete list of accommodations in dataset.

https://doi.org/10.1371/journal.pone.0288748.s003

S4 Table. Regression results for disability type.

https://doi.org/10.1371/journal.pone.0288748.s004

Acknowledgments

We thank ASU’s Student Accessibility and Inclusive Learning Services for their support in providing access to the anonymous data analyzed in this study.

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Assistive technology for the inclusion of students with disabilities: a systematic review

• Cultural and Regional Perspectives
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• Published: 10 June 2022
• Volume 70 , pages 1911–1930, ( 2022 )

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• José María Fernández-Batanero 1 ,
• Marta Montenegro-Rueda 1 ,
• José Fernández-Cerero 1 &
• Inmaculada García-Martínez 2  

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The commitment to increase the inclusion of students with disabilities has ensured that the concept of Assistive Technology (AT) has become increasingly widespread in education. The main objective of this paper focuses on conducting a systematic review of studies regarding the impact of Assistive Technology for the inclusion of students with disabilities. In order to achieve the above, a review of relevant empirical studies published between 2009 and 2020 in four databases (Web of Science (WoS), Scopus, ERIC and PsycINFO) was carried out. The sample consists of 31 articles that met the inclusion criteria of this review, out of a total of 216 identified. Findings of this study include that the use of Assistive Technologies is successful in increasing the inclusion and accessibility of students with disabilities, although barriers such as teacher education, lack of information or accessibility are found.

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Introduction

In the educational field, students with disabilities face a set of barriers that limit their learning and achievement in different activities that take place in the classroom setting. It is essential that these students have access to the same opportunities to participate in society as their peers. In this context, digital technologies are a tool to access the curriculum. In this regard, evidence has shown that digital technologies (computers, laptops and mobile devices) have changed many students’ lives (Bond, 2014 ). Despite these changes affecting education, little attention has been paid to how students with disabilities have incorporated technologies into their daily lives (Passey, 2013 ; European Schoolnet, 2014 ). This is not surprising, given that existing research on children with disabilities is scarcely developed (McLaughlin et al., 2016 ), while generic research often excludes this sector of the student population (Connors & Stalker, 2007 ). This may be a challenge in terms of ensuring equal opportunities to access and benefit from digital technologies.

This concern to ensure equality and equity is evidenced in most of the international initiatives over the past decade, for example the UNESCO-Weidong Group project “Harnessing ICTs for Education 2030” which will, over four years, support participating Member States in harnessing the potential of ICTs to achieve ODS 4 by 2030. The United Nations also adopted, during its General Assembly on 13 December 2006, the resolution drafted by the International Convention on the Rights of People with Disabilities, in order to promote measures for research and development of disability-friendly technologies and their availability and use, including specific technical devices designed to improve the daily lives of people with disabilities.

Conceptualization

“Assistive Technology” (hereinafter AT) according to the World Health Organization (WHO), is a generic term that designates all systems and services related to the use of assistive products and the performance of services (WHO, 2001 ). Generally and according to the Assistive Technology Act of 1998, in the U.S. it is defined as “any item, piece of equipment or system, whether acquired commercially, modified, or customized, that is commonly used to increase, maintain, or improve the functional capabilities of people with disabilities” (Buning et al, 2004 , p. 98). For Lewis ( 1993 ), AT has two main purposes: on the one hand, to increase a person’s capabilities so that his or her abilities balance out the effects of any disability. And second, to provide an alternative way of approaching a task so that disabilities are compensated.

AT is proposed as an alternative for the interaction between students with disabilities and new digital devices (Emiliani et al., 2011 ), which:

Refers to the technologies (devices or services) used to compensate for functional limitations, to facilitate independent living, to enable older people and people with activity limitations to realise their full potential. Some technologies, even if not purposely designed for people with activity limitations, can be configured in such a way as to provide assistance or assistive functions when needed. The term AT covers any kind of equipment or service capable of meeting this definition. Examples include wheelchairs, prosthesis, communicators and telecommunication services. In eInclusion, AT includes, for example, equipment and services for access to information (e.g., for seeing, hearing, reading, writing), interpersonal communication and control of the environment. (p. 102)

AT is divided into low technologies, which do not use programming, such as magnifiers and pencil holding devices, and high technologies, which use programming, such as computers (McCulloch, 2004 ). Authors such as Cook and Hussey ( 1995 ) and Bryant & Crews ( 1998 ) also classify AT into two types: low or simple technology and high and complex technology. Low or simple technology has been described as equipment that is most often low cost and easy to create or obtain. These require a simplified process for operation (pencils, calculator loupes, paper communication boards, wheelchairs, etc.). Complex technology concerns equipment that has electronic technology (computers, electronic communication boards, electric wheelchairs, etc.).

To understand the role of AT regarding people with disabilities, it becomes necessary to review the concept of disability as well. In this regard, it must be said that disability has had different readings depending on the era and the predominance of health models. The contexts have been varied and even complementary, so explaining disability is a difficult task. The International Classification of Functioning, Disability and Health (ICF), published by the World Health Organization (WHO, 2001 ), is a bridge between the medical and social models, since it understands disability as the interrelationship between a person’s health condition and the environmental factors that affect his/her lifestyle. Thus, disability is understood as the circumstance of negative aspects of the individual’s interaction and its contextual factors, activity limitations and participation barriers. In the traditional medical model, a “disability” is defined as any form of impairment or limitation placed on an individual’s normal functioning, so “impairment” implies a reduction or weakening of normal functioning, and “limitation” implies a reduction of normal activity. In this way, we understand limitation as the multiple barriers that limit student learning and participation (Echeita, 2013 ).

AT is the basis for creating inclusive education systems in which students with disabilities enjoy the same training and learning as their peers who are not limited in their daily activities.

The scientific literature reports both the benefits of AT for students with disabilities and the barriers to teaching and learning processes. Regarding the possible benefits, authors such as Angelo ( 2000 ) studied how specialized technologies contribute to the development of skills that provide stimulation and support to this group of students. For Murray & Rabiner ( 2014 ), AT is able to fit instantly to a student’s level and provide instant feedback for improved learning. In addition, they support students with disabilities in performing tasks or functions that they would otherwise be unable to do (Sullivan & Lewis, 2000 ). For their part, Nelson et al., ( 2013 ) focused on improvements in academic performance and language development. Howard-Bostic et al., ( 2015 ) conducted research on the use of Multimedia Assistive Technology (MAT), finding that these tools improve the performance of university students.

NcNicholl et al., ( 2019 ) in a systematic review of AT use for students with disabilities in higher education identified four analytical themes: AT as a facilitator of academic engagement; barriers to effective AT use can hinder academic participation; the transformative possibilities of AT from a psychological perspective; and AT as a facilitator of participation. In this regard, other studies conclude that the potential use of AT for students with disabilities will promote inclusion and decrease stigma (De Witte et al., 2018 ; Asongu et al., 2019 ).

In relation to potential barriers, Byrd and Leon (2017) focused on three main aspects that prevent the inclusion and approach of students with disabilities in the use of so-called specialized Assistive Technologies: 1- AT is not available or accessible to students with disabilities. 2- High costs and precarious financing represent a limitation for the placement of AT for students with disabilities. 3- Lack of training in the use of virtual devices and platforms is the most prevalent barrier to the development of students with disabilities.

Copley & Ziviani ( 2004 ) identified limitations to their use in the field of education for people with disabilities. These include lack of suitable training and support for teachers, negative attitudes, insufficient assessment and planning processes, inadequate funding, difficulties in managing equipment and time-related barriers. Along these lines, there are many studies that have highlighted the lack of teachers’ training in the application of Assistive Technology programs (Murray & Rabiner, 2014 ; Howard-Bostic et al., 2015 ).

Purpose and research questions

AT aims to help people with disabilities overcome their limitations (Sauer et al., 2010 ). Due to the rapid development of technology, there is a need to update research results on the impact of AT for the inclusion of students with disabilities. Therefore, the purpose of this research is aimed in two directions: on the one hand, to assess the overall state of AT research to improve the inclusion of students with disabilities. On the other hand, to investigate the themes and future lines of research in this field.

The specific research questions addressed are:

Q1. What are the trends in scientific production on assistive technology for students with disabilities in the field of education? Q2. What are the findings on the use of Assistive Technology for students with disabilities between 2009 and 2020 in education? Q3. What are the limitations on the application of Assistive Technology among students with disabilities in education? Q4. What are the main lines of research in this field according to the keywords of the reviewed papers in the field of education?

A systematic review of bibliographic analysis has been carried out using analytical screening techniques and document quantification (Fernández-Batanero, Reyes-Rebollo & Montenegro-Rueda, 2019 ) in accordance with the guidelines and standards for systematic reviews of the PRISMA Statement (Preferred Reporting Items for Systematic reviews and Meta-Analyses) (Liberati et al., 2009 ), as an effort to locate all relevant scientific studies that aim to assess the impact of AT on improving the inclusion of students with disabilities. Likewise, social network analysis techniques have been used (Knoke & Yang, 2008 ) using visual representation with the VOSviewer software. This methodology enables the quantification of scientific output related to inclusion and assistive technology.

Data sources and search strategy

To carry out this review of the literature, four databases have been used to find eligible studies on Assistive Technology for students with disabilities. The databases included were Web of Science, Scopus, ERIC and PsycINFO. Consequently, the main reasons for choosing these four databases were their scientific impact and internationally recognized prestige in the academic community of the social sciences and education fields.

To obtain the articles, we applied an advanced search model using the following descriptors in the title, summary or key words fields: assistive technology (AT), inclusion and disability. To give greater accuracy to the study, Boolean operators “AND” and “OR” were incorporated into the different searches. We also tracked reference lists from relevant papers. Searches for studies were limited from 2009 to 2020, in order to extract the most current research in this field. The bibliographic search was carried out in March 2021, and obtained 741 results. After the elimination of duplicate studies, 321 articles remained for eligibility screening.

Eligibility criteria

Firstly, the PICO strategy (Population, Intervention, Comparison, and Outcome) was used to define the eligibility criteria. In this regard, we followed the recommendations of Pertegal-Vega, Oliva-Delgado and Rodríguez-Meirinhos ( 2019 ): population, phenomenon of interest, context, and study design.

The procedure for the selection of publications, in order to obtain in-depth evaluation about the validity of all included studies, was carried out through a double screening using the inclusion-exclusion criteria. Articles were restricted to peer-reviewed journal articles in the last decade. The following inclusion and exclusion criteria were used to identify study articles (Table  1 ):

Process flow of the systemactic review

Using these inclusion and exclusion criteria, we filter the publications following the recommendations for systematic reviews and meta-analyses. Figure  1 shows the PRISMA flow diagram followed for search, identification, screening, eligibility and inclusion processes (Moher et al. 2009). To increase reliability, all authors of the manuscript participated in the selection of the studies to include.

A first initial search, based on a combination of the different selected descriptors, identified 188 articles in the four selected databases. It was also completed with a manual search by reviewing the reference lists of the identified articles, selecting 28 articles. In total, 216 articles have been selected.

After a first reading of titles and abstracts, duplicate articles were removed, resulting in the elimination of 86 items. Subsequently, an exhaustive verification of the remaining 130 articles was carried out, assessing the established selection criteria, and 99 items were deleted for the following reasons: type of document (52) or inadequate context (47). Finally, 31 articles were obtained (Fig.  1 ).

Sample selection flowchart

Coding procedures and data analysis

To analyse the 31 selected studies, a data extraction table was developed to facilitate the review, which included (a) identification of authors and year of publication, (b) participants’ information, (c) methodological design of the study, (d) results and AT included in the study, (e) number of citations of article, and (f) country, resulting in a database that has subsequently been presented descriptively (Appendix 1).

This section reports the results, both quantitative and qualitative, obtained in this study. The data are shown in the following sections in response to each of the research questions stated above.

Overview of research on Assistive Technology for students with disabilities

This systematic literature review has drawn 31 articles from the different databases analysed. The review focused on scientific articles produced between 2009 and 2020, which aimed to evaluate the impact of the use of assistive technology in the education of students with disabilities. As see in Fig.  2 (below), where the distribution of the relevant studies published during this period is shown, there is an increasing trend in research in this field. Looking at the analysis of the year of publication of these studies, it is shown that the publication trend starts from the year 2017 to the present. Between the years 2009–2016 there was a small number of articles published. However, from 2017 onwards, an increase in the number of publications on this topic can be observed.

Distribution of articles by year

Figure  3 displays the number of studies provided by each country. Looking at the location of the countries where these studies analysed were carried out, we can show that they were mainly carried out in the USA (n = 16), followed, although less substantially, by Brazil (n = 4) and Turkey (n = 3). The figure shows that research attracts interest in countries all over the world.

Distribution of the articles analysed by country

The analysis of the study design used does not provide an overview of how research in this field is being approached. These data indicate that, in terms of study design, 58.06% of the studies are conducted qualitatively. Quantitative studies are less common (38.71%), while only one study reviewed is classified as mixed (3.23%) (Fig.  4 ).

Type of methodology used

Research into the use of assistive technology applied to any stage of education has been undertaken. Thus, the data show that the educational level with the highest application of assistive technology is secondary education (41.94%), followed by primary education (38.71%). Studies aimed at the university stage are lower (12.90%). In the case of Early Childhood Education, there are very few (6.45%).

Citation analysis is one of the types of research that determine the impact of publications in scientific processes (Cañedo Andalia, 1999 ). In this way, the quality and impact of the research in this field is not yet relevant, because most of the publicationshave received between 0 and 5 citations (70.97%), 19.35% between 5 and 10 citations and only 9.38% have received more than 10 citations.

Benefits of using Assistive Technology for students with disabilities

Among the type of Assistive Technology used for this group of students, we find a wide variety of tools. Among them, the use of Web 2.0 stands out (28.57%), such as the use of social networks, websites, browsers…; mobile learning (25%), among which we find the Tablet, the iPad or the mobile phone; or the use of hardware or software (21.43%) (Fig.  5 ).

Main Assistive Technology for student inclusion

Considering the articles reviewed, these tools are being used mainly with visually impaired students (25%), followed by hearing impaired students (21.43%) and physically impaired students (14.29%). Students with autism (10.71%), intellectual disability (7.14%) or behavioural disorder (3.57%) are less likely to be used. The rest of the publications (17.86%) do not specify the type of disability (Fig.  6 ).

Students using assistive technology

AT provides students with a set of benefits such as inclusion (20.95%) and accessibility (20.95%) to school, as stated by the articles selected in this review. Among other benefits, we find that they improve the teaching-learning process (13.51%), the development of autonomy and independence (18.92%), the acquisition of social skills (11.49%), the participation (9.46%) and the motivation (4.73%) of students (Fig.  7 ).

Benefits of the use of Assistive Technology

Limitations of the use of Assistive Technology with students with disabilities

All the articles reviewed point out the importance of the use of Assistive Technology as a required tool for students with disabilities at school. However, there are still different challenges that schools must overcome in order to apply these tools with their students. Among the main difficulties found, there are mainly the need for teacher training and education (42.86%), as well as the difficulties of access to them (32.14%) (Fig.  8 ).

Difficulties in the use of Assistive Technology

Lines of research on the use of Assistive Technology with students with disabilities

In order to analyse the research topics addressed in the literature in this field, an analysis of the relationships between the automatically extracted keywords or Key Words Plus (KW+) from the 31 studies analysed was carried out using the VOSviewer programme. Using the process of analysing the network map, three main themes were identified through analysis in the data. These were: “AT as an enabler of inclusion and participation” (cluster 1), “barriers to effective use of AT” (cluster 2) and “possibilities and benefits of AT” (cluster 3).

Therefore, a total of 45KW + has been extracted. In Fig.  9 , the 3 groups or clusters can be clearly observed, which have been generated according to the similarity between them. The size of each node and their distance from each other sets the relationship between them.

Labelled bibliometric map

The 3 thematic clusters that defined the main research topics in this field are:

Cluster1: identified in red, this is the main theme on which this study focuses, i.e. the impact of Assistive Technology on the inclusion and accessibility of students with disabilities. It can be noted that this cluster includes terms such as assistive technology, inclusion, technology, resource, impact, software, web, tablet, support, social technology, and robotic.

Cluster 2: it appears in blue, and it is related to the barriers or obstacles that hinder the application of Assistive Technology in education. In this group some of the most prominent elements are teacher training, education, higher education, society, school, context, training, and evidence.

Cluster 3: is shown in green. This group stands out for the benefits of applying these tools to students with educational needs. It also refers to the possibilities offered by Assistive Technology to make accessible education for all. It highlights items such as: autonomy, participation, social skill, access, assistant teacher, inclusive education, motivation, disability, and skill.

On the other hand, we include the bibliometric density map where it is shown the relevance of the analyzed keywords. Therefore, the following cores can be highlighted (Fig.  10 ):

In the middle zone of the map (yellow color) are placed, due to their importance and co-occurrence, those most relevant keywords in the scientific production about Assistive Technology for students with disabilities (student, disability, assistive technology, teacher).

In the peripheral zone of the map (colors that tend to green), evidence shows less interest and level of co-occurrence in the current scientific production (impact, inclusive education, social technology, experience, assistant teacher).

Bibliometric map tagged

Discussion and conclusions

This review explores the impact of scientific production related to Assistive Technology on the inclusion of students with disabilities published between 2009 and 2020. According to our findings, these tools emerge as suitable instruments for both accessibility and inclusion of students, as well as for meeting their educational needs during their learning process (Clouder et al., 2019 ; Satsangi et al., 2019 ).

Thus, among the papers reviewed, several noteworthy findings will be discussed, in response to the research questions proposed in this study. First, considering the first question on trends in scientific production over time (RQ1), we can mention that there are possible trends and indications that suggest an increase in the use of AT in education in the last few years. Research in this field over the last decade is not very relevant; however, from 2017 to the present, a progressive increase has taken place. We can also highlight that the impact and repercussion of these studies is not very high, since most of the articles have a very low citation rate. The more frequently a paper is cited, the more often the scientific community recognises the influence or impact of the cited topic (Cañedo Andalia, 1999 ). The scarce existence of scientific literature and its low impact is one of the main problems that may hinder the implementation of these tools in the classroom, because this field is underdeveloped. Similarly, the limited existence of scientific literature on the use of AT for the care of students with disabilities makes it difficult to answer the research questions posed. Even so, the findings help us to lay the foundations for working to improve the education of these people, both by offering technological solutions and by working on training and awareness-raising in this regard (Molero-Aranda et al., 2021 ).

With respect to the countries that concentrate the greatest scientific production in this field, it should be said that AT is of world-wide attention, so that AT research has been developed in different countries, mainly in the United States, followed by Brazil and Turkey. This fact enables a reflection on future research in order to know if the country and its context affect the use of these technologies for the inclusion of students.

In relation to the research designs that prevail in the studies analyzed, it should be noted that these mainly show a qualitative approach, with observation and interviews prevailing as data instruments, followed by quantitative ones.

The second research question (RQ2), related to the results of using AT with students with disabilities, aims to synthesise the positive impacts in terms of the improvements or benefits they bring to students. AT has a significant impact on academic engagement. The use of these tools was found to improve the academic performance of students with disabilities (Fortes Alves & Pereira, 2017 ; Tamakloe & Agbenyega, 2017 ; Bouck et al., 2020 ; Sivakova, 2020 ). Some articles also reported the benefits of AT for the development of autonomy and participation (Harper et al., 2017 ; Mercado de Queiroz & Presumido Braccialli 2017 ; McNicholl et al., 2020 ). The results show an increase in the acquisition of social skills (Ari & Inan, 2010 ; Murry, 2018 ). Finally, it is worth mentioning that these tools promote motivation and increase students’ attention (Paula, 2003 ; Arpacik et al., 2018 ; Bondarenko, 2018 ). The results analysed point out that there are different types of Assistive Technology used according to the functionality that they want to provide, highlighting mainly the use of Web 2.0. Although there are still digital gaps, most schools and teachers have access to the Internet which means that they can use this available and low-cost resource, and it can support both student inclusion and learning (Lyner-Cleophas, 2009; Kamali Arslantas et al., 2019 ; Ok & Rao, 2019 ). Mobile learning also stands out (25%), including the iPad or smartphone. These devices are very useful because they are small and portable, and they enable the installation of relevant applications for these students (Ismaili & Ibrahimi, 2017 ; Brinsmead, 2019 ), a fact that has resulted a trend in the use of these tools in recent years, agreeing with previous studies (Fichten et al., 2014 ). In this way, we can outline that the most generic resources are mainly used (McNicholl et al., 2020 ). The use of other useful resources to encourage the participation of this group of students using hardware or software should also be highlighted (21.43%) (Emcarnaçao et al., 2017 ).

These tools are mainly relevant for visually impaired students, followed by hearing impaired and physically handicapped students (Quinn et al., 2009 ; Ferreira et al., 2013 ; Ismaili & Ibrahimi, 2017 ). Thus, it can be stated that AT is successful and necessary to ensure the inclusion of this population in the classroom; however, although it has many benefits for all students, its use also involves challenges and barriers associated with the use of AT in the classroom. These barriers can hinder the effective use of AT.

In this regard, in response to the third research question (RQ3), all articles identified situations where AT cannot be used effectively. These include inadequate training in the use of ATs with learners with disabilities by teachers or difficulties in accessing these tools (Copley & Ziviani, 2004 ; Johnstone et al., 2009 ; Coleman et al., 2015 ; Alammary et al., 2017 ; Ismaili & Ibrahimi, 2017 ; Byrd & León, 2017 ). Teacher training in AT is related to improved student academic performance by being able to select the most appropriate tool to meet the needs of their students (Jones & Hinesmon-Matthews, 2014 ; Laloma, 2005 ; Malcolm & Roll, 2017 ; Yankova, 2019 ). Difficulties of access hinder the implementation of AT in education. These are mainly associated with economic factors, lack of adequate supports or lack of funding (McNicholl et al., 2019; Atanga et al., 2020 ).These tools may effectively support student inclusion by providing adaptations, but their high cost, because some resources such as the iPad are quite expensive, limits their access to wealthier consumers (Flanagan et al., 2013 ; Koch, 2017 ; Brinsmead, 2019 ). As a result, it is clear that rural areas have less resources and greater difficulties to access them than urban areas (Davis et al., 2013 ).

The main research topics in this field (RQ4) taking into account both the review of the articles and the analysis of the bibliometric maps helped to identify the different main topics involved within this field of research. Firstly, the importance of the use of AT as a facilitating element for school inclusion is highlighted, providing access for all students to education, including those with some kind of disability or educational need. Secondly, it highlights the benefits of implementing Assistive Technology with students with disabilities. Finally, it is related to the barriers or obstacles that hinder the application of Assistive Technology in the education of students with disabilities. As well as the possibilities offered by Assistive Technology to access education for the whole population. Research and applications of the use of assistive technology with learners with disabilities have been conducted around the world. However, despite these efforts, it has not been possible to integrate the appropriate tools to satisfy the main needs of these students. This review has identified important directions for future research and possible ways in which schools should consider integrating AT into the learning of students with disabilities. Teachers have a primary role in promoting the use of ATs, therefore, in order to achieve inclusion of students with disabilities, teacher need to acquire the necessary skills and competences (De Sousa, 2014 ; Roque, Perreira, Neto & Macario, 2018 ; Ahmed, 2020 ; Viana & Fontoura Teixeira, 2019 ; Arori, Al Attivah, Dababneh & Hamaidi, 2020 ). The results show that many of the generic devices (smartphones, digital board...) are used as AT, due to the fact that many offer accessibility features. Looking ahead, it is a need to integrate universal design into teacher technology training to maximise the benefits for all learners (Messinger-Willman & Marino, 2010 ).

Implications for further research

The limitations found have been addressed taking into account the results of this review because, although it has been possible to note how current research in this field is developing worldwide, it would be useful to identify the most appropriate AT to meet the needs of students according to their disabilities, as well as to promote training plans for teachers in order to implement these tools properly in the classroom.

In this way, researchers should explore the use of AT in relation to the type and degree of disability of learners. In this sense, it is also necessary to investigate effective teaching and learning strategies for these learners. In order to do so, it is necessary for teachers to have an adequate level of training, so that they can apply these tools in the classroom.

Limitations

A limitation of this paper is that the selection of the articles analyzed is restricted to the databases selected by the authors, although they are the most important for the educational scientific community. Therefore, in future research it would be desirable to study this topic with a wider and more extensive scope, including other articles from journals indexed in other databases with less scientific recognition, but which may include good practices.

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Fernández-Batanero, J.M., Montenegro-Rueda, M., Fernández-Cerero, J. et al. Assistive technology for the inclusion of students with disabilities: a systematic review. Education Tech Research Dev 70 , 1911–1930 (2022). https://doi.org/10.1007/s11423-022-10127-7

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How One School Fosters Belonging for Students With Disabilities

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Fostering a sense of belonging in school takes a lot of intentional effort, especially when it comes to students with disabilities, who have traditionally been excluded from many mainstream classes and activities.

That’s according to a principal who has dedicated her career to that cause.

Cathi Davis, principal of Ruby Bridges Elementary School in Woodinville, Wash. , near Seattle which opened in 2020, runs a school that is designed so students with disabilities spend nearly all of their time in general education classes learning alongside their peers, rather than being pulled out for specialized instruction.

It’s one of 16 schools in Washington state that partner with the Haring Center for Inclusive Education at the University of Washington with the goal of demonstrating that all students benefit when schools are intentionally designed with the needs of students with disabilities at the forefront.

“We did a lot of planning to think about how we could really facilitate an opportunity for students to see themselves throughout the school, and to know that we thought of them in the design of the school,” Davis said during a webinar hosted by Education Week on May 23. “Really, that was less about architecture—that wasn’t about paint, that wasn’t about the parking lot. It was about our mindsets and our heart work that we were doing as a staff to think about how belonging could come off the page for each and every student.”

The approach diverges from the traditional K-12 education model through which students with Individualized Education Programs, or IEPs, are pulled out of classes with their peers into separate settings where they receive individualized or small-group instruction.

Ruby Bridges’ approach helps students with disabilities form relationships with their classmates and others in their school, and helps general education students build empathy and compassion. Several studies over the years examining these more inclusive practices have found either neutral or positive effects on all students’ performance in core subjects like math and reading.

“We know that all students benefit from that general education access,” Davis said. “We know learning’s not linear, and I think more and more we understand that our students are more engaged when learning is tailored to fit their needs and their strengths.”

In Ruby Bridges classrooms, all students have access to supports traditionally outlined in students’ IEPs or 504 plans, like the ability to take breaks when feeling overwhelmed, or the opportunity to learn in a small group with the teacher, while others might work independently on a tablet with headphones on.

During one recent phonics lesson she was observing, Davis recalled one student who was participating in a group lesson, but was bouncing on a trampoline at the same time to help regulate their senses.

“It’s that sense of truly being welcomed into a community, not like, ‘You get to be here, too, but over there,’” Davis said. "…But rather, we are all being together and kind of framing our identity around what that means for us.”

One of the keys to how Ruby Bridges works is its staffing model, which emphasizes collaboration.

For example, rather than having a designated paraprofessional assigned to each student who needs extra support, paraprofessionals work with different students all the time, meaning they could be providing math support in the morning and teaching phonics lessons to English learners in the afternoon.

In practice, the adults in the school are encouraged and required to work together to support students’ learning. “No one person is independently trying to support all of the learning of any one student,” Davis said.

“We’re looking at, what do kids need in this moment to be successful in their learning, and how do we support that best with the right person at this time?” Davis said. “How can we collectively share the load?”

For more on the discussion of creating communities of belonging for all students—including those with disabilities—and its academic and social benefits, check out the video above and Education Week’s recent special report about building strong student-school connections.

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A comparison between the use of two speech-generating devices: A non-speaking student’s displayed communicative competence and agency in morning meetings in a compulsory school for children with severe learning disabilities.

May 21, 2024

By Skip Ryan

Tegler, H., & Pilesjö, M. S. (2023). A comparison between the use of two speech-generating devices: A non-speaking student’s displayed communicative competence and agency in morning meetings in a compulsory school for children with severe learning disabilities. Child Language Teaching and Therapy , 39 (2), 175–194. https://doi.org/10.1177/02656590231174604

This ethnomethodological multi-modal conversation analysis study examined the communicative competence and agency of a 19-year-old student with cerebral palsy and intellectual disabilities during morning meetings at school in two conditions, using a single-message or a multi-message speech generating device (SGD). When provided a single-message device, progressivity was preserved in the student’s ability to respond in a timely manner but his agency was limited because there is only one option to produce on the SGD. When provided a multi-message device, progressivity was challenged because of prolonged composition time. While a multi-message device increased agency relative to a single-message device, the student’s agency was still restricted due to the fact that options were restricted due to his inability to access them with eye-gaze technology. When the student was assigned the role of “teacher”, he was provided more opportunities for taking a turn, displaying communicative competence, and exhibiting agency than when he was assigned the role of “student”. A variety of adult behaviors were attributed to be scaffolding practices: moving the SGD to signal it as the preferred response, making the next contribution relevant and well-timed by pointing to the preferred symbol, holding the response space for the aided speaker by dealing with interrupting peers in quiet side-sequences, providing deontic constructions for other-initiated self-repairs after identifying a contribution as problematic, and using meta-cognitive descriptions to hold space for the student’s turn (e.g., “difficult to choose”).

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More from Center for Literacy and Disability Studies

• Context-situated communicative competence in a child with autism spectrum disorder.
• Mobilizing device-mediated contributions in interaction involving beginner users of eye-gaze-accessed speech-generating devices.
• Creating a response space in multiparty classroom settings for students using eye-gaze accessed speech-generating devices.

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A task force of faculty, students, and staff has created a report of recommendations aimed at building a more inclusive and supportive campus community for students with disabilities. Changes will allow students to better leverage the many resources available on campus and instructors will receive more coordinated support for the delivery of accommodations.

Some implementation steps will begin next year, including more prominently highlighting disability in the university’s Inclusion, Diversity, Equity, and Access in a Learning Environment (IDEAL) initiative and the creation of a centralized office tasked with providing seamless and integrated services.

“The task force report is not meant to serve as a one-size-fits-all solution to supporting and advancing the well-being of students with disabilities at Stanford,” said task force co-chair Paul Fisher, professor of pediatrics and of neurology and neurological sciences. “Rather, we hope it serves as a high-level set of recommendations that set the course for changes that will ultimately improve the lives of students on our campus. Some of these will be things we can accomplish quickly, and others will take more time.”

Charged by Susie Brubaker-Cole, vice provost for student affairs, and Patrick Dunkley, vice provost for institutional equity, access, and community, the task force was co-chaired by Fisher and Susan Weersing, associate dean for graduate and undergraduate studies in the School of Humanities and Sciences.

“I want to recognize the incredible and vital work this committee has done over the past year,” Brubaker-Cole said. “It is because of their hard work and commitment that we now have a road map for creating a more inclusive and accessible environment for every student, regardless of disability.”

While the task force’s work was primarily focused on the student experience at Stanford, Dunkley said he hopes the recommendations will serve as a reference point for future staff accessibility efforts.

“It goes without saying that staff are a key component of our community here at Stanford, and caring for the needs of staff is vital to creating a community that is truly inclusive, accessible, and equitable,” said Dunkley. “We were intentional in including staff on the task force as a means of building a bridge between these efforts and the support of our staff. Our plan is that some of the changes suggested in this report will be applied to staff as well.”

What students had to say

Working closely with Institutional Research & Decision Support, the task force compiled demographic and survey data on the disability community and met with a broad set of students, staff, and faculty stakeholders. Members interviewed students with disabilities and referenced experiences among themselves and research previously conducted by the disability student community.

Among the key demographic findings was a substantial increase in students registering with the Office of Accessible Education, and the most significant growth in accommodation type has been among students with registered psychological disabilities such as anxiety and depression or sleep disorders. Still, some students shared with the task force that they choose not to register with OAE for several reasons, including fear of stigmatization, a lack of understanding of what is required to receive accommodations, or a lack of resources to obtain the required medical documentation.

Throughout the task force’s work, six key themes emerged:

• A need to centralize support for students and instructors into one office
• A recognition that Stanford has staff and faculty with significant expertise in providing accommodations and support
• A recognition that efforts are at times dependent on the dedication of community members acting within a system in need of improvement
• A recognition that instructors and academic departments need more and different types of support in delivering student accommodations
• A recognition that students are taking on an added burden of changing campus culture
• A lack of clarity around leveraging resources and the continued need for students to self-advocate

“Every student deserves to learn and live within a campus community in a meaningful, enriching, and equitable way,” Dean of Students Mona Hicks said. “And while Stanford does have many programs and systems in place to support students with disabilities, it can be difficult to know where to start. Having a more centralized approach could help alleviate some of the stress students feel navigating those resources.”

Following the six themes, the task force recommended changes, which fell into three broad categories: systemic changes, academics and academic support, and community life.

In the coming year, Brubaker-Cole and Dunkley’s teams will begin implementing the task force’s key recommendations, beginning with highlighting disability as a core piece of the university’s IDEAL initiative.

“We must fully integrate disability into IDEAL and recognize the need for change on our campus,” Dunkley said. “We must ensure that all members of our campus community feel like they belong and are supported at Stanford, regardless of their intersecting identities. Diversity and inclusion are critical to our research and educational missions, and we must ensure all in our community have access to the many opportunities and benefits available here.”

In addition, work will begin immediately to create one central office, comprising the many offices already supporting students with disabilities, that would be accountable for the coordination and delivery of services. Staff who support students already and many members of the task force will be crucial in helping chart the next steps, Brubaker-Cole said. There will also be a national search for a leader of the office. The central office will help ensure a singular point of contact for students with disabilities and create a central entity responsible for responding to needs and opportunities in the student community.

“This office will also be responsible for ensuring the continued implementation of the task force’s recommendations because we recognize our work must continue to evolve as the needs of our students change,” said Brubaker-Cole. “We want to continue increasing access to physical spaces and developing the necessary support students need beyond the classroom. This will include continuing to develop community space and programs such as the DisCo, which has been an integral place for community building and support for our disability community on campus.”

For Stanford students interested in learning more, the full report and space for feedback are available on the VPSA website , and updates on the implementation of these recommendations will be provided regularly.

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Berkeley’s Bayhill High School has effectively catered to students with learning differences for 16 years. Now expanding its reach, Bayhill is extending its services to K-12 students throughout the Bay Area, opening the Bayhill Literacy & Learning Center this June.

The new center will offer flexible learning plans catered to students’ unique needs and schedules. Summer, fall, and winter sessions are offered both virtually and on-site. 

“I feel that the center is a natural extension of our mission to educate students with learning differences,” said Donna Austin, executive director of the center. “Offering remediation services a few times a week is far more accessible to some families than finding a private school for learning differences. Students tend to be happier if they can stay in their current school while improving their literacy skills.”

The most common learning disability is dyslexia, which affects 10-20% of school-aged children. Despite its prevalence, few truly understand this neurological language-based disorder. 

According to the International Dyslexia Association, dyslexia is characterized by difficulties with fluent word recognition, decoding and spelling — typically resulting from phonological deficits that are not related to cognitive abilities. These difficulties can impact  students’ reading and comprehension, often leading to feelings of frustration. 

A group of teens from Bayhill High School met recently to discuss their experiences as students with dyslexia. Before they were diagnosed, they said, they had to re-do work repeatedly until it was done correctly, were kept after class or in during breaks to complete their work, or were laughed at when they read out loud in class. 

Once they were diagnosed with dyslexia, the solutions weren’t always helpful or happy.  Some had to leave schools that they missed. 

They said that their individualized education plans and other needs were not always fully understood, even by well-intentioned individuals. 

“It was kind of weird,” said one student. “I just got put into a group with other students and they did all the work. I could’ve done the work too — I probably would’ve been less bored.”

Learning with a disability presents a student with unique challenges, never mind having had to navigate the additional pandemic, large class sizes of diverse learners, increased demands on teachers, non-school related hobbies and interests, and, of course, growing up. So how does one effectively approach remediation? 

Those same students reported that Bayhill High School has effectively met their unique needs, which is the goal of the new Bayhill Literacy & Learning Center. 

Bayhill educators have found that the most effective application of research-based interventions is an individualized approach,  tailoring services to student needs, prioritizing one-on-one learning opportunities, and ensuring that services are flexible to continue to meet student needs throughout remediation.

Sponsored by Bayhill Literacy & Learning Center

At Bayhill Literacy & Learning Center, we believe all students can reach their full potential with access to the right research-based intervention, specifically tailored to their unique strengths and challenges. 

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Practical Applications of AI in Education for Accessibility

2024-05-28 | By Orcam Staff

The intersection of artificial intelligence (AI) and education is a rapidly evolving field. It holds immense potential for transforming learning experiences, particularly for students with diverse needs.

AI in education for accessibility is a topic of growing interest. It focuses on leveraging AI tools and solutions to enhance accessibility in learning environments.

This article delves into the practical applications of AI in education. It highlights how AI is breaking down barriers and creating inclusive learning spaces.

We will explore various AI tools that are making education more accessible. From real-time captioning to adaptive learning platforms, AI is revolutionizing the way we approach education.

We will also touch upon the ethical considerations and data privacy issues surrounding the use of AI in education.

Join us as we navigate the exciting landscape of AI in education for accessibility. Discover how AI is shaping the future of inclusive learning.

Understanding AI in Education for Accessibility

AI in education means using smart computer programs to improve teaching and learning. These programs can adjust lessons to fit each student's needs.

Using AI in education helps make learning more inclusive and accessible, especially for students with disabilities.

The following are some of the ways AI is being used to enhance accessibility in education:

Providing real-time captioning and transcription services

Creating adaptive learning platforms that adjust to individual learning styles

Developing assistive technologies for visually and hearing-impaired students

The Significance of AI for Learners with Disabilities

AI has the potential to revolutionize education for learners with disabilities. It can provide customized learning experiences that cater to individual needs and abilities.

For instance, AI tools can convert text to speech for visually impaired students. They can also provide real-time captioning for students with hearing impairments.

These AI tools help make learning easier and more accessible for students with disabilities, allowing them to join in and learn just like their classmates.

Overcoming Educational Barriers with AI

AI is playing a crucial role in overcoming educational barriers. It is helping to create a more inclusive and equitable learning environment.

AI-powered adaptive learning platforms are online tools that change how they teach based on how a student learns best.

They can provide personalized learning pathways that cater to each student's strengths and weaknesses.

Moreover, AI can facilitate language translation and support English as a Second Language (ESL) learners. This can help break down language barriers and make education more accessible to all.

AI Tools Enhancing Learning Support

AI tools are playing a pivotal role in enhancing learning support. They are providing innovative solutions to address the diverse needs of learners.

One of the key areas where AI is making a significant impact is in real-time captioning and transcription services. These tools are particularly beneficial for students with hearing impairments.

AI is also revolutionizing assistive technologies for visually impaired students. It is helping to create more inclusive learning environments.

Moreover, AI is at the forefront of developing adaptive learning platforms. These platforms are transforming education by providing personalized learning experiences.

Real-time Captioning and Transcription Services

AI-powered real-time captioning and transcription services are a game-changer in education. They are making learning more accessible for students with hearing impairments.

AI tools can add captions to live classes and discussions right away. They can also turn spoken words into written text, helping students keep up with the lessons.

By providing real-time captioning and transcription, AI is ensuring that all students can participate fully in the learning process.

Accessibility Technology for Visual and Hearing Impairments

AI is playing a crucial role in developing accessibility technologies for visually and hearing-impaired students. These technologies are enhancing accessibility and inclusivity in education.

For instance, AI-powered tools can convert text to speech for visually impaired students. They can also provide audio descriptions for visual content.

Similarly, AI can enhance the learning experience for students with hearing impairments. It can provide real-time captioning and sign language interpretation.

These AI solutions are not only enhancing accessibility but also empowering students with disabilities to participate fully in the learning process.

Adaptive Learning Platforms and Personalized Education

AI is at the forefront of developing adaptive learning platforms. These platforms use AI algorithms to adjust to individual learning styles.

They can analyze a student's performance and provide personalized learning pathways. This can help cater to each student's strengths and weaknesses.

Moreover, these platforms can provide immediate feedback and assessment. This can help students understand their progress and areas needing improvement.

By providing personalized and accessible education, AI is helping to create a more inclusive and equitable learning environment.

Ethical Considerations and Data Privacy in Educational AI

As AI continues to transform education, ethical considerations and data privacy have become paramount. These issues are critical to ensuring the responsible use of AI in education.

AI systems often require large amounts of data to function effectively. This data can include sensitive information about students' learning habits and performance. Therefore, it's crucial to have robust data privacy measures in place.

We need to make sure AI is used in a fair and open way, with clear rules to protect everyone's privacy. These principles can help ensure that AI tools are used to enhance learning and not to disadvantage or discriminate against certain groups of students.

Case Studies: AI's Impact in Educational Settings

AI's impact on education is not just theoretical. It's already being felt in classrooms around the world. Let's explore some case studies that highlight the transformative power of AI in education.

Supporting ESL Learners and Language Translation

AI has been a game-changer for English as a Second Language (ESL) learners. Tools like Microsoft's Immersive Reader use AI to translate text into different languages, making content more accessible for non-native speakers. This technology is helping to break down language barriers in education.

AI-Driven Analytics for Student Progress

AI is also revolutionizing the way we track student progress. For instance, AI-powered platforms like BrightBytes analyze student data to provide insights into learning patterns. This allows educators to identify areas where students may need additional support, enhancing the learning experience.

The Future of AI in Education and Accessibility

The future of AI in education and accessibility looks promising. As technology continues to evolve, we can expect to see even more innovative AI solutions that enhance learning for all students.

However, it's important to remember that AI is not a magic bullet. It's a tool that can be used to improve education, but it's not a substitute for good teaching and supportive learning environments.

Challenges and Limitations of AI in Education

Despite its potential, AI in education also faces challenges. One of the main issues is the digital divide. Not all students have access to the technology needed to benefit from AI tools.

Moreover, there are concerns about data privacy and the ethical implications of using AI in education. These issues need to be addressed to ensure that AI is used responsibly and effectively.

The Road Ahead: Potential Developments in AI for Education

Looking ahead, we can expect to see AI playing an even bigger role in education. From personalized learning pathways to AI-powered tutoring systems, the possibilities are endless.

However, for these developments to be successful, it's crucial that educators, policymakers, and AI developers work together. By collaborating, we can ensure that AI is used to create inclusive, accessible, and effective learning environments for all students.

Conclusion: Embracing AI for Inclusive Learning

In conclusion, AI holds immense potential to revolutionize education and make it more accessible. It's a powerful tool that can help overcome barriers and create inclusive learning environments.

However, it's crucial that we approach AI with a critical eye, ensuring it's used ethically and effectively to truly enhance education for all.