Increasing Social Communication of Students With Intellectual Disability in Rural College Classrooms

Participants

Two postsecondary students with ID (Zion and Tori) and three peer partners without a disability (Adrian, Tenley, and Piper) participated in this study. Zion and Tori met the inclusion criteria of (a) having a primary diagnosis of ID, (b) enrolling in a postsecondary program in a rural community, (c) attending at least one college course throughout the semester, and (d) having the need to improve social communication as reported by teachers and/or parents. After Zion and Tori and their guardians signed the consent forms, their corresponding peer partners who attended the same college courses and sat in close proximity were invited to participate in the study. At the start of the semester, the PSE program director selected and assigned peer partners based on areas of shared interest and schedules. Each peer partner also provided consent on a voluntary basis.

Zion, a 21-year-old White male in his third year of the postsecondary college program, attended a 2D Art course and worked at a dining hall on-campus and at a community aquatics center off-campus. In previous semesters, he took physical education courses (Team Sports and Cooperative Games) and worked at Chick-Fil-A as a dining room assistant and at a local sheriff’s office completing various jobs. His interests included drawing, cleaning, swimming, caring for his dogs, and playing video games. Some of his areas of improvement were learning to respond appropriately when given feedback from teachers, managers, and job coaches and increasing the number of tasks completed at work.

Tori, a 21-year-old White female in her third year of the postsecondary college program, attended an Introduction to Special Education course and worked at a dining hall on-campus and at a veterinarian clinic off-campus. She hoped to become a special education paraprofessional or veterinarian assistant one day. She took University 100 and an art course during previous semesters. She enjoyed bowling, playing games, and crafting during her free time when she was not studying and practicing for her driver’s license. Her goals included increasing (a) comfort in hearing her own voice and (b) the number of tasks she completed at work.

Both Adrian and Tenley were 21 years old and graduating in the spring as a fourth-year senior. Adrian, a White male, declared recreational therapy as his major and had no prior experience working with people with a disability. Tenley, a multiple race female majoring in English, had 1 year of experience supporting individuals with a disability at college. Piper was a 20-year-old White female majoring in art. She was in her second year at the college and did not have prior experience or training working with people with disabilities. Adrian and Piper supported Zion in art while Tenley supported Tori in her special education course.

Settings

We conducted the study at a liberal arts university with more than 9,000 students located in a rural area of a southeastern state in the United States. The university housed a postsecondary program as a continuation of high school for 18- to 22-year-old students. All students who attended this PSE program had graduated from high school but were still eligible for services under Individuals with Disabilities Education Act. The program had approximately 10 students with a disability, one program director, and many paid and volunteer peers each year. It offered both inclusive college courses and separate, self-contained recreational and music therapy courses over 4 years, along with paid and voluntary work experiences on- and off-campus. The PSE program served as the primary college experience for these students. All students in the PSE program lived locally with their families and came to campus daily.

Zion’s 2D art course met twice a week for 2 hr and included 17 students and one adjunct instructor. The students sat around a large conference table with enough space to work on art projects and spread out their materials and supplies. His peer partners sat on each side of him. After brief lectures, the instructor assigned multiweek drawing and/or painting projects followed by student presentations and peer critiques. The majority of class time was devoted to project work time.

Tori had 26 classmates and one adjunct instructor in her introductory to special education course, a 75-min course that took place twice a week. The classroom included five rows of tables. Tori sat beside her peer partner in the third row with her peer partner at the end of the table. For the majority of class time, the instructor lectured on the different disability categories. Occasionally, class sessions included small group activities.

The researchers, former special educators with data collection experience as teachers and research interventionists, collected all data in the college classrooms by sitting off to the side but close enough to hear and see the student and peer pairs. Peer training occurred at a convenient location for the peer. The researchers trained Adrian and Piper separately in a student lounge area in the art building, and the researchers trained Tenley in one of the researcher’s office in the education building.

Materials

During peer training, the researchers provided the peer partners with a handout on the goals, strategies for increasing communication, and ideas for conversation topics. During data collection, we used a data collection sheet and Invisible Clocks II (Time Now, 2020) that vibrated every minute to assist with the interval data recordings.

Data Collection

We collected data through direct classroom observations using partial interval recording. We divided the observation period into 1-min intervals and recorded student interactions and communication functions. We coded an interaction as any verbal or nonverbal communicative behavior (i.e., initiations or responses) produced by the student toward their peer partner. We defined an initiation as the student asking a question, making a comment, or producing a nonverbal behavior (e.g., raising a hand for high five) that evoked a response from the peer partner. Consequently, we defined a response as the student immediately communicating after the peer asked a question or made a comment through the use of verbal or nonverbal communication (e.g., head nod and thumbs up). When an interaction occurred, we also coded the communication function (i.e., expressing academic- or social-related information). We defined academic topics as discussing course content or assignments (i.e., art for Zion and special education for Tori) and social topics as any non-course-related topics (e.g., evening activities, job-related conversations, and sports). In addition, we coded if three or more turns took place during multiple consecutive interactions, our primary dependent measure. We defined three turns as three or more consecutive reciprocal exchanges of initiations and/or responses produced by the student. We coded a new interaction when a pause of 5 s or more occurred. At the beginning of each interval, we recorded the class format (large group, small group [2–8 students], independent work, no instruction, or gone from the classroom) and proximity of the student to their peer partner, other peers, and instructor (within 1 m).

The first author trained the second author on the data collection procedures by explaining the data collection form and definitions and then by watching videos of students socially interacting. They practiced collecting data until they reached 90% or above agreement. They watched three different videos (10–15 min in length) to achieve this criterion.

Research Design

We used a single-case multiple baseline design across student and peer pairs to evaluate the effect of peer training on student social interactions (Ledford & Gast, 2018). By using this design, we attempted to control for possible threats to the internal validity of the study. First, we controlled for history and maturation through the staggered introduction of the intervention across different student pairs. Each baseline condition included at least four sessions with a stable or decreasing pattern of data. After the first participant pair moved into the intervention condition and made gains, the second pair received the intervention if they had stable baseline data. This process continued until all participants received the intervention. We used three or more communicative turns as the primary dependent measure, although other dependent measures were collected. We were interested in expanding the student participants’ current communication skills through turn-taking as reciprocity is a measure of quality interactions (Carter et al., 2017). Second, we controlled for adaptation threats (i.e., impact of unfamiliar partners) by recruiting peer partners who already sat with and knew the student since the beginning of the semester to participate in the study. Third, the collection of interobserver and procedural reliability data strengthened the internal validity of the results. Finally, we demonstrated the external validity through the replications of the intervention effects across multiple student–peer pairs; however, more research will be needed in the future to expand the external validity.

This research design allowed us to evaluate the effect of peer training on social communication for postsecondary students with ID through visual analysis of the graphed data. Systematic visual analysis has been validated as a primary approach when analyzing results of single-case research (Horner et al., 2005). We examined changes in levels, trends, and stability between the baseline and intervention conditions (Ledford & Gast, 2018). In addition, we calculated Tau-U to estimate the intervention effects by taking into account the nonoverlapping data points and trends between baseline and intervention (Vannest & Ninci, 2015). Many researchers have reported that Tau-U is a more accurate effect size measure as it accounts for level changes across conditions and baseline trends (e.g., Parker et al., 2011; Rakap, 2015). We interpreted Tau-U as a small effect (<.20), moderate effect (.20–.60), large effect (.60–.80), or very large effect (>.80; Vannest & Ninci, 2015). To analyze findings from the social validity measures, we identified themes associated with the goals, procedures, and outcomes of the study across the perspectives of students and peer partners.

Procedures

Social Interactions

Three or more turns

Figure 1 illustrates the percentage of intervals when the student with ID had three or more conversational turns with their peer partner. Zion’s baseline data with Adrian were low and stable with a mean of 0 (see Table 1 for mean and range scores). After peer training, there was an immediate increase to 7% and a gradual increase over the remaining intervention sessions demonstrating a very large effect with a Tau-U effect size of .96 (90% CI = [.34, 1.00]; p = .01). The overall mean for intervention sessions was 9%. For Tori, her baseline data were at a low level and variable with a mean of 3%. During the intervention, there was an immediate increase to 20% of the intervals with three or more turns, followed by a descending trend. Her Tau-U effect size was .57 (90% CI = [−.50, 1.00]; p = .13), showing a moderate effect, and the mean for intervention sessions was 9%. Zion did not have any interactions with three or more turns with Piper during baseline. However, each intervention session included at least one conversation with multiple exchanges resulting in a slightly higher level for a mean of 1% and a Tau-U effect size of 1.0 (90% CI = [.33, 1.00]; p = .14). Overall, the two students at least minimally increased the percentage of intervals with three or more turns, engaging in longer conversations after the three peers received individual training and implemented the strategies. Results of the visual analysis demonstrated a single replication across two students and a single replication across two peers for Zion.

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Figure 1.

Three or more reciprocal turns.

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Table 1.

Mean Percentage of Interval Scores (Range).

Measures	Zion–Adrian		Tori–Tenley		Zion–Piper
	Baseline	Intervention	Baseline	Intervention	Baseline	Intervention
Student interactions
3 or more turns	0 (0–2)	9 (3–23)	3 (0–10)	9 (3–20)	0 (0–0)	1 (1–2)
Independent initiations	1 (0–3)	3 (0–4)	1 (0–4)	3 (0–7)	0 (0–0)	0.33 (0–1)
Independent responses	13 (1–26)	23 (7–46)	6 (0–15)	14 (7–30)	0.16 (0–2)	6 (4–9)
Communication functions
Academic	13 (1–26)	20 (7–40)	5 (1–15)	13 (4–26)	0.16 (0–2)	2 (0–3)
Social	0 (0–0)	4 (1–9)	1 (0–3)	3 (0–5)	0 (0–0)	4 (3–7)
Class format
Large group	54 (19–78)	9 (0–29)	88 (69–98)	86 (74–99)	35 (0–100)	7 (0–12)
Small group	0 (0–0)	0 (0–0)	8 (0–24)	11 (0–22)	0 (0–0)	0 (0–0)
Independent	38 (0–74)	86 (64–97)	0 (0–2)	0 (0–0)	59 (0–97)	87 (84–91)
No instruction	8 (2–22)	5 (2–9)	4 (0–7)	3 (1–4)	6 (0–22)	5 (2-9)
Gone	0 (0–0)	0 (0–0)	0 (0–0)	0 (0–0)	0 (0–0)	0 (0–0)
Proximity
Peer partner	99 (97–100)	99 (96–100)	99 (95–100)	100 (100–100)	100 (97–100)	98 (96–100)
Other peers	83 (50–100)	45 (0–97)	99 (96–100)	100 (99–100)	61 (0–100)	53 (11–79)
Instructor	13 (8–25)	37 (21–70)	0 (0–0)	0 (0–0)	28 (8–70)	29 (21–38)

Initiations and responses

Figure 2 shows the percentage of intervals when the student independently initiated an interaction or responded to a question or comment from their peer. Zion only initiated two interactions with Adrian with a low level and a slightly descending trend during baseline for a mean of 1%. During the intervention, there was a slight increase in level and positive change in trend with a mean of 3%. Zion initiated between one and four interactions in all intervention sessions except for one. He did respond to Adrian more often although his baseline data were variable with a mean of 13%. His intervention data showed a steady ascending trend with a mean of 23%.

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Figure 2.

Initiations and responses.

Tori seldom initiated a social interaction with Tenley during baseline (M = 1%), only two or three times in three out of seven sessions with an overall low level and a stable trend. However, her initiation data demonstrated a slightly higher level, a descending trend, and a small mean increase to 3% during intervention. For responses, her baseline data were low and variable with an ascending trend and a mean of 6%. During the intervention, she immediately increased performance to 30% in the first session and then the remaining sessions illustrated a descending trend. Her overall intervention mean was 14%.

Zion never initiated toward Piper and only responded once during baseline, showing very low and stable data paths. In intervention, he initiated once and responded between three and eight times during the three sessions. This resulted in positive changes in level and trend with means of 0.33% for initiations and 6% for responses.

Academic and social discussions

Figure 3 displays the percentage of intervals when the pairs were discussing academic and social topics. Interestingly, the data for academic topics follow a similar data path as student responses, and the data path for social topics is parallel to student initiations when comparing Figures 2 and 3. Across pairs, Zion and Piper talked more socially, whereas the other two pairs spoke more about academic content. Mean academic and social scores increased for all participants during the intervention. Zion and Adrian never spoke socially during baseline but communicated about social topics one or more times with a slightly ascending trend during the intervention. His baseline data for academic topics were variable, whereas his intervention data showed a steady incline. Socially, Tori only communicated once or twice with Tenley in baseline sessions, but she increased her social communication to two or four times during all intervention sessions except one illustrating a slightly higher level of data overall. Tori’s discussion of academic topics illustrated low and variable baseline data with a range of 1% to 15%. She did immediately increase to 26% during intervention. Though this was not maintained, her overall intervention data were at a higher level. Like Zion and Adrian, Zion and Piper did not communicate socially prior to peer training. After training, each intervention session included three to six social interactions, with an ascending trend. Likewise, they only had one academic interaction during baseline and two or three during all intervention sessions except one.

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Figure 3.

Academic and social conversational topics.

Contextual Variables

To assist with describing the variables within classrooms, we collected data on the instructional format and proximity of the student with their peer partner, other peers, and instructor at the beginning of each 1-min interval (see Table 1 for means and ranges of the percentage of intervals). The class format for Zion was primarily independent work during his 2D Art course. Because the classes primarily comprised work time to complete assigned art projects, students seldom stayed the entire 2 hr. Zion and his peer partners were typically one of the last students to leave. Over the 11 sessions, the average class time was 80 min. Zion was almost always in proximity to Adrian and Piper; occasionally, the peers walked around the room to get materials without Zion. Other peers were in proximity about half of the time, and his instructor was nearby approximately 30% of the intervals. Tori’s class, Introduction to Special Education, was mostly a large group lecture representing 88% and 86% of the intervals during baseline and intervention, respectively. All but four sessions (2, 3, 7, and 11) included some small group work time. She was almost always in proximity to her peer partner and other peers and never next to her instructor. Her average class time was 74 min over the 11 sessions. It is important to note these contextual variables as they play a part in the opportunities for social interactions in college courses.

Reliability

For each student and peer pair, we evaluated IOA during 27% of the classroom observations for each student participant. We calculated a mean IOA of 99% (range: 96%–100%) for three or more turns, 100% (range: 99%–100%) for student initiations, 99% (range: 97%–100%) for student responses, 99% (range: 96%–100%) for academic topics, and 100% (range: 100%–100%) for social topics across the three pairs. Furthermore, we had a mean IOA of 100% (range: 100%–100%) for classroom format and 99% (range: 97%–100%) for proximity with others.

To evaluate procedural reliability during the peer training sessions, we used a checklist to ensure that all training steps were completed. We evaluated procedural reliability during all three training sessions and had 100% reliability.

Social Validity

All participants completed the survey except for Piper, a peer partner, who did not return the survey. The students with ID stated they liked learning specific content in their courses and being with their peers in inclusive classrooms. Zion said talking with my peers “makes me happy,” while Tori said it “makes me feel more comfortable.” Both peers also noted that the students appeared to be more open and comfortable conversing as the study progressed.

The peer partners, who had no prior training on social communication, found the training to be beneficial and the strategies to be very rewarding as they saw improved communication skills and coursework of the students. They were impressed by the students’ increased conversational skills and their final projects and knowledge on quizzes. The peer partners said they would continue to use the communication strategies when working with other students with disabilities. One peer reported the training should remain the same length, whereas the other peer said the training could be a little longer to include more strategies. When asked about challenges, the peers said it was difficult to converse with the student when a lot of class time included the instructor lecturing or they felt nervous to naturally interact when observed by the researchers.

Key Findings

Postsecondary programs at colleges and universities offer unique learning and social opportunities for students with disabilities to access advanced curricula, enhance interpersonal skills, and develop vocational competency. As adults with ID navigate college campus and life, their college peers have great potential to become natural supports inside and outside classrooms (Blumberg & Daley, 2009; Griffin, Mello et al., 2016; Jones & Goble, 2012). In our study, after peer training, the postsecondary students with ID increased their social interactions in all measures (i.e., three or more turns, initiations, responses, academic, and social topics) while continuing to learn and participate in class. These students carried on a conversation with multiple back and forth turns when asked questions or discussing a topic of interest with a peer. These results support the use of peer mentors to facilitate social and academic communication opportunities in rural postsecondary settings (Ryan, 2014; Workman & Green, 2019) and highlight the need for additional research to further expand the efficacy, as this study only included two participants with ID and we did not collect fidelity data on the peers’ implementation of the strategies after training.

Enhancing students’ communication, especially in the area of conversational turn-taking, is an important skill in further developing social relationships (Weiner, 2005). Reciprocal turn-taking in conversations is a complex skill that requires expressive and receptive competences, including listening, initiating and responding interchanges, yielding to the communication partner, and maintaining the topic or appropriately changing topics (Hay & Fielding-Barnsley, 2009). Data from this study illustrated an initial change in level after peer training although it was minimal for Zion and Piper. While we did not specifically code initiations and responses within three or more turns, it is likely that these increased conversational turns were a result of increased student responses, which had similar data patterns. This finding reaffirms the impact and importance of peer support on social communication (Chung et al., 2012b). We did not provide direct skill training to students with ID in this study. The students increased their social interactions when their peers provided more opportunities to respond to questions or comments.

During our training with college peer partners, we did not ask peers to prompt student initiations. Interestingly, we recorded an increase in independent initiations for both students, which seemed to be incidental or unplanned intervention effects among the increased interactions. These initiations may have been a random occurrence or a result of students feeling more comfortable or confident communicating and hearing many initiations modeled by their peer partners. With more interactions and peer initiations, the students may have also incidentally learned to initiate more often to form a social connection.

We also found that few interactions between the students and peers had a communication function related to social topics. Some student, peer, and classroom factors may have contributed to this outcome. First, Tori’s class format primarily consisted of lectures. In addition, Zion primarily focused his attention on his artwork during class. Moreover, the peer partners naturally knew when to discuss and initiate academic topics, but they might not have been as familiar with the students’ lives outside the classroom. Thus, we also noted similar data patterns for academic topics and student responses. However, for any missed communication opportunities, the peers could potentially benefit from more feedback or coaching on discussing social topics at the beginning and end of classes or ways to further expand academic conversations. Peers are a natural support in college environments and are usually willing to assist students with ID in further developing their academic and social skills (Carter et al., 2018; Hafner et al., 2011).

The instructional format of the class session seemed to impact the amount of natural communication opportunities provided. In our study, we observed some variations in students’ communicative behaviors prior to the intervention. For example, Zion engaged in few interactions during the first session of baseline (1% of intervals with responses and 75% of intervals in a large group). Conversely during the second baseline session, he responded during 26% of the intervals with 74% of the intervals making up independent work time. Similarly, when Tori’s class had small group time for 14% of the intervals during session six of baseline, she had a high response rate of 15%. The class format can be a variable when determining communication opportunities that influence student interactions (Chung et al., 2012a). This study exemplified that classes with less lecturing and more small group or independent work may be more ideal for promoting academic and social interactions.

Finally, this study showed that peers were interested in communicating with students having disabilities and benefited from, at minimum, a brief training in increasing their awareness of communication opportunities. The 15- to 20-min peer training sharing three specific strategies (greet, review academic content, and ask social questions) in this study resulted in increased academic and social communication of students with ID. Although fidelity of implementation data was not collected on the peers, these findings expand the literature and strengthen the evidence of using peer supports within higher education inclusive settings (Blumberg & Daley, 2009; Giust & Valle-Riestra, 2017; Griffin, Mello et al., 2016; Griffin, Wendel et al., 2016; Jones & Goble, 2012) and in particular rural PSE programs (Ryan, 2014; Workman & Green, 2019).

Limitations

We noted a few limitations with this study that could be improved with future replications. First, we only had two student participants because the PSE program only had a few students in inclusive college courses due to work schedule conflicts. Consequently, we trained two peers in separate sessions from Zion’s art course. Second, the data collection method of interval recording does not fully capture the complex nature of communication interactions and classroom contexts. For example, partial interval recordings often underestimate the occurrences of behavior; however, it is an appropriate and reliable recording procedure when collecting communication data in real time. Our anecdotal notes indicated that during many observed intervals in the intervention condition, both Zion and Tori had more than three conversational turns or initiated or responded multiple times during different interactions within one interval. Also, while Tori was never in proximity to her instructor at the beginning of an interval when we collected contextual data, they were occasionally next to each other when the instructor walked around during small group time. Third, there is the potential for the Hawthorne effect influencing our findings as the researchers were present to collect observational data, and their presence may have affected students’ and peers’ behaviors. Fourth, this study lacked peer data on the use of specific strategies and the fidelity of implementations of said strategies after peer training. Fifth, given the confines of a 15-week semester and data collection starting a few weeks into the semester, the researchers did not have time to collect five sessions of baseline data for all participant pairs. This time constraint also limited the researchers’ ability to make intervention modifications with the peers to further increase the student’s social communication or collect maintenance data to demonstrate the prolonged effect of the intervention and further analyze the variability in the data. Such challenges are common for researchers who conduct classroom-based research and attempt to establish experimental control within a set timeframe. Sixth, instructional formats such as lectures and the lack of peer socialization time limited social opportunities and resulted in natural variability within college courses.

Future Research

Ideas for future researchers include replicating this study with more student and peer participants, teaching peers naturalistic strategies, using eCoaching (in-ear coaching) to support peers or instructors, and collecting data across multiple courses, settings, or people (other peers and instructors). A systematic replication of this study with at least three different student–peer pairs would allow for more demonstrations of effect to strengthen the validity of the results. Fidelity data on the peers’ implementation of the strategies should also be collected in the future along with the students’ outcomes. While we taught peers to implement specific strategies to increase academic and social conversations in this study, students may benefit from their peers learning how to use modeling, mand-modeling, and time delay to promote communication. These naturalistic strategies are an evidence-based practice for students with ID (Browder et al., 2014; Courtade et al., 2015). In addition to providing didactic training with the peers, researchers might follow-up the training session with eCoaching in real time during the class period (Rock et al., 2012). The in-ear coach could identify communication opportunities and specifically tell the peer what to say or how to prompt the student to respond simultaneously. Peers could be cued to get the student conversing with other peers and their instructor too. Gilson and Carter (2016) argued the physical presence of a coach hindered the social opportunities and overall independence of college students with ID or autism spectrum disorder, so in-ear coaching was more effective. This eCoaching strategy could also be used with classroom instructors as they could benefit from training similar to that for the peer partners (Jones & Goble, 2012). To establish the external validity of the results, researchers could evaluate generalization in different college courses or settings (e.g., dining hall, recreational center, and student lounge) and with unfamiliar classmates and instructors. Also, additional data could be collected on the number of conversational turns taken or whether students responded to questions or comments from peer partners and other peers.

Implications for Practice

PSE programs provide opportunities for students with ID to be included in college courses and interact with peers without disabilities (Causton-Theoharis et al., 2009; Moore & Schelling, 2015). Overall, the outcomes of these programs can lead to improved employment options, healthy lifestyles, social connections, independence, and self-advocacy skills (Hart et al., 2006; Thoma et al., 2011). Of the surveyed PSE graduates, 91% reported being satisfied or very satisfied with their social life (Grigal et al., 2018). One component of a fulfilled social life comes from acquiring communication skills that can lead to enhanced social relationships. Communication is an important skill and an essential part of life and social interactions. Although more data are needed to corroborate the confidence of the results of this study, its findings showed how one short training on specific strategies for peer partners can result in students with ID taking more conversational turns. Reciprocal turn-taking can expand the communication interactions of students with ID and potentially forges social relationships. As these postsecondary students live in a rural area, developing social connections with peers on campus is even more important as socialization with friends while in their home community may not always be feasible. The ultimate goal for social communication and peer interaction interventions is to expand and diversify students’ social networks, which can lead to enhanced social capital and more future employment opportunities (Eisenman et al., 2013). Furthermore, the enhanced communication skills of students with ID can potentially assist in addressing the challenges when living in rural communities. Students may feel more comfortable and competent in communicating their needs to secure transportation, maintain employment, connect with friends, self-advocate, and locate available resources (Love & Mock, 2019).

PSE programs with trained peers also provide models of acceptable social communication skills that students with ID can imitate and replicate (Hafner et al., 2011; Jones & Goble, 2012). In this study, it can be implied that students increased their percentage of intervals independently initiating toward their peer partners as their communicative responses increased. It is likely that with more opportunities to communicate with a familiar individual, student initiations will continue to increase. In addition, educators should consider matching the class format to the communication needs of students with ID in courses that interest them. Courses incorporating time for small group activities provide natural opportunities for cooperative communication. Similarly, courses designed to include independent work time, such as 2D Art, typically promote collaboration with peers to brainstorm and critique ideas. PSE programs should be designed to purposefully enhance both academic outcomes and social interactions of students with disabilities through the use of trained peer supports. Peer supports are critical in the successful inclusion of students with ID on rural college campuses (Griffin, Mello et al., 2016).