Abstract
Colleges across the nation have seen an increase in programming for students with intellectual and developmental disabilities (IDD) over the past decade. With this increase in programming comes the need to support students with IDD while accessing a large college campus. Using technology, such as Google Maps™, on one’s cell phone is a natural support that is relatively unobtrusive. This study used a peer-mediated instructional package consisting of total task presentation and error correction to teach college students with IDD how to use Google Maps™ to navigate a large, urban college campus in the southeastern United States. The results from this single-subject multiple probe design demonstrated that all students acquired the skills with 100% accuracy and maintained the skill once the instructional package was removed. Social validity data indicated that students thoroughly enjoyed learning the skill from the peer mediator. Implications and future research are discussed.
As college campuses across the country become increasingly diverse, one population of student continues to be underrepresented. Individuals with intellectual and developmental disabilities (IDD) have long been excluded from experiencing campus life. Only recently have efforts in policy and funding created a pathway to inclusive college experiences. Newly made postsecondary education (PSE) programs at institutes of higher education provide individuals with IDD an opportunity to continue their education in a traditional postsecondary setting and immerse students in campus life. These programs provide students with IDD an extended opportunity for inclusive education and further the development of employment skills, self-determination skills, and independent living skills.
Since transportation is a considerable barrier for independent living for individuals with IDD (McMahon et al., 2015), being able to navigate as a pedestrian is a critical life skill that enables independence. Often opportunities for individuals with IDD are limited by the individual’s personal navigation abilities (McMahon et al., 2015). These skills can impact job opportunities, socialization opportunities, and even educational opportunities. Transitioning from a smaller high school campus to larger college campus comes with personal navigation challenges for individuals with and without disabilities. One necessary aspect of campus inclusivity is the expectation for students with IDD to independently navigate the campus to find their classes, food venues, and other campus resources such as the library or bookstore. Fortunately, technology has proven effective when teaching students with IDD how to navigate their community.
Research teams have been studying technological interventions to teach students with IDD how to navigate around their community and more recently, their college campus. For example, the use of a personal digital assistant (PDA) software system integrated with global positioning system (GPS) technology was used to provide visual and auditory prompts to assist students with an intellectual disability (ID) to navigate a fixed bus route (Davies et al., 2010). The technology in this study identified and displayed landmarks as a visual feature, which according to Davies et al. (2010), promoted user attention and focus. The outcomes from this study showed that the GPS-enabled device demonstrated promise for supporting public bus transportation, as well as increased accuracy in reaching the correct destination (Davies et al., 2010). Similarly, a study using total task chaining to instruct young adults with ID to use the Google Maps™ application to access public transportation from campus to their internship placement found that three of the four participants learned to use the Google Maps™ app independently (Price et al., 2018). Most recently, Yuan et al. (2019) studied the impact of constant time delay to teach students with ID how to plan a route and reach their destination using Google Maps™ on an iPad or cellular phone. A mnemonic device (TRAVEL) was used to guide the participants through the steps of using Google Maps™, along with an identified novel location name card indicating the location the students would travel to Yuan et al. (2019). Results from this study indicated that all three participants could set up the route on their device and two of the three participants were able to navigate to the novel location without prompts (Yuan et al., 2019).
The emerging research on technology to teach navigation skills to young adults with IDD has thus far been researcher-driven. There has yet to be research on peer-mediated interventions to teach navigation skills to young adults with IDD. Peer-mediated interventions utilize students as instructional agents or facilitators with other students. Peer-mediated interventions have been used to increase communication skills, social skills, academic skills, and employment skills for different populations of students with disabilities, from preschool to high school (Kaya et al., 2015). Peer-mediated intervention instructional elements can be extensive, such as providing direct instruction or tutoring, or less complex, such as providing a prompt to the target student. Researchers have used peer-mediated interventions to increase various skills in transition-aged students with developmental disabilities. In a study by Honsberger et al. (2019), a peer mediator with IDD provided instruction to participant students with IDD using a literacy-based behavioral intervention to prepare and sell coffee from a food truck, demonstrating the potential for peers with IDD to support the training of newly hired individuals with IDD. Furthermore, a peer-mediated intervention, administered by a peer with autism spectrum disorder (ASD), was implemented to teach high school students with IDD to administer a routine first aid procedure successfully (Kearney et al., 2018). These studies have demonstrated the effectiveness of peer-mediated interventions, particularly the ability of peers with disabilities to successfully teach other students with developmental disabilities acquisition skills.
Given the promising results for using technology, such as Google Maps™, to teach young adults with IDD navigation skills, the authors of the current study were interested in combining the power of peer-mediated instruction and technology to teach students with IDD to navigate a college campus. This study seeks to determine the effectiveness of a peer-mediated instructional package consisting of total task presentation and error correction to teach college students with IDD to use a navigation app (Google Maps™) on their smartphone to navigate the university campus on foot. The research questions addressed in this study were as follows:
Method
Participants
Three college students (aged 20–22 years) enrolled in a PSE program at a university in the southeastern United States participated in the study. All students had a diagnosis of ID according to the Wechsler Adult Intelligence Scale–Fourth Edition (WAIS-IV) (Wechsler, 2008). Two students had a secondary diagnosis of ASD. All the students were new to the PSE program and were not yet familiar with the college campus. They all owned their own smartphones and knew how to access the Wi-Fi at the university to download apps through the app store on their phones. However, none of them had prior experience using the Google Maps™ application. They all had the requisite safety skills required to participate in the study, such as looking both ways before crossing the street, yielding to cars and bicycles, and using pedestrian crosswalks. All students, including the peer mediator, provided written and verbal assent to participate in the study. Even though students were of legal age, these students were not their own legal guardians, therefore prior to the study, parents of all students provided written consent. The study received formal approval from the university’s institutional review board prior to obtaining assent and consent from participants.
Donna
Donna was a 20-year-old student diagnosed with ID and ASD. Her WAIS full-scale IQ was 60. Donna scored on the Job Observation and Behavior Scale: Opportunity for Self Determination (JOBS:OSD) (Brady et al., 2006) a performance score of 82 and support of 71. These scores indicated that Donna’s perceived self-determination skills were slightly higher than the mean of other adults in competitive and supported employment. Donna had no travel experience and had never navigated independently around her community prior to this study.
Dennis
Dennis was a 20-year-old student diagnosed with ID and ASD. His WAIS full-scale IQ was 65. Dennis scored on the JOBS:OSD a performance score of 74 and support of 54. These scores indicated that his perceived self-determination skills were lower than the mean of other adults in competitive and supported employment. Dennis had independently navigated within his gated community to locations he had visited previously with his family, such as the community fitness center, but had never navigated independently outside of his neighborhood.
Jennifer
Jennifer was a 22-year-old student diagnosed with ID and Down Syndrome. Her WAIS-scale IQ is 53. Jennifer scored on the JOBS:OSD a performance score of 84 and support of 80. These scores indicated that Jennifer’s perceived self-determination skills were higher than the mean of other adults in competitive and supported employment. Jennifer had fewer independent living skills and less experience in the community than the other two participants. She had no independent travel experience and had never been left alone in her house before.
Sara
Sara served as the peer mediator for the three target students. Sara was 22-year-old, diagnosed with ID, and enrolled in the same PSE program as the participants. Her WAIS full-scale IQ was 68. She had previous experience with Google Maps™ and learned to navigate the campus with a researcher prior to beginning the study. Sara had previously traveled alone to known locations using ride-sharing apps. Sara knew one of the target students from high school, but did not know the other two students at the initiation of the study aside from meeting them once during orientation. Sara attended the same classes as the target students throughout the semester. Sara was designated as the peer mediator due to her ability to model the steps in the task analysis, follow adult directives, and effectively demonstrate the least-to-most error correction procedures during the peer-training phase. Sara was also interested in participating and was excited to help her peers learn to use a natural, technological support to navigate the campus.
Setting
This study took place on a large, urban campus of a public university in the southeastern United States. The university campus is comprised of 90 buildings on 850 acres. Approximately 24,000 students attended classes on the campus at the time of this study. All buildings around the campus intersect with sidewalks and marked crosswalks to ensure safe pedestrian navigation. Most crosswalks had a speedbump in the road before them, encouraging drivers to slow down. Intersections had either stop signs or streetlights with a pedestrian signal and a call button for safe crossing. The three students and peer mediator participated in the inclusive PSE program within the larger campus environment.
The PSE program is a comprehensive transition program and has 42 students enrolled across two campuses. Navigating the university became a targeted skill because all the students were new to the PSE program. During the particular semester the study took place, all prerequisite classes for the new students happened to be scheduled in the College of Education. This was the same location both caregivers and public transportation picked up and dropped off students. The front of the College of Education building faced north and looked onto a busy student parking lot.
Materials
All students used their own smartphones during this study. Sara, Jennifer, and Donna had iPhones. Sara and Jennifer had an iPhone 8, Donna had an iPhone 11. Dennis had a Samsung Galaxy S7. All students downloaded Google Maps™ to their phones prior to the beginning of study through the App Store. Google Maps™ is a free web-mapping mobile app that can be downloaded onto all versions of smartphones and can be used to, “. . . display map images, topographic maps and satellite images, and can achieve global location search, classified information access, [and] traffic information query. . .” (Li & Zhijian, 2010, p. 87). When opening Google Maps™, one can find specific locations based on GPS data available through the internet. This information can then be used by an individual to navigate from a current location to a new location, either by driving or walking. Only the walking navigation option was used for the purposes of this study.
Dependent Variable
The researchers created a task analysis of the skill. The task analysis was comprised of 10 steps. See Table 1 for the task analysis. The researchers also compiled a list of 10 locations on campus programmed by name on Google Maps™. The locations selected were places the students would need to visit throughout their educational career in the PSE program. The locations on the campus included lecture halls, administrative buildings, the football stadium, student housing, the library, the fitness center, the dining hall, and restaurants. Researchers observed each student individually and collected data on their use of Google Maps™ to navigate to the predetermined location.
Google Maps™ Navigation Task Analysis (iPhone® version).
Students were given a verbal prompt to type the desired location (e.g., “Donna, using your technology, let’s go to the Health and Fitness Center”). All predetermined locations were on the university grounds. The same locations were used for baseline, intervention, and follow-up; however, each location was only used once per phase at most. This ensured researchers were actually measuring the accurate use of Google Maps ™ rather than measuring how well Donna remembered how to get to a place she navigated to a few days prior. The students were not told how to spell the location, however, all smartphones had predictive text. The students only needed to type the first few letters of the location before options were displayed. Students were then able to correctly choose the location they wanted to navigate to.
Each step in the task analysis was scored by the data collector as either (a) correct and independent, or (b) incorrect/no attempt made. Researchers wanted to know how many steps were completed correctly and independently for the purposes of graphing. Therefore, when Sara used the least-to-most prompting hierarchy, the researchers would still count the step as incorrect during data collection. The dependent variable was the percentage of steps in the task analysis completed correctly and independently by the student.
Data Collection and Interobserver Agreement
A researcher-made data sheet was used to collect data. Each student behavior was scored as correct or incorrect. Students needed to complete 90% of the steps correctly and independently for four consecutive sessions to reach mastery criteria. The researchers collected data at the beginning of each session, prior to the peer implementing the instructional package, in order to avoid immediate practice effects. All data were converted to percentages for graphing. The task analysis for using Google Maps™ to navigate on campus had 10 steps, so for example, if during baseline zero steps were performed correct and independent, then the first data point would be marked at 0%. If after the first training session, the participant performed six of the 10 steps correct and independent, then that data point would be marked at 60% for that session.
The two main data collectors were experienced special educators and instructors in the PSE program. A third observer, who was an experienced special educator and graduate student in a special education program, collected data for interobserver agreement (IOA) and fidelity purposes. Prior to the baseline, all observers were trained to use the data sheets. To determine interobserver agreement, data were collected live and concurrently by two observers during 52% of all sessions. These agreement sessions were conducted in 67% of baseline, 50% of intervention, and 50% of follow-up sessions for Donna (56% overall), 67% of baseline, 20% of intervention, and 100% of follow-up sessions for Dennis (50% overall), and 50% of baseline, 33% of intervention, and 100% of follow-up sessions for Jennifer (50% overall). Interobserver agreement was determined by counting the steps in the task analysis marked the same by both observers, and dividing that number by the total number of steps in the task analysis, then multiplying by 100. Agreement between the two researchers across all students and sessions was 100%.
Design
This study used a multiple probe design across participants to determine the impact of the peer-mediated instructional package. This design used multiple probes during baseline to avoid lengthy inaccurate use of Google Maps™ prior to the implementation of the peer-mediated instructional package (Kennedy, 2005). The staggered start of the intervention demonstrated that the increase in skill accuracy was a result of the intervention rather than happenstance. Students moved from baseline to intervention once a low and stable baseline was established.
Independent Variable
The independent variable was a peer-mediated instructional package consisting of total task presentation of utilization of the pedestrian navigation button of Google Maps™ to navigate to predetermined locations on the university campus coupled with a least-to-most error correction procedure. Sara, the peer-mediator, modeled the total task presentation of the skill while simultaneously describing each step she was doing, and then asked the student to complete the whole task independently. If the student made an error on any step, or did not complete a step, Sara used a least-to-most prompting hierarchy with the following steps: (a) verbalizing the step to be performed, (b) verbalizing the step and modeling the correct way to perform the step on her own phone, or (c) verbalizing the step and providing physical assistance in completing the step on the participant’s phone. Sara delivered a prompt to the student only in response to the student making an error, or not initiating a step within 7 s.
Treatment Fidelity
Before implementing the intervention with any of the students, the peer practiced modeling the total task presentation and description of the steps and error correction procedures with one of the researchers, demonstrating the ability to complete the instructional package accurately on two separate practice sessions. Once the intervention phase began, the peer rehearsed the instructional package with the investigator weekly, prior to the beginning of the first session of the week. The fidelity observer collected data on the peer correctly following the instructional package. During the study, researchers collected fidelity data during 37% of the intervention sessions. Fidelity data demonstrated that the peer mediator followed the protocol with 100% fidelity during each observation.
Procedure
Baseline
During baseline, the students were asked to use their technology to navigate to a building on the college campus with no prompting or further instruction. The peer was in the same vicinity as the participating students, but did not interact with the students at all. The student, peer, and researcher walked outside the COE building and the researcher said, “Using your technology, walk to the business building.” No further information or instruction was provided. The building was chosen randomly each day prior to the baseline session. The student’s performance was observed for multiple days. The researcher decided to move from baseline to intervention after at least three data points demonstrating a low rate of correct and independent skill performance. The baseline session ended if the students did not initiate walking within 15 s or if they verbally indicated that they did not know where the location was.
Peer training
Before beginning the intervention with the students, a researcher taught the peer to model a total task presentation of the Google Maps™ application while verbalizing each step as she was completing it. She was also taught to implement an error correction procedure of least-to-most prompting. The peer was already familiar with using Google Maps™ to navigate around her community. Peer training was conducted over 2 days before the beginning of the study, for approximately 20 min each day. After the peer mastered modeling the total task presentation and describing each step as she completed it, the peer was then taught to implement an error correction procedure using least-to-most prompting. During peer training, if the researcher made a mistake or did not perform the next step within 7 s, the peer would provide a verbal prompt (e.g., “open Google Maps”). If there was still no behavior from the researcher after another 7 s, the peer would again provide a verbal prompt and show the researcher the step on her phone. If the researcher still made an error or did not complete the step, the peer would again give a verbal prompt and use physical assistance, taking the researcher’s finger and physically helping the researcher complete the step on the researcher’s phone.
Intervention
The intervention for this study was a peer modeling the total task presentation of the skill while verbalizing each step in the task analysis coupled with an error correction procedure. Students received peer-mediated instruction individually. When delivering the intervention, the peer modeled the total task, teaching each step of the task analysis from the beginning to the end and describing each step as she completed it (Browder & Spooner, 2011; Snell & Brown, 2011). For example, step one in the task analysis is “unlock screen on phone,” Sara would unlock her phone and say, “I am unlocking my phone.” Step two in the task analysis is “toggle to Google Maps™ application on phone,” Sara would complete the action and say, “I am looking for Google Maps on my phone.” She did this with each step in the task analysis.
After modeling the total task, she then asked the student to complete the whole task independently. If a student made an error on any step, the peer mediator prompted the student using a least-to-most prompting procedure (Browder & Spooner, 2011; Richards et al., 2015). The least-to-most prompting procedure was less likely to create prompt dependence in the student (Richards et al., 2015). The prompt hierarchy for corrections included (a) peer verbalizing to the student what step should be performed, (b) peer verbalizing the step and modeling the correct way to perform the step on her own phone, or (c) peer verbalizing the step and providing physical assistance in completing the step on student’s phone. If the student made a subsequent error on the same step, the next level prompt would have been delivered, however, only the first level of prompt (verbal prompt) was ever needed.
After the first intervention session, every other intervention session began by asking the students to use their technology to navigate to a predetermined building. Data were collected on the student performance of the skill before the peer-mediated instructional package was delivered that session. This resulted in a minimum of a 24-h delay for the data collection after the most recent delivery of the instructional package, avoiding the performance data on that day from being influenced by immediate practice effects.
Follow-up
During the follow-up condition, the peer-mediated instructional package was removed to determine whether any of the skill improvements would maintain in the absence of the instructional package. The criterion for removing Google Maps™ was successful completion of nine of the 10 steps (90% accuracy) for four consecutive sessions. The peer mediator was removed after four intervention sessions for Donna, five sessions for Dennis, and six sessions for Jennifer. Follow-up observations were conducted for Donna 28 and 41 days after intervention, follow-up observations for Dennis were held 21 and 34 days after the intervention was removed, and 14 and 27 days after Jennifer’s last intervention session.
Data Analysis
Researchers used visual analysis to determine the levels and trends of individual data points and decide when to implement phase changes (Lane & Gast, 2014). Researchers then summarized data by calculating measures of central tendency and ranges for each student’s skill acquisition during baseline, intervention, and follow-up. Researchers made changes to the condition based on the level and trends of individual data points. Researchers decided to move from baseline to intervention when data demonstrated low and stable performance. Researchers decided to move from intervention to follow-up after each student demonstrated four consecutive sessions in a row at 90% correct and independent responding.
The team then used Tau-U to define effect size. The Tau-U web-based calculator was used to determine the post hoc analysis of true effect size (Vannest et al., 2016). This analysis was based on the weighted average of each student’s baseline and intervention changes (Parker et al., 2011).
Social Validity
A social validity assessment was used to determine student perceptions of the study. The instrument used was adapted from Kearney et al. (2018). The survey contained three items asking students about their perceptions regarding the importance of the skill and the appropriateness of the procedures used. A researcher stated the instructions to each student, read the items, and asked them to answer by circling their response on the survey. The survey used a 4-point scale (Absolutely = 4; Kind of = 3; Not Really = 2; No Way = 1), with an emoticon associated with each response option. Results were analyzed by calculating response means for each question.
Results
Data remained low and stable during baseline. None of the students accurately engaged in any of the steps in the Google Maps™ navigation routine. Throughout this phase, the mean steps completed was 0% for all students. Once the peer-mediated instructional package was introduced, all students quickly demonstrated an increasing trend with their accuracy in completing the skill. During the intervention phase, the average number of steps completed correctly and independently rose to 94% (range = 60%–100%). Students required an average of five sessions to meet mastery criteria. The number of steps completed correctly during the follow-up phase maintained at a high level with an average of 98% (range = 90%–100%). Given the overall mean student performance in the intervention and follow-up phases, the peer-mediated instructional package was an effective tool to teach college students with IDD to navigate around the university campus by foot.
An evaluation of level change within conditions indicated that performance had no change in level during baseline for any participant. All participants demonstrated an improving level trend once the peer-mediated instructional package was introduced. Regarding within condition analysis of trend, a change in performance across conditions went from a zero-celerating trend to an accelerating, improving trend across participants when the intervention was introduced. The effects of the peer-mediated instructional package on student performance are shown in Figure 1. Individual effects are discussed below.

Percentage of steps correct and independent.
Donna
Donna did not initiate any steps during baseline. When the peer-mediated instructional package was introduced, Donna only needed one intervention session before she could complete 100% of the steps accurately and independently. Donna met mastery criteria after only four sessions. Follow-up data were recorded for Donna at 28 and 41 days after the intervention was removed. She maintained 100% skill accuracy for both follow-up sessions.
Dennis
In the first baseline session, Dennis walked around for roughly 5 min looking for the building before verbally stating that he did not know where it was. Throughout baseline, he completed 0% of the steps correctly or independently. Upon introducing the intervention, Dennis was able to complete the steps with an average of 96% accuracy (range = 80%–100%). Dennis reached mastery criteria after five intervention sessions. During the follow-up phase, Dennis maintained 100% skill accuracy 21 and 34 days after intervention.
Jennifer
During baseline, Jennifer did not initiate any of the steps. After introducing the intervention, Jennifer had a slower increase in skill accuracy, reaching an average of 88% accuracy (range = 60%–100%). She reached mastery criteria after six intervention sessions. Jennifer’s skill accuracy was a bit more variable during follow-up, although still high. 14 days after intervention she maintained 100% accuracy, but 27 days into follow-up her skill accuracy dropped to 90%.
Post Hoc Analysis and Effect Size
Researchers conducted a post hoc analysis using Tau-U. Tau-U results showed an aggregate effect size of 1.0 for the baseline and intervention contrast, which demonstrates a strong effect size (Parker et al., 2011).
Social Validity
The social validity assessment was conducted 1 week after the last intervention session. All three of the participants completed the survey. Data analysis on the social validity assessment involved calculating means for each item.
Student beliefs about their navigation skills were overwhelmingly positive. Students reported that they (a) know how to use their technology to navigate around the campus (4.0 of 4.0), (b) are willing to use their technology to navigate around the community (3.7 of 4.0), and (c) want a peer to teach them other skills (4.0 of 4.0). Donna and Jennifer responded “absolutely” to all three questions asked. Dennis responded “absolutely” to all questions except “I am willing to use technology to navigate in the community.” Dennis responded “kind of” to this question.
Discussion
The purpose of this study was to determine whether a peer-mediated instructional package consisting of modeling total task presentation and least-to-most prompting error correction was effective in teaching college students with IDD how to navigate the campus using the Google Maps™ application on their smartphone. In response to the first research question, what is the impact of a peer-mediated instructional package consisting of total task presentation and error correction of student mastery of the Google Maps™ application, researchers found the peer-mediated instructional package to have a highly positive impact on student mastery of Google Maps™. All students who received the peer-mediated instructional package mastered the skill with 100% accuracy, needing only between four and six intervention sessions. To answer the second research question, to what extent were the skills maintained after the intervention was removed, researchers conducted maintenance probes from 14 to 41 days after the intervention was removed. Students were able to maintain the campus navigation skills with high accuracy up to 5 weeks after the removal of the intervention.
This is not the first study that taught college students with IDD how to use a natural, technological support to navigate a university campus. McMahon et al. (2015), Price et al. (2018), and Yuan et al. (2019) have demonstrated that young adults with IDD are capable of mastering Google Maps™ to navigate around their communities. This study builds on this knowledge, demonstrating that young adults with IDD can be taught to use Google Maps™ by their peers. This is the first known study that used a peer-mediator as the teacher of this particular skill. This study found something similar to Honsberger et al. (2019) and Kearney et al. (2018): peer-mediated instruction is powerful. All students stated on the social validity assessment, as well as anecdotally, that they enjoyed having a peer teach them a new skill and would like a peer to teach them other skills.
Limitations
Although this study shows promise for the use of a peer-mediated instructional package to teach students with IDD to navigate the college campus, some limitations should be noted. Replication is needed to determine how effective this intervention may be across populations. The authors recommend additional studies with more participants to extrapolate these findings. A second limitation is the similarity in the characteristics of all participants. All participants received the same diagnosis, were similar in age, had the requisite safety skills needed, and attended the same PSE program on the same college campus. Due to these shared characteristics, the results of this study cannot be generalized to other age groups or populations. In addition, there is no generalization data. One cannot assume that just because the students were able to complete the skill accurately on campus that it would necessarily generalize to an off-campus setting. Finally, to use the Google Maps™ application, access to wireless Internet or cellular data and GPS capabilities from a mobile device is required, perhaps limiting how accessible this intervention is to others.
Implications for Practice
The incredibly steep increasing trend in the campus navigation skills of the college students in this study indicates that this is a skill that may be easily mastered by this population. Perhaps the continued dependence young adults with IDD have on caregivers for community navigation can be attributed to a lack of opportunity to learn and practice the skill rather than a challenge in learning the skill. These researchers advocate for all transition-aged students to be taught community navigation skills in order to increase independence across all environments.
The present findings indicate that the use of peer-mediated instruction for college students with IDD can result in a high rate of skill acquisition and maintenance. The effectiveness of this type of instructional package, accompanied by its high social validity ratings, suggest that peer-mediated instruction can be an effective and enjoyable method for teaching functional skills to promote inclusion and independence in this population of students. Practitioners can use peer-mediated instruction to teach a wide assortment of skills, increasing both student enjoyment and practitioner efficiency at the same time.
Implications for Research
Future research should focus on the generalizability of a peer-mediated instructional package across settings. Although the data show that participants mastered navigating on campus with Google Maps™, generalizing this natural support to a setting off-campus would increase the social validity of the skill and further enable student independence. Researchers should continue to explore the efficacy of Google Maps™ for college students with ID to independently navigate around employment/internships settings, to and from university campuses, and to and from leisure activities located in the neighboring off-campus community.
Additional research is needed to examine replication among different populations that were not targeted in this study, such as other race and ethnicity identities, disability categories, ages, and more. Increasing the sample size should be explored in the future. There have been a few single-case studies examining the impact of various technology to teach campus navigation, but there has been a dearth in the literature regarding community navigation, and more replication is needed prior to making any conclusions.
Researchers should also examine the impact of peer-mediated instruction to teach college students with IDD the skills needed to be successful on campus and in the community. There is a scarcity of literature regarding peer-mediated interventions to teach college students with IDD self-advocacy skills, self-determination skills, and employability skills. Educators know how potent peer-mediated interventions are in teaching K–12 students social skills, communication skills, and academic skills, but the literature needs to be extended to include students with IDD enrolled in PSE programs.
Conclusion
This study extends previous research demonstrating that college students with IDD can use technology to independently navigate a college campus. As PSE programs become more popular for students with IDD, educators need to identify quick and unobtrusive ways to teach students the requisite skills needed for admission to PSE programs, such as safe, independent campus navigation. Hand-held technological devices, such as smart phones, are natural supports for students with disabilities. Almost everyone on a college campus uses their smartphone numerous times throughout the day for a variety of skills, including organizational skills (calendar, notes, or reminders), leisure skills (social media or internet access), and communication skills (email, texting, or phone calls). A student holding a smartphone while walking around campus would not draw any undue attention. Having a peer-mediated technological intervention is one way to quickly increase student accessibility of the campus while maintaining high social validity outcomes for students with IDD.
Footnotes
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding
The author(s) received no financial support for the research, authorship, and/or publication of this article.
