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Comparison of Technology-Based Presentation Modalities in Multiple Stimulus Job Task Preference Assessments

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Title: Comparison of Technology-Based Presentation Modalities in Multiple Stimulus Job Task Preference Assessments
Language: English
Authors: Lauren E. Mucha (ORCID 0000-0002-1159-230X), Lisa S. Cushing (ORCID 0000-0001-6789-3083)
Source: Focus on Autism and Other Developmental Disabilities. 2026 41(2):59-70.
Availability: SAGE Publications and Hammill Institute on Disabilities. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com
Peer Reviewed: Y
Page Count: 12
Publication Date: 2026
Document Type: Journal Articles
Reports - Research
Education Level: High Schools
Secondary Education
Descriptors: Autism Spectrum Disorders, Intellectual Disability, Students with Disabilities, Stimuli, Predictive Validity, Reinforcement, Preferences, Work Attitudes, Vocational Rehabilitation, Vocational Interests, Supported Employment, Special Education, Special Schools, High School Students, Transitional Programs
DOI: 10.1177/10883576251396812
ISSN: 1088-3576
1538-4829
Abstract: This study evaluated the effectiveness of video and electronic pictorial presentation modalities in multiple stimulus without replacement (MSWO) job task preference assessments through methods comparison and evaluation of predictive validity. The study was conducted in a Midwest U.S. school setting with eight transition-age students with ASD and ID. Variations of work task preference assessment, electronic picture-based and video-based MSWO, were compared to an established assessment method, tangible stimulus MSWO. Subsequently, the predictive validity of the assessments was evaluated by observing the task engagement of participants while performing the high- and low-preference work tasks. Results suggest that electronic pictorial and video MSWO assessments of preferences are accurate and effective with some individuals and not as effective as the object modality for others. Findings, limitations, and implications for research and practice are also discussed.
Abstractor: As Provided
Entry Date: 2026
Accession Number: EJ1503868
Database: ERIC
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  Value: <anid>AN0193226599;fdd01jun.26;2026Apr27.04:52;v2.2.500</anid> <title id="AN0193226599-1">Comparison of Technology-Based Presentation Modalities in Multiple Stimulus Job Task Preference Assessments </title> <p>This study evaluated the effectiveness of video and electronic pictorial presentation modalities in multiple stimulus without replacement (MSWO) job task preference assessments through methods comparison and evaluation of predictive validity. The study was conducted in a Midwest U.S. school setting with eight transition-age students with ASD and ID. Variations of work task preference assessment, electronic picture-based and video-based MSWO, were compared to an established assessment method, tangible stimulus MSWO. Subsequently, the predictive validity of the assessments was evaluated by observing the task engagement of participants while performing the high- and low-preference work tasks. Results suggest that electronic pictorial and video MSWO assessments of preferences are accurate and effective with some individuals and not as effective as the object modality for others. Findings, limitations, and implications for research and practice are also discussed.</p> <p>Keywords: autism spectrum disorders; employment; transition; assessment; intellectual disability</p> <p>In preparation for adult life, the [<reflink idref="bib22" id="ref1">22</reflink>] requires transition assessment of employment interests and preferences and the development of postsecondary employment goals for students with disabilities. Additionally, the Workforce Innovation and Opportunity Act was enacted to support students and individuals with significant disabilities in obtaining competitive employment in their communities ([<reflink idref="bib42" id="ref2">42</reflink>]). However, many adults with autism spectrum disorder (ASD) remain unemployed or underemployed ([<reflink idref="bib3" id="ref3">3</reflink>]; [<reflink idref="bib4" id="ref4">4</reflink>]; [<reflink idref="bib10" id="ref5">10</reflink>]; [<reflink idref="bib13" id="ref6">13</reflink>]; [<reflink idref="bib15" id="ref7">15</reflink>]). Individuals with ASD who have an additional diagnosis of intellectual disability (ID) are even less likely to obtain competitive employment outcomes ([<reflink idref="bib26" id="ref8">26</reflink>]). These individuals with significant disabilities can benefit from customized employment, a process that matches a job seeker's skills and interests with an employer's business needs ([<reflink idref="bib41" id="ref9">41</reflink>]; [<reflink idref="bib42" id="ref10">42</reflink>]). Job task preference is one aspect of career preference that can be evaluated during job development to find a match between a student's preferred job duties and the needs of an employer. Preferences for an overall career field and work setting are also important considerations in job matching. Often, traditional career interest assessments are not designed for the needs and characteristics of students with ASD and ID, and a more specialized approach is necessary to evaluate their interests and preferences so they can provide input in their employment planning. Given the poor employment outcomes for individuals with ASD and ID, the mandates of WIOA and IDEA, and the importance of including a student's preferences and interests in transition assessment and career planning, there is a need to develop effective methods of assessing the employment preferences of transition-age students with ASD and ID entering the workforce.</p> <hd id="AN0193226599-2">Job Task Preference Assessments</hd> <p>Systematic methods of work task preference assessment have been used with people with ASD and ID by presenting choices of objects, pictures, and spoken words that represent job tasks (e.g., [<reflink idref="bib8" id="ref11">8</reflink>]; [<reflink idref="bib33" id="ref12">33</reflink>]; [<reflink idref="bib34" id="ref13">34</reflink>]; [<reflink idref="bib37" id="ref14">37</reflink>]). Beginning in the late 1970s, numerous studies implemented stimulus preference assessments to successfully identify the job task preferences of individuals with significant disabilities ([<reflink idref="bib27" id="ref15">27</reflink>]). Most investigations used paired-task procedures, but the research literature also contains studies in which multiple options are presented at once (e.g., [<reflink idref="bib18" id="ref16">18</reflink>]; [<reflink idref="bib24" id="ref17">24</reflink>]; [<reflink idref="bib33" id="ref18">33</reflink>]). In the multiple stimulus without replacement (MSWO) assessment, the participant makes a selection from an array of options, the chosen item is removed from the array (i.e., not replaced), the remaining options are then presented, and the procedure continues until all options have been exhausted or the participant does not make another selection ([<reflink idref="bib14" id="ref19">14</reflink>]). Compared to paired-stimulus assessments, multi-stimulus assessments require less time to administer but are not as accurate for all participants and have not been studied as comprehensively as paired-task assessments ([<reflink idref="bib33" id="ref20">33</reflink>]; [<reflink idref="bib38" id="ref21">38</reflink>]). To date, most studies using stimulus preference assessments to evaluate job task preferences involved adult participants with ID, with limited inclusion of individuals with ASD. One study investigated the use of a multi-stimulus job task preference assessment with transition-age participants with both ASD and ID ([<reflink idref="bib38" id="ref22">38</reflink>]). Stimulus preference assessment could be a useful tool to incorporate student input in employment planning, but it has not been widely researched as a transition assessment in the school setting.</p> <hd id="AN0193226599-3">Technology-Based Presentation Modalities</hd> <p>In most studies of stimulus preference assessment involving work tasks, objects or task materials were used to present options, though some studies utilized alternative presentation modalities for choices, such as pictures and spoken words ([<reflink idref="bib8" id="ref23">8</reflink>]; [<reflink idref="bib34" id="ref24">34</reflink>]; [<reflink idref="bib38" id="ref25">38</reflink>]). Videos and still images from videos have been used to determine employment preferences of individuals with disabilities, by depicting overall jobs (e.g., [<reflink idref="bib20" id="ref26">20</reflink>]; [<reflink idref="bib40" id="ref27">40</reflink>]). In addition, videos have been used successfully in technology-based career preference assessments designed to be widely used with people with disabilities (e.g., [<reflink idref="bib12" id="ref28">12</reflink>]; [<reflink idref="bib17" id="ref29">17</reflink>]; [<reflink idref="bib28" id="ref30">28</reflink>]). However, these assessments may be too broad or complex for some individuals with higher support needs who require a more individualized assessment. In other studies, videos (e.g., [<reflink idref="bib2" id="ref31">2</reflink>]; [<reflink idref="bib6" id="ref32">6</reflink>]; [<reflink idref="bib21" id="ref33">21</reflink>]; [<reflink idref="bib36" id="ref34">36</reflink>]) and electronic pictures (e.g. [<reflink idref="bib1" id="ref35">1</reflink>]; [<reflink idref="bib11" id="ref36">11</reflink>]) have been used to evaluate preferences for reinforcers, videos, activities, and social interactions of participants with ASD. These studies explored the use of computers or tablets to present choices in paired or multi-stimulus formats. The majority of participants were children, with some adults in a few studies. However, transition-age youth were underrepresented.</p> <p>The use of technology-based work task assessments has possible advantages over tangible assessments that should be explored. The presentation of electronic pictures or videos on a tablet device offers ease of administration that eliminates the challenges of using bulky or differently sized objects. Electronic pictures and videos can be reused for multiple administrations of the assessment. Technology-based formats may be more accessible for educators and students who are adept at using iPads, but not familiar with traditional stimulus preference assessments. In addition, videos show the dynamic action of the job task rather than just the object used to complete the task. However, more research is needed to determine the accuracy and validity of work task preference assessments using modalities other than objects.</p> <hd id="AN0193226599-4">Purpose of the Study</hd> <p>In this study, existing procedures of stimulus preference assessment are combined with electronic presentation modalities. The purpose of the study is to determine if electronic picture-based and video-based MSWO preference assessments are effective in identifying work task preferences of transition-age students with ASD and ID. This is evaluated by comparing preference hierarchies produced by electronic picture-based and video-based assessments to object-based assessments, a method with established validity. In addition, task engagement during work sessions is measured to validate preferences identified by object, electronic picture, and video-based assessments.</p> <hd id="AN0193226599-5">Method</hd> <p></p> <hd id="AN0193226599-6">Setting and Participants</hd> <p>This study was conducted during the school day at two sites. The first site was a nonpublic special education school in a large midwestern city. The second site was a transition program that was part of a public high school in a suburb of a large Midwestern U.S. city. At the first site, activities were conducted in several classrooms and one office. In addition, two participants engaged in a weeding task outdoors. At the second site, all participants completed activities in the same classroom. Locations were selected to minimize distractions and allow for video recording of activities. The rooms contained a desk or table large enough to present six moderately sized objects and a chair for the participant. The researcher and research assistant were in the room during study activities, and a school staff person was in the room or nearby. Other students were not present during the study activities.</p> <p>Eligibility criteria for participants included (a) having an Individualized Education Program (IEP) and receiving special education services, (b) autism listed as the primary disability on the IEP, (c) documentation of intellectual disability, (d) minimum age of 15 years old, (e) documentation of legal guardianship if 18 years or older, (f) ability to see and point to objects placed on the table in front of them and pictures and videos on an iPad screen. School administrators from each site identified potential participants and disseminated recruitment materials to the parent(s) or guardian(s). Of eight completed permission forms from the first site, three individuals did not provide assent. Of the five permission forms that were returned at the second site, two students did not meet eligibility criteria. In total, eight students met eligibility criteria and participated in this study. Cameron, David, Elijah, Marshall, and Shane participated at site one, while Elliot, Emily, and Joseph were at site two. Participant demographics are displayed in Table 1.</p> <p>Table 1. Participant Characteristics and Job Tasks for Study on Multiple Stimulus Job Task Preference Assessments.</p> <p>Graph</p> <p> <ephtml> <table><colgroup><col align="left" /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /></colgroup><thead><tr><th align="center">Participant</th><th align="center">Age (yrs.)</th><th align="center">Gender</th><th align="center">Ethnicity</th><th align="center">Communication</th><th align="center">IQ score and assessment</th><th align="center">Tasks</th></tr></thead><tbody><tr><td>Cameron</td><td>20</td><td>M</td><td>Black</td><td>Verbal speech</td><td>45, Stanford Binet Intelligence Scales, 5th Edition</td><td>Use screwdriver, plant seeds, fold shirts, affix labels, fill salt, enter data</td></tr><tr><td>David</td><td>17</td><td>M</td><td>White/Hispanic</td><td>Verbal speech</td><td>47, Reynolds Intellectual Assessment Scale</td><td>Sort mail, cut vegetables, fold shirts, package, water plants, cut fabric</td></tr><tr><td>Elijah</td><td>18</td><td>M</td><td>Asian</td><td>Verbal speech</td><td>Not reported</td><td>Fill orders, set table, enter data, tape boxes, vacuum, use screwdriver</td></tr><tr><td>Elliot</td><td>19</td><td>M</td><td>Black</td><td>Verbal speech</td><td>Not reported</td><td>Cut fabric, use screwdriver, shred, plant seeds, make drink mix, fold shirts</td></tr><tr><td>Emily</td><td>21</td><td>F</td><td>White</td><td>Verbal speech</td><td>Not reported</td><td>Assemble boxes, fill orders, paint, label envelopes, sweep, file</td></tr><tr><td>Joseph</td><td>20</td><td>M</td><td>Black</td><td>AAC device</td><td>Not reported</td><td>Package, fold boxes, fill sugar caddy, use screwdriver, price items, hang shirts</td></tr><tr><td>Marshall</td><td>21</td><td>M</td><td>White</td><td>Verbal speech</td><td>Not reported</td><td>Fold boxes, shred, fill sugar caddy, hole punch, hang shirts, take out trash</td></tr><tr><td>Shane</td><td>19</td><td>M</td><td>White</td><td>AAC device</td><td>49, Wechsler Intelligence Scale for Children, 5th Edition</td><td>Make drink mix, vacuum, hang shirts, inspect items, package, shred</td></tr></tbody></table> </ephtml> </p> <p>1 <emph>Note</emph>. AAC = augmentative and alternative communication.</p> <hd id="AN0193226599-7">Materials</hd> <p>A representative object was identified for each job task included in the object-based preference assessments. The objects consisted of materials used to perform the work task. For each job task in the video-based assessments, a 5- to 10-second video clip was created from the recordings of the six-task, object-based assessments. Videos showed the participant manipulating the materials to perform the key actions of the work task and when possible, featured point-of-view perspective, as this was effective in a prior study ([<reflink idref="bib36" id="ref37">36</reflink>]). The videos were sized to approximately 560-point width by 315-point height on the iPad screen. Three videos were presented simultaneously on the screen in a horizontal orientation in the Keynote application, similar to prior studies ([<reflink idref="bib2" id="ref38">2</reflink>]). Still frames from the videos that show the participant performing the task were used for the electronic pictorial representation of each work task in the electronic picture-based assessments. The electronic pictures were the same size as the videos and were presented using the Keynote application, as in a prior study ([<reflink idref="bib1" id="ref39">1</reflink>]). A black, Generation 8 iPad with a black case was used for all technology-based assessments. Enough materials were gathered for each task so that the participants could work on each task in 1-minute increments during the preference assessments and for up to 5 minutes during longer work periods.</p> <hd id="AN0193226599-8">Procedure and Data Collection</hd> <p></p> <hd id="AN0193226599-9">Parent/Guardian and Teacher Questionnaires</hd> <p>A parent or guardian and a special education teacher completed a questionnaire for each participant. The questionnaire consisted of demographic information and ranking job tasks based on their opinion of the participant's preference, using a 4-point scale of <emph>really dislike</emph>, <emph>dislike</emph>, <emph>like</emph>, and <emph>really like</emph>. The list of 49 tasks was generated from the most common job families for individuals with ASD who entered the workforce after receiving vocational rehabilitation services ([<reflink idref="bib35" id="ref40">35</reflink>]) and school administrator feedback on the feasibility of tasks at each site.</p> <hd id="AN0193226599-10">Selection of Tasks</hd> <p>Direct observation of performance on task analysis was used to assess independence on at least six potentially preferred and six potentially nonpreferred tasks across a variety of job categories, identified from questionnaire responses. Participants performed the tasks given least to most prompting. The prompting hierarchy, ordered from least to most support, consisted of gestural, verbal, model, partial physical, and full physical prompts. The level of prompting needed for each step of the task was observed and used to calculate a percentage of independence. Criteria for tasks included in preference assessments were a minimum score of 60% independence and a range of no more than 20 percentage points (e.g., 75%–95%), to minimize confounding effects of task difficulty and prompting. All participants performed their tasks with 82% or greater independence. All tasks could be worked on for 1-minute and 5-minute intervals. Tasks included in preference assessments are listed in Table 1.</p> <hd id="AN0193226599-11">Preference Assessments</hd> <p>At least 12 MSWO preference assessments were conducted with each participant. Up to three assessments were conducted per day with a 5-minute break between assessments. The schedule was adjusted as needed to accommodate participants' stamina and attention by decreasing the number of assessments per day, thus extending study activities over more days. Six-task object-based assessments were conducted three times, using a procedure similar to prior studies (e.g., [<reflink idref="bib20" id="ref41">20</reflink>]; [<reflink idref="bib33" id="ref42">33</reflink>]). The initial assessment began by presenting each object and having the participant work on the corresponding task for 1 minute. Then, an array of object choices was presented, and the researcher prompted the participant to "pick one." The participant worked on the chosen task for 1 minute or until completion or refusal, given least to most prompting to complete the task correctly. This continued with the remaining tasks until all were completed, or the participant refused to choose after repeated instructions and reordering of choices. A fourth six-task assessment was added for Joseph because he only made a selection during the first-choice trial in one assessment and for Elijah due to a pattern of selection during the choice trials that matched the order in which the objects had been presented during the pairing procedure.</p> <p>Next, nine three-task assessments were conducted using high, moderate, and low preference tasks, as identified by the tangible six-task assessments. Three assessments of each type (object, electronic picture, video) were conducted in a randomized, counterbalanced order with one of each type administered per day. In the first assessment with the picture and video modalities, each picture or video was shown by itself on the iPad screen, and the participant worked on that task for 1 minute or until completion or refusal. Technology-based assessments followed a procedure much like the tangible assessments, with electronic pictures or videos presented on the iPad screen instead of actual objects. Previously chosen options were removed from the display, and the remaining task choices were centered but not resized on the screen for the second and third trials. After completing all assessments, the participants reported their preferred presentation method. The objects, an iPad with electronic pictures, and an iPad with videos were situated in an array on the table. The researcher named the modalities, asked the participant to select the one they liked best, and recorded their selection.</p> <hd id="AN0193226599-12">Task Engagement During Work Periods</hd> <p>Participants worked on their highest and lowest preference job tasks for 5-minute periods. If task preferences differed across assessment modalities, all three tasks were used. Up to four work periods were conducted per day in a randomized, counterbalanced order, and a minimum of five work periods were conducted with each task until a pattern emerged. Prior to the first work session with each task, the researcher demonstrated the task for one trial (e.g., hanging one shirt), and the participant completed one trial given least to most prompting as needed. To begin each work period, a timer was set, a cue was given to start work, and the participant was provided with enough material to work on the task for 5 minutes. The researcher provided assistance if requested or if necessary for correct performance of the task. If the participant was not engaged in the task, least to most prompting was given after one continuous minute of disengagement until the participant resumed work or refused. Two participants declined participation in a specific work period, one by stating he did not want to do a particular task and one by leaving the room prior to the scheduled end of the session. This was not provided as an option, but the researchers respected their decision, as participation is voluntary.</p> <hd id="AN0193226599-13">Dependent Variables</hd> <p>Selection response and task engagement were measured as dependent variables. The selection response is defined as touching or pointing to one of the objects or a picture or video on the iPad screen. The participant stating that they want to do the task was also counted as a selection. Task engagement was measured using momentary time sampling from video recordings of the work periods. The researcher determined whether the participant was on task or off task at the end of each 15-second interval. On task is defined as manipulating materials, asking for help, or receiving instructions, similar to prior research (e.g., [<reflink idref="bib32" id="ref43">32</reflink>]). If the participant was not working on the task, refusing prompting, moving away from the task or task materials, or engaging in another activity, the behavior was recorded as off task.</p> <hd id="AN0193226599-14">Interobserver Agreement and Procedural Fidelity</hd> <p>Interobserver agreement and procedural fidelity were conducted on 27% of six-task preference assessments, 26% of three-task assessments, and 33% of work periods. Interobserver agreement for assessments was calculated as the percentage of tasks and task positions in agreement between the original data sheet and a second coder's observation of the video recording. Agreement was 100% for task selection and position in the six-task and three-task assessments. For the work periods, reliability was determined by the percentage of intervals that the coding of "on task" or "off task" matched. Overall agreement was 97% (range of 90%–100%) for task engagement coding. To measure procedural fidelity, the researcher and secondary coder recorded the presence or absence of key procedural steps using a checklist. Overall, 99% of procedural steps were present (range of 94%–100%) for the six-task assessments. Procedural errors were not significant enough to disqualify the results of any assessment. All steps were present in all reviewed videos of three-task assessments. No procedural steps were missing during the work periods, although two videos had steps that were not observable from the video recording.</p> <hd id="AN0193226599-15">Design and Data Analysis</hd> <p>A methods comparison and evaluation of predictive validity were applied to evaluate the effectiveness of electronic picture and video presentation modalities in job task preference assessments. New variations of work task preference assessment, electronic picture-based and video-based MSWO, were compared to an established assessment method, tangible stimulus MSWO. Subsequently, the predictive validity of the assessments was evaluated by observing the task engagement of participants while performing the high- and low-preference work tasks, using an alternating treatments design similar to [<reflink idref="bib32" id="ref44">32</reflink>].</p> <p>The order in which tasks were selected was used to establish a preference hierarchy for each type of preference assessment. An overall preference hierarchy was determined by totaling the numbers representing the rank from each individual assessment and ranking those totals to establish the hierarchy using a point-based scoring approach ([<reflink idref="bib5" id="ref45">5</reflink>]). If a task was not chosen, it was given the highest possible rank (i.e., 3 or 6). The preference hierarchies were graphed and visually compared. The overall hierarchies and the highest and lowest-ranked work tasks were compared to determine matches between the results of the object-based three-task assessments and the other presentation modalities. In addition, rank-order correlation coefficients were calculated for the relationship between hierarchies for different modalities for each participant and across all participants. The task engagement data were analyzed to assess the predictive validity of the assessments. The percentage of intervals on task for each work session was graphed and visually inspected to determine differences and trends for each participant.</p> <hd id="AN0193226599-16">Results</hd> <p></p> <hd id="AN0193226599-17">Task Preference Hierarchies</hd> <p>The preference hierarchies depicting the rank order of tasks for each presentation type for each participant are shown in Figure 1. When comparing the hierarchies between object-based and electronic picture-based assessments, Cameron, Emily, and Shane had exact matches for their task rankings with both modalities. In addition, David, Elijah, and Joseph had the same top-ranking task; thus, 75% of participants had the same highest preference task with the object and picture modalities. However, two tasks shared the most preferred ranking in Joseph's picture-based results. The least preferred task from the picture modality matched object results for five of eight participants, though David had a tied ranking for two tasks. Hierarchies between the object and video modalities matched exactly for half of the participants: Cameron, Emily, Shane, and Elijah. In addition, Joseph had the same most preferred task with both the object and video presentation methods, totaling five participants with the same top-ranking task.</p> <p>Graph: Figure 1. Hierarchies of Task Preference.</p> <p>Cameron, Emily, and Shane maintained the same rank order of tasks across all three presentation modalities. The most preferred task was consistent across the three modalities for Elijah and Joseph. Although in Joseph's electronic picture assessment results, two tasks held the same rank as the number one task. David's results were similar between the object and electronic picture assessments but not between the object and video assessments. Elliot and Marshall's object-based preference assessment results did not match the electronic picture or the video-based assessment.</p> <hd id="AN0193226599-18">Rank-Order Correlation</hd> <p>The overall rank-order correlation between modalities was calculated using the results for all participants. There was a moderate, positive correlation between the rank order of tasks selected in object and electronic picture modalities (r<subs>s</subs> =.379, <emph>p</emph> =.068) and a low, positive correlation between object and video modalities (r<subs>s</subs> =.321, <emph>p</emph> =.126). The correlation between the electronic picture and video presentation modalities (r<subs>s</subs> =.544, <emph>p</emph> =.006) was moderate and statistically significant.</p> <p>Rank-order correlations between object, electronic picture, and video assessment results for each participant are displayed in Table 2. Hierarchies with exact matches were statistically significant, including the relationships between all modalities for Cameron, Emily, and Shane; the object and video hierarchies for Elijah; and the picture and video hierarchies for Marshall. Both Joseph and David had strong but not statistically significant correlations between their object and picture assessment results. There were moderate but not statistically significant correlations between Elijah's object and picture results and his picture and video results. Joseph's object and video results and Elliot's picture and video results also showed moderate but not statistically significant correlations. There was a perfect negative correlation between the results of Elliot's object and picture assessments. Additionally, Marshall's object and picture results and his object and video results had perfect negative correlations. David's object and video results had a strong negative correlation, and his picture and video results had a moderate negative correlation. Elliot's object and video results were also moderately negatively correlated.</p> <p>Table 2. Rank-Order Correlations for Study Participants.</p> <p>Graph</p> <p> <ephtml> <table><colgroup><col align="left" /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /></colgroup><thead><tr><th align="center">Participant</th><th align="center">Object–picture correlation</th><th align="center">Object–video correlation</th><th align="center">Picture–video correlation</th></tr></thead><tbody><tr><td>Cameron</td><td>1<xref ref-type="table-fn" rid="tfn2">*</xref></td><td>1<xref ref-type="table-fn" rid="tfn2">*</xref></td><td>1<xref ref-type="table-fn" rid="tfn2">*</xref></td></tr><tr><td>Emily</td><td>1<xref ref-type="table-fn" rid="tfn2">*</xref></td><td>1<xref ref-type="table-fn" rid="tfn2">*</xref></td><td>1<xref ref-type="table-fn" rid="tfn2">*</xref></td></tr><tr><td>Shane</td><td>1<xref ref-type="table-fn" rid="tfn2">*</xref></td><td>1<xref ref-type="table-fn" rid="tfn2">*</xref></td><td>1<xref ref-type="table-fn" rid="tfn2">*</xref></td></tr><tr><td>Elijah</td><td>0.5</td><td>1<xref ref-type="table-fn" rid="tfn2">*</xref></td><td>0.5</td></tr><tr><td>Joseph</td><td>0.866</td><td>0.5</td><td>0</td></tr><tr><td>David</td><td>0.866</td><td>−0.866</td><td>−0.5</td></tr><tr><td>Elliot</td><td>−1<xref ref-type="table-fn" rid="tfn2">*</xref></td><td>−0.5</td><td>0.5</td></tr><tr><td>Marshall</td><td>−1<xref ref-type="table-fn" rid="tfn2">*</xref></td><td>−1<xref ref-type="table-fn" rid="tfn2">*</xref></td><td>1<xref ref-type="table-fn" rid="tfn2">*</xref></td></tr></tbody></table> </ephtml> </p> <p>2 <emph>p</emph> <.01.</p> <hd id="AN0193226599-19">Task Engagement</hd> <p>Participants worked on their most and least preferred tasks for 5-minute work periods, and task engagement was recorded using momentary time sampling. Joseph, David, and Elliot worked on three tasks because their task preferences differed across assessment modalities. The percentage of intervals on task during the 5-minute work periods are graphed in Figure 2. Four participants, Cameron, Emily, Shane, and Elijah had high rates of task engagement during both tasks. Cameron and Elijah each had one task with a trend of slightly higher engagement. Emily and Shane each had a task that emerged with an upward trend and higher task engagement in the final sessions. Additionally, Emily and Elijah demonstrated less variability with one task.</p> <p>Graph: Figure 2. Percentage of Intervals on Task During Work Periods.</p> <p>The remaining four participants, Joseph, David, Elliot, and Marshall showed clearer differences in task engagement between tasks. Joseph was 100% on task during his last three sessions of packaging. His performance was inconsistent across sessions while folding boxes, and he had more off-task intervals while filling the sugar caddy. David was 100% on task during all sessions of sorting mail and had lower task engagement when cutting vegetables and folding shirts. Elliot had high task engagement with two tasks, using the screwdriver and cutting fabric, but was off task more while planting and verbally declined the task in the last session. Marshall's task engagement was consistently higher while assembling boxes as compared to filling the sugar caddy.</p> <hd id="AN0193226599-20">Modality Preference</hd> <p>Upon completion of the assessments and work periods, participants indicated their preferred presentation method. David, Emily, and Marshall were partial to the object modality whereas Elijah, Shane, and Elliot preferred the electronic picture modality. The video presentation modality was preferred by Joseph and Cameron.</p> <hd id="AN0193226599-21">Discussion</hd> <p>Identifying the employment interests and preferences of students with ASD and ID can be challenging, but it is essential in preparing individuals for paid employment in inclusive community settings. Task preference is a major component of overall career preference, and identification of preferred tasks can be a route to discovering a fulfilling career that includes those job duties. The major aim of this study was to determine if the electronic picture and video modalities were effective for presenting job task choices in MSWO preference assessments used with transition-age students with ASD and ID. The key findings are described regarding the validation of assessment results through task engagement data and the overall effectiveness of the assessments. Limitations of the study, areas for future research, and implications for practice are discussed.</p> <hd id="AN0193226599-22">Validation of Assessment Results Through Task Engagement Data</hd> <p>Task engagement on high and low preference tasks was analyzed to evaluate the validity of the preference assessments. When trends and consistency were visually examined, four participants' graphed data display small differences in engagement between tasks. These trends are consistent with the results of the preference assessments for Cameron, Emily, and Shane, who have matching results across all modalities. In addition, the trends in Elijah's task engagement data match his object and video assessment results and confirm the high preference task from his picture-based assessment. While similar rates of engagement for four participants do not show large distinctions between tasks, the small differences in trends give some validation of the results. Half of the participants' data show greater variations in engagement between tasks that allow for more definitive confirmation of preference. David's task engagement data match his object and electronic picture but not video assessment results. Elliot's task engagement trends are most consistent with his object-based assessment results and not consistent with his picture and video results. Marshall's graph shows a clear difference in task engagement between his two tasks, which matches his object-based assessments but not his picture or video results. Joseph's inconsistent performance of box assembly makes it difficult to determine a precise ranking based on task engagement, and his preferences may have shifted given exposure to the tasks over the longer work periods. Joseph's task engagement data correspond best with his picture-based assessment results, match his least preferred task from the object results, and contradict his video-based assessment results. Overall, task engagement data confirm the object-based assessment results for seven participants and are inconclusive for the other participant. Electronic picture-based assessment results are confirmed by task engagement for four participants, and the high preference task is confirmed for Elijah. Joseph's task engagement data are inconsistent, but most closely match his electronic picture results. Task engagement data do not confirm the electronic picture results of two participants. Rates of task engagement validate the video-based assessment results for half of the participants and do not match for the other half.</p> <hd id="AN0193226599-23">Overall Effectiveness of Video and Electronic Pictorial MSWO Assessment</hd> <p>The overarching focus of this study is evaluating the effectiveness of MSWO job task preference assessments using electronic picture and video presentation modalities. A match between assessment results and task engagement shows that the assessment accurately predicted the participant's preferences for the tasks when asked to work for a longer period of time. Correspondence with results from the object modality, which uses the most concrete, tangible representation of the task and is supported by prior research, provides additional validation for the electronic picture and video assessments ([<reflink idref="bib1" id="ref46">1</reflink>]; [<reflink idref="bib2" id="ref47">2</reflink>]; [<reflink idref="bib36" id="ref48">36</reflink>]). Both technology-based modalities were effective for some participants. Considering task engagement comparisons and the high, positive correlations with the object modality, the electronic picture-based assessment was highly effective for five of eight participants. It was effective with one additional participant, as the preferred task was identified. The video modality was effective for half of the participants based on correspondence with task engagement and perfectly matched results with the object-based assessment. One other participant had the same high preference task on object and video assessments, but task engagement was inconsistent. Of the three presentation methods, the object modality was the most effective and accurate based on task engagement data. The electronic picture and video assessments were effective with some but not all participants. Several participants were able to access multiple presentation modalities.</p> <hd id="AN0193226599-24">Limitations and Areas for Future Research</hd> <p>Although efforts were made to control study design and procedures, there are several limitations. Some procedures were inconsistent across participants. Due to challenges with Elijah, pre-exposure trials were eliminated after the initial assessment for subsequent participants. Therefore, the procedures to link the presented stimuli with the associated tasks may have been insufficient for some. Further, Elijah's least preferred task identified by the electronic picture modality was not included in his work periods.</p> <p>The range of tasks was restricted by COVID precautions and availability of space and equipment. A major limitation of the study is that tasks were selected from common job families ([<reflink idref="bib35" id="ref49">35</reflink>]) rather than from students' preferred job settings or career fields. This was due to students' limited job exposure because of disability, age, and COVID-related community restrictions. In addition, the inclusion of unfamiliar tasks could have confounding effects due to novelty and skill level, as participants could be more or less likely to engage in new activities. Some participants had not fully mastered all tasks, and they may have been less likely to select harder tasks that were not as reinforcing. Future studies could use familiar tasks or include more exposure to tasks prior to assessing preference to minimize these effects. In addition, only using tasks with similar high independence might have eliminated high-preference/low-skill tasks. Due to the number of potential tasks, we did not control for factors such as effort. Additionally, activities were simulated in the school environment and did not exactly replicate the way tasks would be done in community jobs, which could limit the generalization of identified preferences.</p> <p>In the present study, four participants maintained high rates of engagement with more than one task. It is possible they liked both tasks, were willing to comply with the researcher's stated or implied demands or performed a task because no other option was presented. Offering only one task at a time during work periods can create an absolute reinforcement effect. A concurrent operants design with two or more tasks available at the same time, as in [<reflink idref="bib23" id="ref50">23</reflink>], could allow for better comparison between tasks and may show greater differences in engagement for participants who are compliant and willing to work on most tasks. Another option for validating assessment results is a concurrent chains approach. Similar to [<reflink idref="bib29" id="ref51">29</reflink>] study, the participant would choose between tasks and then work on the selected task during the work period. This could be applied in community work settings where the tasks are typically performed, allowing work periods to more closely replicate actual work conditions.</p> <p>Additionally, the use of only one variable to evaluate predictive validity during work periods may have been insufficient in detecting differences in preference for some participants. Task engagement has frequently been used to validate work task preference (e.g., [<reflink idref="bib8" id="ref52">8</reflink>]; [<reflink idref="bib38" id="ref53">38</reflink>]), but other variables such as work rate and affective behaviors can also gauge preference or nonpreference (e.g., [<reflink idref="bib9" id="ref54">9</reflink>]; [<reflink idref="bib31" id="ref55">31</reflink>]). Affective behaviors were not specifically measured in this study, because low rates of behavior failed to confirm preferences for all individuals in prior studies (e.g., [<reflink idref="bib9" id="ref56">9</reflink>]; [<reflink idref="bib32" id="ref57">32</reflink>]; [<reflink idref="bib33" id="ref58">33</reflink>]; [<reflink idref="bib37" id="ref59">37</reflink>]). However, David and Marshall demonstrated behaviors signaling nonpreference (i.e., loud vocalizations, leaving the room) while performing less preferred tasks. Additionally, participants worked more fluently or productively during some work periods, showing differences in work rate. Task preference may manifest in different ways for different individuals, and metrics other than task engagement may have revealed clearer distinctions for some participants in the present study. A multi-dimensional approach to evaluating preference should be applied to fully capture indicators of preference for all participants.</p> <p>There are opportunities for further research to refine technology-based stimulus preference assessments and evaluate features for optimal use as a transition assessment. The number of stimuli presented in technology-based job task preference assessments can be increased, as in research on non-job preferences (e.g., [<reflink idref="bib1" id="ref60">1</reflink>]; [<reflink idref="bib2" id="ref61">2</reflink>]). Alternative ways of presenting work task choices should be explored, such as electronic pictorial choices without exposure to video, use of pictures for choice-making after viewing videos, and electronic picture or video choices without access to the tasks. In the present study, the comparison of the picture and video modalities generated the only statistically significant correlation between overall results. The pictures were stills from the videos, and both were presented on iPads, so it is logical that participants would respond similarly. Prior studies have successfully used still images to offer choices of videos (e.g., [<reflink idref="bib11" id="ref62">11</reflink>]) and stills from video models to present job choices ([<reflink idref="bib40" id="ref63">40</reflink>]). In contrast, [<reflink idref="bib30" id="ref64">30</reflink>] found that GIFs were more accurate than electronic pictures in identifying preferred social interactions. In the present study, moving images did not provide a benefit in electronic choice presentation when the participant experienced the actual task and a video self-model, but it is unclear if electronic images would be as accurate without those experiences.</p> <p>Further inquiry is warranted to determine why assessments are effective for some participants and not others and identify the necessary features for accurate assessment of employment preferences. The technology-based assessments were not successful with all participants in the present study. Without assessing prerequisite skill sets, it is unclear what characteristics or abilities are needed to access electronic picture and video modalities. Prior studies evaluated the discrimination and matching skills necessary for alternative presentation methods (e.g., [<reflink idref="bib7" id="ref65">7</reflink>]; [<reflink idref="bib25" id="ref66">25</reflink>]; [<reflink idref="bib34" id="ref67">34</reflink>]), a concept that can be applied to electronic pictures and videos on the iPad. Pre-teaching the association between the choice stimuli and the condition or task, as suggested by [<reflink idref="bib19" id="ref68">19</reflink>], is another avenue for future research that could improve the efficacy of assessments.</p> <p>Task preference is a major factor in job selection, as enjoyment of daily work duties contributes to job satisfaction. However, a limitation of job task preference assessment, as implemented in the present study, is the narrow focus on one aspect of a career. A robust transition assessment for employment includes additional considerations to match a student with a job ([<reflink idref="bib28" id="ref69">28</reflink>]). Workers with ASD and ID may have preferences for or sensitivity to environmental conditions and social expectations of a job that could be as important as or even outweigh task preference. [<reflink idref="bib23" id="ref70">23</reflink>] assessed preference for task features, a line of inquiry that can be expanded to include more aspects of the task and workplace. Skill in performing the job is another key factor in job matching ([<reflink idref="bib28" id="ref71">28</reflink>]), which was not thoroughly explored in the present study. In addition, participants were not asked why they chose a particular task, which could provide useful information for job development.</p> <hd id="AN0193226599-25">Implications for Practice</hd> <p>Job task preference assessments are underutilized in special education. While training in and use of preference assessments are common for board certified behavior analysts (BCBA), the majority of non-BCBA professionals have not been trained to use stimulus preference assessments ([<reflink idref="bib16" id="ref72">16</reflink>]). Furthermore, stimulus preference assessments are commonly used to identify reinforcers, and the use of these methods to assess job task preferences in the school setting has been largely overlooked. Research shows that job coaches can be trained to implement preference assessments with workers with disabilities (e.g., [<reflink idref="bib8" id="ref73">8</reflink>]). Teachers, school-based job coaches, vocational rehabilitation counselors, and other professionals working with transition-age students with ASD and ID should also be taught to implement preference assessments in order to evaluate transition-related preferences systematically.</p> <p>Educators and school personnel can integrate stimulus preference assessments into transition planning for students with ASD and ID who otherwise have challenges communicating their preferences and interests. Preference assessments can be a component of job exploration counseling during pre-employment transition services and would be valuable in preparing for supported, customized employment that focuses on matching a worker's preferences and abilities with an employer's needs. Preference assessment is a systematic approach to eliciting student input that can be used in making employment decisions, rather than overreliance on staff or family input, which research shows is not as accurate ([<reflink idref="bib33" id="ref74">33</reflink>]; [<reflink idref="bib38" id="ref75">38</reflink>]). When preferred tasks are identified, the job search can include workplaces where those tasks are performed and positions that include those duties. However, job task preference assessment focuses narrowly on one aspect of career preference. It is one useful tool among several means of gathering information, along with preference for an overall career field, evaluation of skills, environmental fit, and job availability. Preference assessment also has applications in transition planning beyond job task preference, such as exploring preferences for employment variables, living arrangements, and social and leisure aspects of adult life ([<reflink idref="bib6" id="ref76">6</reflink>]; [<reflink idref="bib39" id="ref77">39</reflink>]).</p> <p>An individualized approach is necessary when assessing job task preferences. In this study, preferred presentation modality differed across participants, and not all participants responded accurately to the technology-based modalities. Elliot's preferred modality of electronic pictures and Joseph's preferred modality, videos, did not demonstrate accurate results. Rather than avoid using a modality because of its ineffectiveness, it is important to find a way to improve access to the individual's preferred procedure. Pre-teaching the connection between the task and electronic representation, as suggested by [<reflink idref="bib19" id="ref78">19</reflink>], could increase accuracy for students who prefer to engage with technology-based assessments. Additionally, though it is efficient and produces a hierarchy, the multiple-stimulus procedure may not be successful for all individuals ([<reflink idref="bib33" id="ref79">33</reflink>]; [<reflink idref="bib38" id="ref80">38</reflink>]), and a single or paired-stimulus assessment may be implemented with these students. Observation of a student's affect and behavior while performing tasks can be used to evaluate effectiveness of the assessment procedure so that it can be adjusted as needed. However, observation alone does not provide opportunities for choice, and systematic preference assessments are particularly important for individuals who do not show clear outward indicators of preference. The approach to identifying preferences should be customized to the individual and drawn from methods supported by existing research.</p> <hd id="AN0193226599-26">Conclusion</hd> <p>This study extends the research on job task preference assessments using technology-based presentation modalities with transition-age students with both ASD and ID, a population underrepresented in existing research. Results suggest that the electronic pictorial and video MSWO assessments of job task preferences are accurate and effective with some individuals and not as effective as the established object modality for others. The electronic picture-based MSWO assessment results matched results from assessments using objects with a moderate to strong correlation for six of eight participants, while the video results corresponded at least moderately to object results for five participants. Furthermore, observation of task engagement validated electronic pictorial assessment results for four participants and confirmed the high preference task for one. One participant had inconsistent task engagement, and task engagement data contradicted electronic picture assessment results for two participants. Video-based assessment results were validated by task engagement for 50% of the participants. The object modality was accurate for nearly all participants. Overall, the electronic pictorial procedure was useful for 75% of participants, while the video-based assessment was effective for half. These results show the efficacy of technology-based assessments of job task preference for some individuals and offer opportunities for further research focused on refining electronic pictorial and video assessments to optimize accuracy and efficiency.</p> <ref id="AN0193226599-27"> <title> References </title> <blist> <bibl id="bib1" idref="ref35" type="bt">1</bibl> <bibtext> Brodhead M. 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(2014). https://<ulink href="http://www.govtrack.us/congress/bills/113/hr803">www.govtrack.us/congress/bills/113/hr803</ulink></bibtext> </blist> </ref> <ref id="AN0193226599-28"> <title> Footnotes </title> <blist> <bibtext> The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.</bibtext> </blist> <blist> <bibtext> The authors received no financial support for the research, authorship, and/or publication of this article.</bibtext> </blist> <blist> <bibtext> Lauren E. Mucha</bibtext> </blist> <blist> <bibtext>Graph</bibtext> </blist> <blist> <bibtext>https://orcid.org/0000-0002-1159-230X Lisa S. Cushing</bibtext> </blist> <blist> <bibtext>Graph https://orcid.org/0000-0001-6789-3083</bibtext> </blist> </ref> <aug> <p>By Lauren E. Mucha and Lisa S. Cushing</p> <p>Reported by Author; Author</p> </aug> <nolink nlid="nl1" bibid="bib22" firstref="ref1"></nolink> <nolink nlid="nl2" bibid="bib42" firstref="ref2"></nolink> <nolink nlid="nl3" bibid="bib10" firstref="ref5"></nolink> <nolink nlid="nl4" bibid="bib13" firstref="ref6"></nolink> <nolink nlid="nl5" bibid="bib15" firstref="ref7"></nolink> <nolink nlid="nl6" bibid="bib26" firstref="ref8"></nolink> <nolink nlid="nl7" bibid="bib41" firstref="ref9"></nolink> <nolink nlid="nl8" bibid="bib33" firstref="ref12"></nolink> <nolink nlid="nl9" bibid="bib34" firstref="ref13"></nolink> <nolink nlid="nl10" bibid="bib37" firstref="ref14"></nolink> <nolink nlid="nl11" bibid="bib27" firstref="ref15"></nolink> <nolink nlid="nl12" bibid="bib18" firstref="ref16"></nolink> <nolink nlid="nl13" bibid="bib24" firstref="ref17"></nolink> <nolink nlid="nl14" bibid="bib14" firstref="ref19"></nolink> <nolink nlid="nl15" bibid="bib38" firstref="ref21"></nolink> <nolink nlid="nl16" bibid="bib20" firstref="ref26"></nolink> <nolink nlid="nl17" bibid="bib40" firstref="ref27"></nolink> <nolink nlid="nl18" bibid="bib12" firstref="ref28"></nolink> <nolink nlid="nl19" bibid="bib17" firstref="ref29"></nolink> <nolink nlid="nl20" bibid="bib28" firstref="ref30"></nolink> <nolink nlid="nl21" bibid="bib21" firstref="ref33"></nolink> <nolink nlid="nl22" bibid="bib36" firstref="ref34"></nolink> <nolink nlid="nl23" bibid="bib11" firstref="ref36"></nolink> <nolink nlid="nl24" bibid="bib35" firstref="ref40"></nolink> <nolink nlid="nl25" bibid="bib32" firstref="ref43"></nolink> <nolink nlid="nl26" bibid="bib23" firstref="ref50"></nolink> <nolink nlid="nl27" bibid="bib29" firstref="ref51"></nolink> <nolink nlid="nl28" bibid="bib31" firstref="ref55"></nolink> <nolink nlid="nl29" bibid="bib30" firstref="ref64"></nolink> <nolink nlid="nl30" bibid="bib25" firstref="ref66"></nolink> <nolink nlid="nl31" bibid="bib19" firstref="ref68"></nolink> <nolink nlid="nl32" bibid="bib16" firstref="ref72"></nolink> <nolink nlid="nl33" bibid="bib39" firstref="ref77"></nolink>
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Items – Name: Title
  Label: Title
  Group: Ti
  Data: Comparison of Technology-Based Presentation Modalities in Multiple Stimulus Job Task Preference Assessments
– Name: Language
  Label: Language
  Group: Lang
  Data: English
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Lauren+E%2E+Mucha%22">Lauren E. Mucha</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-1159-230X">0000-0002-1159-230X</externalLink>)<br /><searchLink fieldCode="AR" term="%22Lisa+S%2E+Cushing%22">Lisa S. Cushing</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0001-6789-3083">0000-0001-6789-3083</externalLink>)
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="SO" term="%22Focus+on+Autism+and+Other+Developmental+Disabilities%22"><i>Focus on Autism and Other Developmental Disabilities</i></searchLink>. 2026 41(2):59-70.
– Name: Avail
  Label: Availability
  Group: Avail
  Data: SAGE Publications and Hammill Institute on Disabilities. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com
– Name: PeerReviewed
  Label: Peer Reviewed
  Group: SrcInfo
  Data: Y
– Name: Pages
  Label: Page Count
  Group: Src
  Data: 12
– Name: DatePubCY
  Label: Publication Date
  Group: Date
  Data: 2026
– Name: TypeDocument
  Label: Document Type
  Group: TypDoc
  Data: Journal Articles<br />Reports - Research
– Name: Audience
  Label: Education Level
  Group: Audnce
  Data: <searchLink fieldCode="EL" term="%22High+Schools%22">High Schools</searchLink><br /><searchLink fieldCode="EL" term="%22Secondary+Education%22">Secondary Education</searchLink>
– Name: Subject
  Label: Descriptors
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Autism+Spectrum+Disorders%22">Autism Spectrum Disorders</searchLink><br /><searchLink fieldCode="DE" term="%22Intellectual+Disability%22">Intellectual Disability</searchLink><br /><searchLink fieldCode="DE" term="%22Students+with+Disabilities%22">Students with Disabilities</searchLink><br /><searchLink fieldCode="DE" term="%22Stimuli%22">Stimuli</searchLink><br /><searchLink fieldCode="DE" term="%22Predictive+Validity%22">Predictive Validity</searchLink><br /><searchLink fieldCode="DE" term="%22Reinforcement%22">Reinforcement</searchLink><br /><searchLink fieldCode="DE" term="%22Preferences%22">Preferences</searchLink><br /><searchLink fieldCode="DE" term="%22Work+Attitudes%22">Work Attitudes</searchLink><br /><searchLink fieldCode="DE" term="%22Vocational+Rehabilitation%22">Vocational Rehabilitation</searchLink><br /><searchLink fieldCode="DE" term="%22Vocational+Interests%22">Vocational Interests</searchLink><br /><searchLink fieldCode="DE" term="%22Supported+Employment%22">Supported Employment</searchLink><br /><searchLink fieldCode="DE" term="%22Special+Education%22">Special Education</searchLink><br /><searchLink fieldCode="DE" term="%22Special+Schools%22">Special Schools</searchLink><br /><searchLink fieldCode="DE" term="%22High+School+Students%22">High School Students</searchLink><br /><searchLink fieldCode="DE" term="%22Transitional+Programs%22">Transitional Programs</searchLink>
– Name: DOI
  Label: DOI
  Group: ID
  Data: 10.1177/10883576251396812
– Name: ISSN
  Label: ISSN
  Group: ISSN
  Data: 1088-3576<br />1538-4829
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: This study evaluated the effectiveness of video and electronic pictorial presentation modalities in multiple stimulus without replacement (MSWO) job task preference assessments through methods comparison and evaluation of predictive validity. The study was conducted in a Midwest U.S. school setting with eight transition-age students with ASD and ID. Variations of work task preference assessment, electronic picture-based and video-based MSWO, were compared to an established assessment method, tangible stimulus MSWO. Subsequently, the predictive validity of the assessments was evaluated by observing the task engagement of participants while performing the high- and low-preference work tasks. Results suggest that electronic pictorial and video MSWO assessments of preferences are accurate and effective with some individuals and not as effective as the object modality for others. Findings, limitations, and implications for research and practice are also discussed.
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  Data: As Provided
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  Label: Entry Date
  Group: Date
  Data: 2026
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  Label: Accession Number
  Group: ID
  Data: EJ1503868
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1503868
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    Identifiers:
      – Type: doi
        Value: 10.1177/10883576251396812
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 12
        StartPage: 59
    Subjects:
      – SubjectFull: Autism Spectrum Disorders
        Type: general
      – SubjectFull: Intellectual Disability
        Type: general
      – SubjectFull: Students with Disabilities
        Type: general
      – SubjectFull: Stimuli
        Type: general
      – SubjectFull: Predictive Validity
        Type: general
      – SubjectFull: Reinforcement
        Type: general
      – SubjectFull: Preferences
        Type: general
      – SubjectFull: Work Attitudes
        Type: general
      – SubjectFull: Vocational Rehabilitation
        Type: general
      – SubjectFull: Vocational Interests
        Type: general
      – SubjectFull: Supported Employment
        Type: general
      – SubjectFull: Special Education
        Type: general
      – SubjectFull: Special Schools
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      – SubjectFull: High School Students
        Type: general
      – SubjectFull: Transitional Programs
        Type: general
    Titles:
      – TitleFull: Comparison of Technology-Based Presentation Modalities in Multiple Stimulus Job Task Preference Assessments
        Type: main
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            NameFull: Lauren E. Mucha
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            NameFull: Lisa S. Cushing
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            – D: 01
              M: 06
              Type: published
              Y: 2026
          Identifiers:
            – Type: issn-print
              Value: 1088-3576
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              Value: 1538-4829
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              Value: 41
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              Value: 2
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            – TitleFull: Focus on Autism and Other Developmental Disabilities
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