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Inter-Observer Agreement Inter-observer agreement was assessed on Alex’s target behavior, task completion, for 61% of the sessions <strong>and</strong> was assessed on his <strong>in</strong>dependent use of the token system for 40% of possible sessions. Troy’s target behavior, verbal request<strong>in</strong>g, was measured by two observers for 64% of his sessions <strong>and</strong> for <strong>in</strong>dependent use of his token system, for 52% of possible sessions. Inter-observer agreement was calculated by divid<strong>in</strong>g the smaller number of responses recorded by an observer by the larger number of responses recorded by the other observer (Richards, Taylor, Ramasamy, & Richards, 1999). Mean <strong>in</strong>ter-observer agreement for Alex was calculated at 100% for task completion data <strong>and</strong> 92% (range 50 to 100%) for <strong>in</strong>dependent use of the token system data, <strong>and</strong> for Troy was calculated at 98% (range 57 to 100%) for request<strong>in</strong>g data <strong>and</strong> 94% (range 60 to 100%) for <strong>in</strong>dependent use of the token system data. Results Figure 3 shows number of tasks completed <strong>and</strong> number of tokens taken <strong>in</strong>dependently dur<strong>in</strong>g each session by Alex. Figure 4 shows number of requests for help <strong>and</strong> number of tokens taken <strong>in</strong>dependently dur<strong>in</strong>g each session by Troy. Dur<strong>in</strong>g basel<strong>in</strong>e, Alex did not complete any tasks <strong>and</strong> Troy did not make any verbal requests for help. After self-monitor<strong>in</strong>g tra<strong>in</strong><strong>in</strong>g, both students showed <strong>in</strong>creases <strong>in</strong> their target behaviors. Alex <strong>in</strong>creased number of tasks completed <strong>in</strong> response to changes <strong>in</strong> required number of tasks. That is to say, each time the required number of tasks <strong>in</strong>creased from one to two, then three, then four, Alex met that requirement <strong>and</strong> earned his reward. Similarly, Troy <strong>in</strong>creased his verbal requests for help <strong>in</strong> response to number of times the task was sabotaged. That is to say that he met or exceeded his requirement (i.e., two requests, then four, then five, then six) dur<strong>in</strong>g all but two sessions dur<strong>in</strong>g the <strong>in</strong>tervention phases. On <strong>in</strong>stances where he exceeded the requirement, he chose to cont<strong>in</strong>ue work<strong>in</strong>g once he had earned his re<strong>in</strong>forcer, usually headphones, or he made multiple, repeated requests for help when the teacher did not respond quickly. Data on whether students took their earned token <strong>in</strong>dependently were collected beg<strong>in</strong>n<strong>in</strong>g with Session 9 for Alex <strong>and</strong> Session 14 for Troy. Prior to booster tra<strong>in</strong><strong>in</strong>g neither Alex (Sessions 9-11) nor Troy (Sessions 14-16) took any tokens <strong>in</strong>dependently. After booster tra<strong>in</strong>- Figure 3. Alex: Task completion <strong>and</strong> <strong>in</strong>dependent use of token system. 30 / <strong>Education</strong> <strong>and</strong> <strong>Tra<strong>in</strong><strong>in</strong>g</strong> <strong>in</strong> <strong>Developmental</strong> <strong>Disabilities</strong>-March 2005
<strong>in</strong>g, number of token taken <strong>in</strong>dependently <strong>in</strong>creased for both students. Discussion Figure 4. Troy: Request<strong>in</strong>g help <strong>and</strong> <strong>in</strong>dependent use of token system. This study <strong>in</strong>vestigated effects of self-monitor<strong>in</strong>g with two young adult males with mental retardation <strong>and</strong> autism. Specifically, this research sought to determ<strong>in</strong>e if self-monitor<strong>in</strong>g would <strong>in</strong>crease target behaviors, if such students could learn to use the self-monitor<strong>in</strong>g/ token system <strong>in</strong>dependently, <strong>and</strong> what modifications, if any, would be needed to <strong>in</strong>crease their <strong>in</strong>dependence. Initially, participants demonstrated no occurrences of their target behaviors. Use of prompts (e.g., verbal <strong>and</strong> gestural cues) was not sufficient to <strong>in</strong>crease task completion or verbal requests for help. However, results <strong>in</strong>dicate that that the <strong>in</strong>tervention was effective <strong>in</strong> systematically <strong>in</strong>creas<strong>in</strong>g respond<strong>in</strong>g for both participants’ target behaviors. Collateral effects were noted anecdotally for each participant, <strong>in</strong>clud<strong>in</strong>g <strong>in</strong>creased will<strong>in</strong>gness to complete work <strong>and</strong> <strong>in</strong>- creased verbal <strong>in</strong>teractions outside of tra<strong>in</strong><strong>in</strong>g sessions. Initial tra<strong>in</strong><strong>in</strong>g, which was associated with an <strong>in</strong>crease <strong>in</strong> target behaviors, was not sufficient to ensure students would take tokens they earned. Consequently, additional tra<strong>in</strong><strong>in</strong>g was implemented to establish <strong>in</strong>dependent selection of earned tokens. With this additional <strong>in</strong>tervention, each participant learned to <strong>in</strong>dependently use his token system the majority of the time, with the supplementation of <strong>in</strong>tensive booster session tra<strong>in</strong><strong>in</strong>g <strong>and</strong> a delayed prompt<strong>in</strong>g procedure. Independent use of the token systems was not always high, however. While booster sessions <strong>and</strong> prompt delay strategy were effective <strong>in</strong> <strong>in</strong>creas<strong>in</strong>g number of times participants took their earned tokens <strong>in</strong>dependently, even after the booster sessions, they cont<strong>in</strong>ued to require prompt<strong>in</strong>g dur<strong>in</strong>g several sessions (see Figure 3, Session 21 <strong>and</strong> Figure 4, Sessions 27-30, 33 <strong>and</strong> 35). Further research replicat<strong>in</strong>g <strong>and</strong> extend<strong>in</strong>g this study could determ<strong>in</strong>e if, given more time, the prompt delay strategy Self-monitor<strong>in</strong>g / 31
Page 1 and 2: Education
Page 7 and 8: Using Self-Monitor
Page 9 and 10: monitor their frequency of follow<s
Page 11 and 12: instructional task
Page 13 and 14: Figure 1. Percentage of correct res
Page 15 and 16: Social Validity Informal feedback f
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Page 19 and 20: ple characteristics of communicatio
Page 21 and 22: TABLE 1 Demographic Information, St
Page 23 and 24: TABLE 2 Levels of Social Preference
Page 25 and 26: esponses given by students
Page 27 and 28: (1997). The effects of peer network
Page 29 and 30: his or her monitorin</stron
Page 31 and 32: the five minute pe
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Page 37 and 38: self-monitoring to
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Page 43 and 44: While hearing the
Page 45 and 46: Figure 2. Graphic data for Alley. O
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Page 51 and 52: Computer-Based Video Instruction to
Page 53 and 54: ing materials. He
Page 55 and 56: Generalization Probe Procedures Pri
Page 57 and 58: Figure 1. Hyperstudio “card” wi
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Page 69 and 70: Figure 4. Kent’s performance on c
Page 71 and 72: Mirenda, P., Wilk, D., & Carson, P.
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Page 79 and 80: Figure 2. Number of correct respons
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lar challenge for school personnel
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TABLE 1 Participant Demographic Cha
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Figure 2. Graphic display of Nate
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TABLE 2 Individual and</str
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A functional relationship was estab
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