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Using videoconferencing to support teachers to conduct preference assessments with students with autism and developmental disabilities
Research in Autism Spectrum Disorders 3 (2009) 32–41
Contents lists available at ScienceDirect
Research in Autism Spectrum Disorders Journal homepage: http://ees.elsevier.com/RASD/default.asp
Using videoconferencing to support teachers to conduct preference assessments with students with autism and developmental disabilities Wendy Machalicek a, Mark O’Reilly a,*, Jeffrey M. Chan a, Mandy Rispoli a, Russell Lang a, Tonya Davis a, Karrie Shogren a, Audrey Sorrells a, Giulio Lancioni b, Jeff Sigafoos c, Vanessa Green c, Paul Langthorne d a
University of Texas at Austin, United States University of Bari, Italy Victoria University of Wellington, New Zealand d University of Kent, United Kingdom b c
A R T I C L E I N F O
A B S T R A C T
Article history: Received 6 March 2008 Accepted 12 March 2008
We used widely available videoconferencing equipment to support teachers to conduct preference assessments for three students with autism and developmental disabilities. Supervisors located at a university used videoconferencing equipment to collect data on students’ choice of items, the fidelity of teacher implementation of the assessment protocol, and to provide feedback to the teachers. Preference assessment results suggested a number of potentially reinforcing items for each student. In a second phase of the study, the students were given a routine classroom task to complete (i.e., clean up). The students could choose to complete the clean up task and gain access to a neutral item or one of the highly preferred items identified in the prior preference assessment. All students predominantly chose to complete the task in order to access a preferred item identified in the preference assessment. The results of this classroom intervention validated the results of the preference assessments. The findings of this study provide preliminary support for the use of videoconferencing equipment when supporting teaching personnel during common educational assessments. ß 2008 Elsevier Ltd. All rights reserved.
Keywords: Videoconferencing Preference assessment Teachers
* Corresponding author at: Department of Special Education, 1 University Station, D5300, The University of Texas at Austin, Austin, TX 78712, United States. Tel.: +1 512 471 7140. E-mail address: [email protected] (M. O’Reilly). 1750-9467/$ – see front matter ß 2008 Elsevier Ltd. All rights reserved. doi:10.1016/j.rasd.2008.03.004
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In many parts of the United States, there is an increasing shortage of specialists with the training to work with children with developmental disabilities (Boe & Cook, 2006; U.S. Department of Education, 2004a,2004b). Given current legislation that mandates the use of evidence-based practices (IDEA, 1990; IDEA Amendments, 1997; IDEA Improvement Act, 2004), the lack of teachers who are qualified to implement such practices may be problematic for many schools. This issue may be magnified for schools located in rural communities that face higher attrition rates than urban schools (Westling & Whitten, 1996), and limited access to personnel training programs (Ludlow, Conner, & Schechter, 2005). However, recent advances in videoconferencing technology may provide educators with one way to access the specialist support they need in a more efficient and cost effective manner. Videoconferencing technology enables two or more parties to simultaneously communicate using two way video and audio transmissions. In the health care field, videoconferencing is an increasingly common way to deliver services to patients who reside in communities with limited access to specialists (Hilty, Luo, Morache, Marcelo, & Nesbitt, 2002). This technology has facilitated psychiatric assessments (Elford, 2000; Zarate, Weinstock, & Baer, 1997), psychotherapy, and the supervision of trainee psychotherapists (Gammon, Sorlie, Bergvik, & Sorensen Hoifodt, 1998). It has also been used to provide follow up care for older adults following discharge from hospital (Tousignant, Boissy, Corriveau, & Moffet, 2006). Many special education teacher preparation programs have used videoconferencing technology to provide coursework and feedback to pre-service and in-service teachers in rural or remote settings for over two decades (Howard, Ault, Knowlton, & Swall, 1992). The majority of these initiatives have traditionally relied on broadcasts from Universities via satellite or fiber optic networks to local colleges or schools in rural or remote sites. There are some disadvantages in delivering instruction via satellite or fiber optic network. First, instructional delivery is limited to the geographic area serviced by satellite or fiber optic network. Second, technology needed to receive these broadcasts is expensive which limits the number of locales in remote areas that can receive such transmissions. Recent developments in videoconferencing technology may overcome many of the limitations inherent when using the above technology and also may present opportunities for using videoconferencing in novel ways to support teachers in rural and remote areas. In a recent report Ludlow and Duff (2002) described a distance education initiative at the University of West Virginia that delivered classes via video and audio streaming on the Internet. Students could participate in live classes and actively participate in class sessions using widely available and relatively inexpensive videoconferencing equipment (e.g., laptop or desktop computer, web camera, and broadband Internet connection). Conceivably, students could avail these live class sessions from any geographic location in the world if they have access to such videoconferencing equipment coupled with broadband Internet access. The portability of this new videoconferencing equipment (e.g., many laptop computers now come with an inbuilt web camera and can access the Internet using wireless technology) may open new avenues for the use of videoconferencing when working with pre-service and in-service special education teachers. For example, a teacher could now bring a laptop computer in to the classroom to facilitate live feedback from a specialist on any number of issues (e.g., conducting assessments, delivering instruction, classroom management, etc.). University supervisors could observe teachers delivering instruction in classrooms and provide immediate feedback on their performance while remaining at the University. When working in highly specialized teaching areas that require considerable attention to detail the opportunity to provide immediate feedback to student teachers on their performance is of critical importance. However, despite the potential usefulness of technology in the provision of on-site training to in-service and pre-service teachers little attention has been given to the way in which this technology may improve the skills of individuals working with students with disabilities. One of the fundamental assessment skills that graduate students who are specializing in autism and other developmental disabilities at the University of Texas at Austin must acquire is the ability to accurately conduct a preference assessment. Once preference assessment results have been obtained it is then possible for the teachers to develop individualized instructional interventions for the children in their classrooms.
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In the current study we attempted to examine the use of laptop computers equipped with web cameras and wireless capabilities to deliver supervision to student teachers who were learning to implement paired-choice preference assessments with children with autism and developmental disabilities in classroom settings. The preference assessment results were then used to develop an instructional intervention for the children in the classroom (i.e., the children were to complete a clean up task in order to gain access to a preferred item identified through the paired-choice preference assessment). In order to ascertain whether the training via videoconference was valid we anticipated that if the preference assessment has been conducted in an accurate way by the graduate student teachers (see Section 2) the results from the intervention (see Section 3) would show that the children would complete the task in order to have access to the preferred items. 1. Method 1.1. Participants and settings Three graduate students who were enrolled in the Autism and Developmental Disabilities graduate training program in the Department of Special Education at the University of Texas at Austin participated as teachers. During this study the graduate students were enrolled in a practicum experience that focused on teaching them best practices in assessment and instruction for young children with autism and other developmental delays. The graduate students had no experience implementing paired-choice preference assessments prior to the study. Each teacher was assigned to one student to conduct the paired-choice preference assessment (see below). The research was conducted at a private school for students with developmental delays. Three children with developmental delays participated in the study. Dusty (Caucasian male) and Eric (Asian American male) were 5 and 7 years of age, respectively, and were both diagnosed with autism. They attended the same classroom at the school. Hayden (Caucasian male) was 34 months old and was diagnosed with speech delay and pervasive developmental disorder. He attended a separate classroom for younger children at the same school. All phases of the research were conducted in the children’s classroom during regular class schedules. Three to five other students with similar disabilities and three staff were typically present in the classroom during assessment sessions, but worked in separate areas of the classroom during sessions. Instruction for students not involved in the research continued normally during experimental sessions. Observation, data collection, and supervision/coaching of the preference assessment procedures were conducted from a remote site (i.e., university office situated approximately 7 miles away from the participants’ school). Observation and supervision was conducted by three advanced doctoral students who were board certified behavior analysts and had extensive experience conducting research on the assessment and treatment of children with autism and developmental disabilities. The supervisors provided guidance to the teachers (i.e., graduate students) via the videoconferencing equipment, collected data on teacher’s performance of the preference assessment, and collected data on student’s preferences. 1.2. Videoconferencing equipment Videoconferencing between the classrooms and the University was achieved using (a) one 2.0 GHz MacBookTM laptop computer connected to one external iSightTM camera located in the classroom and (b) one iMacTM desktop computer with a built-in iSightTM camera located at the University. The laptop computer used in the classroom was secured to a chair next to the teacher. iChatTM videoconferencing software was used on both computers. Audio communication was achieved with a JabraTM bluetoothwireless headset worn by the teacher, while the supervisor used the iMacTM’s built-in microphone. A wireless connection was used to access the Internet. The iSightTM camera has a 640 480-pixel video graphics array (VGA), auto exposure, auto focus, and video capture at 30 frames per second. The iSightTM camera used in the classroom was attached via cable to the laptop computer and was placed on a plastic standing mount which was secured to a wide windowsill above the table where the assessment was implemented so that the university
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supervisor could see the entire assessment area. Data were transmitted via a wireless local area network (LAN) with Wi–Fi protected network access (WPN) maintained by the school where the research was conducted to a separate LAN maintained by the university. The confidentiality of data transmission was secured through subscription to an Internet service providing a virtual private network (VPN) with 128-bit encryption. 2. Phase I: preference assessment 2.1. Procedures The first phase of this experiment was designed to examine whether we could successfully use the videoconference technology to instruct pre-service teachers to conduct a preference assessment with children with developmental disabilities in their regular classroom settings, to collect data on the teacher’s performance of the preference assessment, and to collect data on the classroom student’s performance during the preference assessment. 2.1.1. Paired-choice preference assessment The teachers were taught to implement a paired-choice preference assessment with the students (Fisher et al., 1992; Lattimore, Parsons, & Reid, 2002). First, teachers were given a task analysis of how to implement a paired-choice preference assessment (see Table 1) and were told to practice this protocol with the target students prior to videoconferencing sessions. Teachers were also given a written list of eight items to be assessed using the paired-choice preference assessment protocol. Some items differed for each child and are presented in Table 2. The items selected for each child were deemed to be reinforcing for the child based on teacher and parent verbal reports. The list of items also included the sequence of pairing of the items as well as the location (left versus right) of each of the items that summed to a total of 84 pairing trials for each student. The teacher began the preference assessment by presenting the student with two items. If the student failed to approach either item within 5 s, the teacher withdrew this pair of items and moved on to the next trial. If the student touched one of the items, the teacher immediately removed the other item. The student was then given access to the chosen item for 5 s. If the student touched both items at the same time, the teacher held the two items down to the tabletop and waited for the participant to remove their hands from the table. The participant was once again allowed to choose between the two items. The 84 pairing trials were conducted over a 2-day period for each student. The total amount of time to conduct these trials did not exceed 2 h for each student.
Table 1 Preference assessment protocol Step Step Step Step Step
I II III IV V
Place two items on table in front of the student and wait 5 s for the student to touch an item If the student attempts to touch both items, block the attempt by securing the items to the tabletop. If the student touches an item, remove the other item. Allow the student to interact with the chosen item for 5 s If the student does not approach either item, move on to the next pair.
Table 2 Items used in preference assessments for each student Participant
Items
Dusty
ABC board (music toy), 2 ball castles (ball race), ball drop (musical ball race), frog (plastic frog), marble tube (marble race), noise tube (funny noise tube), train (wind up train) Male doll (action figure), fish (plastic fish), Mermaid (action figure), numbers (foam numbers), number puzzle, action board game, sand sifter, timer (kitchen timer) Ball castle (ball race), book (board book), toy car, lock box (box with latches and locks), 2 marble tubes (marble race), plastic monkeys, sand sifter with beans
Eric Hayden
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2.1.2. Supervision and data collection via videoconferencing At times that were mutually convenient for the pre-service teachers and university supervisors a video link was established between the university and the classroom. Cameras and headsets were then adjusted to ensure that the trials were visible and audible to the university supervisors and that communication via the headset worn by the teacher was clear. The university supervisors then indicated to the teacher where to begin on the list of pairings (e.g., ‘‘For Dusty we did the first 50 pairings on the list yesterday. So we need to start today with pairing 51 on the list which is ABC board placed on the right of the table and plastic frog placed on the left of the table.’’). The supervisor then indicated to the teacher to begin the trials. During each trial the supervisor collected data on the number of steps of the preference assessment task analysis performed correctly by the teacher (see Table 1) and the item chosen by the student (see Table 2). The supervisor also recorded those trials when the student did not select an item. Additionally, some of the preference assessment procedures were not relevant during each trial and hence were not included in the scoring (e.g., blocking the student (see step II in Table 1) was only scored during a trial if the student attempted to access both of the items simultaneously). The supervisor also delivered feedback to the teacher. Immediately following successful completion of a trial the supervisor delivered specific and positive feedback to the teacher (‘‘Great job! You correctly placed the two items in front of Dusty. You removed the marble tube immediately when he touched the train. You then let him play with the train for 5 s. Well done!’’). Any errors in implementing the preference assessment protocol were to be immediately interrupted by the supervisor and specific corrective feedback was to be delivered (‘‘You did not remove the ABC board when Dusty touched the noise tube. You need to remove the second item immediately when he touches the other item.). If an error occurred during a trial then that trial was to be repeated. This corrective feedback protocol however, was never implemented during the study, as the teachers did not make any errors when conducting the paired-choice assessment trials. 2.2. Interobserver agreement on student choice and teacher fidelity Two university supervisors simultaneously yet independently scored student choice (i.e., the item selected by the student) and teacher implementation of the preference assessment protocol on 67% of all assessment trials. Both supervisors simultaneously viewed the preference assessment trials on the same computer in the university setting. An agreement for student choice was scored if both observers agreed on the item selected by the student (e.g., both observers circled train as the item chosen by the student for that preference trial). A disagreement for student choice was scored if the observers disagreed on the item chosen by the student (e.g., one observer circled train as the item chosen by the student and the second observer circled lock box as the item chosen by the student). The total number of agreements was divided by the total number of trials and multiplied by 100%. Interobserver agreement on student choice for Dusty, Hayden, and Eric was 100%, 100%, and 98% (range: 96–100%), respectively. Both supervisors also used the task analysis in Table 1 to score teacher adherence to the preference assessment protocol during 67% of the trials. Interobserver agreement on teacher fidelity was calculated for each trial by totaling the number of steps that both observers agreed were implemented correctly by the total number of steps of the preference assessment protocol and multiplied by 100%. The results for each trial were then totaled and divided by the total number of trails during which reliability was conducted. Agreement on procedural fidelity was 100%, 99% (range: 98–100%), and 99% (range: 99–100%) for Dusty’s, Eric’s, and Hayden’s teachers, respectively. 2.3. Results and discussion All three pre-service teachers implemented the paired-choice assessment protocol with 100% accuracy during the observations. Such performance might be explained by the fact that the teachers were given a task analysis of the assessment protocol plus a list of the preferred items to be tested and were told to practice with the students prior to the observations. Additionally, student teachers received descriptive and comprehensive feedback from the university supervisor following each paired-choice assessment trial. These training protocols seem to be a relatively unobtrusive yet
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effective way of training pre-service teachers to implement core assessment protocol with students with autism and other developmental delays in classroom settings. These results do support previous research findings that have demonstrated that various combinations of prior instruction coupled with comprehensive feedback can produce rapid acquisition of instruction and assessment skills for teachers and child care staff (e.g., Dib & Sturmey, 2007; Lavie & Sturmey, 2002). One significant difference between our current research and the previous findings is that feedback was delivered to the teachers via videoconferencing. The results of the paired-choice preference assessments produced a clear pattern of preferences for Dusty, Eric, and Hayden. A ranking of eight preferred items was obtained for each participant. For Dusty, his three most frequently chosen items were the ball castle, ABC board, and ball drop, which he chose 90%, 71%, and 66% of the trials offered. His least frequently chosen item was the frog, which he chose on 19% of trials offered. For Eric, his three most frequently chosen items were the timer, fish, and numbers, which he chose 76%, 66%, and 66% of the trials offered. His least frequently chosen item was the little mermaid, which he chose 23% of trials offered. For Hayden, his three most frequently chosen items were the marble tube, ball castle, and sand sifter with beans, which he chose 90%, 61%, and 52% of the trials offered. His least frequently chosen item was the book, which he chose just 14% of trials offered. The first phase of this study demonstrated that it was possible to collect reliable data on pre-service teachers’ performance of paired-choice preference assessments and on classroom student responses using this widely available videoconferencing technology. It was also possible to provide ongoing feedback to teachers as they conducted these preference assessments via videoconferencing. The teachers did not err when conducting the preference assessments and this curtailed our evaluation of the effectiveness of corrective feedback contingent upon teacher errors using this technology. However, it is conceivable that comprehensive corrective feedback could be delivered immediately using this technology when a teacher errs. The pre-service teachers reported satisfaction with the supervision protocol. They noted that the videoconferencing was relatively unobtrusive during the preference assessment and that feedback from the supervisors was both helpful and positive. The university supervisors noted that the videoconferencing technology was relatively simple to implement and that there were very few technical difficulties when conducting supervision. During five observations of choice trials the Internet connection was lost and the supervisors had to reconnect to the classroom. Reconnection took less than 5 min during any of these observations and therefore did not significantly interfere with data collection. Additionally, these five choice trials were less than 1% of the total number of choice trials observed during this phase of the study. 3. Phase 2: instructional intervention In the second phase of this experiment we designed an instructional intervention for Dusty, Eric, and Hayden. This intervention was developed based on the results of the paired-choice preference assessment conducted in the first phase of the study. The reason for conducting this second phase was to examine whether the results of the preference assessment could be translated in to an effective classroom intervention for the students. A successful educational intervention derived from the results of the preference assessment would provide some support for the validity of the prior preference assessment and videoconferencing for training student teachers to conduct such assessments. The same teachers implemented the instructional intervention with the students under the guidance of the university supervisors. All observations and data collection procedures were conducted in the student’s classrooms. Videoconferencing was not used during this phase of the study. 3.1. Procedures and experimental design A task was selected that each of the three students had acquired, but often required prompting and physical guidance to complete: cleaning up instructional items from a tabletop. The student was presented with two identical tasks (placing five same color plastic screws into matching clear containers) on two separate tables placed approximately three feet apart. The three most frequently
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chosen items were selected from the prior preference assessment to serve as highly preferred items for each student. The classroom teachers identified the neutral item. On one table, a highly preferred item (selected from the prior preference assessment) was placed in plain view next to the clear container. On the other table, a neutral item (i.e., a cloth) was placed next to the clear container. Each of the three preferred items was presented an equal number of times and the presentation order of the three items was randomized over 42 trials for each student over 2 non-consecutive days. The position of the highly preferred and neutral item was randomly placed on the left or right table in order to account for possible position preference. Before each trial, the teacher walked the student to each table and said, ‘‘If you work here, you get ‘‘either the preferred item or the neutral item’’. The student was then brought back to a chair placed an equal distance from either table and the teacher said, ‘‘Choose one’’. The student’s choice of table was recorded when both of their feet crossed a taped line on the floor between the two tables. Once the student had completed the task (i.e., placing all five screws into the plastic container) he was allowed to access the associated item (highly preferred or neutral item) for 30 s. At the end of 30 s, another trial was initiated. If the student did not approach either task the teacher re-presented the trial. If the student approached a table, but did not engage in the task, a least-to-most prompting procedure was used to ensure task completion and the student was allowed to access the item. The student was blocked if he attempted to access the preferred or neutral item prior to completing the task and the trial was repeated. Student choice was measured and was operationalized as (a) selecting a task (crossing the line between the two tables), (b) independent completion of the task selected (without teacher prompting), and (c) subsequent engagement with the item (preferred or neutral) for 30 s. 3.2. Interobserver agreement Two independent observers collected data on each student’s choice of items during the intervention on 50% of the trials for Dusty and Hayden, and 40% of the trials for Eric. An agreement for a trial was scored if both independent observers agreed on the choice (as operationalized above). A disagreement was scored if the independent observers disagreed on student choice. The number of agreements were divided by the total number of trials and multiplied by 100%. Interobserver agreement for each of the three students was 100%.
Fig. 1. Cumulative frequency of Dusty’s choice of task associated with neutral and preferred items during intervention.
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Fig. 2. Cumulative frequency of Eric’s choice of task associated with neutral and preferred items during intervention.
3.3. Results and discussion The cumulative frequency of preferred and neutral item selection for Dusty, Eric, and Hayden is presented in Figs. 1–3, respectively. Each of the students consistently chose to complete the task associated with one of the preferred items over the neutral item. For Dusty, the total number of times
Fig. 3. Cumulative frequency of Hayden’s choice of task associated with neutral and preferred items during intervention.
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he chose one of his preferred items (ball castle, ABC board, and ball drop) was 27 times while he chose the neutral item 15 times. For Eric, the total number of times he choose one of his preferred items (timer, fish, and numbers) was 30 times while he chose the neutral item 12 times. For Hayden, the total number of times he choose one of his preferred items (marble tube, ball castle, and sand sifter with beans) was 30 times while he chose the neutral item 12 times. Overall, the results for phase 2 seem to indicate that the toys, selected from the results of the preference assessments (conducted in phase 1), were indeed preferred items capable of acting as reinforcers for a task demand. It appears that videoconferencing may offer a viable strategy for teacher educators to provide instructions and feedback to teachers, and other practitioners during preference assessments. 4. General discussion Videoconferencing has been used widely in the preparation and support of teachers over the last two decades (Howard et al., 1992). Recent developments in videoconferencing technology may facilitate new ways of using videoconferencing to facilitate the training and support of teachers in schools (Ludlow & Duff, 2002). In the current study we provided preliminary data on the use of relatively inexpensive videoconferencing equipment (computers equipped with web cameras and broadband Internet connection) to provide ongoing feedback to pre-service teachers as they learned to implement paired-choice preference assessment protocols with students with autism and related developmental disabilities. The results of this investigation demonstrated that the supervisors, located at a university setting, were able to observe the teachers implement the preference assessment protocol in real time and collect reliable data on several variables (i.e., teacher implementation of the assessment protocols and student outcomes). The university supervisors were also able to give immediate feedback to the student teachers on their performance in real time. Both the university supervisors and student teachers noted that the technology used was unobtrusive in the classroom setting and was relatively easy to use. The fact that we were able to use this technology to deliver immediate feedback to student teachers in real time emphasizes the strong potential of this technology in the preparation of pre-service teachers. Several empirical studies have suggested that immediate feedback on performance is the most powerful supervision strategy to enhance skill acquisition in new teachers (O’Reilly & Renzaglia, 1994). One of the perennial difficulties with immediate feedback is that university supervisors need to be present in the classroom to deliver such instruction to pre-service teachers. This suggestion is difficult, if not impossible, to implement in many teacher preparation programs as classroom practicum sites can be dispersed over large geographic areas and the ratios of university supervisors to student teachers can be burdensome. The use of laptop computers coupled with web cameras may overcome some of these logistical difficulties and allow university teacher preparation programs the opportunity to provide real time feedback to pre-service teachers as they learn critical teaching skills. This type of technology may also facilitate the availability of specialist support to schools that might otherwise be difficult to obtain. For example, a school district may require specialist support for a student who engages in severe challenging behavior. If that school district is in a geographically remote locale then accessing specialist support may be logistically and financially burdensome. The use of such videoconferencing equipment may overcome these difficulties. A specialist could observe the student with challenging behavior in real time in classroom settings, provide suggestions to teachers with regard to assessment and intervention, and provide ongoing follow up with such a case. This consultation could be potentially accomplished without the specialist ever traveling to the school district. Of course, this suggestion would need empirical verification. The suggestions above must be tempered by the fact that the current investigation is a preliminary one. Future research needs to replicate and extend these findings with pre-service and in-service teachers in school settings. The use of such videoconferencing protocols to facilitate other forms of assessment such as functional analysis of challenging behavior and student performance on instructional goals should be examined. Additionally, researchers should explore the use of videoconferencing as a method to support teachers when they are implementing intervention and
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teaching strategies such as positive behavior support plans, daily living, social and communication skills instruction with students. Some other forms of assessment and instructional intervention strategies may be more difficult to capture using videoconferencing as they may require transition to different settings in the classroom, school, or community. For example, it may be difficult to conduct a videoconferencing strategy as outlined in this study with a student who engages in challenging behavior in community settings such as the mall. Teachers may require face-to-face support in such circumstances or the use of more portable technology such as palmtop computers with web cameras and wireless facilities. Acknowledgement We wish to thank the Capital School of Austin for their support in conducting this research. References Boe, E., & Cook, L. (2006). The chronic and increasing shortage of fully certified teachers in special and general education. Exceptional Children, 72(4), 443–460. Dib, N., & Sturmey, P. (2007). Reducing student stereotypy by improving teachers’ implementation of discrete-trial training. Journal of Applied Behavior Analysis, 40(2), 339–343. Elford, R. (2000). A randomized controlled trial of child psychiatric assessments conducted using videoconferencing. Journal of Telemedicine and Telecare, 6(2), 73–82. Fisher, W., Piazza, C., Bowman, L., Hagopian, L., Owens, J., & Slevin, I. (1992). A comparison of two approaches for identifying reinforcers for persons with severe and profound disabilities. Journal of Applied Behavior Analysis, 25, 491–498. Gammon, D., Sorlie, T., Bergvik, S., & Sorensen Hoifodt, T. (1998). Psychotherapy supervision conducted via videoconferencing: A qualitative study of users’ experiences. Nordic Journal of Psychiatry, 52(5), 411–421. Hilty, D., Luo, J., Morache, C., Marcelo, D., & Nesbitt, T. (2002). Telepsychiatry: An overview for psychiatrists. CNS Drugs, 16(8), 527– 548. Howard, S., Ault, M., Knowlton, H., & Swall, R. (1992). Distance education: Promises and cautions for special education. Teacher Education and Special Education, 15(4), 275–283. Lattimore, P., Parsons, M., & Reid, D. (2002). A prework assessment of task preferences among adults with autism beginning a supported job. Journal of Applied Behavior Analysis, 35(1), 85–88. Lavie, T., & Sturmey, P. (2002). Training staff to conduct a paired-stimulus preference assessment. Journal of Applied Behavior Analysis, 35(2), 209–211. Ludlow, B., & Duff, M. (2002). Live broadcasting online: Interactive training for rural special educators. Rural Special Education Quarterly, 21(4), 26–30. Ludlow, B., Conner, D., & Schecter, J. (2005). Low incidence disabilities and personnel preparation for rural areas: Current status and future trends. Rural Special Education Quarterly, 24(3), 15–24. O’Reilly, M., & Renzaglia, A. (1994). A systematic approach to curriculum selection and supervision strategies: A preservice practicum supervision model. Teacher Education and Special Education, 17, 170–180. Tousignant, M., Boissy, P., Corriveau, H., & Moffet, H. (2006). In home telerehabilitation for older adults after discharge from an acute hospital or rehabilitation unit: A proof-of-concept study and costs estimation. Disability and Rehabilitation: Assistive Technology, 1, 209–216. IDEA Improvement Act. (2004). The Individuals with Disabilities Education Improvement Act of 2004. Pub. L. No. 108–446, § 101, Stat. 2647. IDEA Amendments. (1997). The Individuals with Disabilities Act Amendments of 1997. Pub. L. No. 17–105, § 101, 111 Stat. 37. IDEA. (1990). The Individuals with Disabilities Education Act of 1990. 20 U.S.C. §§ 1400 et seq. U.S. Department of Education. (2004a). IDEA Part B annual report tables. Personnel 2004. Table 3-2. http://www.ideadata.org/ tables29th%5Car_3-1.htm. Accessed 08.04.07. U.S. Department of Education. (2004b). IDEA Part B annual report tables. Personnel 2004. Table 3-1. http://www.ideadata.org/ tables29th%5Car_3-1.htm. Accessed 08.04.07. Westling, D., & Whitten, T. (1996). Rural special education teachers’ plans to continue or leave their teaching positions. Exceptional Children, 62(4), 319–355. Zarate, C., Weinstock, L., & Baer, L. (1997). Applicability of telemedicine for assessing patients with schizophrenia: Acceptance and reliability. The Journal of Clinical Psychiatry, 58(1), 22–25.
Contents lists available at ScienceDirect
Research in Autism Spectrum Disorders Journal homepage: http://ees.elsevier.com/RASD/default.asp
Using videoconferencing to support teachers to conduct preference assessments with students with autism and developmental disabilities Wendy Machalicek a, Mark O’Reilly a,*, Jeffrey M. Chan a, Mandy Rispoli a, Russell Lang a, Tonya Davis a, Karrie Shogren a, Audrey Sorrells a, Giulio Lancioni b, Jeff Sigafoos c, Vanessa Green c, Paul Langthorne d a
University of Texas at Austin, United States University of Bari, Italy Victoria University of Wellington, New Zealand d University of Kent, United Kingdom b c
A R T I C L E I N F O
A B S T R A C T
Article history: Received 6 March 2008 Accepted 12 March 2008
We used widely available videoconferencing equipment to support teachers to conduct preference assessments for three students with autism and developmental disabilities. Supervisors located at a university used videoconferencing equipment to collect data on students’ choice of items, the fidelity of teacher implementation of the assessment protocol, and to provide feedback to the teachers. Preference assessment results suggested a number of potentially reinforcing items for each student. In a second phase of the study, the students were given a routine classroom task to complete (i.e., clean up). The students could choose to complete the clean up task and gain access to a neutral item or one of the highly preferred items identified in the prior preference assessment. All students predominantly chose to complete the task in order to access a preferred item identified in the preference assessment. The results of this classroom intervention validated the results of the preference assessments. The findings of this study provide preliminary support for the use of videoconferencing equipment when supporting teaching personnel during common educational assessments. ß 2008 Elsevier Ltd. All rights reserved.
Keywords: Videoconferencing Preference assessment Teachers
* Corresponding author at: Department of Special Education, 1 University Station, D5300, The University of Texas at Austin, Austin, TX 78712, United States. Tel.: +1 512 471 7140. E-mail address: [email protected] (M. O’Reilly). 1750-9467/$ – see front matter ß 2008 Elsevier Ltd. All rights reserved. doi:10.1016/j.rasd.2008.03.004
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In many parts of the United States, there is an increasing shortage of specialists with the training to work with children with developmental disabilities (Boe & Cook, 2006; U.S. Department of Education, 2004a,2004b). Given current legislation that mandates the use of evidence-based practices (IDEA, 1990; IDEA Amendments, 1997; IDEA Improvement Act, 2004), the lack of teachers who are qualified to implement such practices may be problematic for many schools. This issue may be magnified for schools located in rural communities that face higher attrition rates than urban schools (Westling & Whitten, 1996), and limited access to personnel training programs (Ludlow, Conner, & Schechter, 2005). However, recent advances in videoconferencing technology may provide educators with one way to access the specialist support they need in a more efficient and cost effective manner. Videoconferencing technology enables two or more parties to simultaneously communicate using two way video and audio transmissions. In the health care field, videoconferencing is an increasingly common way to deliver services to patients who reside in communities with limited access to specialists (Hilty, Luo, Morache, Marcelo, & Nesbitt, 2002). This technology has facilitated psychiatric assessments (Elford, 2000; Zarate, Weinstock, & Baer, 1997), psychotherapy, and the supervision of trainee psychotherapists (Gammon, Sorlie, Bergvik, & Sorensen Hoifodt, 1998). It has also been used to provide follow up care for older adults following discharge from hospital (Tousignant, Boissy, Corriveau, & Moffet, 2006). Many special education teacher preparation programs have used videoconferencing technology to provide coursework and feedback to pre-service and in-service teachers in rural or remote settings for over two decades (Howard, Ault, Knowlton, & Swall, 1992). The majority of these initiatives have traditionally relied on broadcasts from Universities via satellite or fiber optic networks to local colleges or schools in rural or remote sites. There are some disadvantages in delivering instruction via satellite or fiber optic network. First, instructional delivery is limited to the geographic area serviced by satellite or fiber optic network. Second, technology needed to receive these broadcasts is expensive which limits the number of locales in remote areas that can receive such transmissions. Recent developments in videoconferencing technology may overcome many of the limitations inherent when using the above technology and also may present opportunities for using videoconferencing in novel ways to support teachers in rural and remote areas. In a recent report Ludlow and Duff (2002) described a distance education initiative at the University of West Virginia that delivered classes via video and audio streaming on the Internet. Students could participate in live classes and actively participate in class sessions using widely available and relatively inexpensive videoconferencing equipment (e.g., laptop or desktop computer, web camera, and broadband Internet connection). Conceivably, students could avail these live class sessions from any geographic location in the world if they have access to such videoconferencing equipment coupled with broadband Internet access. The portability of this new videoconferencing equipment (e.g., many laptop computers now come with an inbuilt web camera and can access the Internet using wireless technology) may open new avenues for the use of videoconferencing when working with pre-service and in-service special education teachers. For example, a teacher could now bring a laptop computer in to the classroom to facilitate live feedback from a specialist on any number of issues (e.g., conducting assessments, delivering instruction, classroom management, etc.). University supervisors could observe teachers delivering instruction in classrooms and provide immediate feedback on their performance while remaining at the University. When working in highly specialized teaching areas that require considerable attention to detail the opportunity to provide immediate feedback to student teachers on their performance is of critical importance. However, despite the potential usefulness of technology in the provision of on-site training to in-service and pre-service teachers little attention has been given to the way in which this technology may improve the skills of individuals working with students with disabilities. One of the fundamental assessment skills that graduate students who are specializing in autism and other developmental disabilities at the University of Texas at Austin must acquire is the ability to accurately conduct a preference assessment. Once preference assessment results have been obtained it is then possible for the teachers to develop individualized instructional interventions for the children in their classrooms.
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In the current study we attempted to examine the use of laptop computers equipped with web cameras and wireless capabilities to deliver supervision to student teachers who were learning to implement paired-choice preference assessments with children with autism and developmental disabilities in classroom settings. The preference assessment results were then used to develop an instructional intervention for the children in the classroom (i.e., the children were to complete a clean up task in order to gain access to a preferred item identified through the paired-choice preference assessment). In order to ascertain whether the training via videoconference was valid we anticipated that if the preference assessment has been conducted in an accurate way by the graduate student teachers (see Section 2) the results from the intervention (see Section 3) would show that the children would complete the task in order to have access to the preferred items. 1. Method 1.1. Participants and settings Three graduate students who were enrolled in the Autism and Developmental Disabilities graduate training program in the Department of Special Education at the University of Texas at Austin participated as teachers. During this study the graduate students were enrolled in a practicum experience that focused on teaching them best practices in assessment and instruction for young children with autism and other developmental delays. The graduate students had no experience implementing paired-choice preference assessments prior to the study. Each teacher was assigned to one student to conduct the paired-choice preference assessment (see below). The research was conducted at a private school for students with developmental delays. Three children with developmental delays participated in the study. Dusty (Caucasian male) and Eric (Asian American male) were 5 and 7 years of age, respectively, and were both diagnosed with autism. They attended the same classroom at the school. Hayden (Caucasian male) was 34 months old and was diagnosed with speech delay and pervasive developmental disorder. He attended a separate classroom for younger children at the same school. All phases of the research were conducted in the children’s classroom during regular class schedules. Three to five other students with similar disabilities and three staff were typically present in the classroom during assessment sessions, but worked in separate areas of the classroom during sessions. Instruction for students not involved in the research continued normally during experimental sessions. Observation, data collection, and supervision/coaching of the preference assessment procedures were conducted from a remote site (i.e., university office situated approximately 7 miles away from the participants’ school). Observation and supervision was conducted by three advanced doctoral students who were board certified behavior analysts and had extensive experience conducting research on the assessment and treatment of children with autism and developmental disabilities. The supervisors provided guidance to the teachers (i.e., graduate students) via the videoconferencing equipment, collected data on teacher’s performance of the preference assessment, and collected data on student’s preferences. 1.2. Videoconferencing equipment Videoconferencing between the classrooms and the University was achieved using (a) one 2.0 GHz MacBookTM laptop computer connected to one external iSightTM camera located in the classroom and (b) one iMacTM desktop computer with a built-in iSightTM camera located at the University. The laptop computer used in the classroom was secured to a chair next to the teacher. iChatTM videoconferencing software was used on both computers. Audio communication was achieved with a JabraTM bluetoothwireless headset worn by the teacher, while the supervisor used the iMacTM’s built-in microphone. A wireless connection was used to access the Internet. The iSightTM camera has a 640 480-pixel video graphics array (VGA), auto exposure, auto focus, and video capture at 30 frames per second. The iSightTM camera used in the classroom was attached via cable to the laptop computer and was placed on a plastic standing mount which was secured to a wide windowsill above the table where the assessment was implemented so that the university
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supervisor could see the entire assessment area. Data were transmitted via a wireless local area network (LAN) with Wi–Fi protected network access (WPN) maintained by the school where the research was conducted to a separate LAN maintained by the university. The confidentiality of data transmission was secured through subscription to an Internet service providing a virtual private network (VPN) with 128-bit encryption. 2. Phase I: preference assessment 2.1. Procedures The first phase of this experiment was designed to examine whether we could successfully use the videoconference technology to instruct pre-service teachers to conduct a preference assessment with children with developmental disabilities in their regular classroom settings, to collect data on the teacher’s performance of the preference assessment, and to collect data on the classroom student’s performance during the preference assessment. 2.1.1. Paired-choice preference assessment The teachers were taught to implement a paired-choice preference assessment with the students (Fisher et al., 1992; Lattimore, Parsons, & Reid, 2002). First, teachers were given a task analysis of how to implement a paired-choice preference assessment (see Table 1) and were told to practice this protocol with the target students prior to videoconferencing sessions. Teachers were also given a written list of eight items to be assessed using the paired-choice preference assessment protocol. Some items differed for each child and are presented in Table 2. The items selected for each child were deemed to be reinforcing for the child based on teacher and parent verbal reports. The list of items also included the sequence of pairing of the items as well as the location (left versus right) of each of the items that summed to a total of 84 pairing trials for each student. The teacher began the preference assessment by presenting the student with two items. If the student failed to approach either item within 5 s, the teacher withdrew this pair of items and moved on to the next trial. If the student touched one of the items, the teacher immediately removed the other item. The student was then given access to the chosen item for 5 s. If the student touched both items at the same time, the teacher held the two items down to the tabletop and waited for the participant to remove their hands from the table. The participant was once again allowed to choose between the two items. The 84 pairing trials were conducted over a 2-day period for each student. The total amount of time to conduct these trials did not exceed 2 h for each student.
Table 1 Preference assessment protocol Step Step Step Step Step
I II III IV V
Place two items on table in front of the student and wait 5 s for the student to touch an item If the student attempts to touch both items, block the attempt by securing the items to the tabletop. If the student touches an item, remove the other item. Allow the student to interact with the chosen item for 5 s If the student does not approach either item, move on to the next pair.
Table 2 Items used in preference assessments for each student Participant
Items
Dusty
ABC board (music toy), 2 ball castles (ball race), ball drop (musical ball race), frog (plastic frog), marble tube (marble race), noise tube (funny noise tube), train (wind up train) Male doll (action figure), fish (plastic fish), Mermaid (action figure), numbers (foam numbers), number puzzle, action board game, sand sifter, timer (kitchen timer) Ball castle (ball race), book (board book), toy car, lock box (box with latches and locks), 2 marble tubes (marble race), plastic monkeys, sand sifter with beans
Eric Hayden
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2.1.2. Supervision and data collection via videoconferencing At times that were mutually convenient for the pre-service teachers and university supervisors a video link was established between the university and the classroom. Cameras and headsets were then adjusted to ensure that the trials were visible and audible to the university supervisors and that communication via the headset worn by the teacher was clear. The university supervisors then indicated to the teacher where to begin on the list of pairings (e.g., ‘‘For Dusty we did the first 50 pairings on the list yesterday. So we need to start today with pairing 51 on the list which is ABC board placed on the right of the table and plastic frog placed on the left of the table.’’). The supervisor then indicated to the teacher to begin the trials. During each trial the supervisor collected data on the number of steps of the preference assessment task analysis performed correctly by the teacher (see Table 1) and the item chosen by the student (see Table 2). The supervisor also recorded those trials when the student did not select an item. Additionally, some of the preference assessment procedures were not relevant during each trial and hence were not included in the scoring (e.g., blocking the student (see step II in Table 1) was only scored during a trial if the student attempted to access both of the items simultaneously). The supervisor also delivered feedback to the teacher. Immediately following successful completion of a trial the supervisor delivered specific and positive feedback to the teacher (‘‘Great job! You correctly placed the two items in front of Dusty. You removed the marble tube immediately when he touched the train. You then let him play with the train for 5 s. Well done!’’). Any errors in implementing the preference assessment protocol were to be immediately interrupted by the supervisor and specific corrective feedback was to be delivered (‘‘You did not remove the ABC board when Dusty touched the noise tube. You need to remove the second item immediately when he touches the other item.). If an error occurred during a trial then that trial was to be repeated. This corrective feedback protocol however, was never implemented during the study, as the teachers did not make any errors when conducting the paired-choice assessment trials. 2.2. Interobserver agreement on student choice and teacher fidelity Two university supervisors simultaneously yet independently scored student choice (i.e., the item selected by the student) and teacher implementation of the preference assessment protocol on 67% of all assessment trials. Both supervisors simultaneously viewed the preference assessment trials on the same computer in the university setting. An agreement for student choice was scored if both observers agreed on the item selected by the student (e.g., both observers circled train as the item chosen by the student for that preference trial). A disagreement for student choice was scored if the observers disagreed on the item chosen by the student (e.g., one observer circled train as the item chosen by the student and the second observer circled lock box as the item chosen by the student). The total number of agreements was divided by the total number of trials and multiplied by 100%. Interobserver agreement on student choice for Dusty, Hayden, and Eric was 100%, 100%, and 98% (range: 96–100%), respectively. Both supervisors also used the task analysis in Table 1 to score teacher adherence to the preference assessment protocol during 67% of the trials. Interobserver agreement on teacher fidelity was calculated for each trial by totaling the number of steps that both observers agreed were implemented correctly by the total number of steps of the preference assessment protocol and multiplied by 100%. The results for each trial were then totaled and divided by the total number of trails during which reliability was conducted. Agreement on procedural fidelity was 100%, 99% (range: 98–100%), and 99% (range: 99–100%) for Dusty’s, Eric’s, and Hayden’s teachers, respectively. 2.3. Results and discussion All three pre-service teachers implemented the paired-choice assessment protocol with 100% accuracy during the observations. Such performance might be explained by the fact that the teachers were given a task analysis of the assessment protocol plus a list of the preferred items to be tested and were told to practice with the students prior to the observations. Additionally, student teachers received descriptive and comprehensive feedback from the university supervisor following each paired-choice assessment trial. These training protocols seem to be a relatively unobtrusive yet
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effective way of training pre-service teachers to implement core assessment protocol with students with autism and other developmental delays in classroom settings. These results do support previous research findings that have demonstrated that various combinations of prior instruction coupled with comprehensive feedback can produce rapid acquisition of instruction and assessment skills for teachers and child care staff (e.g., Dib & Sturmey, 2007; Lavie & Sturmey, 2002). One significant difference between our current research and the previous findings is that feedback was delivered to the teachers via videoconferencing. The results of the paired-choice preference assessments produced a clear pattern of preferences for Dusty, Eric, and Hayden. A ranking of eight preferred items was obtained for each participant. For Dusty, his three most frequently chosen items were the ball castle, ABC board, and ball drop, which he chose 90%, 71%, and 66% of the trials offered. His least frequently chosen item was the frog, which he chose on 19% of trials offered. For Eric, his three most frequently chosen items were the timer, fish, and numbers, which he chose 76%, 66%, and 66% of the trials offered. His least frequently chosen item was the little mermaid, which he chose 23% of trials offered. For Hayden, his three most frequently chosen items were the marble tube, ball castle, and sand sifter with beans, which he chose 90%, 61%, and 52% of the trials offered. His least frequently chosen item was the book, which he chose just 14% of trials offered. The first phase of this study demonstrated that it was possible to collect reliable data on pre-service teachers’ performance of paired-choice preference assessments and on classroom student responses using this widely available videoconferencing technology. It was also possible to provide ongoing feedback to teachers as they conducted these preference assessments via videoconferencing. The teachers did not err when conducting the preference assessments and this curtailed our evaluation of the effectiveness of corrective feedback contingent upon teacher errors using this technology. However, it is conceivable that comprehensive corrective feedback could be delivered immediately using this technology when a teacher errs. The pre-service teachers reported satisfaction with the supervision protocol. They noted that the videoconferencing was relatively unobtrusive during the preference assessment and that feedback from the supervisors was both helpful and positive. The university supervisors noted that the videoconferencing technology was relatively simple to implement and that there were very few technical difficulties when conducting supervision. During five observations of choice trials the Internet connection was lost and the supervisors had to reconnect to the classroom. Reconnection took less than 5 min during any of these observations and therefore did not significantly interfere with data collection. Additionally, these five choice trials were less than 1% of the total number of choice trials observed during this phase of the study. 3. Phase 2: instructional intervention In the second phase of this experiment we designed an instructional intervention for Dusty, Eric, and Hayden. This intervention was developed based on the results of the paired-choice preference assessment conducted in the first phase of the study. The reason for conducting this second phase was to examine whether the results of the preference assessment could be translated in to an effective classroom intervention for the students. A successful educational intervention derived from the results of the preference assessment would provide some support for the validity of the prior preference assessment and videoconferencing for training student teachers to conduct such assessments. The same teachers implemented the instructional intervention with the students under the guidance of the university supervisors. All observations and data collection procedures were conducted in the student’s classrooms. Videoconferencing was not used during this phase of the study. 3.1. Procedures and experimental design A task was selected that each of the three students had acquired, but often required prompting and physical guidance to complete: cleaning up instructional items from a tabletop. The student was presented with two identical tasks (placing five same color plastic screws into matching clear containers) on two separate tables placed approximately three feet apart. The three most frequently
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chosen items were selected from the prior preference assessment to serve as highly preferred items for each student. The classroom teachers identified the neutral item. On one table, a highly preferred item (selected from the prior preference assessment) was placed in plain view next to the clear container. On the other table, a neutral item (i.e., a cloth) was placed next to the clear container. Each of the three preferred items was presented an equal number of times and the presentation order of the three items was randomized over 42 trials for each student over 2 non-consecutive days. The position of the highly preferred and neutral item was randomly placed on the left or right table in order to account for possible position preference. Before each trial, the teacher walked the student to each table and said, ‘‘If you work here, you get ‘‘either the preferred item or the neutral item’’. The student was then brought back to a chair placed an equal distance from either table and the teacher said, ‘‘Choose one’’. The student’s choice of table was recorded when both of their feet crossed a taped line on the floor between the two tables. Once the student had completed the task (i.e., placing all five screws into the plastic container) he was allowed to access the associated item (highly preferred or neutral item) for 30 s. At the end of 30 s, another trial was initiated. If the student did not approach either task the teacher re-presented the trial. If the student approached a table, but did not engage in the task, a least-to-most prompting procedure was used to ensure task completion and the student was allowed to access the item. The student was blocked if he attempted to access the preferred or neutral item prior to completing the task and the trial was repeated. Student choice was measured and was operationalized as (a) selecting a task (crossing the line between the two tables), (b) independent completion of the task selected (without teacher prompting), and (c) subsequent engagement with the item (preferred or neutral) for 30 s. 3.2. Interobserver agreement Two independent observers collected data on each student’s choice of items during the intervention on 50% of the trials for Dusty and Hayden, and 40% of the trials for Eric. An agreement for a trial was scored if both independent observers agreed on the choice (as operationalized above). A disagreement was scored if the independent observers disagreed on student choice. The number of agreements were divided by the total number of trials and multiplied by 100%. Interobserver agreement for each of the three students was 100%.
Fig. 1. Cumulative frequency of Dusty’s choice of task associated with neutral and preferred items during intervention.
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Fig. 2. Cumulative frequency of Eric’s choice of task associated with neutral and preferred items during intervention.
3.3. Results and discussion The cumulative frequency of preferred and neutral item selection for Dusty, Eric, and Hayden is presented in Figs. 1–3, respectively. Each of the students consistently chose to complete the task associated with one of the preferred items over the neutral item. For Dusty, the total number of times
Fig. 3. Cumulative frequency of Hayden’s choice of task associated with neutral and preferred items during intervention.
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he chose one of his preferred items (ball castle, ABC board, and ball drop) was 27 times while he chose the neutral item 15 times. For Eric, the total number of times he choose one of his preferred items (timer, fish, and numbers) was 30 times while he chose the neutral item 12 times. For Hayden, the total number of times he choose one of his preferred items (marble tube, ball castle, and sand sifter with beans) was 30 times while he chose the neutral item 12 times. Overall, the results for phase 2 seem to indicate that the toys, selected from the results of the preference assessments (conducted in phase 1), were indeed preferred items capable of acting as reinforcers for a task demand. It appears that videoconferencing may offer a viable strategy for teacher educators to provide instructions and feedback to teachers, and other practitioners during preference assessments. 4. General discussion Videoconferencing has been used widely in the preparation and support of teachers over the last two decades (Howard et al., 1992). Recent developments in videoconferencing technology may facilitate new ways of using videoconferencing to facilitate the training and support of teachers in schools (Ludlow & Duff, 2002). In the current study we provided preliminary data on the use of relatively inexpensive videoconferencing equipment (computers equipped with web cameras and broadband Internet connection) to provide ongoing feedback to pre-service teachers as they learned to implement paired-choice preference assessment protocols with students with autism and related developmental disabilities. The results of this investigation demonstrated that the supervisors, located at a university setting, were able to observe the teachers implement the preference assessment protocol in real time and collect reliable data on several variables (i.e., teacher implementation of the assessment protocols and student outcomes). The university supervisors were also able to give immediate feedback to the student teachers on their performance in real time. Both the university supervisors and student teachers noted that the technology used was unobtrusive in the classroom setting and was relatively easy to use. The fact that we were able to use this technology to deliver immediate feedback to student teachers in real time emphasizes the strong potential of this technology in the preparation of pre-service teachers. Several empirical studies have suggested that immediate feedback on performance is the most powerful supervision strategy to enhance skill acquisition in new teachers (O’Reilly & Renzaglia, 1994). One of the perennial difficulties with immediate feedback is that university supervisors need to be present in the classroom to deliver such instruction to pre-service teachers. This suggestion is difficult, if not impossible, to implement in many teacher preparation programs as classroom practicum sites can be dispersed over large geographic areas and the ratios of university supervisors to student teachers can be burdensome. The use of laptop computers coupled with web cameras may overcome some of these logistical difficulties and allow university teacher preparation programs the opportunity to provide real time feedback to pre-service teachers as they learn critical teaching skills. This type of technology may also facilitate the availability of specialist support to schools that might otherwise be difficult to obtain. For example, a school district may require specialist support for a student who engages in severe challenging behavior. If that school district is in a geographically remote locale then accessing specialist support may be logistically and financially burdensome. The use of such videoconferencing equipment may overcome these difficulties. A specialist could observe the student with challenging behavior in real time in classroom settings, provide suggestions to teachers with regard to assessment and intervention, and provide ongoing follow up with such a case. This consultation could be potentially accomplished without the specialist ever traveling to the school district. Of course, this suggestion would need empirical verification. The suggestions above must be tempered by the fact that the current investigation is a preliminary one. Future research needs to replicate and extend these findings with pre-service and in-service teachers in school settings. The use of such videoconferencing protocols to facilitate other forms of assessment such as functional analysis of challenging behavior and student performance on instructional goals should be examined. Additionally, researchers should explore the use of videoconferencing as a method to support teachers when they are implementing intervention and
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teaching strategies such as positive behavior support plans, daily living, social and communication skills instruction with students. Some other forms of assessment and instructional intervention strategies may be more difficult to capture using videoconferencing as they may require transition to different settings in the classroom, school, or community. For example, it may be difficult to conduct a videoconferencing strategy as outlined in this study with a student who engages in challenging behavior in community settings such as the mall. Teachers may require face-to-face support in such circumstances or the use of more portable technology such as palmtop computers with web cameras and wireless facilities. Acknowledgement We wish to thank the Capital School of Austin for their support in conducting this research. References Boe, E., & Cook, L. (2006). The chronic and increasing shortage of fully certified teachers in special and general education. Exceptional Children, 72(4), 443–460. Dib, N., & Sturmey, P. (2007). Reducing student stereotypy by improving teachers’ implementation of discrete-trial training. Journal of Applied Behavior Analysis, 40(2), 339–343. Elford, R. (2000). A randomized controlled trial of child psychiatric assessments conducted using videoconferencing. Journal of Telemedicine and Telecare, 6(2), 73–82. Fisher, W., Piazza, C., Bowman, L., Hagopian, L., Owens, J., & Slevin, I. (1992). A comparison of two approaches for identifying reinforcers for persons with severe and profound disabilities. Journal of Applied Behavior Analysis, 25, 491–498. Gammon, D., Sorlie, T., Bergvik, S., & Sorensen Hoifodt, T. (1998). Psychotherapy supervision conducted via videoconferencing: A qualitative study of users’ experiences. Nordic Journal of Psychiatry, 52(5), 411–421. Hilty, D., Luo, J., Morache, C., Marcelo, D., & Nesbitt, T. (2002). Telepsychiatry: An overview for psychiatrists. CNS Drugs, 16(8), 527– 548. Howard, S., Ault, M., Knowlton, H., & Swall, R. (1992). Distance education: Promises and cautions for special education. Teacher Education and Special Education, 15(4), 275–283. Lattimore, P., Parsons, M., & Reid, D. (2002). A prework assessment of task preferences among adults with autism beginning a supported job. Journal of Applied Behavior Analysis, 35(1), 85–88. Lavie, T., & Sturmey, P. (2002). Training staff to conduct a paired-stimulus preference assessment. Journal of Applied Behavior Analysis, 35(2), 209–211. Ludlow, B., & Duff, M. (2002). Live broadcasting online: Interactive training for rural special educators. Rural Special Education Quarterly, 21(4), 26–30. Ludlow, B., Conner, D., & Schecter, J. (2005). Low incidence disabilities and personnel preparation for rural areas: Current status and future trends. Rural Special Education Quarterly, 24(3), 15–24. O’Reilly, M., & Renzaglia, A. (1994). A systematic approach to curriculum selection and supervision strategies: A preservice practicum supervision model. Teacher Education and Special Education, 17, 170–180. Tousignant, M., Boissy, P., Corriveau, H., & Moffet, H. (2006). In home telerehabilitation for older adults after discharge from an acute hospital or rehabilitation unit: A proof-of-concept study and costs estimation. Disability and Rehabilitation: Assistive Technology, 1, 209–216. IDEA Improvement Act. (2004). The Individuals with Disabilities Education Improvement Act of 2004. Pub. L. No. 108–446, § 101, Stat. 2647. IDEA Amendments. (1997). The Individuals with Disabilities Act Amendments of 1997. Pub. L. No. 17–105, § 101, 111 Stat. 37. IDEA. (1990). The Individuals with Disabilities Education Act of 1990. 20 U.S.C. §§ 1400 et seq. U.S. Department of Education. (2004a). IDEA Part B annual report tables. Personnel 2004. Table 3-2. http://www.ideadata.org/ tables29th%5Car_3-1.htm. Accessed 08.04.07. U.S. Department of Education. (2004b). IDEA Part B annual report tables. Personnel 2004. Table 3-1. http://www.ideadata.org/ tables29th%5Car_3-1.htm. Accessed 08.04.07. Westling, D., & Whitten, T. (1996). Rural special education teachers’ plans to continue or leave their teaching positions. Exceptional Children, 62(4), 319–355. Zarate, C., Weinstock, L., & Baer, L. (1997). Applicability of telemedicine for assessing patients with schizophrenia: Acceptance and reliability. The Journal of Clinical Psychiatry, 58(1), 22–25.