TeachTown

TeachTown: Basics is a computer-assisted instructional (CAI) program that is now being used in over 200 school districts. This research-based intervention includes the following features-click here for a walk-through of the computer program.

Curriculum

The program includes a comprehensive curriculum that aligns to standardized measures (e.g. The Assessment of Basic Language and Learning Skills-Revised–ABLLS-R, Partington, 2008) and state content standards (e.g. California). The program was de

signed for students with Autism Spectrum Disorders (ASD) between the ages of 2 to 7 years developmentally. The curriculum includes the following learning domains: 1) Language Development; 2) Social and Emotional Skills; 3) Adaptive Skills; 4) Cognitive Skills; 5) Language Arts; and 6) Mathematics. Each domain has 5 levels: 1) Toddler; 2) Preschool; 3) Pre-K; 4) Kindergarten; and 5) Grade 1. Upon enrollment, the teacher completes a ranking questionnaire regarding the student’s current performance that places each student at a starting rank (i.e. level) for each domain. The curriculum is then dependent on student performance and is adjusted for each student. Teachers can customize the curriculum to meet IEP goals. See the Core Computer Curriculum attachment for an outline of the TeachTown: Basics scope and sequence.

ABA Teaching Approach

The instructional methodologies in the TeachTown: Basics program incorporate common techniques in Applied Behavior Analysis (ABA). Specifically, Discrete Trial instruction and Pivotal Response Training (PRT) are combined as follows: The program presents objectives in discrete tasks and guides learning through prompting and reinforcement (e.g. Lovaas, 1987). The student chooses and starts a lesson by clicking on a building in the town scene. Child-choice keeps motivation and attention to task high (e.g. Koegel, O’Dell, & Koegel, 1987). Depending on the student’s previous history with the lesson, a pre-test, learning exercise, or post-test is presented. Maintenance tasks are interspersed throughout the exercises and occur

for 20% of the trials. Maintenance tasks help the student preserve previously learned skills and keep the student motivated and on task (Koegel, et al, 1989). Each trial follows the discrete trial model (Lovaas, 1987; Smith, Groen, & Wynn, 2000) where the discriminative stimulus is presented (i.e. the instructional cue requiring student response) by presenting 1 or more images (e.g. a happy, sad, and angry face) with a vocal instruction (e.g. “Find the person that is happy”). Next, the student responds by selecting one of the images (e.g. clicks or touches [touch screen] the happy face). A correct response elicits a positive statement (e.g. “You did it!”) followed by a brief (3 second) inter-trial interval (i.e. pause between trials) and the next trial is presented. An incorrect response elicits an isolated lingering correct answer. Due to earlier findings, negative feedback is not included because of reinforcement potential. Students (particularly ASDs) in the pilot phase seemed to choose the incorrect images deliberately and repeatedly to hear the “negative” feedback (e.g. “Try again”). For pre and post-tests, 25 trials are presented including 4 different concepts (e.g. happy, sad, angry, confused). For learning trials, 15 trials are presented (with 3 maintenance trials) targeting at least 2 concepts (e.g. happy and sad). The standard mastery criterion is 80% correct (Lovaas, 1987; Smith, Groen, & Wynn, 2000). The TeachTown: Basics program also requires 80% correct. All responses are coded and presented graphically.

PromptingTrial difficulty is controlled by within-stimulus prompting which has been shown to result in better discrimination, generalization, and independence (i.e. prompt fading) in 1:1 trials (Schreibman, 1975) and using the computer (Panyan, 1984). When necessary, a least to most prompting strategy is utilized (stimuli are introduced in a weak [i.e. faded images] form and gradually strengthened [i.e. saturated images]). Gradually introducing distracters at the student’s pace maximizes learning and minimizes errors that help the student discriminate stimuli (Perez-Gonzalez & Williams, 2002).

Reinforcement

Correct answers are reinforced on a variable ratio schedule with rewards available approximately every 4 correct (or prompted) responses (VR-4). This intermittent sc

hedule of reinforcement has been effective for keeping responses high, particularly on the computer (e.g. Neef & Lutz, 2001). To access a reward (i.e. reinforcer), the student chooses from 6 options that include a variety of casual video games and brief cartoons. The student can play or watch for only 10-20 seconds and then returns to the next trial.

Automatic Data Collection and Reporting

The program contains data tracking and reporting to allow for student progress reports. Data is synchronized using a hosted data server and encrypted internet communication allowing student usage on any computer. Such synchronization allows for consistent programming and allows for school administrators to remotely track classrooms district-wide.

Generalization

Studies have shown that motivating teaching techniques can result in generalization (Koegel, Camarata, Valdez-Menchaca, & Koegel, 1998). Research indicates that the use of multiple exemplars is critical (Stokes & Baer, 1968; Jahr, 2001; Reeve, Reeve, Townsend, & Poulson, 2007). Varying the instructions and stimuli can result in better acquisition, motivation, and generaliz

ation (Dunlap & Koegel, 1980). In addition to providing a motivating platform for students, the program addresses generalization in many ways. Concepts are taught through several teaching modules including receptive identification (e.g. “Find the blue bird”) or identical and non-identical matching (e.g., “Match the tiger” or “Match the color to the object”). Varied instructions (e.g. Trial 1 “Do you see an airplane?”; Trial 2 “Which one is an airplane?”) and multiple exemplars (currently over 15,000 images and sounds) including photographs, drawn images, and animation (e.g. actions) are presented throughout the program. The stimuli in exercise trials are different from pre and post-tests to ensure concept learning rather than memorization. Generalization is also planned by teaching several concepts at a time instead of a common mass trial teaching strategy. The program also includes off-computer activities that encourage the application of computer learned skills, enhance understanding, and teach additional skills (e.g. communication, play, social, and motor skills).

Off-Computer Activities

Research indicates that structured teaching and naturalistic approaches may both positively effect different students (Bernard-Opitz, Ing, & Kong, 2004). To provide a program that is likely to benefit different students, TeachTown: Basics includes a structured approach (the computer program) and a naturalistic approach (the off-computer activities). All computer lessons are tied to off-computer activities. Although PRT (Koegel, 1989) and other naturalistic approaches (e.g. McGee, Daly, & Jacobs, 1994; Rogers & Dawson, 2010) are the recommended instructional methodology, the activities are written for caregivers and teachers. There are approximately 300 activities in the current manual that equally covers the learning domains and the developmental levels. See the sample activity in the attachments below - Friendship Faces.

Research on TeachTown: Basics

In a parent implementation study, a multiple-baseline design (2-5 weeks) was used with eight students (4 with ASD and 4 with Down Syndrome) using the program for 2 months (Whalen, et al., 2006). There was a significant change from pre to post-test scores (53% increase). Collateral effects were observed where the students with ASD demonstrated a 105% increase in language and social behaviors

on the computer compared to a play condition with their parent. They made more spontaneous comments (e.g. “Look, a rocket ship!”), more positive affect, and more joint attention behaviors (e.g. coordinated gaze). Inappropriate behaviors decreased both on and off the computer (61% decrease on computer and 44% decrease in off-computer activities compared to baseline play activities). This study offered promising results for using the program by means of parent implementation.

In another study, 47 preschool and K-1 students in ASD classrooms participated in a randomized efficacy study in the Los Angeles Unified School District (LAUSD) (Whalen, et al, 2010). Students were randomized by classroom with the treatment group receiving the intervention for 3 months while the control group remained in baseline (their regular educational program). Teachers in the trea

tment group had students use the computer program for 20-minutes and do an off-computer activity for 20-minutes per school day. Compared to the students in the control group, the treatment group showed more improvement overall on language and cognitive-developmental measures. In addition, students who used the program demonstrated significant progress. Students who used the program more showed greater gains on standardized measures than those students who used the program less. These findings offer possibilities for improving early school-age skills for students with ASD in a classroom setting and offer hope for a successful program that can be teacher implemented. Two follow-up studies are in progress using the LAUSD data, which will be included in the same paper (Whalen, et al, in progress). The first study looked at the within-subject effects of the program where the treatment group continued for an additional 3 months to assess changes at 3 vs. 6 months, and to assess the effectiveness of the program with the control group by comparing a 3-month baseline to a 3 month intervention phase. Results for certain learning domains show similar results to the between subjects analysis while results for other domains are inconsistent. For instance, auditory memory and expressive language domains seem to improve. However, the program had an inconsistent impact on receptive language and social skills. The second study looked at behaviors of students using the computer and doing 1:1 teaching activities with teachers. Motivation was consistently higher on the computer as measured by positive affect and joint attention behaviors (see IMFAR 2010 poster in attachments).

The most recent study was a replication of the LAUSD study in another school district with 94 students with ASD which also used the Brigance as one of the primary outcome measures (Whalen, et al, in progress). Results were similar to the LAUSD study in that the treatment group showed bigger changes on the Brigance in more domains than the control group. Many of these improvements were statistically significant. Future research will include more clinical trials, new product research and development, and comparing different teaching approaches.

Enjoy the videos of children using the computer program !

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