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Video Selfmodeling to Improve Academic Psychology in the Schools, Vol. 49(1), 2012 C 2011 Wiley Periodicals, Inc. View this article online at wileyonlinelibrary.com/journal/pits DOI: 10.1002/pits.20617 VIDEO SELF-MODELING TO IMPROVE ACADEMIC PERFORMANCE: A LITERATURE REVIEW MARY ANNE PRATER Brigham Young University NARI CARTER Brigham Young University CARYL HITCHCOCK University of Hawaii at Manoa PETER DOWRICK University of Hawaii at Manoa Video self-modeling (VSM) has been used for decades to effectively improve individuals’ behaviors and skills. The purpose of this review is to locate and analyze published studies that used VSM for typical school-based academic skills to determine the effect of VSM interventions on students’ academic performance. Only eight studies were located that met the selection criteria. Based on the results of these 8 studies, VSM shows promise for improving academic performance, although the small number of studies limits our ability to draw strong conclusions about the efficacy of VSM across the school age span and across various academic skills. C 2011 Wiley Periodicals, Inc. Modeling, an instructional approach based on the theory of observational learning, has been known for many years to be an effective teaching tool (Woolfolk, 2010). One factor influencing the power of modeling includes the use of models who are seen as similar to the target person (Schunk, Pintrich, & Meece, 2007), and oneself may be considered the most powerful model of all. In fact, Dowrick (1999) argues that observing oneself engaged in behavioral episodes should not be considered a special case of observational learning, but a “learning mechanism in its own right” (p. 36) and that it increases the likelihood of future occurrences of the behavior. Using the self as a model provides participants with information on how best to perform the skill and strengthens their beliefs in being able to do so (Dowrick, 1999). Two forms of self as model have been used in research and practice. Positive self-review involves catching the student demonstrating the desired skills accurately or appropriately and then showing the positive example to the student. By contrast, feedforward shows the individual performing a skill he or she has not yet acquired or not yet demonstrated in a challenging context (Dowrick, 1999). Positive self-review has application for increasing desirable behaviors that are currently mixed with nondesired behaviors and/or for engaging in disused or low-frequency skills (e.g., student engaged in on-task behavior with disruptive behaviors being edited out). Feedforward, on the other hand, captures individuals demonstrating successes they have not yet shown by combining component skills already in their repertoire or by transferring the context in which the individuals perform the behavior (e.g., students reading fluently from a reader currently at their frustration level, with pauses, mispronunciations, and decoding being edited out; Dowrick, Kim-Rupnow, & Power, 2006). Specif- ically, Dowrick (in press) proposes that component behaviors are reconfigured to produce new skills, with potential rapid “learning from the future” (also see the article by Peter Dowrick in this issue). With the creation and evolution of technological tools, video self-modeling (VSM) has gained prominence as a means for improving behavior skills of students, particularly those with disabilities or at risk for school failure (e.g., Baker, Lang, & O-Reilly, 2009; Buggey, 2007; Hart & Whalon, Correspondence to: Mary Anne Prater, Brigham YoungUniversity, Counseling Psychology and Special Education. McKay School of Education 340 MCKB Provo, UT 84602. E-mail: [email protected] 71 72 Prater et al. 2008). When using VSM, videotaped segments of a student’s performance are edited to present the student performing the desired skill without error. The edited video is then shown to the student. In the school setting, VSM has been used across a variety of skills and with a range of ages and types of students. For example, VSM has been effective in decreasing general disruptive classroom behaviors (e.g., Possell, Kehle, McLoughlin, & Bray, 1999), as well as increasing behaviors such as improving classroom participation (Hartley, Kehle, & Bray, 2002) and on-task behavior (Clare, Jenson, Kehle, & Bray, 2000). Studies have been conducted across a wide range of school ages, including preschool (e.g., Buggey, Hoomes, Sherberger, & Williams, 2011), elementary school (e.g., Hitchcock, Prater, & Dowrick, 2004), middle school (e.g., Kahn, Kehle, Jenson, & Clark, 1990), and high school (e.g., Cihak & Schrader, 2008), and with varying populations, such as those with autism (e.g., Bellini & Akullian, 2007), Tourette’s syndrome (e.g., Clarke, Bray, Kehle, & Truscott, 2001), and physical and cognitive disabilities (Dowrick & Raeburn, 1995). Although VSM has gained interest in research and classroom applications, relatively few studies have examined its effectiveness with academic tasks. In 2003, three of the authors were involved in a review of 18 VSM studies that had been conducted in school-based settings (Hitchcock, Dowrick, & Prater, 2003). Both published journal articles and federal grant reports were included in the review. The setting in which the research was conducted was used as a selection criterion, but the type of targeted skills was not. Thus, the studies examined included some academic skills (e.g., reading, math), but primarily classroom behaviors (e.g., fighting, disruptive behaviors). Hitchcock et al. (2003) concluded that these studies supported the efficacy of VSM to improve student outcomes in schools. We were interested in determining what research has been conducted to date using VSM to improve academic skills. This review seemed timely, given that (a) so few published studies of academic skills were located in the Hitchcock et al. (2003) review; (b) nearly a decade has passed since the Hitchcock et al. (2003) review; (c) technological tools have improved immensely, making videotaping and editing more readily available; and (d) there is increasing interest in interventions using visual media and students with disabilities, particularly for those on the autism spectrum. The purpose of this research was to locate and analyze published studies that used video self-modeling for typical school-based academic skills to determine the effect of video self-modeling on students’ academic performance. METHODS To review VSM research of academic performance, we searched Academic Search Premiere, ERIC, PsychINFO, PsychARTICLES, and Social Works Abstracts for published articles. The follow- ing search terms were used: video, self, modeling, monitoring, video self-modeling and disability*, read*, math, and write. The initial search yielded nearly 650 titles. We also examined reference lists of published literature reviews to identify any additional VSM research on the improvement of academic skills. Selection Criteria Articles were selected for review if they met the following criteria: (a) the research report was published, (b) the publication described a research study and was not a theoretical or opinion piece, (c) the independent variable was VSM, and (d) the dependent variable was an academic skill, such as reading, writing, or math, or a skill that directly influenced academic performance, such as engaging in academic activities and staying on task. We included engaged learning and on-task behavior because these behaviors affect academic learning in the classroom. Dissertations, theses, and other unpublished documents were excluded from the review, as were studies that focused on language development and communication skills, and behaviors that did not directly Psychology in the Schools DOI: 10.1002/pits VSM to Improve Academic Performance 73 influence academic performance, such as recitation of classroom rules. Eight published reports met the selection criteria. Reporting Descriptive Variables and Results We used the following categories to identify and report the descriptive variables of each study: purpose, participants, method, dependent variables and measures, independent variables, treatment integrity/inter-rater agreement, results, maintenance, generalization, and social validity. Each study is summarized under these categories in Tables 1 and 2. RESULTS Participants and Dependent Variables The eight studies reviewed involved 181 students. Participants were students aged 6 through 17 years who were identified as having disabilities (Delano, 2007; Hitchcock et al., 2004; Marcus & Wilder, 2009) and those at risk for academic difficulty. Academic behaviors studied included oral reading fluency (Bray, Kehle, Spackman, & Hintze, 1998; Dowrick et al., 2006; Hitchcock et al., 2004), reading comprehension (Hitchcock et al., 2004), written language (Delano, 2007), novel letter identification (Marcus & Wilder, 2009), and arithmetic (Schunk & Hanson, 1989). Two published reports focused on VSM of behaviors that influence academic performance, namely, voluntary participation (Hartley et al., 2002) and on-task behavior (Clare et al., 2000). Effects of Video Self-Modeling To investigate the effects of VSM on academic behaviors and on behaviors that influence academic performance, researchers created videos of participants that depicted them engaging in targeted behaviors. Specifically, researchers created and edited videos of students reading, answering comprehension questions, identifying letters, computing math problems, participating in reading lessons, and staying on task to provide students with self-models of
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