IES Grant
Title: | Meta-Analysis Training Institute | ||
Center: | NCER | Year: | 2017 |
Principal Investigator: | Pigott, Therese | Awardee: | Georgia State University |
Program: | Methods Training for Education Research [Program Details] | ||
Award Period: | 3 years (9/1/17 – 08/31/20) | Award Amount: | $797,760 |
Type: | Training | Award Number: | R305B190002 |
Description: | Previous Award Number: R305B170019 Co-Principal Investigators: Williams, Ryan; Polanin, Joshua; Tipton, Elizabeth; Beretvas, Natasha Purpose: Systematic reviews and meta-analyses can provide insight about what educational interventions work, for whom, and under what conditions. Large-scale meta-analyses can examine how intervention effects might vary across studies, providing insights about what we do or do not know about how to improve outcomes for all students. Thus, increasing the quality of systematic reviews and meta-analysis in education research enhances our understanding of important educational issues and highlights areas where more research is needed. The Meta-Analysis Training Institute provided researchers with the tools they need to conduct large-scale research syntheses and meta-analyses (50 or more studies) aimed at examining effect size heterogeneity. The program recruited participants who conducted education research in academic institutions or other settings who aimed to develop and submit an IES proposal to carry out meta-analysis. Project Activities: Participants: The training team held three summer training institutes in August 2018, July 2019, and July 2022. (The third training was delayed due to disruptions caused by COVID-19.) The team recruited participants from higher education institutions and research firms, with a particular emphasis placed on recruiting women and minority group members. They received a total of 361 applicants across the 3 sessions and accepted 107 participants. The team reviewed the applications and chose participants based on prior meta-analysis experience, statistics background that included multilevel modeling, and IES grant proposal ideas. Recruitment efforts achieved a level of ethnic diversity: 11 percent Black/African American, 28 percent Asian/Asian American, 8 percent Hispanic/Latino (any race), 58 percent White, and 2 percent Other. The participants were 35 percent male and 72 percent female. The majority (95 percent) of participants were faculty and research professionals, with 12 percent being doctoral students or recent graduates. Program Activities: The workshop took place over the course of 1 week. Each day, participants engaged in lecture sessions, hands-on practice with the methods, and a group project that culminated in a presentation at the end of the workshop. The training team provided each group with a dataset from a published meta-analysis that they used to apply the techniques discussed. The topics covered focus on methods for systematic review and meta-analysis that are rarely covered in introductory workshops and texts such as the use of screening software, multivariate and multivariate meta-analysis models, and selection models for publication bias. Participants learned to use the free software R to conduct meta-analysis. At the end of the week, participants chose to attend sessions on more specialized topics such as evidence and gap maps, meta-analysis for structural equation models and single-case design meta-analysis. Key Outcomes:
Related IES Projects: Meta-Analysis Training Institute (R305B220007) Products and Publications ERIC Citations: Find available citations in ERIC for this award here or here. Project Website: https://www.meta-analysis-training-institute.com/ Additional Online Resources and information: Select Publications: Pigott, T. D., & Polanin, J. R. (2020). Methodological guidance paper: High-quality meta-analysis in a systematic review. Review of Educational Research, 90(1), 24–46. doi.org/10.3102/0034654319877153 Polanin, J. R., Pigott, T. D., Espelage, D. L., & Grotpeter, J. (2019). Best practice guidelines for abstract screening large-evidence systematic reviews and meta-analyses. Research Synthesis Methods, 10(3), 330–342. doi.org/10.1002/jrsm.1354 Polanin, J. R., Zhang, Q., Taylor, J. A., Williams, R. T., Joshi, M., & Burr, L. (2022). Evidence Gap Maps in Education Research. Journal of Research on Educational Effectiveness, 0(0), 1–21. doi.org/10.1080/19345747.2022.2139312 |
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