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Middle school math tutoring — September 2017


Could you provide research on tutoring in math for middle school students?


Following an established REL West research protocol, we conducted a search for research reports as well as descriptive study articles on tutoring in math for middle school students. The sources included ERIC and other federally funded databases and organizations, research institutions, academic research databases, and general Internet search engines (for details, please see the methods section at the end of this memo).

We have not evaluated the quality of references and the resources provided in this response. We offer them only for your information. Also, we searched for references through the most commonly used sources of research, but the list is not comprehensive and other relevant references and resources may exist.

Research References

Beal, C. R., Arroyo, I. M., Cohen, P. R., & Woolf, B. P. (2010). Evaluation of AnimalWatch: An intelligent tutoring system for arithmetic and fractions. Journal of Interactive Online Learning9(1), 64–77. Retrieved from

From the abstract: “Three studies were conducted with middle school students to evaluate a web-based intelligent tutoring system (ITS) for arithmetic and fractions. The studies involved pre- and post-test comparisons, as well as group comparisons to assess the impact of the ITS on students' math problem solving. Results indicated that students improved from pre to post-test after working with the ITS, whereas students who simply repeated the tests showed no improvement. Students who had more sessions with the ITS improved more than those with less access to the software. Improvement was greatest for students with the weakest initial math skills, who were also most likely to use the multimedia help resources for learning that were integrated into the software.”

Chappell, S., Arnold, P., Nunnery, J., & Grant, M. (2015). An examination of an online tutoring program's impact on low-achieving middle school students' mathematics achievement. Online Learning19(5), 37–53. Retrieved from

From the abstract: “The purpose of this mixed methods study was to determine the impact of synchronous online tutoring services on struggling middle school students’ mathematics achievement. The online tutoring was provided as a response to intervention (RTI) Tier 3 support (intensive, individualized intervention) in schools implementing a school-wide mathematics program that addresses Tier 1 (high-quality classroom instruction) and Tier 2 (small group interventions). We employed quasi-experimental, within- and between-group designs to examine impacts for 119 students in two schools to measure the tutoring's impact on mathematics assessment scores. We also conducted qualitative analyses of student and tutor post session commentary. The findings suggest that the tutoring contributed to statistically significant gains in student assessment scores post intervention. Online tutors' descriptions of their practice centered on ongoing progress monitoring of student learning, delivery of guided practice to students, the use of multiple explanations and representations of target concepts. Student perceptions of the online tutoring were predominately positive in nature.”

Gamble, B. E., Kim, S., & An, S. (2012). Impact of a middle school math academy on learning and attitudes of minority male students in an urban district. Journal of Urban Learning, Teaching, and Research, 813–25. Retrieved from

From the abstract: “A growing number of single-gender and after-school programs for youth continue to gain popularity within schools despite little empirical research regarding how these programs should be designed to achieve maximum success. The present study examined the effectiveness of a comprehensive middle school male academy program in terms of student achievement and attitudes toward learning. The results indicated that students who participated in the program improved their algebra readiness and interest in mathematics. Furthermore, there were gains in students' perceived importance of assignment completion, attitudes toward learning, goals for college, and self-concept. Implications for similar programs and future studies are discussed.”

Hanover Research. (2014). Best practices in math interventions. Washington, DC: Author. Retrieved from

From the report: “In the following report, Hanover Research examines best practices in math interventions across all grade levels. This report provides an overview of common practices, summarizes rigorous academic evaluations of math interventions, and concludes with profiles and evaluations of seven math intervention programs.”

Rothman, T., & Henderson, M. (2011). Do school-based tutoring programs significantly improve student performance on standardized tests? Research in Middle Level Education Online34(6), 1–10. Retrieved from

From the abstract: “This study used a pre-post, nonequivalent control group design to examine the impact of an in-district, after-school tutoring program on eighth grade students' standardized test scores in language arts and mathematics. Students who had scored in the near-passing range on either the language arts or mathematics aspect of a standardized test at the end of seventh grade were recruited to receive tutoring in either language arts (LA) or mathematics (MA), depending on the area of weakness. An analysis of covariance revealed that both groups of students tutored in LA (n = 23) or MA (n = 20) significantly outperformed a matched control group (p = .02 for LA; p = .04 for MA). Components of effective after-school academic programs are discussed.”

Simon, D. J., Abrams, L. M., McDonnough, J. T., McLeod, A. M., & Warren, B. J. (2008). Cross-age mentoring and achievement of at-risk minority middle school students. Metropolitan Universities19(4), 75–80. Retrieved from

From the abstract: “Project BEST (Basic Educational Skills and Training) is a mentoring program involving Virginia Commonwealth University students and area middle school students. In the two-tiered program, VCU faculty mentor the Project BEST college students who, in turn, serve as mentors to the middle school students. Activities include Saturday mathematics and science enrichment seminars, after-school tutoring, and a week-long mathematics and science summer camp. Outcomes of the program show that Project BEST has positively impacted students' academic achievement and achievement responsibility.”

What Works Clearinghouse. (2007). Middle school math (What Works Clearinghouse topic report). Washington, DC: Author. Retrieved from

From the abstract: “The What Works Clearinghouse (WWC) reviewed interventions to promote middle school students' math knowledge and skills. Because there is some variation in how school districts organize middle school, we considered curricula aimed at students in grades 6 through 9, covering one or more of the following content areas: numbers and operations, algebra, geometry, measurement, and data analysis and probability. Only core, comprehensive math curricula were eligible for inclusion in this review. These curricula extend over the course of one semester or more, are central to students' regular school instruction, and are based on any combination of text materials, manipulatives, computer software, videotapes, and other materials. The WWC looked at 361 studies. Of these, 203 appeared to be studies of practices or other interventions that did not qualify for our review. Of the 158 remaining studies, 21 studies of 7 curricula met our evidence standards, 4 without reservations and 17 with reservations. Altogether, the WWC looked at 34 interventions: 7 had studies that met WWC standards with or without reservations and 27 had studies that did not meet WWC evidence screens. No eligible studies were identified for an additional 16 programs at the time of this review. (The identification of eligible programs ended in September 2005, and that of eligible studies in July 2006.) The WWC rated the effectiveness of middle school math curricula based on the available research evidence. In looking at math achievement for the 7 curricula: ‘I Can Learn[R] Pre-Algebra and Algebra’ had positive effects; ‘Saxon Middle School Math’ had positive effects; ‘Cognitive Tutor’ had potentially positive effects; ‘The Expert Mathematician’ had potentially positive effects; and ‘UCSMP Algebra’ had potentially positive effects. Two other curricula had mixed effects on math achievement.”

Worley, J., & Naresh, N. (2014). Heterogeneous peer-tutoring: An intervention that fosters collaborations and empowers learners. Middle School Journal46(2), 26–32. Retrieved from

From the abstract: “The goal of the intervention peer-tutoring program described in this paper was to help pre-algebra students (tutees) deepen their knowledge of mathematical concepts by providing them an opportunity to collaborate with their peers—accelerated algebra students (tutors). Over the duration of the program, the tutees and tutors gained a mutual respect for one another as they realized that they could both learn from each other's distinctive learning experiences. In this paper, the authors outline key features of an HPT program that was implemented with a group of middle school students, and describe how this program impacted both the tutors' and the tutees' learning experiences.”

Other Resources

Dabney, K. P., Tai, R. H., Almarode, J. T., Miller-Friedmann, J. L., Sonnert, G., Sadler, P. M., & Hazari, Z. (2012). Out-of-school time science activities and their association with career interest in STEM. International Journal of Science Education2(1), 63–79. Abstract retrieved from

From the abstract: “Spurred by concerns about an inadequately sized science, technology, engineering, and mathematics (STEM) workforce, there has been a growing interest in out-of-school time (OST) science activities as a means to foster STEM career interest. This study examines the association between OST science activities and STEM career interest in university through a logistic regression model and the calculation of prototypical odds ratios. The analysis addresses two main research questions: What is the correlation among different forms of OST activities? And, controlling for student demographic and background variables, what specific forms of OST activities are associated with STEM career interest in university? The study uses data from the ‘Persistence Research in Science and Engineering’ survey (n = 6882), which employs a nationally representative sample of university students enrolled in introductory English courses. Results indicate that students' participation in OST activities, as well as their middle school interest in science and mathematics and their gender, plays a significant role in university career interest in STEM. Conclusions suggest that making OST clubs and competitions and the inclusion of non-fiction and science fiction within English Language Arts programs may be beneficial to the development of students in STEM careers. Limitations include the paucity of research examining which students participate in these activities and what specific features or characteristics benefit them.”

Dietrichson, J., Bog, M., Filges, T., & Klint Jorgensen, A. (2017). Academic interventions for elementary and middle school students with low socioeconomic status. Review of Educational Research87(2), 243–282. Abstract retrieved from

From the abstract: “Socioeconomic status is a major predictor of educational achievement. This systematic review and meta-analysis seeks to identify effective academic interventions for elementary and middle school students with low socioeconomic status. Included studies have used a treatment-control group design, were performed in OECD and EU countries, and measured achievement by standardized tests in mathematics or reading. The analysis included 101 studies performed during 2000 to 2014, 76% of which were randomized controlled trials. The effect sizes (ES) of many interventions indicate that it is possible to substantially improve educational achievement for the target group. Intervention components such as tutoring (ES = 0.36), feedback and progress monitoring (ES = 0.32), and cooperative learning (ES = 0.22) have average ES that are educationally important, statistically significant, and robust. There is also substantial variation in effect sizes, within and between components, which cannot be fully explained by observable study characteristics.”

Gutierrez, Jr., A. J. (2011). Match tutors: The research base for the effectiveness of tutoring. Oakland, CA: Achieve Learning and Resource Center. Retrieved from

From the report: “This summary highlights the considerable research done on effective tutoring programs and practices. Most studies have found that tutoring has had a major impact on the academic achievement of students. Research indicates that small group tutoring sessions (1:1) are better than large group tutoring sessions, tutoring is more effective in math, and that tutors of all ages can be effective. Researchers also found that programs with professionally trained tutors whose work is connected to the classroom see the largest academic gains. Integrating tutoring programs in schools across the United States could dramatically improve the academic performance of elementary, middle and high school students and help reduce the nation’s dropout crisis.”


Keywords and Search Strings

The following keywords and search strings were used to search the reference databases and other sources:

(Math OR mathematics) AND (tutoring OR mentoring OR “after school programs” OR “out-of-school time program”) AND (“middle school” OR “grades 6-8”)

Databases and Resources

We searched ERIC for relevant resources. ERIC is a free online library of over 1.6 million citations of education research sponsored by the Institute of Education Sciences. Additionally, we searched Google Scholar and PsychInfo.

Reference Search and Selection Criteria

When we were searching and reviewing resources, we considered the following criteria:

  • Date of the Publication: References and resources published for the last 15 years, from 2002 to present, were included in the search and review.
  • Search Priorities of Reference Sources: Search priority is given to study reports, briefs, and other documents that are published and/or reviewed by IES and other federal or federally funded organizations and academic databases, including ERIC, EBSCO databases, JSTOR database, PsychInfo, PsychArticle, and Google Scholar.
  • Methodology: Following methodological priorities/considerations were given in the review and selection of the references: (a) study types – randomized controlled trials, quasi-experiments, surveys, descriptive data analyses, literature reviews, policy briefs, etc., generally in this order; (b) target population, samples (representativeness of the target population, sample size, volunteered or randomly selected, etc.), study duration, etc.; and (c) limitations, generalizability of the findings and conclusions, etc.

This memorandum is one in a series of quick-turnaround responses to specific questions posed by educational stakeholders in the West Region (Arizona, California, Nevada, Utah), which is served by the Regional Educational Laboratory West at WestEd. This memorandum was prepared by REL West under a contract with the U.S. Department of Education’s Institute of Education Sciences (IES), Contract ED-IES-17-C-00014524, administered by WestEd. Its content does not necessarily reflect the views or policies of IES or the U.S. Department of Education nor does mention of trade names, commercial products, or organizations imply endorsement by the U.S. Government.