Great Tutors Could Be a Source of Great Teachers

blog_4-19-18_tutoring_500x329In a recent blog, I wrote about findings of three recent reviews of research on tutoring, contained within broader reviews of research on effective programs for struggling elementary readers, struggling secondary readers, and math. The blog reported the astonishing finding that in each of the reviews, outcomes for students tutored by paraprofessionals (teaching assistants) were as good, and usually somewhat better, than outcomes for students tutored by teachers.

It is important to note that the paraprofessionals tutoring students usually had BAs, one indicator of high quality. But since paras are generally paid about half as much as teachers, using them enables schools to serve twice as many struggling students at about the same cost as hiring teacher tutors. And because there are teacher shortages in many areas, such as inner cities and rural locations, sufficient teachers may not be available in some places at any cost.

In my earlier blog, I explained all this, but now I’d like to expand on one aspect of the earlier blog I only briefly mentioned.

If any district or state decided to invest substantially in high-quality paraprofessional tutors and train them in proven one-to-one and one-to-small group tutoring strategies, it would almost certainly increase the achievement of struggling learners and reduce retentions and special education placements. But it could also provide a means of attracting capable recent university graduates into teaching.

Imagine that districts or states recruited students graduating from local universities to serve in a “tutor corps.” Those accepted would be trained and mentored to become outstanding tutors. From within that group, tutors who show the greatest promise would be invited to participate in a fast-track teacher certification program. This would add coursework to the paraprofessionals’ schedules, while they continue tutoring during other times. In time, the paraprofessionals would be given opportunities to do brief classroom internships, and then student teaching. Finally, they would receive their certification, and would be assigned to a school in the district or state.

There are several features worth noting about this proposal. First, the paraprofessionals would be paid throughout their teacher training, because at all points they would be providing valuable services to children. This would make it easier for recent university graduates to take courses leading to certification, which could expand the number of promising recent graduates who might entertain the possibility of becoming teachers. Paying teacher education candidates (as tutors) throughout their time in training could open the profession to a broader range of talented candidates, including diverse candidates who could not afford traditional teacher education.

Second, the whole process of recruiting well-qualified paraprofessionals, training and mentoring them as tutors, selecting the best of them to become certified, and providing coursework and student teaching experiences for them, would be managed by school districts or states, not by universities. School districts and states have a strong motivation to select the best teachers, see that they get excellent training and mentoring, and proceed to certification only when they are ready. Coursework might be provided by university professors contracted by the district or qualified individuals within the district or state. Again, because the district or state has a strong interest in having these experiences be optimal for their future teachers, they would be likely to take an active role in ensuring that coursework and coaching are first rate.

One important advantage of this system would be that it would give school, district, and state leaders opportunities to see future teachers operate in real schools over extended periods of time, first as tutors, then as interns, then as student teachers. At the end of the process, the school district or state should be willing to guarantee that all who succeed in this demanding sequence will be offered a job. They should be able to do this with confidence, because school and district staff would have seen the candidate work with real children in real schools.

The costs of this system might be minimal. During tutoring, internships, and student teaching, teacher candidates are providing invaluable services to struggling students. The only additional cost would entail providing coursework to meet state or district requirements. But this cost could be modest, and in exchange for paying for or providing the courses, the district or state would gain the right to select instructors of very high quality and insist on their effectiveness in practice. These are the schools’ own future teachers, and they should not be satisfied with less than stellar teacher education.

The system I’m proposing could operate alongside of traditional programs provided by universities. School districts or states might in fact create partnerships in which all teacher education candidates would serve as tutors as part of their teacher education, in which case university-led and district-led teacher education may essentially merge into one.

This system is more obviously attuned to the needs of elementary schools than secondary schools, because historically tutors have been rarely used in the secondary grades. Yet recent evidence from studies in England (http://www.bestevidence.org/reading/mhs/mhs_read.htm) has shown positive effects of tutoring in reading in the middle grades, and it seems likely that one-to-one or one-to-small group tutoring would be beneficial in all major subjects and, as in elementary school, may keep students who are far behind grade level in a given subject out of special education and able to keep up with their classmates. If paraprofessional tutors can work in the secondary grades, this would form the basis for a teacher certification plan like the one I have described.

Designing teacher certification programs around the needs of recent BAs sounds like Teach for America, and in many ways it is. But this system would, I’d argue, be more likely to attract large numbers of talented young people who would be more likely than TFA grads to stay in teaching for many years.

The main reason schools, districts, and states should invest in tutoring by paraprofessionals is to serve the large number of struggling learners who exist in every district. But in the course of doing this, districts could also take control of their own destinies and select and train the teachers they need. The result would be better teachers for all students, and a teaching profession that knows how to use proven programs to ensure the success of all.

This blog was developed with support from the Laura and John Arnold Foundation. The views expressed here do not necessarily reflect those of the Foundation.

Advertisements

Effect Sizes: How Big is Big?

blog_4-12-18_elephantandmouseAn effect size is a measure of how much an experimental group exceeds a control group, controlling for pretests. As every quantitative researcher knows, the formula is (XT – XC)/SD, or adjusted treatment mean minus adjusted control mean divided by the unadjusted standard deviation. If this is all gobbledygook to you, I apologize, but sometimes us research types just have to let our inner nerd run free.

Effect sizes have come to be accepted as a standard indicator of the impact an experimental treatment had on a posttest. As research becomes more important in policy and practice, understanding them is becoming increasingly important.

One constant question is how important a given effect size is. How big is big? Many researchers still use a rule of thumb from Cohen to the effect that +0.20 is “small,” +0.50 is “moderate,” and +0.80 or more is “large.”  Yet Cohen himself disavowed these standards long ago.

High-quality experimental-control comparison research in schools rarely gets effect sizes as large as +0.20, and only one-to-one tutoring studies routinely get to +0.50. So Cohen’s rule of thumb was demanding effect sizes for rigorous school research far larger than those typically reported in practice.

An article by Hill, Bloom, Black, and Lipsey (2008) considered several ways to determine the importance of effect sizes. They noted that students learn more each year (in effect sizes) in the early elementary grades than do high school students. They suggested that therefore a given effect size for an experimental treatment may be more important in secondary school than the same effect size would be in elementary school. However, in four additional tables in the same article, they show that actual effect sizes from randomized studies are relatively consistent across the grades. They also found that effect sizes vary greatly depending on methodology and the nature of measures. They end up concluding that it is most reasonable to determine the importance of an effect size by comparing it to effect sizes in other studies with similar measures and designs.

A study done by Alan Cheung and myself (2016) reinforces the importance of methodology in determining what is an important effect size. We analyzed all findings from 645 high-quality studies included in all reviews in our Best Evidence Encyclopedia (www.bestevidence.org). We found that the most important factors in effect sizes were sample size and design (randomized vs. matched). Here is the key table.

Effects of Sample Size and Designs on Effect Sizes

  Sample Size
Design Small Large
Matched +0.33 +0.17
Randomized +0.23 +0.12

What this chart shows is that matched studies with small sample sizes (less than 250 students) have much higher effect sizes, on average, than, say, large randomized studies (+0.33 vs. +0.12). These differences say nothing about the impact on children, but are completely due to differences in study design.

If effect sizes are so different due to study design, then we cannot have a single standard to tell us when an effect size is large or small. All we can do is note when an effect size is large compared to similar studies. For example imagine that a study finds an effect size of +0.20. Is that big or small? If it was a matched study with a small sample size, +0.20 would be a rather small impact. If it were a randomized study with a large sample size, it might be considered quite a large impact.

Beyond study methods, a good general principle is to compare like with like. For example, some treatments may have very small effect sizes, but they may be so inexpensive or may affect so many students that a small effect may be important. For example, principal or superintendent training may affect very many students, or benchmark assessments may be so inexpensive that a small effect size may be worthwhile, and may compare favorably with equally inexpensive means of solving the same problem.

My colleagues and I will be developing a formula to enable researchers and readers to easily put in features of a study to produce an “expected effect size” to determine more accurately whether an effect size should be considered large or small.

Not long ago, it would not have mattered much how large effect sizes were considered, but now it does. That’s an indication of the progress we have made in recent years. Big indeed!

This blog was developed with support from the Laura and John Arnold Foundation. The views expressed here do not necessarily reflect those of the Foundation.

New Findings on Tutoring: Four Shockers

blog_04 05 18_SURPRISE_500x353One-to-one and one-to-small group tutoring have long existed as remedial approaches for students who are performing far below expectations. Everyone knows that tutoring works, and nothing in this blog contradicts this. Although different approaches have their champions, the general consensus is that tutoring is very effective, and the problem with widespread use is primarily cost (and for tutoring by teachers, availability of sufficient teachers). If resources were unlimited, one-to-one tutoring would be the first thing most educators would recommend, and they would not be wrong. But resources are never unlimited, and the numbers of students performing far below grade level are overwhelming, so cost-effectiveness is a serious concern. Further, tutoring seems so obviously effective that we may not really understand what makes it work.

In recent reviews, my colleagues and I examined what is known about tutoring. Beyond the simple conclusion that “tutoring works,” we found some big surprises, four “shockers.” Prepare to be amazed! Further, I propose an explanation to account for these unexpected findings.

We have recently released three reviews that include thorough, up-to-date reviews of research on tutoring. One is a review of research on programs for struggling readers in elementary schools by Amanda Inns and colleagues (2018). Another is a review on programs for secondary readers by Ariane Baye and her colleagues (2017). Finally, there is a review on elementary math programs by Marta Pellegrini et al. (2018). All three use essentially identical methods, from the Best Evidence Encyclopedia (www.bestevidence.org). In addition to sections on tutoring strategies, all three also include other, non-tutoring methods directed at the same populations and outcomes.

What we found challenges much of what everyone thought they knew about tutoring.

Shocker #1: In all three reviews, tutoring by paraprofessionals (teaching assistants) was at least as effective as tutoring by teachers. This was found for reading and math, and for one-to-one and one-to-small group tutoring.  For struggling elementary readers, para tutors actually had higher effect sizes than teacher tutors. Effect sizes were +0.53 for paras and +0.36 for teachers in one-to-one tutoring. For one-to-small group, effect sizes were +0.27 for paras, +0.09 for teachers.

Shocker #2: Volunteer tutoring was far less effective than tutoring by either paras or teachers. Some programs using volunteer tutors provided them with structured materials and extensive training and supervision. These found positive impacts, but far less than those for paraprofessional tutors. Volunteers tutoring one-to-one had an effect size of +0.18, paras had an effect size of +0.53. Because of the need for recruiting, training, supervision, and management, and also because the more effective tutoring models provide stipends or other pay, volunteers were not much less expensive than paraprofessionals as tutors.

Shocker #3:  Inexpensive substitutes for tutoring have not worked. Everyone knows that one-to-one tutoring works, so there has long been a quest for approaches that simulate what makes tutoring work. Yet so far, no one, as far as I know, has found a way to turn lead into tutoring gold. Although tutoring in math was about as effective as tutoring in reading, a program that used online math tutors communicating over the Internet from India and Sri Lanka to tutor students in England, for example, had no effect. Technology has long been touted as a means of simulating tutoring, yet even when computer-assisted instruction programs have been effective, their effect sizes have been far below those of the least expensive tutoring models, one-to-small group tutoring by paraprofessionals. In fact, in the Inns et al. (2018) review, no digital reading program was found to be effective with struggling readers in elementary schools.

 Shocker #4: Certain whole-class and whole-school approaches work as well or better for struggling readers than tutoring, on average. In the Inns et al. (2018) review, the average effect size for one-to-one tutoring approaches was +0.31, and for one-to-small group approaches it was +0.14. Yet the mean for whole-class approaches, such as Ladders to Literacy (ES = +0.48), PALS (ES = +0.65), and Cooperative Integrated Reading and Composition (ES = +0.19) averaged +0.33, similar to one-to-one tutoring by teachers (ES = +0.36). The mean effect sizes for comprehensive tiered school approaches, such as Success for All (ES = +0.41) and Enhanced Core Reading Instruction (ES = +0.22) was +0.43, higher than any category of tutoring (note that these models include tutoring as part of an integrated response to implementation approach). Whole-class and whole-school approaches work with many more students than do tutoring models, so these impacts are obtained at a much lower cost per pupil.

Why does tutoring work?

Most researchers and others would say that well-structured tutoring models work primarily because they allow tutors to fully individualize instruction to the needs of students. Yet if this were the only explanation, then other individualized approaches, such as computer-assisted instruction, would have outcomes similar to those of tutoring. Why is this not the case? And why do paraprofessionals produce at least equal outcomes to those produced by teachers as tutors? None of this squares with the idea that the impact of tutoring is entirely due to the tutor’s ability to recognize and respond to students’ unique needs. If that were so, other forms of individualization would be a lot more effective, and teachers would presumably be a lot more effective at diagnosing and responding to students’ problems than would less highly trained paraprofessionals. Further, whole-class and whole-school reading approaches, which are not completely individualized, would have much lower effect sizes than tutoring.

My theory to account for the positive effects of tutoring in light of the four “shockers” is this:

  • Tutoring does not work due to individualization alone. It works due to individualization plus nurturing and attention.

This theory begins with the fundamental and obvious assumption that children, perhaps especially low achievers, are highly motivated by nurturing and attention, perhaps far more than by academic success. They are eager to please adults who relate to them personally.  The tutoring setting, whether one-to-one or one-to-very small group, gives students the undivided attention of a valued adult who can give them personal nurturing and attention to a degree that a teacher with 20-30 students cannot. Struggling readers may be particularly eager to please a valued adult, because they crave recognition for success in a skill that has previously eluded them.

Nurturing and attention may explain the otherwise puzzling equality of outcomes obtained by teachers and paraprofessionals as tutors. Both types of tutors, using structured materials, may be equally able to individualize instruction, and there is no reason to believe that paras will be any less nurturing or attentive. The assumption that teachers would be more effective as tutors depends on the belief that tutoring is complicated and requires the extensive education a teacher receives. This may be true for very unusual learners, but for most struggling students, a paraprofessional may be as capable as a teacher in providing individualization, nurturing, and attention. This is not to suggest that paraprofessionals are as capable as teachers in every way. Teachers have to be good at many things: preparing and delivering lessons, managing and motivating classes, and much more. However, in their roles as tutors, teachers and paraprofessionals may be more similar.

Volunteers certainly can be nurturing and attentive, and can be readily trained in structured programs to individualize instruction. The problem, however, is that studies of volunteer programs report difficulties in getting volunteers to attend every day and to avoid dropping out when they get a paying job. This is may be less of a problem when volunteers receive a stipend; paid volunteers are much more effective than unpaid ones.

The failure of tutoring substitutes, such as individualized technology, is easy to predict if the importance of nurturing and attention is taken into account. Technology may be fun, and may be individualized, but it usually separates students from the personal attention of caring adults.

Whole-Class and Whole-School Approaches.

Perhaps the biggest shocker of all is the finding that for struggling readers, certain non-technology approaches to instruction for whole classes and schools can be as effective as tutoring. Whole-class and whole-school approaches can serve many more students at much lower cost, of course. These classroom approaches mostly use cooperative learning and phonics-focused teaching, or both, and the whole-school models especially Success for All,  combine these approaches with tutoring for students who need it.

The success of certain whole-class programs, of certain tutoring approaches, and of whole-school approaches that combine proven teaching strategies with tutoring for students who need more, argues for response to intervention (RTI), the policy that has been promoted by the federal government since the 1990s. So what’s new? What’s new is that the approach I’m advocating is not just RTI. It’s RTI done right, where each component of  the strategy has strong evidence of effectiveness.

The good news is that we have powerful and cost-effective tools at our disposal that we could be putting to use on a much more systematic scale. Yet we rarely do this, and as a result far too many students continue to struggle with reading, even ending up in special education due to problems schools could have prevented. That is the real shocker. It’s up to our whole profession to use what works, until reading failure becomes a distant memory. There are many problems in education that we don’t know how to solve, but reading failure in elementary school isn’t one of them.

Practical Implications.

Perhaps the most important practical implication of this discussion is a realization that benefits similar or greater than those of one-to-one tutoring by teachers can be obtained in other ways that can be cost-effectively extended to many more students: Using paraprofessional tutors, using one-to-small group tutoring, or using whole-class and whole-school tiered strategies. It is no longer possible to say with a shrug, “of course tutoring works, but we can’t afford it.” The “four shockers” tell us we can do better, without breaking the bank.

 

References

Baye, A., Lake, C., Inns, A., & Slavin, R. (2017). Effective reading programs for secondary students. Manuscript submitted for publication. Also see Baye, A., Lake, C., Inns, A. & Slavin, R. E. (2017, August). Effective Reading Programs for Secondary Students. Baltimore, MD: Johns Hopkins University, Center for Research and Reform in Education.

Inns, A., Lake, C., Pellegrini, M., & Slavin, R. (2018). Effective programs for struggling readers: A best-evidence synthesis. Paper presented at the annual meeting of the Society for Research on Educational Effectiveness, Washington, DC.

Pellegrini, M., Inns, A., & Slavin, R. (2018). Effective programs in elementary mathematics: A best-evidence synthesis. Paper presented at the annual meeting of the Society for Research on Educational Effectiveness, Washington, DC.

This blog was developed with support from the Laura and John Arnold Foundation. The views expressed here do not necessarily reflect those of the Foundation.

Photo by Westsara (Own work) [CC BY-SA 4.0 (https://creativecommons.org/licenses/by-sa/4.0)], via Wikimedia Commons