A thirty-year look at studies on computer-assisted maths

During the past 30 years, thousands of articles have been written about technology’s effects on pupil achievement. In order to quantify technology’s effects on maths achievement, Jamaal Young at the University of Texas conducted a meta-analysis of all of the meta-analyses on the topic during the last three decades. His second-order meta-analysis was comprised of 19 meta-analyses representing 663 primary studies, more than 141,000 pupils and 1,263 effect sizes. Each meta-analysis that was included had to address the use of technology as a supplement to instruction, use pupil maths achievement as an outcome measure, report an effect size or enough data to calculate one, have been published after 1985 and be accessible to the public.

The author found that all technology enhancements positively affected pupil achievement, regardless of the technology’s purpose. However, technology that helped pupils perform computational functions had the greatest effects on pupil achievement, while combinations of enhancements demonstrated the least effects on pupil achievement. The author found that study quality and the type of technology used in the classroom were the main influencers on effect sizes. The highest-quality studies had the lowest effect sizes, which he attributes to their more rigorous analysis procedures. The high-quality reviews gave an overall effect size for the use of technology of +0.16 (compared with +0.38 for low- and +0.46 for medium-quality reviews).

Source: Technology-enhanced mathematics instruction: A second-order meta-analysis of 30 years of research (November 2017), Educational Research Review, Volume 22

Decades of evidence supports early childhood education

A recent meta-analysis of almost 60 years’ worth of high-quality early childhood education (ECE) studies in the US found that participating in ECE programmes significantly reduced special education placement and grade retention (pupils having to repeat a year), and lead to increased graduation rates from secondary school.

Dana Charles McCoy and colleagues examined data from studies spanning 1960-2016. All had to meet strict inclusion criteria and address ECE’s effects on special education placement, grade retention, or dropout rates, yielding 22 studies. Seven were randomised controlled studies, four were quasi-experimental, and eleven used non-randomised assignment and compared groups who were equivalent at baseline.

Results showed statistically significant effects of ECE. Compared to pupils who did not attend ECE, participants were 8.1% less likely to be placed in special education, 8.3% less likely to be held back a year and 11.4% more likely to graduate from secondary school.

Source: Impacts of early childhood education on medium- and long-term educational outcomes (November 2017), Educational Researcher Volume 46, issue 8

Programme components and disadvantaged pupils

Research shows that pupils from low socioeconomic backgrounds are less likely to attend pre-school or to have a home environment incorporating literacy and language activities than their less disadvantaged peers. As a result, children from low socioeconomic backgrounds are less likely to enter school with the social and academic skills needed to set them up for success. Jans Deitrichson and colleagues at the Danish National Centre for Social Research recently performed a meta-analysis aimed at determining what components within academic interventions are the most effective at improving the achievement of primary school students from low-socioeconomic backgrounds.

A total of 101 studies performed between 2000–2014 were included in the meta-analysis. Seventy-six percent were randomised controlled trials and the rest were quasi-experimental studies. Studies had to target pupils from low socioeconomic backgrounds, utilise standardised test results in reading and maths as the outcome measures, and take place in OECD or EU countries, although most were in the US. They also had to contain information that allowed the researchers to calculate effect sizes.

The authors sorted each study’s academic intervention into “component categories” (the methods used). Examples include coaching/ mentoring of pupils, cooperative learning, incentives, small-group tutoring, or a combination of these or other methods. Analysis demonstrated that tutoring, feedback and progress monitoring, and cooperative learning were the components with the largest effect sizes. The authors stated that although the average effect sizes for these components were not large enough to close the achievement gap between high- and low-socioeconomic pupils, they certainly reduced it. They suggest that cost-effectiveness studies should be performed on these programmes to give policymakers and educators a fuller picture of programme benefits.

Source: Academic interventions for elementary and middle school students with low socioeconomic status: A systematic review and meta-analysis (January 2017), Review of Educational Research, Vol 87, Issue 2

Rethinking the use of tests

Olusola O Adesope and colleagues conducted a meta-analysis to summarise the learning benefits of taking a practice test versus other forms of non-testing learning conditions, such as re-studying, practice, filler activities, or no presentation of the material.

Analysis of 272 independent effect sizes from 188 separate experiments demonstrated that the use of practice tests is associated with a moderate, statistically significant weighted mean effect size compared to re-studying (+0.51) and a much larger weighted mean effect size (+0.93) when compared to filler or no activities.

In addition, the format, number and frequency of practice tests make a difference for the learning benefits on a final test. Practice tests with a multiple-choice option have a larger weighted mean effect size (+0.70) than short-answer tests (+0.48). A single practice test prior to the final test is more effective than when pupils take several practice tests. However, the timing should be carefully considered. A gap of less than a day between the practice and final tests showed a smaller weighted effect size than when there is a gap of one to six days (+0.56 and +0.82, respectively).

Source: Rethinking the use of tests: A meta-analysis of practice testing (February 2017), Review of Educational Research DOI: 10.3102/0034654316689306

A century of research on ability grouping and acceleration

Researchers Saiying Steenbergen-Hu and colleagues recently analysed the results of almost 100 years of research on the effects of ability grouping (which places pupils of similar skills and abilities in the same classes) and acceleration (where pupils are given material and assignments that are usually reserved for older year groups) on pupils’ academic achievement. After screening thousands of studies, their secondary meta-analysis, recently published in Review of Educational Research, synthesised the results of thirteen earlier meta-analyses on ability grouping and six on acceleration that met inclusion criteria for the final review.

They divided ability grouping into four types: (1) between-class ability grouping, where pupils in the same year are divided into low-, medium-, or high-level classes; (2) within-class ability grouping, where pupils within a classroom are taught in groups based on their levels; (3) cross-year subject grouping, where pupils in different year groups are combined into the same class depending on their prior achievement; and (4) grouping for pupils considered gifted.

Results showed academic benefits of within-class grouping, cross-year grouping by subject, and grouping for the gifted, but no benefit of between-class grouping. Results were consistent regardless of whether pupils were high-, medium-, or low-achievers. Analyses of acceleration groups for pupils labelled as gifted showed that these pupils performed the same as older non-gifted pupils, and that being in accelerated classes had positive effects on these pupils’ grades.

Source: What one hundred years of research says about the effects of ability grouping and acceleration on K–12 students’ academic achievement: Findings of two second-order meta-analyses (December 2016), Review of Educational Research, Vol. 86, No. 4

Creativity is modestly correlated with achievement

A new meta-analysis published in the Journal of Educational Psychology examines the link between creativity and academic achievement.

Aleksandra Gajda and colleagues initially selected 148 studies, but narrowed these down to include only those studies that used a quantitative measure of the link between creativity and academic achievement; included more objective measures of creativity (such as the Torrance Test of Creative Thinking) or self-report scales that showed sufficient reliability; and used grade point average (GPA), external exams, or researcher-developed tests to measure academic achievement.

The results showed a positive (albeit modest) relationship between creativity and academic achievement. The relationship was significantly stronger when creativity was measured with tests, particularly verbal tests, rather than when it was measured using self-report scales. The relationship was also significantly stronger when academic achievement was measured using standardised tests, rather than using GPA. The relationship between creativity and academic achievement was stable, no matter when, or where, the study had been carried out.

Source: Creativity and Academic Achievement: A Meta-Analysis (2016), Journal of Educational Psychology