Content uploaded by Jens Dietrichson
Author content
All content in this area was uploaded by Jens Dietrichson on May 09, 2018
Content may be subject to copyright.
A preview of the PDF is not available
Academic Interventions for Elementary and Middle School Students With Low Socioeconomic Status: A Systematic Review and Meta-Analysis
Abstract and Figures
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.
Figures - uploaded by Jens Dietrichson
Author content
All figure content in this area was uploaded by Jens Dietrichson
Content may be subject to copyright.
... Furthermore, high-quality instructional practices, such as reading, writing and other subject-focused strategies, are often the main target of support programmes (Madden et al., 1993). Relatedly, studies have covered careful tracking of student progress, including feedback and progress monitoring (Dietrichson et al., 2017), support for self-management strategies, such as self-monitoring or self-evaluation (Moses et al., 2023), self-regulating strategy intervention (Andrzejewski et al., 2016) and enhanced metacognitive knowledge components of different learning strategy instruction (Donker et al., 2014). The usage of data at both the school and the classroom levels is decisive in improving achievement for low SES and minority students Demie & Mclean, 2015;Reynolds et al., 2006). ...
... The usage of data at both the school and the classroom levels is decisive in improving achievement for low SES and minority students Demie & Mclean, 2015;Reynolds et al., 2006). The significance of personalised support, especially tutoring (Dietrichson et al., 2017) and mentoring programmes as well as individualised academic plans, have also been stressed (Williams et al., 2019). ...
... enhancing parental involvement, see Coles et al., 2023;Furrer & Skinner, 2003;Williams et al., 2019;Wong et al., 2018;student-teacher relationships, see Demie & Mclean, 2015;Kang et al., 2021;Muijs et al., 2004;Teuscher & Makarova, 2018); others need to be more diversified with regard to their more exclusive support of only one of these domains (e.g. quality of instruction and tutoring are more related to achievement; Dietrichson et al., 2017;Lauer et al., 2006;peer-to-peer relationships are more exclusively related to student engagement; Pino-James et al., 2019). ...
Educational inequalities persist between students of low socioeconomic status and their more affluent peers. At the same time, there is evidence of positive relations between student engagement and achievement. This multiple case study investigates a national project aimed at increasing student engagement and achievement through post‐Covid‐19 support focused on disadvantaged schools in the Czech Republic. School staff perceived poor attendance, low student motivation and discipline problems as the most challenging issues to be addressed through project support measures. Attendance problems are tackled mainly through experiential activities; motivation and discipline problems are usually addressed by personnel positions. We argue that the selected measures aimed predominantly to support student emotional and behavioural engagement; strategies to enhance cognitive engagement and student achievement were sidelined. Paradoxically, student engagement may become a goal in itself rather than being inscribed into learning outcomes. Implications for programme support and school improvement research are suggested.
... It has long been known that tutoring can be highly effective (e.g., Bloom 1984;Cohen et al., 1982;Ritter et al., 2006;Nickow et al., 2024). Reviews comparing the effects of interventions for atrisk students often find the largest effect sizes for intensive, smallgroup instruction by adults (e.g., Baye et al., 2019;Dietrichson et al., 2017;Dietrichson et al., 2020;Dietrichson et al., 2021;Fryer, 2017;Neitzel et al., 2022;Slavin et al., 2011). The bulk of these interventions would fit our definition of tutoring. ...
... However, reviews typically also find substantial heterogeneity of the effect sizes. In the few reviews that have examined the heterogeneity using meta-regressions, few moderators showed strong associations with effect sizes and the unexplained heterogeneity remained substantial (Dietrichson et al., 2017;Dietrichson et al., 2021;Nickow et al., 2024;Ritter et al., 2009;Wanzek et al., 2016). Many moderators that theoretically could explain the heterogeneity have never been examined in a moderator analysis. ...
Objectives
This is the protocol for a Campbell systematic review. The objectives are as follows: The first objective is to find and describe machine and statistical learning (ML) methods designed for moderator meta‐analysis. The second objective is to find and describe applications of such ML methods in moderator meta‐analyses of health, medical, and social science interventions. These two parts of the meta‐review will primarily involve a systematic review and will be conducted according to guidelines specified by the Campbell Collaboration (MECCIR guidelines). The outcomes will be a list of ML methods that are designed for moderator meta‐analysis (first objective), and a description of how (some of) these methods have been applied in the health, medical, and social sciences (second objective). The third objective is to examine how the ML methods identified in the meta‐review can help researchers formulate new hypotheses or select among existing ones, and compare the identified methods to one another and to regular meta‐regression methods for moderator analysis. To compare the performance of different moderator meta‐analysis methods, we will apply the methods to data on tutoring interventions from two systematic reviews of interventions to improve academic achievement for students with or at risk‐of academic difficulties, and to an independent test sample of tutoring studies published after the search period in the two reviews.
... However, ethical concerns regarding the accuracy and interpretability of neural networks must be addressed, especially when applied to subjective wellbeing variables. The risk of misinterpreting key predictors due to the opaque nature of neural networks underscores the necessity for caution in deploying these models in predictive contexts [91,92]. ...
This article investigates the factors that affect the job satisfaction of university teachers for which 400 teachers from 4 institutions (public and private) in Ecuador were stratified, resulting in a total of 1600 data points collected through online forms. The research was of a cross-sectional design and quantitative and used machine learning techniques of classification and prediction to analyze variables such as ethnic identity, field of knowledge, gender, number of children, job burnout, perceived stress, and occupational risk. The results indicate that the best classification model is neural networks with a precision of 0.7304; the most significant variables for predicting the job satisfaction of university teachers are: the number of children they have, scores related to perceived stress, professional risk, and burnout, province of the university at which the university teacher surveyed works, and city where the teacher works. This is in contrast to marital status, which does not contribute to its prediction. These findings highlight the need for inclusive policies and effective strategies to improve teacher well-being in the university academic environment.
... First, the authors searched the same keywords in the database of Google Scholar to cover grey literature [42]. Second, the authors searched through the reference lists of previous important review articles [43]. At the end of this stage, the authors retrieved a total of 14,447 articles for further screening. ...
This current systematic review of research represents an attempt to unveil a descriptive picture of the evolving state of the body of knowledge about the well-being of early childhood education (ECE) teachers over 31 years from 1993 to 2023. In this review, 167 articles selected from SCOPUS are analysed using a descriptive quantitative approach. The analysis shows that quantitative research methods and empirical research are predominant in this field. Significant increases have been identified in qualitative and mixed-method research approaches in recent years, presaging a more balanced knowledge base in the near future. However, there has been little change in the scarcity of other research types. Meanwhile, the fragmented conceptualization of well-being, as well as its corresponding measurement, remains an outstanding issue. Overall, this review lays the groundwork for an understanding of the current trajectory of well-being research, especially with respect to ECE teachers, from a developmental perspective.
... Notably, middle schools serve a higher proportion of students from lower socioeconomic backgrounds or with migration backgrounds. These students tend to exhibit lower performance in standardized national assessments compared to their counterparts in academic secondary schools (Dai et al., 2012;Dietrichson et al., 2017). ...
Scientific creativity involves creating novel links between distant scientific and nonscientific concepts. Such creative linking can be captured with the novel word–sentence–construction (Woseco) task. The Woseco task emphasizes syntactic and context-related connections (e.g., “teacher” and “blackboard” being syntactically and contextually connected in the sentence “The teacher writes on the blackboard.”), which may be relevant for achieving remote associations and problem solving, key aspects of scientific creativity. This article tests the Woseco task as a network-building process, capturing individuals’ ability in linking concepts across contexts. We compare Woseco networks against verbal fluency networks from 169 students enrolled in middle schools and academic secondary schools in Austria. Of these students, 90 participated in a Scientific Creativity in Practice program previously shown to promote scientific creative thinking. For the concepts of “school” and “chemistry,” the Woseco networks showed more prominent features of creativity than verbal fluency networks, that is, higher node clustering (t = 14.88, p < .001), lower network distances separating concepts (t = −9.95, p < .001), and overall lower network modularity (t = −23.93, p < .001). Additionally, significant differences in semantic network structure were observed between the intervention and control groups (p < .022), with the intervention group showing more interconnected networks after creativity training in both their Woseco and fluency networks. In conclusion, the Woseco task represents a promising contribution to creativity research for measuring cognitive processes relevant for scientific creativity.
When beginning readers read aloud, the teacher’s feedback affects their reader identities. Teacher’s feedback may also imprint a strong model of what reading is and what proficient readers do. This systematic review investigates the characteristics of teachers’ feedback on elementary students’ reading and furthers its potential to support students’ agency in learning to read. A total of 52 empirical studies in K–5 settings were identified and analyzed. Findings suggest clear associations between how feedback was presented and what aspects of reading were targeted: typically, either explicit feedback on decoding or implicit feedback on meaning. Further, support for student agency was more strongly associated with implicit feedback practices. Finally, two groups of students—struggling readers and L2 learners—tended to receive feedback that does not promote agency. The review concludes by discussing the potential of feedback practices to support students in becoming proficient and independent readers.
This narrative review provides a fine-grained picture of principal resilience research from 47 journal articles starting from its birth in 2005 to 2024. Following the guidelines of Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA), this systematic review clarifies the construct of principal resilience and identifies the drivers and outcomes of principal resilience. As a result, a conceptual framework of principal resilience demonstrating the conceptual and empirical nexus among drivers, mechanisms, and outcomes which may serve as the spotlight for future directions in the perspectives of theory, methodology, and practice is presented. However, fragmentation of construct needs further investigation and evidence is still largely insufficient to declare it a mature scientific field. Promoting principal resilience is not just a buzz direction, but a solid path towards achieving individual principals’ growth and quality education.
The aim of this Campbell systematic review is to assess the effectiveness of volunteer tutoring programs for improving the academic skills of student enrolled in Kindergarten through to 8th Grade (K‐8) in the USA, and to further investigate for whom and under what conditions tutoring can be effective.
Only randomized field trials (in which a treatment was compared to a control group that did not receive the treatment) published from January 1985 to August 2005 were included in our review. The results of the review were based on the data from 1,676 study participants in 28 study cohorts in 21 research articles or reports.
The analysis of these studies – most of which included relatively small samples – showed that volunteer tutoring programs can positively influence language and reading outcomes for students. This review does not suggest that there are any particular volunteer tutoring models that should be recommended for immediate adoption for schools and districts across the country. Rather, we can conclude from the analysis that these programs can positively influence important reading and language sub‐skills for young students.
The results are substantial – approximately one‐third standard deviation. In the end, the results of this analysis should serve as one important piece of evidence used by policymakers and educators who are deciding whether to employ volunteer tutoring as a strategy to improve academic skills for young students.
Abstract
Background
Volunteer tutoring programs are intended to improve student performance, provide mentorship, and improve student self‐esteem, as well as behavior. Despite the best of intention and effort, schools are not certain which volunteer tutoring programs are most effective. Therefore, we contend that a rigorous analysis of the extant literature regarding volunteer tutoring programs can provide schools with information about the most effective types of tutoring programs.
Objectives
To assess the effectiveness of volunteer tutoring programs for improving the academic skills of student enrolled in grades K‐8 in the USA, and to further investigate for whom and under what conditions tutoring can be effective.
Search Strategy
A range of electronic social science databases were searched including Academic Search Premier; Primary Search; Professional Development Collection; Middle Search Plus; Psychology and Behavioral Sciences Collection; PsycINFO; Sociological Collection, ERIC (Education Resources Information Center), and Proquest Digital Dissertations.
Selection Criteria
Only randomized field trials (in which a treatment was compared to a control group that did not receive the treatment) published from January 1985 to August 2005 were included in our review. We only included studies that included academic impacts, although other impacts could be part of the study (e.g. behavioral, emotional). We also only included programs that were used for students in grades K – 8, and programs where adult, non‐professional (volunteer) tutors were used.
Data Collection & Analysis
Details on the methods and procedures (i.e., design, analysis, outcome measures), the intervention (i.e., duration, setting), and the subject samples (i.e., age, gender, ethnicity) were coded for each study to allow for analysis of outcomes for different types of volunteer tutoring programs and for different study characteristics. After we identified all outcomes measured in the included studies, we selected the appropriate effect size metric for the meta‐analysis. We used Hedges’ unbiased estimate g of the standardized mean difference effect size statistic (the difference between the treatment and control group means on an outcome variable divided by their pooled standard deviations) for each outcome measure. When means and standard deviations were not reported, we attempted to estimate the effect sizes using the procedures recommended by Wilson and Lipsey (2001). When studies had multiple measures of an outcome, we computed a pooled mean of effect size.
Main Results
The results of the review were based on the data from 1,676 study participants in 28 study cohorts in 21 research articles or reports. The analysis of these studies – most of which included relatively small samples – showed that volunteer tutoring programs can positively influence language and reading outcomes for students. We began by examining the overall effects of volunteer tutoring on student reading outcome measures. Twenty‐five studies assessed reading measures of one type or another. The average effect of volunteer tutoring programs on reading outcomes for elementary students is 0.23. After removing one outlier study which disproportionately influenced by the overall result, we found an average effect size of 0.30. We also found several significant results in the meta‐analyses of specific academic domains. The outcomes where volunteer tutoring programs made a significant difference were Reading Global (effect size = 0.26), Letters and Words (effect size = 0.41), Oral Fluency (effect size = 0.30), and Writing (effect size = 0.45). We found positive, but not significant, effects of volunteer tutoring on Reading – Comprehension and Mathematics.
When we analyzed the reading outcomes separately by study characteristics, we found no significant difference in effect size by tutor type, grade level, or program focus. Highly structured tutoring programs had a significantly greater effect on global reading outcomes than programs with low structure, but not on the other outcome types. The difference in effect sizes between studies published in journals and non‐published studies was not statistically significant. Other tests of publication bias also suggested the included studies were an unbiased sample.
Reviewers’ Conclusions
This review does not suggest that there are any particular volunteer tutoring models that should be recommended for immediate adoption for schools and districts across the country. Rather, we can conclude from the analysis that these programs can positively influence important reading and language sub‐skills for young students. The results are substantial – approximately one‐third standard deviation. In the end, the results of this analysis should serve as one important piece of evidence used by policymakers and educators who are deciding whether to employ volunteer tutoring as a strategy to improve academic skills for young students. As educators across the country work to meet adequate yearly progress goals in state accountability systems, and as they seek affordable ways to offer additional services to students at risk of not meeting annual academic goals, it would be worthwhile to consider structured, reading‐focused volunteer tutoring programs as strategies to improve reading and language skills.
This meta-analysis reviews experimental and quasiexperimental studies in which upper-elementary, intermediate, and secondary students with learning disabilities learned from graphic organizers. Following an exhaustive search for studies meeting specified design criteria, 55 standardized mean effect sizes were extracted from 16 articles involving 808 participants. Students at levels ranging from grade 4 to grade 12 used graphic organizers to learn in core-content classes (English/reading, science, social studies, mathematics). Posttests measured near and far transfer. Across several conditions, settings, and features, the use of graphic organizers was associated with increases in vocabulary knowledge, comprehension, and inferential knowledge. Mean effect sizes varied from moderate to large based on type of measure, type of graphic organizer, and subject area. Conclusions, implications for future research, and practical recommendations are presented.
This Campbell systematic review sought to answer the following questions with the available high quality experimental studies of programs that combined academic programming with other activities such as youth development or recreation: To what extent and in what ways does access to after‐school programs impact student context (i.e., student location, supervision, and safety), participation in enriching activities, behaviors, social and emotional development, and academic outcomes for youth?
Do the effects of after‐school programs vary among subgroups of youth defined by their baseline characteristics?
Among the program models and settings evaluated, do some seem more beneficial to youth than others? What are the distinguishing characteristics of those more and less successful programs? This review only included well‐implemented experimental design studies.
An extensive search of the literature uncovered only five studies that met the inclusion criteria for this review. The five evaluated programs were fairly homogenous along many dimensions, including their target populations and settings–primarily elementary youth living in lower‐ income, urban settings. Notably, looking across the 97 impacts measured by the five studies included in this review reveals primarily null findings–84 percent showed no significant differences between the program and control youth. Also, not one of these studies reported impacts for parents. In this era of welfare reform, it might be important to understand how this type of intervention targeting low‐income youth may impact parents' job attendance and retention or parental levels of stress while balancing the demands of work and child care. Such parental outcomes could arguably mediate student social and emotional, behavioral, and academic outcomes.
The effectiveness of bilingual programs for promoting academic achievement of language-minority in the United States has been examined in six meta-analyses. The present meta-analytic study investigates this topic for the first time in the European context. Thorough literature searches uncovered 101 European studies, with only seven meeting the inclusion criteria. Two studies were excluded from further analyses. Results from the random-effects model of the five remaining studies indicate a small positive effect (g = 0.23; 95% CI [0.10, 0.36]) for bilingual over submersion programs on reading of language-minority children. Thus, this meta-analysis supports bilingual education—that is, including the home language of language-minority children—in school instruction. However, the generalizability of the results is limited by the small number of studies on this topic. More published studies on bilingual education in Europe are needed as well as closer attention to the size of the effects.
We present the results of three large-scale randomized controlled trials (RCTs) carried out in Chicago, testing interventions to reduce crime and dropout by changing the decision-making of economically disadvantaged youth. We study a program called Becoming a Man (BAM), developed by the non-profit Youth Guidance, in two RCTs implemented in 2009–10 and 2013– 15. In the two studies participation in the program reduced total arrests during the intervention period by 28–35%, reduced violent-crime arrests by 45–50%, improved school engagement, and in the first study where we have follow-up data, increased graduation rates by 12–19%. The third RCT tested a program with partially overlapping components carried out in the Cook County Juvenile Temporary Detention Center (JTDC), which reduced readmission rates to the facility by 21%. These large behavioral responses combined with modest program costs imply benefit-cost ratios for these interventions from 5-to-1 up to 30-to-1 or more. Our data on mechanisms are not ideal, but we find no positive evidence that these effects are due to changes in emotional intelligence or social skills, self-control or “grit,” or a generic mentoring effect. We find suggestive support for the hypothesis that the programs work by helping youth slow down and reflect on whether their automatic thoughts and behaviors are well suited to the situation they are in, or whether the situation could be construed differently.
The heterogeneity statistic I(2), interpreted as the percentage of variability due to heterogeneity between studies rather than sampling error, depends on precision, that is, the size of the studies included.
METHODS: Based on a real meta-analysis, we simulate artificially 'inflating' the sample size under the random effects model. For a given inflation factor M = 1, 2, 3,... and for each trial i, we create a M-inflated trial by drawing a treatment effect estimate from the random effects model, using s(i)(2)/M as within-trial sampling variance.
RESULTS: As precision increases, while estimates of the heterogeneity variance tau(2) remain unchanged on average, estimates of I(2) increase rapidly to nearly 100%. A similar phenomenon is apparent in a sample of 157 meta-analyses.
CONCLUSION: When deciding whether or not to pool treatment estimates in a meta-analysis, the yard-stick should be the clinical relevance of any heterogeneity present. tau(2), rather than I(2), is the appropriate measure for this purpose.
This chapter discusses what researchers can do when studies are missing the information needed for meta-analysis. Despite careful evaluation of coding decisions, researchers will find that studies in a research synthesis invariably differ in the types and quality of the information reported. Here I examine the types of missing data that occur in a research synthesis, and discuss strategies synthesists can use when faced with missing data. Problems caused by missing data can never be entirely alleviated. As such, the first strategy for addressing missing data should be to contact the study authors. Doing so remains a viable strategy in some cases. When it fails, the next strategy is to use statistical missing data methods to check the sensitivity of results to different assumptions about the distribution of the hypothetically complete data and the reasons for the missing data. We can think of these methods as a trade-off - if observations are missing in the data, then the cost is the need to make assumptions about the data and the mechanism that causes the missing data, assumptions that are difficult to verify in practice. Synthesists can feel more confident about results that are robust to different assumptions about the missing data. On the other hand, results that differ depending on the missing data assumptions may indicate that the sample of studies do not provide enough evidence for robust inference. Joseph Schafer and John Graham pointed out that the main goal of statistical methods for missing data is not to recover or estimate the missing values but to make valid inferences about a population of interest (2002). They thus noted that the missing data method is embedded in the particular model or testing procedure the analyst is using. My goal in this chapter is to introduce methods for estimating effect size models when either effect sizes or predictors in the model are missing from primary studies.