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Structured abstracts

Describe your entire study


A structured abstract puts everything together and is one of the quickest ways to convey your argument, study and results. 



Example from Mosteller (2004):

Structured abstract

Background: Class size reduction continues to attract attention as a school reform measure. Prior research on the effects of class size has been inconclusive, leading to ongoing controversy and debate about the magnitude, if any, of a “class-size effect” on learning outcomes for children.

Purpose: To assess the effects of a statewide experiment where class size was substantially reduced in kindergarten and first-grade classes.

Setting: 76 public elementary schools drawn from inner-city, urban, suburban, and rural locations in Tennessee. A total of 328 kindergarten classes and 347 first-grade classes participated in the study.

Subjects: 6,570 students enrolled in kindergarten in the 1985–1986 school year.

Intervention: Students were randomly assigned by project staff to one of three class types: small (13–17 pupils), regular (22–25 pupils), or regular with a teacher aide (22–25 pupils). Students assigned to small classes stayed in small classes for kindergarten and first grade.

Research Design: Randomized-controlled field trial.

Data Collection and Analysis: The Stanford Achievement Tests in reading and mathematics were administered in the spring of each school year, and a set of Tennessee curriculum-referenced tests were administered at the beginning of first grade. Means on each outcome measure were calculated for each class, then separately for White and minority students in each classroom. Two analyses were conducted using multivariate analysis of variance: a cross-sectional analysis of the entire first-grade sample and a longitudinal analysis of a subset of pupils (n = 2291) who were in the study for both kindergarten and first grade and had complete SAT achievement test data.

Findings: Significant benefits of class size reduction were seen across all academic measures. The cross-sectional analysis of first graders yielded an overall difference of about one fourth of a standard deviation among students in small classes vs. regular classes. Minority students benefited in particular, averaging a difference of a third of a standard deviation over their regular class counterparts on five of the six academic measures. In the longitudinal analysis, students in small classes had a highly statistically significant advantage in reading and mathematics over regular classes in both kindergarten and first grade.

Conclusions: This study demonstrates that small classes have an advantage over larger classes in reading and mathematics in the early primary grades. The analysis also strongly suggests that small classes especially benefit the academic performance of minority students. 


Some common types of studies

  • Exploratory study.  "To better understand <situation>,  <population> in <setting> were <observed> using an <observational-study> study.  Data from the experiment were analyzed <analysis-type> to show that <descriptive characteristics / explanation>.  This new model suggests that <conclusion/recommendation>."  

  • Causal mechanism.  "To better understand <relationship-between-constructs>,  <population> in <setting> were <intervention> using a <experimental-design> experiment.  Data from the experiment were analyzed <analysis-type> to show that <results / relationship-between-variables>.  This new model suggests that <conclusion/recommendation>."  The causal study can be used to investigate what factors impact learning (e.g., to provide an explanation of some phenomenon) as is the case in many exploratory qualitative studies.  It can also be used as a variant on the design study in which the researcher manipulates some intervention in order to see the effect as in an educational psychology experiment.  Design-based research studies can often be described as a iterative sequence of causal studies.

  • Radical design.  To better understand how we might <achieve purpose>,  <population> in <setting> were <intervention> using a <study-design>.  In comparison with <existing normal solutions> it offers <advantages>, which have been demonstrated in preliminary tests, but it leaves a number of side-effects to be addressed including <list of side-effects>."  

  • Enhanced design.  To better understand how we might <achieve purpose>,  <population> in <setting> were <intervention> using a <study-design>. In comparison with existing solutions, it offers enhanced levels of <property>, according to analyses based on <model-type>.   These improvements have been confirmed / demonstrated in tests of a working <artifact-type> based on the design.

  • Enhanced model.  "Existing <model-type> models are deficient in dealing with <properties> of <solution strategy>.  An enhanced <model-type> is described, capable of providing more accurate analyses / predictions of <properties> in <solution strategy> designs.  The model has been tested by comparing analyses / predictions with empirically measured values of <properties>" In this study, the researcher is creating a modeling technique that allows researchers to more quickly test designs by modeling (rather than observing) their results. Enhanced modeling techniques are generated by applying existing techniques to designs, and making comparisons with the results of empirical tests on working prototypes or products; areas of discrepancy between predicted and actual results are noted.  The researcher then develops a new model that offers a more accurate prediction, and confirms its accuracy by means of fresh empirical tests.

  • Enhanced Tool. "The effectiveness of <model-type> / <solution strategy> in supporting the design of <artifact-type> has been demonstrated. An enhanced tool / method is described for the design of <artifact-type> based on <model-type> / <solution strategy>.  Examples are provided confirming the effectiveness of its support for <model-type> / <solution strategy> in design." In this kind of study, the researcher is proposing some sort of tool that will assist in modeling.  Enhanced tools and methods arise from observations that modeling techniques or solutions need supporting tools or methods in order to be applied efficiently and reliably.  A tool or method is devised, and is applied in a design context so as to confirm that it provides effective support for the modeling technique or for the use of the solution.