Psychometrics is a field of study concerned with the theory and technique of psychological measurement. As defined by the US National Council on Measurement in Education (NCME), psychometrics refers to psychological measurement. Generally, it refers to the field in psychology and education that is devoted to testing, measurement, assessment, and related activities.
The SAT is a standardized test widely used for college admissions in the United States. Since it was debuted by the College Board in 1926, its name and scoring have changed several times; originally called the Scholastic Aptitude Test, it was later called the Scholastic Assessment Test, then the SAT I: Reasoning Test, then the SAT Reasoning Test, then simply the SAT.
A natural experiment is an empirical study in which individuals are exposed to the experimental and control conditions that are determined by nature or by other factors outside the control of the investigators. The process governing the exposures arguably resembles random assignment. Thus, natural experiments are observational studies and are not controlled in the traditional sense of a randomized experiment. Natural experiments are most useful when there has been a clearly defined exposure involving a well defined subpopulation such that changes in outcomes may be plausibly attributed to the exposure. In this sense, the difference between a natural experiment and a non-experimental observational study is that the former includes a comparison of conditions that pave the way for causal inference, but the latter does not.
A standardized test is a test that is administered and scored in a consistent, or "standard", manner. Standardized tests are designed in such a way that the questions, conditions for administering, scoring procedures, and interpretations are consistent and are administered and scored in a predetermined, standard manner.
Educational assessment or educational evaluation is the systematic process of documenting and using empirical data on the knowledge, skill, attitudes, and beliefs to refine programs and improve student learning. Assessment data can be obtained from directly examining student work to assess the achievement of learning outcomes or can be based on data from which one can make inferences about learning. Assessment is often used interchangeably with test, but not limited to tests. Assessment can focus on the individual learner, the learning community, a course, an academic program, the institution, or the educational system as a whole. The word 'assessment' came into use in an educational context after the Second World War.
Linear discriminant analysis (LDA), normal discriminant analysis (NDA), or discriminant function analysis is a generalization of Fisher's linear discriminant, a method used in statistics, pattern recognition, and machine learning to find a linear combination of features that characterizes or separates two or more classes of objects or events. The resulting combination may be used as a linear classifier, or, more commonly, for dimensionality reduction before later classification.
In statistics, econometrics, epidemiology and related disciplines, the method of instrumental variables (IV) is used to estimate causal relationships when controlled experiments are not feasible or when a treatment is not successfully delivered to every unit in a randomized experiment. Intuitively, IVs are used when an explanatory variable of interest is correlated with the error term, in which case ordinary least squares and ANOVA give biased results. A valid instrument induces changes in the explanatory variable but has no independent effect on the dependent variable, allowing a researcher to uncover the causal effect of the explanatory variable on the dependent variable.
Structural equation modeling (SEM) includes a diverse set of mathematical models, computer algorithms, and statistical methods that fit networks of constructs to data. SEM includes confirmatory factor analysis, confirmatory composite analysis, path analysis, partial least squares path modeling, and latent growth modeling. The concept should not be confused with the related concept of structural models in econometrics, nor with structural models in economics. Structural equation models are often used to assess unobservable 'latent' constructs. They often invoke a measurement model that defines latent variables using one or more observed variables, and a structural model that imputes relationships between latent variables. The links between constructs of a structural equation model may be estimated with independent regression equations or through more involved approaches such as those employed in LISREL.
In the field of psychology, the Dunning–Kruger effect is a cognitive bias in which people with low ability at a task overestimate their ability. It is related to the cognitive bias of illusory superiority and comes from the inability of people to recognize their lack of ability. Without the self-awareness of metacognition, people cannot objectively evaluate their competence or incompetence.
Multilevel models are statistical models of parameters that vary at more than one level. An example could be a model of student performance that contains measures for individual students as well as measures for classrooms within which the students are grouped. These models can be seen as generalizations of linear models, although they can also extend to non-linear models. These models became much more popular after sufficient computing power and software became available.
Formative assessment, formative evaluation, formative feedback, or assessment for learning, including diagnostic testing, is a range of formal and informal assessment procedures conducted by teachers during the learning process in order to modify teaching and learning activities to improve student attainment. The goal of a formative assessment is to monitor student learning to provide ongoing feedback that can help students identify their strengths and weaknesses and target areas that need work. It also helps faculty recognize where students are struggling and address problems immediately. It typically involves qualitative feedback for both student and teacher that focuses on the details of content and performance. It is commonly contrasted with summative assessment, which seeks to monitor educational outcomes, often for purposes of external accountability.
Thomas Joseph Kane is a U.S.-American education economist who currently holds the position of Walter H. Gale Professor of Education and Economics at the Harvard Graduate School of Education. He has performed research on education policy, labour economics and econometrics. During Bill Clinton's first term as U.S. President, Kane served on the Council of Economic Advisers.
Eric Alan Hanushek is an economist who has written prolifically on public policy with a special emphasis on the economics of education. Since 2000 he has been a Paul and Jean Hanna Senior Fellow at the Hoover Institution, an American public policy think tank located at Stanford University in California.
Joshua David Angrist is an Israeli American economist and Ford Professor of Economics at the Massachusetts Institute of Technology. He ranks among the world's top economists in labour economics, urban economics, and the economics of education, and is known for his use of quasi-experimental research designs to study the effects of public policies and changes in economic or social circumstances. He is a co-founder and co-director of the MIT's School Effectiveness & Inequality Initiative, which studies the relationship between human capital and income inequality in the U.S.
Matching is a statistical technique which is used to evaluate the effect of a treatment by comparing the treated and the non-treated units in an observational study or quasi-experiment. The goal of matching is, for every treated unit, to find one non-treated unit(s) with similar observable characteristics against whom the effect of the treatment can be assessed. By matching treated units to similar non-treated units, matching enables a comparison of outcomes among treated and non-treated units to estimate the effect of the treatment reducing bias due to confounding. Propensity score matching, an early matching technique, was developed as part of the Rubin causal model, but has been shown to increase model dependence, bias, inefficiency, and power and is no longer recommended compared to other matching methods.
Class size refers to the number of students a teacher faces during a given period of instruction.
As an educational reform goal, class size reduction (CSR) aims to increase the number of individualized student-teacher interactions intended to improve student learning. A reform long holding theoretical attraction to many constituencies, some have claimed CSR as the most studied educational reform of the last century. Until recently, interpretations of these studies have often been contentious. Some educational groups like the American Federation of Teachers and National Education Association are in favor of reducing class sizes. Others argue that class size reduction has little effect on student achievement. Many are concerned about the costs of reducing class sizes.
Value-added modeling is a method of teacher evaluation that measures the teacher's contribution in a given year by comparing the current test scores of their students to the scores of those same students in previous school years, as well as to the scores of other students in the same grade. In this manner, value-added modeling seeks to isolate the contribution, or value added, that each teacher provides in a given year, which can be compared to the performance measures of other teachers. VAMs are considered to be fairer than simply comparing student achievement scores or gain scores without considering potentially confounding context variables like past performance or income. It is also possible to use this approach to estimate the value added by the school principal or the school as a whole.
Victor Chaim Lavy is an Israeli economist and professor at the University of Warwick and the Hebrew University of Jerusalem. His research interests include labour economics, the economics of education, and development economics. Lavy belongs to the most prominent education economists in the world.
Susanna Loeb is an American education economist and the Barnett Family Professor of Education at the Stanford Graduate School of Education, where she also served as founding director of the Center for Education Policy Analysis (CEPA). Moreover, she directs Policy Analysis for California Education (PACE). Her research interests include the economics of education and the relationship between schools and educational policies, in particular school finance and teacher labor markets.
