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Leadership in action : keys to ensure school success
\"This book outlines how administrators in our school system can move from managerial efforts to leadership functions\"-- Provided by publisher.
Book
A Century of Grading Research: Meaning and Value in the Most Common Educational Measure
Grading refers to the symbols assigned to individual pieces of student work or to composite measures of student performance on report cards. This review of over 100 years of research on grading considers five types of studies: (a) early studies of the reliability of grades, (b) quantitative studies of the composition of K-12 report card grades, (c) survey and interview studies of teachers' perceptions of grades, (d) studies of standards-based grading, and (e) grading in higher education. Early 20th-century studies generally condemned teachers' grades as unreliable. More recent studies of the relationships of grades to tested achievement and survey studies of teachers' grading practices and beliefs suggest that grades assess a multidimensional construct containing both cognitive and noncognitive factors reflecting what teachers value in student work. Implications for future research and for grading practices are discussed.
Journal Article
Disrupting education?
We study the impact of a personalized technology-aided after-school instruction program in middle-school grades in urban India using a lottery that provided winners with free access to the program. Lottery winners scored 0.37 σ higher in math and 0.23 σ higher in Hindi over just a 4.5-month period. IV estimates suggest that attending the program for 90 days would increase math and Hindi test scores by 0.6 σ and 0.39 σ respectively. We find similar absolute test score gains for all students, but much greater relative gains for academically-weaker students. Our results suggest that well-designed, technology-aided instruction programs can sharply improve productivity in delivering education.
Journal Article
Achievement Motivation and Academic Dishonesty
Academic dishonesty is a rampant and troubling phenomenon in the educational sector. Although demographic factors have been linked with students’ academic dishonesty in the literature, many of these aspects are difficult to change. However, students’ motivation, a known malleable factor, may allow for opportunities to shape students’ beliefs, goals, and values, which can, in turn, mitigate academic dishonesty. In light of the growing literature on this topic, a research synthesis is needed to clarify discrepant findings and identify salient motivation factors associated with academic dishonesty. Thus, we examined relations between academic dishonesty and motivation as informed by achievement motivation frameworks. From 79 studies, meta-analytic results indicated that academic dishonesty was negatively associated with classroom mastery goal structure, individual mastery approach goals, intrinsic motivation, self-efficacy, utility value, and internal locus of control. Academic dishonesty was positively linked with amotivation and extrinsic goal orientation. Students’ age was a significant moderator for the relation between intrinsic motivation and academic dishonesty. Implications from meta-analytic findings are drawn with regard to theory and practice.
Journal Article
Experimental Evidence on Teachers’ Racial Bias in Student Evaluation: The Role of Grading Scales
A vast research literature documents racial bias in teachers’ evaluations of students. Theory suggests bias may be larger on grading scales with vague or overly general criteria versus scales with clearly specified criteria, raising the possibility that well-designed grading policies may mitigate bias. This study offers relevant evidence through a randomized Web-based experiment with 1,549 teachers. On a vague grade-level evaluation scale, teachers rated a student writing sample lower when it was randomly signaled to have a Black author, versus a White author. However, there was no evidence of racial bias when teachers used a rubric with more clearly defined evaluation criteria. Contrary to expectation, I found no evidence that the magnitude of grading bias depends on teachers’ implicit or explicit racial attitudes.
Journal Article
What grades and achievement tests measure
Intelligence quotient (IQ), grades, and scores on achievement tests are widely used as measures of cognition, but the correlations among them are far from perfect. This paper uses a variety of datasets to show that personality and IQ predict grades and scores on achievement tests. Personality is relatively more important in predicting grades than scores on achievement tests. IQ is relatively more important in predicting scores on achievement tests. Personality is generally more predictive than IQ on a variety of important life outcomes. Both grades and achievement tests are substantially better predictors of important life outcomes than IQ. The reason is that both capture personality traits that have independent predictive power beyond that of IQ.
Journal Article
Directional Ordering of Self-Concept, School Grades, and Standardized Tests Over Five Years: New Tripartite Models Juxtaposing Within- and Between-Person Perspectives
Much research shows academic self-concept and achievement are reciprocally related over time, based on traditional longitudinal data cross-lag-panel models (CLPM) supporting a reciprocal effects model (REM). However, recent research has challenged CLPM's appropriateness, arguing that CLPMs with random intercepts (RI-CLPMs) provide a more robust (within-person) perspective and better control for unmeasured covariates. However, there is much confusion in educational-psychology research concerning appropriate research questions and interpretations of RI-CLPMs and CLPMs. To clarify this confusion, we juxtapose CLPMs and RI-CLPMs relating math self-concept (MSCs), school grades, and achievement tests over the five years of compulsory secondary schooling (N = 3,425). We extend basic models to evaluate: directional ordering among three rather than only two constructs; longitudinal invariance over time (multiple school years) and multiple groups (school tracks); lag-2 paths between non-adjacent waves; and covariates (gender, primary-school math and verbal achievement). Across all basic and extended RI-CLPMs and CLPMs, there was consistent support for the REM bidirectional-ordering hypothesis that self-concept and achievement are each a cause and an effect of the other. Consistent with the logic of these models, extensions of the basic models had more effect on CLPMs, but the direction and statistical significance of cross-lagged paths were largely unaffected for both RI-CLPMs and CLPMs. This substantive-methodological synergy has important implications for theory, methodology, and policy/practice; we support the importance of MSC as a predictor of subsequent achievement and demonstrate a more robust methodological framework for evaluating longitudinal-panel models.
Journal Article
Why Good Teaching Evaluations May Reward Bad Teaching: On Grade Inflation and Other Unintended Consequences of Student Evaluations
In this article, I address the paradox that university grade point averages have increased for decades, whereas the time students invest in their studies has decreased. I argue that one major contributor to this paradox is grading leniency, encouraged by the practice of university administrators to base important personnel decisions on student evaluations of teaching. Grading leniency creates strong incentives for instructors to teach in ways that would result in good student evaluations. Because many instructors believe that the average student prefers courses that are entertaining, require little work, and result in high grades, they feel under pressure to conform to those expectations. Evidence is presented that the positive association between student grades and their evaluation of teaching reflects a bias rather than teaching effectiveness. If good teaching evaluations reflected improved student learning due to effective teaching, they should be positively related to the grades received in subsequent courses that build on knowledge gained in the previous course. Findings that teaching evaluations of concurrent courses, though positively correlated with concurrent grades, are negatively related to student performance in subsequent courses are more consistent with the assumption that concurrent evaluations are the result of lenient grading rather than effective teaching. Policy implications are discussed.
Journal Article
Examining the accuracy of students’ self-reported academic grades from a correlational and a discrepancy perspective: Evidence from a longitudinal study
The present longitudinal study examined the reliability of self-reported academic grades across three phases in four subject domains for a sample of 916 high-school students. Self-reported grades were found to be highly positively correlated with actual grades in all academic subjects and across grades 9 to 11 underscoring the reliability of self-reported grades as an achievement indicator. Reliability of self-reported grades was found to differ across subject areas (e.g., mathematics self-reports more reliable than language studies), with a slight yet consistent tendency to over-report achievement levels also observed across grade levels and academic subjects. Overall, the absolute value of over- and underreporting was low and these patterns were not found to differ between mathematics and verbal subjects. In sum, study findings demonstrate the consistent predictive utility of students' self-reported achievement across grade levels and subject areas with the observed tendency to over-report academic grades and slight differences between domains nonetheless warranting consideration in future education research.
Journal Article
Student Engagement Predictions in an e-Learning System and Their Impact on Student Course Assessment Scores
Several challenges are associated with e-learning systems, the most significant of which is the lack of student motivation in various course activities and for various course materials. In this study, we used machine learning (ML) algorithms to identify low-engagement students in a social science course at the Open University (OU) to assess the effect of engagement on student performance. The input variables of the study included highest education level, final results, score on the assessment, and the number of clicks on virtual learning environment (VLE) activities, which included dataplus, forumng, glossary, oucollaborate, oucontent, resources, subpages, homepage, and URL during the first course assessment. The output variable was the student level of engagement in the various activities. To predict low-engagement students, we applied several ML algorithms to the dataset. Using these algorithms, trained models were first obtained; then, the accuracy and kappa values of the models were compared. The results demonstrated that the J48, decision tree, JRIP, and gradient-boosted classifiers exhibited better performance in terms of the accuracy, kappa value, and recall compared to the other tested models. Based on these findings, we developed a dashboard to facilitate instructor at the OU. These models can easily be incorporated into VLE systems to help instructors evaluate student engagement during VLE courses with regard to different activities and materials and to provide additional interventions for students in advance of their final exam. Furthermore, this study examined the relationship between student engagement and the course assessment score.
Journal Article