Test Score to Measure Teacher Performance Critique … Article Critique
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¶ … educator evaluation systems that relies only one component i.e. student performance on standardized tests seems to be unpopular with teachers and is controversial among statisticians (Ballou & Springer, 2015). Although there are reasonable concerns about the prevailing system used in teacher assessment, there are various decent reasons that raise alarm about assertions that evaluating teachers' effectiveness mainly through student test scores provides a way of improving student achievement. Any thorough evaluation will essentially involve a combination of various factors that offer a more precise view of teacher activities in classroom and how they contribute to student learning (Ballou & Springer, 2015).
If value-added scores need to be part of the high-stakes teacher decisions, proper evaluation of the magnitude of possible error in the estimates is essential. Otherwise, decisions that rely on such analyses propose the risk of being unfair to teachers. The researchers note that the study does not seek to provide general critique of estimation error within value-added assessment. Instead they focus on problems that they discover in teacher evaluation systems: (1) systems that ignore estimation error altogether and (2) systems that rely on t-statistics as a summary measure of teacher performance. Obviously, it is wrong to evaluate two teachers with similar effectiveness differently. More troubling, resources are likely to be wasted if interventions targeting teachers do take into account the likelihood that the used ratings provide doubtful outcomes owing employment of erroneous methodology (Ballou & Springer, 2015). There exists a broad agreement among statisticians that only student test scores are not adequately reliable and binding measures of teacher effectiveness, even if the most advanced statistical applications like value-added modelling are used. For various reasons, results of the study analyses make researchers doubt if the methodology is capable of accurately identifying more and less effective teachers since value-added assessment estimates prove to be unsound across various statistical models, years, and classes teachers teach (Ballou & Springer, 2015).
Value-added assessment evaluates for data that links students to teachers who taught them the tested subjects. Even though some might believe that state administrative data systems can be accurate in this regard, often this is not true (Ballou & Springer, 2015). Value-added score's instability tends to arise from the differences in student characteristics assigned to specific teachers in a certain year. As seen from the small samples of students in the studies used in the paper and from various influences with regard to student learning both outside and inside school as well as the failure to measure entire student achievements in class, there are appreciable variations. For these reasons, the scholars have warned against heavy dependence on test scores, even if sophisticated value-added assessment approaches are in use. Apart from concerns arising from statistical methodology in the paper, other practical considerations do not support total dependence on student test scores in evaluating teachers. In the research, too much focus on basic math and reading marks may result in narrow and over-simplification of the curriculum to favour only the formats and subjects that are evaluated (Ballou & Springer, 2015).
Although the value-added method seems to support stronger inferences regarding the impact of schools and their programs on student development compared to less sophisticated approaches, a number of studies have consistently warned that contribution of value-added assessment is insufficient in supporting high-stakes inferences regarding individual teachers. In spite of the hopes in many, even deploying the most developed value-added models, fail to adjust adequately for student backgrounds and the context in teachers' classrooms. In addition, less sophisticated models are worse. The difficulty in the study arises mostly because of non-random sorting for both teachers and students across schools, as well as non-random sorting of both students and teachers within institutions. Regardless of the statistical models advanced by the study, they cannot fully compensate the fact that a number of teachers will always have a high number of learners who tend to be very difficult to teach or whose marks on traditional tests are often not valid (like those who have special education needs). Within any school, a score cohort is very small to anticipate all of these characteristics to be representative in same proportion in every classroom. Finally, teachers' value-added impacts can be evaluated only in cases where teachers teach the same mix of successful and struggling students, something which rarely occurs, or if statistical scores of effectiveness are fully adjusted for the different mix of students, which is something that is very hard to accomplish (Ballou & Springer, 2015).
Various extraneous factors have considerable and strong influence on student learning gains, apart from teachers' teaching abilities whose scores will be attached. These comprise the influences of the students' other teachers, both previous teachers and current teachers, teaching other subjects as well as tutors, often associated with very large influences on gaining value. Such factors include school conditions like the quality of curriculum materials, class size, specialist or tutoring supports, and other factors, which affect learning.
In the article, the authors fail to address the effect that other factors, such as peer support parental support and environment help students improve learning, in addition to classroom teaching. For example, many parents can and do help children assimilate lessons at home, away from and in addition to classroom teaching. Some parents, for various reasons cannot supplement their wards' learning quest. This issue itself might project a wrong evaluation of a teacher's capacity to deliver. The teacher may then gain or lose credibility accordingly, for no personal contribution or fault, respectively.
Secondly, learning may thrive if healthy competition exists within the learning environment, making the role of peer support an important contribution to enhanced learning acumen. Not all students can be equal; however, adequate competitiveness can encourage students to exert more to meet existent standards. On the other hand, a slow learner may suffer due to too many brighter learners in the classroom. In the same way, irrespective of the teacher's acumen and skill, a cohort of average learners would hardly be expected to rise above such average or below-average levels.
Last, the environment to which the student belongs affects his off-school study hours and quality. The teacher cannot have much control on conditions outside the institution, often causing an impression on his scores.
The study results do not test the general accuracy of value-added assessments within the state the researchers studied. A considerably small number of students can be categorised as being in the unclaimed, non-exempt group. Even when all are claimed, the effect on teacher value added will be negligible. Teachers within the exempt but claimed group tend to have a performance that is essentially average. Different teachers could be hurt or helped by the failure to leave out such students from rosters; however, no bias arises in the entire value-added scores (Ballou & Springer, 2015).
While various reasons support concerns regarding the current system of teacher evaluation in the study, there are a number of reasons supporting sceptic view of the claims that, evaluating teachers' effectiveness through student test scores may result in the desired outcomes. Findings in the study provide minute support for the perception of the way test-based incentives for schools or individual teachers can improve achievement, or how expectation of such incentives in individual teachers suffice in producing gains in student learning. The research shows that approaches for teacher evaluation that mostly rely on test scores may result in narrowing and over-simplification of the curriculum, and misidentification of both unsuccessful and successful teachers. These negative influences may arise from both statistical and practical difficulties used in evaluating teachers using the test scores of their students. Some much publicized incidents in the study show that use of value-added assessments within high-stakes decisions can result in cheating in teachers. The most common forms of cheating entails altering the student answer sheets and even showing answers to students (Ballou & Springer, 2015).
Statisticians usually agree that such use must be pursued with great restraint. Various pitfalls exist when one makes causal acknowledgments of teacher effectiveness based on the forms of data presented in typical school districts. There is still insufficient understanding of the way different technical problems threaten rationality of such interpretations. One of the concerns raised by scholars is that prospects in value-added methods are capable of misidentifying both unsuccessful and successful teachers and, owing to the methods' instability and inability to separate other effects on learning can generate confusion regarding the relative sources that influence student achievement (Ballou & Springer, 2015). Usually efforts aimed at addressing one statistical problem like the ones in the study normally introduce fresh ones. Even sophisticated evaluations of student test scores generate estimations of teacher quality, which vary significantly from one year to another. Various factors influence the extent of errors arising from value-added models aimed at determining teacher effectiveness. In addition, measurement errors render approximations of teacher effectiveness that arises from value-added models very unstable (Ballou & Springer, 2015).
The statistical concerns described in the study are… [END OF PREVIEW]
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