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This research adopts an intermediate view that ratings are imperfect, but useful and improvable through empirical modeling. The study constructs and cross-validates a covariance structure model to identify sources of desired and undesired influences on ratings, emphasizing how grading leniency and course workload shape evaluative 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is the main goal of the present research on student ratings?","Question",{"text":112,"@type":113},"To construct and confirm a covariance structure model that identifies sources of desired or undesired influences on student ratings.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How were the key findings from the successful model characterized?",{"text":117,"@type":113},"Courses giving higher expected grades were better liked and had lighter workloads, implying that grading leniency influences ratings.",{"name":119,"@type":110,"acceptedAnswer":120},"Why does the thought experiment separate variables such as instruction quality, ability, motivation, and grading leniency?",{"text":121,"@type":113},"It isolates how a single exogenous causal variable could generate correlations among evaluative ratings, expected grades, and course 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intermediate view-that student ratings may be imperfect but are neverthelessuseful and are also improvable through research.Thespecific aim of the present research was to construct andconfirm a covariance structure model that could identifysources of desired or undesired influences on student ratings.  \nThe most ambitious previous effort to describe andconfirm a covariance structure model of student ratings hasbeen Marsh's(1991)hierarchical confirmatory factor analy-sis of data provided by 35 items of the SEEQ (StudentEvaluations of Educational Quality)inventory.Marsh re-ported substantial confirmatory support for a nine-factorfirst-order structure overlaid with a four-factor structure inwhich the higher order factors represented similarity rela-tions among the nine first-order factors.  \nIn contrast with Marsh’s(1991)aim of analyzing thedimensional structure of student ratings,the present researchsought to evaluate theories of causal influences operating onstudent ratings.Altemative theories of the influences thataffect student ratings imply different patterns of relation-  \nAnthony G.Greenwald,Department of Psychology,Universityof Washington;Gerald M.Gillmore,Office of Educational Assess-ment,University of Washington.  \nThe research reported in this article was greatly facilitated by theOffice of Educational Assessment at the University of Washington.Additional support was provided by Grant SBR-9422242 from theNational Science Foundation,and Grant MH 41328 from theNational Institute of Mental Health.For suggestions concerningstatistical analyses,we thank Robert D.Abbott,Robert C.MacCal-lum,and Steven J.Breckler.  \nCorrespondence concerning this article should be addressed toAnthony G.Greenwald,Department of Psychology,Guthrie Hall,Box 351525,University of Washington,Seattle,Washington 98195-1525.Electronic mail may be sent via Internet to Anthony G.Greenwald at agg@u.washington.edu or to Gerald M.Gillmore atoea@u.washington.edu.  \n# No Pain,No Gain?The Importance of Measuring Course Workloadin Student Ratings of Instruction\n\nAnthony G.Greenwald and Gerald M.GillmoreUniversity of Washington  \nSamples of about 200 undergraduate courses were investigated in each of 3 consecutiveacademic terms.Course survey forms assessed evaluative ratings,expected grades,and courseworkloads.A covariance structure model was developed in exploratory fashion for the 1stterm's data,and then successfully cross-validated in each of the next 2 terms.The 2 majorfeatures of the successful model were that(a)courses that gave higher grades were better liked(a positive path from expected grades to evaluative ratings),and(b)courses that gave highergrades had lighter workloads (a negative relation between expected grades and workload).These findings support the conclusion that instructors'grading leniency influences ratings.This effect of grading leniency also importantly qualifies the standard interpretation thatstudent ratings are relatively pure indicators of instructional quality.  \nships among three categories of measures:(a)evaluativeratings,(b)expected grades,and(c)course workloads.  \n## Thought Experiments and Structural Models\n\nImagine collecting data in a large set of courses that sharethe same well-defined educational goal—say,increasingstudents'foreign language vocabulary.Course performancewill be graded,and students receive midterm exams thatallow them to develop expectations about what their finalgrades will be.Student rating surveys are administered,as istypical,before the final exam is given and,therefore,beforethe final grade can be known.The rating surveys areassumed to produce three types of measures:(a)evaluativeratings of the course,(b)estimates of expected final grade,and(c)self-reports of amount of work done for the course.  \nIn each of four replications of this thought experiment,","cbCair1hngzCXM6e","https://ap.wps.com/l/cbCair1hngzCXM6e","pdf",320216,"English","# Thought Experiments and Structural Models\n## Imagine collecting data in shared educational goals\n## Exogenous variables and causal influences\n## Expected relationships and grade aspirations","[{\"question\":\"What is the main goal of the present research on student ratings?\",\"answer\":\"To construct and confirm a covariance structure model that identifies sources of desired or undesired influences on student ratings.\"},{\"question\":\"How were the key findings from the successful model characterized?\",\"answer\":\"Courses giving higher expected grades were better liked and had lighter workloads, implying that grading leniency influences ratings.\"},{\"question\":\"Why does the thought experiment separate variables such as instruction quality, ability, motivation, and grading leniency?\",\"answer\":\"It isolates how a single exogenous causal variable could generate correlations among evaluative ratings, expected grades, and course workload.\"}]","No Pain,No Gain? - The Importance of Measuring Course Workload in Student Ratings of Instruction | PDF",23]