Describe how Brookhart and Nitko’s assertion might apply to your school or school district.
WEEK 2: Assessment Purpose, Strengths, and Weaknesses
Overview: In Week 2, you will explore the purpose of assessment. You will examine the advantages and disadvantages of various assessments utilized in many K – 12 settings. Education is driven by outcomes. As a leader in education, you will be expected to analyze the goals and assumptions inherent in different assessment instruments as part of evaluating curriculum and instruction.
Part A – Mastery-Level Grading or Standards-Based Grading
Brookhart and Nitko (2019) suggest that increased teaching, teacher effort, and working more effectively constitute “positive test preparation” because these actions result in increased student learning (p. 779). The authors, however, dissuade the use of high-stakes test preparation strategies such as coaching and the reallocation of instructional time and resources because they narrow the scope of what is taught in classrooms to cover only sample test items.
In today’s high-stakes testing environment, consider how you, as a K–12 administrator, would respond to Brookhart and Nitko’s assertions.
Write a 250- to 300-word response to the following:
Describe how Brookhart and Nitko’s assertion might apply to your school or school district.
Share specific examples of how you might work with faculty to provide a learning environment that is not high stakes test centered. Include at least 3 steps that must be taken to ensure that this conversation with your faculty might result in improved teaching and learning at the classroom level.
Reference
Brookhart, S. M., & Nitko, A. J. (2019). Educational assessment of students (8th ed.). Pearson Education, Inc.
Part B – Article Synthesis
Select and read 2 of the Week 2 articles provided in the attachments to this post.
Write a 250- to 300-word response to the following:
Describe the types of studies conducted.
Describe the population and sample size of the studies.
Compare the conclusions drawn by the authors relevant to the use of letter grades, standards-based grading, and/or mastery-based grading.
Provide citations according to APA guidelines.
Part 3 – Summative Assessment: Assumptions and Goals of Assessment Tools [
Exam Content
As the leader of your school district’s assessment and evaluation team, you have been asked to share information about two formal assessment tools with parents, teachers, administrators, and the larger community.
Identify 2 formal assessment tools used in a school district of your choice. Select assessments relevant to your current placement and/or your doctoral studies. For example, secondary teachers might consider the ACT, SAT, and/or state-mandated proficiency tests.
Create a 12- to 16-slide presentation providing an analysis of each assessment. Your presentation should:
Include speaker notes with your presentation. Speaker notes should be detailed and thoroughly cited with references.
Include a minimum of 5 peer-reviewed scholarly references with a copy and/or link to the assessments you reviewed.
WEEK 2 Learning Activities
Educational Assessment of Students, Ch. 7
Read Ch. 7, “Diagnostic and Formative Assessments.”
Educational Assessment of Students, Ch. 16
Read Ch. 16, “Standardized Achievement Tests.”
REQUIRED
Brookhart, S. M., Guskey, T. R., Bowers, A. J., et al. (2016). A century of grading research: Meaning and value in the most common educational measure. Review of Educational Research, 86(4), 803-848.
Klugman, E. M., & Ho, A. D. (2020). How can released state test items support interim assessment purposes in an educational crisis? Educational Measurement: Issues & Practice, 39(3), 65-69.
Scarlett, M. H. (2018). “Why did I get a C?”: Communicating student performance using standards-based grading. InSight: A Journal of Scholarly Teaching, 13, 59-75.
Requirements: Multi Answer
Review of Educational ResearchDecember 2016, Vol. 86, No. 4, pp. 803 –848DOI: 10.3102/0034654316672069© 2016 AERA. http://rer.aera.net803A Century of Grading Research: Meaning and Value in the Most Common Educational MeasureSusan M. BrookhartDuquesne UniversityThomas R. GuskeyUniversity of KentuckyAlex J. BowersTeachers College, Columbia UniversityJames H. McMillanVirginia Commonwealth UniversityJeffrey K. Smith and Lisa F. SmithUniversity of OtagoMichael T. Stevens and Megan E. WelshUniversity of California at DavisGrading 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 stud-ies: (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 con-demned teachers’ grades as unreliable. More recent studies of the relation-ships 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 prac-tices are discussed.672069RERXXX10.3102/0034654316672069Brookhart et al.A Century of Gradingresearch-article2016
Brookhart et al.804Keywords: grading, classroom assessment, educational measurementGrading refers to the symbols assigned to individual pieces of student work or to composite measures of student performance on student report cards. Grades or marks, as they were referred to in the first half of the 20th century, were the focus of some of the earliest educational research. Grading research history parallels the history of educational research more generally, with stud-ies becoming both more rigorous and sophisticated over time. Grading is important to study because of the centrality of grades in the educational experi-ence of all students. Grades are widely perceived to be what students “earn” for their achievement (Brookhart, 1993, p. 139), and have pervasive influence on students and schooling (Pattison, Grodsky, & Muller, 2013). Furthermore, grades predict important future educational consequences, such as dropping out of school (Bowers, 2010a; Bowers & Sprott, 2012; Bowers, Sprott, & Taff, 2013), applying and being admitted to college, and college success (Atkinson & Geiser, 2009; Bowers, 2010a; Thorsen & Cliffordson, 2012). Grades are especially predictive of academic success in more open admissions higher edu-cation institutions (Sawyer, 2013).Purpose of This Review, and Research QuestionThis review synthesizes findings from five types of grading studies: (a) early studies of the reliability of grades on student work, (b) quantitative studies of the composition of K–12 report card grades and related educational outcomes, (c) survey and interview studies of teachers’ perceptions of grades and grading prac-tices, (d) studies of standards-based grading (SBG) and the relationship between students’ report card grades and large-scale accountability assessments, and (e) grading in higher education. The central question underlying all of these studies is, “What do grades mean?” In essence, this is a validity question (Kane, 2006; Messick, 1989). It concerns whether evidence supports the intended meaning and use of grades as an educational measure. To date, several reviews have given par-tial answers to that question, but none of these reviews synthesize 100 years of research from five types of studies. The purpose of this review is to provide a more comprehensive and complete answer to the research question, “What do grades mean?”BackgroundThe earliest research on grading concerned mostly the reliability of grades teachers assigned to students’ work. The earliest investigation of which the authors are aware was published in the Journal of the Royal Statistical Society. Edgeworth (1888) applied the “theory of errors” (p. 600) based on normal curve theory to the case of grading examinations. He described three different sources of error: (a) chance; (b) personal differences among graders regarding the whole exam (severity or leniency and speed) and individual items on the exam, now referred to as task variation; and (c) “taking his [the examinee’s] answers as rep-resentative of his proficiency” (p. 614), now referred to as generalizing to the
A Century of Grading805domain. In parsing these sources of error, Edgeworth went beyond simple chance variation in grades to treat grades as subject to multiple sources of variation or error. This nuanced view, which was quite advanced for its time, remains useful today. Edgeworth pointed out the educational consequences of unreliability in grading, especially in awarding diplomas, honors and other qualifications to stu-dents. He used this point to build an argument for improving reliability. Today, the existence of unintended adverse consequences is also an argument for improving validity (Messick, 1989).During the 19th century, student progress reports were presented to parents orally by the teacher during a visit to a student’s home, with little standardization of content. Oral reports were eventually abandoned in favor of written narrative descriptions of how students were performing in certain skills like penmanship, reading, or arithmetic (Guskey & Bailey, 2001). In the 20th century, high school student populations became so diverse and subject area instruction so specific that high schools sought a way to manage the increasing demands and complexity of evaluating student progress (Guskey & Bailey, 2001). Although elementary schools maintained narrative descriptions, high schools increasingly favored per-centage grades because the completion of narrative descriptions was viewed as time-consuming and lacking cost-effectiveness (Farr, 2000). One could argue that this move to percentage grades eliminated the specific communication of what students knew and could do.Reviews by Crooks (1933), A. Z. Smith and Dobbin (1960), and Kirschenbaum, Napier, and Simon (1971) debated whether grading should be norm- or criterion-referenced, based on clearly defined standards for student learning. Although high schools tended to stay with norm-referenced grades to accommodate the need for ranking students for college admissions, some ele-mentary school educators transitioned to what was eventually called mastery learning and then standards-based education. Based on studies of grading reli-ability (F. J. Kelly, 1914; Rugg, 1918), in the 1920s, teachers began to adopt grading systems with fewer and broader categories (e.g., the A–F scale). Still, variation in grading practices persisted. Hill (1935) found variability in the fre-quency of grade reports, ranging from 2 to 12 times per year, and a wide array of grade reporting practices. Of 443 schools studied, 8% employed descriptive grading, 9% percentage grading, 31% percentage-equivalent categorical grad-ing, 54% categorical grading that was not percentage-equivalent, and 2% “gave a general rating on some basis such as ‘degree to which the pupil is working to capacity’” (Hill, 1935, p. 119). By the 1940s, more than 80% of U.S. schools had adopted the A–F grading scale. A–F remained the most commonly used scale until the present day. Current grading reforms move in the direction of SBG, a relatively new and increasingly common practice (Grindberg, 2014) in which grades are based on standards for achievement. In SBG, work habits and other nonachievement factors are reported separately from achievement (Guskey & Bailey, 2010).MethodLiterature searches for each of the five types of studies were conducted by dif-ferent groups of coauthors, using the same general strategy: (a) a keyword search
Brookhart et al.806of electronic databases, (b) review of abstracts against criteria for the type of study, (c) a full read of studies that met criteria, and (d) a snowball search using the references from qualified studies. All searches were limited to articles pub-lished in English. To identify studies of grading reliability, electronic searches using the terms “teachers’ marks (or marking)” and “teachers’ grades (or grad-ing)” were conducted in the following databases: ERIC, the Journal of Educational Measurement, Educational Measurement: Issues and Practice, ProQuest’s Periodicals Index Online, and the Journal of Educational Research. The criterion for inclusion was that the research addressed individual pieces of student work (usually examinations), not composite report card grades. Sixteen empirical stud-ies were found (Table 1).To identify studies of grades and related educational outcomes, search terms included “(grades OR marks) AND (model* OR relationship OR correlation OR association OR factor).” Databases searched included JSTOR, ERIC, and Educational Full Text Wilson Web. Criteria for inclusion were that the study (a) examined the relationship of K–12 grades to schooling outcomes, (b) used quan-titative methods, and (c) examined data from actual student assessments rather than teacher perspectives on grading. Forty-one empirical studies were identified (Tables 2, 3, and 4).For studies of K–12 teachers’ perspectives about grading and grading prac-tices, the search terms used were “grade(s),” “grading,” and “marking” with “teacher perceptions,” “teacher practices,” and “teacher attitudes.” Databases searched included ERIC, Education Research Complete, Dissertation Abstracts, and Google Scholar. Criteria for inclusion were that the study topic was K–12 teachers’ perceptions of grading and grading practices and were published since 1994 (the date of Brookhart’s previous review). Thirty-five empirical studies were found (31 are presented in Table 5, and four that investigated SBG are in Table 6).The search for studies of SBG used the search terms “standards” and (“grades” or “reports) and “education.” Databases searched included Psycinfo, Psycarticles, ERIC, and Education Source. The criterion for inclusion was that articles needed to address SBG. Eight empirical studies were identified (Table 6).For studies of grading in higher education, search terms included “grades” or “grading,” combined with “university,” “college,” and “higher education” in the title. Databases searched included EBSCO Education Research Complete, ERIC, and ProQuest (Education Journals). The inclusion criterion was that the study investigated grading practices in higher education. University websites in 12 dif-ferent countries were also consulted to allow for international comparisons. Fourteen empirical studies were found (Table 7).ResultsGrading ReliabilityTable 1 displays the results of studies on the reliability of teachers’ grades. The main finding was that great variation exists in the grades teachers assign to students’ work (Ashbaugh, 1924; Brimi, 2011; Eells, 1930; Healy, 1935; Hulten, 1925; F. J. Kelly, 1914; Lauterbach, 1928; Rugg, 1918; Silberstein, 1922; Sims, 1933; Starch, 1913, 1915; Starch & Elliott, 1912, 1913a, 1913b). Three studies (Bolton, 1927; (Text continues on p. 820.)
807TABLE 1Early studies of the reliability of gradesStudyMethodSampleMain findingsAshbaugh (1924)Descriptive statistics55 seniors and graduate students in Education grading 1 sev-enth-grade arithmetic paper● Grading the same paper on 3 occasions, the mean remained constant but the distribution narrowed● Grader inconsistency over time; grades more variable on Oc-casion 2 than Occasion 3● After presenting results to the class and discussing the prob-lems and the students’ work, graders devised a point scheme for each problem and grading variability decreasedBolton (1927)Descriptive statistics22 sixth-grade teachers of arith-metic in one district, grading 24 papers● Teachers are consistent with one another in their ratings● Average deviation was 5.1 (out of 100)● Greater variability for lowest-quality work (level of work as a source of variation)Brimi (2011)Descriptive statistics73 English teachers grading one essay● Range of scores was 46 points and covered all five letter grade levels (ABCDF)Eells (1930)Intrarater reliability; correla-tion of Time 1 and Time 2, in 11-week interval61 teachers in a measurement course, grading 3 elementary geography and 2 history ques-tions● Teacher inconsistency over time a major source of variation● Estimated reliability ranged from .25 to .51● Variability lowest for one very poor paper (level of work as a source of variation)Healy (1935)Descriptive statistics175 sixth-grade compositions from 50 different teachers, one each of Excellent, Superior, Average, Poor, Failure, reana-lyzed by trained judges● Format and usage errors weighed more heavily in teachers’ grades than the quality of ideas (relative emphasis of criteria as a source of variation in grades)Hulten (1925)Intrarater reliability; descrip-tive statistics for Time 1 and Time 2, in 2-month interval30 English teachers grading 5 compositions● Teacher inconsistency over time● 20% of compositions changed from pass to fail or vice versa on the second marking(continued)
808StudyMethodSampleMain findingsJacoby (1910)Descriptive statistics6 astronomy professors marking 11 exams● Little variability in grades● Student work quality was highLauter-bach (1928)Descriptive statistics57 teachers grading 120 papers (30 papers per teacher, half handwritten and half typed)● Student work quality was a source of variation in grades● In absolute terms, there was much variation by teacher for each paper● In relative terms, teachers’ marks reliably ranked studentsShriner (1930)Descriptive statistics25 high school English teachers and 25 algebra teachers, grad-ing 25 exams each (English and algebra, respectively)● Teachers’ grading was reliable● Median correlations of each teacher’s grade with the average grade for each paper were .946 (algebra) and .917 (English)● Greater teacher variability in grades for the poorer papersSilber-stein (1922)Descriptive statistics31 teachers grading 1 English paper that originally passed in high school (73%) but failed by Regents (59%)● When teachers regraded the same paper, they changed their grade● Variation in scores on individual questions on the exam were very variable and explained the overall grading variation, except for one question about syntax, where grades were more uniformSims (1933)Descriptive statisticsReanalysis of four data sets: 21 teachers grading 24 arithmetic papers; 25 teachers grading 25 algebra papers; 25 teach-ers grading 25 high school English exams; and 9 readers grading 20 psychology exams● Two kinds of variability in teachers’ grades: (a) differences in students’ work quality and (b) “differences in the standards of grading found among school systems and among teachers within a system” (p. 637)● Teacher variability in assigning grades was large● Variability in marks was reduced by converting scores to gradesStarch (1913)Descriptive statistics10 instructors grading 10 fresh-man English exams● Teacher variability was large, and largest for the two poorest papers● Isolated four sources of variation and reported probable error (p. 632, total probable error [pe] = 5.4 out of 100): (a) differ-ences among the standards of different schools (pe almost 0), TABLE 1 (continued)(continued)
809StudyMethodSampleMain findings(b) differences among the standards of different teachers (pe = 1.0), (c) differences in the relative values placed by different teachers on various elements in a paper, including content and form (pe = 2.1), and (d) differences due to the pure inability to distinguish between closely allied degrees of merit (pe = 2.2)Starch (1915)Descriptive statistics12 teachers grading 24 sixth- and seventh-grade composi-tions● Average teacher variability of 4.2 (out of 100) was reduced to 2.8 by forcing a normal distribution using a 5-category scale (poor, inferior, medium, superior, and excellent)Starch and Elliott (1912)Descriptive statistics142 high school English teach-ers grading 2 exams● Teacher variability in assigning grades was large (a range of 30–40 out of 100 points, pe = 4.0 and 4.8, respectively)● Teacher variability in the relative sense, as wellStarch and Elliott (1913a)Descriptive statistics138 high school mathematics teachers grading 1 geometry exam● Teacher variability was larger than for the English papers in Starch and Elliott (1912): pe = 7.5● Grade for 1 answer varies about as widely as composite grade for the whole examStarch and Elliott (1913b)Descriptive statistics122 high school history teachers grading 1 exam● Teacher variability was larger than for the English or math exams (Starch & Elliott, 1912, 1913a): pe = 7.7● Concluded that variability is due not to subject but to “the examiner and method of examination” (p. 680)TABLE 1 (continued)
810TABLE 2Studies of the relation of K–12 report card grades and tested achievementStudyMethodSampleMain findingsBrennan, Kim, Wenz-Gross, and Siperstein (2001)Correlation736 eighth-grade studentsCompared the Massachusetts Comprehensive Assessment System stan-dardized state reading test scores to grades in mathematics, English, and science, r = .54–.59Carter (1952)Correlation235 high school studentsGrades and standardized algebra achievement scores, r = .52Duckworth, Quinn, and Tsukayama (2012)Structural equation modelinga. 1,364 ninth-grade students● Standardized reading and mathematics test scores compared to GPA, r = .62–.66● Engagement and persistence are mediated through teacher evaluations of student conduct and homework completionb. 510 eighth-grade studentsDuckworth and Selig-man (2006)Correlation140 eighth-grade studentsGPA and 2003 TerraNova Second Edition/California Achievement Test, r = .66McCandless, Roberts, and Starnes (1972)Correlation433 seventh-grade studentsGrades and Metropolitan Achievement Test scores, r = .31, accounting for socioeconomic status, ethnicity, and genderMoore (1939)Correlation200 fifth- and sixth-grade studentsGrades and Stanford Achievement Test, r = .61Pattison, Grodsky, and Muller (2013)CorrelationU.S. nationally representative data sets of over 10,000 students eachHigh school GPA compared to reading (r = 0.46 to 0.54) and mathematics standardized tests, r = .52–.64● National Longitudinal Study of the High School Class of 1972● High School and Beyond sophomore cohort● National Educational Longitu-dinal Study of 1988● Educational Longitudinal Study of 2002Unzicker (1925)Correlation425 seventh- through ninth-grade studentsAverage grades across English, mathematics and history correlated .47 with the Otis intelligence testWoodruff and Ziomek (2004)CorrelationAbout 700,000 high schools stu-dents each year, 1991–2003Self-reported GPA and ACT composite scores, r = .56–.58Self-reported mathematics grades and ACT scores, r = .54–.57Self-reported English grades and ACT scores, r = .45–.50
811TABLE 3Studies of K–12 report card grades as multidimensional measures of academic knowledge, engagement, and persistenceStudyMethodSampleMain findingsBowers (2009)Multidimensional scaling195 students high school studentsGrades were multidimensional, separating core subject and noncore grades versus state standardized assessments in science mathematics and reading and the ACTBowers (2011)Multidimensional scaling4,520 high school students from the Educational Longi-tudinal Study of 2002Three-factor structure: (a) a cognitive factor that describes the relationship between tests and core subject grades, (b) an engagement factor between core subject grades and noncore subject grades, and (c) a factor that described the difference between grades in art and physical educationCasillas et al. (2012)Correlation; hierarchi-cal linear modeling4,660 seventh and eighth graders25% of the explained variance in GPAs was attributable the standardized assessments; academic discipline and commitment to school were strongly related to GPAFarkas, Grobe, Sheehan, and Shuan (1990)Regression486 eighth graders and their teachersStudent work habits were the strongest noncognitive predictors of gradesS. Kelly (2008)Hierarchical linear modeling1,653 sixth-, seventh-, and eighth-grade studentsPositive and significant effects of students’ substantive engagement on subsequent grades but no relationship with procedural engagementKlapp Lekholm and Cliffordson (2008)Structural equation modeling99,070 Swedish studentsGrades consisted of two major factors: (a) a cognitive achievement factor and (b) a noncognitive “common grade dimension”Klapp Lekholm and Cliffordson (2009); Klapp Lekholm (2011)Factor analysis; structural equation modeling99,070 Swedish studentsCognitive achievement factor of grades consists of student self-perception of competence, self-efficacy, coping strategies, and subject-specific interest; noncognitive factor consists of motivation and a general interest in schoolMiner (1967)Factor analysis671 high school studentsExamined academic grades in first, third, sixth, ninth, and twelfth grades; achievement tests in fifth, sixth, and ninth grades; and citizenship grades in first, third, and sixth grades; a three factor solu-tion was identified: (a) objective achievement, (b) behavior factor, and (c) high school achievement as measured through gradesSobel (1936)DescriptiveNot reportedStudents categorized into three groups based on comparing grades and achievement test levels; grade-superior, middle-group, mark-superiorThorsen and Clif-fordson (2012)Structural equation modelingAll Grade 9 students in Swe-den, 99,085 (2003), 105,697 (2004), 108,753 (2005)Generally replicated Klapp Lekholm and Cliffordson (2009)Thorsen (2014)Structural equation modeling3,855 students in SwedenGenerally replicated Klapp Lekholm and Cliffordson (2009) in examining norm-referenced gradesWillingham, Pol-lack, and Lewis (2002)Regression8,454 students from 581schoolsA moderate relationship between grades and tests was identified as well as strong positive relation-ships between grades and student motivation, engagement, completion of work assigned, and persistence
812TABLE 4Studies of grades as predictors of educational outcomesStudyMethodSampleMain findingsAlexander, Entwisle, and Kabbani (2001)Regression301 Grade 9 studentsStudent background, grade retention, academic performance and behavior strongly related to dropping outAllensworth and Easton (2007)Descriptive; regres-sion24,894 first-time ninth grades students in ChicagoGPA and failing a course in early high school strongly predict dropoutAllensworth, Gwynne, Moore, and de la Torre (2014)Descriptive; regres-sion19,963 Grade 8 Chicago studentsMiddle school grades and attendance are stronger predictors of high school performance in comparison to test scores, and middle school grades are a strong predictor of students on or offtrack for high school successBalfanz, Herzog, and MacIver (2007)Regression12,972 sixth-grade students from PhiladelphiaPredictors of dropping out of high school included failing mathemat-ics or English, low attendance, poor behaviorBarrington and Hendricks (1989)analysis of variance; correlation214 high school studentsGPA, number of low grades, intelligence test scores, and student mobility significantly predicted dropout.Bowers (2010a)Cluster analysis188 students tracked from Grade 1 through high schoolLongitudinal low-grade clusters across all types of course subjects correlated with dropping out and not taking the ACTBowers (2010b)Regression193 students tracked from Grade 1 through high schoolReceiving low grades (D or F) and being retained in grade strongly related to dropping outBowers and Sprott (2012)Growth mixture modeling5,400 Grade 10 Education Longitudinal Study of 2002 studentsNoncumulative GPA trajectories in early high school were strongly predictive of dropping outBowers, Sprott, and Taff (2013)Receiver operat-ing characteristic analysis110 dropout flags from 36 previous studiesDropout flags focusing on GPA were some of the most accurate drop-out flags across the literatureCairns, Cairns, and Neck-erman (1989)Cluster analysis; regression475 Grade 7 studentsBeyond student demographics, student aggressiveness and low levels of academic performance associated with dropping outCliffordson (2008)Two-level modeling164,106 Swedish studentsGrades predict achievement in higher education more strongly than Swedish Scholastic Aptitude Test, and criterion-referenced grades predict slightly better than norm-referenced grades(continued)
813StudyMethodSampleMain findingsEkstrom, Goertz
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