22 Matching Annotations
  1. Aug 2023
    1. Grading Contracts: Assessing TheirEffectiveness on Different Racial Formations
      1. The study is designed to examine the different experiences of effectiveness with grading contracts by African American, Asian and Pacific Islander, and White students, what the research questions as "effectiveness on different racial formations", which is important because it is the only study of race for scholarship in labor-based grading contracts and of a quantitative sort, and the author thinks the findings will inform their own practice as an instructor and their implementing them as a co-director of the writing program under study.
      2. There are a few research questions including how effective has my grading contract been for my students; does it work better for some students than others; and how are various racial formations faring on our assessments, and the primary variable of interest is three senses for effectiveness.
      3. The author assumes the variables of effectiveness represent quantity of work produced, its quality, and reactions to and acceptance of grading contracts, which serve as a proxy for experiences the students have of grading contracts.
      4. All the students are positioned through a lens of assets with writing assessment systems positioning only white students with assets, so the participants are positioned as advantanged in the case of white students and disadvantaged in the cases of African American and Asian and Pacific Islander students by effects of conventional grading, and their senses of effectiveness are framed as malleable, because contract grading is alternative to conventional grading and implies the participants have agency to earn a grade whether or not they follow standardized edited academic American English.
      5. The author claims to measure consequential validity of grading contracts which have either positive or negative consequences for quantity and quality of writing by the participants.
      6. The final sample size of the survey reflected the distribution of enrollment by the different racial formations under study, because even though it looked as if more White students responded, when student enrollment statistics are compared to students who completed the exit surveys, students of color are somewhat overrepresented in the survey... White students are underrepresented when compared to overall university enrollment figures, and the sample size, and all students portfolios were included along with their grade distributions, so the sample is big enough to make the claims about effectiveness of grading contracts on different racial formations in the writing program with limitations of the sample in this study only being for African American students which represent the lowest enrollment at the university to make claims about African American students' experiences.
  2. Local file Local file
    1. Theorizing Failure in US Writing Assessments
      1. The study was designed to learn whether labor-based grading affects failure of African American, Asian American, Latino/a, and Native students historically believed to fail at writing. The importance of the study is to show that the students are only believed to fail at writing quality, which, in turn leads to their failure at labor. The author thinks the findings will inform practice by preparing faculty to introduce and apply labor-based contract grading to preventing writing assessment systems from creating failure for the students.
      2. The specific data collection used was an exit survey on the effectiveness of and happiness with labor-based contract grading and analytical scoring of samples from student writing portfolios. The main predictors are that courses graded conventionally produce failure at qualities of writing to standardized edited academic American English and that courses graded with labor-based contracts produce failure at labor required to write in the spirit and manner of writing assignments.
      3. The author assumes the variables of effectiveness, happiness, and analytical scoring in conventionally graded courses for qualities of writing to standardized edited academic American English serve as a proxy for assimilation to white habits of discourse.
      4. The predictors and variables are framed as malleable, because the author reframes both meanings of labor as another kind of failure. The participants are positioned with assets or strengths to write in standardized edited academic American English as well as in writing assessment systems that construct failure for the students when they mesh their English in ways reflective of the language evolving? The implication is the participants have agency to inform disciplinary habits of discourse with their English.
      5. Construct validity here tests the theory that labor-based contract grading produces labor failure at the same time as affording students opportunities to advance in standardized edited academic American English without being penalized for not exacting it in their writing; that is, at the same time, labor contracts prevent quality failure from constructing failure for African American, Asian American, Latino/a, and Native students historically believed to fail.
      6. The author selected students with non-probability sampling to target the population of specific students in the basic and first-year writing course sequences at the university of the study. The final sample size was 30-45% of approximately 1,300 students for each of the years 2005 and 2009 to 2012, which is nearly half of the students enrolled each year making it big enough to make claims about generic survey responses and grade point averages, but that there is another half of the students in which the fewer African American students could be greater represented is a limitation of the sample in this study.

    Annotators

    1. This is a significant ethnic inequality but, perhaps because the benefi-ciaries are White, it goes entirely unremarked in the press furore about the overall accessstatistics (above)

      Success by whites unremarked is how whiteness works, normalizing their success.

    2. Numbers are increasingly used to justify policy priorities and to label teachers, schools,districts, and even entire countries, as educational successes and failures. National testingprograms, such as the No Child Left Behind (NCLB) reforms in the US and the use ofschool performance tables in England, have popularized the idea that numbers can be usedto expose (and change) failing schools (Gillborn and Youdell 2000; Darling-Hammond2007; Barber 2012). For example, across the globe politicians and pressure-groups fre-quently try to make their case by quoting results from PISA (Program of InternationalStudent Assessment) – which is run by the Organization for Economic Co-operation andDevelopment (OECD). Prominent examples exist in the States, the UK and Australia (seeLingard, Creagh, and Vass 2012). Countries’ positions in the PISA tables are often cited asif they unambiguously and accurately represent the relative quality of schooling in differ-ent nations (despite their very different populations and education systems). And yet thecommentaries rarely include any detail about the relatively small samples (less than 200schools in all but one of the US returns since 2000)(NCES n.d.); the selective curricularcoverage of the tests (in reading, math, and science); nor the fact that students in differ-ent countries sometimes take different assessments or miss certain assessments altogether(Stewart 2013). Despite these severe limitations, the UK government frequently cites PISAresults as evidence of the need for change (cf. Department for Education (DfE) 2015, 8)and has stated that it will ‘measure the increased performance of the school system as awhole by reference to international tables of student attainment, such as PISA’ (quoted inScott 2016).

      This reminds me of what might be called the "wrong drivers" by Fullan in education reform.

    3. We build upon previous relevant research and go further byexplicitly drawing on classic work in CRT

      Classic work in CRT must have been quantitative, for instance, to show structural racism in support of people of color's lived experiences in qualitative forms in the same classic work.

    4. uantitative methods cannot matchqualitative approaches in terms of their suitability for understanding the nuances of thenumerous social processes that shape and legitimate race inequity. However, quantitativemethods are well placed to chart the wider structures, within which individuals live theireveryday experiences, and to highlight the structural barriers and inequalities that differentlyracialized groups must navigate

      Quantitative data even not collected by myself can support my claims about structural constraints on observations I make from qualitative research.

    Annotators

    1. Suggestions for Researchers

      These suggestions are about data users who can communicate results to people who are not savvy with data or need application of results to their contexts without analysis of the results in quantitative ways, or even clearer ways.

    2. researchers should not presume to interpret their findings in a vacuum,uninformed by the experiences and insights of the communities that are directly affected by theirwork. There is no easy way to achieve this; as we noted in relation to positionality (above) a socialidentity does not bestow a single unproblematic wisdom or insight on anyone; however, therecognition does place a responsibility on researchers to take seriously how their data, analysis andfindings make sense to the people implicated in the study.

      I guess this means that qualitative methodologies are always required to interpret quantitative data about people of color.

    3. Suggestions for Users

      There are subheadings with lowercase Roman numerals and subheadings in lower case letters to the Roman numerals. How many sets of questions are there suggested for users?

    4. Suggestions for Researchers

      Choose variables that reflect how racism is endemic to U.S. society. Moreover, instead of choosing as many variables as possible, make a model with only those variables that support tenets of CRT.

    5. Each variable that is included willreduce the apparent effect of other variables: it is possible, therefore, tomuddy the waters simply by including a surplus of variables without anysensible judgement about which might be the most relevant. In this way‘the signal is overwhelmed by the noise’

      This reminds of "beneath the white noise", which I have not read about tracking African American students into basic writing yet.

    6. Suggestions for Researchers

      If you do QuantCrit research, then state your background for positioning yourself in the research. Check your biases, or put them out there to be checked. Also, like you put the research perspective on your positionality, take the perspective off of students and put it on the systems that afford opportunities in or limit the students' lives instead.

    7. The lack of positionalitystatements in virtually all quantitative research powerfully symbolizes the beliefthat the data, analysis, and presentation of the research is entirely separate fromthe life histories, concerns and biographies of the researcher/s. This is, of course,in line with one of the most frequent operations of Whiteness in society, wherebyrace and ‘ethnic’ concerns are presented as tangential to mainstream debates andpriorities.[

      A positionality statement is crucial to preventing whiteness from perpetuating white supremacy.

    8. 1) the centrality of racism; 2) numbersare not neutral; 3) categories are neither ‘natural’ nor given: for ‘race’ read ‘racism’; 4) voice andinsight (data cannot speak for itself); and 5) a social justice/equity orientation

      These are key concepts of quantcrit.

    9. simply providing statistical data is no guarantee oftransparency; key questions and inequities can be hidden or misrepresented, for example, dependingon decisions that are made about which data are selected for release, how they are categorized andpresented. Crawford (2019) concluded that “knowing misrepresentations of quantitative data are atthe heart of an institutional process through which race and racism are produced, legitimizedperpetuated in education.” QuantCrit is intended to make these issues more visible and to guide morecritical discussion and analysis of such data.

      This is rationale for quantcrit.

    10. QuantCrit, therefore, adopts ‘a position of principled ambivalence, neitherrejecting numbers out of hand nor falling into the trap of imagining that numeric data have any kindof enhanced status, value, or neutrality’ (p. 174).

      Is this a definition of quantcrit?

    11. Scholars have adopted multiple different approaches tothis task; one of the most frequently cited is a paper that sets out a series of clear questions andchallenges that can shape a QuantCrit approach (Gillborn et al 2018). Inspired by developments inDisability Critical Race Theory (DisCrit) (Annamma et al 2013 & 2018), this strategy takes thesignature elements of CRT, sometimes called ‘tenets’, and translates them into specific principles thatcan act as a set of sensitizing questions and offer critical guidance when navigating quantitative datawhich ‘have no objective reality beyond the frameworks of meaning and politics that create them’(Gillborn et al, 2018, 169).

      These are some of the important scholars for the theory.

    12. The approach began in educational studies and quickly developed aninternational and interdisciplinary character, including applications in medicine (Gerido, 2020) andeven in the art of writing (Hammond, 2019). Simultaneously, there has been ferocious criticism fromdetractors who are outraged by the suggestion that numbers are anything other than objective andscientific (Airaksinen, 2018). The ideas behind QuantCrit took shape initially through the work of agroup of CRT education researchers as they worked to contribute to a special issue of the journal‘Race Ethnicity and Education’ (ed. Garcia, López & Vélez 2018).

      This is background on the theory of QuantCrit.

    Annotators