64 Matching Annotations
  1. Last 7 days
    1. Yet large “leaks” in the metaphorical STEM pipeline likely occur by early child-hood in the U.S.

      This is well worded and has strong imagery

    2. A practical implication of these findings is that factors present before kindergarten may largely explain racial and ethnic underrepresentation in STEM.

      Implied, but not studied, indicating further study is required

    3. However, the study’s antecedent, opportunity, and pro-pensity factors do not fully explain the observed racial dis-parities.

      Limitations, what wasn't conferred.

    4. Asian students were initially less likely than White students to display advanced science achieve-ment in kindergarten (i.e., 7% versus 16%, respectively). Asian students then were more likely than White students to display advanced science achievement by fifth grade (i.e., 16% versus 13%, respectively).

      I wonder how much familial + social pressures played into this? i.e. "The Model Minority"

    5. We used White, non-Hispanic students as the reference group

      Are they saying this was the baseline they used to compare? As in, they just assumed it was the standard, or this was the standard simply because of circumstances?

    6. Internalizing Problem Behaviors subscale consisted of four items (i.e., is the child lonely, sad, anxious, or displays low self-esteem). Problem behavior frequency was rated using a four-point response scale ranging from “never” to “very often.” Higher scores indicated that the behavior occurred more frequently. The internal consistency reliability coefficients for the externalizing and internalizing problem behaviors scales were .89 and .78, respectively (Tourangeau et al., 2019)

      Very cool, as this aligns with the research I am interested in. Mirrors it in a way.

    7. he science achievement measure was designed to assess a student’s understanding about the physical, life, and Earth and space sciences as well as scientific inquiry. The mathe-matics achievement measure was designed to assess a stu-dent’s conceptual knowledge, procedural knowledge, and problem solving. The mathematics achievement measure included items on number sense, properties, and operations; measurement; geometry and spatial sense; data analysis, sta-tistics, and probability; and patterns, algebra, and functions. The reading achievement measure was designed to assess basic reading skills (e.g., print familiarity), vocabulary, and reading comprehension

      It would have been nice to see data supporting these subgroupings.

    8. item response theory (IRT)

      Also, it's cool that I will be using IRT. Used to determine if the distances from 1-2, 2-3, 3-4, & 4-5 are mathematically the same on a Likert-type scale.

    9. Emergent literacy (α = .57) was a standardized composite score of five items related to literacy activities. The first three items assessed the frequency of parents engaging in book reading and picture book reading with the child as well as the child reading outside school. The last two items reported the number of books that their child owned and how long the parent spent on reading to their child. We added standardized scores of the first three items and the last two items to obtain the standardized composite score

      Cool to see this in practice. My research turns self-efficacy into several different subgroups in a similar fashion.

    10. attrition

      Can you measure, for example, all 1st graders in a district, then the following year, all 2nd graders, 3rd, 4th, etc... and just assume that with a large sample size, the data is apples to apples?

    11. Hypothesis 1: Based on prior work examining the early onset and relative stability of racial or ethnic achievement disparities (e.g., Morgan et al., 2016; Von Hippel et al., 2018), we hypothesized that Black, Hispanic, or AINAPI students would be less likely than White students to dis-play advanced science or mathematics achievement during elementary school in unadjusted analyses. We expected the observed differences to be large (Morgan et al., 2016; Plucker & Peters, 2016; Rambo-Hernandez et al., 2019). We hypothesized that Black, Hispanic, or AINAPI stu-dents would be less likely than White students to display advanced levels of science or mathematics achievement by the end of kindergarten and throughout elementary school (Freyer & Levitt, 2004; Rambo-Hernandez et al., 2019; Von Hippel et al., 2018).

      This feels like a strong hypothesis that was well written.

    12. Use of universal screen-ing using standardized measures

      But also, we know students are already overtested, and even so, these tests are often heavily biased to favor the dominant group.

    13. Research Question 1: Are Black, Hispanic, or AINAPI students less likely than White students to display advanced science or mathematics achievement during elementary school? If so, how large are the observed gaps

      This feels off. A big difference between research and evaluation is that research asks few, specific, and concise questions while evaluations go for as much bang for your buck. This first research question looks like it is stretched to thin by having two questions attached to it.

    14. Among antecedent, opportunity, and propensity factors, propensity factors most strongly predict student achievement

      The cliche nature vs nurture argument comes to mind here...

    15. lead poisoning, environmental pollutants,

      It will be microplastics for future generations.

      Lead, asbestos, microplastics, it's all the same thing regirgitated for future generations.

    16. Black, Hispanic, and AINAPI students are more likely to experience concentrated poverty that results in fewer learn-ing opportunities and corresponding racial and ethnic achievement disparities during school because of histori-cally racialized policies and practices as well as ongoing residential and community segregation

      Viscious cycle..

    17. (Fryer & Levitt, 2004; Henry et al., 2020; Morgan et al., 2016; National Assessment of Educational Progress [NAEP], 2015, 2020; Navarro et al., 2012; Reardon & Galindo, 2009; Von Hippel et al., 2018).

      Clearly evident and well researched in the literature.

    18. 2.6 percentage point increase in publica-tions, a 4.3 percentage point increase in citations, and a .03

      2.6 and 4.3 feel signficant but 0.03 feels like a reach unless I am misunderstanding this.

  2. Feb 2026
    1. A thoughtful program can prepare students to be consumers of research, but also be able to access and analyze data to improve their organizations.

      But also, how do we get this message across to the lay person, because as much as we learn this unless we communicate it well politics will not change. Politics are often optics and semantics, so we must learn how to use this data to speak in a manner that is heard. It took 10 years for the TEA stuff to begin to be corrected and that was blatant misuse of data.

    2. First, we encourage individual faculty in educational leadership and policy preparation programs to emphasize through course-work both basic data analytic techniques, such as those presented here, and basic quantitative research concepts.

      Shoutout to literally this class existing

    3. Past research links poverty concentration to higher rates of special education enroll-ments

      Hawaii and California are richer states so they have more money but less students in special education. The cylce keeps turning...

    4. From 2003-2004 to 2016-2017, special education enrollment fell by 32,000 students, while statewide enrollment grew by approximately one million.

      Literal jaw drop... outlandish numbers of disproportionate prejudices..

    5. Educational leaders are thus uniquely positioned to draw on data in their local settings to monitor equity issues pertaining to special education students and other historically underserved groups.

      But also how often do we see leaders who lose sight of the children? I have seen many a leader climbing the ladder at the expense of marginalized communities. I have also seen good leaders but data is a double edged sword.

    6. which found that the Texas Education Agency systematically denied students special education services

      We read studies about what/how Texas drastically lessoned thier special education numbers and it is crazy to think they basically stopped identifitying students for special education based on a govenor's individual beliefs...

    1. to change the discourse. If we can control the discourse, we can contr

      Who controls the narrative? How do we control it? Politics feels like a war of optics and the left seems to need a recalibration.

    2. health and well-being. Thus, the poverty that exists in one part of the world is related to the affluence in another part. Similarly, the poverty that exists on one side of town is related to the affluence and

      How do we say this? What language do we need to use for people to hear us?

    3. People have literally died for education, yet we keep hearing that certain families do not value it

      People have literally died for it, that is how important it is. The hypocrisy in the highlighted statement is deafening.

    4. mplies, "If you come to school not reading you get treated as if you have no right to be in sc

      Following up on what Fagana said, I find it interesting that there is such a dichotamy between "They should learn that at school" vs "They should learn that at home." That type of thinking is a lose-lose mentatlity, and allows both the school and parents to cope out of responsibility. Sex ed for example, I have had many example of parents saying "the school has no right to teach my child about sex ed", and then the parent procedes to NOT teach the child about sex ed....

    5. students' parents were less likely to have transportation to travel across the city or that it was not particularly safe for Black people to be found in the school's neighborhood after d

      Many schools offer additional "voluntary" support and call it tier 1 support. anything that is voluntary is automatically tier 2 because it is not given to the whole school. Saying you "offered it" is not good enough when some families literally cannot attend for a myriad of reasons. Tier 1 means the ENTIRE school gets access. Voluntary opportunities are opportunites for the privledged.

    6. place students' academic struggles in the larger context of social failure including health, wealth, and funding gaps that impede their school success.

      Still thinking about the comment made that SAT does not predict post-secondary success but rather it predicts future earned income potential.

  3. Jan 2026
    1. ages of fourteen and twenty-four made up only 4.7 percent of thecity’s population, they accounted for 40.6 percent of the stop-and-friskchecks by police. More than 90 percent of those stopped were innocent.

      Flagrant bias and misuse of power

    2. A University of Marylandstudy showed that in Harris County, which includes Houston,prosecutors were three times more likely to seek the death penalty forAfrican Americans, and four times more likely for Hispanics, than forwhites convicted of the same charges

      WMD

    3. Sometimes these blind spots don’t matter. When we ask Google Mapsfor directions, it models the world as a series of roads, tunnels, andbridges. It ignores the buildings, because they aren’t relevant to the task.When avionics software guides an airplane, it models the wind, the speedof the plane, and the landing strip below, but not the streets, tunnels,buildings, and people.

      Relativity

    4. Maybe they predicted that a left-handed reliever would give up lots of hitsto right-handed batters—and yet he mowed them down

      Do random 'statistical anomalies' need us to change the model? Repetition seems important in this case.

    5. managers now knowprecisely where every player has hit every ball over the last week, over thelast month, throughout his career, against left-handers, when he has twostrikes, and so on

      There are arguments to be had about if athletes are getting better or technology/data is getting better. I tend to nearly always see it as technology and data. Look at the suits Michael Phelps wore when he broke Olympic records in '04, & '08. There are reasons that those suits are now banned in competitive swimming.

    6. Rhee developed a teacherassessment tool called IMPACT, and at the end of the 2009–10 schoolyear the district fired all the teachers whose scores put them in thebottom 2 percent. At the end of the following year, another 5 percent, or206 teachers, were booted out

      I was having a discussion with a 30-year teacher who is beloved in our school and about to retire. That teacher is mentoring a new teacher who is in his third year [last year of probationary teaching in Colorado] of teaching. The younger teacher was assigned a mentor because his performance scores have been quite low these last two years.

      All that to say myself and the veteran teacher believe that MOST teacher assessment tools used in the school are used as punitive measures and excuses to let people go.

    1. using these algorithms called humans that are really biased,

      Humans are a conglomeration of our experiences, are algorithms anything more than their total inputs?

    2. 200 million people in the United States each year

      In a bucket this big, it is no wonder "one-size algorithms" don't fit all. Big data often uses algorithms to cut corn and the O'Neil video spoke to how the algorithms are produced causing inequalities while cutting these corners.

    1. basically, well-meaning liberal white people—are part of the problem in struggling for social justice.

      It is an incredibly important position to know when to step-up or know when to step back. Step up in the face of oppression to point out the wrong but step back so as to not overpower the voices of the oppressed.

    2. But forces of oppression can be difficult to detect when you benefit from them (we call this a privilege hazard later in the book).d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }.d-08965af7-15f0-4167-901a-aa80e2b72f3c, .lh-08965af7-15f0-4167-901a-aa80e2b72f3c { background-color: var(--pubpub-active-discussion-highlight-color, rgba(45, 46, 47, 0.5)) }2Yolanda Yang, Jillian McCarteng the choices you make (or don’t get to make) each day. These systems of power are as real as rain. But forces of oppression can be difficult to detect when you benefit from them (we call this a privilege hazard later in the book). And this is where data come in: it was a set of intersecting systems of power and privilege that D?Yolanda Yang4 years agoPeople with privilege cannot recognize, even if they do, they are less likely to make any change, as this would decrease their benefit?Jillian McCarten2 years agoOne quote that I think of often is “when one has held a position of privilege for so long, equality feels like oppression.” ?Login to discuss.

      Important

    3. result of many unnamed colleagues and friends who may or may not have considered themselves feminists.

      The casting of many ripples. Positions of low power but high influence are important to cast these ripples.

    4. major systems of oppression are interlocking

      Burn it all down.

      But realistically, we cannot. So what is the next best option? We are fighting the good fight now, but how many of us and how long will it take?

    5. eminism begins with a belief in the “political, social, and economic equality of the sexes,”.d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Michela Banks

      Good definition to share and use.