MétaCan
Menu
Back to cohort
Record W32643322 · doi:10.1002/acm2.12958

An Investigation of Preservice Teachers' Perceptions of African American Students' Ability To Achieve in Mathematics and Science.

2000· article· en· W32643322 on OpenAlexfundno aff
Bradford F. Lewis, Alicia Collins, Vanessa R. Pitts

Bibliographic record

VenueJournal of Applied Clinical Medical Physics · 2000
Typearticle
Languageen
FieldSocial Sciences
TopicScience Education and Pedagogy
Canadian institutionsnot available
FundersBrainlabAtlantic Canada Opportunities Agency
KeywordsMathematics educationPerceptionScience educationPsychologyAfrican americanPedagogySociology

Abstract

fetched live from OpenAlex

This study investigated the perceptions of 30 predominantly white pre-service teachers about African American students' ability to achieve mathematics and science. Participants completed a three-part, open-ended questionnaire that asked them about their experiences with and awareness of African American students' mathematics and science achievement, reasons for African American students' low mathematics and science achievement, and changes or interventions they would suggest to address this problem. The questionnaire essentially assessed student teachers for awareness of, culpability in, and modifications to improve the mathematics and science achievement of African American students. Results indicated that respondents' perceptions of the mathematics and science ability of African American students were best characterized by King's (1991) notion of dysconscious racism, an uncritical habit of mind that justifies inequity and exploitation by accepting the existing order of things as given. Over one-third of the respondents were unaware of the problem. Respondents most often placed culpability for achievement with students' culture and community. Respondents overwhelmingly suggested modifications to the teaching and learning process as a vehicle for improving African American students' mathematics and science achievement. (Contains 34 references.) (SM) Reproductions supplied by EDRS are the best that can be made from the original document. PRESERVICE TEACHERS' PERCEPTIONS 00 ci AN INVESTIGATION OF PRESERVICE TEACHERS' PERCEPTIONS OF AFRICAN AMERICAN STUDENTS' ABILITY TO ACHIEVE IN MATHEMATICS AND SCIENCE PERMISSION TO REPRODUCE AND DISSEMINATE THIS MATERIAL HAS BEEN GRANTED BY radiotJ Le-oi TO THE EDUCATIONAL RESOURCES INFORMATION CENTER (ERIC) 1 U.S. DEPARTMENT OF EDUCATION Office of Educational Research and Improvement EDUCATIONAL RESOURCES INFORMATION CENTER (ERIC) CI This document has been reproduced as received from the person or organization originating it. CI Minor changes have been made to improve reproduction quality. ° Points of view or opinions stated this document do not necessarily represent official OERI position or policy. Bradford F. Lewis, Ph.D. and Vanessa Pitts Department of Instruction and Learning University of Pittsburgh Alicia Collins Department of Administrative and Policy Studies University of Pittsburgh Paper presented at the American Educational Research Association April 24-28, 2000 New Orleans, LA BEST COPY AVALABLE 2 PRESERVICE TEACHERS' PERCEPTIONS 2 An Investigation of Preservice Teachers' Perceptions of African American Students' Ability to Achieve Mathematics and Science INTRODUCTION Somehow, I happened to be alone the classroom with Mr. Ostrowski, my English teacher. He was a tall, rather reddish white man and he had a thick mustache. I had gotten some of my best marks under him, and he had always made me feel that he liked me. He was, as I have mentioned, a natural-born advisor, about what you ought to read, to do, or thinkabout any and everything. We used to make unkind jokes about him: why was he teaching Mason instead of somewhere else, getting for himself some of the success life that he kept telling us how to get? I know that he probably meant well what he happened to advise me that day. I doubt that he meant any harm. It was just his nature as an American white man. I was one of his top students, one of the school's top students but all he could see for me was the kind of future in your place that almost all white people see for black people. He told me, Malcolm, you ought to be thinking about a career. Have you been giving it thought? The truth is, I hadn't. I never have figured out why I told him, Well, yes, sir, I've been thinking I'd like to be a lawyer. Lansing certainly had no Negro lawyers or doctors either those days, to hold up an image I might have aspired to. All I really knew for certain was that a lawyer didn't wash dishes, as I was doing. Mr. Ostrowski looked surprised, I remember, and leaned back his chair and clasped his hands behind his head. He kind of half-smiled and said, Malcolm, one of life's first needs is for us to be realistic. Don't misunderstand me, now. We all here like you, you know that. But you've got to be realistic about being a nigger. A lawyer that's no realistic goal for a nigger. You need to think about something you can be. You're good with your hands making things. Everybody admires your carpentry shop Why don't you plan on carpentry? People like you as a person you'd get all kinds of work. (X, 1964. p.36-37) The problem that gives impetus to the present study is the low number of African American students who pursue science-related careers (Lewis, 1997; Lewis & Collins, 2000). At least since 1977 African Americans have consistently comprised less than 2% of practicing Ph.D. holding scientists (National Science Board, 1996); and at least since 1971 scholars have sought to understand the causes of underrepresentation through empirical research. While extant research has identified numerous factors, which correlate with students' career decisions, such as the number of math and science courses taken (Thomas, 1984), and the influence of math and science

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.061
GPT teacher head0.476
Teacher spread0.415 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2000
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Applied Clinical Medical PhysicsSame topicScience Education and PedagogyFrench-language works237,207