MétaCan
Menu
← Back to cohort
Record W2271868148 · doi:10.18260/1-2--5253

A Middle School Project For Science And Math Enhancement Through Engineering

2020· article· en· W2271868148 on OpenAlexaff
Karen High, Becky Hammack, Beth Watt, Julie Thomas, Adrienne Redmond, Pat Jordan, Jean Dockers

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicEngineering Education and Pedagogy
Canadian institutionsStillwater (Canada)
FundersOklahoma State UniversityConocoPhillips
KeywordsMathematics educationComputer scienceScience and engineeringEngineeringMathematicsEngineering ethics

Abstract

fetched live from OpenAlex

Abstract NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract A Middle School Project for Science and Math Enhancement through Engineering Abstract This study is focused on the impact of curricular and extra curricular engineering-based instructional activities on middle students’ perceptions of their ability to become engineers. Middle school students are at an age where high interest activities are essential for motivation and relevant learning. This is also the age where students’ interest can be piqued to consider careers in STEM fields. This study also looks at math content knowledge, attitudes toward math and science, and perceptions of technology, engineering, and what defines engineering. In 2007, the Stillwater Middle School received a $15,000 grant from the Stillwater Public Education Foundation to start an engineering program for sixth- and seventh-grade students. The grant allowed the middle school to partner with Oklahoma State University to develop a multi- faceted engineering program. Through this partnership between the middle school and local university, three primary instructors have developed, coordinated, and conducted the majority of the components of the program. The ideas and initiative behind the program were proposed and enacted by a chemical engineering professor at Oklahoma State University, who is also highly involved in the pre-service teacher program at the university as well as several engineering education initiatives at her university. She has partnered with two middle school science instructors to develop, fund, conduct, and expand the engineering program at the middle school. The Enriching Science and Math through Engineering project consists of the following three components for students with an embedded teacher professional development program for middle school teachers. A Curriculum Integration project has sixth and seventh grade core team teachers (math, science, social studies, and language arts) using existing and new integrated engineering modules during school. The new modules were developed by the teachers working with engineering and education professors. A Summer Camp is an engineering project based program for 6th and 7th grade students delivered by two science teachers with support from an engineering professor. An After School Mentoring Program that meets once a week for 45 sixth and seventh grade girls. The College of Engineering provided mentors to support the students in understanding engineering and to encourage them to consider engineering careers. Middle school students participate in engineering projects that were age appropriate and encouraged problem solving, creativity and collaborative learning, as well as meet professional engineering women. Seventh grade girls served as cross-age mentors for sixth grade girls in addition to the college level mentors. In 2007, the engineering professor was the lead for the project. In 2008, the two middle school science teachers are providing project leadership. A variety of instruments were administered to determine mathematics and science content knowledge changes, knowledge about engineering and technology and the impact the instructional activities had on overall student perceptions. Results have shown positive impact of the interventions.

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)0.005
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.021
Threshold uncertainty score0.070

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0080.002
Scholarly communication0.0040.002
Open science0.0020.005
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0210.004

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 head0.060
GPT teacher head0.289
Teacher spread0.229 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations2
Published2020
Admission routes1
Has abstractyes

Explore more

Same topicEngineering Education and Pedagogy→French-language works237,207→