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Record W3087554371 · doi:10.18260/1-2--35754

Allowing Freshman Engineering Students to Encounter Multiple Disciplines: Discipline Oriented Labs in the First Semester Engineering Curriculum

2024· article· en· W3087554371 on OpenAlexaff
Benjamin D. McPheron, Willis Troy, C. P. Baker

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicEngineering Education and Pedagogy
Canadian institutionsGeomechanica (Canada)
Fundersnot available
KeywordsCurriculumEngineering educationMathematics educationComputer scienceEngineeringEngineering managementEngineering ethicsPedagogySociologyPsychology

Abstract

fetched live from OpenAlex

Anderson University is a small liberal arts university established in the Church of God movement, located in Anderson, Indiana.The engineering program started in 2013, and now has ABET accredited majors in Mechanical, Electrical, and Computer Engineering.The first semester engineering course has undergone several changes since the program's inception, and has evolved into three corequisite courses, accompanied by a 2-hour recitation section.The first semester engineering curriculum consists of a 1-hour lecture course (ENGR 2001), a 2hour ME lab course (ENGR 2002), and a 2-hour ECE lab course (ENGR 2003).Providing these two lab courses allows students to gain basic understanding of the engineering disciplines offered by the university and affords them tools for exploration of their practice.While lab courses of this sort are not entirely unique to the Anderson University first semester engineering program, some of the mechanisms and course structure differ from other programs.Students also meet for a twohour recitation section in the evenings, which allows them to get tutoring for Calculus and Chemistry, as well as engage in engineering group projects with their cohort.The current formulation of the first semester courses has been offered for two consecutive years.This work presents the course content with an emphasis on lab instruction, course learning outcomes, and assessment results for the first two years, along with lessons learned.

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)0.003
metaresearch head score (Gemma)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.083

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0070.003
Open science0.0020.007
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0250.011

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 head0.007
GPT teacher head0.272
Teacher spread0.264 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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