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Record W2584357700 · doi:10.18260/1-2--6049

An Experimental Program To Enhance Retention Of At Risk Freshmen

2020· article· en· W2584357700 on OpenAlexaboutno aff
Joan Burtner, Benjamin S. Kelley, Allen F. Grum

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicEngineering Education and Pedagogy
Canadian institutionsnot available
Fundersnot available
KeywordsAttritionMathematics educationQuarter (Canadian coin)Engineering educationSession (web analytics)Academic yearScience and engineeringPsychologyMathematicsComputer scienceMedical educationEngineeringMedicineEngineering management

Abstract

fetched live from OpenAlex

Abstract NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract . — Session 2653 ..-. -- An Experimental Program to Enhance Retention of At-Risk Freshmen Benjamin S. Kelley, Joan A. Burtner, and Allen F. Grum Mercer University School of Engineering, Macon, Georgia INTRODUCTION In the Fall of 1992, the Mercer University School of Engineering implemented an experimental program entitled Applications in Math and Science (AIMS). This program targeted marginally-qualified and thus at-risk entering engineering freshmen. The goals of the program were to 1) increase the rate of retention of this group of students from their freshman to their sophomore year and 2) enhance their performance in introductory science and mathematics courses. The year-long program consisted of two parts: the Fall Quarter applications courses in math and science, and the Winter and Spring Quarter follow-up lab courses designed to provide academic support for the students while they were enrolled in regular Chemistry and Calculus courses, Program success was measured in terms of satisfactory performance in Calculus and Chemistry courses as well as persistence in the School of Engineering at the beginning of the student’s second year in college. Motivation for an Intervention Strategy Approximately one-third of all of the undergraduate students who enrolled at Mercer for the 1990 Fall Quarter were no longer enrolled in the Fall of 1991. For the School of Engineering, the attrition rate was even higher. Almost half of the 1990 freshman engineering class did not return to the Engineering School for their sophomore year. These statistics clearly indicated that there was a need for some kind of intervention. In addition to the concern about low rates of retention, the School of Engineering had a variety of other reasons for wanting to implement this experimental program. The primary motivating factors included several that may be somewhat unique to schools like Mercer. First, the School of Engineering has a primary mission of quality undergraduate education and teaching. This philosophy of quality education and teaching led us to examine the possible causes for the lack of persistence of our least-qualified entering freshmen. Second, because Mercer is a small private school, by the time the student arrives on campus, the university has already made a substantial investment of time and money in the student. Finally, because Mercer is a moderately selective school, our freshmen engineering students are academically qualified and expect to succeed in an engineering curriculum. The Importance of the Freshman Year In terms of retention, the freshman year appears to be the most critical. Various sources indicate that the freshman-to-sophomore attrition rate for four year colleges is approximately 30%. 1JZ3 In fact, almost 20% of the freshmen leave before the end of their first term. Many of the students decide to leave within the first six weeks of classes. Because of the importance of the first year, the School of Engineering decided to design a program that focused on at-risk freshmen engineering students. ---- .- ?@xij 1996 ASEE Annual Conference Proceedings ‘.JyyHll’3

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.517

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.019
GPT teacher head0.322
Teacher spread0.303 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations2
Published2020
Admission routes1
Has abstractyes

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