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The Learning Loss Effect In Genetics: What Ideas Do Students Retain Or Lose After Instruction?, Amber Todd, William L. Romine Oct 2018

The Learning Loss Effect In Genetics: What Ideas Do Students Retain Or Lose After Instruction?, Amber Todd, William L. Romine

Biological Sciences Faculty Publications

Modern genetics is a relatively new domain, but it is increasingly important for students to have a firm grasp on the content, because genetic technologies are becoming more commonplace. In a previous study, we used the Learning Progression-based Assessment of Modern Genetics to assess high school students’ knowledge of genetics concepts after an intensive inquiry-based genetics instructional period. Given that this type of intensive inquiry-based instruction is unique, we are now investigating how students’ knowledge of genetics changes after instruction (i.e., learning loss effect). Using a six-measure longitudinal design, we found that students retained significant gains in five of the …


Development And Evaluation Of A Model For Secondary Evolution Educators’ Professional Development Needs, William L. Romine, Ellen Barnett, Patricia J. Friedrichsen, Aaron J. Sickel Nov 2014

Development And Evaluation Of A Model For Secondary Evolution Educators’ Professional Development Needs, William L. Romine, Ellen Barnett, Patricia J. Friedrichsen, Aaron J. Sickel

Biological Sciences Faculty Publications

Background

Professional development (PD) efforts have improved acceptance and pedagogical practice related to the theory of evolution in high school biology teachers. However, these teachers express need for more PD related to evolution. It therefore becomes necessary to understand teachers’ PD needs prior to structuring PD efforts.

Methods

We formulated and validated a model to explain secondary teachers’ PD needs using data from a survey of 276 secondary biology teachers who reported teaching evolution.

Results

In addition to reliable subscales, we found that obstacles to teaching evolution, school and community support for evolution instruction, confidence in evolution instruction, and prior …


Engineering Mathematics Education At Wright State University: Uncorking The First Year Bottleneck, Nathan W. Klingbeil, Kuldip S. Rattan, Michael L. Raymer, David B. Reynolds, Richard Mercer Feb 2007

Engineering Mathematics Education At Wright State University: Uncorking The First Year Bottleneck, Nathan W. Klingbeil, Kuldip S. Rattan, Michael L. Raymer, David B. Reynolds, Richard Mercer

Kno.e.sis Publications

No abstract provided.


Work In Progress: The Wsu Model For Engineering Mathematics Education, Nathan W. Klingbeil, Richard Mercer, Kuldip S. Rattan, Michael L. Raymer, David B. Reynolds Oct 2005

Work In Progress: The Wsu Model For Engineering Mathematics Education, Nathan W. Klingbeil, Richard Mercer, Kuldip S. Rattan, Michael L. Raymer, David B. Reynolds

Kno.e.sis Publications

This paper summarizes progress to date on the WSU model for engineering mathematics education, an NSF funded curriculum reform initiative at Wright State University. The WSU model seeks to increase student retention, motivation and success in engineering through application-driven, just-in-time engineering math instruction. The WSU approach involves the development of a novel freshman-level engineering mathematics course EGR 101, as well as a large-scale restructuring of the engineering curriculum. By removing traditional math prerequisites and moving core engineering courses earlier in the program, the WSU model shifts the traditional emphasis on math prerequisite requirements to an emphasis on engineering motivation for …


A Proposed Undergraduate Bioinformatics Curriculum For Computer Scientists, Travis E. Doom, Michael L. Raymer, Dan E. Krane, Oscar Garcia Jan 2002

A Proposed Undergraduate Bioinformatics Curriculum For Computer Scientists, Travis E. Doom, Michael L. Raymer, Dan E. Krane, Oscar Garcia

Kno.e.sis Publications

Bioinformatics is a new and rapidly evolving discipline that has emerged from the fields of experimental molecular biology and biochemistry, and from the the artificial intelligence, database, and algorithms disciplines of computer science. Largely because of the inherently interdisciplinary nature of bioinformatics research, academia has been slow to respond to strong industry and government demands for trained scientists to develop and apply novel bioinformatics techniques to the rapidly-growing, freely-available repositories of genetic and proteomic data. While some institutions are responding to this demand by establishing graduate programs in bioinformatics, the entrance barriers for these programs are high, largely due to …