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Development and Assessment of Modules to Integrate Quantitative Skills in Introductory Biology Courses
Redesigning undergraduate biology courses to integrate quantitative reasoning and skill development is critical to prepare students for careers in modern medicine and scientific research. In this paper, we report on the development, implementation, and assessment of stand-alone modules that integrat...
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Published in: | CBE life sciences education 2016-06, Vol.15 (2), p.ar14-12 |
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description | Redesigning undergraduate biology courses to integrate quantitative reasoning and skill development is critical to prepare students for careers in modern medicine and scientific research. In this paper, we report on the development, implementation, and assessment of stand-alone modules that integrate quantitative reasoning into introductory biology courses. Modules are designed to improve skills in quantitative numeracy, interpreting data sets using visual tools, and making inferences about biological phenomena using mathematical/statistical models. We also examine demographic/background data that predict student improvement in these skills through exposure to these modules. We carried out pre/postassessment tests across four semesters and used student interviews in one semester to examine how students at different levels approached quantitative problems. We found that students improved in all skills in most semesters, although there was variation in the degree of improvement among skills from semester to semester. One demographic variable, transfer status, stood out as a major predictor of the degree to which students improved (transfer students achieved much lower gains every semester, despite the fact that pretest scores in each focus area were similar between transfer and nontransfer students). We propose that increased exposure to quantitative skill development in biology courses is effective at building competency in quantitative reasoning. |
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In this paper, we report on the development, implementation, and assessment of stand-alone modules that integrate quantitative reasoning into introductory biology courses. Modules are designed to improve skills in quantitative numeracy, interpreting data sets using visual tools, and making inferences about biological phenomena using mathematical/statistical models. We also examine demographic/background data that predict student improvement in these skills through exposure to these modules. We carried out pre/postassessment tests across four semesters and used student interviews in one semester to examine how students at different levels approached quantitative problems. We found that students improved in all skills in most semesters, although there was variation in the degree of improvement among skills from semester to semester. One demographic variable, transfer status, stood out as a major predictor of the degree to which students improved (transfer students achieved much lower gains every semester, despite the fact that pretest scores in each focus area were similar between transfer and nontransfer students). 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Hoffman, S. Leupen, et al. CBE—Life Sciences Education © 2016 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).</rights><rights>2016 K. Hoffman, S. Leupen, © 2016 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). 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In this paper, we report on the development, implementation, and assessment of stand-alone modules that integrate quantitative reasoning into introductory biology courses. Modules are designed to improve skills in quantitative numeracy, interpreting data sets using visual tools, and making inferences about biological phenomena using mathematical/statistical models. We also examine demographic/background data that predict student improvement in these skills through exposure to these modules. We carried out pre/postassessment tests across four semesters and used student interviews in one semester to examine how students at different levels approached quantitative problems. We found that students improved in all skills in most semesters, although there was variation in the degree of improvement among skills from semester to semester. One demographic variable, transfer status, stood out as a major predictor of the degree to which students improved (transfer students achieved much lower gains every semester, despite the fact that pretest scores in each focus area were similar between transfer and nontransfer students). We propose that increased exposure to quantitative skill development in biology courses is effective at building competency in quantitative reasoning.</description><subject>Attitude</subject><subject>Biology</subject><subject>Biology - education</subject><subject>College Science</subject><subject>Data Interpretation, Statistical</subject><subject>Demography</subject><subject>Educational Measurement - methods</subject><subject>Female</subject><subject>Genetics</subject><subject>Grounded Theory</subject><subject>Humans</subject><subject>Interviews</subject><subject>Learning</subject><subject>Learning Modules</subject><subject>Logistic Models</subject><subject>Male</subject><subject>Maryland (Baltimore)</subject><subject>Mathematical Models</subject><subject>Models, Theoretical</subject><subject>Pretests Posttests</subject><subject>Skill Development</subject><subject>Statistical Analysis</subject><subject>Students</subject><subject>Summative Evaluation</subject><subject>Teaching Methods</subject><subject>Thinking</subject><subject>Thinking Skills</subject><subject>Undergraduate Study</subject><subject>Worksheets</subject><issn>1931-7913</issn><issn>1931-7913</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>7SW</sourceid><recordid>eNqFkUFvEzEQhS1ERUvLlRvIRy6bemKvvb4glVCgqFWFaM-W12sHg7MOtjdS_j0OKVE59TQzmm-eZuYh9BrIDKAT56a3M2gbIhsCHX-GTkBSaIQE-vxRfoxe5vyTEMYJtC_Q8VwA48DhBLmPdmNDXK_sWLAeB3yRs835bxkdvonDFGzGJeKrsdhl0sXib5Meiy-6-I3F33_5EDL24w5IFTclpi3-4GOIyy1exClVwTN05HTI9tVDPEX3ny7vFl-a69vPV4uL68Yw1pamFUyKAQh3nM6N49wJRjV3rDe9I5Y76Ton-k6IXvfEEOcEpV1Ph44Ac66jp-j9Xnc99Ss7mHpG0kGtk1_ptFVRe_V_Z_Q_1DJuFJNEUsqrwLsHgRR_TzYXtfLZ2BD0aOOUVf05tPV7c3gaFZ1gQs5bUtHZHjUp5pysO2wERO18VNVHBa0iUu18rANvH99xwP8ZV4E3e8Ambw7ty68ABEBK-gcZAaVH</recordid><startdate>20160601</startdate><enddate>20160601</enddate><creator>Hoffman, Kathleen</creator><creator>Leupen, Sarah</creator><creator>Dowell, Kathy</creator><creator>Kephart, Kerrie</creator><creator>Leips, Jeff</creator><general>American Society for Cell Biology</general><scope>7SW</scope><scope>BJH</scope><scope>BNH</scope><scope>BNI</scope><scope>BNJ</scope><scope>BNO</scope><scope>ERI</scope><scope>PET</scope><scope>REK</scope><scope>WWN</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>20160601</creationdate><title>Development and Assessment of Modules to Integrate Quantitative Skills in Introductory Biology Courses</title><author>Hoffman, Kathleen ; Leupen, Sarah ; Dowell, Kathy ; Kephart, Kerrie ; Leips, Jeff</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c445t-57497d106f632cf66f743a6f4bcbf0e6f9f8f7b877bab0c0ff7338b3d8014ff83</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Attitude</topic><topic>Biology</topic><topic>Biology - education</topic><topic>College Science</topic><topic>Data Interpretation, Statistical</topic><topic>Demography</topic><topic>Educational Measurement - methods</topic><topic>Female</topic><topic>Genetics</topic><topic>Grounded Theory</topic><topic>Humans</topic><topic>Interviews</topic><topic>Learning</topic><topic>Learning Modules</topic><topic>Logistic Models</topic><topic>Male</topic><topic>Maryland (Baltimore)</topic><topic>Mathematical Models</topic><topic>Models, Theoretical</topic><topic>Pretests Posttests</topic><topic>Skill Development</topic><topic>Statistical Analysis</topic><topic>Students</topic><topic>Summative Evaluation</topic><topic>Teaching Methods</topic><topic>Thinking</topic><topic>Thinking Skills</topic><topic>Undergraduate Study</topic><topic>Worksheets</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Hoffman, Kathleen</creatorcontrib><creatorcontrib>Leupen, Sarah</creatorcontrib><creatorcontrib>Dowell, Kathy</creatorcontrib><creatorcontrib>Kephart, Kerrie</creatorcontrib><creatorcontrib>Leips, Jeff</creatorcontrib><collection>ERIC</collection><collection>ERIC (Ovid)</collection><collection>ERIC</collection><collection>ERIC</collection><collection>ERIC (Legacy Platform)</collection><collection>ERIC( SilverPlatter )</collection><collection>ERIC</collection><collection>ERIC PlusText (Legacy Platform)</collection><collection>Education Resources Information Center (ERIC)</collection><collection>ERIC</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>CBE life sciences education</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Hoffman, Kathleen</au><au>Leupen, Sarah</au><au>Dowell, Kathy</au><au>Kephart, Kerrie</au><au>Leips, Jeff</au><au>Batzli, Janet</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><ericid>EJ1101199</ericid><atitle>Development and Assessment of Modules to Integrate Quantitative Skills in Introductory Biology Courses</atitle><jtitle>CBE life sciences education</jtitle><addtitle>CBE Life Sci Educ</addtitle><date>2016-06-01</date><risdate>2016</risdate><volume>15</volume><issue>2</issue><spage>ar14</spage><epage>12</epage><pages>ar14-12</pages><issn>1931-7913</issn><eissn>1931-7913</eissn><abstract>Redesigning undergraduate biology courses to integrate quantitative reasoning and skill development is critical to prepare students for careers in modern medicine and scientific research. In this paper, we report on the development, implementation, and assessment of stand-alone modules that integrate quantitative reasoning into introductory biology courses. Modules are designed to improve skills in quantitative numeracy, interpreting data sets using visual tools, and making inferences about biological phenomena using mathematical/statistical models. We also examine demographic/background data that predict student improvement in these skills through exposure to these modules. We carried out pre/postassessment tests across four semesters and used student interviews in one semester to examine how students at different levels approached quantitative problems. We found that students improved in all skills in most semesters, although there was variation in the degree of improvement among skills from semester to semester. One demographic variable, transfer status, stood out as a major predictor of the degree to which students improved (transfer students achieved much lower gains every semester, despite the fact that pretest scores in each focus area were similar between transfer and nontransfer students). We propose that increased exposure to quantitative skill development in biology courses is effective at building competency in quantitative reasoning.</abstract><cop>United States</cop><pub>American Society for Cell Biology</pub><pmid>27146161</pmid><doi>10.1187/cbe.15-09-0186</doi><tpages>12</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Attitude Biology Biology - education College Science Data Interpretation, Statistical Demography Educational Measurement - methods Female Genetics Grounded Theory Humans Interviews Learning Learning Modules Logistic Models Male Maryland (Baltimore) Mathematical Models Models, Theoretical Pretests Posttests Skill Development Statistical Analysis Students Summative Evaluation Teaching Methods Thinking Thinking Skills Undergraduate Study Worksheets |
title | Development and Assessment of Modules to Integrate Quantitative Skills in Introductory Biology Courses |
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