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Facilitating Growth through Frustration: Using Genomics Research in a Course-Based Undergraduate Research Experience

    Authors: David Lopatto1, Anne G. Rosenwald2,*, Justin R. DiAngelo3, Amy T. Hark4, Matthew Skerritt5, Matthew Wawersik6, Anna K. Allen7, Consuelo Alvarez8, Sara Anderson9, Cindy Arrigo10, Andrew Arsham11, Daron Barnard12, Christopher Bazinet13, James E. J. Bedard14, Indrani Bose15, John M. Braverman16, Martin G. Burg17, Rebecca C. Burgess18, Paula Croonquist19, Chunguang Du20, Sondra Dubowsky21, Heather Eisler22, Matthew A. Escobar23, Michael Foulk24, Emily Furbee25, Thomas Giarla26, Rivka L. Glaser27, Anya L. Goodman28, Yuying Gosser29, Adam Haberman30, Charles Hauser31, Shan Hays32, Carina E. Howell33, Jennifer Jemc34, M. Logan Johnson35, Christopher J. Jones36, Lisa Kadlec37, Jacob D. Kagey38, Kimberly L. Keller39, Jennifer Kennell40, S. Catherine Silver Key41, Adam J. Kleinschmit42, Melissa Kleinschmit42, Nighat P. Kokan43, Olga Ruiz Kopp44, Meg M. Laakso45, Judith Leatherman46, Lindsey J. Long47, Mollie Manier48, Juan C. Martinez-Cruzado49, Luis F. Matos50, Amie Jo McClellan51, Gerard McNeil52, Evan Merkhofer53, Vida Mingo54, Hemlata Mistry55, Elizabeth Mitchell21, Nathan T. Mortimer56, Debaditya Mukhopadhyay57, Jennifer Leigh Myka58, Alexis Nagengast59, Paul Overvoorde60, Don Paetkau61, Leocadia Paliulis62, Susan Parrish63, Mary Lai Preuss64, James V. Price44, Nicholas A. Pullen65, Catherine Reinke66, Dennis Revie67, Srebrenka Robic68, Jennifer A. Roecklein-Canfield69, Michael R. Rubin70, Takrima Sadikot71, Jamie Siders Sanford72, Maria Santisteban73, Kenneth Saville74, Stephanie Schroeder64, Christopher D. Shaffer75, Karim A. Sharif76, Diane E. Sklensky77, Chiyedza Small78, Mary Smith79, Sheryl Smith80, Rebecca Spokony81, Aparna Sreenivasan82, Joyce Stamm83, Rachel Sterne-Marr84, Katherine C. Teeter85, Justin Thackeray86, Jeffrey S. Thompson87, Stephanie Toering Peters88, Melanie Van Stry89, Norma Velazquez-Ulloa90, Cindy Wolfe91, James Youngblom92, Brian Yowler93, Leming Zhou94, Janie Brennan95, Jeremy Buhler96, Wilson Leung75, Laura K. Reed97, Sarah C. R. Elgin75
    VIEW AFFILIATIONS HIDE AFFILIATIONS
    Affiliations: 1: Center for Teaching, Learning and Assessment, Grinnell College, Grinnell, IA 50112, USA; 2: Biology, Georgetown University, Washington, DC 20057, USA; 3: Division of Science, Penn State Berks, Reading, PA 19610, USA; 4: Biology, Muhlenberg College, Allentown, PA 18104, USA; 5: Science, SUNY Corning Community College, Corning, NY 14830, USA; 6: Biology, College of William and Mary, Williamsburg, VA 23187, USA; 7: Biology, Howard University, Washington, DC 20059, USA; 8: Biology, Longwood University, Farmville, VA 23909, USA; 9: Biosciences, Minnesota State University Moorhead, Moorhead, MN 56563, USA; 10: Biology, New Jersey City University, Jersey City, NJ 07305, USA; 11: Biology, Bemidji State University, Bemidji, MN 56601, USA; 12: Biology, Worcester State University, Worcester, MA 01602, USA; 13: Biological Sciences, St. John’s University, Queens, NY 11439, USA; 14: Biology, University of the Fraser Valley, Abbotsford, BC, V2S 7M8, Canada; 15: Biology, Western Carolina University, Cullowhee, NC 28723, USA; 16: Biology, Saint Joseph’s University, Philadelphia, PA 19131, USA; 17: Biomedical Sciences and Cell & Molecular Biology, Grand Valley State University, Allendale, MI 49401, USA; 18: Biological Sciences, Stevenson University, Owings Mills, MD 21117, USA; 19: Biology, Anoka-Ramsey Community College, Coon Rapids, MN 55433, USA; 20: Biology, Montclair State University, Montclair, NJ 07043, USA; 21: Biology, McLennan Community College, Waco, TX 76708, USA; 22: Biology, University of the Cumberlands, Williamsburg, KY 40769, USA; 23: Biological Sciences, California State University San Marcos, CA 92096, USA; 24: Biology, Mercyhurst University, Erie, PA 16546, USA; 25: Biology, Washington and Jefferson College, Washington, PA 15301, USA; 26: Biology, Siena College, Loudonville, NY 12211, USA; 27: Biological Sciences, Stevenson University, Owings Mills, MD 21117, USA; 28: Chemistry and Biochemistry, California Polytechnic State University, San Luis Obispo, CA 93407, USA; 29: Student Research and Scholarship, City College CUNY, New York, NY 10031, USA; 30: Biology, University of San Diego, San Diego, CA 92110, USA; 31: Biology, St. Edward’s University, Austin, TX 78704, USA; 32: Biology, Western Colorado University, Gunnison, CO 81231, USA; 33: Biological Sciences, Lock Haven University, Lock Haven, PA 17745, USA; 34: Biology, Loyola University Chicago, Chicago, IL 60660, USA; 35: Biology, Notre Dame College, South Euclid, OH 44121, USA; 36: Biological Sciences, Moravian College, Bethlehem, PA 18018, USA; 37: Biology, Wilkes University, Wilkes-Barre, PA 18766, USA; 38: Biology, University of Detroit Mercy, Detroit, MI 48221, USA; 39: Biology, William Woods University, Fulton, MO 65251, USA; 40: Biology, Vassar College, Poughkeepsie, NY 12604, USA; 41: Biological and Biomedical Sciences, North Carolina Central University, Durham, NC 27707, USA; 42: Natural and Applied Science, University of Dubuque, Dubuque, IA 52001, USA; 43: Natural Sciences, Cardinal Stritch University, Milwaukee, WI 53217, USA; 44: Biology, Utah Valley University, Orem, UT 84058, USA; 45: Biology, Eastern University, St. Davids, PA 19087, USA; 46: Biological Sciences, University of Northern Colorado, Greeley, CO 80639, USA; 47: Biology, Oklahoma Christian University, Oklahoma City, OK 73136, USA; 48: Biological Sciences, George Washington University, Washington, DC 20052, USA; 49: Biología, University of Puerto Rico at Mayagüez, Mayagüez, PR 00680, USA; 50: Biology, Eastern Washington University, Cheney, WA 99004, USA; 51: Science and Mathematics, Bennington College, Bennington, VT 05201, USA; 52: Biology, York College / CUNY, Jamaica, NY 11451, USA; 53: Natural Sciences, Mount Saint Mary College, Newbergh, NY 12550, USA; 54: Biology, Columbia College, Columbia, SC 29203, USA; 55: Biology and Biochemistry, Widener University, Chester, PA 19013, USA; 56: Biological Sciences, Illinois State University, Normal, IL 61790, USA; 57: Molecular Biology, Biochemistry, and Bioinformatics, Towson University, Towson, MD 21252, USA; 58: Biology, Gateway Community and Technical College, Florence, KY 41042, USA; 59: Chemistry and Biochemistry, Widener University, Chester, PA 19013, USA; 60: Biology, Macalester College, St. Paul, MN 55105, USA; 61: Biology, Saint Mary’s College, Notre Dame, IN 46556, USA; 62: Biology, Bucknell University, Lewisburg, PA 17837, USA; 63: Biology, McDaniel College, Westminster, MD 21157, USA; 64: Biological Sciences, Webster University, St. Louis, MO 63119, USA; 65: Biological Sciences, University of Northern Colorado, Greeley, CO 80639, USA; 66: Biology, Linfield College, McMinnville, OR 97128, USA; 67: Biology, California Lutheran University, Thousand Oaks, CA 91360, USA; 68: Biology, Agnes Scott College, Decatur, GA 30030, USA; 69: Chemistry, Simmons College, Boston, MA 02115, USA; 70: Biology, University of Puerto Rico at Cayey, Cayey, PR 00736, USA; 71: Biology, Washburn University, Topeka, KS 66621, USA; 72: Biology, Ohio Northern University, Ada, OH 45810, USA; 73: Biology, University of North Carolina at Pembroke, Pembroke, NC 28372, USA; 74: Biology, Albion College, Albion, MI 49224, USA; 75: Biology, Washington University in St. Louis, St. Louis, MO 63130, USA; 76: Biology, Massasoit Community College, Brockton, MA 02302, USA; 77: Biology, Lane College, Jackson, TN 38301, USA; 78: Biology, Medgar Evers College, CUNY, Brooklyn, NY 11225, USA; 79: Biology, North Carolina A & T State University, Greensboro, NC 27411, USA; 80: Biology, Arcadia, University, Glenside, PA 19038, USA; 81: Natural Sciences, Baruch College, CUNY, New York, NY 10010, USA; 82: Biology, School of Natural Sciences, California State University, Monterey Bay, Seaside, CA 93950, USA; 83: Biology, University of Evansville, Evansville, IN 47722, USA; 84: Biology, Siena College, Loudonville, NY 12211, USA; 85: Biology, Northern Michigan University, Marquette, MI 49855, USA; 86: Biology, Clark University, Worcester, MA 01610, USA; 87: Biology, Denison University, Granville, OH 43023, USA; 88: Biology, Wartburg College, Waverly, IA 50677, USA; 89: Biology, Lane College, Jackson, TN 38301, USA; 90: Biology, Lewis & Clark College, Portland, OR 97219, USA; 91: Biology, Kentucky Wesleyan College, Owensboro, KY 42301, USA; 92: Biological Sciences, California State University Stanislaus, Turlock, CA 95382, USA; 93: Biology, Grove City College, Grove City, PA 16127, USA; 94: Health Information Management, University of Pittsburgh, Pittsburgh, PA 15213, USA; 95: Energy, Environmental and Chemical Engineering, Washington University in St. Louis, St. Louis, MO 63130, USA; 96: Computer Science and Engineering, Washington University in St. Louis, St. Louis, MO 63130, USA; 97: Biological Sciences, University of Alabama Tuscaloosa, AL 35487, USA
    AUTHOR AND ARTICLE INFORMATION AUTHOR AND ARTICLE INFORMATION
    • Received 16 October 2019 Accepted 23 January 2020 Published 28 February 2020
    • ©2020 Author(s). Published by the American Society for Microbiology

    • [open-access] This is an Open Access article distributed under the terms of the Creative Commons Attribution-Noncommercial-NoDerivatives 4.0 International license (https://creativecommons.org/licenses/by-nc-nd/4.0/ and https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode), which grants the public the nonexclusive right to copy, distribute, or display the published work.
    • †Supplemental materials available at http://asmscience.org/jmbe
    • *Corresponding author. Mailing address: Biology Department, Georgetown University, 306 Regents Hall, 37th and O Sts, NW, Washington, DC 20057. Phone: 202-687-5997. E-mail [email protected]
    Source: J. Microbiol. Biol. Educ. February 2020 vol. 21 no. 1 doi:10.1128/jmbe.v21i1.2005
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    Abstract:

    A hallmark of the research experience is encountering difficulty and working through those challenges to achieve success. This ability is essential to being a successful scientist, but replicating such challenges in a teaching setting can be difficult. The Genomics Education Partnership (GEP) is a consortium of faculty who engage their students in a genomics Course-Based Undergraduate Research Experience (CURE). Students participate in genome annotation, generating gene models using multiple lines of experimental evidence. Our observations suggested that the students’ learning experience is continuous and recursive, frequently beginning with frustration but eventually leading to success as they come up with defendable gene models. In order to explore our “formative frustration” hypothesis, we gathered data from faculty via a survey, and from students via both a general survey and a set of student focus groups. Upon analyzing these data, we found that all three datasets mentioned frustration and struggle, as well as learning and better understanding of the scientific process. Bioinformatics projects are particularly well suited to the process of iteration and refinement because iterations can be performed quickly and are inexpensive in both time and money. Based on these findings, we suggest that a dynamic of “formative frustration” is an important aspect for a successful CURE.

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2020-02-28
2020-08-10

Abstract:

A hallmark of the research experience is encountering difficulty and working through those challenges to achieve success. This ability is essential to being a successful scientist, but replicating such challenges in a teaching setting can be difficult. The Genomics Education Partnership (GEP) is a consortium of faculty who engage their students in a genomics Course-Based Undergraduate Research Experience (CURE). Students participate in genome annotation, generating gene models using multiple lines of experimental evidence. Our observations suggested that the students’ learning experience is continuous and recursive, frequently beginning with frustration but eventually leading to success as they come up with defendable gene models. In order to explore our “formative frustration” hypothesis, we gathered data from faculty via a survey, and from students via both a general survey and a set of student focus groups. Upon analyzing these data, we found that all three datasets mentioned frustration and struggle, as well as learning and better understanding of the scientific process. Bioinformatics projects are particularly well suited to the process of iteration and refinement because iterations can be performed quickly and are inexpensive in both time and money. Based on these findings, we suggest that a dynamic of “formative frustration” is an important aspect for a successful CURE.

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Author and Article Information

  • Received 16 October 2019 Accepted 23 January 2020 Published 28 February 2020
  • ©2020 Author(s). Published by the American Society for Microbiology

  • [open-access] This is an Open Access article distributed under the terms of the Creative Commons Attribution-Noncommercial-NoDerivatives 4.0 International license (https://creativecommons.org/licenses/by-nc-nd/4.0/ and https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode), which grants the public the nonexclusive right to copy, distribute, or display the published work.
  • †Supplemental materials available at http://asmscience.org/jmbe
  • *Corresponding author. Mailing address: Biology Department, Georgetown University, 306 Regents Hall, 37th and O Sts, NW, Washington, DC 20057. Phone: 202-687-5997. E-mail [email protected]

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Facilitating Growth through Frustration: Using Genomics Research in a Course-Based Undergraduate Research Experience
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Reed, foaf_surname=Reed, pub_isAffiliatedWith=[com.pub2web.rdf.cci.facet.ContentItem[id=http://asm.metastore.ingenta.com/content/affiliation/jmbe/10.1128/jmbe.v21i1.2005-aff97]]}], com.pub2web.rdf.cci.facet.ContentItem[id=http://asm.metastore.ingenta.com/content/author/jmbe/10.1128/jmbe.v21i1.2005-103,webId=/content/author/jmbe/10.1128/jmbe.v21i1.2005-103,properties={foaf_givenname=Sarah C. R., foaf_name=Sarah C. R. Elgin, foaf_surname=Elgin, pub_isAffiliatedWith=[com.pub2web.rdf.cci.facet.ContentItem[id=http://asm.metastore.ingenta.com/content/affiliation/jmbe/10.1128/jmbe.v21i1.2005-aff75]]}]]
Citation: Lopatto D, Rosenwald A, DiAngelo J, Hark A, Skerritt M, Wawersik M, Allen A, Alvarez C, Anderson S, Arrigo C, Arsham A, Barnard D, Bazinet C, Bedard J, Bose I, Braverman J, Burg M, Burgess R, Croonquist P, Du C, Dubowsky S, Eisler H, Escobar M, Foulk M, Furbee E, Giarla T, Glaser R, Goodman A, Gosser Y, Haberman A, Hauser C, Hays S, Howell C, Jemc J, Johnson M, Jones C, Kadlec L, Kagey J, Keller K, Kennell J, Key S, Kleinschmit A, Kleinschmit M, Kokan N, Kopp O, Laakso M, Leatherman J, Long L, Manier M, Martinez-Cruzado J, Matos L, McClellan A, McNeil G, Merkhofer E, Mingo V, Mistry H, Mitchell E, Mortimer N, Mukhopadhyay D, Myka J, Nagengast A, Overvoorde P, Paetkau D, Paliulis L, Parrish S, Preuss M, Price J, Pullen N, Reinke C, Revie D, Robic S, Roecklein-Canfield J, Rubin M, Sadikot T, Sanford J, Santisteban M, Saville K, Schroeder S, Shaffer C, Sharif K, Sklensky D, Small C, Smith M, Smith S, Spokony R, Sreenivasan A, Stamm J, Sterne-Marr R, Teeter K, Thackeray J, Thompson J, Peters S, Van Stry M, Velazquez-Ulloa N, Wolfe C, Youngblom J, Yowler B, Zhou L, Brennan J, Buhler J, Leung W, Reed L, Elgin S. 2020. Facilitating growth through frustration: using genomics research in a course-based undergraduate research experience . J. Microbiol. Biol. Educ. 21(1): doi:10.1128/jmbe.v21i1.2005
/content/jmbe/10.1128/jmbe.v21i1.2005.f1-jmbe-21-6
FIGURE 1
The GEP mirror of the UCSC Genome Browser for (Sept 2008 GEP/dot assembly), with lines of evidence supporting the presence of a protein-coding gene in this region. The genome sequence is shown in the top line (Improved Sequence), with multiple lines of evidence supporting the presence of a gene mapped against that sequence. There are apparent contradictions in these evidence tracks. The BLASTx alignment track indicates that the region at 93000–12000 of shows significant similarity to protein sequences for two isoforms of the gene (Sequence Homology track). Computer-based gene predictors indicate a gene in this region (Gene Predictions tracks), but vary on the number, size, and location of predicted exons. RNA-Seq data appear to support the presence of three or four exons, yet TopHat and Cufflinks differ on the number and location of intron splice sites. The region from 7500 to 8000 might contain an exon of (predicted by N-SCAN), or it might be a separate gene (predicted by Genscan and SGP) as there is some RNA-Seq data, but little or no conservation is indicated in this region. Students must reconcile these differences to generate the best-supported gene models for this region of the genome.
jmbe/21/1/jmbe-21-6f1_thmb.gif
jmbe/21/1/jmbe-21-6f1.gif
Image of FIGURE 1

Click to view

FIGURE 1

The GEP mirror of the UCSC Genome Browser for (Sept 2008 GEP/dot assembly), with lines of evidence supporting the presence of a protein-coding gene in this region. The genome sequence is shown in the top line (Improved Sequence), with multiple lines of evidence supporting the presence of a gene mapped against that sequence. There are apparent contradictions in these evidence tracks. The BLASTx alignment track indicates that the region at 93000–12000 of shows significant similarity to protein sequences for two isoforms of the gene (Sequence Homology track). Computer-based gene predictors indicate a gene in this region (Gene Predictions tracks), but vary on the number, size, and location of predicted exons. RNA-Seq data appear to support the presence of three or four exons, yet TopHat and Cufflinks differ on the number and location of intron splice sites. The region from 7500 to 8000 might contain an exon of (predicted by N-SCAN), or it might be a separate gene (predicted by Genscan and SGP) as there is some RNA-Seq data, but little or no conservation is indicated in this region. Students must reconcile these differences to generate the best-supported gene models for this region of the genome.

Source: J. Microbiol. Biol. Educ. February 2020 vol. 21 no. 1 doi:10.1128/jmbe.v21i1.2005
Download as Powerpoint
/content/jmbe/10.1128/jmbe.v21i1.2005.f2-jmbe-21-6
FIGURE 2
Faculty observe that setbacks in the research process promote student learning. Results from analysis of comments from the Formative Failure faculty survey ( Appendix 2 ) on the effects on student learning from course setbacks (survey question 9.D: problems affecting all students in the class, =161) and student setbacks (survey question 10.D: problems encountered by individual students, =134). The percent of faculty responses that were positive (blue), negative (orange), or neutral (no effect; grey) are shown. GEP = Genomics Education Partnership.
jmbe/21/1/jmbe-21-6f2_thmb.gif
jmbe/21/1/jmbe-21-6f2.gif
Image of FIGURE 2

Click to view

FIGURE 2

Faculty observe that setbacks in the research process promote student learning. Results from analysis of comments from the Formative Failure faculty survey ( Appendix 2 ) on the effects on student learning from course setbacks (survey question 9.D: problems affecting all students in the class, =161) and student setbacks (survey question 10.D: problems encountered by individual students, =134). The percent of faculty responses that were positive (blue), negative (orange), or neutral (no effect; grey) are shown. GEP = Genomics Education Partnership.

Source: J. Microbiol. Biol. Educ. February 2020 vol. 21 no. 1 doi:10.1128/jmbe.v21i1.2005
Download as Powerpoint
/content/jmbe/10.1128/jmbe.v21i1.2005.f3-jmbe-21-6
FIGURE 3
Faculty are more likely to let their students risk failure in GEP research projects than in wet bench or field work lab courses and research projects. Faculty were asked how likely they were to let students fail in performance of wet bench lab work (coursework and research), field work (coursework or research), and GEP research activities. The degree of willingness to risk failure was evaluated as 1 (very likely) to 3 (not at all). Note that many GEP faculty members do not do field work, so the number of responses in that category is lower. (Percentages do not sum to 100%, as “not applicable” responses are not shown.) GEP = Genomics Education Partnership.
jmbe/21/1/jmbe-21-6f3_thmb.gif
jmbe/21/1/jmbe-21-6f3.gif
Image of FIGURE 3

Click to view

FIGURE 3

Faculty are more likely to let their students risk failure in GEP research projects than in wet bench or field work lab courses and research projects. Faculty were asked how likely they were to let students fail in performance of wet bench lab work (coursework and research), field work (coursework or research), and GEP research activities. The degree of willingness to risk failure was evaluated as 1 (very likely) to 3 (not at all). Note that many GEP faculty members do not do field work, so the number of responses in that category is lower. (Percentages do not sum to 100%, as “not applicable” responses are not shown.) GEP = Genomics Education Partnership.

Source: J. Microbiol. Biol. Educ. February 2020 vol. 21 no. 1 doi:10.1128/jmbe.v21i1.2005
Download as Powerpoint
/content/jmbe/10.1128/jmbe.v21i1.2005.f4-jmbe-21-6
FIGURE 4
Genomics-based CUREs can support an iterative learning process. A collaborative Learning Environment (1) supports the entire process, which includes a defined learning objective (2), a formative strategy (3), and iterative experimentation (4). Adapted with permission from ( 10 ).
jmbe/21/1/jmbe-21-6f4_thmb.gif
jmbe/21/1/jmbe-21-6f4.gif
Image of FIGURE 4

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FIGURE 4

Genomics-based CUREs can support an iterative learning process. A collaborative Learning Environment (1) supports the entire process, which includes a defined learning objective (2), a formative strategy (3), and iterative experimentation (4). Adapted with permission from ( 10 ).

Source: J. Microbiol. Biol. Educ. February 2020 vol. 21 no. 1 doi:10.1128/jmbe.v21i1.2005
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