Publications

Uhl J, Sripathi KN, Saldanha J, Moscarella RA, Haudek KC. Exploring student thinking about genetics information flow in large enrollment undergraduate classes [Presentation]. In: PKAL-Ohio. Dayton, OH; 2019.

Jescovitch LN, Doherty JH, Scott EE, et al. Challenges in Developing Computerized Scoring Models for Principle-Based Reasoning in a Physiology Context. In: NARST. Baltimore, MD; 2019.

Jescovitch LN, Doherty JH, Scott EE, et al. Comparison of analytic and holistic coding approaches and machine learning performances across a flux learning progression. In: Society for the Advancement of Biology Education Research . Minneapolis, MN; 2019.

Saldanha J, Shiroda M, Merrill JE, Urban-Lurain M, Haudek KC. Automated Analyses of Constructed Response (AACR) questions in STEM courses provide insights into student thinking [Poster]. In: CREATE for STEM Mini-Conference. ; 2019.

Uhl J, Fleming M, Merrill JE, Haudek KC. Development of a constructed response automated assessment question to elicit student thinking about epigenetics [Roundtable discussion]. In: National Meeting for the Society for the Advancement of Biology Education Research. Minneapolis, MN; 2019.

You HS, Merrill JE, Haudek KC, Urban-Lurain M. Rasch validation of computer scored constructed response items in undergraduate introductory biology courses. In: NARST. Baltimore, MD; 2019.

Roland K, Kaplan JJ. P-values mean what? Conceptions students are demonstrating on open-ended responses [Poster]. In: U.S. Conference on Teaching Statistics. Penn State University; 2019.

Shiroda M, Uhl J, Saldanha J, Sripathi KN, Merrill JE, Haudek KC. Student use of Vision and Change core concepts during discussions to answer conceptual questions in small group interview [Poster]. In: Gordon Research Conference. Lewiston, ME; 2019.

Shiroda M, Merrill JE, Koslowsky D, Haudek KC. Application of automated analysis of constructed responses in large enrollment undergraduate classrooms [Presentation]. In: Gordon Research Conference. Lewiston, ME; 2019.

Sbeglia G, Nehm RH. Student reasoning about matter and energy transformation across contexts: Psychometric evaluation of cognitive coherence using Rasch analysis. In: Society for the Advancement of Biology Education Research. Minneapolis, MN; 2019.

Cheuk T, Osborne J, Remington-Cunningham K, et al. Towards an Equitable Design Framework of Developing Argumentation in Science Items and Rubrics for Machine Learning. In: NARST. ; 2019.

Roland K, Kaplan JJ. Students’ understanding of definitional and relational characteristics of confidence intervals: Initial results [Poster]. In: Joint Statistical Meetings. Denver, CO; 2019.

Shiroda M, Uhl J, Saldanha J, Sripathi KN, Merrill JE, Haudek KC. Student use of Vision and Change core concepts during discussions to answer conceptual questions in small group interview [Poster]. In: CREATE for STEM Mini-Conference. East Lansing, MI; 2019.

Sieke SA, Knight JK. Student misconceptions regarding mutations in non-coding regions. In: Society for the Advancement of Biology Education Research. Minneapolis, MN; 2019.

Saldanha J, Shiroda M, Merrill JE, Urban-Lurain M, Haudek KC. Automated Analyses of Constructed Response (AACR) questions in STEM courses provide insights into student thinking [Poster]. In: Spring Conference on Student Learning and Success. ; 2019.

Uhl J, Sripathi KN, Santiago M, et al. Automated analysis can guide instructor understanding of student writing about cellular respiration [Poster]. In: CREATE for STEM Mini-Conference. ; 2019.

Fleming M, Uhl J, Haudek KC. Development of constructed response items to elicit student thinking about ecology and use with automated assessment. In: Society for the Advancement of Biology Education Research. Minneapolis, MN; 2019. https://saberbio.wildapricot.org/resources/Documents/SAB\%20ER\%202019\%20Round\%20table\%20abstracts.2.pdf.

Nehm RH, Mead L. Evolution assessment: Introduction to the special issue. Evolution: Education and Outreach. 2019;12:7. doi:10.1186/s12052-019-0098-x.

Ha M, Wei X, Wang J, Hou D, Nehm RH. Chinese pre-service biology teachers evolutionary knowledge, reasoning patterns, and acceptance levels. International Journal of Science Education. 2019;41:628–651. doi:10.1080/09500693.2019.1572936.

Sbeglia G, Nehm RH. Do you see what I-SEA? A Rasch analysis of the psychometric properties of the Inventory of Student Evolution Acceptance. Science Education. 2019;103:287–316. doi:10.1002/sce.21494.

Sieke SA, McIntosh BB, Steele M, Knight JK. Characterizing students ideas about the effects of a mutation in a noncoding region of DNA. CBE - Life Sciences Education. 2019;18:ar18. doi:10.1187/cbe.18-09-0173.

McCourt J, Andrews TC, Knight JK, et al. What Motivates Biology Instructors to Engage and Persist in Teaching Professional Development? CBE—Life Sciences Education. 2018;16(3). doi:10.1187/cbe.16-08-0241.

Yoho R, Urban-Lurain M, Merrill JE, Haudek KC. Structure and function relationships in the educational expectations. Journal of College Science Teaching. 2018;47(6). https://my.nsta.org/resource/?id=10.2505/4/jcst18_047_06_24.

Pelletreau KN, Knight JK, Lemons PP, et al. A Faculty Professional Development Model That Improves Student Learning, Encourages Active-Learning Instructional Practices, and Works for Faculty at Multiple Institutions. CBE—Life Sciences Education. 2018;17:es5. doi:10.1187/cbe.17-12-0260.

Jescovitch LN, Haudek KC, Steele M, et al. Predicting mental models of undergraduate thinking in STEM courses using computerized analysis [Poster]. In: STEM Alliance. Michigan State University; 2018.

Sripathi KN, Cockerill H, Knapp J, Urban-Lurain M, Haudek KC, Merrill JE. Probing students’ mental models about structure-function relationships in the cell membrane. In: Conference at the Interface of Discipline-Based Education Research (DBER) in STEM and Psychological Science. St. Louis, MO; 2018.

Santiago M, Kaplan JJ, Prevost LB, Steele M, Haudek KC, Urban-Lurain M. Visualizing students’ conceptual understanding in STEM: Faculty perspectives and a live web app demo. In: AAC&U 2018 Transforming STEM Higher Education. Atlanta, GA; 2018.

Haudek KC. Revealing student thinking using automated analysis of constructed response items. In: Conference at the Interface of Discipline-Based Education Research (DBER) in STEM and Psychological Science. St. Louis, MO; 2018.

Haudek KC, Sripathi KN, Jescovitch LN, et al. Rubrics for student writing: Research tools to uncover trends in student thinking [Poster]. In: STEM Alliance. Michigan State University; 2018.

Santiago M, Steele M, Sripathi KN, et al. Web-based system to support instructors’ understanding of student thinking on key STEM concepts [Poster]. In: STEM Alliance. Michigan State University; 2018.

Lyford A. Investigating Undergraduate Student Understanding of Graphical Displays of Quantitative Data through Machine Learning Algorithms. 2017;Doctor of Philosophy. https://iase-web.org/documents/dissertations/17.AlexanderLyford.Dissertation.pdf.

Lira CT, Steele M, Haudek KC, Merrill JE, Urban-Lurain M. Student Misconceptions of Molecular Energy Evaluated Using Rapid Analysis of Constructed Responses. In: Midwest Thermodynamics and Statistical Mechanics. ; 2017.

Cockerill H, Bierema AM-K, Moscarella RA, Haudek KC, Urban-Lurain M, Merrill JE. Exploring Students Ideas of the Origin of Genetic Variation [Poster]. In: CREATE for STEM Mini-Conference. East Lansing, MI; 2017.

Smith MK. Using Evidence to Transform Undergraduate Teaching. In: Teaching As Research National Conference. ; 2017.

Moscarella RA, Mazur A, Haudek KC, Urban-Lurain M, Merrill JE. A student reasoning framework describing the role of a mRNA in the transcription of DNA. In: Gordon Research Conference on Undergraduate Biology Education Research. ; 2017.

Lyford A. Leveraging Ensembles of Machine Learning Algorithms to Provide Real-Time Instructor Feedback. In: Joint Statistical Meetings. ; 2017.

Cockerill H, Bierema AM-K, Moscarella RA, Sripathi KN, Yoho R, Haudek KC. Qualitative Analysis of Undergraduate Students’ Writing of the Origin of Genetic Variation [Poster]. In: Mid-Michigan Symposium for Undergraduate Research Experiences. ; 2017.

Wang X, Colton J, Sbeglia G, Finch S, Nehm RH. Longitudinal Learning Dynamics and the Conceptual Restructuring of Evolutionary Understanding. In: NARST. ; 2017.

Yoho R, Foster T, Haudek KC, Urban-Lurain M, Merrill JE. Using Machine Learning to Explore Student Thinking in Constructed Responses – An Example of Enzyme Binding Structure and Function. In: American Society for Microbiology Conference on Undergraduate Education. ; 2017.

Williams C, Nyutu E, Moscarella RA, Sydlik M, Urban-Lurain M. A method for analyzing and visualizing project teamwork [Poster]. In: Michigan Academy of Science, Arts & Letters Conference. ; 2017.

Moscarella RA, Hall D, Haudek KC, et al. Exploring students ideas about the flow of genetic information from DNA to RNA. In: Society for the Advancement of Biology Education Research. ; 2017.

You HS, Sripathi KN, Yoho R, et al. Towards meaningful scores: Development and validation of analytic rubrics for diagnostic purposes. In: Society for the Advacement of Biology Education Research. ; 2017.

Cockerill H, Bierema AM-K, Moscarella RA, Haudek KC, Urban-Lurain M, Merrill JE. Undergraduate students’ understanding of the origin of genetic variation: insights from the automated analysis of constructed responses. In: University Undergraduate Research and Arts Forum. ; 2017.

Carter K, Prevost LB. Investigating text analysis models for assessing student understanding of structure and function. In: Transforming Research in Undergraduate STEM Education (TRUSE). ; 2017.

Tornabene R, Nehm RH, Schmiemann P. Testing the Impact of Situational Features on Measures of Biology Students Genetics Understanding. In: NARST. ; 2017.

Sbeglia G, Nehm RH. Does evolution acceptance differ across biological scales? A Rasch analysis of the Inventory of Student Evolution Acceptance (I-SEA). In: Society for the Advacement of Biology Education Research. ; 2017.

Lyford A. Understanding Undergraduate Learning in Statistics through Machine Learning Algorithms. In: Mathematics Association of America Southeastern Section 96th Annual Meeting. Mercer University; 2017.

Foster T, Haudek KC, Moscarella RA, Yoho R, Urban-Lurain M, Merrill JE. Enzyme Structure and Function: Comparing Student Responses to Multiple Question Versions [Poster]. In: CREATE for STEM Mini Conference. ; 2017.

Kaplan JJ, Froelich A, Lyford A. Using Formative Assessment to Improve Student Learning in Large Enrollment Classes. In: U.S. Conference on Teaching Statistics. ; 2017.

Schmiemann P, Nehm RH, Tornabene R. Assessment of Genetics Understanding: Under What Conditions Do Situational Features Have an Impact on Measures? Science & Education. 2017;26:1161–1191. doi:10.1007/s11191-017-9925-z.