Publications

A library of publications associated with AACR and Beyond Multiple Choice

2019

Journal Article

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.

Conference Paper

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.

2018

Journal Article

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.

Conference Paper

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.

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.

2017

Conference Paper

Bala AM, Lira CT. A Cooperative Learning Exercise to Improve Student s Understanding of Internal Energy. In: ; 2017.

Sieke SA, Knight JK. Identifying and analyzing student misconceptions about the effects of a non-coding mutation. In: Society for the Advacement of Biology Education Research. ; 2017.

Foster T, Haudek KC, Moscarella RA, Yoho R, Urban-Lurain M, Merrill JE. Computerized scoring of student open response questions: A case study of enzyme structure and function [Poster]. In: National Meeting for the Society for the Advancement of Biology Education Research (SABER). Minneapolis, MN; 2017.

Macneill B, Romero M, Hoskinson A-M, Prevost LB. Follow that carbon atom! Using machine learning to trace student understanding of the carbon cycle. In: Ecological Society of America 102nd Annual Meeting. ; 2017.

Lemons PP. Solving Educational Problems: Opportunities and Challenges in Innovative Teaching. In: Innovative Teaching and Experiential Learning Symposium, Augusta University. ; 2017.

Sripathi KN, Knapp J, Moscarella RA, Haudek KC, Urban-Lurain M, Merrill JE. Developing a Constructed Response Question Targeting Student Understanding of Phospholipid Properties within a Cell Membrane. In: Society for the Advacement of Biology Education Research. ; 2017.

Foster T, Haudek KC, Moscarella RA, Yoho R, Urban-Lurain M, Merrill JE. Computerized scoring of open response questions: A case study of enzyme structure and function [Poster]. In: University Undergraduate Research and Arts Forum (UURAF). Michigan State University; 2017.

Lyford A. Providing Real-time Instructor Feedback about Undergraduate Learning in Statistics through Machine Learning Algorithms. In: U.S. Conference on Teaching Statistics. State College, PA; 2017. https://www.causeweb.org/cause/uscots/uscots17/posters/1-20.

Knapp J, Sripathi KN, Haudek KC, Urban-Lurain M, Merrill JE. Prevalent Student Conceptions Involving Structure-Function Relationships in Cell Membranes [Poster]. In: Mid-Michigan Symposium for Undergraduate Research Experiences. ; 2017.

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.

Journal Article

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.

Book Chapter

Rachmatullah A, Ha M, Roshayanti F, Nehm RH. Evolution Education in Indonesia: Pre-service Biology Teachers Evolutionary Knowledge Levels, Reasoning Models, and Acceptance Patterns. In: Deniz H, Borgerding L, eds. Evolution Education Around the Globe. Springer; 2017.