Publications

A library of publications associated with AACR and Beyond Multiple Choice

2019

Conference Paper

Uhl JD, Sripathi KN, Santiago MM, et al. Automated analysis can guide instructor understanding of student writing about cellular respiration [Poster]. In: Spring Conference On Student Learning And Success. ; 2019.

Uhl JD, 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.

Uhl JD, Fleming MP, 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.

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.

Journal Article

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

2018

Journal Article

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.

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.

Conference Paper

Santiago MM, 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 MM, 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.

2017

Conference Paper

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.

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 GC, 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.

Williams CT, Nyutu EN, 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.

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

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

Sripathi KN, Steele M, Haudek KC, Merrill JE, Urban-Lurain M. Representing students constructed responses in STEM courses: Which visualizations appeal to various stakeholders? In: Gordon Research Conference On Visualization In Science And Education. ; 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.

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.

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.

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.

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.

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.

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

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.

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.

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, 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.

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.

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

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.

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.

Thesis

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.

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.

2016

Journal Article

Prevost LB, Smith MK, Knight JK. Using student writing and lexical analysis to reveal student thinking about the role of stop codons in the central dogma. CBE - Life Sciences Education. 2016;15:pii: ar65. doi:10.1187/cbe.15-12-0267.

Conference Paper

Ha M, Nehm RH. Predicting the Accuracy of Computer Scoring of Text: Probabilistic, Multi-Model, and Semantic Similarity Approaches. In: Narst. Baltimore, MD; 2016.

Stuhlsatz M, Wilson CD, Buck-Bracey Z, Urban-Lurain M, Merrill JE, Haudek KC. Applying Automated Analysis to Develop a Cost-Effective Measure of Science Teacher Pedagogical Content Knowledge. In: Narst. Baltimore, MD; 2016.