Publications

A library of publications associated with AACR and Beyond Multiple Choice

2017

Conference Paper

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.

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. Enzyme Structure and Function: Comparing Student Responses to Multiple Question Versions [Poster]. In: Create For Stem Mini Conference. ; 2017.

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.

Ha M, Nehm RH. The Impact of Misspelled Words on Automated Computer Scoring: A Case Study of Scientific Explanations. Journal of Science Education and Technology. 2016;25:358–374. https://link.springer.com/article/10.1007/s10956-015-9598-9.

Federer MR, Nehm RH, Pearl D. Examining Gender Differences in Written Assessment Tasks in Biology: A Case Study of Evolutionary Explanations. CBE—Life Sciences Education. 2016;15(Spring). https://www.lifescied.org/doi/pdf/10.1187/cbe.14-01-0018.

Conference Paper

Moscarella RA, Haudek KC, Knight JK, et al. Automated Analysis Provides Insights into Students' Challenges Understanding the Processes Underlying the Flow of Genetic Information. In: Narst. Baltimore, MD; 2016.

Lemons PP, McCourt J, Knight JK, et al. A community of enhanced assessment facilitates reformed teaching. In: American Association For The Advancement Of Science. Washington, DC; 2016. http://www.enfusestem.org/projects/a-community-of-enhanced-assessment-facilitates-reformed-teaching/.

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.

Steele M, Merrill JE, Haudek KC, Urban-Lurain M. The Development of Constructed Response Astronomy Assessment Items. In: Narst. Baltimore, MD; 2016. http://matthewmsteele.github.io/NARST2016/.

Urban-Lurain M, Bierema AM-K, Haudek KC, et al. Expanding a National Network for Automated Analysis of Constructed Response Assessments to Reveal Student Thinking in STEM. In: American Association For The Advancement Of Science. Washington, DC: American Association for the Advancement of Science; 2016. http://www.enfusestem.org/projects/collaborative-research-expanding-a-national-network-for-automated-analysis-of-constructed-response-assessments-to-reveal-student-thinking-in-stem-5/.

Moscarella RA, Haudek KC, Knight JK, et al. Automated Analysis of Written Assessments in STEM: Methodological Issues. In: Narst. Baltimore, MD; 2016.

Prevost LB, Bierema AM-K, Kaplan JJ, et al. An iterative approach to developing, refining and validating machine-scored constructed response assessments. In: American Association For The Advancement Of Science. Washington, DC; 2016. http://www.enfusestem.org/projects/an-iterative-approach-to-developing-refining-and-validating-machine-scored-constructed-response-assessments/.

Smith MK. Transforming the Classroom and Helping Others to Adopt Teaching Innovations. In: Australian Physiological Society. ; 2016.

Bierema AM-K, Moscarella RA, Urban-Lurain M, Merrill JE, Haudek KC. The Importance of Random Assortment and Blinding in Qualitative Data Analysis. In: Narst. Baltimore, MD; 2016.

Lyford A. Investigating Undergraduate Student Understanding of Graphical Displays of Data through Supervised Learning Algorithms [Poster]. In: Seer Center Inaugural Reception & Poster Session. ; 2016.

Lira CT, Steele M, Haudek KC, Merrill JE, Urban-Lurain M. Rapid Analysis of Written Responses to Reveal Student Misconceptions in Thermodynamics. In: Annual Meeting Of The Aiche. ; 2016.

Miscellaneous

Pelletreau KN, Andrews TC, Armstrong N, et al. A clicker-based case study that untangles student thinking about the processes in the central dogma. CourseSource. 2016;3:1-11. doi:https://doi.org/10.24918/cs.2016.15.

2015

Conference Paper

Ha M, Nehm RH. Assessment item "Cover Stories", semantic similarity and successful computerized scoring of open-ended text. In: Narst. ; 2015.

Park M, Haudek KC, Urban-Lurain M. Computerized lexical analysis of students' written responses for diagnosing conceptual understanding of energy. In: Narst. ; 2015.

Chen J, Ha M, Nehm RH. Measuring semantic similarity in written text: Applications to learning and assessment. In: Narst. ; 2015.

Ha M, Nehm RH. Exploring students' evolutionary explanations across natural, sexual, and artificial selection secenarios. In: Narst. ; 2015.

Steele M, Haudek KC, Merrill JE, Moscarella RA, Park M, Urban-Lurain M. Automated Reporting of the Lexical and Statistical Analysis of Student Constructed Responses. In: Create For Stem Mini-Conference. ; 2015.

Moscarella RA, Stoltzfus JR, Merrill JE, Haudek KC, Urban-Lurain M. Creation of scoring rubrics assisted by Computerized Text Analysis. In: Create For Stem Mini Conference. East Lansing, MI; 2015.

Park M, Urban-Lurain M, Haudek KC. A Promising Approach to Examining Student Energy Conceptions. In: Create For Stem Mini Conference. ; 2015.

Mazur A, Moscarella RA, Merrill JE, Urban-Lurain M. Biology Central Dogma: What are the Student Learning Challenges? In: University Undergraduate Research And Arts Forum. Michigan State University; 2015.

Urban-Lurain M, Merrill JE, Haudek KC, et al. Automated analysis of constructed responses: What are we modeling? In: Society For The Advancement Of Biology Education Research. ; 2015.

Crumbs T, McCourt J, Lemons PP. Analysis of Teachers' Thinking about Pedagogical Practices in College Biology Courses [Poster]. In: University Of Georgia Research Experiences For Undergraduates Poster Session. Georgia, USA; 2015.

Moscarella RA, Park M, Steele M, et al. Insights into Students Thinking about the Central Dogma from the Automated Analysis of Constructed Response Questions. In: Saber. ; 2015.

Mazur A, Moscarella RA, Urban-Lurain M, Merrill JE. Student writing reveals misconceptions in the Central Dogma of Biology. In: The Mid-Michigan Symposium For Undergraduate Research Experiences. ; 2015.

Carter K, Prevost LB. Assessing student understanding of core principle structure and function. In: Saber. Minneapolis, MN; 2015.

Steele M, Park M, Urban-Lurain M. AACR: Automated Analysis of Constructed Response Physics and Astronomy Questions. In: American Association Of Physics Teachers Summer Meeting. ; 2015.

Smith MK. Moving Beyond First-Generation Biology Education Research: Using Faculty Learning Communities to Enhance Student-Centered Instruction. In: Gordon Research Conference On Undergraduate Biology Education Research. ; 2015.

Prevost LB. Assessing student ecological understanding using text analysis and machine learning. In: The Ecological Society Of America Annual Meeting. ; 2015.

Merrill JE, Haudek KC, Smith MK, et al. Faculty Learning Communities as a Focus for Assessment-Driven Instructional Change. In: Create For Stem Mini Conference. East Lansing, MI; 2015.

Steele M, Park M, Urban-Lurain M. AACR: Probing Student Thinking with Computer Analyzed Constructed Response Questions. In: American Association Of Physics Teachers Summer Meeting. ; 2015.

Pelletreau KN, Knight JK, Lemons PP, et al. Using student constructed responses to guide the development of instructional activities by cross- institutional faculty learning communities. In: Gordon Research Conference On Undergraduate Biology Education Research. ; 2015.

McCourt J, Andrews TC, Crumbs T, et al. Using faculty learning communities to promote the development of student-centered biology instructors. In: Saber. ; 2015.

Ha M, Nehm RH. Exploring the use of machine translation and machine grading of open-ended assessments in international comparison studies. In: European Science Education Research Association Meeting. ; 2015.

Romero M, Carter K, Prevost LB. Assessing writing about matter and energy: Comparing text analysis and machine learning. In: Society For Advancement Of Biology Education Research. ; 2015.

Moscarella RA, Mazur A, Pelletreau KN, Smith MK, Urban-Lurain M, Merrill JE. The Central Dogma of molecular biology: Investigating student challenges understanding transcription. In: Saber. ; 2015.

Prevost LB. Assessing student biological understanding using text analysis and machine learning. In: Gordon Research Conference On Undergraduate Biology Education Research. ; 2015.

Haudek KC, Moscarella RA, Weston MM, Merrill JE, Urban-Lurain M. Construction of rubrics to evaluate content in students' scientific explanation using computerized text analysis. In: Narst. ; 2015.

Thesis

Williams LC. Students' understanding of structure-property relationships and the role of intermolecular forces. Chemistry. 2015;Doctor of Philosophy.

Journal Article

Ha M, Baldwin B, Nehm RH. The Long-Term Impacts of Short-Term Professional Development: Science Teachers and Evolution. Evo Edu Outreach. 2015;8(11). doi:10.1186/s12052-015-0040-9.

Urban-Lurain M, Cooper M, Haudek KC, et al. Expanding a national network for automated analysis of constructed response assessments to reveal student thinking in STEM. Computers in Education Journal. 2015;6(1):65-81.

Weston MM, Haudek KC, Prevost LB, Urban-Lurain M, Merrill JE. Examining the Impact of Question Surface Features on Students’ Answers to Constructed-Response Questions on Photosynthesis. CBE—Life Sciences Education. 2015;14(2). doi:doi:10.1187/cbe.14-07-0110.

2014

Journal Article

Federer MR, Nehm RH, Opfer JE, Pearl D. Using a Constructed-Response Instrument to Explore the Effects of Item Position and Item Features on the Assessment of Students Written Scientific Explanations. Research in Science Education. 2014. doi:10.1007/s11165-014-9435-9.

Conference Paper

Ha M, Ponnuraj GT, Nehm RH. EvoGrader: An Online Formative Assessment Tool for Automatically Analyzing Students Ideas in Written Evolutionary Explanations. In: Saber. ; 2014.