Ross Nehm

SUNY: Stony Brook University, Ecology and Evolution, Faculty Member

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The Nehm Lab studies science learning, with a focus on biological concepts such as natural selection and evolution. We explore novice and expert reasoning strategies, the psychometric evaluation of measurement instruments, science teacher learning and belief revision, the conceptual restructuring of folk-biological knowledge, and the comparative efficacy of educational innovations. Recently, the lab has collaborated with computer scientists to build machine-learning models for the automated analysis of complex scientific practices (such as evolutionary explanations). The lab has been supported by the National Science Foundation's EAR, CCLI, TUES, CAREER and REESE programs. Dr. Nehm is associate director of the Ph.D. Program in Science Education at Stony Brook. Dr. Nehm's major awards include a CAREER award from the National Science Foundation, a teaching award from Berkeley, and a mentoring award from CUNY. In 2013-14 Dr. Nehm was named an Education Mentor in the Life Sciences by the U.S. National Academies. Dr. Nehm currently serves as Editor-in Chief of the journal Evolution Education and Outreach and board member of multiple academic journals and book series.
Phone: 631-632-7247
Address: Stony Brook University (SUNY)
Center for Science and Math Education &
Department of Ecology & Evolution
650 Life Sciences Building
Stony Brook, NY 11794-5233

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Judith L Green

University of California, Santa Barbara

Dan Davies

Bath Spa University

E. Wayne Ross

University of British Columbia

Daniel Cassany

Pompeu Fabra University

David Seamon

Kansas State University

Armando Marques-Guedes

UNL - New University of Lisbon

Jon R Sayers

The University of Sheffield

Ebru Mugaloglu

Bogazici University

Brian J. Reiser

Northwestern University

Monica F Cox

The Ohio State University

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Papers by Ross Nehm

Are Faculty Changing? How Reform Frameworks, Sampling Intensities, and Instrument Measures Impact Inferences about Student-Centered Teaching Practices

CBE- Life Sciences Education, Sep 1, 2021

Although recent studies have used the Classroom Observation Protocol for Undergraduate STEM (COPU... more Although recent studies have used the Classroom Observation Protocol for Undergraduate STEM (COPUS) to make claims about faculty reform, important questions remain: How should COPUS measures be situated within existing reform frameworks? Is there a universal sampling intensity that allows for valid inferences about the frequency of student-centered instruction within a semester or across semesters of a course? These questions were addressed using longitudinal COPUS observations (128 classes, three faculty, 4 years). CO-PUS behaviors were used to categorize classes into didactic, interactive lecture, or student-centered instructional styles. Sampling intensities (one to 11 classes) were simulated (1000 times) within a course and across semesters. The sampling intensities required for generating valid inferences about 1) the presence of student-centered instruction and 2) the proportion of instructional styles in a course and through time were calculated. Results indicated that the sampling intensity needed to characterize courses and instructors varied and was much higher than previously recommended for instructors with: 1) rare instances of student-centered classes, 2) variability in instructional style, and 3) longitudinal changes in instructional patterns. These conditions are common in early reform contexts. This study highlights the risks of broad, decontextualized sampling protocol recommendations and illustrates how reform frameworks, sampling intensities, and COPUS measures interact to impact inferences about faculty change.

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Illuminating the complexities of conflict with evolution: validation of the scales of evolutionary conflict measure (SECM)

Evolution: Education and Outreach, Nov 23, 2020

Background: Although personal, familial, and community conflict with evolution have been document... more Background: Although personal, familial, and community conflict with evolution have been documented in the literature, these scales require conceptualization as a construct and operationalization as a measure. The Scales of Conflict with Evolution Measure (SECM) instrument was developed in response to these needs. Using a construct validity framework, the content, internal structure, convergent, and substantive validity of the SECM were evaluated using Rasch analysis, Structural Equation Modeling (SEM), and follow up questioning. The conceptual utility of the instrument was explored by examining whether it added explanatory insights into evolution acceptance above and beyond religiosity, evolution knowledge, and background variables. Results: A literature review and expert consultation indicated that construct of evolutionary conflict perception should (i) encompass the hierarchical nature of human social structures (personal, family, community) and (ii) probe conflict as it relates to human values, cultures, and beliefs. A three-dimensional construct was operationalized as a nine-item rating scale measure. Using Rasch analyses of SECM responses from a diverse sample of > 1000 students studying evolution, the instrument met criteria of robust measurement, including: fit to model expectations; threedimensional structure; high reliability; good rating scale function; measurement invariance with time; and convergence with a similar construct. SEM showed that: (i) family and community conflict had unique causal contributions to personal conflict, with family showing a stronger and modest impact, and (ii) personal conflict had a significant and modest causal impact on evolution acceptance above and beyond the contributions of religiosity, evolution knowledge, and background variables. Conclusion: The SECM is an easy-to-administer instrument to measure conflict with evolution and is supported by several forms of validity evidence. The SECM has potential for facilitating measurement of evolutionary conflict in educational settings, thereby raising instructor awareness of conflict levels in students, promoting rigorous evaluations of educational interventions designed to reduce conflict, and fostering conceptual advances in the field of evolution education. Future work is needed to gather additional forms of validity evidence and to test current validity claims in additional participant samples. SECM measures should also be incorporated into more complex SEM models that treat evolution knowledge and religiosity as part of the structural paths to evolution acceptance. Such models could provide insights into the most worthwhile targets for the development of educational interventions to mitigate conflict at multiple scales.

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An application of Bayesian inference to examine student retention and attrition in the STEM classroom

Frontiers in Education, Feb 14, 2023

Introduction: As artificial intelligence (AI) technology becomes more widespread in the classroom... more Introduction: As artificial intelligence (AI) technology becomes more widespread in the classroom environment, educators have relied on data-driven machine learning (ML) techniques and statistical frameworks to derive insights into student performance patterns. Bayesian methodologies have emerged as a more intuitive approach to frequentist methods of inference since they link prior assumptions and data together to provide a quantitative distribution of final model parameter estimates. Despite their alignment with four recent ML assessment criteria developed in the educational literature, Bayesian methodologies have received considerably less attention by academic stakeholders prompting the need to empirically discern how these techniques can be used to provide actionable insights into student performance. Methods: To identify the factors most indicative of student retention and attrition, we apply a Bayesian framework to comparatively examine the differential impact that the amalgamation of traditional and AI-driven predictors has on student performance in an undergraduate in-person science, technology, engineering, and mathematics (STEM) course. Results: Interaction with the course learning management system (LMS) and performance on diagnostic concept inventory (CI) assessments provided the greatest insights into final course performance. Establishing informative prior values using historical classroom data did not always appreciably enhance model fit. Discussion: We discuss how Bayesian methodologies are a more pragmatic and interpretable way of assessing student performance and are a promising tool for use in science education research and assessment.

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Enhancing data pipelines for forecasting student performance: integrating feature selection with cross-validation

International journal of educational technology in higher education, Aug 17, 2021

Educational data mining (EDM) focuses on developing mathematical frameworks for analyzing large e... more

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How strongly does statistical reasoning influence knowledge and acceptance of evolution?

Journal of Research in Science Teaching, Mar 18, 2019

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Do you see what I‐SEA? A Rasch analysis of the psychometric properties of the Inventory of Student Evolution Acceptance

Science Education, Jan 23, 2019

Theoretical perspectives and empirical research suggest that acceptance of evolution may be conti... more Theoretical perspectives and empirical research suggest that acceptance of evolution may be contingent upon what is evolving (e.g., plants vs. humans) and the scale of change (microevolution vs. macroevolution). The Inventory of Student Evolution Acceptance (I-SEA) is the only instrument designed to measure acceptance at different evolutionary scales and in different evolutionary contexts. Nevertheless, current validity testing for this instrument remains limited and grounded in Classical Test Theory. In this study, we examine patterns of evolution acceptance using the I-SEA instrument in a large sample of undergraduates (n > 2,000 participants) from six semesters of an evolution-focused biology class. We examine three research questions: (RQ1) Does Rasch analysis support the psychometric properties of the I-SEA discussed by Nadelson and Southerland? (RQ2) How variable are I-SEA measures across semesters, and are they sensitive to evolution instruction? (RQ3) Are I-SEA measures comparable to evolution acceptance measures produced by the Generalized Acceptance of EvolutioN Evaluation? Our empirical results support theoretical claims that evolution acceptance does not appear to be a unidimensional construct among novice learners. We identify limitations of the I-SEA and recommend multiple modifications to improve instrument quality.

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Measuring evolution learning: impacts of student participation incentives and test timing

Evolution: Education and Outreach, Jun 20, 2022

Background: Policy documents like Vision and Change and the Next Generation Science Standards emp... more Background: Policy documents like Vision and Change and the Next Generation Science Standards emphasize the importance of using constructed-response assessments to measure student learning, but little work has examined the extent to which administration conditions (e.g., participation incentives, end-of-course timing) bias inferences about learning using such instruments. This study investigates potential biases in the measurement of evolution understanding (one time point) and learning (pre-post) using a constructed-response instrument. The constructed-response ACORNS instrument (Assessment of COntextual Reasoning about Natural Selection) was administered at the beginning of the semester, during the final exam, and at end of the semester to large samples of North American undergraduates (N = 488-1379, 68-96% participation rate). Three ACORNS scores were studied: number of evolutionary core concepts (CC), presence of evolutionary misconceptions (MIS), and presence of normative scientific reasoning across contexts (MODC). Hierarchical logistic and linear models (HLMs) were used to study the impact of participation incentives (regular credit vs. extra credit) and end-of-course timing (final exam vs. post-test) on inferences about evolution understanding (single time point) and learning (pre-post) derived from the three ACORNS scores. The analyses also explored whether results were generalizable across race/ethnicity and gender. Results: Variation in participation incentives and end-of-course ACORNS administration timing did not meaningfully impact inferences about evolution understanding (i.e., interpretations of CC, MIS, and MODC magnitudes at a single time point); all comparisons were either insignificant or, if significant, considered to be small effect sizes. Furthermore, participation incentives and end-of-course timing did not meaningfully impact inferences about evolution learning (i.e., interpretations of CC, MIS, and MODC changes through time). These findings were consistent across race/ethnicity and gender groups. Inferences about evolution understanding and learning derived from ACORNS scores were in most cases robust to variations in participation incentives and end-of-course timing, suggesting that educators may have some flexibility in terms of when and how they deploy the ACORNS instrument.

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A Lesson on Matter and Energy at the Organismal Scale: Linking Patterns and Processes Across Diverse Taxa

CourseSource, 2020

Pathways and transformations of energy and matter (PTEM) are a conceptually challenging but essen... more Pathways and transformations of energy and matter (PTEM) are a conceptually challenging but essential component of biological literacy. Curricular gaps about PTEM nevertheless remain; although lessons targeting PTEM at small scales (chemical, molecular, cellular) and large scales (ecological, global) are most common, they do not necessarily address understanding of the intervening organismal scale. Moreover, at the organismal scale, student reasoning about PTEM in one taxonomic category (e.g., animal growth) does not necessarily transfer to others (e.g., fungal growth). Building on prior studies, we developed five organismal-scale activities about animals, plants, and fungi that address misconceptions, promote active learning, and require minimal background knowledge of chemistry. These activities are best suited for large (>200) activelearning courses for non-majors or majors with heterogeneous science concept mastery. The lessons involve answering 17 clicker questions, making predictions, building explanatory models, and correcting common misconceptions. The activities include: (i) introducing matter and energy, (ii) understanding what is (and is not) food, (iii) predicting change in mass across the tree of life, (iv) explaining changes in matter and energy using conceptual models, and (v) correcting misconceptions about matter and energy. Pre-post assessments produced significant (p <.01) and meaningful (Cohen's d =-1.8) learning gains, as well as widespread improvement (98% of 449 students). Instructors may choose to use the five activities in isolation or together, or independently make use of the clicker question set. For more advanced students, the activities may be used as pre-course assignments in preparation for more complex learning tasks.

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Is Active Learning Enough? The Contributions of Misconception-Focused Instruction and Active-Learning Dosage on Student Learning of Evolution

BioScience, Sep 7, 2022

AI and formative assessment: The train has left the station

Journal of Research in Science Teaching

In response to Li, Reigh, He, and Miller's commentary, Can we and should we use artificial in... more In response to Li, Reigh, He, and Miller's commentary, Can we and should we use artificial intelligence for formative assessment in science, we argue that artificial intelligence (AI) is already being widely employed in formative assessment across various educational contexts. While agreeing with Li et al.'s call for further studies on equity issues related to AI, we emphasize the need for science educators to adapt to the AI revolution that has outpaced the research community. We challenge the somewhat restrictive view of formative assessment presented by Li et al., highlighting the significant contributions of AI in providing formative feedback to students, assisting teachers in assessment practices, and aiding in instructional decisions. We contend that AI‐generated scores should not be equated with the entirety of formative assessment practice; no single assessment tool can capture all aspects of student thinking and backgrounds. We address concerns raised by Li et al. r...

Quantifying variability in predictions of student performance: Examining the impact of bootstrap resampling in data pipelines

Computers and Education: Artificial Intelligence

A Meta-Analysis of Machine Learning-Based Science Assessments: Factors Impacting Machine-Human Score Agreements

Journal of Science Education and Technology, 2020

Machine learning (ML) has been increasingly employed in science assessment to facilitate automati... more Machine learning (ML) has been increasingly employed in science assessment to facilitate automatic scoring efforts, although with varying degrees of success (i.e., magnitudes of machine-human score agreements [MHAs]). Little work has empirically examined the factors that impact MHA disparities in this growing field, thus constraining the improvement of machine scoring capacity and its wide applications in science education. We performed a meta-analysis of 110 studies of MHAs in order to identify the factors most strongly contributing to scoring success (i.e., high Cohen's kappa [κ]). We empirically examined six factors proposed as contributors to MHA magnitudes: algorithm, subject domain, assessment format, construct, school level, and machine supervision type. Our analyses of 110 MHAs revealed substantial heterogeneity in (mean = .64; range = .09-.97 , taking weights into consideration). Using three-level random-effects modeling, MHA score heterogeneity was explained by the variability both within publications (i.e., the assessment task level: 82.6%) and between publications (i.e., the individual study level: 16.7%). Our results also suggest that all six factors have significant moderator effects on scoring success magnitudes. Among these, algorithm and subject domain had significantly larger effects than the other factors, suggesting that technical features and assessment external features might be primary targets for improving MHAs and ML-based science assessments.

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Assessment of Genetics Understanding

Science & Education, 2017

Understanding how situational features of assessment tasks impact reasoning is important for many... more Understanding how situational features of assessment tasks impact reasoning is important for many educational pursuits, notably the selection of curricular examples to illustrate phenomena, the design of formative and summative assessment items, and determination of whether instruction has fostered the development of abstract schemas divorced from particular instances. The goal of our study was to employ an experimental research design to quantify the degree to which situational features impact inferences about participants' understanding of Mendelian genetics. Two participant samples from different educational levels and cultural backgrounds (high school, n = 480; university, n = 444; Germany and USA) were used to test for context effects. A multi-matrix test design was employed, and item packets differing in situational features (e.g., plant, animal, human, fictitious) were randomly distributed to participants in the two samples. Rasch analyses of participant scores from both samples produced good item fit, person reliability, and item reliability and indicated that the university sample displayed stronger performance on the items compared to the high school sample. We found, surprisingly, that in both samples, no significant differences in performance occurred among the animal, plant, and human item contexts, or between the fictitious and Breal^item contexts. In the university sample, we were also able to test for differences in performance between genders, among ethnic groups, and by prior biology coursework. None of these factors had a meaningful impact upon performance or context effects. Thus some, but not all, types of genetics problem solving or item formats are impacted by situational features.

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Is Belief in Genetic Determinism Similar Across Countries and Traits?

Contributions from Biology Education Research, 2021

Discovery-Based Learning in the Life Sciences. By Kathleen M. Susman. Hoboken (New Jersey): Wiley-Blackwell. $64.95 (paper). xiv + 163 p. + 2 pl.; ill.; index. ISBN: 978-1-118-90756-6. 2015

The Quarterly Review of Biology, 2018

Testing the Impact of Novel Assessment Sources and Machine Learning Methods on Predictive Outcome Modeling in Undergraduate Biology

Journal of Science Education and Technology, 2021

High levels of attrition characterize undergraduate science courses in the USA. Predictive analyt... more High levels of attrition characterize undergraduate science courses in the USA. Predictive analytics research seeks to build models that identify at-risk students and suggest interventions that enhance student success. This study examines whether incorporating a novel assessment type (concept inventories [CI]) and using machine learning (ML) methods (1) improves prediction quality, (2) reduces the time point of successful prediction, and (3) suggests more actionable course-level interventions. A corpus of university and course-level assessment and non-assessment variables (53 variables in total) from 3225 students (over six semesters) was gathered. Five ML methods were employed (two individuals, three ensembles) at three time points (pre-course, week 3, week 6) to quantify predictive efficacy. Inclusion of course-specific CI data along with university-specific corpora significantly improved prediction performance. Ensemble ML methods, in particular the generalized linear model with elastic net (GLMNET), yielded significantly higher area under the curve (AUC) values compared with non-ensemble techniques. Logistic regression achieved the poorest prediction performance and consistently underperformed. Surprisingly, increasing corpus size (i.e., amount of historical data) did not meaningfully impact prediction success. We discuss the roles that novel assessment types and ML techniques may play in advancing predictive learning analytics and addressing attrition in undergraduate science education.

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Genetics and Identity

Science & Education, 2020

Many countries throughout the world are struggling to address longstanding inequalities stemming ... more Many countries throughout the world are struggling to address longstanding inequalities stemming from deeply ingrained societal prejudices about race, ethnicity, sex, gender, disability, and sexual orientation. 1 Prejudice can manifest itself in many different and often cryptic forms. A cognitive form of prejudice that influences how humans-particularly those living in Westernized cultures-make sense of societal inequalities is genetic essentialism (Henrich et al. 2010). Genetic essentialism is the belief that people of the same socially-defined group (e.g., race or gender) share genes that make them physically, cognitively, and behaviorally uniform, and distinct from other groups (Dar-Nimrod and Heine 2011). Several studies demonstrate that genetic essentialism mediates and moderates prejudiced attitudes toward racial minorities (Dar-Nimrod and Heine 2011), women (

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Evolution assessment: introduction to the special issue

Evolution: Education and Outreach, 2019

The first article in the collection, by Furrow and Hsu (2019), introduces educators to 14 evoluti... more

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Tools for Critical Thinking in Biology. By Stephen H. Jenkins. Oxford and New York: Oxford University Press. $49.95. xv + 324 p. + 23 pl.; ill.; index. ISBN: 978-0-19-998104-5. 2015

The Quarterly Review of Biology, 2016

The Impact of Misspelled Words on Automated Computer Scoring: A Case Study of Scientific Explanations

Journal of Science Education and Technology, 2016

Automated computerized scoring systems (ACSSs) are being increasingly used to analyze text in man... more Automated computerized scoring systems (ACSSs) are being increasingly used to analyze text in many educational settings. Nevertheless, the impact of misspelled words (MSW) on scoring accuracy remains to be investigated in many domains, particularly jargon-rich disciplines such as the life sciences. Empirical studies confirm that MSW are a pervasive feature of human-generated text and that despite improvements, spell-check and auto-replace programs continue to be characterized by significant errors. Our study explored four research questions relating to MSW and text-based computer assessments: (1) Do English language learners (ELLs) produce equivalent magnitudes and types of spelling errors as non-ELLs? (2) To what degree do MSW impact concept-specific computer scoring rules? (3) What impact do MSW have on computer scoring accuracy? and (4) Are MSW more likely to impact false-positive or false-negative feedback to students? We found that although ELLs produced twice as many MSW as non-ELLs, MSW were relatively uncommon in our corpora. The MSW in the corpora were found to be important features of the computer scoring models. Although MSW did not significantly or meaningfully impact computer scoring efficacy across nine different computer scoring models, MSW had a greater impact on the scoring algorithms for naïve ideas than key concepts. Linguistic and concept redundancy in student responses explains the weak connection between MSW and scoring accuracy. Lastly, we found that MSW tend to have a greater impact on false-positive feedback. We discuss the implications of these findings for the development of next-generation science assessments.

Are Faculty Changing? How Reform Frameworks, Sampling Intensities, and Instrument Measures Impact Inferences about Student-Centered Teaching Practices

CBE- Life Sciences Education, Sep 1, 2021

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Illuminating the complexities of conflict with evolution: validation of the scales of evolutionary conflict measure (SECM)

Evolution: Education and Outreach, Nov 23, 2020

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An application of Bayesian inference to examine student retention and attrition in the STEM classroom

Frontiers in Education, Feb 14, 2023

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Enhancing data pipelines for forecasting student performance: integrating feature selection with cross-validation

International journal of educational technology in higher education, Aug 17, 2021

Educational data mining (EDM) focuses on developing mathematical frameworks for analyzing large e... more

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How strongly does statistical reasoning influence knowledge and acceptance of evolution?

Journal of Research in Science Teaching, Mar 18, 2019

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Do you see what I‐SEA? A Rasch analysis of the psychometric properties of the Inventory of Student Evolution Acceptance

Science Education, Jan 23, 2019

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Measuring evolution learning: impacts of student participation incentives and test timing

Evolution: Education and Outreach, Jun 20, 2022

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A Lesson on Matter and Energy at the Organismal Scale: Linking Patterns and Processes Across Diverse Taxa

CourseSource, 2020

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Is Active Learning Enough? The Contributions of Misconception-Focused Instruction and Active-Learning Dosage on Student Learning of Evolution

BioScience, Sep 7, 2022

AI and formative assessment: The train has left the station

Journal of Research in Science Teaching

Quantifying variability in predictions of student performance: Examining the impact of bootstrap resampling in data pipelines

Computers and Education: Artificial Intelligence

A Meta-Analysis of Machine Learning-Based Science Assessments: Factors Impacting Machine-Human Score Agreements

Journal of Science Education and Technology, 2020

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Assessment of Genetics Understanding

Science & Education, 2017

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Is Belief in Genetic Determinism Similar Across Countries and Traits?

Contributions from Biology Education Research, 2021

Discovery-Based Learning in the Life Sciences. By Kathleen M. Susman. Hoboken (New Jersey): Wiley-Blackwell. $64.95 (paper). xiv + 163 p. + 2 pl.; ill.; index. ISBN: 978-1-118-90756-6. 2015

The Quarterly Review of Biology, 2018

Testing the Impact of Novel Assessment Sources and Machine Learning Methods on Predictive Outcome Modeling in Undergraduate Biology

Journal of Science Education and Technology, 2021

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Genetics and Identity

Science & Education, 2020

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Evolution assessment: introduction to the special issue

Evolution: Education and Outreach, 2019

The first article in the collection, by Furrow and Hsu (2019), introduces educators to 14 evoluti... more

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Tools for Critical Thinking in Biology. By Stephen H. Jenkins. Oxford and New York: Oxford University Press. $49.95. xv + 324 p. + 23 pl.; ill.; index. ISBN: 978-0-19-998104-5. 2015

The Quarterly Review of Biology, 2016

The Impact of Misspelled Words on Automated Computer Scoring: A Case Study of Scientific Explanations

Journal of Science Education and Technology, 2016

NSF: Transforming STEM assessment methodologies: Research on cyber-enabled measurement of cognitive models of natural selection. PRINCIPAL INVESTIGATOR.

NSF: Collaborative Research: Educational assessment tools for genomics and bioinformatics education. PRINCIPAL INVESTIGATOR at OSU.

NSF: Collaborative Research: Automated Analysis of Constructed Response Concept Inventories to Reveal Student Thinking: Forging a National Network for Innovative Assessment Methods. PRINCIPAL INVESTIGATOR at OSU

NSF: CAREER: Integrating science research on the Neogene of the Dominican Republic with the science education of Dominican American teachers and students in New York City. PRINCIPAL INVESTIGATOR

NSF: National Science Foundation Postdoctoral Fellowship. PRINCIPAL INVESTIGATOR.

NSF: Dissertation Improvement Grant, Division of Systematic Biology. The Neogene mass extinction in the western Atlantic: Determining the influence of methodology on patterns of extinction and faunal turnover.

The Global Challenge of Genomics Education: A Path to the Future

Genomics Applications for the Developing World, 2012

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The developmental basis of morphological disarmament in Prunum (Neogastropoda: Marginellidae)

Mollusc Assemblage Variability in the Río Gurabo Section (Dominican Republic Neogene): Implications for Species-Level Stasis

Evolutionary Stasis and …, 2008

... Rysanek Rivera, Jermaine Lawson, Maria Harvey, and Ross H. Nehm ... Upper panel: location of ... more

Science Education and the Dominican Republic Project

Evolutionary Stasis and Change in the …, 2008

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Macroevolutionary pattern and developmental process in marginellid gastropods from the Neogene of the Caribbean Basin

Assessing the Effects of Taphonomic Processes on Palaeobiological Patterns using Turbinid Gastropod Shells and Opercula

Evolutionary Stasis and Change in the …, 2008

For nearly 30 years the Dominican Republic Neogene has served as a productive research system for... more For nearly 30 years the Dominican Republic Neogene has served as a productive research system for exploring a broad array of palaeobiological topics, including speciation (e.g., Cheetham, 1986, 1987; Nehm and Geary, 1994; Nehm, 2005), intraspecific morphological variation (e.g., Anderson, 1994, 1996; Foster, 1986; Nehm, 2001), palaeoecological reconstruction (e.g., Vokes, 1989; Costa et al., 2001), and faunal turnover (e.g., Budd

Palaeobiological Research in the Cibao Valley of the Northern Dominican Republic

Evolutionary Stasis and Change in the Dominican …, 2008

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The Dynamics of Evolutionary Stasis and Change in the ‘Prunum maoense Group’

Evolutionary Stasis and Change in the Dominican …, 2008

... The description and study of ontogenetic variability is an essential component of systematic ... more

Quantifying the effects of sampling method and effort on estimates of species richness and relative abundance of Neogene benthic marine mollusks (Cibao Valley, …

Geological Society of …, 2004

Linking Macroevolutionary 6 Pattern and Developmental Process in Marginellid Gastropods

Evolutionary patterns: growth, form, and tempo in the …, 2001

Page 179. Linking Macroevolutionary 6 Pattern and Developmental Process in Marginellid Gastropods... more

Evolutionary Stasis and Change in the Dominican Republic Neogene

The richly fossiliferous Neogene stratigraphic sections of the Dominican Republic serve as one of... more The richly fossiliferous Neogene stratigraphic sections of the Dominican Republic serve as one of only a few geological research systems in the world where morphological stasis and punctuated speciation have been investigated in multiple lineages. This research system provides unprecedented opportunities for comparative studies of evolutionary stasis and change and their environmental and ecological contexts. In this volume, a diverse group of geologists and paleobiologists collectively focus their attention on this research system, providing an updated geological framework and a series of novel studies of evolutionary stasis and change among different lineages and associated ecological communities. This collection of studies illustrates the immense potential of collaborative, multidisciplinary, and field-based paleobiological research for studies of macroevolutionary change in the fossil record.

Genetics of original sin: The impact of natural selection on the future of humanity

Science Education, 2011

... The Books. Genetics of original sin: The impact of natural selection on the future of humanit... more

Evolution: Evidence and Acceptance

BioScience, 2012

Although scientists view evolution as an indisputable feature of the natural world, most American... more

Bernard Marcus: Evolution That Anyone Can Understand

Science & Education, 2012

The deluge of scholarly titles produced in association with the 150th anniversary of the publicat... more

MORPHOLOGY AND EVOLUTION OF THE LATE CENOZOIC MARINE BIOTA OF TROPICAL AMERICA-Calibrating spatial and temporal species richness …

Journal of Paleontology, 2001

... complexes (Budd and Klaus) and geminate species pairs (Marko and Jackson) to genera (Cheetham... more

DOES INCREASING SCIENCE TEACHERS'KNOWLEDGE OF EVOLUTION AND THE NATURE OF SCIENCE TRANSLATE INTO GREATER ADVOCACY FOR …

2005 Salt Lake City Annual Meeting, 2005

This study investigated whether an increase in secondary science teacher knowledge about evolutio... more

Big Science at Small Colleges: A Collaborative Model for Genomics Curriculum Development at Liberal Arts Colleges

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Scoring guide for the open response instrument (ORI) and evolutionary gain and loss test (EGALT)

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Human vs. Computer Diagnosis of Mental Models of Natural Selection: Testing the Efficacy of Lexical Analyses of Open Response Text

National Association of …, 2010

Our study empirically tests the efficacy of computerized Lexical Analyses (LA) of open-response t... more Our study empirically tests the efficacy of computerized Lexical Analyses (LA) of open-response text relative to expert human scoring. Specifically, we explored whether LA can diagnose the explanatory elements (or key concepts) that comprise students' explanatory models of natural selection with equal fidelity as expert human scorers in a sample of > 800 essays produced by undergraduate biology students. We used SPSS Text Analysis (TA) 3.0 to perform our LA and measure Kappa values (inter-rater reliability) of KC detection (i.e., computer-human rating correspondence). Our first analysis indicated that the LA functions (or extraction rules) developed and deployed in TA matched or exceeded the inter-rater reliability benchmark of 0.80 in the vast majority of cases for individual Key Concepts (KCs) for all three item prompts. The second analysis explored the measurement of human-computer correspondence in the combined sample of all 827 essays. Here we found outstanding correspondence, and that the extraction rules that we generated in TA are broadly applicable to different evolutionary scenarios (e.g., bacterial resistance, cheetah running speed, etc.). This result is encouraging, as it suggests that the development of new item sets may not necessitate the development of new Lexical Analysis (LA) rules.

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The effects of a marine and coastal resource education project on urban science teachers' curricula, pedagogical practices, and 'sense of place

OCEANS, 2005. Proceedings of MTS/IEEE, 2005

A marine and coastal resource education project for secondary science teachers, "NYC Marine Life"... more A marine and coastal resource education project for secondary science teachers, "NYC Marine Life", was developed for a cohort of pre-certified, in-service secondary science teachers. The project had five overarching goals: (1) to increase teacher knowledge of the biodiversity and marine environments that occur throughout the New York City region; (2) to increase teacher use of local coastal and marine examples when teaching required components of the secondary science curriculum (e.g., the NYS Living Environment); (3) to assess the impact of "NYC Marine Life" on the percentage of teachers who introduce their secondary students to coastal habitats; and (4) to determine how learning about local natural history and marine biology affected teachers' cognitive conceptualizations of the city and their "sense of place". Nineteen pre-certified secondary science teachers participated in the 13-week intervention. This cohort consisted largely of teaching fellows originally from outside of NYC. Pre-and post-course instruments, along with transcribed oral interviews, were employed to assess program goals. On the pre-course instrument 100% of teachers self-reported having limited knowledge of the marine resources of New York City and 61% self-reported having no knowledge of this topic at all. Pre/post intervention analyses indicated that (1) teacher self-reported knowledge and measured knowledge of the biology, ecology, and geology of the marine resources of the NYC region increased significantly; (2) teachers' planned use of local coastal and marine resource examples in their classroom curricula increased significantly; and (3) the percentage of teachers who intended to make use of the field increased significantly. "Sense of place" also emerged as a component of planned pedagogical change; several teachers thought that students needed to be better connected with their local environment. Constraints imparted by the NY Regents test, the lack of marine biology in the Living Environment curriculum, the difficulty of accessing the field, and student unfamiliarity with marine biodiversity were reported as explanations for why teachers would not change their curricula and pedagogy.

Integrating the Dominican Republic Project with new approaches to multicultural urban science education

2004 Denver Annual Meeting, 2004

Exploring the relationships among mollusk community change and the tempo and mode of speciation in the upper Gurabo Formation (Neogene, Dominican Republic)

Geological Society of …, 2004

History and philosophy of science and the teaching of macroevolution

by Kostas Kampourakis and Ross Nehm

M.R.Matthews (Ed) International Handbook of Research in History, Philosophy and Science Teaching, Springer Dordrecht., 2014

Although macroevolution has been the subject of sustained attention in the history and philosophy... more Although macroevolution has been the subject of sustained attention in the history and philosophy of science (HPS) community, only in recent years have science educators begun to more fully engage with the topic. This chapter first explores how science educators have conceptualised macroevolution and how their perspectives align with the views from HPS. Second, it illustrates how science educators’ limited engagement with HPS scholarship on macroevolution has influenced construct delineation, measurement instrument development, and educational arguments about which aspects of macroevolution are most important for students to learn. Third, it discusses how scientific debates about the causal factors responsible for macroevolutionary patterns have been exploited by creationists and have impacted the teaching of evolution. Finally, it emphasizes that the rich perspectives that HPS has to offer on the important topic of macroevolution have yet to be integrated into science education scholarship.

Ross Nehm

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