Science and Mathematics Education Commons^™

You Mean What? Commognitive Conflict In Resolving Contextual Logarithm Problems, Endrayana Putut Laksminto Emanuel, Fatkul Anam, Radhitya Duta Pradana, Anik Kirana, Sikky El Walida

Jurnal Pendidikan Sains

Students’ approaches to solving contextual mathematics problems involving logarithms vary significantly due to differences in their prior mathematical understanding. These differences may trigger commognitive conflict during the interpretation and reasoning processes when students attempt to construct mathematical meaning from contextual situations. This qualitative study aimed to explore how commognitive conflict emerges as a mechanism of mathematical interpretation in students’ discourse while solving logarithmic contextual problems. Twenty students participated in the study and were grouped based on their performance. One student was selected as the main research subject for an in-depth analysis. The findings reveal that commognitive conflict appeared in two …

Pinnlab: An Interactive Dashboard For Teaching Data-Driven Parameter Estimation In Differential Equations Using Physics-Informed Neural Networks, Mohan J. Parthasarathy, Padmanabhan Seshaiyer

CODEE Journal

Undergraduate instruction in ordinary differential equations (ODEs) is typically organized around the forward problem: finding solution trajectories when the governing equation and its parameters are known. In scientific practice, however, inverse problems are often more relevant, requiring unknown parameters to be inferred from noisy observations while assessing whether a proposed model is consistent with the data. We introduce PINNLab, an open-source MATLAB dashboard designed to help undergraduate students explore inverse modeling through physics-informed neural networks (PINNs). PINNLab presents PINNs as a complementary data-driven framework that connects differential equations, optimization, empirical data, and scientific machine learning. The instructional sequence is organized …

A Professional Development Course On Data-Driven Dynamical Systems At A Primarily Undergraduate Institution: Part A - Scientific Content, Alessandro M. Selvitella, Jeffrey R. Anderson

CODEE Journal

In the age of data-driven decision making, ordinary differential equations (ODEs) remain a powerful and interpretable framework for modeling dynamic processes, especially when integrated with modern tools from statistical learning and data-driven dynamical systems. Yet, general undergraduate and graduate curricula do not typically address key opportunities in data-driven dynamical systems.

This first paper in a series focuses on the mathematical and methodological core of a professional development course first developed in the academic year 2025-2026 at a Primarily Undergraduate Institution, Purdue University Fort Wayne. The curriculum developed in this course emphasized how regression, regularization, and sparse identification can be used …

Beyond The Best Fit: Fitting Sir-Style Models To Data While Prioritizing Biological Meaning, Meredith L. Greer

CODEE Journal

Many students find comfort in mathematics because math classes have been a place where they can find the “right answer” to exercises. Modeling courses typically emphasize more nuance, teaching students to try modeling approaches, compare back with real-world mechanisms and data, and then refine their models, in an ongoing cycle. One topic, however, can cause students to quickly revert into “right answer” mode: fitting a model to data. Phrases such as best fit and minimize the distance suggest there is one optimal solution that can be determined by an algorithm, and these algorithms typically have no relationship to the biology …

Parent Cultural Wealth: How Beliefs, Curriculum Familiarity, And Community Awareness Facilitate Home-Based Cs Conversations, Nicol Howard, Leiny Y. Garcia, Jean Ryoo, Julie Flapan, Michelle Choi, Paula Nazario, Wei Wei

Mathematics, Physics, and Computer Science Faculty Articles and Research

Parents are critical influences on children's computer science (CS) pathways, yet families’ involvement remains understudied. Guided by parental involvement and community cultural wealth frameworks, this work-in-progress examined survey data from 53 parents representing families historically underrepresented in computing within California (71% women; 54% Hispanic/Latin/x/e). Findings revealed that CS school curriculum familiarity and awareness of CS community events significantly predicted parent-child CS conversations, while parent CS confidence and attitudes did not, suggesting that curriculum transparency and community connections can promote equitable involvement. Future work will integrate qualitative interviews to examine how families draw upon their cultural wealth.

Course Portfolio: Elements Of Physics Phys 151, Evan A. Rich

UNL Faculty Course Portfolios

This course portfolio documents the instructional design, teaching methods, and ongoing assessment efforts for PHYS 151: Elements of Physics, an algebra-based introductory physics course at the University of Nebraska-Lincoln. The course serves a broad undergraduate population, including architecture, construction management, and life science majors. The portfolio describes the teaching framework that integrates pre-lecture video preparation, active in-class engagement through iClicker questions, and collaborative weekly recitation sections, all unified around a structured six-step problem-solving approach. A central concern of the course is building students’ self-efficacy in physics, particularly among those with math anxiety or limited preparation. Two assessments are reported: a …

The Architecture Of Chemical Understanding: How Representation Selection, Ordering, And Feature Salience Shape Students' Conceptions In Chemistry, Isaiah Nelsen

USF Tampa Graduate Theses and Dissertations

Chemical representations play a central role in how students learn and reason aboutchemistry. While representations are routinely used in chemistry classrooms, students often struggle to extract relevant information, connect representations to underlying chemical principles, and apply this information to problem-solving. This dissertation investigates the role of representations in supporting students’ conceptual understanding and reasoning across general and organic chemistry through three qualitative studies.

The first study in this work explores how variation in chemical representation influences how students understand foundational chemistry principles. This study sought to characterize how second semester general chemistry students approach dipole–dipole interaction tasks with four distinct …

From Process Retrieval To Understanding: A Look Into Curiosity And Metacognition In My Physics Classrooms, Nahuel Acosta Burroso

Critical and Creative Thinking Capstones Collection

In the modern high school physics classroom, the rapid proliferation of generative artificial intelligence (GenAI) has created a unique educational challenge. While these tools can solve complex problems quickly, they often lead to cognitive offloading, where students bypass the internal dialogue and deep thinking needed for true understanding. This project follows an action research journey that shifts the focus from restricting technology to cultivating curiosity and metacognition. I define curiosity as the gap identifier that appears when a student realizes they do not know something, while metacognition acts as the navigator that helps them decide what to do next. By …

1, 2, 2, 1, 1, 2, 1, 2, 2, 1, 2, 2, 1, 1, ..., Annemarie Torresen

Masters Theses

1

I invite you to see it and feel it and sit in it and breathe it in and

hold it in your lap. Art isn’t too scary, and neither is math.

2

bouncing between bounds of a binary

bippity boppity! let’s break brains and bread

balance or belly flop, what’s mine is yours:

bumptious and bumbling and barely able

i offer it broken and let you like it that way

Machine Learning For Modeling In An Elementary Differential Equations Class, Nathan Albin, Andrew G. Bennett, Abhinav Chand

CODEE Journal

Mixing machine learning with modeling is an area of increasing importance. This paper presents a lesson where students model a spring-mass system both using traditional analysis with linear damping and using machine learning to learn the damping from real data. The machine learning is implemented in a Jupyter notebook hosted on Google Colab, allowing students to train the neural network without requiring the students to carry out coding. Students get experience with how machine learning can fail, how it can work, and the time and data requirements for machine learning to succeed, and are asked to apply this knowledge to …

Parameter Estimation In Ode Models Using Least-Squares Regression, Ulrich A. Hoensch

CODEE Journal

We present a method of estimating model parameters for non-linear ODEs using least-squares regression. The coefficient of determination can be used as a measure of model fit. The method is demonstrated using US population data to fit a logistic growth model. Also, a competing species model is used to describe the interaction of two different species of yeast.

Robert, Powers; Unl Chemistry; Nmr-Assisted Drug Discovery, Mark Griep, Robert Powers

Department of Chemistry: Faculty Interviews

Dr. Robert Powers became a chemistry professor at the University of Nebraska-Lincoln in 2003 and is about to retire after 23 years. Prior to UNL, Bob was a drug discovery researcher for 11 years at American Cyanamid, which eventually became Wyeth and is now part of Pfizer. Bob was born in Jersey City, New Jersey. Something in his youth must have sparked an interest in chemistry because he earned a bachelor's in that subject from Rutgers University in New Brunswick. Then he traveled 1200 miles west to Purdue University in Indiana where he earned his doctorate. Next, he did postdoctoral …

Virtualizing Practical Science Education: A Sociological Analysis Of Undergraduate Teaching And Learning, Sina J. Fakoyede, Femi E. Babalola, Oluwatoyin T. Obateru, Oluwayemisi D. Akomolafe, Deborah O. Alabi, Stella K. Ekundayo

Higher Learning Research Communications

Objectives: The study aims to investigate the perspectives of university teachers and students on integrating practical science teaching with virtual learning in a multicultural and diverse society, specifically within the context of southwestern Nigeria.

Methods: A mixed-methods approach was employed, involving data collection from 100 university lecturers and 400 undergraduate students across 10 universities. Qualitative data were gathered through semi-structured interviews with lecturers and focus group discussions with students. Quantitative data were obtained via structured questionnaires, allowing for triangulation and comprehensive analysis.

Results: Findings revealed that certain lecturers showed preferential support influenced by students’ cultural backgrounds or academic behavior during …

The One-Shot Ceiling: Comparing Rag And Fine-Tuning Architectures For Ai-Assisted Math Mentoring, Michael J. Cummins

Computer Science Honors Papers

Providing individualized feedback to math students is a resource-intensive bottleneck in STEM education. We present Mentir-AI, a tool designed to elevate teacher capacity by generating high-quality mathematical feedback using the Mathforum's "Problem of the Week" archive. By analyzing a corpus of nearly one million interactions, we compare the efficacy of Retrieval-Augmented Generation (RAG) and Fine-Tuning (FT) architectures. This study details the development of an automated grading pipeline, the evolution of a multi-component system prompt, and the implementation of an automated mentor grading system in AI-led evaluation. While Fine-Tuning demonstrates superior instructional judgement, our results identify persistent failure modes in mathematical …

Developing Narrative-Based Stem Learning Tool For K-6 Visually Impaired Students, Daniel Tsivkovski, Dylan Ravel, Jeffrey Kraskouskas, Brandon Foley, Maryam Etezad, Franceli Cibrian, Rajeev Joshi, Ariel Han

Student Scholar Symposium Abstracts and Posters

This research develops a free, accessible web application that enables K-6 students who are blind or visually impaired (BVI) to learn STEM concepts using refreshable braille displays. Currently, most online learning tools are not designed for BVI students, creating a significant educational barrier.

The application interfaces with commercial braille displays and uses narrative-based learning to make STEM content approachable and engaging. By presenting material as personalized interactive stories generated with the help of Artificial Intellligence (AI), students can connect with concepts while developing braille reading skills. The curriculum design prioritizes accessibility through the Accessible Rich Internet Applications (ARIA) standards and …

Program And Proceedings, The Nebraska Academy Of Sciences 1880–2026: 146th Anniversary Year, One Hundred-Thirty-Sixth Annual Meeting

Nebraska Academy of Sciences: Programs and Proceedings

Program and abstracts of the proceedings for the Nebraska Academy of Sciences 136th annual meeting, 2025

Sessions

Aeronautics and Space Science

Anthropology

Biological and Medical Sciences

Earth Sciences

Ecology, Sustainability, and Environmental Science

Physics and Engineering

General Poster Session

2026 Maiben Lecture: Shifting Extremes: Understanding Nebraska’s Changing Climate and Preparing for What Lies Ahead, Deborah Bathke

2026 Friends of Science Awards: Julie Shaffer and Irina Filina

2026 C. Bertrand and Marian Othmer Schultz Colleaguate Schoalrship Award: Piper Ryschon and Bryce Reeson

In Memoriam: Paul Royster

Emergent Storylines That Influence Positions And Mathematical Status In Collaborative Small-Group Proof Activity, Brittney M. Ellis, Tenchita Alzaga Elizondo

School of Mathematical & Statistical Sciences Faculty Publications

In this paper, we used positioning theory to examine storylines that emerged in students’ discourse as they collaborated on a proof construction task. We purposefully selected a case of group work from an inquiry-oriented introduction to proof course as prior analyses showed it was highly collaborative (Alzaga Elizondo, 2022), yet power dynamics seemed unbalanced. We hypothesized that positioning theory could provide a useful lens to interrogate such power dynamics. Through this analysis, we identified several implicit storylines that influenced the interaction related to the nature of proofs, the nature of mathematics, writing proofs, the role of an external authority, …

David Berkowitz, Enzyme-Assisted Organic Synthesis & Nsf Officer, Mark A. Griep, David B. Berkowitz

Department of Chemistry: Faculty Interviews

Dr. Dave Berkowitz was born in Urbana, Illinois. He earned his bachelor's degree in chemistry from the University of Chicago, where he did undergraduate research. Next, he earned his doctorate from Harvard University. However, his advisor, Steve Benner, moved from Harvard to ETH Zurich, also called the Swiss Federal Institute of Technology. Dave accompanied him to Zurich, where he completed his dissertation work. When Dave returned to the U.S., he did a postdoc with the legendary Samuel Danishefsky at Yale University. In 1991, he joined UNL as an assistant professor of chemistry and quickly rose through the ranks. Dave is …

Energy Scaling And Frequency Ratios Of Particles And Constants, Alison Christina Menzmer, Donald Chakeres, Vola Andrianarijaona

Campus Research Month

We are exploring quantum aspects of various physical quantities (including Bohr radius, Rydberg constant, Planck time, and Hubble constant) and mass energies of elementary particles (including electron, neutron, and quarks). We express all physical units in an energy equivalence in Hertz, normalized to 1 Hz. Furthermore, the logarithms of these normalized energies are scaled by the logarithm of a chosen particle, which allows the generation of an Arrhenius plot exhibiting numerical structures. Our results presented in this poster show that the proton is a good candidate for an Arrhenius plot with partial fractions (1 + 1/n) and (1 - 1/n).

Development Of Problem-Based Teaching Modules On Linear Systems Of Equations And Inequalities To Improve Mathematical Problem-Solving Skills, Elsya Suharnita, Kartini Kartini, Sehatta Saragih

Jurnal Pendidikan Sains

This study addresses the low mathematical problem-solving competency among Indonesian students, as evidenced by the PISA 2018 results that showed 71% failed to meet the minimum mathematical competency level. This study aims to develop a problem-based learning (PBL) module for systems of equations and inequalities content to improve Phase E students' mathematical problem-solving abilities. Using the ADDIE (Analysis, Design, Development, Implementation, Evaluation) model, this study involved expert validation, a small group trial with 12 students, and field implementation using a posttest-only control group design with 24 students in the experimental group and 25 students in the control group. The results …

Cognitive Conflict In Iconic Visual Representations: Comparing Conventional And Ai Approaches, Endrayana Putut Laksminto Emanuel, Herfa Maulina Dewi Soewardini, Radhitya Duta Pradana, Sikky El Walida

Jurnal Pendidikan Sains

Background of study: The rapid integration of Artificial Intelligence (AI) in higher education has transformed mathematical problem-solving practices, yet it introduces potential discrepancies in students’ visual understanding, particularly in geometric contexts, leading to commognitive conflicts in visual mediators. Aims and scope of paper: This study aims to analyze and compare the sources of commognitive conflict in iconic visual representations when students solve flat shape problems using conventional methods versus AI-assisted approaches. Methods: A qualitative design was employed involving 20 first-year mathematics education students divided into two groups (AI-assisted and conventional). Data were collected through students’ written work and semi-structured interviews …

Asphalt Pavement Rejuvenation Investigated By Nuclear Magnetic Resonance Relaxometry, Catherine Skaggs

Miners Solving for Tomorrow Research Conference

Asphalt is a relatively inexpensive material commonly used for road pavements; however, asphalt ages from exposure to oxygen and UV radiation, leading to loss of elasticity, which leads to cracks and potholes. To slow or reverse asphalt aging, pavement preservation treatments are in use. It’s unclear whether these treatments truly rejuvenate the pavement structure or merely offer a short-term benefit. Nuclear Magnetic Resonance (NMR) relaxometry is an analytical technique that uses the recovery of excited nuclear magnetization as a parameter to gain insights into molecular environments. Recovery-time distributions gathered from asphalt materials show differences between regular and rejuvenated asphalt samples, …

Curriculum For A Two Semester Calculus Course Specializing In Life Science And Data Science, Patrick Mcclain

LSU Master's Theses

Traditionally, introductory calculus has been designed for engineering and physics students, often leaving students majoring in data science or life sciences with a curriculum that lacks professional relevance and is overly reliant on problems that focus on computational fluency. This thesis proposes a two-semester sequence, called MATH 153X and MATH 154X, specifically tailored for the Louisiana State University (LSU) Dual Enrollment program and university-level data science and life sciences majors. By integrating modern computational tools—such as symbolic calculators and artificial intelligence (AI) tools—the proposed curriculum shifts the pedagogical focus from procedural symbolic manipulation toward conceptual literacy.

Through a series …

Advancing Environmental Justice Through Chemical Education: Perspective From New Orleans’ Water And Air Quality Challenges, Ja’Lynn Keller, Sita Aggarwal, Rami A. Al-Horani, Morewell Gasseller, Navneet Goyal

Faculty and Staff Publications

New Orleans, Louisiana, faces profound environmental vulnerabilities arising from the convergence of industrial pollution, urban runoff, and climate change–driven weather events. This paper examines systemic challenges affecting water and air quality in the region, with particular focus on low-income and marginalized communities disproportionately burdened by environmental degradation. Drawing on educational and community-based monitoring initiatives at Xavier University of Louisiana and Southeastern Louisiana University, we highlight the integration of student learning with real-time data collection of contaminants such as fecal coliforms, heavy metals, hydrocarbons, and polycyclic aromatic hydrocarbons (PAHs). The aftermath of Hurricane Katrina revealed significant fecal contamination in sediment layers, …

A Review Of Oer Math Homework Systems, Rachel Bailey, Nathan Carter

Open Educational Resources Publications

This report evaluates four leading open educational resource (OER) math homework systems—MyOpenMath, WeBWorK, Ximera, and XYZ Homework—for their suitability in Bentley University’s first-year mathematics courses. The review compares cost, usability, LMS integration, available content, and alignment with Bentley curricula. MyOpenMath emerges as the strongest option due to its usability, robust problem libraries, and fully free access. XYZ Homework offers comparable features but includes student fees. Ximera and WeBWorK provide powerful capabilities but require greater technical expertise. The report concludes with recommendations for implementation and needed faculty support.

Measuring What Matters: Specifications Grading And Latin* Students’ Mathematics Identity, Luis Miguel Fernández, Mayra Ortiz Galarza, Cristina Villalobos, Martha Asare

School of Mathematical & Statistical Sciences Faculty Publications

This study examined Specifications Grading, an alternative grading system emphasizing clearly defined learning outcomes and revision, and mathematics identity among 846 Latin* Calculus I students at a Hispanic-Serving Institution. Mathematics identity, comprising competence/performance, recognition, and interest, was measured at the beginning and end of the semester. Repeated-measures analyses indicated stable competence/performance and recognition alongside declines in interest. Specifications Grading was associated with increased mathematics identity, and multilingual students experienced smaller declines than their peers overall.

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Este estudio examinó la calificación por especificaciones, un sistema de evaluación alternativo que enfatiza resultados de aprendizaje claramente definidos y oportunidades estructuradas de revisión, …

“It’S A Lot More To It Than Just Research”: Integrating Critical Data Literacy And Reasoning With Data Into A Stem Summer Camp, Marc T. Sager, Saki L. Milton, Candace Walkington

Publications

Purpose: This study explores how middle-grade girls from predominantly underrepresented and underserved racially and ethnically minoritized (UUREM) backgrounds developed critical data literacy (CDL) through participation in a week-long residential STEM camp. Given the increasing importance of data science education in a data-driven world, this research examines how informal learning environments can support CDL development among youth from historically marginalized groups.

Design/Methodology/Approach: The study draws on qualitative interview data from eleven participants, and their group-produced artifacts to investigate how the camp experience supported engagement with data and the development of CDL. Interviews explored participants' experiences with data collection, organization, analysis, and …

An Undergraduate Chemistry Experiment Integrating Theoretical And Practical Aspects Of Hypervalent Iodine(I) Compounds, Vladimir L. Kolesnichenko, Galina Z. Goloverda

Faculty and Staff Publications

A simple reaction sequence has been developed to produce iodine chloride-pyridine (PyICl) and pyridinium dichloroiodate (PyHICl2), convenient iodinating agents, in a high yield. Our approach is safe and simple to handle, avoiding the use of elemental chlorine or hazardous manipulations. Designed for an upper-level undergraduate hybrid lecture/lab chemistry course, the experiment integrates key concepts from both inorganic and organic chemistry. The pre-experiment lecture explains the connections between molecular structure, reactivity trends, and reaction types. Over three 4 h lab sessions, students carry out a sequence of quantitative transformations and characterize each intermediate and the final product using ESI mass spectrometry, …

George Sturgeon, Metal Fluorides & Vice Chair, Mark A. Griep, George D. Sturgeon

Department of Chemistry: Faculty Interviews

Dr. George Sturgeon was a chemistry professor at the University of Nebraska -Lincoln for 39 years, from 1964 to 2003. During his time at UNL, he spent 15 years as the vice chair. Something in his youth must have sparked an interest in chemistry because he earned a bachelor’s in that subject from the University of North Dakota in Grand Forks. Then, he traveled 870 miles east to Michigan State University in East Lansing where he earned his doctorate. Immediately after graduating, he joined the University of Nebraska-Lincoln in 1964 as an assistant professor but was soon promoted to associate …

The Butterfly Effect In Economics: Exploring Chaos With A Simple Financial Model, Sandy Hs Herho

CODEE Journal

Wild swings in financial markets need not result from external shocks like earthquakes or wars—they can emerge from deterministic chaos. This article introduces kalimusada, an open-source Python library that lets students and instructors explore this phenomenon through a simple three- equation model of financial dynamics. The model couples interest rates, investment, and prices through nonlinear feedback, generating bounded but unpredictable oscillations characteristic of chaos. Tiny differences in starting conditions—smaller than any measurement could detect—grow exponentially until two initially identical economies follow completely different paths. The library provides ready-to-use tools for visualizing this “butterfly effect” in economics, computing divergence metrics, and …