pubs

2024

1. NATURE PHYS

   Computing in physics education

   Marcos D. Caballero, and Tor Ole B. Odden

   Nature Physics, 2024

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   Computing is central to the enterprise of physics but few undergraduate physics courses include it in their curricula. Here we discuss why and how to integrate computing into physics education.

2. SIGCSE

   Using Natural Language Processing to Explore Instructional Change Strategies in Undergraduate Science Education Literature

   Emily Bolger, and Marcos Caballero

   In Proceedings of the 55th ACM Technical Symposium on Computer Science Education V. 2, 2024

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   Over ten years ago, our collaborators conducted a NSF-funded project identifying four broad categories of change strategies used to improve undergraduate STEM education through a comprehensive interdisciplinary literature review of articles from 1995 to 2008. Since this first iteration, there have been many major developments in undergraduate STEM education; particularly, the rapid development in sophisticated technology tools. These developments affect the nature of classroom instruction as well as expand the bounds on analyzing a corpus of articles. Thus, it is crucial to repeat this review to better understand the changes in STEM education from the more recent past. Our goal is to use machine learning to identify, potentially new, themes in the recent literature. We plan to compare and contrast both AI-assisted modeling and traditional, human-qualitative coding approaches in an effort to: (1) identify the benefits and faults of using AI verses human coding, and (2) portray a comprehensive story of change instruction literature from 2010. This lightning talk will describe the data extraction process and preliminary results from machine learning models. In addition to sharing the beginnings of our work, we hope to gain new perspectives and ideas from computing education scientists regarding our data representation and modeling choices.

3. SIGCSE

   Exploring the Scurry of Squirrels in Central Park

   Rachel Lyn-Salmon Frisbie, Devin Silvia, Marcos D. Caballero, Rachel Roca, Amanda Bowerman, and Krithi Sachithanand

   In Proceedings of the 55th ACM Technical Symposium on Computer Science Education V. 2, 2024

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   As computing becomes increasingly intertwined with other disciplines, research that centers computing education in an interdisciplinary context (and the challenges surrounding it) is increasingly relevant. In particular, writing modular code (i.e. using functions) is a fundamental part of scientific programming. However, functions have been identified as challenging for students to learn. This assignment leverages a fun, real, and approachable dataset from the 2018 Central Park Squirrel Census as well as experiences authentic to developing scientific programs to introduce the concept of functions in Python. The assignment is intended to be delivered in a "flipped classroom" format, where students are first introduced to concepts in videos and short problems prior to coming to class. Once in class, the students work collaboratively in groups of 4-6 with a hands-on programming activity. By the end of the assignment, students have not only had the opportunity to learn about functions in an authentic context, but they have also been able to make calculations and propose their own problems to learn about the data.

2023

1. IN REVIEW

   Beyond Active Learning: Using 3-Dimensional Learning to Create Scientifically Authentic, Student-Centered Classrooms

   Melanie M. Cooper, Marcos D Caballero, Justin H Carmel, Erin M Duffy, Cori L Fata-Hartley, Deborah G Herrington, Paul C Nelson, James T Laverty, Lynmarie A Posey, Jon R Stoltzfus, Ryan L Stowe, Ryan D Sweeder, Stuart Tessmer, Sonia M Underwood, and Diane Ebert-May

   bioRxiv, 2023

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   In recent years, much of the emphasis for transformation of introductory STEM courses has focused on "active learning", and while this approach has been shown to produce more equitable outcomes for students, the construct of "active learning" is somewhat ill-defined, and can encompass a wide range of pedagogical techniques. Here we present an alternative approach for how to think about the transformation of STEM courses that focuses instead on what students should know and what they can do with that knowledge. This approach, known as three-dimensional learning (3DL), emerged from the National Academy’s "A Framework for K-12 Science Education", which describes a vision for science education that centers the role of constructing productive causal accounts for phenomena. Over the past 10 years, we have collected data from introductory biology, chemistry, and physics courses to assess the impact of such a transformation on higher education courses. Here we report on an analysis of video data of class sessions that allows us to characterize these sessions as active, 3D, neither, or both 3D and active. We find that 3D classes are likely to also involve student engagement (i.e. be active), but the reverse is not necessarily true. That is, focusing on transformations involving 3DL also tends to increase student engagement, whereas focusing solely on student engagement might result in courses where students are engaged in activities that do not involve meaningful engagement with core ideas of the discipline.Competing Interest StatementThe authors have declared no competing interest.

2. IN REVIEW

   Couplet scoring for research based assessment instruments

   Michael Vignal, Gayle Geschwind, Marcos D. Caballero, and H. J. Lewandowski

   2023

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   Contemporary content-focused research-based assessment instruments typically use instrument items (i.e., questions) as the unit of assessment for instrument scoring, reporting, and validation. However, traditional item-based scoring has a number of limitations, including several arising from the use of the common assessment development conventions of single-construct items, unidimensionality, and single-correct-answer items. Couplet scoring, introduced in this paper, employs the couplet as an alternative unit of assessment, where a couplet is essentially an item viewed and scored through the lens of a specific assessment objective (AO). With couplet scoring, a single item may have more than one AO and therefore more than one couplet. In this paper, we outline the limitations of traditional item scoring, introduce couplet scoring and discuss its affordances (especially as they relate to limitations of item scoring), and use a recently developed content RBAI to ground our discussion.

3. PRPER

   Survey of physics reasoning on uncertainty concepts in experiments: An assessment of measurement uncertainty for introductory physics labs

   Michael Vignal, Gayle Geschwind, Benjamin Pollard, Rachel Henderson, Marcos D. Caballero, and H. J. Lewandowski

   Oct 2023

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   [This paper is part of the Focused Collection on Instructional labs: Improving traditions and new directions.] Measurement uncertainty is a critical feature of experimental research in the physical sciences, and the concepts and practices surrounding measurement uncertainty are important components of physics lab courses. However, there has not been a broadly applicable, research-based assessment tool that allows physics instructors to easily measure students’ knowledge of measurement uncertainty concepts and practices. To address this need, we employed evidence-centered design to create the Survey of Physics Reasoning on Uncertainty Concepts in Experiments (SPRUCE). SPRUCE is a pre-post assessment instrument intended for use in introductory (first and second year) physics lab courses to help instructors and researchers identify student strengths and challenges with measurement uncertainty. In this paper, we discuss the development of SPRUCE’s assessment items guided by evidence-centered design, focusing on how instructors’ and researchers’ assessment priorities were incorporated into the assessment items and how students’ reasoning from pilot testing informed decisions around item answer options. We also present an example of some of the feedback an instructor would receive after implementing SPRUCE in a pre-post fashion, along with a brief discussion of how that feedback could be interpreted and acted upon.

4. IN REVIEW

   Supporting teachers to integrate computational practices and design opportunities for equitable participation in science classrooms

   D. Stroupe, D. Reinholz, S. Byun, J. Christensen, J. Willison, and Marcos D. Caballero

   Oct 2023
5. Physics Computational Literacy: What, Why, and How?

   Tor Ole B. Odden, and Marcos D. Caballero

   In International Handbook of Physics Education Research, Oct 2023

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6. 

   Making graduate admissions in physics more equitable

   Nicholas T. Young, Kirsten Tollefson, and Marcos D. Caballero

   Physics Today, Jul 2023

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   The admission of graduate students to post-bachelor’s physics programs is a complex and challenging system. Any graduate director, faculty member, or graduate student can recount their own vivid experience with that complicated and, quite often, opaque process.3 At Michigan State University, we set out to understand the admissions process, determine how it was functioning, and make changes to it. We hoped to admit more diverse candidates to our program, evaluate them more equitably and holistically, and, ultimately, create a more inclusive program where each student is valued and supported in their studies. We are far from our ideal collective vision but feel that our progress toward that vision is nonetheless important to share with our colleagues.

2022

1. REPORT

   2021 PICUP Virtual Capstone Conference Report

   Marcos D. Caballero, Larry Engelhardt, Alexis V. Knaub, Michelle Kuchera, Marié Lopez Puerto, Brandon Lunk, Kelly Roos, and Todd Zimmerman

   Jul 2022

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2. 

   Rubric-based holistic review: A promising route to equitable graduate admissions in physics

   Nicholas T. Young, K. Tollefson, Remco G. T. Zegers, and Marcos D. Caballero

   Phys. Rev. Phys. Educ. Res., Nov 2022

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   As systematic inequities in higher education and society have been brought to the forefront, graduate programs are interested in increasing the diversity of their applicants and enrollees. Yet, structures in place to evaluate applicants may not support such aims. One potential solution to support those aims is rubric-based holistic review. Starting in 2018, our physics department implemented a rubric-based holistic review process for all applicants to our graduate program. The rubric assessed applicants on 18 metrics covering their grades, test scores, research experiences, noncognitive competencies, and fit with the program. We then compared faculty’s ratings of applicants by admission status, sex, and undergraduate program over a three-year period. We find that the rubric scores show statistically significant differences between admitted and nonadmitted students as hoped. We also find that differences in rubric scores based on sex or undergraduate program reflected known systematic inequities such as applicants from smaller and less prestigious undergraduate universities scoring lower on the physics GRE and women performing more volunteer work in academia. Our results then suggest rubric-based holistic review as a possible route to making graduate admissions in physics more equitable.

3. 

   Students’ perspectives on computational challenges in physics class

   P. C. Hamerski, Daryl McPadden, Marcos D. Caballero, and Paul W. Irving

   Phys. Rev. Phys. Educ. Res., Aug 2022

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   High school science classrooms across the United States are answering calls to make computation a part of science learning. The problem is that there is little known about the barriers to learning that computation might bring to a science classroom or about how to help students overcome these challenges. This case study explores these challenges from the perspectives of students in a high school physics classroom with a newly revamped, computation-integrated curriculum. Focusing mainly on interviews to center the perspectives of students, we found that computation is a double-edged sword: It can make science learning more authentic for students who are familiar with it, but it can also generate frustration and an aversion towards physics for students who are not.

4. 

   Development and illustration of a framework for computational thinking practices in introductory physics

   Daniel P. Weller, Theodore E. Bott, Marcos D. Caballero, and Paul W. Irving

   Phys. Rev. Phys. Educ. Res., Jul 2022

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   Physics classes with computation integrated into the curriculum are a fitting setting for investigating computational thinking. In this paper, we present a framework for exploring this topic in introductory physics courses. The framework, which was developed by reviewing relevant literature and acquiring video data from high school classrooms, comprises 14 practices that students could engage in when working with Glowscript VPython activities. For every practice, we provide in-class video data to exemplify the practice. In doing this work, we hope to provide ways for teachers to assess their students’ development of computational thinking and give physics education researchers a foundation to study the topic in greater depth.

5. PRPER

   Classification of open-ended responses to a research-based assessment using natural language processing

   Joseph Wilson, Benjamin Pollard, John M. Aiken, Marcos D. Caballero, and  H. J. Lewandowski

   Physical Review Physics Education Research, Jul 2022

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   Surveys have long been used in physics education research to understand student reasoning and inform course improvements. However, to make analysis of large sets of responses practical, most surveys use a closed-response format with a small set of potential responses. Open-ended formats, such as written free response, can provide deeper insights into student thinking, but take much longer to analyze, especially with a large number of responses. Here, we explore natural language processing as a computational solution to this problem. We create a machine learning model that can take student responses from the Physics Measurement Questionnaire as input, and output a categorization of student reasoning based on different reasoning paradigms. Our model yields classifications with the same level of agreement as that between two humans categorizing the data, but can be done by a computer, and thus can be scaled for large datasets. In this work, we describe the algorithms and methodologies used to create, train, and test our natural language processing system. We also present the results of the analysis and discuss the utility of these approaches for analyzing open-response data in education research.

6. JMB

   Three Cases That Demonstrate How Students Connect the Domains of Mathematics and Computing

   Odd Petter Sand, Marcos D. Caballero, Knut Martin Mørken, and Elise Lockwood

   Journal of Mathematical Behavior, Jul 2022

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   This study uses actor-oriented transfer perspective to investigate different ways in which students make connections across the domains of mathematics and computing. We interview first-year students at the University of Oslo as they work with a set of tutorials that we designed to integrate knowledge from both domains. The cases we present here demonstrate four different types of cross-domain connections: (a) mathematically reproducing the work of a computer program, (b) cyclically improving a program to produce better output, (c) coupling math to output to justify program improvements and (d) coupling math to code to justify program design. We provide rich examples of the ways in which students make these connections and discuss affordances for mathematical learning in this context.

7. DEME

   Students’ Development of a Logarithm Function in Python Using Taylor Expansions: A Teaching Design Case Study

   Odd Petter Sand, Elise Lockwood, Marcos D. Caballero, and Knut Martin Mørken

   Digital Experiences in Mathematics Education, Jul 2022

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   We present here the lessons learned by iteratively designing a tutorial for first-year university students using computer programming to work with mathematical models. Alternating between design and implementation, we used video-taped task interviews and classroom observations to ensure that the design promoted student understanding. The final version of the tutorial we present here has students make their own logarithm function from scratch, using Taylor polynomials. To ensure that the resulting function is accurate and reasonably fast, the students had to understand and apply concepts both from computing and from mathematics. We identify three categories of such concepts and identify three design features that students attended to when demonstrating such understanding. Additionally, we describe four important take-aways from a teaching design point of view that resulted from this iterative design process.

8. Exploring Self-Efficacy in Data Science

   P. C. Hamerski, Devin Silvia, and Marcos D. Caballero

   In Proceedings of the 27th ACM Conference on on Innovation and Technology in Computer Science Education Vol. 2, Jul 2022

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   Data science is often heralded as a key learning goal for students in STEM classrooms. There are also myriad efforts to integrate data science into these classrooms, and many dedicated research efforts for identifying the best ways to do so. However, the problem is that there is little agreement on how to introduce data science to students, whether it be through computer science courses where students can learn programming, through STEM courses where students can learn disciplinary knowledge, or through newly designed data science centric courses. Furthermore, best practices for teaching data science require an understanding of what data science is from students’ perspectives, and how they experience it. This poster explores this problem by showcasing an interview study of an undergraduate course offered at Michigan State University, which focuses on computational modeling and data analysis. Students in this course learn data science via problem-based group work and apply it to several disciplinary contexts. The interview study examines how students perceived what they learned, and how their self-efficacy developed over the course of the semester. In effect, we demonstrate a course where students are learning data science, identify the key features of the course that students perceive, and build an understanding of data science self-efficacy, which can be used to help design positive, effective experiences in data science courses.

9. Teachers’ use of resources for equitable integration of computation in science classrooms

   David Stroupe, Sunghwan Byun, Julia Willson, Julie Christensen, Marcos D. Caballero, and Daniel L. Reinholz

   In Proceedings of the 16th International Conference of the Learning Sciences-ICLS2022, Jul 2022

2021

1. PRPER

   Introductory physics lab instructors’ perspectives on measurement uncertainty

   Benjamin Pollard, Robert Hobbs, Rachel Henderson, Marcos D. Caballero, and H. J. Lewandowski

   Physical Review Physics Education Research, Jul 2021

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   Introductory physics lab courses serve as the starting point for students to learn and experience experimental physics at the undergraduate level. They often focus on measurement uncertainty, an essential topic for practicing physicists and a foundation for more advanced lab learning. As such, measurement uncertainty has been a focus when studying and improving introductory physics lab courses. There is a need for a research-based assessment explicitly focused on measurement uncertainty that captures the breadth of learning related to the topic, and that has been developed and documented in an evidence-centered way. In this work, we present the first step in the development of such an assessment, with the goal of establishing the breadth and depth of the domain of measurement uncertainty in introductory physics labs. We conducted and analyzed interviews with introductory physics lab instructors across the US, identifying prevalent concepts and practices related to measurement uncertainty, and their level of emphasis in introductory physics labs. We find that instructors discuss a range of measurement uncertainty topics beyond basic statistical ideas like mean and standard deviation, including those connected to modeling, another lab learning goal. We describe how these findings will be used in the subsequent development of the assessment, called the Survey Of Physics Reasoning On Uncertainty Concepts In Experiments (SPRUCE).

2. PRPER

   Framework for evaluating statistical models in physics education research

   John M. Aiken, Riccardo De Bin, H. J. Lewandowski, and Marcos D. Caballero

   Physical Review Physics Education Research, Jul 2021

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   Across the field of education research there has been an increased focus on the development, critique, and evaluation of statistical methods and data usage due to recently created, very large datasets and machine learning techniques. In physics education research (PER), this increased focus has recently been shown through the 2019 Physical Review PER Focused Collection examining quantitative methods in PER. Quantitative PER has provided strong arguments for reforming courses by including interactive engagement, demonstrated that students often move away from scientistlike views due to science education, and has injected robust assessment into the physics classroom via concept inventories. The work presented here examines the impact that machine learning may have on physics education research, presents a framework for the entire process including data management, model evaluation, and results communication, and demonstrates the utility of this framework through the analysis of two types of survey data.

3. PRPER

   Physics Graduate Record Exam does not help applicants “stand out”

   Nicholas T. Young, and Marcos D. Caballero

   Physical Review Physics Education Research, Jul 2021

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   One argument for keeping the physics Graduate Record Exam (GRE) is that it can help applicants who might otherwise be missed in the admissions process stand out. In this work, we evaluate whether this claim is supported by physics graduate school admissions decisions. We used admissions data from five Ph.D.-granting physics departments over a 2-year period (N=2537) to see how the fraction of applicants admitted varied based on their physics GRE scores. We compared applicants with low GPAs to applicants with higher GPAs, applicants from large undergraduate universities to applicants from smaller undergraduate universities, and applicants from selective undergraduate institutions to applicants from less selective undergraduate institutions. We also performed a mediation and moderation analysis to provide statistical rigor and to better understand the previous relationships. We find that for applicants who might otherwise have been missed (e.g., have a low GPA or attended a small or less selective school), having a high physics GRE score did not seem to increase the applicant’s chances of being admitted to the schools. However, having a low physics GRE score seemed to penalize otherwise competitive applicants (i.e., applicants with mid to high GPAs). Thus, our work suggests that the physics GRE does not, in fact, help applicants who might otherwise be missed stand out.

4. JEDM

   Predictive and Explanatory Models Might Miss Informative Features in Educational Data

   Nicholas T. Young, and Marcos D. Caballero

   Journal of Educational Data Mining, Jul 2021

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   We encounter variables with little variation often in educational data mining (EDM) due to the demographics of higher education and the questions we ask. Yet, little work has examined how to analyze such data. Therefore, we conducted a simulation study using logistic regression, penalized regression, and random forest. We systematically varied the fraction of positive outcomes, feature imbalances, and odds ratios. We find the algorithms treat features with the same odds ratios differently based on the features’ imbalance and the outcome imbalance. While none of the algorithms fully solved how to handle imbalanced data, penalized approaches such as Firth and Log-F reduced the difference between the built-in odds ratio and value determined by the algorithm. Our results suggest that EDM studies might contain false negatives when determining which variables are related to an outcome. We then apply our findings to a graduate admissions dataset. We end by proposing recommendations that researchers should consider penalized regression for datasets on the order of hundreds of cases and should include more context about their data in publications such as the outcome and feature imbalances.

5. PRPER

   Investigating institutional influence on graduate program admissions by modeling physics Graduate Record Examination cutoff scores

   Nils J. Mikkelsen, Nicholas T. Young, and Marcos D. Caballero

   Physical Review Physics Education Research, Jul 2021

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   Despite limiting access to applicants from underrepresented racial and ethnic groups, the practice of using hard or soft Graduate Record Examination (GRE) cutoff scores in physics graduate program admissions is still a popular method for reducing the pool of applicants. The present study considers whether the undergraduate institutions of applicants have any influence on the admissions process by modeling a physics GRE cutoff score with application data from admissions offices of five universities. Two distinct approaches based on inferential and predictive modeling are conducted. While there is some disagreement regarding the relative importance between features, the two approaches largely agree that including institutional information significantly aids the analysis. Both models identify cases where the institutional effects are comparable to factors of known importance such as gender and undergraduate GPA. As the results are stable across many cutoff scores, we advocate against the practice of employing physics GRE cutoff scores in admissions.

6. PERC

   Comparing student conceptions and construction of while loops in modeling motion

   Grace Mackessy, Paul W. Irving, Marcos D. Caballero, and Leanne Doughty

   In 2021 Physics Education Research Conference Proceedings, Jul 2021
7. PERC

   Analyzing time-to-degree for transfer students at a Large Midwestern University

   Alyssa C. Waterson, Rachel Henderson, and Marcos D. Caballero

   In 2021 Physics Education Research Conference Proceedings, Jul 2021

2020

1. PRPER

   Communities of practice as a curriculum design theory in an introductory physics class for engineers

   Paul W. Irving, Daryl McPadden, and Marcos D. Caballero

   Physical Review Physics Education Research, Jul 2020

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   The communities of practice framework has become an essential framework for understanding identity development both in physics education research (PER) and in science, technology, engineering, and mathematics, more broadly. However, the use of communities of practice as a learning theory that informs curriculum design is significantly less prevalent within the PER community. One possible reason for this is that communities of practice as a theory originated in professional environments and it subsequently moved towards a framework that is centered around informing management practices. Some significant interpretations and negotiations need to be completed in order to apply and to design for communities of practice in the classroom environment. In this paper, we outline an introductory physics course called Projects and Practices in Physics (P-Cubed) that was designed using the communities of practice as a guiding framework. We present the curriculum decisions that focus specifically on the adaption process from professional practice to the classroom context along with the theoretical underpinnings of the curriculum design decisions that went into the development of the P-Cubed classroom.

2. PLOSONE

   Predicting time to graduation at a large enrollment American university

   John M. Aiken, Riccardo De Bin, Morten Hjorth-Jensen, and Marcos D. Caballero

   PLOS ONE, Jul 2020

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   The time it takes a student to graduate with a university degree is mitigated by a variety of factors such as their background, the academic performance at university, and their integration into the social communities of the university they attend. Different universities have different populations, student services, instruction styles, and degree programs, however, they all collect institutional data. This study presents data for 160,933 students attending a large American research university. The data includes performance, enrollment, demographics, and preparation features. Discrete time hazard models for the time-to-graduation are presented in the context of Tinto’s Theory of Drop Out. Additionally, a novel machine learning method: gradient boosted trees, is applied and compared to the typical maximum likelihood method. We demonstrate that enrollment factors (such as changing a major) lead to greater increases in model predictive performance of when a student graduates than performance factors (such as grades) or preparation (such as high school GPA).

3. PRPER

   Thematic analysis of 18 years of physics education research conference proceedings using natural language processing

   Tor Ole B. Odden, Alessandro Marin, and Marcos D. Caballero

   Physical Review Physics Education Research, Jul 2020

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   We have used an unsupervised machine learning method called latent Dirichlet allocation (LDA) to thematically analyze all papers published in the Physics Education Research Conference Proceedings between 2001 and 2018. By looking at co-occurrences of words across the data corpus, this technique has allowed us to identify ten distinct themes or "topics" that have seen varying levels of prevalence in physics education research (PER) over time and to rate the distribution of these topics within each paper. Our analysis suggests that although all identified topics have seen sustained interest over time, PER has also seen several waves of increased interest in certain topics, beginning with initial interest in qualitative, theory-building studies of student understanding, which gave way to a focus on problem solving in the late 2000s. Since 2010 the field has seen a shift toward more sociocultural views of teaching and learning with a particular focus on communities of practice, student identities, and institutional change. Based on these results, we suggest that unsupervised text analysis techniques like LDA may hold promise for providing quantitative, independent, and replicable analyses of educational research literature.

4. PLOSONE

   Characterizing College Science Instruction: The Three-Dimensional Learning Observation Protocol

   Kinsey Bain, Rebecca L. Matz, Cori L. Fata-Hartley, Marcos D. Caballero, Diane Ebert-May, Sonia M. Underwood, Justin H. Carmel, Deborah G. Herrington, James T. Laverty, Erin M. Duffy, Jon R. Stoltzfus, Lydia Bender, Lynmarie A. Posey, Mark Urban-Lurain, Ryan L. Stowe, Ryan D. Sweeder, Stuart H. Tessmer, and Melanie M. Cooper

   PLOS ONE, Jul 2020

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   The importance of improving STEM education is of perennial interest, and to this end, the education community needs ways to characterize transformation efforts. Three-dimensional learning (3DL) is one such approach to transformation, in which core ideas of the discipline, scientific practices, and crosscutting concepts are combined to support student development of disciplinary expertise. We have previously reported on an approach to the characterization of assessments, the Three-Dimensional Learning Assessment Protocol (3D-LAP), that can be used to identify whether assessments have the potential to engage students in 3DL. Here we present the development of a companion, the Three-Dimensional Learning Observation Protocol (3D-LOP), an observation protocol that can reliably distinguish between instruction that has potential for engagement with 3DL and instruction that does not. The 3D-LOP goes beyond other observation protocols, because it is intended not only to characterize the pedagogical approaches being used in the instructional environment, but also to identify whether students are being asked to engage with scientific practices, core ideas, and crosscutting concepts. We demonstrate herein that the 3D-LOP can be used reliably to code for the presence of 3DL; further, we present data that show the utility of the 3D-LOP in differentiating between instruction that has the potential to promote 3DL from instruction that does not. Our team plans to continue using this protocol to evaluate outcomes of instructional transformation projects. We also propose that the 3D-LOP can be used to support practitioners in developing curricular materials and selecting instructional strategies to promote engagement in three-dimensional instruction.

5. PRPER

   Learning assistant approaches to teaching computational physics problems in a problem-based learning course

   Alanna Pawlak, Paul W. Irving, and Marcos D. Caballero

   Physical Review Physics Education Research, Jul 2020

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   An increasing number of introductory physics courses are seeking to incorporate "authentic practices," and a large area of focus in this trend is the incorporation of computational problems into the curriculum. These problems offer students an opportunity to engage with the programming practices and numerical problem-solving methods used by physicists. Understanding how instructors approach teaching such problems is essential for improving instruction and problem design. We conducted a phenomenographic study using semistructured interviews with undergraduate learning assistants in a problem-based introductory mechanics course that incorporates several computational problems. The learning assistants’ prior involvement as students, along with their relatively fewer experiences with programming and physics compared to the faculty instructors, give them a unique perspective on teaching in the course. We present here the results of our analysis: the identification of four approaches that learning assistants make take to teaching computational problems in this course. These approaches, programming focus, learning physics via computation focus, computation as a tool focus, and shifting perceptions of learning focus, provide a lens for understanding the different ways learning assistants perceive computation, the degree to which they take up course-intended learning goals surrounding computation, the factors that may impact the approaches they take, and how we might affect their approaches through training and support.

2019

1. PRPER

   Editorial: Focused Collection: Quantitative Methods in PER: A Critical Examination

   Alexis V. Knaub, John M. Aiken, and Marcos D. Caballero

   Physical Review Physics Education Research, Jul 2019

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2. PICUP: The Partnership for the Integration of Computation into Undergraduate Physics

   Marcos D. Caballero, Larry Engelhardt, Robert Hilborn, Marié Lopez Puerto, and Kelly Roos

   APS News, Jul 2019

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3. PRPER

   Physics computational literacy: An exploratory case study using computational essays

   Tor Ole B. Odden, Elise Lockwood, and Marcos D. Caballero

   Physical Review Physics Education Research, Jul 2019

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   Computation is becoming an increasingly important part of physics education. However, there are currently few theories of learning that can be used to help explain and predict the unique challenges and affordances associated with computation in physics. In this study, we adapt the existing theory of computational literacy, which posits that computational learning can be divided into material, cognitive, and social aspects, to the context of undergraduate physics. Based on an exploratory study of undergraduate physics computational literacy, using a newly developed teaching tool known as a computational essay, we have identified a variety of student practices, knowledge, and beliefs across these three aspects of computational literacy. We illustrate these categories with data collected from students who engaged in an initial implementation of computational essays in a 3rd-semester electricity and magnetism class. We conclude by arguing that this framework can be used to theoretically diagnose student difficulties with computation, distinguish educational approaches that focus on material vs cognitive aspects of computational literacy, and highlight the benefits and limitations of open-ended projects like computational essays to student learning.

4. EJP

   Design, Analysis, Tools, and Apprenticeship (DATA) Lab

   Kelsey Funkhouser, William Martinez, Rachel Henderson, and Marcos D. Caballero

   European Journal of Physics, Jul 2019

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   Recently in the United States, there have been several national calls to emphasise physics practices and skills within laboratory courses. In this paper, we describe the redesign and implementation of a two-course sequence of algebra-based physics laboratories at Michigan State University called the design, analysis, tools and apprenticeship (DATA) lab. The large-scale course transformation removes physics-specific content from the overall learning goals of the course and, instead, uses physics concepts to focus on specific laboratory practices and research skills that students can take into their future careers. Students in the DATA Lab engage in the exploration of physical systems to increase their understanding of experimental process, data analysis, collaboration, and scientific communication. In order to ensure our students are making progress toward the skills outlined in the course learning goals, we designed all of the assessments in the courses to evaluate their progress specific to these laboratory practices. Here, we will describe the structures, scaffolds, goals, and assessments of the course.

5. PRPER

   Identifying features predictive of faculty integrating computation into physics courses

   Nicholas T. Young, Grant Allen, John M. Aiken, Rachel Henderson, and Marcos D. Caballero

   Physical Review Physics Education Research, Jul 2019

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   Computation is a central aspect of 21st century physics practice; it is used to model complicated systems, to simulate impossible experiments, and to analyze mountains of data. Physics departments and their faculty are increasingly recognizing the importance of teaching computation to their students. We recently completed a national survey of faculty in physics departments to understand the state of computational instruction and the factors that underlie that instruction. The data collected from the faculty responding to the survey included a variety of scales, binary questions, and numerical responses. We then used random forest, a supervised learning technique, to explore the factors that are most predictive of whether a faculty member decides to include computation in their physics courses. We find that experience using computation with students in their research, or lack thereof and various personal beliefs to be most predictive of a faculty member having experience teaching computation. Interestingly, we find demographic and departmental factors to be less useful factors in our model. The results of this study inform future efforts to promote greater integration of computation into the physics curriculum as well as comment on the current state of computational instruction across the United States.

6. PRPER

   Modeling student pathways in a physics bachelor’s degree program

   John M. Aiken, Rachel Henderson, and Marcos D. Caballero

   Physical Review Physics Education Research, Jul 2019

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   Physics education research (PER) has used quantitative modeling techniques to explore learning, affect, and other aspects of physics education. However, these studies have rarely examined the predictive output of the models, instead focusing on the inferences or causal relationships observed in various data sets. This research introduces a modern predictive modeling approach to the PER community using transcript data for students declaring physics majors at Michigan State University. Using a machine learning model, this analysis demonstrates that students who switch from a physics degree program to an engineering degree program do not take the third semester course in thermodynamics and modern physics, and may take engineering courses while registered as a physics major. Performance in introductory physics and calculus courses, measured by grade as well as a students’ declared gender and ethnicity play a much smaller role relative to the other features included in the model. These results are used to compare traditional statistical analysis to a more modern modeling approach.

7. TPT

   PICUP: A Community of Teachers Integrating Computation into Undergraduate Physics Courses

   Marcos D. Caballero, Norman Chonacky, Larry Engelhardt, Robert C. Hilborn, Marie Puerto, and Kelly R. Roos

   The Physics Teacher, Jul 2019

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8. PERC

   Preliminary Analysis of Student-Identified Themes around Computation in High School Physics

   Theodore Bott, Daniel Weller, Marcos D. Caballero, and Paul W. Irving

   In 2019 Physics Education Research Conference Proceedings, Jul 2019
9. PERC

   How do previous coding experiences influence undergraduate physics students?

   Jacqueline Bumler, P. C. Hamerski, Marcos D. Caballero, and Paul W. Irving

   In 2019 Physics Education Research Conference Proceedings, Jul 2019
10. PERC

    A Longitudinal Exploration of Students’ Beliefs about Experimental Physics

    Rachel Henderson, Kelsey Funkhouser, and Marcos D. Caballero

    In 2019 Physics Education Research Conference Proceedings, Jul 2019
11. PERC

    Computational Essays and Computational Literacy at the University of Oslo

    Tor Ole B. Odden, and Marcos D. Caballero

    In 2019 Physics Education Research Conference Proceedings, Jul 2019
12. PERC

    Investigating Teacher Learning Goals Involving Computation in High School Physics

    Daniel Weller, Marcos D. Caballero, and Paul W. Irving

    In 2019 Physics Education Research Conference Proceedings, Jul 2019
13. PERC

    Using Machine Learning to Understand Physics Graduate School Admissions

    Nicholas T. Young, and Marcos D. Caballero

    In 2019 Physics Education Research Conference Proceedings, Jul 2019

2018

1. Labs are Necessary, and We Need to Invest in Them

   Marcos D. Caballero, Dimitri R. Dounas-Frazer, Heather J. Lewandowski, and MacKenzie R. Stetzer

   APS News, Jul 2018

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2. Integrating a Computational Perspective in Physics Courses

   Marcos D. Caballero, and Morten Hjorth-Jensen

   In New Trends in Physics Education Research, Jul 2018

   arXiv
3. PRPER

   Prevalence and nature of computational instruction in undergraduate physics programs across the United States

   Marcos D. Caballero, and Laura Merner

   Physical Review Physics Education Research, Jul 2018

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   A national survey of physics faculty was conducted to investigate the prevalence and nature of computational instruction in physics courses across the United States. 1246 faculty from 357 unique institutions responded to the survey. The results suggest that more faculty have some form of computational teaching experience than a decade ago, but it appears that this experience does not necessarily translate to computational instruction in undergraduate students’ formal course work. Further, we find that formal programs in computational physics are absent from most departments. A majority of faculty do report using computation on homework and in projects, but few report using computation with interactive engagement methods in the classroom or on exams. Specific factors that underlie these results are the subject of future work, but we do find that there is a variation on the reported experience with computation and the highest degree that students can earn at the surveyed institutions.

4. SCIADV

   Evaluating the extent of a large-scale transformation in gateway science courses

   Rebecca L. Matz, Cori L. Fata-Hartley, Lynmarie A. Posey, James T. Laverty, Sonia M. Underwood, Justin H. Carmel, Deborah G. Herrington, Ryan L. Stowe, Marcos D. Caballero, Diane Ebert-May, and Melanie M. Cooper

   Science Advances, Jul 2018

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   We evaluate the impact of an institutional effort to transform undergraduate science courses using an approach based on course assessments. The approach is guided by A Framework for K-12 Science Education and focuses on scientific and engineering practices, crosscutting concepts, and core ideas, together called three-dimensional learning. To evaluate the extent of change, we applied the Three-dimensional Learning Assessment Protocol to 4 years of chemistry, physics, and biology course exams. Changes in exams differed by discipline and even by course, apparently depending on an interplay between departmental culture, course organization, and perceived course ownership, demonstrating the complex nature of transformation in higher education. We conclude that while transformation must be supported at all organizational levels, ultimately, change is controlled by factors at the course and departmental levels.

5. SCI ED

   Fostering students’ epistemic agency through the co-configuration of moth research

   David Stroupe, Marcos D. Caballero, and Peter White

   Science Education, Jul 2018

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   We argue that students should take on roles as epistemic agents—those who shape knowledge production and practices of a community. In this study, the research team—a science educator and two scientists—worked with a sixth-grade teacher to provide 90 students with opportunities to take up epistemic agency over a 22-day unit about moth ecology. We used cultural historical activity theory (CHAT) to analyze the co-configuration of activity. During planning, tensions arose among the research team around how and why to position students as epistemic agents, while still attending to meaningful science questions. During instruction, students prompted the constant negotiation of epistemic roles and practices as they acted on shifting agentic participation structures.

6. PRPER

   Analysis of the most common concept inventories in physics: What are we assessing?

   James T. Laverty, and Marcos D. Caballero

   Physical Review Physics Education Research, Jul 2018

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   Assessing student learning is a cornerstone of educational practice. Standardized assessments have played a significant role in the development of instruction, curricula, and educational spaces in college physics. However, the use of these assessments to evaluate student learning is only productive if they continue to align with our learning goals. Recently, there have been calls to elevate the process of science ("scientific practices") to the same level of importance and emphasis as the concepts of physics ("core ideas" and "crosscutting concepts"). We use the recently developed Three-Dimensional Learning Assessment Protocol to investigate how well the most commonly used standardized assessments in introductory physics (i.e., concept inventories) align with this modern understanding of physics education’s learning goals. We find that many of the questions on concept inventories do elicit evidence of student understanding of core ideas, but do not have the potential to elicit evidence of scientific practices or crosscutting concepts. Furthermore, we find that the individual scientific practices and crosscutting concepts that are assessed using these tools are limited to a select few. We discuss the implications that these findings have on designing and testing curricula and instruction both in the past and for the future.

7. PRPER

   Development of the Modes of Collaboration framework

   Alanna Pawlak, Paul W. Irving, and Marcos D. Caballero

   Physical Review Physics Education Research, Jul 2018

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   Group work is becoming increasingly common in introductory physics classrooms. Understanding how students engage in these group learning environments is important for designing and facilitating productive learning opportunities for students. We conducted a study in which we collected video of groups of students working on conceptual electricity and magnetism problems in an introductory physics course. In this setting, students needed to negotiate a common understanding and coordinate group decisions in order to complete the activity successfully. We observed students interacting in several distinct ways while solving these problems. Analysis of these observations focused on identifying the different ways students interacted and articulating what defines and distinguishes them, resulting in the development of the modes of collaboration framework. The modes of collaboration framework defines student interactions along three dimensions: social, discursive, and disciplinary content. This multidimensional approach offers a unique lens through which to consider group work and provides a flexibility that could allow the framework to be adapted for a variety of contexts. We present the framework and several examples of its application here.

8. PERC

   What counts in laboratories: toward a practice-based identity survey

   Kelsey Funkhouser, Marcos D. Caballero, Paul W. Irving, and Vashti Sawtelle

   In 2018 Physics Education Research Conference Proceedings, Jul 2018
9. PERC

   Denoting and Comparing Leadership Attributes and Behaviors in Group Work

   Kristina Griswold, Daryl McPadden, Marcos D. Caballero, and Paul W. Irving

   In 2018 Physics Education Research Conference Proceedings, Jul 2018
10. PERC

    The difficulties associated with integrating computation into undergraduate physics

    Ashleigh Leary, Paul W. Irving, and Marcos D. Caballero

    In 2018 Physics Education Research Conference Proceedings, Jul 2018
11. PERC

    Feedback as a mechanism for improving students scientific communication skills

    Daryl McPadden, P. C. Hamerski, Marcos D. Caballero, and Paul W. Irving

    In 2018 Physics Education Research Conference Proceedings, Jul 2018
12. PERC

    How computation can facilitate sensemaking about physics: A case study

    Odd Petter Sand, Tor O.B. Odden, Christine Lindstrøm, and Marcos D. Caballero

    In 2018 Physics Education Research Conference Proceedings, Jul 2018
13. PERC

    Examining the relationship between student performance and video interactions

    Robert Solli, John M. Aiken, Rachel Henderson, and Marcos D. Caballero

    In 2018 Physics Education Research Conference Proceedings, Jul 2018

2017

1. Taking A Scientific Approach To Physics Education

   Marcos D. Caballero

   Student Journal of Physics, Jul 2017

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2. EJP

   P^3: a practice focused learning environment

   Paul W. Irving, Michael J. Obsniuk, and Marcos D. Caballero

   European Journal of Physics, Jul 2017
3. PRPER

   Assessing learning outcomes in middle-division classical mechanics: The Colorado Classical Mechanics and Math Methods Instrument

   Marcos D. Caballero, Leanne Doughty, Anna M. Turnbull, Rachel E. Pepper, and Steven J. Pollock

   Physical Review Physics Education Research, Jul 2017
4. PERC

   Expanding the PICUP community of practice

   Paul W. Irving, and Marcos D. Caballero

   In 2017 Physics Education Research Conference Proceedings, Jul 2017
5. PERC

   Examining Thematic Variation in a Phenomenographical Study on Computational Physics

   Nathaniel Hawkins, Michael J. Obsniuk, Paul W. Irving, and Marcos D. Caballero

   In 2017 Physics Education Research Conference Proceedings, Jul 2017

2016

1. PLOSONE

   Characterizing College Science Assessments: The Three-Dimensional Learning Assessment Protocol

   James T. Laverty, Sonia M. Underwood, Rebecca L. Matz, Lynmarie A. Posey, Justin H. Carmel, Marcos D. Caballero, Cori L. Fata-Hartley, Diane Ebert-May, Sarah E. Jardeleza, and Melanie M. Cooper

   PLOS ONE, Jul 2016
2. PERC

   Methods for Analyzing Pathways through a Physics Major

   John M. Aiken, and Marcos D. Caballero

   In 2016 Physics Education Research Conference Proceedings, Jul 2016

2015

1. Challenge faculty to transform STEM learning

   Melanie M. Cooper, Marcos D. Caballero, Diane Ebert-May, Cori L. Fata-Hartley, Sarah E. Jardeleza, Joseph S. Krajcik, James T. Laverty, Rebecca L. Matz, Lynmarie A. Posey, and Sonia M. Underwood

   Science, Jul 2015
2. PRPER

   Educational transformation in upper-division physics: The Science Education Initiative model, outcomes, and lessons learned

   Stephanie V. Chasteen, Bethany Wilcox, Marcos D. Caballero, Katherine K. Perkins, Steven J. Pollock, and Carl E. Wieman

   Physical Review Special Topics – Physics Education Research, Jul 2015
3. PRPER

   Development and uses of upper-division conceptual assessments

   Bethany R. Wilcox, Marcos D. Caballero, Charles Baily, Homeyra Sadaghiani, Stephanie V. Chasteen, Qing X. Ryan, and Steven J. Pollock

   Physical Review Special Topics – Physics Education Research, Jul 2015
4. EJP

   Unpacking students’ use of mathematics in upper-division physics: where do we go from here?

   Marcos D. Caballero, Bethany R. Wilcox, Leanne Doughty, and Steven J. Pollock

   European Journal of Physics, Jul 2015
5. PERC

   Computation across the curriculum: What skills are needed?

   Marcos D. Caballero

   In 2015 Physics Education Research Conference Proceedings, Jul 2015
6. PERC

   Troubleshooting Formative Feedback in P^3 (A group-based learning environment)

   Paul W. Irving, Vashti Sawtelle, and Marcos D. Caballero

   In 2015 Physics Education Research Conference Proceedings, Jul 2015
7. PERC

   Developing the Next Generation of Physics Assessments

   James T. Laverty, Melanie M. Cooper, and Marcos D. Caballero

   In 2015 Physics Education Research Conference Proceedings, Jul 2015
8. PERC

   A Case Study: Novel Group Interactions through Computational Physics

   Michael J. Obsniuk, Paul W. Irving, and Marcos D. Caballero

   In 2015 Physics Education Research Conference Proceedings, Jul 2015
9. PERC

   Identification of a shared answer-making game in group context

   Alanna Pawlak, Paul W. Irving, and Marcos D. Caballero

   In 2015 Physics Education Research Conference Proceedings, Jul 2015
10. PERC

    Student Ideas around Vector Decomposition in the Upper-Division

    Anna Turnbull, Leanne Doughty, Vashti Sawtelle, and Marcos D. Caballero

    In 2015 Physics Education Research Conference Proceedings, Jul 2015

2014

1. PRPER

   Uncovering the hidden meaning of cross-curriculum comparison results on the Force Concept Inventory

   Lin Ding, and Marcos D. Caballero

   Physical Review Special Topics – Physics Education Research, Jul 2014
2. AJP

   Bridging physics and biology teaching through modeling

   Anne-Marie Hoskinson, Brian A. Couch, Benjamin M. Zwickl, Kathleen A. Hinko, and Marcos D. Caballero

   American Journal of Physics, Jul 2014
3. AJP

   A model for incorporating computation without changing the course: An example from middle-division classical mechanics

   Marcos D. Caballero, and Steven J. Pollock

   American Journal of Physics, Jul 2014
4. TPT

   Integrating Numerical Computation into the Modeling Instruction Curriculum

   Marcos D. Caballero, John B. Burk, John M. Aiken, Brian D. Thoms, Scott S. Douglas, Erin M. Scanlon, and Michael F. Schatz

   The Physics Teacher, Jul 2014
5. PERC

   Student Use of a Single Lecture Video in a Flipped Introductory Mechanics Course

   John M. Aiken, Shih-Yin Lin, Scott S. Douglas, Edwin F. Greco, Brian D. Thoms, Marcos D. Caballero, and Michael F. Schatz

   In 2014 Physics Education Research Conference Proceedings, Jul 2014
6. PERC

   Rubric Design for Separating the Roles of Open-Ended Assessments

   Leanne Doughty, and Marcos D. Caballero

   In 2014 Physics Education Research Conference Proceedings, Jul 2014
7. PERC

   Peer Evaluation of Video Lab Reports in a Blended Introductory Physics Course

   Scott S. Douglas, Shih-Yin Lin, John M. Aiken, Edwin F. Greco, Brian D. Thoms, Marcos D. Caballero, and Michael F. Schatz

   In 2014 Physics Education Research Conference Proceedings, Jul 2014
8. PERC

   Engaging Physics Faculty in Course Transformation

   James T. Laverty, Stuart H. Tessmer, Melanie M. Cooper, and Marcos D. Caballero

   In 2014 Physics Education Research Conference Proceedings, Jul 2014
9. PERC

   Peer Evaluation of Video Lab Reports in an Introductory Physics MOOC

   Shih-Yin Lin, Scott S. Douglas, John M. Aiken, Edwin F. Greco, Brian D. Thoms, Marcos D. Caballero, and Michael F. Schatz

   In 2014 Physics Education Research Conference Proceedings, Jul 2014
10. PERC

    Just Math: A new epistemic frame

    Wolf. Stephen F., Leanne Doughty, Paul W. Irving, Eleanor C. Sayre, and Marcos D. Caballero

    In 2014 Physics Education Research Conference Proceedings, Jul 2014

2013

1. PRPER

   Analytic framework for students’ use of mathematics in upper-division physics

   Bethany R. Wilcox, Marcos D. Caballero, Daniel A. Rehn, and Steven J. Pollock

   Physical Review Special Topics – Physics Education Research, Jul 2013
2. How can we improve problem solving in undergraduate biology?: Applying lessons from 30 years of physics education research

   Anne-Marie Hoskinson, Marcos D. Caballero, and Jennifer K. Knight

   Cell Biology Education - Life Science Education, Jul 2013
3. PERC

   The Initial State of Students Taking an Introductory Physics MOOC

   John M. Aiken, Shih-Yin Lin, Scott S. Douglas, Edwin F. Greco, Brian D. Thoms, Marcos D. Caballero, and Michael F. Schatz

   In 2013 Physics Education Research Conference Proceedings, Jul 2013
4. PERC

   Assessing Student Learning in Middle-Division Classical Mechanics/Math Methods

   Marcos D. Caballero, and Steven J. Pollock

   In 2013 Physics Education Research Conference Proceedings, Jul 2013

2012

1. PRPER

   Colorado Upper-Division Electrostatics diagnostic: A conceptual assessment for the junior level

   Stephanie V. Chasteen, Rachel E. Pepper, Marcos D. Caballero, Steven J. Pollock, and Katherine K. Perkins

   Physical Review Special Topics – Physics Education Research, Jul 2012
2. PRPER

   Implementing and assessing computational modeling in introductory mechanics

   Marcos D. Caballero, Matthew A. Kohlmyer, and Michael F. Schatz

   Physical Review Special Topics – Physics Education Research, Jul 2012
3. AJP

   Comparing large lecture mechanics curricula using the Force Concept Inventory: A five thousand student study

   Marcos D. Caballero, Edwin F. Greco, Eric R. Murray, Keith R. Bujak, M. Jackson Marr, Richard Catrambone, Matthew A. Kohlmyer, and Michael F. Schatz

   American Journal of Physics, Jul 2012
4. PERC

   Understanding Student Computational Thinking with Computational Modeling

   John M. Aiken, Marcos D. Caballero, Scott S. Douglas, John B. Burk, Erin M. Scanlon, Brian D. Thoms, and Michael F. Schatz

   In 2012 Physics Education Research Conference Proceedings, Jul 2012
5. PERC

   ACER: A Framework on the Use of Mathematics in Upper-division Physics

   Marcos D. Caballero, Bethany R. Wilcox, Rachel E. Pepper, and Steven J. Pollock

   In 2012 Physics Education Research Conference Proceedings, Jul 2012
6. PERC

   Upper-division Student Understanding of Coulomb’s Law: Difficulties with Continuous Charge Distributions

   Bethany R. Wilcox, Marcos D. Caballero, Rachel E. Pepper, and Steven J. Pollock

   In 2012 Physics Education Research Conference Proceedings, Jul 2012

2011

1. PERC

   Fostering Computational Thinking

   Marcos D. Caballero, Matthew A. Kohlmyer, and Michael F.

   In 2011 Physics Education Research Conference Proceedings, Jul 2011
2. Comparing the Matter and Interactions Curriculum with a Traditional Physics Curriculum: A Think Aloud Study

   Keith R. Bujak, Marcos D. Caballero, Michael F. Schatz, M. Jackson Marr, and Richard Catrambone

   In 2011 AERA Conference Proceedings, Jul 2011

2009

1. PRPER

   Tale of two curricula: The performance of 2000 students in introductory electromagnetism

   Matthew A. Kohlmyer, Marcos D. Caballero, Richard Catrambone, Ruth W. Chabay, Lin Ding, Mark P. Haugan, M. Jackson Marr, Bruce A. Sherwood, and Michael F. Schatz

   Physical Review Special Topics – Physics Education Research, Jul 2009
2. Placing the Deep Impact Mission into context: Two decades of observations of 9P/Tempel 1 from McDonald Observatory

   Anita L. Cochran, Edwin S. Barker, Marcos D. Caballero, and Judit Györgey-Ries

   Icarus, Jul 2009