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REU 2015 Project Descriptions

CiDER faculty at North Dakota State University engage in discipline-based education research at the undergraduate level in biology, biochemistry, chemistry, math, and physics. These faculty have compiled brief REU project descriptions across four broad foci, (1) Visual representations and reasoning, (2) Deconstructing assessments and instructional practices, (3) Math in STEM, and (4) Student reasoning and metacognition. Each REU student will work closely with the associated project mentor(s), taking ownership of a portion of the research. As part of your application and to help ensure a good research experience this summer, we will ask you to identify your top 3 project choices.

Focus 1: Visual representations and reasoning

Project 1.1. Breaking the cycle: Using student-constructed models of biogeochemical cycling to reveal content (and system) understanding
Faculty mentor: Jenni Momsen

Pedagogical approaches that engage students in the active construction and evaluation of conceptual models may support students’ acquisition of deep content knowledge and systems thinking skills, both critical skills in contemporary ecology. The process of creating conceptual models of biogeochemical cycling, for example, requires that students actively select specific pools and describe how matter moves between pools, thus revealing content understanding. This project will use existing assessment data to characterize biology students’ content understanding and reasoning skills in the context of carbon cycling. Specific questions may include:

1. What (eco)system structures and processes do students identify when modeling carbon cycling?
2. How do students organize those structures and processes?
3. How do students predict and reason about the effects of a perturbation on the ecosystem?

At the end of this research experience, an REU student will be able to:
- Characterize student’s content knowledge and reasoning skills in relation to carbon cycling
- Maintain secure data storage
- Complete basic data analysis in R
- Synthesize literature, and
- Present findings to a broad scientific audience.

Project 1.2. Using student-generated drawings to uncover content understanding in human anatomy and physiology
Faculty mentors: Jenni Momsen, Jeff Boyer
Graduate mentor: Tara Slominski

Human Anatomy & Physiology (HA&P) has a reputation of being challenging, often referred to as a “weeder” course. According to literature, students attribute this difficulty to the nature of HA&P, a discipline filled with abstract concepts that are hard to visualize and system level relationships that require a mechanistic understanding. We also know that students have a more difficult time learning human physiology than anatomy. In order to improve HA&P curriculum and provide students with better learning opportunities, we need to have a better understanding of how and why students are struggling in this course. Students will work closely with a graduate student and faculty member to code and analyze student drawings from an HA&P course. Specifically, this project will target 3 questions:

1. Prior to instruction on neuron physiology, to what extent do HA&P students think neurons have to touch to communicate?
2. Is it possible to elucidate the alternative idea of “Touching” with auditorium friendly assessments?
3. What can we learn about the presence of the “Contact” p-prim from analyzing written assessments in HA&P?

Through this research experience, students will:
- Develop skills in data analysis such as creating and applying rubrics and statistical analyses
- Learn qualitative and quantitative data techniques
- Gain classroom observational skills and improve classroom assessments
- Develop a rich understanding of Human Anatomy and Physiology content for their particular project (some familiarity of Anatomy and Physiology is preferred.)

Project 1.3. Recognizing student difficulties in Human Anatomy and Physiology
Faculty mentors: Lisa Montplaisir, Mary Jo Kenyon

Students often express more frustration when learning about abstract body systems than those containing large and familiar organ structures. This idea coincides with literature suggesting students struggle more with concepts that they can’t easily visualize. Literature also tells us that students have a more difficult time learning human physiology than they do human anatomy. A better understanding of these student difficulties could result in better curriculum design and a better learning experience for the student. This research will ascertain the prevalence of these difficulties in a real Human Anatomy and Physiology course. Students will work closely with a graduate student and faculty member to analyze a series of assessments. The analyses will be framed by two guiding questions: Do students struggle more with some body systems than others? Do students struggle more with physiology content than anatomical?

Through this research experience, students will:
- Develop skills in data analysis such as creating and applying rubrics and statistical analyses
- Gain a rich understanding of Human Anatomy and Physiology content for their particular project (Some familiarity of Anatomy and Physiology is preferred.)

Members of the research team will be expected to:
- Work independently and as part of a team to analyze figures
- Read research articles on visualizations and participate in a weekly discussion of the research
- Present their research progress in lab group meetings
- Synthesize research findings in the form of a scientific poster to be presented at the conclusion of the program

Project 1.4. A picture is worth a thousand data points:  Developing visual literacy in the molecular life sciences
Faculty mentor: Erika G. Offerdahl
Graduate mentor: Jessie Arneson

Visualizations (e.g. graphs, diagrams) are ubiquitous in science. As scientists, we use them to communicate complex data sets, processes, and relationships to one another, our students, and the public. National calls to transform science instruction underscore the need to develop students’ understanding of the tools and disciplinary practices of scientists.  Visual thinking – the ability to interpret and make sense of visualizations – is one such disciplinary practice that, to date, is seldom an explicit learning outcome of undergraduate science curricula.  Moreover, while science instruction makes extensive use of visualizations in textbooks, simulations, and lecture slides, it is unclear the degree to which such visualizations support development of students’ visual thinking skills.  The goal of this study is to (1) create instructional materials that scaffold the development of visual thinking skills and (2) analyze performance data to determine the effectiveness of these materials.  

Members of the visualization team will benefit from the experience by:
- Deepening their conceptual understanding of molecular biology and biochemistry
- Systematically categorizing or “coding” textbook visualizations using an established coding scheme 
- Developing skills in creating and querying Access databases 
- Applying basic descriptive statistics to characterize textbook visualizations

Members of the visualization team will be expected to:
- Work independently and as part of a team to create instructional materials and analyze student performance data
- Read research articles on visualization and participate in weekly discussion of the research
- Present their research progress in lab group meeting at least twice during the summer
- Synthesize research findings in the form of a scientific poster to be presented at the conclusion of the program.

Focus 2: Deconstructing assessments and instructional practices

Project 2.1. Will this be on the test? Characterizing the cognitive skills, conceptual understanding, and disciplinary practices routinely assessed in biology
Faculty mentors: Jenni Momsen, Lisa Montplaisir, Erika Offerdahl

Assessment drives learning is a refrain that echoes through many colleges and universities, wherein students selectively study and learn the content and skills they believe critical to passing an exam. It follows that to understand the cognitive skills and content understanding students develop as a result of their undergraduate science major, we must turn our attention to assessments and the nature of the tasks we routinely use to assess student learning. This project will use established coding frames and coding rubrics created de novo to characterize assessments drawn from across the biology major’s curriculum. Specific questions may include:

1. What cognitive levels are routinely assessed in introductory versus upper division courses?
2. What biological skills are students expected to become proficient with?
3. How do assessments change in response to faculty professional development?

At the end of this research experience, students will be able to:
- Use multiple coding schemes to describe assessment items,
- Create and maintain data storage,
- Complete basic data analysis using R,
- Synthesize relevant literature, and
- Present findings to a broad scientific audience.

Project 2.2. Digital exhaust: Predicting performance from online interactions 
Faculty mentors: Erika Offerdahl, Jeff Boyer

When students interact with online tools, such as a learning management system (e.g., Blackboard, Moodle, D2L, etc.), they leave behind a digital “exhaust” that is collected in access logs.  Thus, it is possible to summarize and analyze patterns of student behavior based on these documented timestamps.  It is likely that successful students exhibit different access patterns than non-successful students.  Instructors may benefit from understanding how and when students interact online.  In essence, a pattern of interaction with an online resource or tool may provide information to instructors that indicate a need to intervene with students who are not performing adequately within a course. Thus, the purpose of this research is to identify students’ online interaction patterns and to determine if these can be used as an intervention tool for struggling students (i.e., an early warning system).  The research questions that guide this work are:

- To what degree does interaction with online resources predict course performance?
- Could interaction with online resources serve as an early warning system for students who need intervention?

At the end of this research experience, students will be able to:
- “Clean” collected data in preparation for data analysis
- Analyze and summarize data using R and other statistical tools
- Test hypotheses against data sets
- Develop predictive models for student performance
- Present findings based on available evidence.

Focus 3: Math in STEM

Project 3.1. Interpreting multi-variable expressions in Physics: Patterns in student reasoning
Faculty mentor: Mila Kryjevskaia

Many physics instructors would agree that mathematics is an essential element of physics problem solving.  However, the way mathematics is used is physics courses is distinctly different from the way it is taught.  In physics, conceptual understanding of a specific phenomenon is imbedded in a symbolic form.  As a result, without a robust understanding of physics concepts, simple manipulation of symbols in mathematical expressions is often inappropriate and unhelpful.  In the context of a math course, for example, it may be appropriate to reason that, for the given relationship y = x/a, if x increases, y must also increase; in such cases, it is commonly assumed that variables (e.g., x and y) and constants (e.g., positive a) have been clearly established.  However, a direct mapping of the same reasoning in the context of physics (namely, for the given relationship f= v/l, if the propagation speed v increases, frequency f must also increase) leads to an erroneous conclusion.  In order to correctly interpret the relationship among the wavelength, frequency, and propagation speed, student must possess a conceptual understanding of the propagation speed and recognize that v could be change only by changing medium (in non-dispersive media).  Therefore a modification to a source (or f) affects the wavelength rather than the speed.  Similarly, many students think that the capacitance will always change if the potential difference between the capacitor’s plates is changed.  In this investigation we will probe the extent to which students’ incorrect reasoning approaches could be altered by making explicit connections during instruction between the treatments of multi-variable expressions in several contexts, such as waves and electrostatics.  We will also examine students’ ability to transfer their understanding between these contexts.

Research assistants will (1) examine student abilities to interpret and analyze multi-variable expressions in introductory physics courses, (2) identify pattern in student reasoning, (3) draw parallels between various contexts, and (4) discuss implications for instruction.

Project 3.2. Investigating the interplay of students’ mathematics and physics thinking
Faculty mentor: Warren Christensen

Despite four or more semesters devoted to learning calculus, linear algebra, and differential equations in mathematics classrooms, students often encounter substantial challenges when asked to perform physics tasks that require the use of what should be learned skills from math. This project will further develop investigations into students thinking about mathematics within the context of middle-division of math and the upper-division of physics classes. Topics of interest include investigations into students understanding of linear algebra concepts like matrix multiplication after having used those skills in a first-semester quantum mechanics course, and concepts of coordinate systems in the context of electricity and magnetism. Conducting research at the upper-division necessarily requires a focus on qualitative research due to small number of students typically enrolled in upper-division physics course. The REU student on this project, will analyze previously collected interview data to better understand students nuanced thinking about their mathematical understanding. The student may also participate in conducting interviews among undergraduates, graduate students and, potentially, physics faculty.

Project 3.3. Are you speaking my language?: Contextual sensitivity of graphical skills in the domains of physics and biology
Faculty mentors: Warren Christensen, Jenni Momsen
Postdoc mentor: La Toya Kissoon-Charles

This project will investigate students in an Introductory Physics for Life Sciences  (IPLS) course and their ability to read and interpret graphs in the context of physics and biology. It’s well known in the Physics Education Literature that students struggle to interpret kinematics graphs. IPLS students often struggle with physics due to a lack of mathematics skills, but it’s not clear to what extent students are struggling with the mathematics and/or the physics of the questions. It may be that IPLS students (who are primarily Life Science Majors) would be more successful at interpreting a graph if it’s within a familiar domain, such as Biological Sciences. The hypothesis we are testing is to what extent does a question in the context of biology make graphical analysis easier for students to answer correctly when compared to an analogous question in the context of physics. 

The researcher on this project will be able to:
- Analyze and categorize students’ written responses
- Develop and test hypotheses
- Develop new questions for future study
- Make and support claims from the data collected.

Focus 4: Student reasoning and metacognition

Project 4.1. Confirmation Bias in Science: Investigation of student reasoning in physics courses
Faculty mentor: Mila Kryjevskaia

The term "confirmation bias" refers to a tendency to favor evidence that confirms specific preconceived notions, believes, expectations, or even hypothesis at hand. "When men wish to construct or support a theory, how they torture facts into their service!" (Mackay). Understanding the difference between (1) impartially interpreting data in order to arrive at an unbiased conclusion and (2) selectively interpreting data to justify a specific conclusion is particularly important for science and engineering students. However, many introductory physics student responses to a variety of tasks suggest that students tend to apply both thinking schemas when presented with an unfamiliar situation. While one schema involves an unbiased and systematic analysis of a presented situation, the other reveals reasoning steps that lead to an intuitive answer that is perhaps more intuitively appealing to a student. This project focuses on probing whether the latter reasoning pattern is consistent with the confirmation bias. 

Project 4.2. Answer first: Applying heuristic-analytic theory of reasoning to examine student intuitive thinking in the context of physics
Faculty mentor: Mila Kryjevskaia

This study is motivated by the emerging body of evidence that suggests that student conceptual and reasoning competence demonstrated on one task often fails to be exhibited on another.  Indeed, even after instruction specifically designed to address student conceptual and reasoning difficulties identified by rigorous research, many undergraduate physics students fail to build reasoning chains from fundamental principles even though they possess required knowledge and skills to do so.  Instead, they often rely on a variety of intuitive reasoning strategies.  In this study, we have developed a methodology that allows for the disentanglement of student conceptual understanding and reasoning approaches.  We then apply heuristic-analytic theory of reasoning in order to account for, in a mechanistic fashion, the observed inconsistencies in student responses.  We argue that efforts to improve student metacognition, which serves to regulate the conflict between intuitive and analytical reasoning, are likely to lead to improved student reasoning.

Project 4.3. Students’ conceptual understanding of fundamental chemistry concepts
Faculty mentor: James Nyachwaya

Conceptual understanding in chemistry is a goal that many instructors have for their courses and students. One way of measuring the level of conceptual understanding is through assessment. Research in chemistry education has consistently shown that while most students show mastery of facts and memorized procedures, they struggle to demonstrate true, conceptual understanding. Through student responses to open ended questions, we seek to characterize students’ conceptual understanding of basic, fundamental chemistry concepts. Our data are drawn from a general chemistry course.

Research Question:
What is the nature of general chemistry students’ conceptual understanding of fundamental concepts such as the particulate nature of matter?

In the course of the research experience, participants will:
- Synthesize literature on conceptual understanding in chemistry,
- Analyze student data to determine the nature of understanding,
- Synthesize research findings in the form of a scientific poster to be presented at the conclusion of the program, and
- Present their research progress in lab group meetings.

Student Focused. Land Grant. Research University.

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Last Updated: Saturday, November 08, 2014 10:04:09 PM