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An open call on our campus to physics majors yielded seven students with varied backgrounds in astronomy and no experience with research. This qualitative case study provided insights into the challenges and successes of each group as they participated in the thirteen-week short course on RV Tauri variables created by Michael Fitzgerald. Student teams met weekly to collaborate with one another, the local mentor (author), and Dr. Fitzgerald. Observations in B, V, i, and z wavebands were collected via remote telescope network over a two week period and analyzed using Python. Student teams determined the period of variablility and estimated the distance using empirically-derived period-luminosity relationships. Throughout the process students wrestled with the nature of science and scientific inquiry, generating several questions. Students initially struggled to appreciate the significance of the results, likely a consequence of myopic focus on calculation. Implications for mentoring teams in astronomy research are presented. &amp;nbsp;&amp;nbsp;

AAPT WM 21

Mentoring Undergraduates Teams in Variable Star Research

case study

mentoring

variable stars

The 2020 AAPT Virtual Summer Meeting brought together physics educators from around the globe to learn about the latest in physics theory, research methodology and education from leaders in their field. The program featured plenary speakers, sessions, workshops and many special activities.

For more information please visit the 2020 AAPT Virtual Summer Meeting page at: https://www.aapt.org/Conferences/SM2020/index.cfm.


AAPT SM 20

The 2020 AAPT Virtual Summer Meeting brought together physics educators from around the globe to learn about the latest in physics theory, research methodology and education from leaders in their field. 

An open call on our campus to physics majors yielded seven students with varied backgrounds in astronomy and no experience with research. This qualitative case study provided insights into the challenges and successes of each group as they participated in the thirteen-week short course on RV Tauri variables created by Michael Fitzgerald. Student teams met weekly to collaborate with one another, the local mentor (author), and Dr. Fitzgerald. Observations in B, V, i, and z wavebands were collected via remote telescope network over a two week period and analyzed using Python. Student teams determined the period of variablility and estimated the distance using empirically-derived period-luminosity relationships. Throughout the process students wrestled with the nature of science and scientific inquiry, generating several questions. Students initially struggled to appreciate the significance of the results, likely a consequence of myopic focus on calculation. Implications for mentoring teams in astronomy research are presented. &nbsp;&nbsp;

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Tests of scientific reasoning have been around since the 1970’s, including the well-known two-tiered Classroom Test of Scientific Reasoning (CTSR) by Lawson. However, some of the questions asked on CTSR are specific to benchtop science experiments, and modern psychometric tools had not been invented to thoroughly test the test. Starting from a large pool of test items, the 20 item MSU Formal Reasoning Test (FORT) was iteratively developed. This one tier test covers the following concepts: control of variables, hypothesis testing, correlational reasoning, proportional reasoning, and probability. The final version of the FORT was given to 240 students, and item response theory (IRT) analysis was performed on each question, using a 3-P model.&nbsp; In this talk, I will discuss several questions on the FORT and their associated IRT curves. Additionally, I will share results of the FORT for samples of physics and astronomy students.&nbsp;

Testing Formal Reasoning Skills: An Updated Approach

This study investigated the effects of introducing computational activities to a general education astronomy course taught using active learning techniques. Computation is an important active learning tool for developing understanding of concepts, connecting concepts with formulae, and associating science with prediction. Spreadsheet based computational exercises were tied to lecture-tutorials, think-pair-share activities, and group worksheets. These exercises were completed in a collaborative environment. The results of this curriculum modification are discussed, along with reflections on the factors leading to the introduction of computational activities, factors that supported the change, and barriers faced while implementing this change. These findings are compared with results from other case studies of instructional change and theories of adoption. Student learning pre to post was measured with the TOAST and LPCI, and qualitative data was collected in the form of student surveys to investigate student learning, attitudes toward computational exercises, and overall perceptions of the course.

Introduction of Computational Activities to a General Education Astronomy Course

Students’ sense of belonging in science has been identified as a predictor for students’ motivation, self-efficacy, and persistence in the field—especially for historically underrepresented students. In this research, we explore the various contributors and potential barriers to students’ sense of belonging as it applies to an introductory general education astronomy labs. We collected a number of attitudinal surveys from lab students spanning between Spring 2018 to Spring 2020. Through the use of iterative thematic coding, we have developed a set of themes based on student-reported contributors and barriers to their sense of belonging in a scientific environment. This study is being conducted at San Francisco State University; a Hispanic-serving institution and one of the most diverse large universities in the country. Through this research, we hope to give further voice to a population of students that may not yet be well represented in the current literature.

Students' Sense of Belonging in Introductory Astronomy Labs

Introductory astronomy courses are popular as undergraduate electives and as free choice learning experiences, currently delivered as Massive Open Online Courses. Research has shown that utilizing writing assignment in science courses are important to make learner thinking visible and help improve science reasoning. We will present a suite of tools and strategies, iteratively revised through our research, that are being used to improve engagement and writing in several astronomy MOOCs. We also will present new online tools being developed to identify fake science online. These tools utilize machine learning and are trained by to distinguish reliable and fake ideas in online articles specially about controversial topics such as climate change and evolution. Additionally, another tool is being developed to give computer generated feedback on student writing to improve scientific reasoning and support iterative instructor feedback in introductory astronomy courses. All tools will be available broadly to instructors and online.

Tools to Improve Writing, Thinking, and Reasoning in Astronomy Courses

The origin of the Universe is something that people have pondered for thousands of years. As evidence has mounted, the Big Bang theory has become the consensus scientific model. Much of this same evidence refutes opposing theories such as the earlier Steady State model or the often-held conception of an exploding ball of matter. High school students often have difficulty distinguishing between these competing explanatory models. Also, the NGSS for high school includes the nature of and evidence for the Big Bang, providing students with a rich opportunity to explore, with the help of a scaffold, the connections between evidence and competing models about the origins of the Universe. This presentation will include the development of the Origins of the Universe build-a-MEL scaffold and data from ongoing analyses.

The Origins build-a-MEL: A Scaffold to Explore the Universe’s Origins

Colorado School of Mines engineering physics majors take a two-semester sequence of Advanced Physics Labs during their junior year of studies that introduce them to laboratory measurement techniques in atomic physics, modern physics, nuclear physics, optics, and solid-state physics.&nbsp; These courses introduce students to measurement and uncertainty, data reduction and error analysis, and effective scientific writing. &nbsp;We require students to use the Python programming language to generate plots that can be imported into lab reports and presentations.&nbsp; To provide an authentic learning experience, students complete a “Python Programming and Plotting Assignment” in the first-semester course before their first set of measurements.&nbsp; In this presentation, we will share open source data students have plotted from COVID-19 Cases Reported at Mines, Lifetime Measurements of the Tau Lepton, Fitting the Cosmic Microwave Background Radiation Spectrum, and student-selected data sets.&nbsp; Faculty, students, and teaching assistants from the courses will share their perspectives.

Plotting Open Source Data in the Advanced Physics Lab Course

For Classical Mechanics at the sophomore level, I completely changed the way that homework was graded, using a self-grading/professor review process, 2 years in a row. Students would attempt all problems, then be given access to my complete solution for the assignment. They would grade themselves, most importantly including comments on self-reflection of their work, mistakes, understanding and correcting their errors with full commentary. Getting the correct answer was not the requisite for an excellent score. This was incredibly successful both from the student experiences (confidence and pressure relief), my experiences (insight into student understanding and process, gaps in skills/knowledge) &nbsp;and higher overall grades in the course. I will discuss methods used, examples of student self-gaded work, student feedback and the impact on other courses in the department and college.

Student Self-grading of Homework in Classical Mechanics

Standards-based grading uses a set of learning objectives rather than individual assignments or problems to determine grades. Standards based grading is common in the secondary education setting, but less so at the college level. We will discuss some of the significant advantages of the approach, especially for online classes, some of the particular challenges for implementing it in college classes, and describe two ways in which we have been able to meet those challenges. This is part of a series of talks stemming from the NextGen PET FOLC project. This work was supported by the National Science Foundation grant NSF DUE-1626496 &nbsp;

Standards Based Grading for College Physics Courses

We discuss student narratives, well-structured scientific explanations, as both formative and summative assessment tools. We will review the elements and organization of the narrative in the context of the NextGen PET curriculum; present some rubrics and metrics for evaluating narratives; suggest scaffolds and assignments to build students’ narrative writing (and reading) skills; and share our data and thoughts for the narrative as a particularly useful tool in the context of online classes. This is part of a series of talks stemming from the NextGen PET FOLC project. This work was supported by the National Science Foundation grant NSF DUE-1626496Sponsored by Lawrence Escalada

Scientific Explanations: Narrative structure, Prompts and Rubrics

The COVID-19 Pandemic resulted in a rapid switch to remote teaching for most university courses.&nbsp; One major concern of many introductory physics instructors has been the security of assessments (such as exams) in this remote environment.&nbsp; As an alternative to the high-stakes exams that are more traditional for introductory physics courses, we assigned group projects to students as an alternative assessment (along with individual low-stakes quizzes).&nbsp; We discuss advantages and disadvantages of putting group projects into practice, such as students’ engagement with the project and their affective response to working in groups on a high-stakes assignment.

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Mentoring Undergraduates Teams in Variable Star Research

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