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Smartphone based labs are a cornerstone of our efforts to reform the introductory labs in both our calculus-based and algebra-based classes. Students use smartphones to collect data in the lab (Bluetooth paired with sensors) and at home (using the native sensors in the phone). In this talk, we will give a brief overview of the project, then emphasize the at-home labs. These labs have allowed us to substantially reduce crowding in the lab, emphasize data analysis, and give students an opportunity to be more exploratory in their approach to lab. We will highlight examples of our at-home labs and discuss lessons learned during the first year of the project.

AAPT SM 22

Smartphones in the introductory mechanics lab

ICPR 2020 is the premier international conference on Pattern Recognition, gathering leading researchers from around the world to present their latest achievements in Pattern Analysis and Recognition, applied Artificial Intelligence and Machine Learning. The topic of the year is " Putting Artificial intelligence to work on Patterns". 
For the first time, ICPR has employed a two-round review process similar to journal submissions, with new papers allowed to be submitted in either the first or second round and papers submitted in the first round and not accepted allowed to be revised and re-submitted for second round review. 

In this edition of the **ICPR 2020** Conference, there are 1407 Oral/Poster presentations organized in five Tracks: 
- Artificial Intelligence, Machine Learning for Pattern Analysis; 
- Biometrics, Human Analysis and Behavior Understanding; Computer Vision, Robotics and Intelligent Systems; 
- Document and Media Analysis; and 
- Image and Signal Processing. 

The **ICPR 2020** Main Conference program also includes 7 Keynotes from prominent world-renowned scientists, 8 Tutorials, 28 Demos, 8 Challenges, 2 Panels, as well as an Industry/Sponsor Exhibition. In addition, 41 Workshops on a range of important current and emerging research topics complete the ICPR 2020 program. 


ICPR 2020

technical paper

AAPT meetings are a great way to reflect on your teaching, recommit to best practices and re-energize your career with new research, products, and techniques. Listen to internationally known plenary speakers, attend sessions, workshops, and special activities. This meeting is an excellent opportunity to share your expertise and learn from and network with leaders in the field.



QuarkNet is a project funded by NSF, ATLAS, CMS and Fermilab with additional support from participating universities. My role in the project is to oversee the Data Activities Portfolio (DAP), a compendium of activities to help teachers incorporate 21st Century physics into their curriculum. This talk will explain the DAP structure that follows guidelines for Effective Teacher Professional Development as described by Linda Darling-Hammond, Maria E. Hyler, and Madelyn Gardner, with assistance from Danny Espinoza. We will provide data about the efficacy of our activities in the classroom.

Planning Effective Professional Development

With the transition to remote learning, many lab-based curricula had to be quickly amended. Here, I present a build-it-yourself experiment that can be used by students with a wide range of mathematical backgrounds to explore principles of mechanics and experimental design. This coupled harmonic oscillator experiment, initially developed for a sophomore level waves and optics lab at UT Austin, is built with readily available materials and doesn't suffer from parametric oscillations: a common difficulty in such experiments. In an introductory physics class, this experiment can be used as a platform to discuss transfer of energy and momentum in a system that challenges students' intuition. Freedom in the setup's construction leads to student-led investigations of experimental error mitigation. Students familiar with trigonometry can explore the small angle approximation. Finally, students familiar with linear algebra can study decomposition of waves into sinusoidal (eigenfunction) components, and an introduction to Fourier transforms.

Take-home Experiment: Student-led Exploration of Coupled Harmonic Oscillators

For the second year of the pandemic, we developed new labs for our life-science stream intro physics courses. Despite the return to on-campus learning, our students engaged in unscheduled, remote experiments. The goal of our labs was to connect life science topics (fluids, optics, spectroscopy) to an everyday context through hands-on experiments. We created ‘at-home’ lab kits for students, combining common items (rulers, string, battery) reinforced with standardized items for consistency (e.g. known masses) and specialized materials (capillaries, LEDs, diffraction grating). We employed smart phone apps for measurement, embedded Geogebra for data analysis, and complemented activities with the video- and simulation-elements from virtual labs of the previous year. Some of highlights of our experience over the year include: a citizen-science lab, insights into the workflow of students, and their preference regarding ‘scheduled & on-campus’ vs ‘asynchronous & remote’.

Lab Kits for ‘At-Home’ Experiments in Physics for Life Sciences

During the Spring and Summer sessions of 2020 and 2021, our students used the circuit kits we sent them to create light sources for use in the optics portion of the course. Various single-colored LEDs and an RGB LED were used with the Fresnel-lens book mark and diffraction grating slides included in their kit to explore ray optics, image formation, color mixing, and interference effects. Christmas lights, Fresnel book marks, magnifying glasses, and reading glasses were could be used in the explorations by those without access to the kits. The use of multi-colored light sources increased the quality of student discussion of the concepts involved.

Using Circuit Kits and LEDs to Teach Optics at Home

Machine Learning (ML) is becoming ubiquitous in the realms of science, business, law enforcement, and even the arts. I have developed a three-week general education course on machine learning for non-scientists. Each day in the first half of the course, students engage with demonstrations and tutorials. They learn how to implement simple examples of text and image classification as well as generative algorithms and adversarial networks. In the second half of the course, the students carry out a project of their own design. I do not assume students have previous experience with programming, calculus, or ML algorithms. They learn by experimenting with existing code to achieve goals of increasing complexity. I will report on the successes and challenges of this course and share what I have learned about how students can effectively grapple with the opportunities and dangers that ML represents.

Teaching Machine Learning to Non-Scientists

In an earlier study we showed that small amounts of extra credit offered for early progress on online homework assignments can reduce cramming behavior in introductory physics students. This work expands on the prior study by implementing a planning prompt intervention. In the prompt we asked students to what degree they intended to earn extra credit offered for early work on the module sequence, and what their plan was to realize their intentions. The survey was due several days before the first extra credit deadline. We found that students who completed the prompt earned on average 0.6 more extra credit points and completed the modules an average of 1.1 days earlier compared to a previous semester. We detect the impact of the survey by creating a multilinear model based on data from students exposed to the intervention as well as students in a previous semester.

Planning Prompt Surveys to Encourage Early Completion of Homework Assignments

Heileman et al. developed a methodology for quantifying the complexity of program curricula. Using that framework, they showed that Engineering programs that were deemed higher quality had curricula and degree plans that were simpler than engineering programs that were ranked to be lower quality. They also propose that curricula that is simpler is more agreeable to students, claiming that a simpler curriculum would be beneficial to student retention. The purpose of this presentation is to determine whether or not this trend holds for physics programs in the U.S. Physics curricula from different universities were analyzed using the methods developed by Heileman et al. to see if there is a correlation between program complexity and program quality.

Curricular Analytics in Physics

Research-validated clicker questions comprise an easy-to-implement instructional tool that serves to scaffold and formatively assess student learning. We present findings from the implementation, in consecutive years, of a research-validated Clicker Question Sequence (CQS) on student understanding of the uncertainty principle as it applies to two-state quantum systems. This study was conducted in an advanced undergraduate quantum mechanics course, in both the virtual learning environment of 2020 and the in-person classroom setting of 2021. Students were assessed after receiving traditional lecture-based instruction, and their performance was compared with that on a similar assessment given after engaging with the CQS. We examine and remark on the constant and differing trends observed in the two modes of instruction.

Clicker Question Sequence on Uncertainty Principle: Virtual and In-Person Implementation

The field of quantum computing is presently gaining tremendous attention from governments, researchers, engineers, academics and investors. There is an ongoing push for the development of quantum computers, advances in information technology, and the development of a quantum workforce. This needs to be accompanied by the development of quantum computing courses and curricula and the development and adoption of evidence-based materials and pedagogies to support the education of the next generation of quantum information scientists At Texas Tech University (TTU), we have introduced a course in Quantum Computing and have begun to research student understanding of topics in this field. Our goal is to develop evidence-based materials for the course. We did a series of interviews to identify students’ strengths and difficulties in these topics. We report on the results of these interivews and our initial work on the development of supplementary materials for the course.

Investigating Students’ Strengths and Difficulties in Quantum Computing

This talk will focus on ways to assist high school physics teachers in incorporating 21st century physics side by side with classical topics. The talk will compare the QuarkNet approach with the seven characteristics of effective professional development developed by Linda Darling-Hammond et.al.

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Smartphones in the introductory mechanics lab

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