ترغب بنشر مسار تعليمي؟ اضغط هنا

Using mobile-device sensors to teach students error analysis

72   0   0.0 ( 0 )
 نشر من قبل Arturo C. Marti
 تاريخ النشر 2020
  مجال البحث فيزياء
والبحث باللغة English




اسأل ChatGPT حول البحث

Science students must deal with the errors inherent to all physical measurements and be conscious of the need to expressvthem as a best estimate and a range of uncertainty. Errors are routinely classified as statistical or systematic. Although statistical errors are usually dealt with in the first years of science studies, the typical approaches are based on manually performing repetitive observations. Our work proposes a set of laboratory experiments to teach error and uncertainties based on data recorded with the sensors available in many mobile devices. The main aspects addressed are the physical meaning of the mean value and standard deviation, and the interpretation of histograms and distributions. The normality of the fluctuations is analyzed qualitatively comparing histograms with normal curves and quantitatively comparing the number of observations in intervals to the number expected according to a normal distribution and also performing a Chi-squared test. We show that the distribution usually follows a normal distribution, however, when the sensor is placed on top of a loudspeaker playing a pure tone significant differences with a normal distribution are observed. As applications to every day situations we discuss the intensity of the fluctuations in different situations, such as placing the device on a table or holding it with the hands in different ways. Other activities are focused on the smoothness of a road quantified in terms of the fluctuations registered by the accelerometer. The present proposal contributes to gaining a deep insight into modern technologies and statistical errors and, finally, motivating and encouraging engineering and science students.


قيم البحث

اقرأ أيضاً

The detection and study of extrasolar planets is an exciting and thriving field in modern astrophysics, and an increasingly popular topic in introductory astronomy courses. One detection method relies on searching for stars whose light has been gravi tationally microlensed by an extrasolar planet. In order to facilitate instructors abilities to bring this interesting mix of general relativity and extrasolar planet detection into the introductory astronomy classroom, we have developed a new Lecture-Tutorial, Detecting Exoplanets with Gravitational Microlensing. In this paper, we describe how this new Lecture-Tutorials representations of astrophysical phenomena, which we selected and created based on theoretically motivated considerations of their pedagogical affordances, are used to help introductory astronomy students develop more expert-like reasoning abilities.
We discuss our outreach efforts to introduce school students to network science and explain why networks researchers should be involved in such outreach activities. We provide overviews of modules that we have designed for these efforts, comment on o ur successes and failures, and illustrate the potentially enormous impact of such outreach efforts.
Quantum computing is a growing field at the intersection of physics and computer science. The goal of this article is to highlight a successfully trialled quantum computing course for high school students between the ages of 15 and 18 years old. This course bridges the gap between popular science articles and advanced undergraduate textbooks. Conceptual ideas in the text are reinforced with active learning techniques, such as interactive problem sets and simulation-based labs at various levels. The course is freely available for use and download under the Creative Commons Attribution- NonCommercial-ShareAlike 4.0 International license.
Analysis of stochastic processes can be used to engender critical thinking. Quantum dots have a reversible, stochastic transition between luminescent and non-luminescent states. The luminescence intermittency is known as blinking, and is not evident from ensemble measurements. In order to stimulate critical thinking, students design, perform, and analyze a semiconductor quantum dot blinking laboratory experiment. The design of the experiment and stochastic nature of the data collected require students to make judgements throughout the course of the single-particle measurement and analysis. Some of the decisions do not have uniquely correct answers, challenging the students to engage in critical thinking. We propose that students self-examined decision making develops a constructivist view of science. The experiment is visually striking, interdisciplinary, and develops higher order thinking.
We demonstrate how students use of modeling can be examined and assessed using student notebooks collected from an upper-division electronics lab course. The use of models is a ubiquitous practice in undergraduate physics education, but the process o f constructing, testing, and refining these models is much less common. We focus our attention on a lab course that has been transformed to engage students in this modeling process during lab activities. The design of the lab activities was guided by a framework that captures the different components of model-based reasoning, called the Modeling Framework for Experimental Physics. We demonstrate how this framework can be used to assess students written work and to identify how students model-based reasoning differed from activity to activity. Broadly speaking, we were able to identify the different steps of students model-based reasoning and assess the completeness of their reasoning. Varying degrees of scaffolding present across the activities had an impact on how thoroughly students would engage in the full modeling process, with more scaffolded activities resulting in more thorough engagement with the process. Finally, we identified that the step in the process with which students had the most difficulty was the comparison between their interpreted data and their model prediction. Students did not use sufficiently sophisticated criteria in evaluating such comparisons, which had the effect of halting the modeling process. This may indicate that in order to engage students further in using model-based reasoning during lab activities, the instructor needs to provide further scaffolding for how students make these types of experimental comparisons. This is an important design consideration for other such courses attempting to incorporate modeling as a learning goal.
التعليقات
جاري جلب التعليقات جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
mircosoft-partner

هل ترغب بارسال اشعارات عن اخر التحديثات في شمرا-اكاديميا