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Register a new userParticipating in the Physics Lab: Does Gender Matter?
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It is a well-studied notion that women are under-represented in the physical sciences, with a leaky pipeline metaphor describing how the number of women decreases at higher levels in academia[1,2]. It is unclear, however, where the major leaks exist and what factors are responsible for this[2]. Our focus here is on women in physics with an emphasis on practical laboratory work.
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While laboratory instruction is a cornerstone of physics education, the impact of student behaviours in labs on retention, persistence in the field, and the formation of students physics identity remains an open question. In this study, we performed in-lab observations of student actions over two semesters in two pedagogically different sections of the same introductory physics course. We used a cluster analysis to identify different categories of student behaviour and analyzed how they correlate with lab structure and gender. We find that, in lab structures which fostered collaborative group work and promoted decision making, there was a task division along gender lines with respect to laptop and equipment usage (and found no such divide among students in guided verification labs).
Writing is an integral part of the process of science. In the undergraduate physics curriculum, the most common place that students engage with scientific writing is in lab classes, typically through lab notebooks, reports, and proposals. There has not been much research on why and how we include writing in physics lab classes, and instructors may incorporate writing for a variety of reasons. Through a broader study of multiweek projects in advanced lab classes, we have developed a framework for thinking about and understanding the role of writing in lab classes. This framework defines and describes the breadth of goals for incorporating writing in lab classes, and is a tool we can use to begin to understand why, and subsequently how, we teach scientific writing in physics.
The use of lab notebooks for scientific documentation is a ubiquitous part of physics research. However, it is common for undergraduate physics laboratory courses not to emphasize the development of documentation skills, despite the fact that such courses are some of the earliest opportunities for students to start engaging in this practice. One potential impediment to the inclusion of explicit documentation training is that it may be unclear to instructors which features of authentic documentation practice are efficacious to teach and how to incorporate these features into the lab class environment. In this work, we outline some of the salient features of authentic documentation, informed by interviews with physics researchers, and provide recommendations for how these can be incorporated into the lab curriculum. We do not focus on structural details or templates for notebooks. Instead, we address holistic considerations for the purpose of scientific documentation that can guide students to develop their own documentation style. Taking into consideration all the aspects that can help improve students documentation, it is also important to consider the design of the lab activities themselves. Students should have experience with implementing these authentic features of documentation during lab activities in order for them to find practice with documentation beneficial.
Recently there are increasing concerns about the fairness of Artificial Intelligence (AI) in real-world applications such as computer vision and recommendations. For example, recognition algorithms in computer vision are unfair to black people such as poorly detecting their faces and inappropriately identifying them as gorillas. As one crucial application of AI, dialogue systems have been extensively applied in our society. They are usually built with real human conversational data; thus they could inherit some fairness issues which are held in the real world. However, the fairness of dialogue systems has not been well investigated. In this paper, we perform a pioneering study about the fairness issues in dialogue systems. In particular, we construct a benchmark dataset and propose quantitative measures to understand fairness in dialogue models. Our studies demonstrate that popular dialogue models show significant prejudice towards different genders and races. Besides, to mitigate the bias in dialogue systems, we propose two simple but effective debiasing methods. Experiments show that our methods can reduce the bias in dialogue systems significantly. The dataset and the implementation are released to foster fairness research in dialogue systems.
A set of virtual experiments were designed to use with introductory physics I (analytical and general) class, which covers kinematics, Newton laws, energy, momentum, and rotational dynamics. Virtual experiments were based on video analysis and simulations. Only open educational resources (OER) were used for experiments. Virtual experiments were designed to simulate in-person physical laboratory experiments. All the calculations and data analysis (analytical and graphical) were done with Microsoft excel. Formatted excel tables were given to students and step by step calculations with excel were done during the class. Specific emphasis was given to student learning outcomes such as understand, apply, analyze and evaluate. Student learning outcomes were studied with detailed lab reports per each experiment and end of the semester written exam (which based on experiments). Lab class was fully web-enhanced and managed by using a Learning management system (LMS). Every lab class was recorded and added to the LMS. Virtual labs were done by using live video conference technology and labs were tested with the both synchronous and asynchronous type of remote teaching methods.
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