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As computation becomes increasingly central to mathematics education, instructors must balance competing forces when choosing which computational tools to use in their courses. This is compounded in probability and statistics where computation is widely used. Grounded in a social constructivist perspective, we believe that tools mediate our activities and that different tools play different mediational roles. As such, this study explores how different computational tools mediate undergraduate students' mathematical activity of argumentation. Using Toulmin’s argument model, this research investigates how two classes in probability and statistics using different computational tools, R or Minitab, performed on a mirrored assignment. Through analysis of students’ assignments, a difference emerged across the classes use of visuals. Our findings suggest Minitab promoted more deliberate consideration and use of visuals than R, leading to a difference in arguments produced by the students. 

Technology has become an integral part of undergraduate mathematics, particularly the use of technology to solve problems (i.e., the use of computation). In probability and statistics, this push has resulted in several projects designing and assessing tools that are conjectured to be advantageous to students and their learning. Despite this trend, minimal research exists on how students perceive the use of computational tools in their courses. As such, we designed a brief survey for students enrolled in introductory probability and statistics at a university in the Northeastern United States. Using thematic analysis, we qualitatively analyzed these survey responses to explore their perceptions of the integration of computation into their courses. Three themes were identified, relating to features of tools, augmentation of actions, and long-term benefits. This exploration of students’ perceptions allows us to better understand their views on computation and the need for professors to make instructional goals explicit. 

The need for high-quality remote learning experiences has been illustrated by the COVID-19 pandemic. As such, there is a need to explore instructional videos that go beyond expert exposition as the main pedagogical approach. An emerging body of research has begun to investigate instructional videos that feature dialogue. However, this body of research has focused primarily on whether such videos are effective. In contrast, the purpose of our study is to investigate the dialogic learning processes involved as students viewing dialogic videos develop mathematical meaning. We employed a Bakhtinian perspective to analyse the learning of a pair of Grade 9 students who engaged with dialogic instructional videos. The results focus on ventriloquation as a learning process. 

Ultra-miniaturized microendoscopes are vital for numerous biomedical applications. Such minimally invasive imagers allow for navigation into hard-to-reach regions and observation of deep brain activity in freely moving animals. Conventional solutions use distal microlenses. However, as lenses become smaller and less invasive, they develop greater aberrations and restricted fields of view. In addition, most of the imagers capable of variable focusing require mechanical actuation of the lens, increasing the distal complexity and weight. Here, we demonstrate a distal lens-free approach to microendoscopy enabled by computational image recovery. Our approach is entirely actuation free and uses a single pseudorandom spatial mask at the distal end of a multicore fiber. Experimentally, this lensless approach increases the space-bandwidth product, i.e., field of view divided by resolution, by threefold over a best-case lens- based system. In addition, the microendoscope demonstrates color resolved imaging and refocusing to 11 distinct depth planes from a single camera frame without any actuated parts.