Collaborating Authors

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Collaborative and Privacy-Preserving Machine Teaching via Consensus Optimization Machine Learning

In this work, we define a collaborative and privacy-preserving machine teaching paradigm with multiple distributed teachers. We focus on consensus super teaching. It aims at organizing distributed teachers to jointly select a compact while informative training subset from data hosted by the teachers to make a learner learn better. The challenges arise from three perspectives. First, the state-of-the-art pool-based super teaching method applies mixed-integer non-linear programming (MINLP) which does not scale well to very large data sets. Second, it is desirable to restrict data access of the teachers to only their own data during the collaboration stage to mitigate privacy leaks. Finally, the teaching collaboration should be communication-efficient since large communication overheads can cause synchronization delays between teachers. To address these challenges, we formulate collaborative teaching as a consensus and privacy-preserving optimization process to minimize teaching risk. We theoretically demonstrate the necessity of collaboration between teachers for improving the learner's learning. Furthermore, we show that the proposed method enjoys a similar property as the Oracle property of adaptive Lasso. The empirical study illustrates that our teaching method can deliver significantly more accurate teaching results with high speed, while the non-collaborative MINLP-based super teaching becomes prohibitively expensive to compute.



Educators who teach science using R tend to face common pedagogical problems even across different scientific domains. Yet instructors who teach with R often feel isolated at their institutions. They may be the only ones in their departments to teach using R; even if there are others, there tends not to be a culture of collaboration around teaching materials the way that there is around research. In a three-part series of blog posts, some participants at the rOpenSci 2018 unconf briefly survey the state of teaching science with R. A first post summarizes the main challenges that educators face, as a tool to help them think through the decisions they make about their course materials. The second post explains what makes for a good educational resource which can address these shared challenges.

Indiana teaching assistant accused of molesting 17 kids

FOX News

JEFFERSONVILLE, Ind. – An 18-year-old southern Indiana man has been arrested on charges alleging he molested 17 children ages 3 to 7 while he worked at a YMCA and as an elementary school teaching assistant.

Teaching to the Test Is OK

U.S. News

If you know any kids in public schools, then chances are they are about to take or have recently taken some standardized test that feeds into state accountability systems, as required by federal education policy. In the years since the inception of this springtime ritual, nationally tied to the enactment of the No Child Left Behind Act in 2002, many have wrung their hands about testing slowly crowding out learning in our public schools. Since teachers are the primary means of both instruction and preparing students for these exams, much of the concern about testing's adverse consequences has focused on whether and how teachers respond to these goals that appear at odds. Are they teaching to the test to the detriment of authentic instruction? And how do their choices affect our kids?