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  1. Step-based tutoring systems are known to be more effective than traditional answer-based systems. They however require that each step in a student’s work be accepted and evaluated automatically to provide effective feedback. In the domain of linear circuit analysis, it is frequently necessary to allow students to draw or edit circuits on their screen to simplify or otherwise transform them. Here, the interface developed to accept such input and provide immediate feedback in the Circuit Tutor system is described, along with systematic assessment data. Advanced simplification methods such as removing circuit sections that are removably hinged, voltage-splittable, or current-splittable aremore »taught to students in an interactive tutorial and then supported in the circuit editor itself. To address the learning curve associated with such an interface, ~70 video tutorials were created to demonstrate exactly how to work the randomly generated problems at each level of each of the tutorials in the system. A complete written record or “transcript” of student’s work in the system is being made available, showing both incorrect and correct steps. Introductory interactive (multiple choice) tutorials are now included on most topics. Assessment of exercises using the interactive editor was carried out by professional evaluators for several institutions, including three that heavily serve underrepresented minorities. Both quantitative and qualitative methods were used, including focus groups, surveys, and interviews. Controlled, randomized, blind evaluations were carried out in three different course sections in Spring and Fall 2019 to evaluate three tutorials using the interactive editor, comparing use of Circuit Tutor to both a commercial answer-based system and to conventional textbook-based paper homework. In Fall 2019, students rated the software a mean of 4.14/5 for being helpful to learn the material vs. 3.05/5 for paper homework (HW), p < 0.001 and effect size d = 1.11σ. On relevant exam questions that semester, students scored significantly (p = 0.014) higher with an effect size of d = 0.64σ when using Circuit Tutor compared to paper HW in one class section, with no significant difference in the other section.« less
  2. Jarm T., Cvetkoska A. (Ed.)
  3. Estimating central aortic blood pressure is important for cardiovascular health and risk prediction purposes. Cardiovascular system is a multi-channel dynamical system that yields multiple blood pressures at various body sites in response to central aortic blood pressure. This paper concerns the development and analysis of an observer-based approach to de-convolution of unknown input in a class of coprime multi-channel systems applicable to non-invasive estimation of central aortic blood pressure. A multi-channel system yields multiple outputs in response to a common input. Hence, the relationship between any pair of two outputs constitutes a hypothetical input-output system with unknown input embedded asmore »a state. The central idea underlying our approach is to derive the unknown input by designing an observer for the hypothetical input-output system. In this paper, we developed an unknown input observer (UIO) for input de-convolution in coprime multi-channel systems. We provide a universal design algorithm as well as meaningful physical insights and inherent performance limitations associated with the algorithm. The validity and potential of our approach was illustrated using a case study of estimating central aortic blood pressure waveform from two non-invasively acquired peripheral arterial pulse waveforms. The UIO could reduce the root-mean-squared error associated with the central aortic blood pressure by up to 27.5% and 28.8% against conventional inverse filtering and peripheral arterial pulse scaling techniques.« less
  4. We consider the problem of transmitting at the optimal rate over a rapidly-varying wireless channel with unknown statistics when the feedback about channel quality is very limited. One motivation for this problem is that, in emerging wireless networks, the use of mmWave bands means that the channel quality can fluctuate rapidly and thus, one cannot rely on full channel-state feedback to make transmission rate decisions. Inspired by related problems in the context of multi-armed bandits, we consider a well-known algorithm called Thompson sampling to address this problem. However, unlike the traditional multi-armed bandit problem, a direct application of Thompson samplingmore »results in a computational and storage complexity that grows exponentially with time. Therefore, we propose an algorithm called Modified Thompson sampling (MTS), whose computational and storage complexity is simply linear in the number of channel states and which achieves at most logarithmic regret as a function of time when compared to an optimal algorithm which knows the probability distribution of the channel states.« less