Engin Bumbacher

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How do instructors guide students to discover mathematical content? Are current explanatory models of pedagogical practice suitable to capture pragmatic essentials of discovery-based instruction? We examined videographed data from the implementation of a natural user interface design for proportions, so as to determine one constructivist tutor's methodology(More)
Tangible user interfaces (TUIs) have been the focus of much attention in the HCI and learning communities because of their many potential benefits for learning. However, there have recently been debates about whether TUIs can actually increase learning outcomes and if so, under which conditions. In this article, we investigate the effect of object(More)
Interacting with biological systems via experiments is important for academia, industry, and education, but access barriers exist due to training, costs, safety, logistics, and spatial separation. High-throughput equipment combined with web streaming could enable interactive biology experiments online, but no such platform currently exists. We present a(More)
We developed Trap it!, a human-biology interaction (HBI) medium encompassing a touchscreen interface, microscopy, and light projection. Users can interact with living cells by drawing on a touchscreen displaying the microscope view of the cells. These drawings are projected onto the microscopy field as light patterns, prompting observable movement in(More)
Studies comparing virtual and physical manipulative environments (VME and PME) in inquiry-based science learning have mostly focused on students' learning outcomes but not on the actual processes they engage in during the learning activities. In this paper, we examined experimentation strategies in an inquiry activity and their relation to conceptual(More)
This paper introduces a new environment for programming robots and physical computing devices---the Spatial Computing Platform (SCP)---and compares it to a text-based programming environment (the Cricket Logo). The SCP simplifies the process of constructing conditional statements that link the robot's inputs and outputs together. It does this by providing(More)
ACKNOWLEDGEMENTS The summit and this report are supported by NSF‐1332686. Any opinions, findings, conclusions, or recommendations expressed in this Report are those of the authors and do not necessarily reflect the views of the authors' institutions or the NSF. Special thanks to Kathy Menchaca, who helped to organize and run this meeting. for providing(More)
Recent research in CS education has leveraged machine learning techniques to capture students' progressions through assignments in programming courses based on their code submissions [1, 2]. With this in mind, we present a methodology for creating a set of descriptors of the students' progression based on their coding styles as captured by different(More)
1. Methodology: Cluster-based feature selection a. Kernel K-means clustering of snapshots with Gaussian Kernels. Dissimilarity Matrix based on Euclidian Distance. Silhouette value. b. Each snapshot assigned to corresponding cluster  New feature set per student: number of different clusters visited, and of all cluster changes; a measure of the variance of(More)