Engin Bumbacher

Trap it!: A Playful Human-Biology Interaction for a Museum Installation

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 phototactic responses. The system design enables stable and robust HBI and a wide variety of programmed activities (art, games, and experiments). We investigated its affordances as an exhibit in a science museum in both facilitated and unfacilitated contexts. Overall, it had a low barrier of entry and fostered rich communication among visitors. Visitors were particularly excited upon realizing that the interaction involved real organisms, an understanding that was facilitated by the eyepiece on the physical system. With the results from user study, we provide our observations, insights and guidelines for designing HBI as a permanent museum exhibit.

Tangible vs. virtual representations: when tangibles benefit the training of spatial skills

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 representation (physical vs. virtual) on learning in the domain of spatial skills. We ran a comparative study with 46 participants to measure the effects of the object representation on the ability to establish a link between 2D and 3D representations of an object. The participants were split into two conditions: in the first one, the 3D representation of the object was virtual; in the second one, it was tangible. Findings show that in both conditions the TUI led to a significant improvement of the spatial skills. The learning outcomes were not different between the two conditions, but the performance during the activities was significantly higher when using the tangible representation as opposed to the virtual one, and even more so in for difficult cases.

Interactive Cloud Experimentation for Biology: An Online Education Case Study

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 cloud experimentation architecture (paralleling cloud computation), which is optimized for a class of domain-specific equipments (biotic processing units - BPU) to share and execute many experiments in parallel remotely and interactively at all time. We implemented an instance of this architecture that enables chemotactic experiments with a slime mold Physarum Polycephelum. A user study in the blended teaching and research setting of a graduate-level biophysics class demonstrated that this platform lowers the access barrier for non-biologists, enables discovery, and facilitates learning analytics. This architecture is flexible for integration with various biological specimens and equipments to facilitate scalable interactive online education, collaborations, research, and citizen science.

Interactive and scalable biology cloud experimentation for scientific inquiry and education.

A real-time interactive, fully automated, low-cost and scalable biology cloud experimentation platform could provide access to scientific experimentation for learners and researchers alike.

Authentic Science Inquiry Learning at Scale Enabled by an Interactive Biology Cloud Experimentation Lab

National guidelines advocate for a more sophisticated STEM education that integrates complex and authentic scientific practices, e.g., experimentation, data collection, data analysis, and modeling. How to achieve that is currently unclear for both presential and distance education. We recently developed a scalable cloud lab that enables many online users to perform phototaxis experiment with real, living Euglena cells (opposed to just simulations). Here we iteratively designed and deployed an open course on the edX platform including suitable user interfaces that facilitates inquiry-based learning on this cloud lab: Online students (>300) run real experiments (>2,300), performed data analysis, explored models, and even formulated and experimentally tested their own hypotheses. Platform and course content are now suited for global adaptation in formal K-16 education. We will demo our cloud lab at the conference.

Design Guidelines and Empirical Case Study for Scaling Authentic Inquiry-based Science Learning via Open Online Courses and Interactive Biology Cloud Labs

The Next Generation Science Standards (NGSS) and other national frameworks are calling for much more sophisticated approaches to STEM education, centered around the integration of complex experimentation (including real labs, not just simulations), data collection and analysis, modeling, and data-driven argumentation, i.e., students can behave like real scientists. How to implement such complex approaches in scalable ways is an unsolved challenge - both for presential and distance education. Here we report on the iterative design and large-scale deployment of an open online course with a “biology cloud experimentation lab” (using living cells) that engaged remote learners (> 300 students) in the scientific practices of experimentation, modeling and data analysis to investigate the phototaxis of a microorganism. We demonstrate (1) the robustness and scalability of the cloud lab technology (> 2,300 experiments run), (2) the design principles and synergistic integration of multiple UI and learning activities and suitable data formats to facilitate NGSS-aligned science activities, and (3) design features that leverages the natural variability of real biology experiments to instigate authentic inquiry. This platform and course content are now suited for large-scale adaptation in formal K-16 education; and we provide recommendations for inquiry-based science learning in general.

Student Coding Styles as Predictors of Help-Seeking Behavior

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 non-semantic and semantic features of their code submissions. Preliminary findings show that these descriptors extracted from a single assignment can be used to predict whether or not a student got help throughout the entire quarter. Based on these findings, we plan on developing a model of the impact of teacher intervention on a student’s pathway through homework assignments.

BeatTable: a tangible approach to rhythms and ratios

Frameworks that create synergies across disciplines provide a powerful means for learning by relating concepts from the different fields that are usually difficult to grasp individually. We discuss the design of the BeatTable, a microworld that uses the relation between mathematics and music to engage learners in using ratios and proportions to create rhythms and learn about musical composition. The BeatTable is a physical table with a digital environment that can be controlled by tangible instruments, and through immediate auditory and visual feedback makes salient the relationships between math and music. With a low-floor, high-ceiling design philosophy, BeatTable provides learners the opportunity to build on their conceptions about music and to practice and hone their use of ratios and proportions. We present what our design choices, the technology used, and a description of initial user feedback.

Interactive Biology Cloud Lab Enables Authentic Inquiry-Based Science Learning At MOOC Scale

Abstract The Next Generation Science Standards (NGSS) and other national frameworks are calling for much more sophisticated approaches to STEM education, centered around the integration of complex experimentation (including real labs, not just simulations), data collection and analysis, modeling, and data-driven argumentation, i.e., students can behave like real scientists. How to implement such complex approaches in scalable ways is an unsolved challenge - both for presential and distance education. Here we report on the iterative design and large-scale deployment of an open online course with a “biology cloud experimentation lab” (using living cells) that engaged remote learners (> 300 students) in the scientific practices of experimentation, modeling and data analysis to investigate the phototaxis of a microorganism. We demonstrate (1) the robustness and scalability of the cloud lab technology (> 2, 300 experiments run), (2) the design principles and synergistic integration of multiple UI and learning activities and suitable data formats to facilitate NGSS-aligned science activities, and (3) design features that leverages the natural variability of real biology experiments to instigate authentic inquiry. This platform and course content are now suited for large-scale adaptation in formal K-16 education; and we provide recommendations for inquiry-based science learning in general.

Sketching intentions: comparing different metaphors for programming robots

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 robots inputs and outputs together. It does this by providing the user with a virtual canvas that they can draw rectangles on using the mouse. Each rectangle represents a range of sensor values, and specific outputs can be assigned to each rectangle. When the sensor values enter into the specified range, the outputs will turn on. We designed a study with 60 youth to compare this environment to Cricket Logo, a well-known variant of Logo designed to control robotic devices. We found that participants using the spatial computing platform were able to build programs of higher complexity and make more changes to their programs over the course of an hour-long workshop.