Incarcerated students enrolled in education programs in prisons and jails experience a range of benefits, from reduced recidivism to improved psychosocial well-being. With respect to computer science education, little is still known about how courses impact incarcerated students' experiences, though recent work has explored fears and confidence of incarcerated students enrolled in computer science courses. Our work investigates incarcerated students' changes in self-efficacy over multiple iterations of four different classes. Our findings showed that all subscales of computer programming self-efficacy (algorithm, control, cooperation, debugging, and logic), but not generalized self-efficacy, were statistically significantly increased at the end of the courses relative to the beginning (p < 0.001, n = 36). A similar pattern of results across the full sample (n = 188) adds additional support for the veracity of the effects found in the subset of paired data. Additionally, we share students' qualitative data to add nuance to our findings and emphasize the importance of these educational experiences for incarcerated students' personal and professional development.

Educational programs for incarcerated individuals, often called "behind bars" initiatives, have been shown to improve participants' social and economic outcomes upon release. Since its founding in 2018, MIT's Education Justice Institute (TEJI) has offered accredited classes for incarcerated students, with an increasing focus on computer education. Our courses have been delivered both in person and remotely (e.g., via Zoom). In this poster, we share insights into the challenges present in the incarcerated education environment, and highlight how remote learning offers unique advantages to incarcerated students. We also present preliminary findings from two years of data collected across four recurring computer science courses. This poster aims to foster a dialogue with the broader computer science education community, focusing on: (i) qualitative insights gained from extensive interactions with incarcerated education systems, (ii) preliminary empirical results obtained through IRB-approved surveys, (iii) common challenges faced during data collection, and (iv) an opportunity to seek feedback and pose questions to computer science education experts.

Self-efficacy and digital literacy are key predictors to incarcerated people’s success in the modern workplace. While digitization in correctional facilities is expanding, few templates exist for how to design computing curricula that foster self-efficacy and digital literacy in carceral environments. As a result, formerly incarcerated people face increasing social and professional exclusion post-release. We report on a 12-week college-accredited web design class, taught virtually and synchronously, across 5 correctional facilities across the United States. The program brought together men and women from gender-segregated facilities into one classroom to learn fundamentals in HTML, CSS and Javascript, and create websites addressing social issues of their choosing. We conducted surveys with participating students, using dichotomous and open-ended questions, and performed thematic and quantitative analyses of their responses that suggest students’ increased self-efficacy. Our study discusses key design choices, needs, and recommendations for furthering computing curricula that foster self-efficacy and digital literacy in carceral settings.

We present FabRobotics, a digital fabrication pipeline that combines traditional 3D printing with mobile robots. By integrating these two technologies, we aim to create new opportunities for 3D printers to fabricate objects quickly and efficiently, and for mobile robots to enhance their adaptability and interactivity. To explore this novel research opportunity, we have developed a proof-of-concept implementation pipeline, allowing users to execute hybrid turn-taking control of a 3D printer and mobile robots to autonomously 3D print objects on/with mobile robots. The system was implemented with commercially available 3D printers (Prusa MINI) and mobile robots (toio), and we share various techniques and knowledge specific to fusing 3D printers and mobile robots (e.g. printing mobile robot docks for stable prints on robots). Based on the proof-of-concept system, we demonstrate various application usages and functionalities, showcasing how 3D printing and mobile robots can mutually advance each other for novel fabrication and interaction. Lastly, we share our further exploration of extended prototypes (e.g. fusing two printers) and discuss future technical challenges and research opportunities.

In this paper, we introduce a method to rapidly create 3D geometries by folding 2D sheets via pull-up nets. Given a 3D structure, we unfold its mesh into a planar 2D sheet using heuristic algorithms and populate these with cutlines and throughholes. We develop a web-based simulation tool that translates users’ 3D meshes into manufacturable 2D sheets. After laser-cutting the sheet and feeding thread through these throughholes to form a pull-up net, pulling the thread will fold the sheet into the 3D structure using a single degree of freedom. We introduce the fabrication process and build a variety of prototypes demonstrating the method’s ability to rapidly create a breadth of geometries suitable for low-fidelity prototyping that are both load-bearing and aesthetic across a range of scales. Future work will expand the breadth of geometries available and evaluate the ability of our prototypes to sustain structural loads.

This paper introduces a computational composite material comprising layers for actuation, computation and energy storage. Key to its design is inexpensive materials assembled from traditionally available fabrication machines to support the rapid exploration of applications from computational composites. The actuation layer is a soft magnetic sheet that is programmed to either bond, repel, or remain agnostic to other areas of the sheet. The computation layer is a flexible PCB made from copper-clad kapton engraved by a fiber laser, powered by a third energy-storage layer comprised of 0.4mm-thin lithium polymer batteries. We present the material layup and an accompanying digital fabrication process enabling users to rapidly prototype their own untethered, interactive and tangible prototypes. The material is low-profile, inexpensive, and fully untethered, capable of being used for a variety of applications in HCI and robotics including structural origami and proprioception.

This paper introduces a cube-based reconfigurable robot that utilizes an electromagnet-based actuation framework to reconfigure in three dimensions via pivoting. While a variety of actuation mechanisms for self-reconfigurable robots have been explored, they often suffer from cost, complexity, assembly and sizing requirements that prevent scaled production of such robots. To address this challenge, we use an actuation mechanism based on electromagnets embedded into the edges of each cube to interchangeably create identically or oppositely polarized electromagnet pairs, resulting in repulsive or attractive forces, respectively. By leveraging attraction for hinge formation, and repulsion to drive pivoting maneuvers, we can reconfigure the robot by voxelizing it and actuating its constituent modules-termed Electrovoxels-via electromagnetically actuated pivoting. To demonstrate this, we develop fully untethered, three-dimensional self-reconfigurable robots and demonstrate 2D and 3D self-reconfiguration using pivot and traversal maneuvers on an air-table and in microgravity on a parabolic flight. This paper describes the hardware design of our robots, its pivoting framework, our reconfiguration planning software, and an evaluation of the dynamical and electrical characteristics of our system to inform the design of scalable self-reconfigurable robots.

This paper introduces a method to generate highly selective encodings that can be magnetically “programmed” onto physical modules to enable them to self-assemble in chosen configurations. We generate these encodings based on Hadamard matrices, and show how to design the faces of modules to be maximally attractive to their intended mate, while remaining maximally agnostic to other faces. We derive guarantees on these bounds, and verify their attraction and agnosticism experimentally. Using cubic modules whose faces have been covered in soft magnetic material, we show how inexpensive, passive modules with planar faces can be used to selectively self-assemble into target shapes without geometric guides. We show that these modules can be easily re-programmed for new target shapes using a CNC-based magnetic plotter, and demonstrate self-assembly of 8 cubes in a water tank.

In this paper, we present Mixels, programmable magnetic pixels that can be rapidly fabricated using an electromagnetic printhead mounted on an off-the-shelve 3-axis CNC machine. The ability to program magnetic material pixel-wise with varying magnetic force enables Mixels to create new tangible, tactile, and haptic interfaces. To facilitate the creation of interactive objects with Mixels, we provide a user interface that lets users specify the high-level magnetic behavior and that then computes the underlying magnetic pixel assignments and fabrication instructions to program the magnetic surface. Our custom hardware add-on based on an electromagnetic printhead and hall effect sensor clips onto a standard 3-axis CNC machine and can both write and read magnetic pixel values from magnetic material. Our evaluation shows that our system can reliably program and read magnetic pixels of various strengths, that we can predict the behavior of two interacting magnetic surfaces before programming them, that our electromagnet is strong enough to create pixels that utilize the maximum magnetic strength of the material being programmed, and that this material remains magnetized when removed from the magnetic plotter.

LaserFactory is an integrated fabrication process that augments a commercially available fabrication machine to support the manufacture of fully functioning devices without human intervention. In addition to creating 2D and 3D mechanical structures, LaserFactory creates conductive circuit traces with arbitrary geometries, picks-and-places electronic and electromechanical components, and solders them in place. To enable this functionality, we make four contributions. First, we build a hardware add-on to the laser cutter head that can deposit silver circuit traces and assemble components. Second, we develop a new method to cure dispensed silver using a CO2 laser. Third, we build a motion-based signaling method that allows our system to be readily integrated with commercial laser cutters. Finally, we provide a design and visualization tool for making functional devices with LaserFactory. Having described the LaserFactory system, we demonstrate how it is used to fabricate devices such as a fully functioning quadcopter and a sensor-equipped wristband. Our evaluation shows that LaserFactory can assemble a variety of differently sized components (up to 65g), that these can be connected by narrow traces (down to 0.75mm) that become highly conductive after laser soldering (3.2Ω/m), and that our acceleration-based sensing scheme works reliably (to 99.5% accuracy).

CurveBoards are breadboards integrated into physical objects. In contrast to traditional breadboards, CurveBoards better preserve the object's look and feel while maintaining high circuit fluidity, which enables designers to exchange and reposition components during design iteration. Since CurveBoards are fully functional, i.e., the screens are displaying content and the buttons take user input, designers can test interactive scenarios and log interaction data on the physical prototype while still being able to make changes to the component layout and circuit design as needed. We present an interactive editor that enables users to convert 3D models into CurveBoards and discuss our fabrication technique for making CurveBoard prototypes. We also provide a technical evaluation of CurveBoard's conductivity and durability and summarize informal user feedback.

In this paper, we propose a different perspective on the use of support material: rather than printing support structures for overhangs, our idea is to make use of its transient nature, i.e. the fact that it can be dissolved when placed in a solvent, such as water. This enables a range of new use cases, such as quickly dissolving and replacing parts of a prototype during design iteration, printing temporary assembly labels directly on the object that leave no marks when dissolved, and creating time-dependent mechanisms, such as fading in parts of an image in a shadow art piece or releasing relaxing scents from a 3D printed structure sequentially overnight. Since we use regular support material (PVA), our approach works on consumer 3D printers without any modifications. To facilitate the design of objects that leverage dissolvable support, we built a custom 3D editor plugin that includes a simulation showing how support material dissolves over time. In our evaluation, our simulation predicted geometries that are statistically similar to the example shapes within 10% error across all samples.