More Like this

1. Seeds of (r)Evolution: Constructionism Co-Design with High School Science Teachers

   Kelter, J.; Peel, A.; Bain, C.; Anton, G.; Dabholkar, S.; Aslan, U.; Horn, M.S.; Wilensky, U. (June 2020, Constructionism 2020)

   In the decades since Papert published Mindstorms (1980), computation has transformed nearly every branch of scientific practice. Accordingly, there is increasing recognition that computation and computational thinking (CT) must be a core part of STEM education in a broad range of subjects. Previous work has demonstrated the efficacy of incorporating computation into STEM courses and introduced a taxonomy of CT practices in STEM. However, this work rarely involved teachers as more than implementers of units designed by researchers. In The Children’s Machine, Papert asked “What can be done to mobilize the potential force for change inherent in the position of teachers?” (Papert, 1994, pg. 79). We argue that involving teachers as co-design partners supports them to be cultural change agents in education. We report here on the first phase of a research project in which we worked with STEM educators to co-design curricular science units that incorporate computational thinking and practices. Eight high school teachers and one university professor joined nine members of our research team for a month-long Computational Thinking Summer Institute (CTSI). The co-design process was a constructionist design and learning experience for both the teachers and researchers. We focus here on understanding the co-design process and its implications for teachers by asking: (1) How did teachers shift in their attitudes and confidence regarding CT? (2) What different co-design styles emerged and did any tensions arise? Generally, we found that teachers gained confidence and skills in CT and computational tools over the course of the summer. Only one teacher reported a decrease in confidence in one aspect of CT (computational modeling), but this seemed to result from gaining a broader and more nuanced understanding of this rich area. A range of co-design styles emerged over the summer. Some teachers chose to focus on designing the curriculum and advising on the computational tools to be used in it, while leaving the construction of those tools to their co-designers. Other teachers actively participated in constructing models and computational tools themselves. The pluralism of co-design styles allowed teachers of various comfort levels with computation to meaningfully contribute to a computationally enhanced constructionist curriculum. However, it also led to a tension for some teachers between working to finish their curriculum versus gaining experience with computational tools. In the time crunch to complete their unit during CTSI, some teachers chose to save time by working on the curriculum while their co-design partners (researchers) created the supporting computational tools. These teachers still grew in their computational sophistication, but they could not devote as much time as they wanted to their own computational learning. 

   more » « less
2. Recommend Me? Designing Fairness Metrics with Providers

   https://doi.org/10.1145/3630106.3659044  

   Smith, Jessie J; Satwani, Aishwarya; Burke, Robin; Fiesler, Casey (June 2024, ACM)

   Fairness metrics have become a useful tool to measure how fair or unfair a machine learning system may be for its stakeholders. In the context of recommender systems, previous research has explored how various stakeholders experience algorithmic fairness or unfairness, but it is also important to capture these experiences in the design of fairness metrics. Therefore, we conducted four focus groups with providers (those whose items, content, or profiles are being recommended) of two different domains: content creators and dating app users. We explored how our participants experience unfairness on their associated platforms, and worked with them to co-design fairness goals, definitions, and metrics that might capture these experiences. This work represents an important step towards designing fairness metrics with the stakeholders who will be impacted by their operationalizations. We analyze the efficacy and challenges of enacting these metrics in practice and explore how future work might benefit from this methodology. 

   more » « less
3. Exploring Diversity and Inclusion in the Professional Formation of Engineers through Design Sessions

   https://doi.org/10.1109/FIE.2018.8659044  

   Zoltowski, Carla B.; Eddington, Sean M.; Brightman, Andrew O.; Buzzanell, Patrice M.; Joshi, Rucha (October 2018, 2018 IEEE Frontiers in Education Conference (FIE))

   This Research Work-in-Progress paper builds on previous literature related to the professional formation of engineers and issues pertaining to diversity and inclusion within engineering though a comparative analysis of two different disciplines. These issues are complex, interrelated and challenging to untangle, and thus require innovative strategies to explore them. Our larger study utilizes design thinking with an embedded mixed-methods research approach to investigate foundational understandings of professional formation and diversity and inclusion in engineering. Herein, we describe preliminary findings from co-design sessions we conducted in Biomedical Engineering (BME) and Electrical and Computer Engineering (ECE) at Purdue University. We compare the design solutions generated by stakeholders and discuss insights regarding the unique contexts and needs of each program, as well as the impacts of the different activities and contexts of the design sessions themselves. 

   more » « less
4. Exploring Diversity and Inclusion in the Professional Formation of Engineers through Design Sessions

   Zoltowski, C. B.; Eddington, S. M.; Brightman, A. O.; Buzzanell, P. M.; Joshi, R. (October 2018, Conference proceedings - Frontiers in Education Conference)

   This Research Work-in-Progress paper builds on previous literature related to the professional formation of engineers and issues pertaining to diversity and inclusion within engineering though a comparative analysis of two different disciplines. These issues are complex, interrelated and challenging to untangle, and thus require innovative strategies to explore them. Our larger study utilizes design thinking with an embedded mixed-methods research approach to investigate foundational understandings of professional formation and diversity and inclusion in engineering. Herein, we describe preliminary findings from co-design sessions we conducted in Biomedical Engineering (BME) and Electrical and Computer Engineering (ECE) at Purdue University. We compare the design solutions generated by stakeholders and discuss insights regarding the unique contexts and needs of each program, as well as the impacts of the different activities and contexts of the design sessions themselves. 

   more » « less
5. Modular Controllers Facilitate the Co-Optimization of Morphology and Control in Soft Robots

   https://doi.org/10.1145/3583131.3590416  

   Mertan, Alican; Cheney, Nick (July 2023, Proceedings of the Genetic and Evolutionary Computation Conference)

   Soft robotics is a rapidly growing area of robotics research that would benefit greatly from design automation, given the challenges of manually engineering complex, compliant, and generally non-intuitive robot body plans and behaviors. It has been suggested that a major hurdle currently limiting soft robot brain-body co-optimization is the fragile specialization between a robot's controller and the particular body plan it controls, resulting in premature convergence. Here we posit that modular controllers are more robust to changes to a robot's body plan. We demonstrate a decreased reduction in locomotion performance after morphological mutations to soft robots with modular controllers, relative to those with similar global controllers - leading to fitter offspring. Moreover, we show that the increased transferability of modular controllers to similar body plans enables more effective brain-body co-optimization of soft robots, resulting in an increased rate of positive morphological mutations and higher overall performance of evolved robots. We hope that this work helps provide specific methods to improve soft robot design automation in this particular setting, while also providing evidence to support our understanding of the challenges of brain-body co-optimization more generally. 

   more » « less