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1. Code-first learning environments for science education: a design experiment on kinetic molecular theory

   Aslan, U. ; LaGrassa, N. ; Horn, M.S. ; Wilensky, U. ( June 2020 , Constructionism 2020)

   Code-first learning entails the use of computer code to learn a concept, and creating computational models is one such effective method for learning about scientific phenomena. Many code-first learning approaches employ the visual block-based programming paradigm in order to be accessible to school children with no prior programming experience, providing them with high- level domain-specific code-blocks that encapsulate the underlying complex programming logic. However, even with the aid of visual clues and the benefit of simpler primitives like “forward” and “repeat,” many phenomena studied in classrooms such as the behavior of gas particles in Kinetic Molecular Theory (KMT) are challenging to describe in code. We hypothesized that code blocks designed from a phenomenological perspective to model the behavior of familiar objects and events would both promote students’ authoring of computational models and their ability to encode and test their beliefs within their models. We created these phenomenological blocks within a code-first gas particle sandbox and integrated it into a KMT lesson plan. Two high school teachers taught this curriculum to 121 students, from which we gathered and analyzed video footage from lesson activities and student focus groups. We found that the phenomenological blocks gave students the ability to start programmingmore »right away and to express their intuitive understanding of KMT through computational models. This exploratory study demonstrates the potential for phenomenological programming to broaden the application and accessibility of code-first computational modeling for learning scientific phenomena.« less
2. Phenomenological programming: a novel approach to designing domain specific programming environments for science learning

   https://doi.org/10.1145/3392063.3394428  

   Aslan, Umit ; LaGrassa, Nicholas ; Horn, Michael ; Wilensky, Uri ( January 2020 , ACM Interaction Design and Children (IDC) conference)

   There has been a growing interest in the use of computer-based models of scientific phenomena as part of classroom curricula, especially models that learners create for themselves. However, while studies show that constructing computational models of phenomena can serve as a powerful foundation for learning science, this approach has struggled to gain widespread adoption in classrooms because it not only requires teachers to learn sophisticated technological tools (such as computer programming), but it also requires precious instructional time to introduce these tools to students. Moreover, many core scientific topics such as the kinetic molecular theory, natural selection, and electricity are difficult to model even with novice-friendly environments. To address these limitations, we present a novel design approach called phenomenological programming that builds on students' intuitive understanding of real-world objects, patterns, and events to support the construction of agent-based computational models. We present preliminary case studies and discuss their implications for STEM content learning and the learnability and expressive power of phenomenological programming.
3. Integrating Computational Modeling in K-12 STEM Classrooms

   https://doi.org/10.1145/3287324.3293757  

   Biswas, Gautam ; Hutchins, Nicole ; Lédeczi, Ákos ; Grover, Shuchi ; Basu, Satabdi ( February 2019 , Proceedings of the 50th ACM Technical Symposium on Computer Science Education)

   C2STEM is a web-based learning environment founded on a novel paradigm that combines block-structured, visual programming with the concept of domain specific modeling languages (DSMLs) to promote the synergistic learning of discipline-specific and computational thinking (CT) concepts and practices. Our design-based, collaborative learning environment aims to provide students in K-12 classrooms with immersive experiences in CT through computational modeling in realistic scenarios (e.g., building models of scientific phenomena). The goal is to increase student engagement and include inclusive opportunities for developing key computational skills needed for the 21st century workforce. Research implementations that include a semester-long high school physics classroom study have demonstrated the effectiveness of our approach in supporting synergistic learning of STEM and CS/CT concepts and practices, especially when compared to a traditional classroom approach. This technology demonstration will showcase our CS+X (X = physics, marine biology, or earth science) learning environment and associated curricula. Participants can engage in our design process and learn how to develop curricular modules that cover STEM and CS/CT concepts and practices. Our work is supported by an NSF STEM+C grant and involves a multi-institutional team comprising Vanderbilt University, SRI International, Looking Glass Ventures, Stanford University, Salem State University, and ETR. More information,more »including example computational modeling tasks, can be found at C2STEM.org.« less
4. The First Year of an Undergraduate Service Learning Partnership to Enhance Engineering Education and Elementary Pre-Service Teacher Education

   https://doi.org/10.18260/1-2--35320  

   Ringleb, S. ; Kidd, J. ; Pazos, P. ; Gutierrez, K. ; Ayala, O. ; Kaipa, K. ( June 2020 , 2020 ASEE Virtual Annual Conference Content Access, Virtual Online)

   This project was designed to address three major challenges faced by undergraduate engineering students (UES) and pre-service teachers (PSTs): 1) retention for UESs after the first year, and continued engagement when they reach more difficult concepts, 2) to prepare PSTs to teach engineering, which is a requirement in the Next Generation Science Standards as well as many state level standards of learning, and 3) to prepare both groups of students to communicate and collaborate in a multi-disciplinary context, which is a necessary skill in their future places of work. This project was implemented in three pairs of classes: 1) an introductory mechanical engineering class, fulfilling a general education requirement for information literacy and a foundations class in education, 2) fluid mechanics in mechanical engineering technology and a science methods class in education, and 3) mechanical engineering courses requiring programming (e.g., computational methods and robotics) with an educational technology class. All collaborations taught elementary level students (4th or 5th grade). For collaborations 1 and 2, the elementary students came to campus for a field trip where they toured engineering labs and participated in a one hour lesson taught by both the UESs and PSTs. In collaboration 3, the UESs and PSTsmore »worked with the upper-elementary students in their school during an after school club. In collaborations 1 and 2, students were assigned to teams and worked remotely on some parts of the project. A collaboration tool, built in Google Sites and Google Drive, was used to facilitate the project completion. The collaboration tool includes a team repository for all the project documents and templates. Students in collaboration 3 worked together directly during class time on smaller assignments. In all three collaborations lesson plans were implemented using the BSCS 5E instructional model, which was aligned to the engineering design process. Instruments were developed to assess knowledge in collaborations 1 (engineering design process) and 3 (computational thinking), while in collaboration 2, knowledge was assessed with questions from the fundamentals of engineering exam and a science content assessment. Comprehensive Assessment of Team Member Effectiveness (CATME) was also used in all 3 collaborations to assess teamwork across the collaborations. Finally, each student wrote a reflection on their experiences, which was used to qualitatively assess the project impact. The results from the first full semester of implementation have led us to improvements in the implementation and instrument refinement for year 2.« less
5. Use, Modify, Create: Comparing Computational Thinking Lesson Progressions for STEM Classes

   https://doi.org/10.1145/3304221.3319786  

   Lytle, Nicholas ; Barnes, Tiffany ; Cateté, Veronica ; Boulden, Danielle ; Dong, Yihuan ; Houchins, Jennifer ; Milliken, Alexandra ; Isvik, Amy ; Bounajim, Dolly ; Wiebe, Eric ( July 2019 , Proceedings of the 2019 ACM Conference on Innovation and Technology in Computer Science Education)

   Computational Thinking (CT) is being infused into curricula in a variety of core K-12 STEM courses. As these topics are being introduced to students without prior programming experience and are potentially taught by instructors unfamiliar with programming and CT, appropriate lesson design might help support both students and teachers. “Use-Modify-Create" (UMC), a CT lesson progression, has students ease into CT topics by first “Using" a given artifact, “Modifying" an existing one, and then eventually “Creating" new ones. While studies have presented lessons adopting and adapting this progression and advocating for its use, few have focused on evaluating UMC’s pedagogical effectiveness and claims. We present a comparison study between two CT lesson progressions for middle school science classes. Students participated in a 4-day activity focused on developing an agent-based simulation in a block-based programming environment. While some classrooms had students develop code on days 2-4, others used a scaffolded lesson plan modeled after the UMC framework. Through analyzing student’s exit tickets, classroom observations, and teacher interviews, we illustrate differences in perception of assignment difficulty from both the students and teachers, as well as student perception of artifact “ownership" between conditions.