Computational thinking (CT), the ability to devise computational solutions for real‐life problems, has received growing attention from both educators and researchers. To better improve university students' CT competence, collaborative programming is regarded as an effective learning approach. However, how novice programmers develop CT competence through collaborative problem solving remains unclear. This study adopted an innovative approach, quantitative ethnography, to analyze the collaborative programming activities of a high‐performing and a low‐performing team. Both the discourse analysis and epistemic network models revealed that across concepts, practices, and identity, the high‐performing team exhibited CT that was systematic, whereas the CT of the low‐performing team was characterized by tinkering or guess‐and‐check approaches. However, the low‐performing group's CT development trajectory ultimately converged towards the high‐performing group's. This study thus improves understanding of how novices learn CT, and it illustrates a useful method for modeling CT based in authentic problem‐solving contexts.
A Case Study of Middle Schoolers’ Use of Computational Thinking Concepts and Practices during Coded Music Composition
Researchers and practitioners have demonstrated various benefits
of introducing computational thinking (CT) through music com-
position coding. While researchers have studied the impacts on
participant attitudes towards CT and their learning of CT concepts,
more case studies are needed on both learning CT concepts as well
as CT practices, i.e., the processes of constructing music coding
projects. This paper presents a case study of middle schoolers in
an informal learning environment focused on integrating music
composition with coding in TunePad. Specifically, we collected and
analyzed logs of coding events, final code products, and surveys to
explore both CT concept use and CT practices exhibited by the par-
ticipants as they completed open-ended music coding activities to
create their own melodies with specific music and CT requirements
and recommendations
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- Award ID(s):
- 2048793
- NSF-PAR ID:
- 10322529
- Date Published:
- Journal Name:
- 27th ACM Conference on Innovation and Technology in Computer Science Education
- Volume:
- 1
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract -
null (Ed.)In order to expand opportunities to learn computer science (CS),there is a growing push for inclusion of CS concepts and practices, such as computational thinking (CT), in required subjects like science. Integrated, transdisciplinary (CS/CT+X) approaches have shown promise for broadening access to CS and CT learning opportunities, addressing potential self-selection bias associated with elective CS coursework and afterschool programs, and promotinga more expansive and authentic contextualization of CS work. Emerging research also points to pedagogical strategies that can transcend simply broadening access, by also working to confront barriers to equitable and inclusive engagement in CS. Yet, approaches to integration vary widely, and there is little consensus on whether and how different models for CS and CT integration contribute to desired outcomes. There has also been little theory development that can ground systematic examination of the affordances and tradeoffs of different models. Toward that end, we propose a typology through which to examine CT integration in science (CT+S). The purpose of delineating a typology of CT+S integration is to encourage instantiation, implementation, and inspection of different models for integration, and to promote shared understanding among learning designers, researchers, and practitioners working at the intersection of CT and science. For each model in the typology, we characterize how CT+S integration is accomplished, the ways in which CT learning supports science learning, and the affordances and tensions for equity and inclusion that may arise upon implementation in science classrooms.more » « less
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There is increasing interest in broadening participation in computational thinking (CT) by integrating CT into pre-college STEM curricula and instruction. Science, in particular, is emerging as an important discipline to support integrated learning. This highlights the need for carefully designed assessments targeting the integration of science and CT to help teachers and researchers gauge students’ proficiency with integrating the disciplines. We describe a principled design process to develop assessment tasks and rubrics that integrate concepts and practices across science, CT, and computational modeling. We conducted a pilot study with 10 high school students who responded to integrative assessment tasks as part of a physics-based computational modeling unit. Our findings indicate that the tasks and rubrics successfully elicit both Physics and CT constructs while distinguishing important aspects of proficiency related to the two disciplines. This work illustrates the promise of using such assessments formatively in integrated STEM and computing learning contexts.more » « less
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We develop computing practices for neurodiverse learners. While many researchers in special education adopt a behavioral perspective, we leverage a neurodiversity perspective that is more widely accepted within the autism community itself. We report on an initial phase of a research-practice partnership with a pilot cohort of four middle school teachers with whom we are co-designing embodied musical practices using networked Internet of Things (IoT) wearables with embedded inertial measurement units (IMUs). Our culturally and epistemically diverse teaching fellows work with diverse student populations (Black, Brown, Native American, neurodivergent) at Title 1 schools. The neurodiversity perspective sensitizes our co-design to tactile, kinetic, sensory, and ensemble energies that overflow neurotypical learning modalities, which typically privilege screen- based interaction, cognitivism, and isolation. We find “wearable music” to be an inclusive, mobile, and mobilizing computing approach that foregrounds embodied interactions in fun and engaging group activities surfacing computational thinking (CT). In later phases of this research, our teaching fellows will run workshops for additional educators, scaling the curriculum for implementation and evaluation in many more classrooms.more » « less
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Massachusetts defined K-12 Digital Literacy/Computer Science (DLCS) standards in 2016 and developed a 5-12 teacher licensure process, expecting K-4 teachers to be capable of teaching to the standards under their elementary license. An NSF CSforAll planning grant led to the establishment of an NSF 4-year ResearchPractice Partnership (RPP) of district and school administrators, teachers, university researchers, and external evaluators in 2018. The RPP focused on the 33 K-5 serving schools to engage all students in integrated CS/CT teaching and learning and to create a cadre of skilled and confident elementary classroom teachers ready to support their students in learning CS/CT concepts and practices. The pandemic exacerbated barriers and inequities across the district, which serves over 25,000 diverse students (9.7% white/nonHispanic, 83.7% high needs). Having observed a lack of awareness and expertise among many K-5 teachers for implementing CS/CT content and practices and seeing barriers to equitable CS/CT teaching and learning, the RPP designed an iterative, teacher-led, co-design of curriculum supported by equity-focused and embedded professional learning. This experience report describes how we refined our strategies for curriculum development and diffusion, professional learning, and importantly, our commitment to addressing diversity, equity, and inclusion beyond just reaching all students. The RPP broadened its focus on understanding race and equity to empower students to understand how technology affects their identities and to equip them to critically participate in the creation and use of technologymore » « less
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