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Creators/Authors contains: "Herro, Danielle"

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  1. ; ; ; ( , Information and Learning Sciences)
    Purpose

    This study is part of a participatory design research project and aims to develop and study pedagogical frameworks and tools for integrating computational thinking (CT) concepts and data science practices into elementary school classrooms.

     Design/methodology/approach

    This paper describes a pedagogical approach that uses a data science framework the research team developed to assist teachers in providing data science instruction to elementary-aged students. Using phenomenological case study methodology, the authors use classroom observations, student focus groups, video recordings and artifacts to detail ways learners engage in data science practices and understand how they perceive their engagement during activities and learning.

     Findings

    Findings suggest student engagement in data science is enhanced when data problems are contextualized and connected to students’ lived experiences; data analysis and data-based decision-making is practiced in multiple ways; and students are given choices to communicate patterns, interpret graphs and tell data stories. The authors note challenges students experienced with data practices including conflict between inconsistencies in data patterns and lived experiences and focusing on data visualization appearances versus relationships between variables.

     Originality/value

    Data science instruction in elementary schools is an understudied, emerging and important area of data science education. Most elementary schools offer limited data science instruction; few elementary schools offer data science curriculum with embedded CT practices integrated across disciplines. This research assists elementary educators in fostering children's data science engagement and agency while developing their ability to reason, visualize and make decisions with data.

     
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  2. ; ; ( , European Journal of Engineering Education)
    Manufacturing engineers work in teams with a wide range of skills and credentials. Teamwork and collaborative problem solving (CPS) skills enable higher productivity and efficiency. However, these skills are largely absent from engineering education curricula and research in contexts involving multi-educational teams inclusive of technical college engineering students. We address this gap in research and practice through a qualitative case study exploring the contributions, experiences, and perspectives of technical college students working in multi-educational level teams to solve real-world engineering manufacturing problems. Data analyses resulted in six themes: (1) positive team culture, (2) valuing industry skills, (3) sharing responsibilities to iteratively make changes, (4) applying technical roles, (5) peer interactions, and (6) career preparation. Technical college students’ perceptions of challenges and successes are also discussed. Results imply that to effectively promote CPS and teamwork in similar contexts educators and industry leaders should consider the importance of (1) valuing students’/workers’ current professional identities while promoting productive conflict, (2) respecting differing team roles while encouraging skill development, and (3) fostering future career skills. 
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  3. ; ; ; ; ( , The Journal of Experimental Education)
    The importance of data literacies and the shortage of research surrounding data science in elementary schools motivated this research-practice partnership (RPP) between researchers and teachers from a STEM elementary school. We used a narrative case study methodology to describe the instructional practices of one music teacher who co-designed a data science curricular unit during a summer professional development program and implemented it in her 5th-grade music classroom. Data collected for this study include in-person and video observations, reflective journals, artifacts, and interviews. Findings suggest that this teacher integrated data science literacies into her classroom by supporting multiple avenues for data storytelling and relying on learners’ everyday discourse and experiences. Our study details a practical example of implementing data science with non-STEM domains in elementary classrooms. 
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  4. ; ; ; ( , Teaching and Teacher Education)
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  5. ; ; ; ; ( , Journal of Engineering Design)
    null (Ed.)
    This study explored seven engineering graduate students’ collaborative problem-solving (CPS) skills while working in interdisciplinary teams. Students worked in two different teams, in face-to-face and online environments, to solve complex manufacturing design challenges posed by their instructor. The students were assessed using an observational rubric with four dimensions: peer interactions, positive communication, tools and methods and iteration and adaption, and scored via each dimension’s associated attributes, and subsequently interviewed. Six students scored emergent or proficient in CPS and had slightly higher CPS scores during the second observation. One student demonstrated a limited ability for CPS and the observable CPS skills decreased during the project. Interviews revealed the importance of (1) relying on instructor and student chosen technologies for collaborative tasks, (2) recognising and drawing on peer expertise early in the project, (3) building trust during and outside of team meetings and (4) valuing off-site and online collaborative work. Findings advance the understanding of how graduate students working in interdisciplinary teams rely on particular features of collaboration to solve engineering design challenges, which may assist in developing future skills and fostering productive teamwork. 
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