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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.

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 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.

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.

The purpose of this study is to identify and assess collaborative problem solving (CPS) behaviors in elementary students in science, technology, engineering, arts/humanities and mathematics (STEAM)-related making and to garner students perspectives. We offer a valid way for researchers to understand collaborative processes and for educators to create opportunities for collaboration. Additionally, the feedback from the assessment offers students a way to reflect on their CPS skills.

This qualitative study evaluated 52 elementary students’ CPS skills using co-measure, a validated rubric assessing students’ CPS when working in STEAM-related makerspace activities. Students worked in collaborative groups to “make” artifacts when solving a problem posed by their teacher. They were assessed using co-measure’s four dimensions: peer interactions, positive communication, inquiry rich/multiple paths and transdisciplinary approaches and scored via each dimension’s associated attributes. Student interviews provided their perspectives on CPS.

A majority of students scored in the acceptable or proficient range in the social dimensions of peer interactions and positive communication. Students scored slightly lower on the cognitive dimensions of inquiry rich/multiple paths and markedly lower on transdisciplinary approaches when collaborating. Findings suggest to increase CPS skills, teachers might develop “making” activities fostering greater inquiry and model ways to strategize and verify information, approach the problem drawing on student interest and prior knowledge and collaboratively use tools, materials and methods that mimic the real world when problem-solving.

Much of the current research on assessing CPS during making is in the early stages of considering appropriate assessment approaches, especially in schools. To expand this literature the study includes elementary students between the ages of 6-10, the focus is on assessing their collaboration using an observational rubric. The authors use preliminary findings from young children’s perspectives on making to position the future work.