ISLS 2022

Hiroshima, Japan
May 30–June 5, 2022
June 6–10, 2022
Conference Website

The ISLS Annual Meeting is a major international event, which hosts keynotes, symposia, workshops, panels, submitted paper sessions, and poster sessions. It covers timely and important issues and reports research findings across the entire field of the Learning Sciences. The ISLS Annual Meeting brings together those interested in learning experiences across schools, homes, workplaces, and communities who seek to understand how collaboration and learning are enabled by knowledge, tools, networks, and social structures. The ISLS Annual Meeting is a continuation of the International Conference of the Learning Sciences (ICLS) and the International Conference on Computer-Supported Collaborative Learning (CSCL).

Developing the Systems Thinking and Computational Thinking Identification Tool

Jonathan Bowers, Namsoo Shin, Linsey Brennan, Emil Eidin, A. Lynn Stephens, Steve Roderick

We developed the Systems Thinking (ST) and Computational Thinking (CT) Identification Tool (ID Tool) to identify student involvement in ST and CT as they construct and revise computational models. Our ID Tool builds off the ST and CT Through Modeling Framework, emphasizing the synergistic relationship between ST and CT and demonstrating how both can be supported through computational modeling. This paper describes the process of designing and validating the ID Tool with special emphasis on the observable indicators of testing and debugging computational models. We collected 75 hours of students’ interactions with a computational modeling tool and analyzed them using the ID Tool to characterize students’ use of ST and CT when involved in modeling. The results suggest that the ID Tool has the potential to allow researchers and practitioners to identify student involvement in various aspects of ST and CT as they construct and revise computational models.

Argumentation with Summary Tables in Geoscience Learning

Kathryn M. Bateman, Brandin Conrath, Scott McDonald, and Amy Pallant

In this study, we examine the interactions and discourse of a middle school classroom as they use a Summary Table to scaffold the generation of scientific arguments during the implementation of an online plate tectonics curriculum. Creating time and space for scientific discourse provided students with sense-making opportunities around complex science ideas to support their explanations of the phenomenon. The Summary Table scaffolded the development of increasingly sophisticated explanations by structuring students’ observations to connect with the driving question of the unit. Specifically, the Summary Table supported small and whole group discussions positioning students to argue and partake in open critique of their claims and evidence in increasingly public ways as they develop sophisticated science explanations.

Insights from Using a Systematic Design Process to Develop Classroom-based Assessment Resources for Measuring Elementary Students’ Science and Literacy Proficiencies

Gary Weiser, Alison K. Billman, Christopher .J Harris, Lauren M. Brodsky, and Daniel Damelin

The Framework and NGSS bring to the forefront the role of language in doing science and in learning from doing science. Yet, most existing science assessments for elementary learners do not integrate or attend to aspects of scientific language and literacy that are essential components of science proficiency. Accordingly, there is a need for high-quality classroom resources capable of providing teachers with information on where students are in the process of developing proficiency in science and scientific-specific literacy. In this paper, we present our design process for developing assessment resources – tasks, rubrics, and teacher support materials – and describe initial insights from using the process to develop resources for elementary grade classrooms. We highlight challenges and opportunities that have emerged from our work attending to the role of literacy assessing multi-dimensional science learning,
incorporating equity and inclusion considerations in assessment design, and embracing the
affordances of technology.

Applying Deweyan Perspective of Inquiry to Teaching Experimentation Using Simulation

Gey-Hong Gweon and Hee-Sun Lee

We investigated whether and how learning of experimental inquiry can be facilitated with computer simulations. As a theoretical framework, we built upon Dewey’s concept of the continuum of inquiry and identified three types of requisite knowledge that provide support for, and evolve with, experimental inquiry. Preliminary findings from two teachers’ classrooms indicate that teacher framing styles identified in the classroom discourse may be a factor in explaining contrasting student experimentation behaviors.

Collaborating Online Through a Pandemic: Designing Virtual Spaces for Rightful Presence

Rishi Krishnamoorthy, Tasha Austin, Ravit Golan Duncan, Edna Tan, Frieda Reichsman, Burrell Smithen, and Jaya Joshi

Since spring of 2020, our ‘new normal’ world pivoted towards online spaces. This changed where formal teaching and learning interactions unfolded, and also shifted the conditions for participation in teaching, learning and research activities calling into question how and where inequitable power dynamics are (re)produced in these ‘new’ spaces. In this paper, we reflect on the affordances and constraints of community-engaged research with middle school youth in online virtual design meeting ‘rooms.’ Drawing on critical postmodern and queer feminist constructions of space, the university researchers explicitly worked towards Rightful Presence when structuring and facilitating the online design meeting room. We argue that virtual spaces are not neutral and are shaped through settled power dynamics that can further (re)produce inequitable conditions for participating and/or open new possibilities for disrupting settled adult-youth powered relations by both youth and adults.

Agents, Models, and Ethics: Importance of Interdisciplinary Explorations in AI Education

Including William Finzer and Jie Chao

Artificial Intelligence (AI) is proliferating in both visible and invisible ways across our society. It is imperative for our new generation to gain a fundamental understanding of how intelligence is created, applied, and also its potential to perpetuate biases and unfairness. Because of the nature of AI, it is important that we take an interdisciplinary approach in order to ground the systems and models in real and meaningful contexts for learner exploration. This symposium explores these approaches with a multi-disciplinary group of researchers presenting empirical studies on designing and studying AI learning environments. These studies provide unique insights towards design recommendations, challenges, and opportunities in the rapidly emerging area of study in K-12 education.

Data Storytelling in the Classroom

Including Natalya St. Clair and A. Lynn Stephens

With the rising demand for data skills across industries and disciplines, and the prevalence of data in all aspects and levels of our lives, it is critical to find new, more effective ways to develop students’ data literacies. Stories can be an accessible way for students to personally connect to, and think critically about, data and its implications. But how can data storytelling be effectively implemented into classroom settings, in which instruction is often constrained to focus narrowly on quantitative skills? This interactive poster session showcases eight innovations in data storytelling in the classroom. Together, the contributions consider the various facets and functions of stories for supporting data literacies in contexts that span K-12 to university. By seeking to define the value and roles of storytelling in data literacy learning, this session will inform ways to create more effective and engaging data literacy instruction.

Professional Learning to Promote Three-Dimensional Teaching Using Computational Modeling in Remote Classroom Contexts

Namsoo Shin, Linsey Brennan, Jonathan Bowers, Emanuel Eidin, A. Lynn Stephens, Cynthia McIntyre, Steve Roderick, and Daniel Damelin

This study explores how to support teachers in developing and implementing effective pedagogical strategies to promote students in making sense of phenomena through computational modeling in remote contexts. Qualitative analyses of eight teachers’ interviews were conducted to characterize their pedagogical strategies to achieve three-dimensional learning. Findings indicate that typical teacher strategies include the teacher and students co-constructing a model and using whole class or group discussions to support students’ modeling practices.

Student Reflections on Data Investigations of Local and Extreme Weather: A Cultural Historical Activity Theory Perspective

Asli Sezen-Barrie, Josephine Louie, Brianna Roche, Emily Fagan, Pam Buffington, Brian Fitzgerald, Kevin Waterman, William Finzer, and Deb L. Morrison

This study analyzes middle-school students’ reflections on working with large-scale scientific data to investigate local extreme weather using the digital tool CODAP. Drawing from student focus group interviews and Cultural Historical Activity Theory, we examine factors that appeared to impede or facilitate data science learning in a sample of rural middle schools.

Examining Learning Opportunities for Integrating AI Education in English Language Art Classrooms

Cansu Tatar, Shiyan Jiang, Jie Chao, Kenia Wiedemann, James Fiacco, William Finzer, and Carolyn Rosé

We conducted a co-design study with high school ELA teachers to investigate their perspectives in the integration of a technology-enhanced AI curriculum. The teachers explored the AI and text mining activities and reflected on them from teaching and learning perspectives. The findings of this study suggest that building models with texts positioned ELA teachers as experts in AI teaching and they were empowered to identify existing learning resources and opportunities in ELA classrooms that could be leveraged in integrating AI learning in their classrooms.

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