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We report on our work collaborating with two Bay-Area middle-school (grades 6, 7, and 8) districts to design, implement, and research the use of text visualizations in supporting English Language Arts and data literacy learning outcomes. Through co- design, classroom research, and participatory professional development with English Language Arts teachers, the project developed and tested text analytics tools, visualizations, and pedagogical routines. This article overviews the constraints we encountered, including technical constraints related to devices, access, and use, and pedagogical constraints including teacher and classroom time, and highlights a few strategies developed in response to those constraints. Drawing on classroom video, co- design sessions with teachers, and qualitative interviews, we find that “small” data visualizations that visualize text mining data created on single texts or small excerpts may support student data literacy and self-e!cacy as well as the development of a more expansive linguistic-experiential reservoir. We present a routine, “What did the computer miss?”, used by our collaborating teachers to support thinking with and about computing technologies that works especially well with single-/small- text data visualizations in the middle-school context, and conclude with suggestions and future directions for research and collaboration. 

This paper uses interaction analysis to examine an episode moment-by-moment of how a group of educators recognized and acknowledged that a specific design decision could be harmful for a historically marginalized population of students enrolled in the district. However, once a key change was made to be more culturally responsive and considerate, new and unexpected pedagogical challenges appeared. This case serves to illustrate some of the unexpected tensions that can appear in real-time when unanticipated questions about cultural relevance are foregrounded during lesson and materials co-design. It also serves as a reminder that educational technologies are not “race” neutral. 

Interactive data learning tools provide explorable ways for students to build intuitions about data, data representations, and statistical parameters. However, these tools rely on visual consumption and are not accessible to blind and low vision (BLV) students. In this work, we investigate opportunities to leverage active exploration, enriched with multimodal feedback and embodied interaction, to foster an understanding of the relationships among individual data values, data representations, and statistical measures. We explore these opportunities in the form of an accessible learning platform that allows students to hear and feel how statistical measures are changing in real time as they construct and manipulate physicalized data representations. We introduced the platform to four teachers of students with visual impairments (TVIs) through a two-hour-long focus group. TVIs embraced the platform’s exploratory nature and universality and recommended the consideration of additional auditory and texture-based interactions to enhance engagement.