Research

Since the introduction of ChatGPT in 2022, large language models have surged in popularity; the computational demands of these tools have led to a significant rise in data center development—and public backlash. Using news and social media discourse as proxies, we aim to understand how people discuss this issue and the potential implications for policymakers, researchers, and the media that may follow.

This chapter explores how research about the digital divide, its meaning, and the actions resulting from it, have changed over the past few decades. The goal of this chapter is to analyze the body of scholarship about the digital divide in order to better understand past progress and potential avenues for further research. As a “meta” study of others’ work and research, this chapter presents a content analysis that explores what previous digital divide research has studied and how it has been conducted. This chapter concludes that there are opportunities to 1) continue refining the concepts used to understand the digital divide, 2) gather and analyze data that will contribute to a deeper, better understanding of the problem, and 3) engage with advocacy groups and policymakers at every level of government.

Social emotional learning (SEL) is commonly taught in elementary schools, but lack of personnel and resources make it hard to provide individualized instruction. To inform our design, we analyzed interviews (N=5) and classroom observations (N=7) from teachers and noted common themes and takeaways. Using these themes and takeaways, we designed an AI-powered robot coach that can teach SEL lessons to students following a provided lesson plan (composed of interaction "stages"). We predict that the condition with more robot emotion (fictional self-disclosure) will increase the depth and effectiveness of the interaction.