Based on a systematic review we explore how empowerment has been articulated in 188 papers in Child-Computer Interaction (CCI) literature since 2003. Using an existing framework outlining functional, educational, democratic, mainstream, and critical empowerment, our analysis shows that while empowerment is rarely defined in CCI papers, a wide range of different articulations coexists. We explore the prevalence of different articulations in the literature and how this has shifted over time. We show that although empowerment has been part of the CCI discourse since the early days, a shift can be noticed in terms of how empowerment is articulated from an emphasis on empowerment in its functional meaning towards a more even distribution and the advent of critical articulations of empowerment. We conclude the paper by looking ahead into a new decade of CCI research and posing three questions to assist CCI researchers in more clearly articulating the nature and understanding of empowerment.

The rise of digital technologies and Machine Learning (ML)-tools for creative expression brings about novel opportunities for studying creativity and cognition at scale. In this paper, we present a pilot study of crea.blender SDG - an online GAN based image generation game. We designed crea.blender SDG with two goals in mind: The first, to let people create images relating to the United Nations Sustainable Development Goals (SDGs) and through them, engage in large-scale conversations on complex socioscientific problems. The second, as a fun and inspiring gateway for public participation in research, generating data for the creativity and cognition research and design community. Specifically in this pilot, we study and affirm that the design of crea.blender SDG is flexible enough to allow users to create images that express both anxiety and hope for the future; affirm that user generated images express these ideas in ways that are meaningful to people other than the original creator; and begin to investigate which specific features of images are more closely related to dystopian or utopian ideas of the future. Finally, we discuss implications for future design and research with ML-based creativity tools.

This paper presents a pilot study of NaturalLanguageProcessing4All (NLP4All), a Constructionist, low-threshold, XAI learning tool designed to bring Natural Language Processing methods into high school classrooms. Specifically, NLP4All is designed to let non-programmers explore different corpora of text through classification activities. Together with a high school Social Studies teacher, I developed a 2-week (6-hour) learning unit focusing on analyzing tweets from political parties to explore the differences and similarities between their policy views and communication styles. In the analysis, I find that text classification shows unexplored promise as a learning activity; that students were able to draw on their prior knowledge to classify tweets; that using NLP4All to collaboratively classify tweets led to productive classroom discussions; and that while students were able to build good machine learning models for classifying tweets, their rationales often focused on identifying one party, rather than distinguishing between parties. Finally, I discuss other educational contexts where NLP and ML can be productive for children, and future design features that may be worth exploring.

We present an interface for programming relationships between two or more NetLogo [18] models running concurrently. The interface is designed specifically to help high school aged novices explore and define computational relationships between agent-based models, and to investigate how prompting learners to reason about the relationships between complex systems may change how they reason about the systems individually.

Understanding processes of evolution and natural selection is both important and challenging for learners. We describe a "codefirst" learning environment called Frog Pond designed to introduce natural selection to elementary and middle school aged learners. Learners use NetTango, a blocksbased programming interface to NetLogo, to control frogs inhabiting a lily pond. Simple programs result in changes to the frog population over successive generations. Our approach foregrounds computational thinking as a bridge to understanding evolution as an emergent phenomenon.