Advances in artificial intelligence present a need for fostering AI literacy in workplaces. While there is a lack of research on how this can be achieved, there are documented successful approaches in child-computer interaction (CCI), albeit aimed at K-12 education. We present an in-vivo explorative case study of how CCI approaches can be adopted for adult professionals via a full-day workshop developed in collaboration with a trade union to upskill workers. Analyzing data from pre- and post-surveys, a follow-up survey, and materials produced by participants (n=53), we demonstrate how this increased participants’ knowledge of AI while their self-efficacy and empowerment did not improve. This is similar to findings from K-12 education, pointing to self-efficacy and empowerment as major challenges for AI literacy across sectors. We discuss the role of ambassadorships and professional organizations in addressing these issues, and indicate research directions for the CHI community.
https://doi.org/10.1145/3613904.3642607
ChatGPT has entered classrooms, circumventing typical training and vetting procedures. Unlike other educational technologies, it placed teachers in direct contact with the versatility of generative AI. Consequently, teachers are urgently tasked to assess its capabilities to inform their use of ChatGPT. However, it is unclear what support teachers have and need and whether existing documentation, such as model cards, provides adequate direction for educators in this new paradigm. By interviewing 22 middle- and high-school ELA and Social Studies teachers, we connect the discourse on AI transparency and documentation with educational technology integration, highlighting the information needs of teachers. Our findings reveal that teachers confront significant information gaps, lacking clarity on exploring ChatGPT's capabilities for bespoke learning tasks and ensuring its fit with the needs of diverse learners. As a solution, we propose a framework for interactive model documentation that empowers teachers to navigate the interplay between pedagogical and technical knowledge.
https://doi.org/10.1145/3613904.3642592
A growing number of students in higher education are using ChatGPT for various educational purposes, ranging from seeking information to writing essays. Although many universities have officially banned the use of ChatGPT because of its potential harm and unintended consequences, it is still important to uncover how students leverage ChatGPT for learning, what challenges emerge, and how we can make better use of ChatGPT in higher education. Thus, we conducted focus group workshops and a series of participatory design sessions with thirty students who have actively interacted with ChatGPT for one semester in university and with other five stakeholders (e.g., professors, AI experts). Based on these, this paper identifies real opportunities and challenges of utilizing and designing ChatGPT for higher education.
https://doi.org/10.1145/3613904.3642785
Collaborative technology provides powerful opportunities to engage young people in active learning experiences that are inclusive, immersive, and personally meaningful. In particular, interactive narratives have proven to be effective scaffolds for learning, and learnersourcing has emerged as a promising student-driven approach to enable personalized education and quality control at-scale. We introduce the first synthesis of these ideas in the context of teaching artificial intelligence (AI), which is now seen as a critical component of 21st-century education. Specifically, we explore the design of a narrative-based learnersourcing platform where engagement is centered around a learner-made choose-your-own-adventure story. In grounding our approach, we draw from pedagogical literature, digital storytelling, and recent work on learnersourcing. We report on our iterative, learner-centered design process as well as our study findings that demonstrate the platform’s positive effects on knowledge gains, interest in AI concepts, and the overall user experience of narrative-based learnersourcing technology.
https://doi.org/10.1145/3613904.3642198
ml-machine.org is a web- and micro:bit-based educational tool for building machine learning models designed to enable more widespread teaching of AI literacy in secondary education. It has been designed as a research product in collaboration with partners from the educational sector, including the Danish Broadcasting Corporation and the Micro:bit Educational Foundation. ml-machine.org currently has more than 5000 unique users and is used in schools and teacher training. It is publicly available and promoted on the broadcasting corporation's platforms. We describe the two-year process of developing and disseminating ml-machine.org. Based on interviews with partners and educators, we report on how ml-machine.org supports inquiry into the adoption and appropriation of such educational tools. We also provide insights on working with formal education infrastructures in order to scale and integrate a research product into teacher practices. Based on these experiences, we propose infrastructure as a novel quality of research products.
https://doi.org/10.1145/3613904.3642539