Department of Educational Theory and Practice Abstracts

Presenters: Maria Goebert

Showcase Advisor: Jianwei Zhang

Abstract: Multilingual learners make up a significant portion of many world language classrooms. In less commonly taught languages, such as Russian, heritage speakers and non-heritage learners often share the same classes. Teachers in these settings must differentiate instruction to meet the 
diverse needs of their students.  

This qualitative study explores the perspectives of twelve Russian language educators, working across various educational settings, on the language learning needs of multilingual students in linguistically diverse classrooms. It examines how these teachers adapt their instruction to support their students and meet the demands of different teaching modalities. The study also illuminates Russian language educators’ perspectives on effective professional development sessions in support of their work with linguistically diverse learners. By highlighting educators’ perceptions and practices, this study aims to clarify the role of world language classes and address ongoing questions about effectively supporting multilingual learners.

Presenters: Jaesung Park, Devan Walton, Gregory Massara, Yingru Zhao, Soojeong Ahn

Showcase Advisor: Haesol Bae

Abstract: The climate crisis calls on K-12 teachers to understand and practice climate change education (CCE) and to determine how they teach it in the classroom. Its wickedness as a global issue requires them to reflect on their individual beliefs and values to better articulate their ideas on the design and implementation of climate change curricula. We propose teachers’ collaborative exploration and inquiry of diverse pedagogical approaches to CCE as a foundation for relevant professional development for K-12 educators. This research is a preliminary study exploring the theoretical standpoint of how K-12 teachers can develop and elaborate their ideas on CCE through discussions with their colleagues. In addition, the highlights from the authors’ group discussion on the diversity of teaching orientations to and pedagogical perspectives on CCE will be presented to exemplify how the collaborative exploration of diverse approaches to CCE can be an effective way to support teachers’ professional development.

Presenters: Lei Ding

Showcase Advisor: Jianwei Zhang

Abstract: This study investigates students' understanding of AI and their engagement with AI in authentic research experiences. The design of authentic research experiences is conducted under the framework of community-based learning and Knowledge Building. The participants were 12th-grade students who participated in the Innovative Solutions project supported by three teachers and a cluster of professional partners from community-based organizations. A survey was conducted to investigate students' perception of AI and their engagement with AI for their schoolwork, including authentic research experiences. Thematic analysis of survey data revealed core facets of students' epistemic understanding of good research, including aims, criteria, and process. As compelling themes, students were aware of the personal and social impact of AI, and thus think that they should be independent of learning when using AI, and use AI for guidance to learn as well. The findings inform educational designs to integrate AI in authentic research experiences among students.

Presenters: Lin Zhu

Showcase Advisor: Jianwei Zhang

Abstract: This qualitative self-study explores human and AI collaboration in beginner game design. Through iterative prompting, a novice developer built a small HTML game, Number Explorer, with ChatGPT. Guided by constructionist gaming and COFI frameworks, the analysis examined chat logs, code versions, and reflective notes. Findings show that over time, the learner shifted from simply requesting code to actively managing the partnership and making decisions based on game feel. The study also highlights a tension between the AI's tendency to suggest familiar design templates and the learner's active pushback to protect the original game vision. Ultimately, the results suggest that AI-supported game making shifts core skills away from learning syntax toward goal setting, checking intended behavior, and steering the collaboration.

Presenters: Elham Tajik

Showcase Advisor: Jonathan Foster 

Abstract: Artificial intelligence (AI) is increasingly influencing K–12 education and has begun to reshape teaching practices. As AI-based educational technologies become more common, teachers play a critical role in determining how effectively these systems are integrated into classroom instruction. Previous research has explored factors that influence teachers’ trust in AI. For example, Nazaretsky et al. (2022) identified eight dimensions affecting teachers’ trust in AI-based tools, including the need for pedagogical shifts. Similarly, Depaepe et al. (2025) reported four factors shaping pre-service teachers’ trust and confidence in AI-based educational technologies. Despite these contributions, there is still limited understanding of how teachers’ perceptions of AI are structured and how these perceptions influence adoption in real classroom contexts.