The artifacts selected for EDTC 813 reflect a cohesive inquiry arc focused on informal learning and the emerging role of artificial intelligence, specifically ChatGPT, in educational practice. Together, they demonstrate my ability to design research instruments, collect and analyze qualitative and quantitative data, apply professional software tools such as Atlas.ti and Qualtrics, and communicate findings through formal written reports. This course deepened my competency as both a researcher and a practitioner, prepared to navigate the rapidly evolving landscape of educational technology.

Artifact: Assessment 1 — Informal Learning Interview (Video + Questions + Transcript)

Rationale: This informal learning interview, comprising the video recording, interview questions, and annotated transcript, documents a real-world qualitative inquiry into how educators engage with informal learning outside of structured institutional settings. I selected this multi-component artifact because it demonstrates my competency in qualitative data collection, research design, and reflective practice simultaneously. Conducting and analyzing an authentic interview required me to apply the research skills developed throughout my doctoral program while exercising the listening and communication competencies that are central to my work as a Clinical Supervisor. This artifact reflects the integration of technology tools (video recording, document analysis) with scholarly inquiry, and it underscores my commitment to understanding learning as a dynamic, lifelong process that extends far beyond the classroom.

Artifact: Assessment 2 — Survey on Teachers' Perspectives on ChatGPT in Education (Qualtrics)

Rationale: This survey, designed and deployed using Qualtrics through NJCU, investigates teachers' perspectives on the use of ChatGPT in educational settings, one of the most timely and consequential questions in educational technology today. I selected this artifact because it demonstrates my ability to design rigorous, IRB-aligned survey instruments and to leverage institutional research platforms to collect meaningful data from educational practitioners. As an educator who works at the intersection of technology and child development, I approached this topic with both scholarly curiosity and professional urgency. The survey design reflects my understanding of research ethics, questionnaire construction, and the importance of centering teacher voice in educational technology decision-making. This work directly informs my growing expertise in the responsible and pedagogically sound integration of artificial intelligence in education.

Artifact: Assessment 3 — Informal Learning Report: Analyzing Data Collaboratively with Atlas.

Rationale: This informal learning report documents the process of collaborative qualitative data analysis using Atlas.ti, a professional-grade software platform for qualitative research. I selected this artifact because it represents a significant methodological milestone in my doctoral development: the application of systematic, software-supported qualitative coding to real data in a collaborative context. Atlas.ti is widely used in dissertation-level research across the social sciences, and this experience prepared me directly for the qualitative analysis I will conduct in my own dissertation. Beyond the technical skill development, this artifact also reflects my belief that research is strengthened by collaboration and dialogue, a value I carry into every professional context, from clinical team meetings to academic partnerships.

Artifact: Final Report — Turn Raw Survey Data into a Descriptive Report (Teacher Opinions on ChatGPT)

Rationale: This final report synthesizes the raw survey data collected on teachers' opinions about ChatGPT in education into a structured, professionally written descriptive analysis. I selected this as the capstone artifact of EDTC 813 because it demonstrates the full research cycle: from instrument design and data collection to analysis, interpretation, and formal reporting. The topic, artificial intelligence in education, is not only academically significant but personally relevant, as I actively explore how AI tools can responsibly support the learning and development of bilingual and neurodiverse children. This report reflects my capacity to conduct applied research with rigor and to communicate findings in a format accessible to practitioners, administrators, and scholars alike. It also demonstrates my proficiency with integrated software tools, which is central to the Fundamentals of Educational Technology Leadership domain.