Nexellence ResearchCORE Summer Program Information Session
Join the Nexellence Institute and Northwestern University’s Center for Talent Development (CTD) for an online information session introducing the ResearchCORE Summer Programs, high‑engagement academic research intensives for motivated middle and high school students.
Led by Dr. Michelle Yin, Associate Professor at Northwestern University, this session will provide an overview of the ResearchCORE curriculum, instructional approach, and the skill development pathways available for students entering grades 6–12.
Families will gain insight into how ResearchCORE supports students in building essential academic research competencies—from forming strong research questions to conducting data analysis using Python and presenting findings through formal research presentations. Participants will also hear about how these programs prepare students for advanced academic work, including IB Personal Projects, Extended Essays, AP Seminar, and A‑Level EPQs.
Program Pathways Covered
Nexellence ResearchCORE Foundation (Rising Grades 6–8)
A three‑week, in‑person program introducing students to the fundamentals of academic research.
Students will:
- Learn to frame testable research questions
- Design fair and ethical studies, including observations and simple experiments
- Understand sampling, consent, and research ethics
- Use Python to analyze and interpret real‑world datasets (no prior coding experience required)
- Create clear data charts and interpret correlations responsibly
- Produce a research brief and deliver a short research defense
Nexellence ResearchCORE Scholar (Rising Grades 9–12)
A three‑week, advanced intensive for high school students preparing for research‑based academic pathways.
Students will:
- Develop a focused research proposal supported by a mini literature review
- Select quantitative, qualitative, or mixed‑methods research designs
- Build data dictionaries and ethics‑informed feasibility plans
- Clean, analyze, and draw conclusions from real datasets using Python
- Design publication‑quality visualizations to support formal research presentations