amightyo (Itauma Itauma) · GitHub
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amightyo/README.md

Hello, I'm Dr. Itauma Itauma 👋

Associate Professor of Data Science and Analytics Harrisburg University

I am an analytics researcher and educator passionate about using data to understand not just what happens, but why it happens. My work integrates artificial intelligence, learning analytics, advanced quantitative methods, and evidence synthesis to develop data-driven solutions for education, health, and organizational decision-making.

I enjoy collaborating on interdisciplinary research that bridges theory, analytics, and practical impact.


🔬 Research Interests

  • Artificial Intelligence
  • Human–AI Decision-Making
  • AI Literacy & Responsible AI
  • Learning Analytics
  • Data Science
  • Structural Equation Modeling (SEM)
  • Bayesian Statistics
  • Meta-analysis
  • Bibliometric Analysis
  • Health Analytics
  • Evidence-Based Decision Making

🛠 Tools & Technologies

Programming & Analytics

  • R
  • Python
  • SAS
  • Stata
  • SQL

Statistical Software

  • Jamovi
  • JASP

Data Visualization & Reporting

  • Power BI
  • Quarto
  • LaTeX

Version Control

  • Git
  • GitHub

📚 Current Research

  • Human–AI Decision-Making and Responsible AI
  • AI Decision-Support Meta-analysis
  • Bayesian Health Analytics
  • Structural Equation Modeling in Education
  • Learning Analytics & Student Success
  • Systems Thinking in Higher Education
  • Bibliometric Analysis of Emerging AI Research

🎓 Teaching

Graduate and doctoral courses in:

  • Structural Equation Modeling
  • Machine Learning
  • Artificial Intelligence
  • Bayesian Data Analysis
  • Learning Analytics
  • Research Design
  • Advanced Analytics

🤝 Collaboration

I welcome collaborations in:

  • Artificial Intelligence
  • Human–AI Collaboration
  • Learning Analytics
  • Health Analytics
  • Evidence Synthesis
  • Structural Equation Modeling
  • Bayesian Statistics
  • Meta-analysis
  • Data Science Education
  • Interdisciplinary Analytics Research

🌱 Research Philosophy

I believe analytics should move beyond prediction toward explanation.

My goal is to help researchers, students, and organizations make better decisions by combining rigorous quantitative methods with meaningful theoretical questions. Whether using Structural Equation Modeling, Bayesian inference, machine learning, or meta-analysis, I strive to generate evidence that advances both scientific knowledge and practical impact.


📫 Connect

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  1. anly550-sem-student-engagement anly550-sem-student-engagement Public

    Teaching demonstration materials for ANLY 550 Structural Equation Modeling.

  2. DrItauma-NU/MTH-3340 DrItauma-NU/MTH-3340 Public

    Statistics II

  3. MachineLearning MachineLearning Public

    Jupyter Notebook 1

  4. AI_fundamentals AI_fundamentals Public

    Forked from udacity/AI_fundamentals

    Jupyter Notebook

  5. EDA_Course_Materials EDA_Course_Materials Public

    Data Analysis with R Course Materials. UDACITY!

    HTML

  6. SASsy SASsy Public

    Forked from lpezet/SASsy

    ECL Bundle helper for SAS Users

    ECL