Publications & Academic Work

MA in Statistics

University of California, Los Angeles (UCLA)

BA in Mathematics/Economics, Minor in Statistics

University of California, Los Angeles (UCLA)

AI-Powered Cognitive Scaffolding Systems for Statistics Education

Proposed Research

Abstract:

This proposed research would investigate how AI-powered cognitive scaffolding systems affect learning outcomes in introductory statistics, with particular attention to diverse student populations across different institutional contexts. Through a mixed-methods randomized controlled trial, it would examine the effectiveness of adaptive AI tutoring that provides progressive hints and just-in-time support, addressing questions of trustworthiness, fairness, and equity in AI-enhanced education while building an open-source platform for free statistics education.

Keywords: AI in education, cognitive scaffolding, statistics education, educational equity, trustworthy AI, learning analytics

Rising Success, Persistent Gaps: Student-Level Statistics Outcomes Across California's Community College Placement-Reform Era (2018 to 2025)

Author: Safaa Dabagh

Journal: Community College Review (SAGE)

Submitted: June 2026

Status: Under Review

A student-level analysis of 867 transfer-level introductory statistics enrollments across 17 semesters (Fall 2018 to Fall 2025) at a large California community college, spanning the AB 705 and AB 1705 placement reforms. Course success rose steadily across the reform era (42% to 69%) and for every racial and ethnic group, which contradicts the premise that direct placement depresses outcomes, while a persistent gap of about 24 percentage points between White and Latinx students shows that broadened access alone did not equalize outcomes. The temporal trend is reported as correlational, with semester-clustered standard errors, composition-adjusted robustness checks, and confidence intervals on all subgroup estimates.

AI-Assisted Assessment Design in Mathematics and Statistics: A Multi-Course Bloom's Taxonomy Analysis of Cognitive Demand Shift

Author: Safaa Dabagh

Journal: Teaching Statistics

Status: Revise & Resubmit

A Bloom's-taxonomy analysis of how AI-assisted assessment design shifts the cognitive demand of mathematics and statistics course materials. Assessment items across multiple courses are coded by cognitive level to characterize where AI-supported design raises or lowers the demand placed on students, informing how instructors can use AI tools without eroding the rigor of their assessments.

Raising the Floor, Holding the Bar: Distributional Effects of AI-Assisted Course Design in Two Community College Mathematics Courses

Author: Safaa Dabagh

Repository: EdArXiv / OSF preprint

DOI: 10.35542/osf.io/x9nkw_v1

Status: Preprint Available

A distributional analysis of AI-assisted course design across two community college mathematics courses (College Algebra for STEM and Introductory Statistics). Rather than focusing on average outcomes, the study asks who is affected and where in the grade distribution. The strongest effect is a floor effect in algebra, where the lowest-performing students gained the most, alongside evidence that the validity of an assessment depends on how well it is aligned with the AI-designed instruction.

Socioeconomic Disadvantage, Not Gun Policy or Mental Illness, Is Associated With State-Level Mass Shooting Rates: A Negative-Binomial Panel Analysis, 2018 to 2024

Author: Safaa Dabagh

Repository: Research Square preprint

Status: Preprint Available

A state-year panel analysis of 3,783 mass-shooting incidents across the 50 U.S. states (2018 to 2024) using negative-binomial regression with a population offset, calendar-year fixed effects, and cluster-robust (CR2) standard errors, triangulated with LASSO and tree-ensemble variable selection. Socioeconomic disadvantage, meaning poverty and income inequality, which are statistically inseparable at the state level, is associated with higher mass-shooting incidence, while gun-law strength and mental-illness prevalence show no positive association. The discussion centers on how sensitive such conclusions are to the way “mass shooting” is defined.

Instructor of Mathematics with Main Focus on Statistics

Santa Monica College (SMC) • 2016-Present

• Math 54: Introductory Statistics
• Math 4/4C: College Algebra and other mathematics classes

West Los Angeles College • Ongoing

• Mathematics and statistics courses

Loyola Marymount University • Current

• Applied Statistics in Biology: Statistics course designed for life sciences students

Joyce University of Nursing and Health Sciences • Current

• Faculty-Adjunct: Statistics and data science courses for nursing and health sciences graduate programs

Teaching Approach:

• Hybrid and online course delivery
• Canvas LMS integration and course design
• Focus on educational equity and student success for diverse learners
• Experience across multiple institutional contexts (community colleges, research university)

AI in Education Certificates & Training In Progress

View my AI in Education journey for detailed progress tracking.

• Completed: Google AI for Educators
• In Progress: Coursera AI in Education
• Planned: Lehigh University Certificate in AI & Learning Analytics (Application 2026)

Programming & Statistical Analysis

• R: Advanced statistical analysis, data visualization (ggplot2), modeling
• Python: Data analysis (pandas, numpy), machine learning (scikit-learn), AI integration
• Statistical Methods: Regression, multilevel modeling, causal inference, survey analysis
• Learning Analytics: Educational data mining, student modeling, A/B testing

Educational Technology

• LMS: Canvas, course design, online pedagogy
• Web Development: HTML, CSS, JavaScript, Firebase
• AI Integration: Claude API, GPT API, prompt engineering
• Data Platforms: Google Colab, Jupyter notebooks, Observable

• Free Statistics Learning Platform: Building open-source educational resources accessible to all students regardless of financial means
• Community College Advocacy: Conducting research that centers community college student experiences and needs
• Educational Equity: Focus on understanding and addressing achievement gaps in STEM education
• Mommy Coding Camp: Teaching coding and computational thinking to children (Learn more)