Nora Hernández

About Me

I hold a PhD in AI Education, with a strong focus on quantitative analysis and learning analytics. I have over 5 years of experience applying Bayesian statistics, machine learning, and mixed methods to complex educational data. My background spans Mechatronics, Computer Science, and Educational Technology, bridging theoretically-sound models with rigorous technical execution for strategic, data‑driven outcomes.

I am committed to translating insights into action. I have designed and evaluated learning programmes across Mexico and Hong Kong, developed culturally relevant curricula, and taught at the university level. I bring advanced analytical skills (R, Python) together with a deep understanding of how people learn. This combination allows me to contribute effectively to quantitative research, program evaluation, and the design of impactful learning experiences.

Quantitative Researcher AI Literacy & Ethics Learning Specialist Learning Analytics Bayesian & ML

Education

Ph.D. (AI Education)

The University of Hong Kong, 2021–2026

Thesis: Culturally‑Based Approaches for Artificial Intelligence Education with Music for Secondary School Students

M.Sc. Computer Science

Tecnológico de Monterrey, 2018–2020

M.Ed. Educational Technology and Innovation

Universidad del Valle de México, 2018–2020

B.Eng. Mechatronics

Tecnológico de Monterrey, 2011–2016

Skills

Languages & Tools

R (tidyverse, brms, lme4, bnlearn, Shiny), Python (Pandas, NumPy, Scikit-learn), Git, LaTeX, Excel.

Statistical Methods

Bayesian Inference (MCMC, Hierarchical Modeling), A/B Testing, Hypothesis Testing, Regression, Time Series, Causal Inference, Bayesian Networks.

Domain Expertise

Learning Analytics, Educational Data Mining, Sequence Process Mining, AI/ML Ethics, STEAM Education.

Learning & Development

Curriculum and Assessment Design, LMS workflows, Microsoft Office (Advanced Word, Excel, PowerPoint).

Languages

Spanish (native), English (fluent), German (basic), Mandarin (basic).

Research

Research Methods

Bayesian & Statistical Modeling

Bayesian inference (MCMC, regression, hierarchical models), hypothesis testing, regression analysis, causal inference, and A/B testing.

Machine Learning & NLP

Classification, topic modeling, sentiment analysis, and clustering using Python (Scikit-learn) and R, applied to educational and textual data.

Sequential & Process Mining

Sequence analysis, process mining, and pattern detection to model learner behaviors, interaction flows, and temporal dynamics in digital environments.

Qualitative & Mixed Methods

Thematic analysis, semi-structured interviews, reflective journals, and mixed-methods designs that integrate quantitative findings with rich contextual insights.

Research Interests

AI (in) Education

Designing equitable access for learning about AI while exploring how AI can enhance teaching and learning experiences.

Learning Analytics

Developing data‑driven approaches to understand students’ learning processes and enhance outcomes, acknowledging cultural context.

Culturally Relevant Education

Investigating how educational technologies can be designed to incorporate and honour diverse cultural perspectives.

STEAM Education

Examining approaches that integrate arts into AI education to foster creativity, innovation, and engagement.

Current Projects

Equitable ICT Education for Secondary School Students

In partnership with SEED Foundation and Impact Analytics, this longitudinal study examines the long‑term effects of ICT education on youth digital skills and opportunities.

Status: In progress (2022–2027)

Culturally‑based AI Education for Secondary School Students

My Ph.D. thesis investigates the effect of culturally relevant and cross‑cultural learning on students’ AI learning outcomes.

Status: Completed (2023–2025)

Publications

Journal Articles

Collaborating with classmates and AI to create music pieces: A topic modeling and sentiment analysis approach

BJET (In preparation)

Ng, D.K.T., Hernández López, N.P., Hu, X.

Interaction Patterns in AI Education: A comparison of two contexts

Under review, 2025

Hernández López, N.P., Hu, X., Wang, C., Ng, D.K.T.

Computing Education Meets the Arts: Insights from a Systematic Review

Review of Educational Research, Under Review

Hernández López, N.P., Hu, X.

Conference Proceedings

Insights from Culturally Relevant AI Education Programme for Secondary School Students

Artificial Intelligence in Education (AIED), 2025

Hernández López, N.P., Hu, X., Ng, D.K.T.

DOI: 10.1007/978-3-031-98465-5_35

WekiMusic: Machine Learning Music Activities to Foster Constructionist AI Education

IEEE ICALT, 2025

Hernández López, N.P., Hu, X.

DOI: 10.1109/ICALT64023.2025.00035

Perceptions of Learning Analytics Dashboard and Their Associations with Online Professional Learning Outcomes for College Teachers in the Global South

IEEE ICALT, 2025

Wang, C., Hu, X., Hernández López, N.P.

DOI: 10.1109/ICALT64023.2025.00040

Culturally Relevant Artificial Intelligence Education with Music for Secondary School Students

AIED, 2024

Hernández López, N.P., Hu, X.

DOI: 10.1007/978-3-031-64312-5_46

Preliminary Evaluation of Learning Analytics Dashboard for College Teachers' Online Professional Learning

IEEE ICALT, 2024

Wang, C., Ng, J.T.D., Hernández López, N.P., Hu, X.

DOI: 10.1109/ICALT61570.2024.00030

Needs Analysis of Learning Analytics Dashboard for College Teacher Online Professional Learning in an International Training Initiative for the Global South

LAK, 2024

Wang, C., Hu, X., Hernández López, N.P., Ng., J.T.D.

DOI: 10.1145/3636555.3636932

What Can Students Learn From Their Own Data? Data Literacy With Student-Facing Learning Analytics

ISLS Annual Meeting, 2023

Hernández López, N.P., Hu, X.

DOI: 10.22318/icls2023.579283

Student-facing Learning Analytics for Data Literacy: Findings from an Integrative Review

LAK, 2023

Hernández López, N.P., Hu, X.

DOI: 10.13140/RG.2.2.27533.04327

Book Chapters

Understanding Learning in Culturally Relevant Artificial Intelligence Education

LASI Europe 2024 DC, 2024

Hernández López, N.P.

CEUR Workshop Proceedings

Razonamiento Estadístico (Statistical Reasoning)

Conocimiento y Razonamiento Computacional, 2019

Estrada Real, A., Hernández López, N.P.

Academia Mexicana de Computación

Teaching

Teaching Philosophy

I draw on constructionism and culturally responsive pedagogy to design project‑based learning that makes knowledge meaningful and accessible . My goal is to create a learning environment where every learner feels capable, curious, and confident to apply what they have learned.

Teaching Qualifications

Certificate in Teaching and Learning in Higher Education

The University of Hong Kong, 2022

  • Completed a formal programme covering course design, active learning, assessment for learning, and inclusive pedagogy.

Teaching Experience

Teaching Assistant

MLIM7351: Information System Analysis and Development (Master’s level) – The University of Hong Kong, Spring–Fall 2024

  • Led special sessions on database design and SQL.
  • Provided individual consultations and graded assignments with detailed feedback.

Private Online Tutor

Computer Science & Mathematics – Students aged 8–14, 2021

  • Provided one‑to‑one tutoring, breaking down complex concepts into intuitive explanations.
  • Tailored instruction to each student’s learning style and maintained regular parent feedback.

Curriculum Designer

Aerobot Planet – Mexico, 2016–2020

  • Co‑created a summer‑camp and extra‑curricular robotics and coding curriculum for 8–14 year olds.
  • Designed project‑based learning activities and formative assessments.

Selected Projects

Culturally Relevant AI Literacy Programme

2024 – Mixed‑Methods Evaluation, R (sequence analysis, Bayesian modeling, NLP), Qualitative Interviews

  • Designed and delivered a 4‑week AI curriculum to 400+ secondary students in Mexico and Hong Kong.
  • Applied thematic analysis and NLP to student reflections, sequential analysis to student interactions with the WekiMusic platform, and used and Bayesian regression to model knowledge and sequences relationships.
  • Published at AIED 2024 and 2025; findings informed programme refinement.

WekiMusic: Machine Learning Music Activities

2024 – Constructionist AI Education, Weka, JavaScript, OSC

  • Developed an interactive tool where students use Machine Learning models to experiment with music.
  • Conducted usability testing with secondary school students to measure engagement and learning outcomes.
  • Presented findings at IEEE ICALT 2025.

Learning Analytics Dashboard for Teacher Training

2024 – Data Visualisation & Evaluation, Pre‑/Post‑test Analysis

  • Co‑developed an interactive dashboard for college teachers in the Global South to monitor engagement and learning outcomes.
  • Performed needs analysis and statistical evaluation (t‑tests, effect sizes) to measure professional learning gains.
  • Published at LAK 2024.

Contextual Hybrid Bayesian Recommender System

2020 – Master’s Thesis, Bayesian Networks, Hybrid Recommendation, R/Python

  • Built a Bayesian network model encoding user preferences, item attributes, and contextual factors (time, location, mood).
  • Designed a two‑stage hybrid architecture (collaborative + content‑based) to produce recommendations under data sparsity.
  • Validated the model with expert knowledge and real‑world user data; conducted a usability study showing improved practical usefulness over a state‑of‑the‑art baseline.

Service & Outreach

Public Talks & Presentations

SCAPE Seminar: AI in Education

The University of Hong Kong (March 2025)

Shared insights on culturally relevant AI tools for developing student creativity. Audience: faculty and students from HKU Education.

Panel de Discusión: El Papel de la Mujer en la Ciencia

Consulate General of Mexico, Hong Kong (March 2023)

Panelist discussing challenges and opportunities for women in science abroad.

TALE 2022 Interdisciplinary Postgraduate Student Forum

IEEE TALE (November 2022)

Presented doctoral research in a round‑table format. Recipient of 2nd Runner Up Award.

Forum for Social Experiments for AI in Education

Peking University, China (October 2022)

Shared insights on integrating arts into computer science and AI education.

Professional Learning

Doctoral Consortiums

  • AIED 2024 – Recife, Brazil
  • LASI Europe 2024 – Jeréz de la Frontera, Spain

Learning Analytics Summer Institute

  • LASI 2023 – Singapore (Erik Duval Travel Scholarship)
  • LASI 2022 – Canada (online) (Erik Duval Travel Scholarship)

Volunteering (Conferences)

AIED 2025

Italy (July 2025)

  • Assisted with registration, supported chairs and speakers.

JCDL 2024

Hong Kong (December 2024)

  • Assisted with registration, logistics, and poster session facilitation.

AIED 2024

Brazil (July 2024)

  • Supported registration and in‑person sessions.

ISMIR 2022

India (online, December 2022)

  • Supported online sessions.

Contact

Get in Touch

Location

Hong Kong

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