Teaching | Ehsan Misaghi

AI Literacy for INT D 403 (Foundations of Collaborative Care)

Mon, 01 Sep 2025 00:00:00 -0600

Overview

Delivered teaching on foundational AI literacy for health professional learners in a collaborative care context.

Key Take Aways

AI is already part of healthcare and will grow in importance/usage
Understanding how to use AI critically is part of being a modern health professional
Your assignment is a chance to practice role clarity, collaboration, and AI literacy together

Discovery Learning (Medical Students)

Sun, 01 Sep 2024 00:00:00 -0600

I facilitate discovery learning sessions for medical students using small-group, case-driven inquiry. I teach using the Socratic method and direct the students in the direction that will enhance their learning based on their individual needs. Learners work through clinical presentations to identify what they know, what they need to learn, and how to justify decisions using evidence—building clinical reasoning, teamwork, and self-directed learning skills.

Teaching Assistant - BIOL 207 (Molecular Genetics and Heredity)

Sat, 01 Jan 2022 00:00:00 -0600

Overview

Supported undergraduate learning in BIOL 207: Molecular Genetics and Heredity at the University of Alberta, for which I was nominated for by my students and received teaching awards. The course covers the chromosomal and molecular basis of gene transmission and function, mapping strategies, gene isolation approaches, and regulatory mechanisms in prokaryotes and eukaryotes.

Responsibilities

Facilitated student learning in tutorials/labs and supported concept mastery
Demonstrated methods/approaches and provided real-time feedback
Supported assessment and learner success through structured guidance and marking

Key takeaways

Genetics concepts “stick” when students practice moving between mechanism → prediction → interpretation
Clear feedback loops (what to fix, why it matters, how to verify) accelerate learning and confidence
Good assessment support emphasizes reasoning and evidence hygiene, not memorization

AI in Medicine Course

Wed, 01 Sep 2021 00:00:00 -0600

Teaching Assistant - ZOOL 303 (Animal Developmental Biology)

Wed, 01 Sep 2021 00:00:00 -0600

Overview

Supported undergraduate learning in ZOOL 303: Animal Developmental Biology at the University of Alberta, for which I received commendations from the Faculty. The course introduces principles of animal development across vertebrates and invertebrates and integrates molecular, cellular, and comparative perspectives to explain embryogenesis and organ system development.

Responsibilities

Supported students with developmental biology concepts and mechanisms
Facilitated learning through guided problem-solving and discussion
Helped learners connect experimental evidence to developmental outcomes

Key takeaways

Students learn development best by linking gene regulation + cell interactions + morphology
“Mechanism first” teaching reduces rote memorization and improves transfer across model organisms
Structured reasoning (what changes, when, and why) improves interpretation of experimental results

Software Educator - MATLAB/Simulink and HSPICE/PSPICE

Fri, 15 Jun 2012 00:00:00 +0330

Overview

Provided hands-on instruction to support engineering learners in coding, computational modeling and simulation, focusing on practical tool fluency and systematic debugging.

Tools taught

MATLAB (data analysis, visualization, basic modeling)
Simulink (block-diagram modeling and simulation)
HSPICE / PSPICE (circuit simulation and verification)

Teaching approach

Live demonstration → guided practice → independent problem-solving with feedback
Debugging as a skill: inputs → assumptions → model → outputs → verification → feedback
Emphasis on interpretation: what the model means and how to validate results

Teaching Assistant - Biomedical Engineering & Computing Courses

Fri, 15 Jun 2012 00:00:00 +0330

Overview

Supported instruction and assessment in core biomedical engineering and computing coursework, emphasizing problem-solving, conceptual mastery, and application.

Courses supported

Introduction to Biomedical Engineering
Principles of Medical Imaging
Computer Programming

Responsibilities (edit to match what you actually did)

Supported tutorials/problem sessions and office hours
Helped create/mark problem sets, quizzes, and/or exams
Assisted learners with debugging, conceptual clarity, and applying methods to real-world problems

Key takeaways

Students progress fastest when problems are scaffolded from fundamentals → application → edge cases
Programming competence improves when learners adopt a structured troubleshooting workflow
In medical imaging, linking physics + signal processing + interpretation improves transfer across modalities