An engineer’s habits. A teacher’s instincts.

I spent the first part of my career in information technology. After finishing a bachelor’s degree at Villanova University in Management Information Systems and International Business, I worked for a financial corporation as an information systems engineer, working with UNIX systems, mid-tier infrastructure, enterprise databases, scheduled website maintenance across the organization, and a stretch in Tier 2 support. This work taught me a specific habit of mind — when something breaks, you find out what is actually broken rather than relying on your assumptions, and you do not stop at the first explanation that would let you close the ticket.

Then I taught. I homeschooled a highly gifted student, taught Sunday school across several age groups, and assisted a parent-run organization advocating for gifted and twice-exceptional children in our school district. I wrote lesson plans, built and revised curriculum, and spent a lot of time with learners the standard learning designs had not anticipated.

For years I thought of those as two unrelated careers. They are not. Instructional design is where systems thinking and teaching intersect, and the questions are always the same: what is it that actually prevents a person from learning, and how can I help?

I completed my Master of Education in Curriculum and Instruction with a concentration in Educational Technology at the University of Florida (opens in a new tab), and my current work focuses on online learning in higher education environments.

Yana Rulinsky, smiling, wearing a pale top and a pearl necklace, in front of a wall of bookshelves.

What I believe about this work

Three principles have shaped everything on this site, and I hold all three of them close to my heart.

Quality. A course either meets the necessary standards, or it does not. In my design workflow, I utilize quality rubrics that somebody else can check, and I review my courses against the Quality Matters rubric standard by standard, which is genuinely a humbling exercise the first time you use it to evaluate your own work.

Equity. Close to one in five students in American postsecondary education has a disability, and a great deal of course material is still built as though that was not the case. Accessibility runs through nearly every project on this site — as the subject of a micro-credential, as Universal Design for Learning in a middle school unit, and as captioning and contrast decisions in an online course build. Accessibility is the constraint I design against and not a box I check at the end.

Innovation. I am a technology enthusiast with what I have always thought of as a “trust but verify” approach. New educational technology is worth trying and worth being skeptical about at the same time, and I would rather find out which than pick a side. My own research on the subject of instructional video in online courses and my work on student affect detection, both in the case studies, make the case.

Generative AI and EdTech in my design work

I use EdTech and AI technologies across my instructional design workflow — to derive a design specification from a body of research, to draft narration and assessment items against that specification, to create instructional videos and animation, to prepare accurate consent documentation, and to run preliminary analysis of my design decisions.

Having said that, there is a time and place for educational and generative AI technologies. I, the instructional and learning designer, plan, organize, design, develop, create, and evaluate all my learning designs and take full responsibility for my work, while the technology helps me deliver the best results for my clients every single time and for every single project.

That is what “trust but verify” means in practice, and it is the standard to which I hold all my work.

What I am doing now

I am building a practice around quality online learning in higher education environments, working toward Quality Matters peer reviewer certification, and writing about learner and educator readiness, student engagement, multimedia in instructional design, and the question of where generative AI does and does not belong in the field of Education.