From independent study to connected learning
My 2006 doctoral dissertation examined Internet Technologies as a Means of Organizing Independent Work of Technical University Students in Foreign Language Instruction. The question was how to give practice outside class a clear purpose, a useful sequence, and a connection back to the teacher.
That question still shapes my work. Homework needs more than a page of exercises: the learner needs to understand what to do, why it matters, and how the result will be used.
What earlier tools made possible
My research and later work with Moodle gave me a way to think about learning beyond a single classroom meeting. Materials, tasks, and feedback could belong to a continuing course. That work remains part of the foundation of the system I build today.
The challenge in individual teaching is maintaining that structure while adapting the practice to a particular learner. A task that suits one person may be too difficult, too easy, or irrelevant for another.
What AI adds to my workflow
AI helps me draft variations of an exercise, prepare dialogues, and review patterns in lesson notes. Structured records of goals, vocabulary, and recurring difficulties give that preparation a starting point. Spaced-review schedules and other routine checks can be handled by scripts.
I still review the draft for natural language, level, purpose, and fit. A fluent-looking exercise can contain an error or ask for more than the learner is ready to do.
What remains a teaching decision
I decide what independent work is for and how it follows from class. Afterward, I distinguish what the learner could do alone from what required help. That evidence informs the next task.
The connection between my earlier research and current practice is this continuing design problem: making work between lessons meaningful, manageable, and useful to the next meeting.
Based on my dissertation and subsequent work on independent learning. Selected publications →