Hours and consistency
Know how much time you spent with the language, and whether contact was steady or clustered into a few heavy days.
Language learning analytics
Turn language study logs into useful analytics.
LinguaTrackr builds language learning analytics from the sessions you log: hours, activity mix, streaks, goals, and history you can compare across weeks and months. Charts only matter when they answer a real question about your routine.
language learning analytics
See totals, trends, streaks, goals, and activity distribution from real sessions.
Compare languages and periods so you notice when listening rises or reading drops off.
Export CSV or JSON when you want a backup or deeper analysis outside the app.
A streak is not a study report.
Many apps tell you that you showed up. Fewer tell you what you did: how many hours of Spanish listening you got this month, whether speaking vanished from the routine, or whether this week matched the goal you set. Language learning analytics should explain the shape of your effort, not decorate a dashboard.
A review that changes next week’s plan
You open the week and see twelve hours total: mostly podcasts, almost no reading, two short speaking sessions, and Anki logged under apps. That picture is enough to set next week’s goal from reality: keep the listening, add three reading sessions, and protect one longer conversation. The analytics informed the plan; they did not invent fluency.
Metrics that are worth measuring
Prefer questions that change behaviour over vanity totals that only look impressive.
Activity balance
See whether your learning is mostly listening, mostly apps, or mixed across reading, speaking, writing, and study.
Goals tied to reality
Set daily or weekly goals from what you actually managed, then watch completion against the activity that matters for this phase.
How people use the analytics
The point is a long-term record you can interpret, not a scoreboard.
Weekly reviews
Check total time, activity balance, and streak history against what you intended to do.
Period comparisons
Notice whether listening is rising month to month, or whether a skill quietly disappeared from your log.
Material history
Titles, tags, and notes help you remember what you spent time with, not only that minutes were logged.
Data you can leave with
Export session history as CSV or JSON for backups or personal analysis. The tracker should not hold years of learning hostage.
Related pages
More detail on adjacent topics, without repeating the same page three times.
- Language immersion tracker
How immersion logging works before the analytics can mean anything.
- Comprehensible input tracker
Measuring CI hours and input difficulty over time.
- Japanese immersion tracker
Japanese examples that feed the same analytics model.
- XP and levels
How XP maps to accumulated study time, not fluency claims.
- How to track language learning
Practical guidance on logs, metrics, and when to leave the spreadsheet.
Common questions
Short answers for this page. More detail lives in the docs.
What language learning analytics does LinguaTrackr show?
Totals, streaks, calendars, goals, activity breakdowns, language-specific history, weekly reviews, and deeper analytics such as heatmaps and period comparisons built from your logged sessions.
Which metrics should I care about?
Start with hours in the language, consistency of contact, and activity balance. Then use titles and tags to remember what carried those hours. Avoid treating streaks or XP as proof of fluency.
Do I need to import data for analytics to work?
No. Add sessions in the app and the dashboard builds analytics from language, activity type, time, quantity metrics, difficulty, titles, tags, and notes. Session CSV import is optional for migrating prepared history.
Can I export my language learning data?
Yes. Export full session history as CSV or JSON from Export and import in the dashboard.
Free to use · Private by default
Build analytics from real sessions.
Free language learning analytics from the work you already do. Private by default.