Kliniki Yangu.
My clinic visit.

Hospital SMS messages can place names, compact dates, times, appointment IDs and visit status together in one paragraph. A reader needs to find the relevant detail and understand whether the message records a past event or gives a future appointment.

This prototype uses family hospital messages and clinic appointments to teach those practical digital skills. The audience is a defined subset of women who want support with phone use. Pregnancy, income, nationality and English proficiency do not establish a person's literacy or digital ability.

1. Locate: tap the date, time and hospital inside a full unfamiliar message.
2. Interpret: distinguish a started visit, a completed consultation and a future appointment; recognise when the next appointment date is absent.
3. Keep: choose the appointment card that matches the message and save it within the practice.
4. Clarify: choose to confirm unclear information with a known clinic contact, keeping personal details private.

The digital skills are the assessment target. The experience does not diagnose symptoms, prescribe care, set an antenatal schedule, book an appointment or create a real phone reminder.

The lesson records first-attempt accuracy and hint use for its three final questions in the current page session. This is a working assessment feature, not evidence from a user study. A retry can improve the answer without rewriting the first-attempt record.

The next step is a small formative study with consenting adult participants who describe their own digital experience. Ask them to attempt an equivalent message task before the lesson, then a new one afterwards. Observe the first tap, errors, assistance requested and whether the task is completed independently. Keep facilitation consistent and record the language used.

Recruit through an appropriate local partner and arrange clinical-context and Kiswahili review before field use. Participation should be voluntary and separate from care. Use fictional records; do not ask for pregnancy details, real messages or phone numbers. A small convenience sample can guide revisions but cannot establish effectiveness for Kenyan mothers generally.

Plain HTML, CSS and JavaScript keep the lesson portable. Its content and font load locally, with no analytics, registration or external content requests. Once the page is fully loaded, its core interactions continue if the connection drops. The downloaded project also opens locally. This does not provide automatic offline reopening or background synchronisation.

Optional narration depends on the browser and an installed or available voice for the selected language. It is synthetic device speech, not a recorded narration track, and availability or offline operation cannot be assumed. Draft Kiswahili needs review with a fluent local reviewer and intended learners.

Author: Kevin Gakarau. This is an independent portfolio project created with AI-assisted drafting and implementation. It has no affiliation with Peek Vision, a clinic or WHO. The SMS wording was revised using examples supplied by the project author, with personal names, hospital identities and reference numbers replaced. This is a design input, not learner research. The next iteration needs observation and review with intended learners.