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Eduway Student Life: student retention and early alerts on WhatsApp. Reach a quiet student in week 3, not week 16.

Your systems already know who missed 3 classes in week 3. Today, that signal sits in a report until the grade lands. Eduway acts on it the same week.

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Asked in plain words: Students who missed 2 or more classes this week

Missed 2+ classes this weekDynamic segment · 38 students
  • Yara S.Missed 2 classes
  • Omar H.Missed 3 classes
  • Lina K.Missed 2 classes
  • Noora S.Missed 3 classes5 unread
Start the check-in journey
Signals, not a risk score: your people decide who to call. Illustrative data.

Students rarely announce they are leaving. They just stop answering.

First a missed class, then an unread message, then a grade that slips after midterms. Each signal sits in a different system, so nobody sees the pattern until the student has already decided. By then the conversation is about a transfer form.

About 3 in 10 first-year students are no longer at the institution they started at, one year later National Student Clearinghouse Research Center, June 2026: retention 69.1%, fall 2024 entrants. U.S. data.

Signals in, a check-in out, and a person in the loop.

  1. Signals arrive

    Attendance, LMS logins, unread messages, grades and payments come in from the systems you already run.

  2. Ask in plain words

    “Students who missed 2 or more classes this week” becomes a list that keeps itself current. With your historical data, predictive segments add who is likely to drop out.

  3. People decide

    Your team sees the signals, not a black-box score, and chooses who gets a check-in journey.

  4. A conversation starts

    From their own advisor, on WhatsApp, with voice or SMS if there is no reply, and a button to book a meeting.

Segments

Ask in plain words first. Add predictions with your historical data.

Describe the students you mean, like “students who missed 2 or more classes this week”, and a dynamic segment keeps the list current from the systems you already run. With your historical data, predictive segments add the students likely to drop out, burn out or need tutoring. Every flagged student shows why.

  • Plain-words segments that update themselves
  • Predictive segments with your historical data
  • The signals behind every flag, not a score
  • A check-in journey for the whole segment
Dropout riskPredictive segment · 38 students
  • Omar H.Missed 3 classes9 unread
  • Karim B.GPA down 0.6No login 12 days
  • Maya R.Missed 2 labsLate payment
  • Yousef A.Missed 4 classes
Start the check-in journey
Signals, not a score: the model flags students, your people decide. Illustrative data.
Creating a predictive segment with the dropout-risk model and a confidence threshold

Creating a live predictive segment: pick the model, tune the confidence threshold, preview the students who match.

What Student Life includes

  • Plain-words and predictive segments
  • Journey Builder
  • The Educator calendar: a term of class reminders, set once
  • WhatsApp, SMS, email, Telegram, voice and web chat
  • Arabic and English

Before we talk.

What data does the dropout model use?

Signals you already hold: attendance, LMS activity, message engagement, grades and, if you choose, payments. You decide which sources connect, and every flagged student shows the signals behind the flag.

Does the AI decide who gets contacted?

No. The model flags students; your team decides who gets a check-in, and every message can be approved before it goes out.

Can professors message students on WhatsApp without giving out their number?

Yes. Messages send from the institution’s official channel. Professors only see students linked to their course.

Do students have to install anything?

No. Students use WhatsApp, SMS, email or Telegram, the channels already on their phones.

Somebody in your first-year class has already gone quiet.

See how Student Life would find them, in a discovery session with your own example.

Book a discovery session info@eduway.me