The Computer Society of Kenya

Since 1986


Wednesday April 18, 2019

As our schools laptops project continues to face hurdles, folks in advanced economies are forging ahead to the next level by integrating Artificial Intelligence (AI) into their educational sector.

AI can provide personalised learning, assist in marking or grading and offer translation services that can enhance both learning and teaching experience.

Personalised learning means that the system can adjust the learning content based on student-specific needs or weakness. A teacher can now avoid using the one-size-fits-all approach that is common in traditional learning environments.

AI provides personalised learning, based on the testing and instant feedback arising from students as they engage with the digital learning platforms.

These types of systems respond to the needs of the student, putting greater emphasis on challenging topics or repeating content and tasks that students may not have mastered.

The learning system can therefore place students with different capabilities on different and appropriate learning paths, based on their most recent performance as the course progresses.

Students can also learn at their own pace as teachers get alert messages that flag out students who are not making the expected progress despite the personalised learning paths being presented.

Computer vision, another branch of AI, can also be deployed to capture and decipher student’s facial expression in real time, enabling teachers to pick out the students who are lost or struggling with concepts but are probably too shy to admit it or seek help.

Teachers can then have targeted and instant interventions rather than wait till the end of term to mark and award 'fail' grades to the struggling or absent-minded students.


Which brings us to the issue of grading or marking of scripts - the ultimate teacher’s nightmare.

With class sizes ranging from sixty to one hundred students in public schools, an average teacher would need to grade around five hundred scripts per week if they were to give out one assignment for each of the five subjects taught in a week.

AI can come in handy in assisting the teacher to grade assignments. Already the multiple-choice assignments are easy to do using technology but essay-based assignments are the next target for automated grading.

Using machine-learning algorithms, computers are now able to derive meaning and context from text-based answers. Though still at a rudimentary stage, this technology will be a game changer in the lives of teachers or lecturers.

In the near future, full thesis type of work would be able to be reviewed and assessed by AI, leaving teachers or lecturers with the much-needed time to focus on research.

Furthermore, automated grading also has the advantage of being able to easily point out to teachers those areas or topics in which students are performing poorly.

If a majority of students are failing a specific question, then perhaps the teacher is not addressing the particular content well or maybe the instruction set is not clear within the course material.

The role of the teacher or lecturer will therefore need to shift in the light of these developments.

It will have to move from being the 'know-it-all' subject matter expert, to a more facilitative role that involves guiding and encouraging the students to take more control of their learning experience.


Natural Language Processing (NLP) is another branch of AI that can be brought to bear in education. It is the engine behind your ability to talk to your phone and ask it to provide answers to a wide range of questions such as directions to your destination or topical trends in politics, religion, sports and history.

AI takes your speech or voice, translates it into text and uses algorithms to mine huge conversational data sets and build models that help it answer the questions in a human like manner.

Commonly known as Chat-bots, many enterprises have already deployed these tools as their customer care agents and nothing stops teachers from providing similar interfaces for the educational sector.

Educational chat-bots already exist and are able to respond to commonly asked student queries around the clock. But perhaps more powerful would be to use NLP as a translation tool particularly for the early childhood education subsector.

All English content taught at the lower primary level can be automatically translated into Kiswahili or even local dialect to bring the children who are struggling with English as their instructional language to the same level as their more proficient peers.

This can also be used at tertiary level, where most research content is published in English, meaning that content published in other languages such as French, Chinese or Arabic remains inaccessible. It can unlock these knew knowledge that is publicly available but somehow hidden away in a foreign language.

Is the Kenyan Education sector ready and preparing for all these development in the education sector?

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