Brief Introduction

MA in Artificial Intelligence for education and innovation is a 2- year long postgraduate course divided into 4 semesters, spread over 6 months each. The course is designed to familiarize students with the science and engineering of making computer machines able to perform tasks which normally require human intelligence, such as speech recognition. The objective of course is to impart theoretical and practical knowledge in the specialized area of Artificial Intelligence for education and innovation. The target students are educators who are expected to have an innovative orientation so as to impart the same innovativeness on the students

 Artificial intelligence is becoming popular as the veiled decision maker of our times. The program will aid in bridging the gap between advanced technology and innovations in our schools. Artificial Intelligence technology is currently being integrated in schools in Tanzania, Uganda, Kenya, South Sudan, Ethiopia and Sudan. This integration is taking a slow pace and there is minimal innovations getting out of it.  However, the problem to use of artificial intelligence technology in teaching appears not to be technological but pedagogical where most people do not have practical knowledge and skills. 

The impact of Artificial Intelligence growing rapidly in the education sector, whether it’s in speech and language technology, healthcare, strategic planning, or information retrieval and data mining. This is increasingly being supported by governments and industries, who are constantly seeking out professionals in this field. If you’re looking for a career that is highly diverse, extremely well-paid, and puts you at the forefront of exciting technological advancements and innovation, then this MSc programme will give you the knowledge and tools you need to embark on a thrilling career.

  COURSE LECTURER
1 Foundation of Technology in Education: students will acquire skills about the processes and knowledge related to technology. Tools to be used in teaching in the digital era    
2 Content creation: the course prepares student how to contextualize digital media/ text information for an end user or audience    
3 Educational technology tools: skills on using and managing appropriate technological tools and resources such as hardware and software for theory and practical teaching    
4 Entrepreneurship: application of Artificial Intelligence knowledge through critical thinking on new of enhancing quality of products and service delivery  
5 Computer Architecture and organization: this course help the students to have a clear view as to how a computer system works. Specifically, its emphasis is on behind the design of modern computer systems.    
6 Problem Solving and programming: the course entails problem solving process, problem solving approaches, data types, variables and constants    
7 Machine learning platforms:  the course introduces the students write algorithms and statistical models that will allow computers to perform a specific task without using explicit instructions    
8 Decision management: these are the key tools for identifying, preventing and resolving issues through the effective implementation of problem solving and decision-making skills.  
9 Digital media in education:  is the art of blending technology and content in a way that is practical, innovative, and user-friendly for learning purposes    
10 Deep learning: this is a subset course from machine learning where an Artificial Intelligence function mimics the workings of the human brain in processing data for use in decision making. Deep learning AI is able to learn from data that is both unstructured and unlabeled.  
11 Compliance and Ethics: this course prepares the students in areas of ethics that must be adhered to will handling technology and rights of other persons    
12 Multimedia in structural strategies  
13 Research methods: this course prepare students to be inquisitive with a critical mind aimed at problem solving. Thus, students can be able to unearth existing gaps and find solutions through research  
14 Data structure and algorithms: This is a beginner’s course to learn design, implementation, and analysis of basic data structures using Java language. The course covers well-known data structures such as dynamic arrays, linked lists, stacks, queues, and binary tree.  
     
     
  • Researchers interested in the intersection of artificial intelligence research, learning and education
  • Science teachers (both primary and secondary) in charge of tapping to the skills of young scientist and developing their capabilities
  • Experts in the area of integrating technology with education curriculums
  • Innovators especially in the area of educational technologies
  • Hold a bachelor’s degree with second class honors upper division (or GPA of 3.3 -4.0) in science or engineering disciplines (Degree in Education, science Subjects, Computing/ Computer Science/ Information Technology/ Computer Engineering)
  • Hold a bachelor’s degree with second class honors lower division (or GPA of 2.8-3.3) in science or engineering disciplines – two years working experience
  • Holders of other related qualifications such as business courses from recognized universities.
  • In addition, the applicant must have obtained the minimum university entry requirement i.e. scored at least a C+ in their KCSE (or its equivalent).
  • Be holders of a Bachelor Degree in Education (Science Subjects), Computing/Computer Science/Information Technology/Computer Engineering or related field of at least Upper Second-Class Honors from a recognized University

Teacher and AI collaboration

AI has already been applied to education primarily in some tools that help develop skills and testing systems. As AI educational solutions continue to mature, the hope is that AI can help fill needs gaps in learning and teaching and allow schools and teachers to do more than ever before. AI can drive efficiency, personalization and streamline admin tasks to allow teachers the time and freedom to provide understanding and adaptability—uniquely human capabilities where machines would struggle.

Differentiated and individualized learning

Adjusting learning based on an individual student’s particular needs has been a priority for educators for years, but AI will allow a level of differentiation that’s impossible for teachers who have to manage 30 students in each class. This kind of custom-tailored education could be a machine-assisted solution to helping students at different levels work together in one classroom, with teachers facilitating the learning and offering help and support when needed.

Universal access for all students

Artificial intelligence tools can help make global classrooms available to all including those who speak different languages or who might have visual or hearing impairments.

Automate administrative tasks

An educator spends a tremendous amount of time grading homework and tests. AI can step in and make quick work out of these tasks while at the same time offering recommendations for how to close the gaps in learning. Although machines can already grade multiple-choice tests, they are very close to being able to assess written responses as well.

Tutoring and support outside the classroom

Ask any parent who has struggled to help their teenager with algebra, and they will be very excited about the potential of AI to support their children when they are struggling at home with homework or test preparations. Tutoring and studying programs are becoming more advanced thanks to artificial intelligence, and soon they will be more available and able to respond to a range of learning styles