The LICQual Level 2 Award in Artificial Intelligence in Education and Learning is a dynamic and skill-enhancing course designed to deepen learners’ understanding of how AI technologies are transforming educational landscapes.
As artificial intelligence continues to redefine the way students interact with content, educators engage with learners, and institutions manage systems, this course serves as a practical and theoretical bridge between foundational knowledge and intermediate-level application. It is ideal for educators, digital learning professionals, and technology enthusiasts aiming to integrate AI effectively into their teaching strategies and institutional frameworks.
This program equips participants with an intermediate-level grasp of core AI principles while introducing more advanced tools, platforms, and real-world applications used in educational contexts. Learners will explore how machine learning, data-driven personalization, and intelligent content delivery are shaping adaptive learning environments.
The LICQual Level 2 Award in Artificial Intelligence in Education and Learning also addresses evolving pedagogical approaches supported by AI, such as predictive analytics for learner performance and AI-facilitated feedback systems that drive engagement and achievement.
The units are tailored to cover topics such as advanced AI tools for education, automated assessments, chatbot integration, ethical and regulatory concerns, and the design of inclusive AI-based learning experiences. Learners will engage with practical demonstrations, hands-on scenarios, and critical evaluations of AI’s role in supporting both educators and students.
By completing this course, participants will be able to evaluate and apply AI technologies in diverse educational settings. They will develop the ability to select appropriate AI tools for specific learning objectives, enhance learner interaction using smart content systems, and implement AI solutions that align with pedagogical goals and ethical standards.
The course promotes critical thinking, creativity, and innovation, enabling participants to contribute to the development of AI-powered education systems that are equitable, scalable, and impactful.
The LICQual Level 2 Award in Artificial Intelligence in Education and Learning is particularly relevant in today’s rapidly evolving educational landscape. As institutions embrace digital transformation, professionals who possess the knowledge and skills to effectively implement AI in teaching and learning contexts are increasingly in demand.
This course empowers participants to become leaders in educational innovation, supporting the transition to more intelligent, data-driven, and learner-centric environments.
Course Overview
Qualification Title
LICQual Level 2 Award in Artificial Intelligence in Education and Learning
Total Units
6
Total Credits
6
GLH
12
Qualification #
LICQ2200504
Qualification Specification
To enroll in the LICQual Level 2 Award in Artificial Intelligence in Education and Learning applicants must meet the following criteria:
|
Qualification# |
Unit Title |
Credits |
GLH |
|---|---|---|---|
|
LICQ2200504-1 |
Understanding Machine Learning in Education |
1 |
2 |
|
LICQ2200504-2 |
AI Tools for Personalized Learning |
1 |
2 |
|
LICQ2200504-3 |
Virtual Tutors and AI-Powered Feedback Systems |
1 |
2 |
|
LICQ2200504-4 |
Data Collection and Student Performance Analytics |
1 |
2 |
|
LICQ2200504-5 |
Ensuring Data Privacy in AI Applications |
1 |
2 |
|
LICQ2200504-6 |
Designing AI-Enabled Microlearning Experiences |
1 |
2 |
By the end of this course,applicants will be able to:
1. Understanding Machine Learning in Education
- Explain the role of machine learning algorithms in shaping educational systems.
- Identify key types of machine learning models used to support adaptive learning.
2. AI Tools for Personalized Learning
- Evaluate AI-driven platforms that support individualized learning paths.
- Apply basic techniques for implementing personalized instruction using AI tools.
3. Virtual Tutors and AI-Powered Feedback Systems
- Describe the functions of virtual tutors and their impact on learner support.
- Analyze how AI systems provide automated and timely feedback to enhance learning outcomes.
4. Data Collection and Student Performance Analytics
- Explain how AI systems collect and analyze student data to inform teaching strategies.
- Interpret performance analytics to make data-driven educational decisions.
5. Ensuring Data Privacy in AI Applications
- Identify major data privacy concerns in AI-driven education systems.
- Apply best practices to ensure ethical use and protection of student data.
6. Designing AI-Enabled Microlearning Experiences
- Understand the principles of microlearning and how AI enhances its delivery.
- Design simple AI-supported microlearning modules tailored to learner needs.
This diploma is ideal for:
- Educators aiming to integrate AI tools into their teaching practices
- Instructional designers developing personalized learning experiences
- School administrators seeking to enhance academic performance through AI-driven analytics
- E-learning professionals looking to advance their knowledge of AI-powered platforms
- Curriculum developers interested in designing adaptive and data-informed content
- Trainers and facilitators working in digital or remote learning environments
- Education technology specialists implementing AI in classrooms and institutions
- Academic researchers focusing on AI applications in student assessment and feedback
- Professionals transitioning into the edtech industry with an interest in AI
- Developers of educational software seeking insight into AI use in learning
- Policy makers creating frameworks for AI in education systems
- Graduate students studying education, learning science, or artificial intelligence
- NGO workers involved in educational innovation and digital inclusion projects
- Corporate trainers leveraging AI to support employee development and microlearning
- Data analysts and assessment specialists exploring performance metrics in education
- Education consultants providing guidance on AI adoption and implementation
- Teachers interested in using virtual tutors and intelligent feedback systems
- Digital strategists designing learner-centric AI-based interventions
- Anyone with foundational knowledge of AI who wishes to expand their application in education
Assessment and Verification
All units within this qualification are subject to internal assessment by the approved centre and external verification by LICQual. The qualification follows a criterion-referenced assessment approach, ensuring that learners meet all specified learning outcomes.
To achieve a ‘Pass’ in any unit, learners must provide valid, sufficient, and authentic evidence demonstrating their attainment of all learning outcomes and compliance with the prescribed assessment criteria. The Assessor is responsible for evaluating the evidence and determining whether the learner has successfully met the required standards.
Assessors must maintain a clear and comprehensive audit trail, documenting the basis for their assessment decisions to ensure transparency, consistency, and compliance with quality assurance requirements.
