The LICQual Level 2 Award in Artificial Intelligence in Education and Learning is a progressive qualification designed to build upon foundational AI concepts and introduce practical applications in educational settings. This course aims to deepen learners’ understanding of how artificial intelligence can be strategically utilized to transform teaching methods, personalize learning pathways, and optimize institutional decision-making. As AI continues to revolutionize the global education landscape, this qualification equips participants with the tools and insight needed to adapt and innovate.
Focusing on both theoretical knowledge and applied skills, the LICQual Level 2 Award in Artificial Intelligence in Education and Learning covers advanced topics such as predictive analytics for student performance, AI-assisted curriculum design, and intelligent learning environments. The curriculum also emphasizes ethical considerations and the responsible use of AI technologies to maintain fairness and inclusivity in education. This award is ideal for educators, academic managers, EdTech developers, and professionals seeking to drive educational excellence through AI integration.
Learners will engage with interactive materials, case studies, and real-world scenarios that illustrate how AI can enhance student engagement, improve administrative efficiency, and support personalized learning strategies. The LICQual Level 2 Award in Artificial Intelligence in Education and Learning also encourages critical thinking and problem-solving, preparing learners to assess and implement AI tools effectively in diverse educational contexts.
Whether working in primary, secondary, higher education, or vocational training, participants will gain a competitive edge through this internationally aligned qualification. By focusing on emerging AI trends and technologies in education, the course supports career development and offers a clear progression path to higher-level diplomas and certifications in educational technology and digital transformation. It empowers learners to become proactive contributors to AI-driven innovation within their institutions.
In conclusion, the LICQual Level 2 Award in Artificial Intelligence in Education and Learning provides an essential stepping stone for professionals aiming to leverage AI to enhance educational outcomes. This course not only strengthens practical and ethical knowledge but also aligns learners with the future of smart education systems. With AI rapidly reshaping the learning environment, this qualification ensures that participants are prepared to lead, innovate, and succeed in a digitally advanced academic world.
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.