Postgraduate Diploma in Education (PGDE), Woolf

Credits: 5

Status: Core Module

Module Description

This module introduces educators to the fundamental principles, history, and transformative potential of Artificial Intelligence (AI) within educational contexts. Learners will gain a deep understanding of AI’s evolution, societal impact, and ethical challenges, while also exploring its practical applications in instructional design, curriculum development, and assessment. The course covers AI’s role in adaptive learning, learning analytics, and innovative pedagogical approaches such as STEAM, project-based learning (PBL), and gamification. Educators will also engage with AI tools such as ChatGPT, AR/VR, and various AI-driven platforms. By the end of the module, participants will be able to design inclusive and future-ready learning environments powered by AI.

Learning Outcomes

LO1 Demonstrate critical understanding of AI evolution, principles, and potential in education.

LO2 Evaluate ethical implications and algorithmic bias in AI-based educational decision- making.

LO3 Apply design thinking, including divergent and convergent approaches to integrate AI tools in instructional and learning design.

Credits: 5

Status: Core Module

Module Description

This application-oriented module equips educators with the skills to effectively use Generative AI (GenAI) tools to enhance teaching, content development, and learner engagement. It introduces key GenAI platforms such as ChatGPT, Bard, and other LLM- based tools, focusing on their practical application in curriculum development, assessment design, instructional support, and real-time feedback. Educators will explore how to ethically and creatively leverage GenAI for producing lesson plans, quizzes, feedback templates, adaptive activities, and multilingual support. The module emphasizes prompt engineering, customization for student needs, and integration with existing LMS platforms. Through hands-on projects and guided practice, educators will learn to use GenAI to increase productivity, creativity, and student inclusivity. At the end of this module, learners will be able to design and apply GenAI-powered solutions for content creation, feedback delivery, and personalized instruction in diverse educational contexts.

Learning Outcomes

LO1 Demonstrate foundational knowledge of generative AI tools and their potential in educational settings

LO2 Apply GenAI platforms to create instructional content, assessments, and adaptive feedback.

LO3 Critically evaluate ethical, inclusive, and pedagogical considerations in GenAI- assisted teaching.

Credits: 5

Status: Core Module

Module Description

The Curriculum & Instruction module offers educators a comprehensive and practical exploration of modern curriculum design and instructional practices essential for today’s diverse learning environments. The module focuses on empowering participants to align curricula with academic standards and social-emotional learning (SEL) principles, while ensuring that teaching methods remain inclusive, responsive, and engaging for all learners. Learners will critically examine key pedagogical theories and research-based strategies to support differentiated instruction, culturally responsive teaching, and social- emotional integration in lesson planning. Emphasis will be placed on applying backward design principles to ensure that curriculum planning begins with clear learning outcomes and incorporates authentic assessment methods to evaluate student understanding and growth. Additionally, educators will develop the ability to interpret assessment data to refine instructional practices and optimize learning experiences. Through hands-on projects, interactive workshops, and reflective tasks, participants will also gain practical skills in fostering student engagement, critical thinking, problem-solving, and holistic development. By the end of this module, educators will be equipped to design and implement innovative, inclusive, and evidence-based curricula that support the academic, social, and emotional needs of all learners, preparing them for success in both education and life.

Learning Outcomes

LO1. Design and deliver comprehensive curriculum units that integrate social-emotional learning, mindfulness, and inclusive instructional strategies.

LO2. Create and apply authentic assessments to monitor student progress, inform instruction, and improve learning outcomes.

LO3 Implement research-based teaching practices to create engaging, inclusive, and student-centered learning environments that promote reflection, critical thinking, and problem-solving.

Credits: 5

Status: Core Module

Module Description

This module draws upon educational sciences and research to empower educators to cultivate strong, collaborative relationships within classrooms and across broader communities. Rooted in child, adult, and social learning theories, the course explores how fostering meaningful connections among students, educators, families, and community members enhances teaching effectiveness and student achievement. Learners will critically examine pedagogical approaches centered on relationship-building, cultural responsiveness, and inclusiveness. They will learn practical strategies to develop nurturing environments that encourage trust, connection, and mutual respect. Through interactive workshops, reflective activities, and integration of community resources, educators will be equipped to embed community collaboration into everyday teaching practice. By the end of this module learners will have developed the expertise to lead community-based pedagogical initiatives, design inclusive learning experiences, and integrate community partnerships into their curriculum to inspire and engage students meaningfully.

Learning Outcomes

LO1. Lead community-based pedagogical initiatives and design learning experiences that prioritize connection, inclusivity, and collaboration.

LO2. Foster a nurturing classroom culture that encourages human connection, mutual respect, vulnerability, and cultural responsiveness.

LO3.Evaluate and refine pedagogical practices through reflective teaching, data-driven assessment, and integration of community perspectives.

Credits: 5

Status: Core Module

Module Description

This module prepares educators and instructional designers to strategically integrate Artificial Intelligence (AI) into instructional planning, curriculum design, and assessment frameworks. It explores how AI can enhance learning outcomes through personalized instruction, intelligent feedback systems, and adaptive assessments. Learners will engage with principles of backward design, competency-based education, and AI-supported curriculum mapping to align content with learner needs and institutional goals. Participants will critically examine the ethical use of AI in instructional design, as well as its role in supporting formative and summative assessment, automated grading, and feedback generation. Through case studies, practical tool demonstrations, and prototype development, educators will explore best practices in AI-driven content curation, learning progression models, and inclusive instructional strategies. At the end of this course, learners will be able to design AI-integrated instructional experiences and assessment strategies that support personalized, ethical, and effective learning.

Learning Outcomes

LO1. Apply instructional design principles to integrate AI into curriculum and assessment planning.

LO2. Critically evaluate AI tools and platforms for content delivery, assessment, and personalized learning pathways.

LO3. Design ethical, inclusive, and data-informed AI-supported instructional and assessment solutions.

Credits: 5

Status: Core Module

Module Description

This module addresses the evolving expectations of educational leaders in the 21st century, focusing on synchronizing leadership approaches with the dynamic needs of modern students and educational environments. Participants will explore transformative leadership theories, organizational dynamics, ethical decision-making, and strategic visioning to lead effectively in complex, changing contexts. The course integrates critical thinking, innovation, adaptability, and holistic leadership strategies essential for shaping educational institutions and driving broader societal change. Emphasis is placed on navigating resistance during organizational change, promoting collaboration, building high-performing teams, and fostering a culture of continuous improvement. Learners will engage in interactive case studies, collaborative projects, and practical leadership development tasks. The module prepares the learners with the knowledge, skills, and mindset to influence educational policies, design leadership initiatives, and implement sustainable, ethical leadership practices that foster positive transformation within and beyond their institutions.

Learning Outcomes

LO1. Utilize strategic thinking and vision-setting skills to design, articulate, and execute leadership initiatives that align with institutional objectives and proactively address emerging challenges.

LO2. Lead and facilitate organizational change by effectively managing resistance, inspiring collective commitment, and fostering a collaborative and inclusive environment.

LO3.Develop and implement comprehensive leadership development programs aimed at identifying, cultivating, and sustaining leadership talent across diverse educational settings.

Credits: 5

Status: Core Module

Module Description

This module introduces educators to the transformative potential of Augmented Reality (AR) and Virtual Reality (VR) in teaching and learning. It explores how immersive technologies enhanced by AI can improve engagement, understanding, and retention across a range of educational contexts, including STEM, medical training, and special education. Learners will gain practical experience with AR/VR tools and examine instructional design principles, cognitive load, personalization, and adaptive learning. The module also addresses critical considerations such as accessibility, ethics, digital well-being, and infrastructure challenges. Through hands-on projects and case studies, participants will design and evaluate AI-powered immersive learning experiences that are inclusive, effective, and future-ready. At the end of this course, educators will be able to design, implement, and critically assess immersive AR/VR learning experiences that enhance educational outcomes.

Learning Outcomes

LO1. Critically evaluate the pedagogical impact of AR and VR technologies on learner engagement, understanding, and motivation.

LO2. Design and implement interactive, AI-enhanced AR/VR learning experiences tailored to diverse educational needs.

LO3.Critically examine the effectiveness, accessibility, and ethical implications of immersive learning interventions in educational environments.

Credits: 5

Status: Core Module

Module Description

This module introduces educators to the core concepts and practical applications of Machine Learning (ML) and Natural Language Processing (NLP) in education. It explores how these AI technologies enhance personalized learning, automate assessments, and improve communication and engagement. The first part covers ML fundamentals supervised and unsupervised learning, classification, and clustering along with their use in predictive analytics, adaptive platforms, and data-informed teaching. Ethical issues such as bias and responsible AI use are also addressed. The second part focuses on NLP tools and techniques, including sentiment analysis, chatbots, automated feedback, and speech recognition. Educators will gain hands-on experience with AI tools that support multilingual learning and accessibility. Through real-world case studies and assignments, participants will evaluate and design AI-driven solutions to meet diverse educational needs. At the end of this course, educators will be able to apply ML and NLP tools to enhance learning experiences, improve outcomes, and support inclusive, AI-powered teaching.

Learning Outcomes

LO1. Demonstrate a critical understanding of core Machine Learning and Natural Language Processing concepts and their relevance to education.

LO2. Apply ML and NLP tools to enhance instructional delivery, automate assessment, and support personalized, inclusive learning.

LO3.Critically evaluate AI-driven educational technologies with respect to their effectiveness, ethical implications, and implementation challenges in diverse learning contexts.

Credits: 5

Status: Core Module

Module Description

This module explores the integral connection between education and the implementation of best practices to ensure excellence in teaching and learning. Learners will critically engage with evidence-based approaches, including active learning and technology integration. The course is designed to enable learners to design curriculum aligned with contemporary educational standards and foster transformative learning experiences. By examining real-world case studies and dynamic classroom scenarios, learners will gain the knowledge and skills to evaluate the effectiveness of pedagogical strategies and integrate interdisciplinary and inclusive practices into curriculum planning. The course also emphasizes assessment and feedback mechanisms, leadership in collaborative environments, and the application of data-driven decision-making to create holistic and equitable learning ecosystems. This module is adaptive and may be repeated for credit, with topics evolving based on faculty expertise and cohort needs, ensuring ongoing relevance to contemporary challenges and innovations in education.

Learning Outcomes

LO1. Design and adapt curriculum and instructional strategies that align with educational best  practices  to  meet  diverse  learner  needs  and  workforce  demands.

LO2. Implement effective assessment and feedback systems to monitor student progress, personalize instruction, and promote a culture of continuous improvement.

LO3.Integrate inclusive, interdisciplinary, and technology-enhanced strategies to foster collaborative, engaging, and equitable learning environments across educational settings.

Credits: 5

Status: Core Module

Module Description

This module provides an in-depth exploration of the theories, practices, and challenges inherent in transforming educational environments to meet the demands of contemporary society. Designed for educators, administrators, and policymakers, the course offers a critical examination of historical and current reform movements, with the aim of identifying key lessons and innovative approaches to school improvement. Learners will engage with essential themes, including change leadership, stakeholder engagement, policy advocacy, and the integration of technology as a driver of reform. Through collaborative projects and real-world case studies, learners will analyze both successful and unsuccessful reform efforts, developing a nuanced understanding of the conditions necessary for sustainable, systemic change. By the end of the module, participants will possess the knowledge and skills required to lead transformational initiatives, design inclusive reform strategies, and become effective change agents within their schools and communities. The course emphasizes improving student learning, promoting equity, and fostering a culture of continuous improvement.

Learning Outcomes

LO1. Demonstrate leadership in designing, implementing, and driving school-wide reform initiatives that advance educational equity and ensure inclusive access for all learners.

LO2. Critically assess and advocate for educational policies and classroom practices that promote sustainable improvement and foster inclusive, student-centered learning environments.

LO3.Collaborate effectively with stakeholders to build community partnerships and lead professional development initiatives that support a unified vision for transformative school change.

Credits: 5

Status: Core Module

Module Description

This module provides educators and educational leaders with a critical understanding of ethical, legal, and governance issues surrounding the use of Artificial Intelligence (AI) in education. As AI becomes increasingly integrated into teaching, learning, and administration, it is essential to address concerns related to data privacy, algorithmic bias, student safety, and accountability. Learners will explore global and regional frameworks, including the UAE’s digital and AI governance strategies, to understand how to implement responsible AI practices in educational contexts. The module covers key areas such as digital well-being, cybersecurity, equity and inclusion, and the ethical implications of AI-driven decision-making. It also introduces tools and policies that support ethical data use, transparent algorithms, and responsible innovation. Through case studies, policy analysis, and scenario-based discussions, learners will develop strategies to foster safe, inclusive, and trustworthy AI-enhanced learning environments. At the end of this course, learners will be able to evaluate ethical challenges, apply digital safety practices, and implement governance frameworks for responsible AI use in education.

Learning Outcomes

LO1. Critically evaluate ethical principles, risks, and implications of AI in education.

LO2.Apply digital safety practices to protect student data, well-being, and online behaviour.

LO3.Design governance strategies and institutional policies for the responsible implementation of AI in educational settings.

Credits: 5

Status: Core Module

Module Description

This concluding module enables participants to apply their accumulated knowledge to a capstone action research project. Learners will identify an educational issue, conduct critical inquiry, and design innovative solutions. The module emphasizes practical research skills, ethical research design, data collection, and dissemination of findings. Participants will demonstrate reflective practice and leadership through evidence-based interventions that drive improvement and inform policy and practice within their educational contexts.

Learning Outcomes

LO1. Explore and define a significant educational challenge, and conceptualize an inclusive, research-informed AI-driven solution responsive to diverse learner needs.

LO2.Execute and manage the designed intervention, critically examine data to assess its impact,  and  evaluate  its  potential  for  wider  adoption  and  sustainability.

LO3.Synthesize and present research insights to inform policy and practice, while articulating personal and professional development as an AI-informed and reflective educator.