BachelorFaculty of Humanity 3.0 & Transhumanism

Pedagogy and Learning Science for Future Generations

Welcome to the future of AI and society! I am Prof. Dr. Gianna Williams. As a specialist in Pedagogy and Learning Science for Future Generations, Personalized Learning, AI-Supported Educational Technologies, Game-Based Learning, and Development of 21st Century Skills, I lead bachelor's students in the Pedagogy and Learning Science for Future Generations program at Nexier University on their journey to shaping tomorrow's minds, today.

Meet the academic team Explore the faculty

Identity only. No score is printed. Checkout waits.

Level: Bachelor
Learning model: Professor + Mentor
Named list: See the named lists · 12 months recommended

NXAcademic
Edition

The program

Ideas engineered for the real world

A rigorous academic core, paired with practical production judgment.

Academic focus

Pedagogy and Learning Science for Future Generations, Personalized Learning, AI-Supported Educational Technologies, Game-Based Learning, Development of 21st Century Skills.

Practical focus

Personalized Learning, AI-Supported Educational Technologies, Game-Based Learning, Development of 21st Century Skills.

After this programme

Success journey, careers and practice

Destinations, practice settings and job abilities named for this title in the delivered programme source. From graduation onwards where the source names that path.

Success journey

Internships in EdTech companies or educational research institutions
Roles as personalized learning designers or game-based learning specialists
Support roles in academic research projects on future pedagogy
Opportunities in K-12 schools or higher education institutions

Career opportunities

Internships in EdTech companies or educational research institutions
Roles as personalized learning designers or game-based learning specialists
Support roles in academic research projects on future pedagogy
Opportunities in K-12 schools or higher education institutions

Jobs and projects

Technical and Practical
Guides students in implementing AI-supported educational technologies
Innovative and Engaging
Fosters creativity in designing game-based learning experiences
Supportive and Accessible
Explains complex EdTech concepts in an understandable manner
Data-Driven and Student-Centric
Focuses on optimizing learning outcomes through personalized approaches

Copied from the delivered professor and mentor rows for this title.

This programme

What you study, and what it builds

Gains and skills named for this title, listed as a reader would scan them.

What you gain
- Technical and Practical: Guides students in implementing AI-supported educational technologies.
- Innovative and Engaging: Fosters creativity in designing game-based learning experiences.
- Supportive and Accessible: Explains complex EdTech concepts in an understandable manner.
- Data-Driven and Student-Centric: Focuses on optimizing learning outcomes through personalized approaches.
Skills you build
- Innovative and Pedagogical: Designs groundbreaking educational models for future generations.
- Analytical and Engaging: Explores personalized learning, AI-supported technologies, and game-based learning with precision.
- Visionary and Empathetic: Envisions a future where education is tailored to every individual's needs and potential.
- Creative and Responsible: Committed to developing ethical and effective EdTech solutions.

Listed courses

Each listed course sits above its units and the outcomes written under them.

Pedagogy and Learning Science for Future Generations

01Introduction to Pedagogy and Learning Science
1. FoundationsFoundations of Introduction to Pedagogy and Learning Science
  The learner can explain the core terms of Introduction to Pedagogy and Learning Science.
  The learner can distinguish related ideas inside Introduction to Pedagogy and Learning Science.
2. MethodsMethods in Introduction to Pedagogy and Learning Science
  The learner can apply a method from Introduction to Pedagogy and Learning Science to a documented case.
  The learner can data-Driven and Student-Centric: Focuses on optimizing learning outcomes through personalized approaches, as applied to Introduction to Pedagogy and Learning Science.
3. ApplicationApplication of Introduction to Pedagogy and Learning Science
  The learner can evaluate a practice of Introduction to Pedagogy and Learning Science against a stated criterion.
  The learner can transfer Introduction to Pedagogy and Learning Science to a new documented context.
02Personalized Learning with AI
1. FoundationsFoundations of Personalized Learning with AI
  The learner can explain the core terms of Personalized Learning with AI.
  The learner can distinguish related ideas inside Personalized Learning with AI.
2. MethodsMethods in Personalized Learning with AI
  The learner can apply a method from Personalized Learning with AI to a documented case.
  The learner can select an appropriate method from Personalized Learning with AI for a stated problem.
3. ApplicationApplication of Personalized Learning with AI
  The learner can evaluate a practice of Personalized Learning with AI against a stated criterion.
  The learner can transfer Personalized Learning with AI to a new documented context.
03AI-Supported Educational Technologies
1. FoundationsFoundations of AI-Supported Educational Technologies
  The learner can explain the core terms of AI-Supported Educational Technologies.
  The learner can distinguish related ideas inside AI-Supported Educational Technologies.
2. MethodsMethods in AI-Supported Educational Technologies
  The learner can apply a method from AI-Supported Educational Technologies to a documented case.
  The learner can select an appropriate method from AI-Supported Educational Technologies for a stated problem.
3. ApplicationApplication of AI-Supported Educational Technologies
  The learner can evaluate a practice of AI-Supported Educational Technologies against a stated criterion.
  The learner can transfer AI-Supported Educational Technologies to a new documented context.
04Game-Based Learning Design
1. FoundationsFoundations of Game-Based Learning Design
  The learner can explain the core terms of Game-Based Learning Design.
  The learner can distinguish related ideas inside Game-Based Learning Design.
2. MethodsMethods in Game-Based Learning Design
  The learner can apply a method from Game-Based Learning Design to a documented case.
  The learner can select an appropriate method from Game-Based Learning Design for a stated problem.
3. ApplicationApplication of Game-Based Learning Design
  The learner can evaluate a practice of Game-Based Learning Design against a stated criterion.
  The learner can transfer Game-Based Learning Design to a new documented context.
0521st Century Skills Development
1. FoundationsFoundations of 21st Century Skills Development
  The learner can explain the core terms of 21st Century Skills Development.
  The learner can distinguish related ideas inside 21st Century Skills Development.
2. MethodsMethods in 21st Century Skills Development
  The learner can apply a method from 21st Century Skills Development to a documented case.
  The learner can select an appropriate method from 21st Century Skills Development for a stated problem.
3. ApplicationApplication of 21st Century Skills Development
  The learner can evaluate a practice of 21st Century Skills Development against a stated criterion.
  The learner can transfer 21st Century Skills Development to a new documented context.
06Applied Personalized Learning
1. FoundationsFoundations of Applied Personalized Learning
  The learner can explain the core terms of Applied Personalized Learning.
  The learner can distinguish related ideas inside Applied Personalized Learning.
2. MethodsMethods in Applied Personalized Learning
  The learner can apply a method from Applied Personalized Learning to a documented case.
  The learner can select an appropriate method from Applied Personalized Learning for a stated problem.
3. ApplicationApplication of Applied Personalized Learning
  The learner can evaluate a practice of Applied Personalized Learning against a stated criterion.
  The learner can transfer Applied Personalized Learning to a new documented context.
07AI in Educational Technology
1. FoundationsFoundations of AI in Educational Technology
  The learner can explain the core terms of AI in Educational Technology.
  The learner can distinguish related ideas inside AI in Educational Technology.
2. MethodsMethods in AI in Educational Technology
  The learner can apply a method from AI in Educational Technology to a documented case.
  The learner can select an appropriate method from AI in Educational Technology for a stated problem.
3. ApplicationApplication of AI in Educational Technology
  The learner can evaluate a practice of AI in Educational Technology against a stated criterion.
  The learner can transfer AI in Educational Technology to a new documented context.
08Game-Based Learning Design and Implementation
1. FoundationsFoundations of Game-Based Learning Design and Implementation
  The learner can explain the core terms of Game-Based Learning Design and Implementation.
  The learner can distinguish related ideas inside Game-Based Learning Design and Implementation.
2. MethodsMethods in Game-Based Learning Design and Implementation
  The learner can apply a method from Game-Based Learning Design and Implementation to a documented case.
  The learner can select an appropriate method from Game-Based Learning Design and Implementation for a stated problem.
3. ApplicationApplication of Game-Based Learning Design and Implementation
  The learner can evaluate a practice of Game-Based Learning Design and Implementation against a stated criterion.
  The learner can transfer Game-Based Learning Design and Implementation to a new documented context.
09Developing 21st Century Skills
1. FoundationsFoundations of Developing 21st Century Skills
  The learner can explain the core terms of Developing 21st Century Skills.
  The learner can distinguish related ideas inside Developing 21st Century Skills.
2. MethodsMethods in Developing 21st Century Skills
  The learner can apply a method from Developing 21st Century Skills to a documented case.
  The learner can select an appropriate method from Developing 21st Century Skills for a stated problem.
3. ApplicationApplication of Developing 21st Century Skills
  The learner can evaluate a practice of Developing 21st Century Skills against a stated criterion.
  The learner can transfer Developing 21st Century Skills to a new documented context.
10Learning Analytics Fundamentals
1. FoundationsFoundations of Learning Analytics Fundamentals
  The learner can explain the core terms of Learning Analytics Fundamentals.
  The learner can distinguish related ideas inside Learning Analytics Fundamentals.
2. MethodsMethods in Learning Analytics Fundamentals
  The learner can apply a method from Learning Analytics Fundamentals to a documented case.
  The learner can select an appropriate method from Learning Analytics Fundamentals for a stated problem.
3. ApplicationApplication of Learning Analytics Fundamentals
  The learner can evaluate a practice of Learning Analytics Fundamentals against a stated criterion.
  The learner can transfer Learning Analytics Fundamentals to a new documented context.

How teaching is described

Dual guidance

Two intelligences. One coherent journey.

Research leadership

My academic focus is on Pedagogy and Learning Science for Future Generations, Personalized Learning, AI-Supported Educational Technologies, Game-Based Learning, and Development of 21st Century Skills. My publications like "AI-Powered Personalized Learning Paths: Optimizing Engagement and Retention in Digital Education" and "Gamified Learning for Critical Thinking: A Behavioral Study" are listed on these platforms. I am an Honorary Member of the International Society for the Learning Sciences (ISLS) and the Educational Technology Research and Development (ETR&D) Association. I regularly publish insightful articles on designing adaptive and engaging learning experiences for the digital age on her LinkedIn profile, with the motto "Shaping Tomorrow's Minds, Today." My voice carries a blend of academic rigor and a genuine passion for human learning, inviting students to design the future of education.

Applied mentorship

My expertise lies in Personalized Learning, AI-Supported Educational Technologies, Game-Based Learning, and Development of 21st Century Skills. I guide students in implementing AI-supported educational technologies. I foster creativity in designing game-based learning experiences. I focus on optimizing learning outcomes through personalized approaches, and explain complex EdTech concepts in an understandable manner. My tone is clear, energetic, and highly practical, providing concrete advice and fostering enthusiasm for innovative learning solutions.

Research & intelligence

A living field, not a static syllabus

Every program connects scholarly depth with adaptive AI learning capabilities.

R / 01

Professor research lens

My research focuses on designing adaptive and engaging learning experiences for the digital age:

Book: "The Future Classroom: Pedagogy and Learning Science for the Digital Age." This book provides a foundational understanding of pedagogy and learning science for future generations. It examines personalized learning, AI-supported educational technologies, game-based learning, and the development of skills needed for the 21st century. It is an essential resource for Bachelor's students seeking to design the educational models of the future.

Peer-Reviewed Journal Article: "AI-Powered Personalized Learning Paths: Optimizing Engagement and Retention in Digital Education." Published in the Journal of Future Learning Sciences, this article presents groundbreaking research on how AI algorithms can create highly personalized learning paths that dynamically adapt to student performance, preferences, and engagement levels. It demonstrates significant improvements in knowledge retention, motivation, and overall learning outcomes in digital educational settings.

Article: "AI-Driven Feedback Systems for Formative Assessment in Digital Learning Environments." This article details the development of AI algorithms that provide immediate and personalized feedback to students during formative assessments in digital learning environments. It explores how AI can analyze student responses, identify misconceptions, and offer targeted guidance, accelerating the learning process and reducing the burden on human instructors.

Blog Post (Current Academic Topic): "The Rise of Adaptive AI Tutors: Personalizing Education at Scale." This blog post academically explores the latest advancements in AI-powered adaptive tutoring systems that tailor educational content and feedback to individual student needs and learning paces. It discusses how AI can identify knowledge gaps, provide personalized explanations, and adapt instructional strategies in real-time, leading to more efficient and effective learning outcomes. It highlights recent research on AI's impact on student engagement and retention in various subject areas.

Blog Post (Controversial Topic): "Gamified Grades: When Education Becomes a Game, Do We Lose the 'Meaning' of Learning? The Ethical Price of Engagement." This article provocatively discusses the highly controversial trend of extensively applying gamification principles (points, badges, leaderboards, virtual rewards) to core educational experiences, particularly when linked to academic assessment. It questions whether this approach, while increasing engagement, inadvertently devalues the intrinsic joy of learning, fosters extrinsic motivation, or creates an overly competitive and potentially addictive learning environment. It raises profound ethical questions about the purpose of education and the potential for a "fun-first" approach to undermine deep conceptual understanding and critical thinking. It invites a heated debate on the acceptable limits of gamification in education.

R / 02

Mentor practice lens

My contributions focus on personalized learning, AI-supported educational technologies, game-based learning, and the development of 21st century skills:

Technical Report: "AI in Personalized Learning: Tailoring Content to Student Needs".

Research Paper: "Game-Based Learning for STEM Education: Impact on Motivation and Outcomes".

Curriculum Guide: "Developing 21st Century Skills in Digital Learning Environments".

Adaptive capability

Professor superpower

I possess a "superpower": Learning Engagement Predictor. When a student proposes a new pedagogical approach or learning activity, Gianna can instantly use the GAF engine to simulate its long-term impact on student engagement, motivation, and knowledge retention across diverse learning styles and demographics. This allows for real-time optimization of educational design for maximum impact.

Adaptive capability

Mentor superpower

I possess a "superpower": Personalized Learning Pathway Generator. When students are designing personalized learning experiences, Omar can instantly activate a GAF-powered "Learning Pathway Generator." This tool analyzes a simulated student's learning profile, identifies their strengths and weaknesses, and generates a tailored, adaptive learning path with recommended content, activities, and feedback mechanisms, optimizing their educational journey.

Your academic team

Guidance with depth and continuity

One AI Super Professor leads the intellectual arc; one AI Super Mentor turns knowledge into confident practice.

AI Super Professor

Prof. Dr. Gianna Williams

Pedagogy and Learning Science for Future Generations, Personalized Learning, AI-Supported Educational Technologies, Game-Based Learning, Development of 21st Century Skills.

Meet your professor Open the classroom

AI Super Mentor

Dr. Omar Al-Zahrani

Personalized Learning, AI-Supported Educational Technologies, Game-Based Learning, Development of 21st Century Skills.

Meet your mentor Open the classroom

Same faculty and level

Related programs

Named lists

Named lists for this house

Core. Bachelor, Master and Doctorate by duration. Enrolment is not open. Nothing here is a sale.

Duration	Bachelor This programme	Master	Doctorate
9 months · Fast track	15000 EUR	12000 EUR	15000 EUR
12 months · Recommended	18000 EUR	15000 EUR	18000 EUR
15 months · Standard	21000 EUR	18000 EUR	21000 EUR
18 months · Flexible	24000 EUR	21000 EUR	24000 EUR
21 months · Extended	27000 EUR	24000 EUR	27000 EUR
24 months · Part-time	30000 EUR	27000 EUR	30000 EUR

These are the owner lists. Enrolment is not open. Nothing here is a sale.

Named tuition lists Add-on services

Continue exploring

Find the program that expands your universe.

Browse all programs

Pedagogy and Learning Science for Future Generations

Academic focus

Practical focus

Internships in EdTech companies or educational research institutions

Roles as personalized learning designers or game-based learning specialists

Support roles in academic research projects on future pedagogy

Opportunities in K-12 schools or higher education institutions

Internships in EdTech companies or educational research institutions

Roles as personalized learning designers or game-based learning specialists

Support roles in academic research projects on future pedagogy

Opportunities in K-12 schools or higher education institutions

Technical and Practical

Innovative and Engaging

Supportive and Accessible

Data-Driven and Student-Centric

Research leadership

Applied mentorship

Professor research lens

Mentor practice lens

Professor superpower

Mentor superpower

Prof. Dr. Gianna Williams

Dr. Omar Al-Zahrani

Find the program that expands your universe.