Upskilling and Reskilling Personnel in the Age of GenAI:
The Impact of Reflection, Critical Thinking, and Learning Analytics

Abstract

This workshop will focus on the need to embed reflection and critical thinking as central components of workplace learning and how Learning Analytics can support these processes. At the intersection of industry and research, the workshop will explore how instructional approaches can go beyond technical training to cultivate adaptive expertise, critical digital literacies, and thoughtful decision-making. Participants will engage in activities and discussions about how reflective practice and critical inquiry, aided by Learning Analytics (LA), can be integrated into upskilling and reskilling programs, ensuring that learners embrace new skills and are able to question, evaluate, and shape their impact. By foregrounding these instructional elements, the workshop underscores the role of reflective and critical capacities in building resilient, future-ready learning ecosystems.

Background: Learning Analytics

Participants will explore how learning analytics can:

• Capture and analyze how learners develop strategies, transfer skills, and engage with GenAI tools.
• Provide dashboards and data-informed feedback that prompt reflection, metacognition, and critical inquiry.
• Evaluate program effectiveness by monitoring not only skill acquisition but also growth in reflective capacity, ethical reasoning, and decision-making quality.
• Identify patterns of AI use, such as overreliance, misuse, or underuse, that require targeted pedagogical interventions.

By doing so, LA becomes a mechanism for building data-informed, learner-centered, and ethically responsible reflection and critical thinking.

Keynote Talk: 'Upskilling and Reskilling in the Age of AI: Designing Human-AI Learning Systems and Measuring Impact'

Speaker: Dr. Majd Sakr

Professor Majd Sakr is Chief Learning & Research Officer of Accenture and Accenture LearnVantage. In this role, he is responsible for the $1B+ internal training investment that supports Accenture's growth while providing best-in-class learning experiences for the company's 770,000 people. Professor Sakr also leads Accenture LearnVantage, the company's comprehensive learning and training services to help organizations reskill and upskill their people and achieve greater business value in the age of AI.

In this role, he brings extensive expertise in workforce training and technology-enhanced learning to help the company deepen thought leadership in learning and development, grow capabilities and ecosystem partnership, and foster a culture of continuous learning and innovation within Accenture and in its clients' organizations.

Professor Majd has been a faculty member in the Computer Science Department within the School of Computer Science at Carnegie Mellon University for two decades. He is the founder and director of the Technology for Effective and Efficient Learning (TEEL) Lab. For a decade, he served as the co-director of the Master of Computational Data Science (MCDS) Program at the School of Computer Science at Carnegie Mellon.

From 2007-2013, Majd was a Computer Science faculty at Carnegie Mellon University in Qatar (CMUQ), where he also held the positions of Assistant Dean for Research and Coordinator of the Computer Science Program. He founded the Cloud Computing Lab and co-founded the Qri8 Qatar Robotics Innovation Lab at CMUQ. He also co-founded the Qatar Cloud Computing Center. His research interests include workforce training at scale, cloud computing, and human-robot interaction.

He holds a BS, MS, and PhD in electrical engineering from the University of Pittsburgh.

Keynote Abstract

Drawing on Accenture's global workforce training initiatives across platforms such as Udacity, instructor-led executive education, and large-scale technology center programs, in this talk we will examine how learning analytics and generative AI are being operationalized across the full spectrum of enterprise learning. From foundational AI literacy to advanced, role-embedded, and agentic workflows, these efforts signal a shift from static curricula toward adaptive, data-driven learning ecosystems. AI-led learning initiatives will deliver integrated and personalized pathways, enable reflective practice, and drive real-time feedback grounded in learner behavior and performance data.

A central focus of the talk is the evolving role of analytics and data as an active learning instrument, not merely a reporting mechanism. In practice, analytics are used to surface moments for reflection, detect skill atrophy, balance AI assistance with deliberate learning challenges, and support human–AI collaboration through Socratic and adaptive AI agents. To evaluate impact at scale, Accenture applies the "SKAI" framework, measuring Satisfaction, Knowledge, Application, and Impact, as a systematic approach to assessing learning effectiveness and return on investment. Complementing this, enterprise-wide data and dashboards track proxy metrics that bridge learning outcomes to business outcomes, including on-the-job application, talent retention, and workforce readiness, providing a pathway toward linking learning analytics to productivity and profitability.

Workshop Goals

• Highlight emerging research and practice in AI-supported upskilling and reskilling.
• Explore the role of LA, reflection, and critical thinking in effective workforce learning.
• Foster cross-sector dialogue between academics, EdTech leaders, and workplace training professionals.
• Identify promising directions for research and practice in AI-supported learning adaptivity.

Format & Activities

Participants, who we anticipate will bridge between academia and industry, will engage in interactive activities and collaboration to:

• Analyze real and hypothetical data traces to identify opportunities for adaptive scaffolding, reflection, and critical thinking.
• Co-create strategies for integrating LA into workplace training programs in ways that respect privacy, autonomy, and ethical considerations.
• Discuss implications for designing GenAI-enabled systems that complement rather than replace human judgment.

To achieve these goals, we envision a very interactive, non-conference style workshop. The workshop will combine expert input, participant interaction, and collaborative discussion. Planned activities include:

1. Keynote Talk
2. Participant Introductions (1-2 minutes each)
3. Breakout Group Discussions
4. Synthesis and Next Steps

Expected Outcomes

By the end of the workshop, participants will leave with:

• Concrete strategies for embedding reflective practice and critical inquiry into upskilling and reskilling training programs.
• Design principles for integrating LA to support adaptive expertise and digital literacy.
• A shared understanding of how to create resilient, future-ready workplaces where employees are empowered to shape the role of GenAI rather than passively adapt to it.

Schedule

• 9:00-9:15 - Introduction
• 9:15-9:45 - Keynote (Dr. Majd Sakr)
• 9:45-10:00 Introduce Cases (2-3 cases)
• 10:00-10:30 - Discussion, part 1
• 10:30-11:00 - Coffee break
• 11:00-11:30 - Discussion, part 2
• 11:30-12:30 Synthesis (all together)