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AI-Powered Learning Experience Platforms: Investigating Personalized Learning in the Workplace

A Case of an International Company in Sweden

Abstract
Purpose: This thesis investigates the implementation and impact of Degreed, an AI-powered LXP, within a multinational corporation in Sweden, focusing on its role in facilitating personalized learning and professional development. The study aims to understand the perceptions of both management and employees regarding Degreed's effectiveness in meeting their learning needs and enhancing their professional development. Theory: The research is grounded in the theoretical frameworks of andragogy, the Zone of Proximal Development (ZPD), the Technology Acceptance Model (TAM), and the Learning Ecosystem Framework 2.0 (LEF 2.0). The study also draws upon existing literature on workplace learning, personalized learning, learning analytics, and AI-powered learning platforms. Method: The study employs a mixed-methods approach, combining interviews with L&D managers and employees, along with a survey questionnaire. The qualitative data from the interviews and open-ended survey responses were analyzed using thematic analysis, while the quantitative data from the survey were analyzed using descriptive statistics. Results: The findings reveal that Degreed has been successful in aggregating learning resources, offering personalized recommendations, and facilitating skill development aligned with strategic objectives. However, challenges persist in fully leveraging the platform's potential for social learning, extrinsic motivation, and seamless integration of AI-powered features. The study underscores the importance of aligning the platform's functionalities with the diverse learning needs and preferences of employees, fostering a culture of continuous learning, and ensuring that AI-powered features are transparent, ethical, and user-friendly. The insights gained from this research can inform organizations seeking to implement or optimize LXPs for their workforce, contributing to the creation of learning ecosystems that empower employees to take ownership of their professional development and achieve their full potential.
Degree
Student essay
URI
https://hdl.handle.net/2077/83632
Collections
  • Masteruppsatser (IPKL)
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Thesis (1.752Mb)
Date
2024-10-14
Author
Khamis, Rasha
Keywords
Learning Experience Platforms
Personalized Learning
AI
Learning Analytics
Workplace Learning
Language
eng
Metadata
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