A methodology for planning, implementation and evaluation of skills intelligence management - results of a design science project in technology organisations.

Introduction: The evolving labour market requirements amidst digital transformation necessitate robust skills intelligence for informed decision-making and adaptability. Novel technologies such as Big Data, Machine Learning, and Artificial Intelligence have significant potential for enhancing skills intelligence. Methods: This study bridges the gap between theory and practice by designing a novel software artefact for skills intelligence management. With its systematic framework for identifying skills intelligence elements, an assessment instrument, and an implementation methodology, the artefact ensures a thorough approach to skills intelligence management. Results: The artefact was demonstrated in 11 organisations. Feedback collected from interviews, focus group sessions, and observations (N = 19) indicated that the artefact is a feasible starting point for implementing or systematising skills intelligence management. Participants suggested improvements but concurred that the systematic approach enhances skills intelligence data collection and quality. Discussion: The study shows that the artefact facilitates the application of advanced technologies in skills intelligence management. Additionally, it contributes a set of principles for effective skills intelligence management, fostering a broader conversation on this critical topic. Participants' feedback underscores the artefact's potential and provides a basis for further refinement and application in diverse organisational contexts.

Integrating AI tools in teacher professional learning: a conceptual model and illustrative case.

This conceptual paper aims to explore the complex nature of integrating AI technologies in teacher professional learning, highlighting the potential for AI to synergize teacher noticing and decision-making processes, support adaptive teaching, foster alignment with competence frameworks, and cultivate professional vision, thereby framing teacher practices within the framework of professional vision. We argue that rather than looking at the process of adopting AI solutions by teachers from a technology perspective or how teachers contribute to designing and developing such tools, we take the perspective of the teacher and ask how such tools are meaningfully integrated into teacher practices. In our conceptual paper, we illustrate the case of a novel approach to the teacher training model where the development of teacher' professional vision and professional learning is combined with the design of the AI solutions. We argue the importance of involving teachers into the design of AI solutions through professional learning models to support teachers to develop knowledge-based reasoning skills and at the same time to learn about pedagogical concepts and develop new mental models.