Research Projects

LEAD and CharVEL are two collaborative research groups operating at the Tampere University of Technology (LEAD) and the University of Tampere (CharVEL). Their research work focuses on professional growth and learning in the contexts of education and working life. The LEAD research group studies factors related to the teaching, learning, and development of expertise in the formal (higher education) and informal (working life) engineering contexts. LEAD is part of the Novi research center in the Industrial and Information Management Laboratory at the Tampere University of Technology. CharVEL research group investigates characteristics and predictors related to vocational expertise and excellence in the context of secondary and post-secondary education.

The research themes are examined within several intertwined research projects. Professional growth is examined in various learning environments, both physical and virtual, including environments that are closed (formal, e.g., curriculum-based education in vocational and higher education institutions), open (non-formal and informal, e.g., workplaces, social media), and take hybrid forms (e.g., apprenticeships). The research on learning focuses on factors related to the regulation of learning, self-directedness in learning, active learning methods, and emotions in different learning situations and environments.

The research groups apply qualitative, quantitative, and mixed methods to investigate professional growth and learning. The research designs are mostly longitudinal and involve intervention component. The survey and interview instruments are based on existing, internationally validated research instruments and groups’ earlier research on modeling of vocational expertise and excellence. The qualitative interview data analysis takes the form of qualitative content analysis of the textual empirical data, while the quantitative data is collected through smart rings, mobile applications, and electronic surveys. The groups also apply Bayesian nominal indicator modeling to learn structures from self-assessment and objective data (algorithmic modeling) and to validate the qualitative analysis results.

Research projects

2017-2021 Regulation of learning and active learning methods in the context of engineering education (REALMEE). Funding: Tampere University of Technology
2016-2019 Skills, Education and the Future of Work (SEFW). Funding: Academy of Finland
2017-2019 Next Move (NeMo) 2 – Vocational expertise, working life skills and workplaces as learning environments in apprenticeship education. Funding: City of Tampere Apprenticeship Fund
2016-2017 Demonstration of Expertise in Specialization Education (ASOS). Funding: Finnish Ministry of Culture and Education
2015-2017 Mentoring in Apprenticeship Education (MAE). Funding: City of Tampere Apprenticeship Fund
2014-2017 Next Move (NeMo) – Apprenticeships and changing skills requirements. Funding: City of Tampere Apprenticeship Fund

Earlier research project

2011-2015 Participatory Learning Model and Environments in Life-cycle Services for Children and Adolescents (PALM). Funding: RYM Indoor Environment Program
2012-2014 Pathways to Vocational Excellence (PaVE). Funding: Finnish Ministry of Culture and Education
2011-2013 Professional Excellence in Air Traffic Management. Funding: TEKES (Finnish Funding Agency for Technology and Innovation)
2010-2011 Non-linear modeling of Factors Contributing to Growth-oriented Atmosphere. Funding: Academy of Finland
2009-2011 Actualizing Vocational Excellence (AVE). Funding: Finnish Ministry of Culture and Education
2007-2008 Bayesian Modeling of Activities and Profiles: A case study in computer-supported collaborative learning (BMap). Funding: Finnish Work Environment Fund
2007-2008 Modeling of Vocational Excellence (MoVE). Funding: Finnish Ministry of Culture and Education

International research projects

2011- MOVE – Modelling Vocational Excellence. Funding: WorldSkills Foundation
2011- Developing and Understanding Vocational Excellence (DuVE). Funding: University of Oxford