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Dissertation: Deep learning in digital environments requires more perceptive planning, scaffolding, and evaluation of learning


The so-called digital leap of learning is a constant topic of discussion in the media and educational institutions. However, instead of taking superficial digital leaps, it is time to move toward more goal-oriented, dialogical, and collaborative knowledge construction where students can choose digital work environments that they prefer. Sanna Ruhalahti, MBA , has advanced a pedagogical model in the context of vocational teacher education, where authentic and dialogical collaborative knowledge construction is taken into the direction of deep learning in digital environments.

Ruhalahti redesigned the pedagogical model DDD (Dialogical, Digital and Deep learning) through her doctoral research with an aim to help learning designers. Consequently, six design principles were developed to support the planning of dialogical collaborative knowledge construction and deep learning outcomes. To facilitate the evaluation of skills demonstrating deep learning, the research also introduces a redesigned pragmatical framework for evaluating deep learning.

“In practice, this also requires increased perceptiveness in the student’s zone of proximal development. The research showed that authentic and dialogical collaborative knowledge construction supporting deep learning provides a fruitful approach when developing teacher education in the context of digital learning,” Ruhalahti points out.

Based on the research, dialogical skills and knowledge should also be integrated deeper into the processes of vocational teacher education. This would ensure the learning of deep dialogical skills and knowledge that will be part of teachers’ competence in the future. In fact, Ruhalahti proposes that the learning process be planned in such a way that copied and transferred knowledge is not useful, because knowledge, its quantity, and its use have undergone a revolution in the digital era. This planning is facilitated by supporting an investigative approach and by emphasising authentic aspects more transparently than before.

According to Ruhalahti, self-paced studies placed in the beginning and in the end of the learning process help students to steer their development toward deep learning. Furthermore, assignments and processes advancing deep learning must be designed in such a way that they support skills leading to deep learning as part of dialogical collaborative knowledge construction.

Scaffolding is still needed, however, and the teacher as an expert in the relevant field is able to identify the most critical phases of the learning process. Further, in terms of peer learning enabled by the learning community, for instance an experienced student may guide a less experienced one and students’ field-specific expertise may be combined. This also puts emphasis on the role of the learning community.

“In addition to a dialogical learning community, deep learning requires higher-order thinking skills. Most of all, deep learning in a digital environment requires a learning community that is committed to a common goal and to the authenticity of the learning situation. It means that students with very diverse backgrounds and skill levels can enter the community.
In addition, training for dialogical knowledge construction through various dialogical methods is needed within the learning process. The related key skills are equality, symmetrical participation, listening, inquiring, being aware of one’s own assumptions, and weaving syntheses.” Notes Ruhalahti.

Altogether 76 Finnish vocational teacher students and 14 teachers around the world took part in the qualitative research.

Public examination of the dissertation:

The dissertation Redesigning a Pedagogical Model for Scaffolding Dialogical, Digital and Deep Learning in Vocational Teacher Education by Sanna Ruhalahti, BBA, is proposed by permission of the Faculty of Education at the University of Lapland for public examination in Castrén Hall on Friday 12 April at 12 noon. The opponent is Associate Professor Sami Paavola from the University of Helsinki and the custos is Professor Heli Ruokamo from the University of Lapland. The language of the event is Finnish.

Information on the doctoral candidate:

Sanna Marjatta Ruhalahti, MBA, born 1971, graduated as a cleaning technician from Järvenpää Home Economics Teacher School in 1991. In 2000, she upgraded her degree to a bachelor degree at Turku University of Applied Sciences. In 1997 she graduated as a vocational teacher from the Jyväskylä School of Professional Teacher Education. She earned a master-level degree at Satakunta University of Applied Sciences in 2008. Ruhalahti has worked at HAMK University of Applied Sciences, School of Professional Teacher Education as a teacher educator since 2006. Before that, she worked as a vocational teacher and as the coordinator of international affairs at Pori Adult Education Centre. Her areas of expertise have dealt with digitalization of teaching and learning, especially the development of dialogical competence to support deep learning both in the national and in the international domains of education.

Further information:

Sanna Ruhalahti

Information on the publication:

Sanna Ruhalahti: Redesigning a Pedagogical Model for Scaffolding Dialogical, Digital and Deep Learning in Vocational Teacher Education, Acta electronica Universitatis Lapponiensis 257, ISSN 1796-6310, ISBN 978-952-337-145-3.

Permanent address of the e-dissertation:

LaY/Communications & Language centre/J-EK & AT