Work

Enhancing knowledge transformation in digital education: an analysis of the SECI model’s application in course design and execution

Year: 2024

Type: article

Abstract: This study investigates the application of the SECI model in the design and execution of educational courses in "Innovation and Digitization Management" and "Data-Based Decision Making" micro-degrees developed in 2023 and 2024. Leveraging Natural Language Processing (NLP) and text analysis, we explore the patterns in course content that correlate with positive learner feedback and effective knowledge transformation. The methodology includes data preprocessing, tokenization, vectorization, and clustering to systematically compare and contrast course elements with learner feedback. Preliminary findings indicate that the integration of the SECI model, emphasizing real-time content sharing and example-based learning, significantly enhances the transfer of knowledge from tacit to explicit forms. This research aims to identify a replicable cadence in content preparation that optimizes learning outcomes.

Source: Discover Education

DOI: 10.1007/s44217-024-00229-0

Author: Dmitrij Żatuchin

Institutions: Estonian Business School, Estonian Entrepreneurship University of Applied Sciences

Language: English

Topic: E-Learning and Knowledge Management

Subfield: Computer Science Applications

Field: Computer Science

Domain: Physical Sciences

SDG: Quality education

Open Access status: gold

Estimated APC paid: $1,340