A Conceptual Model for Effective Quality Management of Online and Blended Learning

Yves Blieck, Chang Zhu, Kim Schildkamp, Katrien Struyven, Bram Pynoo, Cindy L. Poortman, Koen Depryck

Research output: Contribution to journalArticleAcademicpeer-review

5 Citations (Scopus)
14 Downloads (Pure)

Abstract

Institutions considering online and blended learning (OBL) face the challenge of strategically adopting OBL to develop, implement, monitor, assess and improve the quality of programmes and courses. The principles of continuous quality improvement (CQI) allow this challenge to be addressed. Effective CQI management implies that quality assurance and quality improvement follow and inform each other as part of a continuous cycle. Scholars report however, that quality management of OBL usually focuses on assurance. The purpose of this paper is to provide a state of the art approach for effective CQI management which allows practitioners to achieve coherence between quality assurance and improvement of OBL. In this conceptual paper we link and integrate work across fields to address the challenge of achieving coherence between quality assurance and improvement. We discuss research in the context of CQI that uncovers features of OBL that prevent practitioners from achieving coherence. The conceptual model for effective CQI of OBL integrates data based decision-making. The conceptual model provides a foundation for research on the effectiveness of this CQI management approach in the context of OBL. The quality management approach supports practitioners during the entire CQI-cycle to foster dialogue and consultation between all stakeholders in the institution in order to strategically develop assess and improve the quality of OBL programmes and courses. The originality of the model lies in making explicit data-based decision making as a driver for effective CQI management in the context of OBL.

Original languageEnglish
Pages (from-to)189-204
Number of pages16
JournalElectronic Journal of e-Learning
Volume18
Issue number2
DOIs
Publication statusPublished - 1 Feb 2020

Keywords

  • data-based decision making
  • e-learning
  • online and blended learning
  • quality assurance
  • quality enhancement
  • quality improvement

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