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The megaclass as a service production system and the challenge of facilitating its continuous quality improvement: Towards a research agenda in a complex domain
Author(s) -
Ograjenšek Irena,
Gal Iddo
Publication year - 2018
Publication title -
quality and reliability engineering international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.913
H-Index - 62
eISSN - 1099-1638
pISSN - 0748-8017
DOI - 10.1002/qre.2341
Subject(s) - knowledge management , quality (philosophy) , metacognition , production (economics) , service (business) , domain (mathematical analysis) , service quality , cognition , computer science , psychology , business , marketing , mathematical analysis , philosophy , mathematics , epistemology , economics , macroeconomics , neuroscience
Abstract This paper aims to fill a gap in the literature on continuous quality improvement in higher education, regarding factors that may contribute to the effectiveness of megaclasses. We argue for the need to view megaclasses as a complex service production system, using introductory statistics classes as an example. Given the multiple virtual and tangible factors and processes and diverse learning communities involved in the megaclass, we believe that there is a need to better understand both its academic learning outcomes (ie, formation of knowledge, attitudes, and beliefs) and outcomes of service processes (ie, satisfaction levels of stakeholders and service metrics). We propose directions for a research agenda in this rapidly developing arena, using a model of 6 research areas influencing the above outcomes: (1) teaching methods; (2) cognition, learning, and assessment; (3) emotions, attitudes, and beliefs; (4) self‐management and metacognition; (5) social interaction and inquiry patterns; and (6) technology‐based interactions. We examine 7 traditional and emerging research methods that may jointly contribute to a better understanding of outcomes in megaclasses and Massive Open Online Classes and discuss their implications.