Design Principles for High-Performance Blended Learning Services Delivery

Abstract

The ''perfect'' orchestration of training participants, IT and process design is one of the ongoing challenges within blended learning service research and practice. Blended learning services (BLS) offer a great variety of options to design learning processes, overcoming many shortcomings of pure e-learning services and providing better scalability and more advantages for learners than pure face-to-face class teaching. Nevertheless, due to inconclusive results of blended learning design research in the literature, BLS designers can hardly find support for the systematic design of efficient and successful blended learning processes, which would enable a high degree of learning success with a balanced degree of delivery effort. Based on major determinants of BLS processes' quality, the authors identify, develop, and evaluate design principles for high performance BLS using an action design research approach. They first derive a set of initial design principles, based on insights from literature and own exploratory case studies as well as workshops with experts from the field. They then improve the design principles iteratively in expert workshops as well as apply the design principles in four software training sessions. Finally, they present seven evaluated design principles for BLS, which are the core of a nascent design theory and contribute to a time-efficient and successful BLS delivery. Furthermore, these principles enable practitioners to systematically apply the design knowledge formalized within the principles in order to improve BLS design and delivery.

Technology as a Double-Edged Sword: From Behavior Prediction with UTAUT to Students’ Outcomes Considering Personal Characteristics

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Project-Based Teaching in Organic Chemistry through Blended Learning Model to Develop Self-Study Capacity of High School Students in Vietnam

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Analysis of Competitor Intelligence in the Era of Big Data: An Integrated System Using Text Summarization Based on Global Optimization

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