The digital Dalton Plan: Progressive education as integral part of web-based learning environments

Abstract

e-Learning systems increasingly support learning management and self-organized learning processes. Since the latter have been studied in the field of progressive education extensively, it is worthwhile to consider them for developing digital learning environments to support self-regulated learning processes. In this paper we aim at transforming one of the most prominent and sustainable approaches to self-organized learning, the “Dalton Plan†as proposed by Helen Parkhurst. Its assignment structure supports learners when managing their learning tasks, thus triggering self-organized acquisition of knowledge, and its feedback graphs enable transparent learning processes. Since e-learning environments have become common use, rather than creating another system, we propose a modular approach that can be used for extending existing e-learning environments. In order to design a respective component, we interviewed experts in self-organized e-learning. Their input facilitated integrating the Dalton Plan with existing features of e-learning environments. After representing each interview in concept maps, we were able to aggregate them for deriving e-learning requirements conform to the Dalton Plan instruments. In the course of implementing them, particular attention had to be paid to the asynchrony of interaction during runtime. Java Server Faces technology enable the Dalton Plan component to be migrated into existing web 2.0 e-learning platforms. The result was evaluated based on the acquired concept maps, as they also captured the transformation process of the Dalton Plan to e-learning features. The findings encourage embodying further progressive education approaches in this way, since the structured (concept) mapping of the Dalton Plan to e-learning features turned out to be accurate. The experts were able to recognize the potential of the approach both in terms of structuring the knowledge acquisition process, and in terms of developing progressive learning support features.

https://doi.org/10.34105/j.kmel.2018.10.002