Goal trees as structuring element in a digital data-driven study assistant

Abstract

The Future Skills Report about the future of learning and higher Education (Ehlers & Kellermann, 2019) defines a variety of skills in which the active learner plays a central role. Starting from this perspective, our idea is to promote future skills with a digital data-driven study assistant for. As a theoretical foundation research about constructivism, self-regulation and goal-setting is reviewed and the concept of Goal Trees as structuring element of a software is derived. On a psychological level we show how Goal Trees may increase motivation and simplify study planning. On the level of user interface design, we show how Goal Trees may be used as structuring element of a digital data-driven study assistant. Consequently we outline how functionalities derived from research about goal-setting and self-regulation can be implemented in a study assistant. Finally advantages and challenges of implementing such a system are discussed. © 2019 16th International Conference on Cognition and Exploratory Learning in Digital Age, CELDA 2019. All rights reserved.