Enhancing the Credibility of the Decision-Making Journey Through Serious Games Learning Analytics

Introduction

Learning outcomes should be revisited to warrant personalised E-learning progress pathways with structured knowledge diffusion which happens with time-conditioned decision making, enabling active learning methods to expose learners to case-informed based collective reasoning skills development through Advanced Learning Tasks. Building upon the latest generation of serious games capability to provide innovative tools to enhance collective learning with documented impact in real business environments, a new challenge for business education and research is how digital knowledge representation enhances the learners’ capability to act in an accountable manner when it comes to decision taking and its consequences.

We strive to demonstrate how real or realistic business environments which expose the decision takers to a breadth of data resulted from the impact of their actions can lead to a new class of learning analytics. Thus, we will propose a framework by which we place the analytics produced by a simulation game as a new class of learning analytics and determine whether the success obtained in the simulation can be an indicator of success in real professional settings.

The value of Technology enhanced learning with Personalised Learning Analytics goes beyond collaborative learning tools adoption with sense-making obtained through the use of Decision Support Systems and effectively addressing learner behaviour variability in the carrying out of Advanced Learning Tasks: sense-giving of exploration, description, explanation and comparison. Simbound, the world first gamification platform for Digital Marketing training, allows learners to enter the world of fast internet marketing transactions and allows them to use digital tools of various complexity to improve their understanding and confidence. The serious game enables a new view on both tried and tested commercial methodologies but also opens up new possibilities in marketing technology education and research. Learners are usually grouped in teams and have the task of creating websites for their virtual company and then to increase their exposure through various channels such as paid advertisement and e-mail newsletters which will ultimately lead to sales. As of 10^th of December 2018 Simbound includes new features such as co-operative play in between teams “co-opetition” and new online community management simulations.

The current research summarises the Simbound learning experience as a relevant Case Study for enriching Personalized Learning using analytics, to explore the Effect of Analytics on Learning Outcomes and Advanced Learning Tasks.

Enhancing the credibility of the simulation enabled learning methodology and associated decision-making journey relies upon recognising differences between a virtual, simulation-based training into decision making and the real context of transferring gained skills to real business decision taking. To raise the effectiveness of marketing simulation-based training, the game designer must focus on a set of learning analytics that are relevant inside the decision taking context of choice. Recognising relevant differences between realistic decision making training and real business decision taking is a key challenge to be collaboratively addressed with instructors and practitioners. To gain insights over the learning experience in the context of decision making vs decision taking training skills, new learning outcomes are to be set up and new competences are to be developed and trained to address the complexity of a real business workplace.

The objective of the study reflects how can we measure the degree to which Simbound skills are acquired (team performance) and transferred (organizational decision-making support) to the workplace?