Rob Nadolski

Serious Games for Higher Education: A Framework for Reducing Design Complexity.

Westera, W., Nadolski, R., Hummel, H. G. K., & Wopereis, I. (2008). Serious games for higher education: a framework for reducing design complexity. Journal of Computer Assisted Learning, 24(5), 420-432.

EMERGO: A methodology and toolkit for developing serious games in higher education

Societal changes demand educators to apply new pedagogical approaches. Many educational stakeholders feel that serious games could play a key role in fulfilling this demand, and they lick their chops when looking at the booming industry of leisure games. However, current toolkits for developing leisure games show severe shortcomings when applied to serious games. Developing effective serious games in an efficient way requires a specific approach and tool set. This article describes the EMERGO methodology and generic toolkit for developing and delivering scenario-based serious games that are aimed at the acquisition of complex cognitive skills in higher education. Preliminary evaluation results with case developers using the EMERGO methodology and toolkit and with learners using EMERGO cases are presented.

Scripted collaboration in serious gaming for complex learning: Effects of multiple perspectives when acquiring water management skills

Hummel, H. G. K., Van Houcke, J., Nadolski, R. J., Van der Hiele, T., Kurvers, H., & Lohr, A. (2011). Scripted collaboration in gaming for complex learning: Effects of multiple perspectives when acquiring water management skills. British Journal of Educational Technology, 42(6), 1029-1041. doi:10.1111/j.1467-8535.2010.01122.x

Combining social-based and information-based approaches for personalised recommendation on sequencing learning activities

Lifelong learners who select learning activities to attain certain learning goals need to know which are suitable and in which sequence they should be performed. Learners need support in this way-finding process, and we argue that this could be provided by using Personalised Recommender Systems (PRSs). To enable personalisation, collaborative filtering could use information about learners and learning activities, since their alignment contributes to learning efficiency. A model for way-finding presents personalised recommendations in relation to information about learning goals, learning activities and learners. A PRS has been developed according to this model, and recommends to learners the best next learning activities. Both model and system combine social-based (i.e., completion data from other learners) and information-based (i.e., metadata from learner profiles and learning activities) approaches to recommend the best next learning activity to be completed.

Optimizing the number of steps in learning tasks for complex skills.

BACKGROUND Carrying out whole tasks is often too difficult for novice learners attempting to acquire complex skills. The common solution is to split up the tasks into a number of smaller steps. The number of steps must be optimized for efficient and effective learning. AIM The aim of the study is to investigate the relation between the number of steps provided to learners and the quality of their learning of complex skills. It is hypothesized that students receiving an optimized number of steps will learn better than those receiving either the whole task in only one step or those receiving a large number of steps. SAMPLE Participants were 35 sophomore law students studying at Dutch universities, mean age=22.8 years (SD=3.5), 63% were female. METHOD Participants were randomly assigned to 1 of 3 computer-delivered versions of a multimedia programme on how to prepare and carry out a law plea. The versions differed only in the number of learning steps provided. Videotaped plea-performance results were determined, various related learning measures were acquired and all computer actions were logged and analyzed. RESULTS Participants exposed to an intermediate (i.e. optimized) number of steps outperformed all others on the compulsory learning task. No differences in performance on a transfer task were found. A high number of steps proved to be less efficient for carrying out the learning task. CONCLUSIONS An intermediate number of steps is the most effective, proving that the number of steps can be optimized for improving learning.

CopperCore Service Integration - Integrating IMS Learning Design and IMS Question and Test Interoperability

This article describes a framework for the integration of e-Learning services. There is a need for this type of integration in general, but the presented solution was a direct result of work done on the IMS Learning Design specification (LD). This specification relies heavily on other specifications and services. The presented architecture is described using the example of two of such services: CopperCore, a LD service, and APIS, an IMS Question and Test Interoperability service. One of the design goals of the architecture was to minimize the intrusion for both the services as well as any legacy client that already uses these services.

A model for optimizing step size of learning tasks in competency-based multimedia practicals

Learners are often overwhelmed by the complexity of realistic learning tasks, but reducing this complexity through traditional Instructional Design (ID) methods jeopardizes the authenticity of the learning experience. To solve this apparent paradox, a two-phase ID model is presented. Phase 1 consists of cognitive task analysis, where a systematic approach to problem solving (SAP) is identified in conjunction with skill decomposition and determination of task complexity. In the subsequent design phase, inductive micro-level sequencing based on the four-component ID model (van Merriënboer, 1997) is applied where worked-out examples and problems accompanied by process worksheets assure the necessary variability of practice. Step size in a multiple-step whole-task approach—needed for the process worksheets—is determined on the basis of estimated part-task complexity. A developmental study of the model is illustrated with examples from the domain of law.

CopperCore Service Integration.

In an e-learning environment there is a need to integrate various e-learning services like assessment services, collaboration services, learning design services and communication services. In this article we present the design and implementation of a generic integrative service framework, called CopperCore Service Integration (CCSI). We will concentrate on the integration of two services: CopperCore, an IMS Learning Design service and an IMS Question and Test Interoperability service called Assessment Provision through Interoperable Segments (APIS). One of the design goals of the architecture was to minimize the intrusion for both the services as well as any legacy client that already uses these services. The result of this work is that the flow of learning activities can be made dependent on test results.

Implications of Learning Analytics for Serious Game Design

This paper addresses the implications of combining learning analytics and serious games for improving game quality, monitoring and assessment of player behavior, gaming performance, game progression, learning goals achievement, and users appreciation. We introduce two modes of serious games analytics: in-game (real time) analytics, and post-game (off-line) analytics. We also explain the GLEANER framework for in-game analytics and describe a practical example for off-line analytics. We conclude with a brief outlook on future work, highlighting opportunities and challenges towards a solid uptake of SGs in authentic educational and training settings.

Deploying Serious Games for Management in Higher Education: lessons learned and good practices

Baalsrud Hauge, J., Bellotti, F., Nadolski, R. J., Kickmeier-Rust, M., Berta, R., & Carvalho, M. B. (2013). Deploying Serious Games for Management in Higher Education: lessons learned and good practices. In C. Vaz de Carvalho, & P. Escudeiro (Eds.), Proceedings of the 7th European Conference on Games-Based Learning (pp. 225-234). Porto, Portugal: Academic Conferences and Publishing International Limited.