PERFORMANCE SUPPORT SYSTEM IN HIGHER EDUCATION – INTRODUCTION AND EMPIRICAL VALIDATION Slavi Stoyanov Open University of the Netherlands, Educational Technology Expertise Centre, PO Box 2960, 6401 DL Heerlen, the Netherlands Piet Kommers University of Twente, Faculty of Behavioural Sciences, PO Box 217, 7500 AE Enschede, The Netherlands Theo Bastiaens FernUniversität Hagen, Institute of Educational Science and Media Research, Universitätsstr. 11/ TGZ, D-58084 Hagen, Germany Catalina Martínez Mediano National University of Distance Education, Faculty of Education, Madrid, 28040, Spain ABSTRACT The paper defines and empirically validates the concept of performance support system in higher engineering education. The validation of the concept is based upon an experimental study investigating the effect of performance support system on achievements and attitudes of students. The study confirmed the expectation that the performance support system produced significantly better results than the traditional method of teaching when achievements of students were compared. The analysis of the students’ attitudes towards the method revealed that the operationalization of support was better implemented in the tested performance support system than performance. KEYWORDS Performance support system, learning to solve problems, learning adaptation, higher engineering education. 1. INTRODUCTION Determining the most effective and efficient conditions for supporting performance of learners in higher education has always been considered by learning designers, curriculum developers and teachers as one of the most important and challenging tasks (Brown et al, 1996; Ericsson, 2006; Merrill, 2002; Spiro & Jehng, 1990; van Merriënboer and Kirschner, 2007). While the consensus among experts on the role of performance support in higher education is increasing, there is a disagreement on what does performance support mean, and specifically which learning outcomes performance is related to. Is it memorizing of information, understanding of principles, applying rules, or acquiring of so called high-order cognitive skills (Brown et al, 1996; Spiro & Jehng, 1990; van Merriënboer and Kirschner, 2007)? These types of learning outcomes require different type of instructional support. There is a tendency in the contemporary learning design paradigm for paying more attention to the higher levels of learning taxonomy, as some authors prefer to use the term problem solving rather than high-order cognitive skills (Jonassen, 2000, 2004; Merrill, 2002). Most of the studies on learning to solve problems have investigated well-defined, often artificial problems, rather than authentic problems, which are ill-structured. Ill-structured problems are the problems that students will IADIS International Conference on Cognition and Exploratory Learning in Digital Age (CELDA 2007) 279