A Methodological Approach to Address Individual Factors and Gender Differences in Adaptive eLearning

Adaptive eLearning systems aim at personalizing the learning objects and test items according to a learner’s specific needs. There is a variety of existing adaptive eLearning systems, either research prototypes or systems in commercial use. However, these systems are primarily limited to adapt to learners’ current knowledge or to certain test items learners are capable of solving. Thus, in the past such approaches to adaptive eLearning have been criticized for the lack of adapting to individual factor and gender based-differences. In the current article we introduce the Competence Performance Approach, as an extension of Knowledge Space Theory, and propose the same methodology as basis for modelling individual factors and gender-based differences. 1 Adaptive approaches to eLearning Adaptive eLearning systems are used to tailor learners’ views of learning objects to their personal requirements. Such technologies are often incorporated to guide through a large body of learning objects assisting learners in their comprehension of that material. For example, an adaptive system may only provide learning objects which are suitable for the learner. Too difficult and also too easy learning objects might not be displayed in order to avoid visual and cognitive load and to suggest an appropriate learning path through the learning content. Existing adaptive eLearning systems such as ALEKS (www.aleks.com), ELM-ART [1], or KBS Hyperbook [2] demonstrated benefits for learners in terms of navigating through contents [3] and in terms of classroom and platform independence [4]. [5] found advantages of JointZone, an adaptive eLearning system in medical education, in terms of acceptance and also learning performance. Generally, these adaptive approaches attempt to compete the one-fits-all approach of traditional eLearning [6], accounting for certain requirements and preferences of a learner. Primarily, such approaches provide adaptive navigation and adaptive presentation of contents ([7], [8], [9], [10]). Adaptive navigation, as already mentioned, refers to guidance through learning objects by, for example, a customized hyperlink structure or format. The degree of freedom granted within a system is determined by a specific underlying learner model. Adaptive presentation refers to a customized presentation of learning objects. On the one hand this might refer to the visual or auditory design; on the other hand this might refer to the amount or grade of details of presented learning contents. However, adaptive eLearning systems have also been criticized and discussed regarding deficits and weaknesses. A major point is that almost all existing eLearning systems do not account for gender differences or individual factors such as personal abilities, preferences, learning styles, or learning strategies. This is remarkable since research on individual differences and gender emphasize possible gender-bias (e.g., androcentricity/gynocentricity, overgeneralization, gender insensitivity, or double standards; cf. [11]), which is influencing research and design. Moreover, individual abilities, needs, and preferences (e.g., different cognitive abilities, different learning styles and strategies, different Kickmeier-Rust, M. D., Albert, D., & Roth, R. (2007). A Methodological Approach to Address Individual Factors and Gender Differences in Adaptive eLearning. In K. Siebenhandl, M. Wagner, & S. Zauchner (Eds.), Gender in E-Learning and Educational Games: A Reader (pp. 71-84). Innsbruck: Studienverlag.