E-learning materials often have a linear design where all learners are forced into a single-mode pedagogy, which is contrary to the interaction that occurs in face-to-face learning. Ideally, e-learning materials should be nonlinear, interactive, contain context-sensitive and active learning elements, and accommodate various learning levels and styles. This paper presents an educator’s perspecti...

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Designing creative learning environments involves not only facilitating student creativity, but also modeling creative pedagogical practice. In this paper we explore the implementation of a framework for designing creative learning environments using mobile social media as a catalyst for redefining both lecturer pedagogical practice, as well as redesigning the curriculum around student generate...

„ provide a set of recommendations that draw upon those requirements and other examples of contemporary practice, and also align with the aspirations of UNSW 2025 Strategy: Our Strategic Priorities and Themes (UNSW 2025) For information on this project please see https://www.learningenvironments.unsw.edu.au/content/lsproject UNSW 2025 identifies themes that learning and teaching spaces and the ...

Advances in computer technology and multi-media systems have led to widespread interest in computer-based instruction and learning environments. The use of video, animation, graphics, and simulation allow the presentation of material in realistic contexts, thus addressing the problems of inert knowledge while promoting constructive and generative learning. But the true potential and bene ts of ...

Personal Learning Environments (PLEs) are attracting increasing interest in the e-learning domain. However, the term Personal Learning Environment is used in a variety of different ways in the field. This paper firstly draws distinctions between the term PLE and similar terms. It then discusses the dimensions which characterise current conceptions of PLEs, thereby defining a space of PLEs. Thre...

This study assessed 96 law school students’ preferences for online, hybrid, or traditional learning environments, and their reasons for these preferences, learning strategies, and motivational orientations. A discriminant analysis revealed that non-traditional learning environment familiarity, self-efficacy, and employment status were the strongest predictors of preferences for non-traditional ...

Existing intelligent learning environments for programming represent a step towards comprehensive adaptive learning environments that support all activities in learning programming. In most of these systems, however, only the tutoring component is adaptive. The user interface usually looks the same for the novice and for the advanced learner, while the student's knowledge of the subject matter ...

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