Context awareness in mobile computing: A review

Context awareness is increasingly gaining applicability in interactive ubiquitous mobile computing systems. In order to apply this concept in design of applications for dynamic environments, it is necessary to understand what constitutes context awareness, the classification of context and context-aware development frameworks. The concept of context awareness is discussed, various approaches to context awareness are reviewed, and important aspects of context-aware mobile computing are analysed. Recommendations for better understanding of context awareness and design principles for development of context-aware applications are provided.

Agent-based adaptive e-learning model for any learning management system

Many scholars are interested in improving e-learning in order to provide easy access to educational materials. There is, however, the need to incorporate the ability to classify learners into these learning systems. Learner classification is used adaptively to provide relevant information for the various categories of learners. There is also a need for learning to continue, whether learners are on- or off-line. In many parts of the world, especially in the developing world, most people do not have reliable continuous internet connections. We tested an Adaptive e-Learning Model prototype that implements an adaptive presentation of course content under conditions of intermittent Internet connections. This prototype was tested in February 2011 on undergraduate students studying a database systems course. This study found out that it is possible to have models that can adapt to characteristics such as the learner’s level of knowledge and that it is possible for learners to be able to study under both on- and off-line modes through adaptation.

Automatic assessment of online discussions using text mining

Online discussion forums have rapidly gained usage in e-learning systems. This has placed a heavy burden on course instructors in terms of moderating student discussions. Previous methods of assessing student participation in online discussions followed strictly quantitative approaches that did not necessarily capture the students’ effort. Along with this growth in usage there is a need for accelerated knowledge extraction tools for analysing and presenting online messages in a useful and meaningful manner. This article discussed a qualitative approach which involves content analysis of the discussions and generation of clustered keywords which can be used to identify topics of discussion. The authors applied a new k-means++ clustering algorithm with latent semantic analysis to assess the topics expressed by students in online discussion forums. The proposed algorithm was then compared with the standard k-means++ algorithm. Using the Moodle course management forum to validate the proposed algorithm, the authors show that the k-mean++ clustering algorithm with latent semantic analysis performs better than a stand-alone k-means++.

The impact of Memory Transfer Language (MTL) on reducing misconceptions in teaching programming to novices

Despite the fact that programming is at the heart of computer science, it is argued that even at its simplest level it is a difficult subject to teach and learn. For any new learner programming concepts are abstract and confusing. As teaching programming continues to be a daunting task, this article revisits common challenges inherent in teaching computer programming to novices. Further, Memory Transfer Language (MTL) as used to teach programming is introduced and demonstrated. Different kinds of misconceptions in programming and their associated bugs are analysed. An experiment using MTL to teach programming was carried out, using error-counts in examination scripts from two groups of students, one instructed using MTL and the other through the conventional approach. Results indicated a highly significant statistical difference (p = 0) between the two groups, showing that MTL can help novices avoid common programming misconceptions and reduce the errors they make. This shows that if programming is taught using MTL, comprehension is enhanced.