Nurul Fazmidar Mohd. Noor

Visualization Notations, Models and Taxonomies

Visualization taxonomies are an important means of imposing some structure on a rather diverse fi eld. We review some earlier work in this area, particularly work based on the use of a notation to label classes of visualization techniques that are appropriate to particular entities. We propose a new notation introducing it in the context of a new visualization reference model, one we hope will lead eventually to a means of describing visualizations in a clear and unambiguous way.

Navigation technique in 3D information visualisation

Information visualisation (IV) involves representing information visually as a mean of getting insight into data. Many techniques are available in visualising information, with city/urban planning as one of them. The challenge that lies with city/urban planning technique in information visualisation is how to enhance the information legibility as to assist users in their way finding task. Therefore, Universiti Malaya (DM) campus is used as the subject domain to study the efficiency of the city visualisation method applied to 3D virtual environment. Few navigation aids are identified and incorporated into the visualised virtual environment, and the effectiveness of these navigation aids in helping users finding the information in the 3D virtual environment, by means of navigating within it is investigated.

Predicting the adoption of cloud-based technology using fuzzy analytic hierarchy process and structural equation modelling approaches.

Abstract With the emergence of cloud-based technology, personalized learning mechanism has increasingly become a fundamental requirement for most learning systems. This study aimed to identify the key factors that influence user adoption of cloud-based collaborative learning technology in the educational context. Grounded on the Unified Theory of Acceptance and Use of Technology (UTAUT), personalization construct was linked to the behavioral intention, performance expectancy and effort expectancy. This research applied a new methodological approach combining both Fuzzy Analytic Hierarchy Process (FAHP) and Structural Equation Modelling (SEM) to determine the relative weight and importance of the factors as well as to test the proposed hypotheses in the research model. Using a survey questionnaire, data was collected from 150 students of four Malaysian public universities. The findings of FAHP demonstrated that performance expectancy, social influence, and personalization were the most important factors predicting behavioral intention to adopt cloud-based collaborative learning technology from experts’ point of view. The results of the SEM showed that users’ behavioral intention was significantly influenced by performance expectancy, effort expectancy, social influence and personalization. Although, personalization performed a direct influence on behavioral intention, its indirect influence through performance expectancy and effort expectancy was also considerable. This study and its findings can serve as a baseline by which cloud service providers, ministry of education, and educational institutions can make strategic and strong decisions about adoption of cloud-based technology in educational environments.

A meta-analysis on the correlation between measurements of spatial tasks and standardized tests of environmental spatial abilities

Previous findings indicate that spatial abilities at different scales of space, e.g. small-scale and large-scale space (Montello and Golledge 1999; Montello 1993) are partially dissociated (Hegarty et al. 2006). Traditionally, the attempts to identify and assess these different sets of spatial abilities have focused mostly on small-scale spaces, whereas significantly less work has focused on assessing large-scale or environmental spatial abilities. This is unfortunate because the existing psychometric tests for small scale spatial abilities account for only 5% of the variance in the ability to learn large-scale environments (Hegarty and Waller 2005) and therefore represent poor predictors of environmental learning (Allen et al. 1996; Waller 2000, 2005). Given the limited work on developing standardized measures of environmental spatial abilities, such abilities have been investigated through people’s performance on non-standardized spatial tasks in large-scale outdoor spaces (McNamara et al. 2003). A multitude of such tasks have been designed and employed with the intention to measure environmental spatial abilities. However, progress with the development of standardized tests for large-scale spatial abilities is currently hindered by a threefold challenge: (1) spatial tasks in large-scale spaces are usually complex involving several spatial abilities rather than just one, (2) several spatial tasks have been employed for assessing the same spatial ability, and (3) spatial tasks in large-scale spaces are strongly coupled with the environment in which they are investigated. The goal of this meta-analysis is to investigate the relationships between environmental spatial abilities and their measurements, i.e. standardized tests or non-standardized spatial tasks, with the particular aim to identify those spatial tasks which have been successfully and consistently used to measure a particular environmental spatial ability. Our work has focused on identifying strong relationships between specific spatial tasks and environmental spatial abilities as a preliminary step in a larger research agenda aiming towards the development of standardized tests for measuring environmental spatial abilities.

Stemming Hausa text: using affix-stripping rules and reference look-up

Stemming is a process of reducing a derivational or inflectional word to its root or stem by stripping all its affixes. It is been used in applications such as information retrieval, machine translation, and text summarization, as their pre-processing step to increase efficiency. Currently, there are a few stemming algorithms which have been developed for languages such as English, Arabic, Turkish, Malay and Amharic. Unfortunately, no algorithm has been used to stem text in Hausa, a Chadic language spoken in West Africa. To address this need, we propose stemming Hausa text using affix-stripping rules and reference lookup. We stemmed Hausa text, using 78 affix stripping rules applied in 4 steps and a reference look-up consisting of 1500 Hausa root words. The over-stemming index, under-stemming index, stemmer weight, word stemmed factor, correctly stemmed words factor and average words conflation factor were calculated to determine the effect of reference look-up on the strength and accuracy of the stemmer. It was observed that reference look-up aided in reducing both over-stemming and under-stemming errors, increased accuracy and has a tendency to reduce the strength of an affix stripping stemmer. The rationality behind the approach used is discussed and directions for future research are identified.

Inventive problem-solving puzzle game design and development

This paper depicts the production of a game for learning theory of inventive problem solving or TRIZ. The theory is meant for resolving engineering contradiction and forecasting trends and evolution of technologies. Despite being an effective invention tool, TRIZ has been criticised for its steep learning curve by people who have no engineering background. Beginning learners commonly face difficulties to comprehend TRIZ principles, not to mention using them to solve problems. To resolve this issue, a ten-level puzzle game was designed and developed. A key challenge was confronted by the production team as the game designers were trying to ensure transfer of knowledge, from solving in-game puzzles to understanding of the usage of each principle. This paper illustrates how the challenge was overcome in the gamification process. The insight might benefit content experts in other fields of study who intend to design and develop games for teaching and learning purposes.