No description available.

No description available.

No description available.

There has recently been great promise and interest in the use of adaptive learning systems to provide personalized course content, tailored to the ability levels and pace of individual students. Yet, not all the technologies in this space provide the same capabilities. In this thesis I analyze a representative group of adaptive learning providers according to the pedagogical model of their design. Then, I discuss case studies of two systems to analyze their design according to a humanist design philosophy and a more cybernetic design tradition, and I conclude with a set of design guidelines and selection criteria for faculty and administrators interested in evaluating, selecting, and implementing an adaptive learning system that fits their pedagogical values.

A thesis submitted to the Faculty of Arts in fulfilment of the requirements for the Degree, Masters of Communication Science in the Department of Communication Science at the University of Zululand, 2018. / The enhancement of the quality of education through the digitisation of the learning systems is a national priority in South Africa and beyond. Some academic institutions, both basic and higher level, have responded to this by adopting the use of ICT in their practice. However, the enormous digital divide between urban and rural areas has escalated with its negative effect on the schools. Most rural schools remain underdeveloped with a huge deficit in teaching and learning resources, while technological progressions continue at an unprecedented speed. These advancements in technology come with drastic changes in all spheres of life, particularly in the labour market. Thus, the need for preparing high school learners with relevant skills for the future, which mostly relies on ICT capabilities. This study, therefore, focuses on how the use of ICT in a rural classroom can help bring the learners to speed with the digital revolutions we are witnessing. The study adopts the Technology Acceptance Model as well as the Interactive Model to propose plausible solutions. The data were collected from 121 rural secondary school teachers in the King Cetshwayo District Municipality. The findings of the study revealed that the lack of ICT skills among teachers, and insufficient resources to support classroom experiences are key barriers to the effective use of innovative communication protocols, which include ICT in the rural classroom. This has policy implications for the department of higher education in terms of human resource development and the provision of appropriate logistics.

Hypertext is the dominant method to navigate the Internet, providing user freedom and control over navigational behaviour. There has been an increase in converting existing educational material into Internet web pages but weaknesses have been identified in current WWW learning systems. There is a lack of conceptual support for learning from hypertext, navigational disorientation and cognitive overload. This implies the need for an established pedagogical approach to developing the web as a teaching and learning medium. Guided Discovery Learning is proposed as an educational pedagogy suitable for supporting WWW learning. The hypothesis is that a guided discovery environment will produce greater gains in learning and satisfaction, than a non-adaptive hypertext environment. A second hypothesis is that combining concept maps with this specific educational paradigm will provide cognitive support. The third hypothesis is that student learning styles will not influence learning outcome or user satisfaction. Thus, providing evidence that the guided discovery learning paradigm can be used for many types of learning styles. This was investigated by the building of a guided discovery system and a framework devised for assessing teaching styles. The system provided varying discovery steps, guided advice, individualistic system instruction and navigational control. An 84 subject experiment compared a Guided discovery condition, a Map-only condition and an Unguided condition. Subjects were subdivided according to learning styles, with measures for learning outcome and user satisfaction. The results indicate that providing guidance will result in a significant increase in level of learning. Guided discovery condition subjects, regardless of learning styles, experienced levels of satisfaction comparable to those in the other conditions. The concept mapping tool did not appear to affect learning outcome or user satisfaction. The conclusion was that using a particular approach to guidance would result in a more supportive environment for learning. This research contributes to the need for a better understanding of the pedagogic design that should be incorporated into WWW learning environments, with a recommendation for a guided discovery approach to alleviate major hypertext and WWW issues for distance learning.

Learning is one of the most interactive processes that humans practice. The level of interaction between the instructor and his or her audience has the greatest effect on the output of the learning process. Recent years have witnessed the introduction of e-learning (electronic learning), which was then followed by m-learning (mobile learning). While researchers have studied e-learning and m-learning to devise a framework that can be followed to provide the best possible output of the learning process, m-learning is still being studied in the shadow of e-learning. Such an approach might be valid to a limited extent, since both aims to provide educational material over electronic channels. However, m-learning has more space for user interaction because of the nature of the devices and their capabilities. The objective of this work is to devise a framework that utilises augmented reality and context awareness in m-learning systems to increase their level of interaction and, hence, their usability. The proposed framework was implemented and deployed over an iPhone device. The implementation focused on a specific course. Its material represented the use of augmented reality and the flow of the material utilised context awareness. Furthermore, a software prototype application for smart phones, to assess usability issues of m-learning applications, was designed and implemented. This prototype application was developed using the Java language and the Android software development kit, so that the recommended guidelines of the proposed framework were maintained. A questionnaire survey was conducted at the University, with approximately twenty-four undergraduate computer science students. Twenty-four identical smart phones were used to evaluate the developed prototype, in terms of ease of use, ease of navigating the application content, user satisfaction, attractiveness and learnability. Several validation tests were conducted on the proposed augmented reality m-learning verses m-learning. Generally, the respondents rated m-learning with augmented reality as superior to m-learning alone.

Instructors' use of e-learning systems in higher education institutions is a central concern of researchers, academicians, and practitioners. Higher education institutions are investing substantial resources to incorporate and maintain the infrastructure of e-learning systems; however, instructors' use of e-learning systems in two-year colleges is relatively limited. In this context, the goal of this study was to investigate the factors that may affect instructors' intention to use e-learning systems in two-year colleges. Based on literature review on technology acceptance, this study proposed a theoretical model predicting instructors' intention to use e-learning systems in two-year colleges based on their resistance to change, perceived value of e-learning systems, computer self-efficacy (CSE), and attitude toward e-learning systems. Consequently, this study investigated the effect of four independent variables on the dependent variable, intention to use e-learning systems. A Web-based survey was designed to empirically assess the effect of aforementioned constructs on instructors' intention to use e-learning systems in two-year colleges. The Web-based survey was developed as a multi-item measure using Likert-type scales. Existing validated scales were used to develop the Web-based survey. The target population of this study was instructors of public and private two-year colleges. The sample for this study was 119 (over 41% response rate) full-time, part-time, and adjunct instructors in different academic departments at a two-year college. Two statistical methods were used to formulate and test predictive models: Multiple Linear Regression (MLR) and Ordinal Logistic Regression (OLR). Both MLR and OLR results showed that the theoretical model was able to predict instructors' intention to use e-learning systems. All four independent variables have significant effects on the dependent variable. Results of both analyses were consistent on resistance to change as having the greatest weight on predicting instructors' intention to use e-learning systems, while CSE in both analyses was found to have the least weight. This study contributes to the body of knowledge by providing empirical results for the key constructs that affect two-year college instructors' intention to use e-learning systems. Results of this research may also help IT practitioners to concentrate their efforts on ways to address resistance to change as it was found to be the most significant factor affecting e-learning accepted by two-year college instructors.

In the automotive industry test drives are conducted during the development of new vehicle models or as a part of quality assurance for series vehicles. During the test drives, data is recorded for the use of fault analysis resulting in millions of data points. Since multiple vehicles are tested in parallel, the amount of data that is to be analysed is tremendous. Hence, manually analysing each recording is not feasible. Furthermore the complexity of vehicles is ever-increasing leading to an increase of the data volume and complexity of the recordings. Only by effective means of analysing the recordings, one can make sure that the effort put in the conducting of test drives pays off. Consequently, effective means of test drive analysis can become a competitive advantage. This Thesis researches ways to detect unknown or unmodelled faults in recordings from test drives with the following two aims: (1) in a data base of recordings, the expert shall be pointed to potential errors by reporting anomalies, and (2) the time required for the manual analysis of one recording shall be shortened. The idea to achieve the first aim is to learn the normal behaviour from a training set of recordings and then to autonomously detect anomalies. The one-class classifier “support vector data description” (SVDD) is identified to be most suitable, though it suffers from the need to specify parameters beforehand. One main contribution of this Thesis is a new autonomous parameter tuning approach, making SVDD applicable to the problem at hand. Another vital contribution is a novel approach enhancing SVDD to work with multivariate time series. The outcome is the classifier “SVDDsubseq” that is directly applicable to test drive data, without the need for expert knowledge to configure or tune the classifier. The second aim is achieved by adapting visual data mining techniques to make the manual analysis of test drives more efficient. The methods of “parallel coordinates” and “scatter plot matrices” are enhanced by sophisticated filter and query operations, combined with a query tool that allows to graphically formulate search patterns. As a combination of the autonomous classifier “SVDDsubseq” and user-driven visual data mining techniques, a novel, data-driven, semi-autonomous approach to detect unmodelled faults in recordings from test drives is proposed and successfully validated on recordings from test drives. The methodologies in this Thesis can be used as a guideline when setting up an anomaly detection system for own vehicle data.

Today popular learning management systems (LMS) lack interactivity. Interactivity is very important in the learning process, because it‘s a great mean of interest and motivation. The level of interactivity could be increased by using scripts, but some of the modern scripting languages are not universal, and the majority are too hard to comprehend for non-IT specialists. That’s why a brand new scripting language has been created. It can be integrated to an open-source PHP based LMS and because of it‘s simplicity and usage of native language in syntax is rather easy to learn for non-IT staff. Experiments showed that it‘s rather convenient, compared to other similar languages and it’s speed does not slow down the process of webpage generation to an extent a user would notice. It’s also capable of performing basic mathematical and other scientific task modeling, making the language sufficient for common use. The script language has some of the complex template language properties, so it can be also used as a tool of managing content rendering. Practical integration of the script language with “Google Maps” service and VRML showed that it can be expanded to the required extent. Further works with this language may include expansion of syntax and implementation of AJAX technology.