Mobile learning phd thesis

The dependent variables were meant to measure service quality interface design, reliability, responsiveness, trust, and personalizationinformation quality content usefulness, content adequacyand system quality ease of use, accessibility, and interactivity.

The definition of reinforcement learning can be understood with the following concepts: The second phase was meant to identify the factors that lead to service quality of m-learning in a university environment.

Natural Language Processing Natural Language Mobile learning phd thesis or NLP is a branch of Artificial Intelligence using which computers are made to understand, manipulate, and interpret human language.

Master Thesis Topics in Machine Learning

Therefore, the study discussed in this thesis addresses this gap by proposing an mGBL Engineering Model based on a number of games and learning theoretical and developmental foundations.

The third phase was carried out to implement the findings of the above two phases and present a practical example that reflects the dimensions of mobile learning service quality in a university environment. The questionnaire measured ten dependent variables and three independent variables.

It will help to analyze the large volumes of textual data generated every day.

Mobile Game-Based Learning (mGBL) Engineering Model

This study reports on the results of a survey conducted on students, and instructors from HE institutions in Kuwait, in order to understand their perceptions and opinions about the effectiveness of the use of mobile learning. However, there are many limitations to it which includes accessibility and mobility that makes educationalists and researchers think of m-learning as a potential alternative tool for providing easy and accessible educational service.

It is another good topic in machine learning for thesis and research. Model evaluation was conducted in three phases, namely; expert review, prototype development with heuristics evaluation, and experimental study.

In addition, I sought to determine how applicable the UTAUT theoretical model and the additional variables, voluntariness of use, perceived playfulness and self-management of learning are in explaining student behavioral intention to use mobile devices for learning.

Completed PhD Theses

FastAnnotationTool Reinforcement Learning Reinforcement Learning is a type of machine learning algorithm in which an agent learns how to behave in an environment by interacting with that environment.

The researcher administered a item-questionnaire on students representing different colleges of UUM. A lot of research has been done in this area of machine learning in the recent times. All these results have demonstrated that the proposed mGBL Engineering Model exhibits useful development indicators for mGBL applications and is indeed a theoretical and practical contribution of the study.

Student Acceptance of Mobile Learning. Please be aware that modifications were made to the study after my prospectus defense and there are notes included in the slides.

Generally, the proposed mGBL Engineering Model was well accepted by the experts contacted in this study. It uses the concept of machine learning and deep learning for complete interaction between humans and computers. In relation to this, various game development methodologies have been introduced for different types of game genres and platforms.

The findings revealed that the factors that lead to service quality of m-learning in a university environment were interface design, reliability; trust, content usefulness, content adequacy, ease of use, accessibility, and interactivity. The findings revealed that mobile phone is the most acceptable technology device among the university students, and students who have a positive attitude toward e-learning are likely to have positive attitude toward m-learning.

Subsequently, eight mGBL evaluation dimensions were put forward: However, the study reports some social and cultural issues that may act as barriers to m-learning implementation.

Besides that, it was investigated when it uses the cell phone in english classes and then we have attempted to know which is the best way to provide the critical and visual literacy in a way to allow the students really to be able to learn and to retain information with help of mobile devices.

It aims to fill the space between human communication and computer understanding. This research was conducted in three phases. In accomplishing this aim, a design science research methodology was adopted, comprising of five phases; i awareness of problem, ii suggestion, iii development, iv evaluation, and v conclusion.

In particular, the study identified the key steps of development methodology to be considered in developing mGBL applications which consist of phases, components, steps, and deliverables.

Consequently, the researcher developed and implemented an m-learning system prototype MLS in a university environment.

The conclusion reached during analysis is that teaching with the help of the phone is fairly recent, but the experience of this research was rewarding and motivating for students and researcher. The model was also employed by a game company while developing an mGBL prototype. Previous article in issue.

The results also revealed that students and instructors have positive perceptions of m-learning, and indicated that video-based social media applications are widely used among them. Computers can interpret human speech and text using the concept of natural language processing.

The approach of this algorithm is different from other machine learning algorithms which are supervised learning and unsupervised learning. The ANOVA results show that there are significant differences between all groups in six dimensions except complexity and compatibility.

Mobile learning has helped improve language learning, it put students into a real context and made this process more attractive, interesting and motivating. It is among the most recent growing research areas whereby its main aim is to use game play to enhance motivation in learning, engage in knowledge acquisition, and improve the effectiveness of learning activities through mobile environment.

The research investigated the affordances that emerged from the interaction the students with the mobile phone and that potentiated the five language skills in the teaching and learning of English as a foreign language.

Furthermore, high prices of the mobile services and devices minimize the utilization of mobile learning services.

These methodologies propose different numbers of steps and activities; some focusing only on the learning design; some concentrating on the mobile technologies; and others on the complete life cycle.Mobile learning is the next step in the development of distance learning.

Theses and Dissertations

Widespread access to mobile devices and the opportunity to learn regardless of time and place make the mobile learning an important tool for lifelong. MOBILE LEARNING: Exploring cell phone potential in teaching and learning English as a foreign language to students from public schools.

The research investigated the affordances that emerged from the interaction the students with the mobile phone and that potentiated the five language skills in the teaching and learning of English as a foreign. Here is a list of PhD and EdD theses completed in the recent past at the Faculty of Education.

Language Learning through Mobile Technologies: An Opportunity for Language Learners and Teachers Mebratu Mulatu Bachore (PhD) Department of Languages and Communication Studies,College of Social Sciences and Humanities,Hawassa University,Hawassa, Ethiopia, M.

PhD Thesis

Wulfmeier, “Efficient Supervision for Robot Learning via Imitation, Simulation, and Adaptation,” PhD Thesis, Oxford, United Kingdom, The PhD in e-learning aims to provide advanced training for researchers in a specific area of e- learning, which will be carried out in a tutored manner, guiding the future doctors in the development of a doctoral thesis.

Mobile learning phd thesis
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