Modelling, Design and Implementation of a Web-based Personalised E-learning System
Chapter One
Objectives
The objectives of this project are to:
- Develop a model for a web-based personalised e-learning system that will allow teachers and students to efficiently utilize the power of computer networks to deliver and access educational services in a personalized
- Design the prototype web-based personalised e-learning application that allow teachers to author learning objects in a standardized uniform format and that allows students study those materials in a style most convenient to them, using standard software design techniques hence creating a blueprint that can easily be replicated or improved upon by other researchers as technology
- Implement the automatic profiling of students to determine their preferred learning style based on Honey and Mumford Learning Style Questionnaire(LSQ).
Chapter Two
LITERATURE REVIEW
Introduction
Over the last two decades, the search for new and efficient ways of integrating technology into education for improved teaching and learning experiences and the delivery of ancillary educational services has resulted in a dramatic increase in the use of Information and Communication Technology (ICT) based solutions in educational service delivery generally known as electronic learning (e-learning).
Learning Theories
In education, learning theories are attempts to explain how people learn, there by helping in understanding the complex process of learning. There are basically three main schools of thought in learning theories – Behaviouralism, Cognitivism, and Constructivism. This thesis will briefly discuss these fundamental learning theories to highlight their potential influence on personalised e-learning programme.
Behaviourist theorists define learning as nothing more than the acquisition of new behaviour. From an educational perspective the behaviourist learner is viewed as a passive recipient of knowledge. Learning can then be viewed as the acquisition of this objective knowledge through rehearsal and correction, Tuckey (1992). From teaching perspective behaviouralism maintains that the role of a teacher is to reinforce correct behaviour from their students. The behaviourist expects the teacher to predetermine all the skills they believe are necessary for the students to learn and then present them to the group in a sequenced manner, Conway (1997). The influence of this theory on
personalised e-learning is twofold, first the learning system should reinforce student behaviour that it perceives to be correct and second, the learning system should have a predetermined view as to the best order in which skills and knowledge should be presented.
Cognitivists maintain that there is an external reality and an internal representation of that reality. According to Bruner (1960), information equals learning, so outward appearances to that effect are merely communications illuminating the result of learning rather than learning itself. As the mind seeks a view of the objective reality it gives through a number of processes when it receives information (by attention); this information is then integrated into the inherent order of memory via a process of encoding; information becomes knowledge when it is integrated into the existing cognitive structure; and knowledge can then be remembered in the process of retrieval.
From the educational perspective, the emphasis on teaching and learning strategies shifts to techniques to complement the attention, encoding and retrieval of knowledge. This can be achieved by careful organisation of content, and the use of analogies and mnemonics, Newby (1996).
Computers process information in a similar fashion to how cognitive scientists believe humans do. Information is received, stored and retrieved. When viewed from personalised e-learning perspective the role of the computer in the educational domain would be to present a view of the information to be learned and drill the students until they understand it, Adewale (2007).
Finally, constructivism subsumes the attention, encoding and retrieval of knowledge processes from cognitivism, but maintains that there is no single accurate representation of the world, only interpretations of experience. Knowledge is a collection of concepts which fits with the experience of the individual. New information is important for different reasons to the recipients of the information, Tuckey (1992). From the perspective of e-learning, the information presented would have to be relevant to the learner in the framework of what they have previously learned, Henze, Nejdl and Wolpers (1999a; 1999b).
The constructivist approach implies that learners will learn more with a teacher than from a teacher, Newby (1999b). Similarly, learners will learn more with a computer than from a computer, Reeves (1998). It is argued that traditional teacher-centric approaches to learning do not transfer successfully to technology and must be revolutionised. The philosophy must change from computers as teaching machine to computers as tools to empower learners and teachers, Oppenheimer (1997).
Learning Styles: Definition and Concepts
Although learning style may be simply defined as the way people come to understand and remember information, there are various other definitions for the term. James and Gardner (1995), for example, define learning style as the “complex manner in which, and conditions under which, learners most efficiently and most effectively perceive, process, store, and recall what they are attempting to learn”. Merriam and Caffarella (1991) present Smith’s definition of learning style, which is popular in adult education, as the “individual’s characteristic way of processing information, feeling, and behaving
in learning situations”. Swanson (1995) quotes Reichmann’s reference to learning style as “a particular set of behaviours and attitudes related to the learning context” and also presents Keefe’s definition of learning style as “the cognitive, affective, and physiological factors that serve as relatively stable indicators of how learners perceive, interact with, and respond to the learning environment”.
Litzinger and Osif (1993) define learning styles as the ways in which children and adults think and learn. Learning styles are sometimes described as the personally constructed filters people use to orient their relationships with the world, as stated by O’Connor (1997). These filters are influenced by factors such as age, maturity, and experience; as such they are likely to change over time. In addition, the study of learning styles has provided us with categories or groupings of these filters. For example, filters may be categorised by the senses (auditor- visual or kinaesthetic). Some people may respond to auditory information more readily than information presented visually, for example. Other studies of learning styles have focused on a combination of sensory and cognitive approach to examine how students process information. One result is Gardner’s (1983) theory of multiple intelligences, which categorizes learning styles as visual-spatial (ability to perceive the visual), verbal- linguistic (ability to use words and language), logical-mathematical (ability to use reason, logic, and numbers), bodily-kinaesthetic (ability to control body movements and handle objects skillfully), musical rhythmic (ability to produce and appreciate music), and interpersonal (ability to relate and understand others intrapersonal (ability to self-reflect and be aware of one’s inner state of being), and naturalistic (ability to use awareness of the natural world and the sciences). Armstrong (1994) examined the use of Gardner’s theory in the classroom and came to four conclusions: each person possesses all eight intelligences, the intelligences have the capacity to be developed to higher levels, the intelligences work together in complex ways, and there exist numerous ways to be intelligent. Yet other theorists have looked at the study of learning styles through the lens of gender, noting that males and females tend to approach learning and learning situations differently, Belenky et al (1986).
In their review of the myriad studies on learning styles, Claxton and Murrell (1988) noted four main categorizations of the ways people learn: personality models’, information processing models’, social interaction models’, instructional and environ- mental /preference models.
Chapter Three
System Modeling and Design Architecture
Design considerations
When designing a personalised e-learning course there are many ways in which the course can be personalised. For example, it can be personalised according to the learners’ learning goals and/or their preferred learning styles. It is commonly believed that most people favour some particular method of interacting with, taking in, and processing stimuli or information. Based on this concept, the idea of personalised “learning styles” originated in the 1970s, and has gained popularity in recent years. A learning style is the method of learning peculiar to an individual that is presumed to allow that individual to learn best. Honey and Murmford (1992) define learning style as ‘a description of the attitudes and behaviour which determine an individual’s preferred way of learning’. Subsequently they come up with four learning styles which they describe as those of activities, reflectors, theorists and pragmatists.
Learning styles attempt to establish indicators on how learners perceive, process, and interact with learning environments. Considering these indicators, it is possible to design learning materials and instructional designs more suitable to the manner each learner learns. Many learning style approaches had been presented in Adewale (2007). There are some that are appropriate only for a specific field, like the Felder and Silverman learning style model that is suitable only for engineering education.
Meanwhile the Honey and Mumford (2000) learning style model is categorized as being information processing model type or more specifically it is an information processing model based on experiential learning. The other models categorize the learner on the basis of less relevant aspects related to learning (e.g. senses and the environmental factors) whereas learning has mainly to do with perceiving and processing information. For this reason, the Honey and Mumford (2000) learning style model is an appropriate model to choose for the development and implementation of the web-based personalised e-learning system Adewale (2007). The model also provides an ideal structure for reviewing experience, learning lessons, and planning improvements.
Chapter Four
Systems Requirement and Implementation
System Requirement
The minimum hardware requirement for the effective development and implementation of this system are as follows:
- A Pentium IV CPU, 1.8 GHz processor with 512MBmemory
- A 40 GB hard drivecapacity
- Agraphic adaptor with screen resolution of 800 x 600 pixels and 32 bit quality
Chapter Five
Summary, Conclusion and Recommendations
Summary
This research work involved the study and overview of e-learning and the evolving trends of its implementation in the teaching and learning process. It further made a case for the student-centered paradigm shift towards instruction, with active, collaborative, and personalised learning as key principles based on the client-centered philosophy of business. In exploring this paradigm shift, different learning theories and their associated learning styles were surveyed. The cognitivisim learning theory and the Honey and Mumford learning style classification was then adopted for this work due to there correlation to the way computers process and relay information. A personalised e- learning model was developed and finally implemented as a web-based system using Apache as web server, PHP as the server-side scripting language, HTML as client-side scripting language and MySQL as the relational database.
Conclusion
This thesis presented a formal description of personalised e-learning system, a pedagogically sound approach to adaptively composing and personalizing the access of learning contents in tertiary institutions. A mathematical model for the profiling of learners to determine their learning style based on the Honey and Mumford LSQ was also presented. Based on the mathematical model, the software architecture for the Web-based Personalised E-Learning System was designed using the three tier client-server systems architecture. In so doing it presented the main components of the model performing the functions of personalised learning materials to meet individual learner’s learning requirements based on their learning style.
Finally, the architectural design was implemented using the Apache WapmServer, MySQL, and PHP web technology tools.
Recommendations
To successfully integrate this system into the teaching and learning process, the thesis puts forward the following recommendations:
- The need for the provision of a well-maintained computer network infrastructure in the tertiary institutions that will allow tutors and learners to easily compose and access learning
- Learners should be encouraged to acquire portable personal computers in order to avail themselves of this new technology to improve their personal study
- Seminars and workshops should be organized for tutors and learners to sensitize them on how to efficiently utilize the
Further Research
To increase the level of automation of the system, it is suggested that further research be carried out on how to integrate the technology of ontology and semantic web to improve the searching and personalization of learning contents from the web. It is also suggested that further research be conducted on how to make the system available on mobile devices to increase the ubiquity of its use.
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