Ahmed Al-Hunaiyyan

Blended E-Learning Design: Discussion of Cultural Issues

Blended e-learning is becoming an educational issue especially with the new development of e-learning technology and globalization. Educators as the question: can we design these systems to accommodate different cultural groups and various learning strategies. This paper addresses some design issues when selecting a blended e-learning approach; it discusses some cultural elements that affect the design of blended e-learning. The paper also explores issues related to learning design, then emphasizes on the importance of cultural learning objects (CLO) and its role in the design of multimediabased e-learning systems.

Towards knowledge modeling and manipulation technologies

We identified different knowledge base modelling and manipulation techniques based on 4 categories.Compared knowledge base modelling and manipulation technologies based on their underlying theories, knowledge representation technique, knowledge acquisition technique, challenges, applications, development tools and development languages.We discussed the relevance of knowledge-based business.We proposed a promising technique for knowledge-based business management and other knowledge related applications. A system which represents knowledge is normally referred to as a knowledge based system (KBS). This article focuses on surveying publications related to knowledge base modelling and manipulation technologies, between the years 20002015. A total of 185 articles excluding the subject descriptive articles which are mentioned in the introductory parts, were evaluated in this survey. The main aim of this study is to identify different knowledge base modelling and manipulation techniques based on 4 categories; 1) linguistic knowledge base; 2) expert knowledge base; 3) ontology and 4) cognitive knowledge base. This led to the proposition of 8 research questions, which focused on the different categories of knowledge base modelling technologies, their underlying theories, knowledge representation technique, knowledge acquisition technique, challenges, applications, development tools and development languages. A part of the findings from this survey is the high dependence of linguistic knowledge base, expert knowledge base and ontology on volatile expert knowledge. A promising technique for knowledge-based business management and other knowledge related applications is also discussed.

Towards an effective integrated e-learning system: Implementation, quality assurance and competency models

Engineering e-learning systems is becoming of a vital importance in order to have an effective implementation of these systems in the different learning environments. The vast and rapid development in the computer, communication and Internet technologies has significantly affected contemporary educational systems. The wide utilization of technology, the abundance of information and knowledge, and the use of multimedia applications, create real challenges to present an efficient and attractive e-learning model that encompasses all these elements. In addition, the dimension of quality assurance in the emerged e-learning environment becomes a real challenge. In such a complex environment, the teacher/instructor competency level and readiness require a new dynamic frame work to ensure the quality of education. This paper presents a new blended e-learning model and quality assurance framework for an efficient implementation in higher education with concentration on online engineering. In addition, a new integrated competency level is presented to ensure the teacher/instructor readiness for the new e-learning environment. The proposed model and framework successfully incorporates all the above elements.

The design of multimedia blended e-learning systems: Cultural considerations

New technology has been used inside and outside the classroom to enhance student learning. The transition from traditional learning systems, to multimedia based e-learning systems, urge designers to consider human-factor issues to increase usability. Blended learning has been defined as the combination of characteristics from both traditional learning and e-learning environments. Blended e-learning is becoming an educational issue especially with the new development of e-learning technology and globalization. Educators ask the question: can we design these systems to accommodate different cultural groups and various learning strategies. This paper addresses some design issues when selecting a blended e-learning approach; it discusses some cultural elements that affect the design of blended e-learning. The paper also emphasizes on the importance of cultural learning objects (CLO) and its role in the design of multimedia-based e-learning systems.

Looking perfect: Instagram use in a Kuwaiti cultural context

ABSTRACT This study surveys 539 Arab university students to examine gender motivational differences in Instagram use, exploring the Self-Perfectionist Personality concept and usage activities that best predict a Self-Presentation motive on Instagram. While both genders utilized Instagram mainly for Entertainment, they varied on the priority of other motives. Females were less likely to have public accounts, post personal pictures, and disclose personal information. Also, self-perfectionists of both genders excessively edited their personal pictures before posting them and were more likely to use Instagram for Self-Presentation. Outcomes are discussed in the light of the influences of culture and gender roles in Kuwait.

Adaptive feedback in computer-based learning environments: a review

Adaptive support within a learning environment is useful because most learners have different personal characteristics such as prior knowledge, learning progress, and learning preferences. This study reviews various implementation of adaptive feedback, based on the four adaptation characteristics: means, target, goal, and strategy. This review focuses on 20 different implementations of feedback in a computer-based learning environment, ranging from multimedia web-based intelligent tutoring systems, dialog-based intelligent tutoring systems, web-based intelligent e-learning systems, adaptive hypermedia systems, and adaptive learning environment. The main objective of the review is to compare computer-based learning environments according to their implementation of feedback and to identify open research questions in adaptive feedback implementations. The review resulted in categorizing these feedback implementations based on the students’ information used for providing feedback, the aspect of the domain or pedagogical knowledge that is adapted to provide feedback based on the students’ characteristics, the pedagogical reason for providing feedback, and the steps taken to provide feedback with or without students’ participation. Other information such as the common adaptive feedback means, goals, and implementation techniques are identified. This review reveals a distinct relationship between the characteristics of feedback, features of adaptive feedback, and computer-based learning models. Other information such as the common adaptive feedback means, goals, implementation techniques, and open research questions are identified.

A Cognitive Knowledge-based Framework for Adaptive Feedback

Adaptive learning environments provide personalization of the instructional process based on different parameters such as: sequence and difficulty of task, type and time of feedback, learning pace and others. One of the key feature in learning support is the personalization of feedback. Adaptive feedback support within a learning environment is useful because most learners have different personal characteristics such as prior knowledge, learning progress and learning preferences. In a computer-based learning environment, feedback is considered as one of the most effective factors which influence learning. Although, there are various tools that provide adaptive feedback in learning environments, some problems still exist. One of the problems we are looking into is How to design effective tutoring feedback strategies? We propose a cognitive knowledge based framework for adaptive feedback, which combines the three facets of knowledge (pedagogical, domain and learner model) in a learning environment, using concept algebra.

Design of an Algebraic Concept Operator for Adaptive Feedback in Physics

In an adaptive learning environment, the feedback provided during problem-solving requires a means, target, goal, and strategy. One of the challenges of representing feedback to meet these criteria, is the representation of the effect of multiple concepts on a single concept. Currently, most of the methods (linguistic knowledge base, expert knowledge base, and ontology) used in representing knowledge in an adaptive learning environment only provide relationships between a pair of concept. However, a cognitive knowledge base which represents a concept as an object, attribute, and relations (OAR) model, provides a means to determine the effect of multiple concepts on a single concept. Using the OAR model, the relationships between multiple pedagogical, domain, and student attributes are represented for providing adaptive feedback. Most researchers have proposed adaptive feedback methods that are not fully grounded in pedagogical principles. In addition, the three knowledge components of the learning environment (pedagogical, domain and student models) are mostly treated in isolation. A reason for this could be the complex nature of representing multiple adaptive feedback characteristics across the main components of a learning environment. Thus, there is a need to design a concept operator that can relate the three facets of knowledge in an adaptive learning environment. Using the algebraic concept operator \( R_{i}^{in} \), the effect of multiple attributes of the three knowledge components on the student’s performance is represented. The algebraic concept operator introduced in this article will allow teachers and pedagogy experts to understand and utilize a variety of effective feedback approaches.