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In the current global competitive environment, if an organization is to be successful, it has to be a learning organization. Organizations learn from their assertive and adaptive interaction with the environment and from their internal dynamics. Organizational learning needs to be supported as external environments and internal dynamics of organizations become more complex. Discusses different learning processes and the different intelligent systems which can support and enhance organizational learning. Finally, presents a conceptual framework of an integrated intelligent system for supporting organizational learning. Intends to be useful to both organizational theorists/ practitioners and IT managers, who are involved in the development and implementation of learning organizations.

This paper aims to present a comprehensive overview of the patterns and trends of publications on artificial intelligence (AI) in personalised learning. It addresses the need to investigate the intellectual structure and development of this area in view of the growing amount of related research and practices.

A bibliometric analysis was conducted to cover publications on AI in personalised learning published from 2000 to 2022, including a total of 1,005 publications collected from the Web of Science and Scopus. The patterns and trends in terms of sources of publications, intellectual structure and major topics were analysed.

Research on AI in personalised learning has been widely published in various sources. The intellectual bases of related work were mostly on studies on the application of AI technologies in education and personalised learning. The relevant research covered mainly AI technologies and techniques, as well as the design and development of AI systems to support personalised learning. The emerging topics have addressed areas such as big data, learning analytics and deep learning.

This study depicted the research hotspots of personalisation in learning with the support of AI and illustrated the evolution and emerging trends in the field. The results highlight its latest developments and the need for future work on diverse means to support personalised learning with AI, the pedagogical issues, as well as teachers’ roles and teaching strategies.

This paper aims to present part of the work of an ongoing research project that is looking at socio‐ cultural and technological developments from a mobile technology convergence view; in order to show how culturally aware convergence developments in mobile technology can be adopted and employed for the betterment of society.

The paper presents a scenario for a mobile technology enabled learning environment in support of the conventional learning approach with a focus on enabling parental involvement and contribution to the daily learning objectives of their children and hence enhancing a quality learning experience. It further critically discusses issues of interface design – at both the device and application levels – that will have an impact on the quality of e‐learning, with a focus on mobile technology.

The paper shows how interface design can positively enhance the quality defining characteristics of learning in an e‐learning environment. Ways of achieving these characteristics of learning through effective e‐learning are reported. This is done by addressing requirements for quality‐learning through effective interface‐design considerations, towards meeting the overall quality requirements of learning that should be intrinsic to a holistic e‐learning environment. The value of human computer interaction and the critical factors of promoting productive interaction are addressed.

There are several factors affecting quality of e‐learning as a tool and approach to flexible and independent learning. The advent and use of mobile technology has been investigated in this work from a socio‐cultural and technological perspectives in two continents. The limitations lie in the depth of investigations and how far the findings can be applied to the diversity of learners.

As the effects of cultures and the rapid technological advancements take toll on teaching and learning the findings reported in this paper have far reaching implications for learners from different cultures and also for attempts at bridging existing digital divide.

The approach adopted in the research is unique by virtue of new findings and ideas presented. The paper highlights the opportunities for mobile devices and technology to play a role in the development of communities through technology aided learning (e‐learning), with a focus on e‐learning systems and technology requirements for delivering a quality learning experience.

This study examines learner satisfaction and success as mechanisms through which online learning quality translates into learners’ continuous intentions of use by extending DeLone and McLean’s information system success model. It also examines the moderating effect of perceived supervisory support and learners’ self-regulation on online learning quality in Higher Education Institutions.

Survey data were obtained from 540 students in both private and public higher institutions of learning in Ghana. The Partial Least Squares – Structural Equations Modelling (PLS-SEM) technique was used to test the hypothesised relationships.

The results revealed that system quality emerged as the single most important variable in the DeLone and McLean model, that influences learner success and satisfaction. Further, learner satisfaction has a significant positive effect on learner attitudes, whilst self-regulation was found to moderate the relationship between online learning quality and learner success as well as learner satisfaction.

The study appears to be among the first to explore the inter-relationship among online learning environment quality and learner attitudes and moderating factors perceived supervisory support and self-regulation. The study highlights insightful practical implications for students, faculty and administrators of higher institutions.

The purpose of this study is to examine the effect of extrinsic aspects of the technology acceptance model, namely, information quality, functionality, accessibility, user interface design, system quality, functionality, facilitating conditions and computer playfulness as well as intrinsic aspects, namely, perceived self-efficacy, enjoyment and learning goals. orientation on perceived usefulness and perceived ease of use in the context of the learning management system (LMS) as a system to support employee learning and development. This study also analyzes the effect of perceived ease of use on perceived usefulness and analyzes the effect of these two variables on the intention to adopt a LMS. This study included 3,205 respondents who are employees of banking companies in Indonesia and who used the LMS for their learning and self-development needs during the COVID-19 pandemic.

This research is a quantitative study that uses online surveys to collect data and partial least squares statistical tools to analyze survey data.

The results showed that accessibility alone had no effect on perceived usefulness and perceived ease of use, while enjoyment had no effect on the intention to use LMS and perceived ease of use and functionality had no effect on the intention to use LMS.

This research focuses on the concept of technology acceptance with extrinsic and intrinsic aspects. This research context involves employees working in the banking sector with the adoption of the LMS.

LMS in banking companies can be optimized by providing online training and reducing the operational costs of employee training. By using LMS, companies can offer online courses to employees and track progress in distance learning, become a learning choice and information dissemination during the pandemic and also support future business continuity.

This study focuses on testing the technology adoption model on LMSs in the banking sector by adding extrinsic aspects, namely, system quality, facilitating conditioning, computer playfulness and user interface design, and combining intrinsic aspects, namely, perceived self-efficacy, enjoyment and learning goal orientation.

The purpose of this study is to explore a support system for beginners in drawing in a networked environment. Learners can receive advice and assessments from art experts without time and/or place constraints by using the proposed system. The authors investigate the possibilities of online supporting drawing learning. Two key factors are introduced: a digital pen as a drawing tool and a drawing process model (DPM).

The major difference between an offline drawing class and an online drawing class is the availability of instruction during learners' drawing. The instruction for the learners' drawing process is more important than instructional comments for his/her work. Therefore, quick and personalized feedback from a tutor is an indispensable function for a networked learning environment. In this study, the learner's drawing process that is recorded by a digital pen is reused in order to replay and refer his/her drawing process. To generate an evaluation for the drawing process automatically, these data are also reused in the system the authors propose.

The paper provides three findings. One is the DPM to capture learner's drawing features. Second is a drawing learning support system based on the DPM. And third is a feasibility study of the support system in a real art school. In this study, the learner's drawing process is reused in two evaluations. One is the tutors' evaluation, and the other is the system's evaluation. For the latter, the authors implemented the automated evaluation function based on the DPM. This model consists of three types of parameters. They are the drawing step, the drawing phase and the features of the drawing strokes.

Because of the art school curriculum, the authors cannot examine the learning effectiveness deeply. So the research results in this paper may lack generality. Therefore, researchers are encouraged to test the proposed approach further.

The paper includes implication for the skill learning support based on the ICT.

This paper fulfils an identified need to capture and support how drawing behaviour can be done.

The purpose of this paper is to establish a model for adopting social networked learning in higher institutions of learning in developing countries of Africa.

Mixed methods research methodology involving survey and interviews was adopted in the collection of data for building the model. The model was theoretically underpinned by the Technology Acceptance Model and the social constructivist learning theory, and was built and validated using structural equation modelling and Delphi techniques respectively.

Adoption of social networked learning in developing countries of Africa requires self efficacy, reliable technical and administrative support, infrastructure, system interactivity, adequate budgeting and accountability, and a flexible organisational culture.

The model provides a framework for integrating social software tools with the traditional learning systems of developing countries of Africa. This has a positive outcome of providing social constructivist information and communication technology (ICT) supported learning at low or no cost.

The model has the potential to encourage formation of communities of practice to encourage development of social learning and a student‐centered pedagogy.

The novelty of this research lies in the extension of the traditional technology acceptance models with constructs for proper budgeting and accountability and organisational culture. Time and other resources need to be devoted to developing social networked learning and the model takes this into account.

The purpose of this paper is to examine the integration of digital library (DL) technologies with ontology‐based knowledge representation in providing semantic rich information access (IA) in e‐learning. DL technologies have powerful and flexible content management and access functionalities, whereas ontology helps teachers and students to link content materials to their learning objectives. This paper demonstrates that the integration provides a powerful and meaningful e‐learning environment.

DiLight is designed as an interactive e‐learning system that integrates DL and ontology technologies. By conducting comparative experiments involving DiLight in students' actual learning process, the authors examined the advantages and limitations of DiLight in e‐learning.

Compared to a widely used e‐learning environment, DiLight can provide significantly better support for students' complex IA tasks because DiLight is more useful for relationship discovery and problem solving. DiLight is also effective even when students were either less familiar with tasks or felt that they were more difficult. There is no single best access method for all learning situations. Therefore, multiple IA methods should be built into e‐learning systems. Although most of time the search was the first choice of the students, ontology‐based methods were useful in supporting them to complete their tasks too.

This is a comparative empirical study using an interactive e‐learning system called DiLight to explore the usage of integrated DL and ontology in e‐learning. The experiment results demonstrate the value of the multiple IA methods provided by DL, and the usefulness of integrating DL with ontology.

The purpose of this paper is to propose a hybrid model based on the expectation-confirmation model (ECM), flow theory, and updated DeLone and McLean information system (IS) success model to examine whether quality factors as the antecedents to nurse beliefs affected nurses’ intention to continue using the blended electronic learning (e-learning) system.

Sample data for this study were collected from nurses at five hospitals in Taiwan. A total of 500 questionnaires were distributed, 396 (79.2 percent) questionnaires were returned. Consequently, 378 usable questionnaires were analyzed in this study, with a usable response rate of 75.6 percent. Collected data were analyzed using structural equation modeling.

Information quality, system quality, support service quality, and instructor quality contribute significantly to perceived usefulness (PU), confirmation, and flow, which together explain nurses’ satisfaction with the usage of the blended e-learning system, and this in turn leads to their continued system usage intention.

First, the application of the ECM with the view of updated DeLone and McLean IS success model reveals deep insights into quality evaluation (including information quality, system quality, and support service quality) in the field of nurses’ e-learning continuance intention. Especially, this study additionally contributes to the identification of instructor quality that may lead to nurses’ continued blended e-learning usage intention. Next, the empirical evidence on capturing both extrinsic motivator (i.e. PU) and intrinsic motivator (i.e. flow) for completely explaining quality antecedents of nurses’ blended e-learning continuance intention is well documented.

The purpose of this paper is to identify a framework to support adaptivity in e-learning environments. The framework reflects a novel hybrid approach incorporating the concept of the event-condition-action (ECA) model and intelligent agents. Moreover, a system prototype is developed reflecting the hybrid approach to supporting adaptivity in any given learning management system based on learners’ learning styles.

This paper offers a brief review of current frameworks and systems to support adaptivity in e-learning environments. A framework to support adaptivity is designed and discussed, reflecting the hybrid approach in detail. A system prototype is developed incorporating different adaptive features based on the Felder-Silverman learning styles model. Finally, the prototype is implemented in Moodle.

The system prototype supports real-time adaptivity in any given learning management system based on learners’ learning styles. It can deal with any type of content provided by course designers and instructors in the learning management system. Moreover, it can support adaptivity at both course and learner levels.

To the best of the authors’ knowledge, no previous work has been done incorporating the concept of the ECA model and intelligent agents as hybrid architecture to support adaptivity in e-learning environments. The system prototype has wider applicability and can be adapted to support different types of adaptivity.