| 1. |
- Abu Khousa, Eman, et al.
(author)
-
A social learning analytics approach to cognitive apprenticeship
- 2015
-
In: Smart Learning Environments. - : Springer Berlin/Heidelberg. - 2196-7091. ; 2:14
-
Journal article (peer-reviewed)abstract
- The need for graduates who are immediately prepared for employment has been widely advocated over the last decade to narrow the notorious gap between industry and higher education. Current instructional methods in formal higher education claim to deliver career-ready graduates, yet industry managers argue their imminent workforce needs are not completely met. From the candidates view, formal academic path is well defined through standard curricula, but their career path and supporting professional competencies are not confidently asserted. In this paper, we adopt a data analytics approach combined with contemporary social computing techniques to measure, instil, and track the development of professional competences of learners in higher education. We propose to augment higher-education systems with a virtual learning environment made-up of three major successive layers: (1) career readiness, to assert general professional dispositions, (2) career prediction to identify and nurture confidence in a targeted domain of employment, and (3) a career development process to raise the skills that are relevant to the predicted profession. We analyze self-declared career readiness data as well as standard individual learner profiles which include career interests and domain-related qualifications. Using these combinations of data sources, we categorize learners into Communities of Practice (CoPs), within which learners thrive collaboratively to build further their career readiness and assert their professional confidence. Towards these perspectives, we use a judicious clustering algorithm that utilizes a fuzzy-logic objective function which addresses issues pertaining to overlapping domains of career interests. Our proposed Fuzzy Pairwise-constraints K-Means (FCKM) algorithm is validated empirically using a two-dimensional synthetic dataset. The experimental results show improved performance of our clustering approach compared to baseline methods.
|
|
| 2. |
- Abu Khousa, Eman, et al.
(author)
-
Social network analysis to influence career development
- 2018
-
In: Journal of Ambient Intelligence and Humanized Computing. - : Springer. - 1868-5137 .- 1868-5145. ; 9:3, s. 601-616
-
Journal article (peer-reviewed)abstract
- Social network analysis techniques have shown a potential for influencing gradu-ates to meet industry needs. In this paper, we propose a social-web driven solutions to bridge formal education and industry needs. The proposed career development frame-work utilizes social network analytics, influence diffusion algorithms and persuasive technology models along three phases: (1) career readiness to measure and visualize the general cognitive dispositions required for a successful career in the 21st Century, (2) career prediction to persuade future graduates into a desired career path by clustering learners whose career prospects are deemed similar, into a community of practice; and (3) career development to drive growth within a social network structure where social network analytics and persuasive techniques are applied to incite the adoption of desired career behaviors. The process starts by discovering behavioral features to create a cognitive profile and diagnose individual deficiencies. Then, we develop a fuzzy clustering algorithm that predicts similar patterns with controlled constraint-violations to construct a social structure for collaborative cognitive attainment. This social framework facilitates the deployment of novel influence diffusion approaches, whereby we propose a reciprocal-weighted similarity function and a triadic clo-sure approach. In doing so, we investigate contemporary social network analytics to maximize influence diffusion across a synthesized social network. The outcome of this social computing approach leads to a persuasive model that supports behavioral changes and developments. The performance results obtained from both analytical and experi-mental evaluations validate our data-driven strategy for persuasive behavioral change.
|
|
| 3. |
- AbuKhousa, Eman, et al.
(author)
-
Envisioning an Architecture of Metaverse Intensive Learning Experience (MiLEx) : Career Readiness in the 21st Century and Collective Intelligence Development Scenario
- 2023
-
In: Future Internet. - : MDPI. - 1999-5903. ; 15:2
-
Journal article (peer-reviewed)abstract
- The metaverse presents a new opportunity to construct personalized learning paths and to promote practices that scale the development of future skills and collective intelligence. The attitudes, knowledge and skills that are necessary to face the challenges of the 21st century should be developed through iterative cycles of continuous learning, where learners are enabled to experience, reflect, and produce new ideas while participating in a collective creativity process. In this paper, we propose an architecture to develop a metaverse-intensive learning experience (MiLEx) platform with an illustrative scenario that reinforces the development of 21st century career practices and collective intelligence. The learning ecosystem of MiLEx integrates four key elements: (1) key players that define the main actors and their roles in the learning process; (2) a learning context that defines the learning space and the networks of expected interactions among human and non-human objects; (3) experiential learning instances that deliver education via a real-life–virtual merge; and (4) technology support for building practice communities online, developing experiential cycles and transforming knowledge between human and non-human objects within the community. The proposed MiLEx architecture incorporates sets of technological and data components to (1) discover/profile learners and design learner-centric, theoretically grounded and immersive learning experiences; (2) create elements and experiential learning scenarios; (3) analyze learner’s interactive and behavioral patterns; (4) support the emergence of collective intelligence; (5) assess learning outcomes and monitor the learner’s maturity process; and (6) evaluate experienced learning and recommend future experiences. We also present the MiLEx continuum as a cyclic flow of information to promote immersive learning. Finally, we discuss some open issues to increase the learning value and propose some future work suggestions to further shape the transformative potential of metaverse-based learning environments.
|
|
| 4. |
- Al Falahi, Kanna, et al.
(author)
-
Clustering Algorithms For Intelligent Web
- 2016
-
In: International Journal of Computational Complexity and Intelligent Algorithmslgorithms. - : InderScience Publishers. - 2048-4720. ; 1:1, s. 1-22
-
Journal article (peer-reviewed)abstract
- Detecting users and data in the web is an important issue as the web is changing and new information is created every day. In this paper we will discuss six different clustering algorithms that are related to the intelligent web. These algorithms will help us to identify groups of interest in the web, which is very necessary in or- der to perform certain actions on specific group such as targeted advertisement. The algorithms under consideration are: Single-Link algorithm, Average-Link algorithm, Minimum-Spanning-Tree Single-Link algorithm, K-means algorithm, ROCK algorithm and DBSCAN algorithm. These algorithms are categorized into three groups: Hierarchical, Partitional and Density-based algorithms. We will show how each algorithm works and discuss their advantages and disadvantages. We will compare these algorithms to each others and discuss their ability to handle social web data which are of large datasets and high dimensionality. Finally a case study related to using clustering in social networks will be discussed.
|
|
| 5. |
- Al Falahi, Kanna, et al.
(author)
-
Models of Influence in Online Social Networks
- 2014
-
In: International Journal of Intelligent Systems. - USA : John Wiley & Sons. - 0884-8173 .- 1098-111X. ; 2:29, s. 161-183
-
Journal article (peer-reviewed)abstract
- Online social networks gained their popularity from relationships users can build with each other. These social ties play an important role in asserting users’ behaviors in a social network. For example, a user might purchase a product that his friend recently bought. Such phenomenon is called social influence, which is used to study users’ behavior when the action of one user can affect the behavior of his neighbors in a social network. Social influence is increasingly investigated nowadays as it can help spreading messages widely, particularly in the context of marketing, to rapidly promote products and services based on social friends’ behavior in the network. This wide interest in social influence raises the need to develop models to evaluate the rate of social influence. In this paper, we discuss metrics used to measure influence probabilities. Then, we reveal means to maximize social influence by identifying and using the most influential users in a social network. Along with these contributions, we also survey existing social influence models, and classify them into an original categorization framework. Then, based on our proposed metrics, we show the results of an experimental evaluation to compare the influence power of some of the surveyed salient models used to maximize social influence.
|
|
| 6. |
- Al Falahi, Kanna, et al.
(author)
-
Social Networks and Recommendation Systems : A World of Current and Future Synergies
- 2012
-
In: Computational Social Network. - London : Springer London. - 9781447140481 - 9781447140474 ; , s. 445-465
-
Book chapter (peer-reviewed)abstract
- Recently, there has been a significant growth in the science of networks, as well as a big boom in social networking sites (SNS), which has arguably had a great impact on multiple aspects of everyday life. Since the beginnings of the World Wide Web, another fast-growing field has been that of recommender systems (RS), which has furthermore had a proven record of immediate financial importance, given that a well-targeted online recommendation often translates into an actual purchase. Although in their beginnings, both SNSs as well as RSs had largely separate paths as well as communities of researchers dealing with them, recently the almost immediate synergies arising from bringing the two together have started to become apparent in a number of real-world systems. However, this is just the beginning; multiple potentially beneficial mutual synergies remain to be explored. In this chapter, after introducing the two fields, we will provide a survey of their existing interaction, as well as a forward-looking view on their potential future.
|
|
| 7. |
- Atif, Yacine, 1967-, et al.
(author)
-
A Cyberphysical Learning Approach for Digital Smart Citizenship Competence Development
- 2017
-
In: WWW '17. - New York, New York, USA : ACM Digital Library. - 9781450349130 ; , s. 397-405
-
Conference paper (peer-reviewed)abstract
- Smart Cities have emerged as a global concept that argues for the effective exploitation of digital technologies to drive sustainable innovation and well-being for citizens. Despite the large investments being placed on Smart City infrastructure, however, there is still very scarce attention on the new learning approaches that will be needed for cultivating Digital Smart Citizenship competences, namely the competences which will be needed by the citizens and workforce of such cities for exploiting the digital technologies in creative and innovative ways for driving financial and societal sustainability. In this context, this paper introduces cyberphysical learning as an overarching model of cultivating Digital Smart Citizenship competences by exploiting the potential of Internet of Things technologies and social media, in order to create authentic blended and augmented learning experiences.
|
|
| 8. |
- Atif, Yacine, 1967-, et al.
(author)
-
A fuzzy logic approach to influence maximization in social networks
- 2020
-
In: Journal of Ambient Intelligence and Humanized Computing. - : Springer. - 1868-5137 .- 1868-5145. ; 11:6, s. 2435-2451
-
Journal article (peer-reviewed)abstract
- Within a community, social relationships are paramount to profile individuals’ conduct. For instance, an individual within a social network might be compelled to embrace a behaviour that his/her companion has recently adopted. Such social attitude is labelled social influence, which assesses the extent by which an individual’s social neighbourhood adopt that individual’s behaviour. We suggest an original approach to influence maximization using a fuzzy-logic based model, which combines influence-weights associated with historical logs of the social network users, and their favourable location in the network. Our approach uses a two-phases process to maximise influence diffusion. First, we harness the complexity of the problem by partitioning the network into significantly-enriched community-structures, which we then use as modules to locate the most influential nodes across the entire network. These key users are determined relatively to a fuzzy-logic based technique that identifies the most influential users, out of which the seed-set candidates to diffuse a behaviour or an innovation are extracted following the allocated budget for the influence campaign. This way to deal with influence propagation in social networks, is different from previous models, which do not compare structural and behavioural attributes among members of the network. The performance results show the validity of the proposed partitioning-approach of a social network into communities, and its contribution to “activate” a higher number of nodes overall. Our experimental study involves both empirical and real contemporary social-networks, whereby a smaller seed set of key users, is shown to scale influence to the high-end compared to some renowned techniques, which employ a larger seed set of key users and yet they influence less nodes in the social network.
|
|
| 9. |
- Atif, Yacine, 1967-, et al.
(author)
-
Building a smart campus to support ubiquitous learning
- 2014
-
In: Journal of Ambient Intelligence and Humanized Computing. - : Springer Science and Business Media LLC. - 1868-5137 .- 1868-5145. ; 6:2, s. 223-238
-
Journal article (peer-reviewed)abstract
- New technological advances in user mobility and context immersion are enabling novel adaptive and pervasive learning models in ambient environments. These advances allow physical learning spaces with embedded computing capabilities to provide an augmented self-aware learning experience. In this paper, we aim at developing a novel ubiquitous learning model within a pervasive smart campus environment. The goal of our research consists of identifying the steps towards building such an environment and the involved learning processes. We define a model of a smart campus, and advocate learning practices in the light of new paradigms such as context-awareness, ubiquitous learning, pervasive environment, resource virtualization, autonomic computing and adaptive learning. We reveal a comprehensive architecture that defines the various components and their inter-operations in a smart educational environment. The smart campus approach is presented as a composition of ambient learning spaces, which are environments where physical learning resources are augmented with digital and social services. We present a model of these spaces to harness future ubiquitous learning environments. One of the distinguished features of this model is the ability to unleash the instructional value of surrounding physical structures. Another one is the provision of a personalized learning agenda when moving across these ambient learning environments. To achieve these goals, we profile learners and augment physical campus structures to advocate context-aware learning processes. We suggest a social community platform for knowledge sharing which involves peer learners, domain experts as well as campus physical resources. Within this pervasive social scope, learners are continuously immersed in a pedagogically supported experiential learning loop as a persuasive approach to learning. A learning path, which responds to learners’ goals and qualifications, autonomously guides learners in achieving their objectives in the proposed smart campus. We evaluated our ubiquitous learning approach to assert the performance of these building blocks in the proposed smart campus model. The results show interesting tradeoffs and promising insights.
|
|
| 10. |
- Atif, Yacine, 1967-
(author)
-
Building Trust in E-Commerce
- 2002
-
In: IEEE Internet Computing. - USA : IEEE Computer Society. - 1089-7801 .- 1941-0131. ; 6:1, s. 18-24
-
Journal article (peer-reviewed)abstract
- A network of Internet-based intermediaries that guarantee delivery and payment in e-commerce could help bolster consumer and merchant confidence.
|
|
