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1 – 3 of 3Muddesar Iqbal, Sohail Sarwar, Muhammad Safyan and Moustafa Nasralla
The purpose of this study is to present a systematic and comprehensive review of personalized, adaptive and semantic e-learning systems.
Abstract
Purpose
The purpose of this study is to present a systematic and comprehensive review of personalized, adaptive and semantic e-learning systems.
Design/methodology/approach
Preferred reporting items of systematic reviews and meta-analyses guidelines have been used for a thorough insight into associated aspects of e-learning that complement the e-learning pedagogies and processes. The aspects of e-learning systems have been reviewed comprehensively such as personalization and adaptivity, e-learning and semantics, learner profiling and learner categorization, which are handy in intelligent content recommendations for learners.
Findings
The adoption of semantic Web based technologies would complement the learner’s performance in terms of learning outcomes.
Research limitations/implications
The evaluation of the proposed framework depends upon the yearly batch of learners and recording is a cumbersome/tedious process.
Social implications
E-Learning systems may have diverse and positive impact on society including democratized learning and inclusivity regardless of socio-economic or geographic status.
Originality/value
A preliminary framework of an ontology-based e-learning system has been proposed at a modular level of granularity for implementation, along with evaluation metrics followed by a future roadmap.
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Keywords
Hung-Tai Tsou, Yu-Hsun Lin and Pui Yan Loo
Social live streaming services (SLSS) have infused gamification into interface design and feature applications. Firms adopt gamification mechanisms to win customer loyalty in the…
Abstract
Purpose
Social live streaming services (SLSS) have infused gamification into interface design and feature applications. Firms adopt gamification mechanisms to win customer loyalty in the live streaming and SLSS markets. Based on the mechanics-dynamics-aesthetics (MDA) framework and uses and gratifications 2.0 theory (UGT 2.0), this study aims to investigate the effects of game mechanics (mechanics) on enjoyment and user retention (aesthetics) through rewards and social interaction (dynamics) in the context of SLSS.
Design/methodology/approach
This study used an online survey via Google Forms, SurveyCake and social media platforms like Facebook, Instagram and Line to collect data from 232 SLSS users in Taiwan. Partial least squares structural equation modeling (PLS-SEM) was adopted to analyze the data.
Findings
The results validated the relationships between game mechanics and dynamic elements (rewards and social interaction) that triggered aesthetic elements (enjoyment feelings) among users. In addition, users experienced a sense of enjoyment that led to usage retention when using the gamified SLSS. Further, this study found enjoyment crucial for users to stay interactive with gamified services.
Originality/value
Driven by UGT 2.0, this study closed the gaps by integrating the MDA framework into the SLSS context and better understanding how game mechanics are connected to rewards and social interaction, leading to enjoyment and user retention when using SLSS. This study provides fresh insights into gamification-oriented SLSS practices. It offers significant theoretical and managerial implications and provides guidelines for SLSS platform operators on fostering user retention.
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Åsne Stige, Efpraxia D. Zamani, Patrick Mikalef and Yuzhen Zhu
The aim of this article is to map the use of AI in the user experience (UX) design process. Disrupting the UX process by introducing novel digital tools such as artificial…
Abstract
Purpose
The aim of this article is to map the use of AI in the user experience (UX) design process. Disrupting the UX process by introducing novel digital tools such as artificial intelligence (AI) has the potential to improve efficiency and accuracy, while creating more innovative and creative solutions. Thus, understanding how AI can be leveraged for UX has important research and practical implications.
Design/methodology/approach
This article builds on a systematic literature review approach and aims to understand how AI is used in UX design today, as well as uncover some prominent themes for future research. Through a process of selection and filtering, 46 research articles are analysed, with findings synthesized based on a user-centred design and development process.
Findings
The authors’ analysis shows how AI is leveraged in the UX design process at different key areas. Namely, these include understanding the context of use, uncovering user requirements, aiding solution design, and evaluating design, and for assisting development of solutions. The authors also highlight the ways in which AI is changing the UX design process through illustrative examples.
Originality/value
While there is increased interest in the use of AI in organizations, there is still limited work on how AI can be introduced into processes that depend heavily on human creativity and input. Thus, the authors show the ways in which AI can enhance such activities and assume tasks that have been typically performed by humans.
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