scholarly journals Review of smart learning: Patterns and trends in research and practice

2021 ◽  
Vol 37 (2) ◽  
pp. 189-204
Author(s):  
Kam Cheong Li ◽  
Billy Tak-Ming Wong
Keyword(s):  
Learning Environments ◽  
Learning Technologies ◽  
Comprehensive Overview ◽  
Research Issues ◽  
Research And Practice ◽  
Smart Learning ◽  
Depth Analysis ◽  
Views And Perceptions ◽  
Effective Use ◽  
Future Work

This article presents a review of the literature on smart learning in order to provide a comprehensive overview of its latest developments in research and practice. The review covered 90 studies published from 2010 to 2019, which were collected from three publication databases, namely Web of Science, Scopus and ProQuest. They were analysed for the patterns and trends in terms of publication years, sources of publication, countries or regions of publication, research purposes, research methods, educational levels of the studies, application domains, research issues, research participants, learning devices or tools, learning environments and learning features. Overall, the findings show that increasing global attention was given to smart learning from diverse disciplines and contexts of application. The results also reveal the areas which should be addressed in future work: development of pedagogies which make effective use of smart learning technologies in different learning environments; examination of smart learning to cope with learners’ needs in informal contexts; in-depth analysis of how smart learning could be tailored to fit the characteristics of various application domains; and investigation of the views and perceptions of teachers on smart learning technologies, their readiness to use these technologies and their challenges and needs for support.

scholarly journals Scientific production and thematic breakthroughs in smart learning environments: a bibliometric analysis

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Friday Joseph Agbo ◽  
Solomon Sunday Oyelere ◽  
Jarkko Suhonen ◽  
Markku Tukiainen
Keyword(s):  
Learning Environments ◽  
Bibliometric Analysis ◽  
Adaptive Learning ◽  
The United States ◽  
Scientific Production ◽  
Comprehensive Overview ◽  
Scientific Publications ◽  
Smart Learning Environment ◽  
Smart Learning ◽  
Smart Learning Environments

AbstractThis study examines the research landscape of smart learning environments by conducting a comprehensive bibliometric analysis of the field over the years. The study focused on the research trends, scholar’s productivity, and thematic focus of scientific publications in the field of smart learning environments. A total of 1081 data consisting of peer-reviewed articles were retrieved from the Scopus database. A bibliometric approach was applied to analyse the data for a comprehensive overview of the trend, thematic focus, and scientific production in the field of smart learning environments. The result from this bibliometric analysis indicates that the first paper on smart learning environments was published in 2002; implying the beginning of the field. Among other sources, “Computers & Education,” “Smart Learning Environments,” and “Computers in Human Behaviour” are the most relevant outlets publishing articles associated with smart learning environments. The work of Kinshuk et al., published in 2016, stands out as the most cited work among the analysed documents. The United States has the highest number of scientific productions and remained the most relevant country in the smart learning environment field. Besides, the results also showed names of prolific scholars and most relevant institutions in the field. Keywords such as “learning analytics,” “adaptive learning,” “personalized learning,” “blockchain,” and “deep learning” remain the trending keywords. Furthermore, thematic analysis shows that “digital storytelling” and its associated components such as “virtual reality,” “critical thinking,” and “serious games” are the emerging themes of the smart learning environments but need to be further developed to establish more ties with “smart learning”. The study provides useful contribution to the field by clearly presenting a comprehensive overview and research hotspots, thematic focus, and future direction of the field. These findings can guide scholars, especially the young ones in field of smart learning environments in defining their research focus and what aspect of smart leaning can be explored.

scholarly journals Past, present, and future of smart learning: a topic-based bibliometric analysis

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Xieling Chen ◽  
Di Zou ◽  
Haoran Xie ◽  
Fu Lee Wang
Keyword(s):  
Cloud Computing ◽  
Blended Learning ◽  
Information And Communication Technologies ◽  
Content Management ◽  
Research Field ◽  
Smart Devices ◽  
Major Research ◽  
Research Issues ◽  
Course Content ◽  
Smart Learning

AbstractInnovative information and communication technologies have reformed higher education from the traditional way to smart learning. Smart learning applies technological and social developments and facilitates effective personalized learning with innovative technologies, especially smart devices and online technologies. Smart learning has attracted increasing research interest from the academia. This study aims to comprehensively review the research field of smart learning by conducting a topic modeling analysis of 555 smart learning publications collected from the Scopus database. In particular, it seeks answers to (1) what the major research topics concerning smart learning were, and (2) how these topics evolved. Results demonstrate several major research issues, for example, Interactive and multimedia learning, STEM (science, technology, engineering, and mathematics) education, Attendance and attention recognition, Blended learning for smart learning, and Affective and biometric computing. Furthermore, several emerging topics were identified, for example, Smart learning analytics, Software engineering for e-learning systems, IoT (Internet of things) and cloud computing, and STEM education. Additionally, potential inter-topic directions were highlighted, for instance, Attendance and attention recognition and IoT and cloud computing, Semantics and ontology and Mobile learning, Feedback and assessment and MOOCs (massive open online courses) and course content management, as well as Blended learning for smart learning and Ecosystem and ambient intelligence.

scholarly journals State-of-the-Art Software-Based Remote Attestation: Opportunities and Open Issues for Internet of Things

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1598
Author(s):  
Sigurd Frej Joel Jørgensen Ankergård ◽  
Edlira Dushku ◽  
Nicola Dragoni
Keyword(s):  
Internet Of Things ◽  
Smart Cities ◽  
Cyber Attacks ◽  
Resource Constrained ◽  
Remote Attestation ◽  
Comprehensive Overview ◽  
Research Issues ◽  
Advantages And Disadvantages ◽  
Iot Devices ◽  
Specialized Hardware

The Internet of Things (IoT) ecosystem comprises billions of heterogeneous Internet-connected devices which are revolutionizing many domains, such as healthcare, transportation, smart cities, to mention only a few. Along with the unprecedented new opportunities, the IoT revolution is creating an enormous attack surface for potential sophisticated cyber attacks. In this context, Remote Attestation (RA) has gained wide interest as an important security technique to remotely detect adversarial presence and assure the legitimate state of an IoT device. While many RA approaches proposed in the literature make different assumptions regarding the architecture of IoT devices and adversary capabilities, most typical RA schemes rely on minimal Root of Trust by leveraging hardware that guarantees code and memory isolation. However, the presence of a specialized hardware is not always a realistic assumption, for instance, in the context of legacy IoT devices and resource-constrained IoT devices. In this paper, we survey and analyze existing software-based RA schemes (i.e., RA schemes not relying on specialized hardware components) through the lens of IoT. In particular, we provide a comprehensive overview of their design characteristics and security capabilities, analyzing their advantages and disadvantages. Finally, we discuss the opportunities that these RA schemes bring in attesting legacy and resource-constrained IoT devices, along with open research issues.

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