IoT and Big Data Analytics in E-Learning

Попчев, Иван; Orozova, Daniela; Stoyanov, Stanimir

doi:10.1109/bdkcse48644.2019.9010666

Cited by 6 publications

(3 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…AI is also being injected into elearning systems to provide intelligent feedback to learners and to personalize the learning experience based on their preferences and performance [66]. As a further step towards individualized instruction and more effective evaluation, researchers are investigating how to use big data analytics and the IoT in online education [67].…”

Section: Overview Of the Iot And E-learning In Heismentioning

confidence: 99%

IoT Adoption Model for E-Learning in Higher Education Institutes: A Case Study in Saudi Arabia

Ali,

Madni,

Jahangeer

et al. 2023

Sustainability

View full text Add to dashboard Cite

The realm of the Internet of Things (IoT), while continually transforming as a novel paradigm in the nexus of technology and education, still contends with numerous obstacles that hinder its incorporation into higher education institutions’ (HEIs) e-learning platforms. Despite substantial strides in IoT utilization from industrialized nations—the United States, the United Kingdom, Japan, and China serving as prime exemplars—the scope of its implementation in developing countries, notably Saudi Arabia, Malaysia, Pakistan, and Bangladesh, lags behind. A significant gap exists in research centered on the trajectory of IoT integration within e-learning systems of economically disadvantaged nations. Specifically, this study centers on Saudi Arabia to illuminate the main factors catalyzing or encumbering IoT uptake within its HEIs’ e-learning sector. As a preliminary step, this research has embarked on an exhaustive dissection of prior studies to unearth critical variables implicated in the IoT adoption process. Subsequently, we employed an inferential methodology, amassing data from 384 respondents in Saudi Arabian HEIs. Our examination divulges that usability, accessibility, technical support, and individual proficiencies considerably contribute to the rate of IoT incorporation. Furthermore, our data infer that financial obstacles, self-efficacy, interactive capability, online surveillance, automated attendance tracking, training programs, network and data safeguarding measures, and relevant tools significantly influence IoT adoption. Contrarily, factors such as accessibility, internet quality, infrastructure preparedness, usability, privacy concerns, and faculty support appeared to have a negligible impact on the adoption rates within HEIs. This research culminates in offering concrete recommendations to bolster IoT integration within Saudi Arabian HEIs, presenting valuable insights for government entities, policy architects, and HEIs to address the hurdles associated with IoT implementation in the higher education sector.

show abstract

Section: Overview Of the Iot And E-learning In Heismentioning

confidence: 99%

IoT Adoption Model for E-Learning in Higher Education Institutes: A Case Study in Saudi Arabia

Ali,

Madni,

Jahangeer

et al. 2023

Sustainability

View full text Add to dashboard Cite

show abstract

“…The taxonomy is characterized by the basics of barriers, motivation, individual models, organizational models, and adoption of cloud computing at various levels in HLIs that help in further research in terms of more scientific and technological contexts. Furthermore, Popchev et al (2019) propose the conceptual model of E-Learning in terms of IoT adoption. For this purpose, Big Data analytics are identified based on the diagnostic, descriptive, predictive, and prescriptive manners.…”

Section: Related Workmentioning

confidence: 99%

Factors Influencing the Adoption of IoT for E-Learning in Higher Educational Institutes in Developing Countries

et al. 2022

View full text Add to dashboard Cite

The internet of things (IoT) is an emerging paradigm of educational applications and innovative technology in the current era. While capabilities are increasing day by day, there are still many limitations and challenges to utilizing these technologies within E-Learning in higher educational institutes (HEIs). The IoT is well-implemented in the United States of America (USA), United Kingdom (UK), Japan, and China but not in developing countries, including Saudi Arabia, Malaysia, Pakistan, Bangladesh, etc. Few studies have investigated the adoption of IoT in E-Learning within developing countries. Therefore, this research aims to examine the factors influencing IoT adoption for E-Learning to be utilized in HEIs. Further, an adoption model is proposed for IoT-based E-Learning in the contexts of developing countries and provides recommendations for enhancing the IoT adoption for E-Learning in HEIs. The IoT-based E-Learning model categorizes these influencing factors into four groups: individual, organizational, environmental, and technological. Influencing factors are compared along with a detailed description in order to determine which factors should be prioritized for efficient IoT-based E-Learning in HEIs. We identify the privacy (27%), infrastructure readiness (24%), financial constraints (24%), ease of use (20%), support of faculty (18%), interaction (15%), attitude (14%), and network and data security (14%), as the significant E-Learning influencing factors on IoT adoption in HEIs. These findings from the researcher's perspective will show that the national culture has a significant role in the individual, organizational, technological, and environmental behavior toward using new technology in developing countries.

show abstract

“…Thereafter these datasets can be analyzed using different tools [2,8,9]. Big data has been applied to problems in the field of education and e-learning [22,[24][25][26].…”

Section: Introductionmentioning

confidence: 99%

InterCriteria Analysis as a tool for analyzing Big Data datasets: Case study of 2021 national statistics of Bulgarian system of higher education

Bureva¹,

Petrov²,

Atanassova³

et al. 2022

NIFS

View full text Add to dashboard Cite

In the paper, the intuitionistic fuzzy sets based InterCriteria Analysis (ICA) and big data systems are applied to the 2021 dataset of the National Statistical Institute with respect to the Bulgarian system of higher education. The results are produced using the Big Data platform Hortonworks and the ICA software ICrAData. Discussion is presented on the discovered relationships regarding tendencies between enrolled and graduated students, and teaching staff.

show abstract

IoT and Big Data Analytics in E-Learning

Cited by 6 publications

References 9 publications

IoT Adoption Model for E-Learning in Higher Education Institutes: A Case Study in Saudi Arabia

IoT Adoption Model for E-Learning in Higher Education Institutes: A Case Study in Saudi Arabia

Factors Influencing the Adoption of IoT for E-Learning in Higher Educational Institutes in Developing Countries

InterCriteria Analysis as a tool for analyzing Big Data datasets: Case study of 2021 national statistics of Bulgarian system of higher education

Contact Info

Product

Resources

About