When E-Learning Meets Big Data, Cognitive Computing, and Collaborative Environments

The internet of things & Big data analytics in eLearning brings tremendous challenges & opportunities to educational institutions & students. In recent trends, the growth of Pervasive computing, Social media, evolving IoT capabilities, technologies such as cloud computing, and big data and analytics are improving the core values of teaching and conducting research but also instilling a new digital culture and developing an IoT-centric society. The primary purpose of this paper is to provide an impact of IoT & Big data analytics in the area of E-learning and study on different E-learning approaches.

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A Hybrid-Algorithm for E-project Selection on Social Media

Journal of Information Technology and Digital World - September 2019 ◽

10.36548/jitdw.2020.2.005 ◽

2020 ◽

Vol 2 (2) ◽

pp. 116-122

Author(s):

Dr. Pasumponpandian A.

Keyword(s):

Social Media ◽

Big Data ◽

Hybrid Algorithm ◽

Optimal Algorithm ◽

Big Data Analytics ◽

Minimal Risk ◽

Cognitive Computing ◽

Development Environment ◽

Nsga Ii ◽

The Right

The integration of two of the biggest giants in the computing world has resulted in the development and advancement of new methodologies in data processing. Cognitive computing and big data analytics are integrated to give rise to advanced technologically sound algorithms like MOIWO and NSGA. There is an important role played by the E-projects portfolio selection (EPPS) issue in the web development environment that is handled with the help of a decision making algorithm based on big data. The EPPS problem tackles choosing the right projects for investment on the social media in order to achieve maximum return at minimal risk conditions. In order to address this issue and further optimize EPPS probe on social media, the proposed work focuses on building a hybrid algorithm known as NSGA-II-MOIWO. This algorithms makes use of the positive aspects of MOIWO algorithm and NSGA-II algorithm in order to develop an efficient one. The experimental results are recorded and analyzed in order to determine the most optimal algorithm based on the return and risk of investment. Based on the results, it is found that NSGA-II-MOIWO outperforms both MOIWO and NSGA, proving to be a better hybrid alternative.

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eSurgery - Digital Transformation in Surgery, Surgical Edu-cation and Training: Survey Analysis of the Status Quo in Germany. (Preprint)

10.2196/preprints.30289 ◽

2021 ◽

Author(s):

Juliane Kröplin ◽

Tobias Huber ◽

Christian Geis ◽

Benedikt Braun ◽

Tobias Fritz

Keyword(s):

Big Data ◽

Patient Care ◽

Data Protection ◽

Surgical Education ◽

Education And Training ◽

Simulator Training ◽

Special Focus ◽

Teaching Content ◽

E Learning ◽

And Training

UNSTRUCTURED Objective In surgery electronic healthcare systems offer numerous options to improve patient care. Aim of this study was to analyse the current status of digitalisation and its influence in surgery, with a special focus on surgical education and training. Methods An individually created questionnaire was used to analyse the subjective assessment of the digitalisation processes in clinical surgery. The online questionnaire consisted of 16 questions regarding the importance and the corresponding implementation of the teaching contents: big data, health apps, messenger apps, telemedicine, data protection/IT security, ethics, simulator training, economics and e-learning were included. The participation link was sent to members of the German Society of Surgery via the e-mail distribution list. Results In total, 119 surgeons (response rate = 19.8 %) took part in the survey. 18.5 % of them were trainees (TR). 81.5 % had already completed specialist training (SP). 66.4 % confirm a positive influence of digitalisation on the quality of patient care. The presence of a surgical robot was confirmed by 47.9 % of the participants. 22.0 % (n=26) of the participants confirm the possibil-ity of using virtual simulators. According to 79.0 % of the participants, the integration of digital technologies in surgical education for basic and advanced stage surgeons should be aimed for. Data protection (1.7) and e-Learning (1.7) were rated as the most important teaching content. The greatest discrepancy between importance and implementation was seen in the teaching content of big data (mean: 2.2 to 3.8). Conclusion The results of the survey reveal the particular importance of digitalisation content for surgery, surgical education and training. At the same time, the results underline the desire for in-creased integration of digital competence teaching. The data also show an overall more pro-gressive and optimistic perception of TR. In order to meet the challenges of the digital trans-formation, the implementation of suitable curricula, including virtual simulation-based training and blended-learning teaching concepts should be emphasized.

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BIG DATA AND THE IMPACT ON E-LEARNING PLATFORM: A CASE STUDY

EDULEARN16 Proceedings ◽

10.21125/edulearn.2016.2232 ◽

2016 ◽

Author(s):

Andrea Molinari ◽

Paolo Bouquet

Keyword(s):

Big Data ◽

Learning Platform ◽

E Learning ◽

The Impact

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LOOKING BEYOND E-LEARNING: THE IMPACT OF COGNITIVE COMPUTING

ICERI2018 Proceedings ◽

10.21125/iceri.2018.2249 ◽

2018 ◽

Author(s):

Mauro Coccoli ◽

Paolo Maresca ◽

Andrea Molinari ◽

Lidia Stanganelli

Keyword(s):

Cognitive Computing ◽

E Learning ◽

The Impact

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Big Data and Data Analytics Research

Web Services ◽

10.4018/978-1-5225-7501-6.ch112 ◽

2019 ◽

pp. 2161-2171

Author(s):

Miltiadis D. Lytras ◽

Vijay Raghavan ◽

Ernesto Damiani

Keyword(s):

Decision Making ◽

Big Data ◽

Data Analytics ◽

Business Models ◽

Internet Technology ◽

Cognitive Computing ◽

New Paradigm ◽

Web Science ◽

New Business ◽

Value Propositions

The Big Data and Data Analytics is a brand new paradigm, for the integration of Internet Technology in the human and machine context. For the first time in the history of the human mankind we are able to transforming raw data that are massively produced by humans and machines in to knowledge and wisdom capable of supporting smart decision making, innovative services, new business models, innovation, and entrepreneurship. For the Web Science research, this is a new methodological and technological spectrum of advanced methods, frameworks and functionalities never experienced in the past. At the same moment communities out of web science need to realize the potential of this new paradigm with the support of new sound business models and a critical shift in the perception of decision making. In this short visioning article, the authors are analyzing the main aspects of Big Data and Data Analytics Research and they provide their own metaphor for the next years. A number of research directions are outlined as well as a new roadmap towards the evolution of Big Data to Smart Decisions and Cognitive Computing. The authors do hope that the readers would like to react and to propose their own value propositions for the domain initiating a scientific dialogue beyond self-fulfilled expectations.

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Introduction to Use and Analysis of Big Data in E-Learning

Technology-Supported Teaching and Research Methods for Educators - Advances in Educational Technologies and Instructional Design ◽

10.4018/978-1-5225-5915-3.ch004 ◽

2019 ◽

pp. 75-87

Author(s):

Renuka Mahajan

Keyword(s):

Big Data ◽

Big Data Analysis ◽

Vital Role ◽

Interaction Data ◽

The World ◽

Learner Interaction ◽

E Learning ◽

One Year ◽

Tools And Techniques ◽

Data Analytic

In today's world everything is connected and is either consuming data or generating data. The world is changing so fast that even one-year-old data may not be useful, and hence, big data analysis plays a very vital role for higher management of any organizations for decision making. Data warehousing helps in gathering and storing verifiable information into a single entity. Data can be of different types like speech, text, etc. It can be structured or unstructured. Each data point is characterized in terms of volume or variety. This chapter gives an overview of how to utilize the learner interaction data from a particular website and how patterns can be captured by analyzing learner interaction data with big data analytic tools. Big data has risen in the field of education and has many challenges like storage, combining, analysis, and scalability of big data. It covers tools and techniques that can be used. The results from this study will have implications for new learners to the e-learning website, website designers, and academicians.

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