Potentiating Digital Educational Environments Through Data Analytics

2021 ◽  
pp. 40-47
Author(s):  
Flávio Lima Faria ◽  
Maitê Gil ◽  
Eva Oliveira ◽  
Cristina Sylla
Keyword(s):  
Data Analytics ◽  
Educational Environments

scholarly journals Teachers as Producers of Data Analytics: A Case Study of a Teacher-Focused Educational Data Science Program

2016 ◽  
Vol 3 (3) ◽  
pp. 193-214 ◽  
Author(s):  
Chase McCoy ◽  
Patrick Shih
Keyword(s):  
Data Analytics ◽  
Data Science ◽  
Administrative Support ◽  
Community Support ◽  
Practitioner Research ◽  
Structured Interviews ◽  
Educational Environments ◽  
Study Results ◽  
Research Domain

Educational data science (EDS) is an emerging, interdisciplinary research domain that seeks to improve educational assessment, teaching, and student learning through data analytics. Teachers have been portrayed in the EDS literature as users of pre-constructed data dashboards in educational technologies, with little consideration given to them as active producers of data analytics. This article presents the case study results of an EDS program at a large university in Midwestern U.S.A. in which faculty and instructors were provided with access to institutional data and data analytics technologies in order to explore questions related to their classroom and departmental environments. Semi-structured interviews of program participants were conducted to examine the participants’ experiences as practitioner researchers in EDS. The analysis showed that participants were motivated to participate to improve their learning and educational environments through data analytics, as opposed to developing a research agenda in EDS; that participants experienced a range of barriers related to data literacy; and that participant community support in addition to administrative support are vital to teacher-focused EDS programs. This study adds to a small but growing body of research in EDS and practitioner research that considers teachers as producers and not just consumers of data analytics.

Big Data Analytics: The Next Big Thing

2019 ◽  
Vol 54 (5) ◽  
pp. 20
Author(s):  
Dheeraj Kumar Pradhan
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics

Strategy in Discovery Mode - Wie Big Data & Analytics strategisches Denken verdrängen kann

2020 ◽  
Vol 49 (5) ◽  
pp. 11-17
Author(s):  
Thomas Wrona ◽  
Pauline Reinecke
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics

Big Data & Analytics (BDA) ist zu einer kaum hinterfragten Institution für Effizienz und Wettbewerbsvorteil von Unternehmen geworden. Zu viele prominente Beispiele, wie der Erfolg von Google oder Amazon, scheinen die Bedeutung zu bestätigen, die Daten und Algorithmen zur Erlangung von langfristigen Wettbewerbsvorteilen zukommt. Sowohl die Praxis als auch die Wissenschaft scheinen geradezu euphorisch auf den „Datenzug“ aufzuspringen. Wenn Risiken thematisiert werden, dann handelt es sich meist um ethische Fragen. Dabei wird häufig übersehen, dass die diskutierten Vorteile sich primär aus einer operativen Effizienzperspektive ergeben. Strategische Wirkungen werden allenfalls in Bezug auf Geschäftsmodellinnovationen diskutiert, deren tatsächlicher Innovationsgrad noch zu beurteilen ist. Im Folgenden soll gezeigt werden, dass durch BDA zwar Wettbewerbsvorteile erzeugt werden können, dass aber hiermit auch große strategische Risiken verbunden sind, die derzeit kaum beachtet werden.

Data Analytics on Graphs Part II: Signals on Graphs

2020 ◽  
Vol 13 (2-3) ◽  
pp. 158-331
Author(s):  
Ljubiša Stanković ◽  
Danilo Mandic ◽  
Miloš Daković ◽  
Miloš Brajović ◽  
Bruno Scalzo ◽  
...  
Keyword(s):  
Data Analytics

Support for Study: Online Educational Environments and the Rights to Education

2008 ◽  
Vol 12 (1) ◽  
Author(s):  
Lin Lin ◽  
Karen Swan
Keyword(s):  
Online Learning ◽  
Conceptual Framework ◽  
Collaborative Inquiry ◽  
Expert Knowledge ◽  
The Self ◽  
Open Educational Resource ◽  
Educational Resource ◽  
Online Learners ◽  
Educational Environments ◽  
Independent Inquiry

This paper uses an online learning conceptual framework to examine the “rights to education” that the current online educational environments could provide. The conceptual framework is composed of three inquiries or three spaces for inquiries, namely, independent inquiry, collaborative inquiry, and formative inquiry towards expert knowledge [42] that online learners pursue and undertake in the process of their learning. Our examinations reveal that most online open educational resource environments (OERs) can incorporate more Web2.0 or Web3.0 technologies so as to provide the self-directed learners, who are the main audience of OERs, with more opportunities to participate, collaborate, and co-create knowledge, and accordingly, to achieve their full rights to education.

Four Ways Technology Has Negatively Changed Education

2019 ◽  
Vol 9 (4) ◽  
pp. 10-20
Author(s):  
Khadija Alhumaid
Keyword(s):  
Social Media ◽  
Social Interactions ◽  
Classroom Technology ◽  
Relevant Research ◽  
Reading And Writing ◽  
Internet Connection ◽  
Educational Environments ◽  
Technological Tools ◽  
Teachers And Students

Abstract Our experience with technology is a bitter-sweet one. We relish its presence in our lives, but we dread the effect it may have on our manners, attitudes and social interactions. We open the gates of our schools to all types of technological tools, yet we fear it may badly impact our students’ performance. This article investigates the ways through which classroom technology such as iPad, Internet connection, laptops and social media, impacts negatively on education. Relevant research has proven that technology could change education negatively through four paths: deteriorating students’ competences of reading and writing, dehumanizing educational environments, distorting social interactions between teachers and students and isolating individuals when using technology.

Summary of the SciTech 2020 Technical Panel on In Situ/In Transit Computational Environments for Visualization and Data Analytics

2021 ◽  
Author(s):  
Earl P. Duque ◽  
Steve M. Legensky ◽  
Brad J. Whitlock ◽  
David H. Rogers ◽  
Andrew C. Bauer ◽  
...  
Keyword(s):  
Data Analytics ◽  
In Transit

Data Analytics to Help Improve Hydraulic Fracture Geometry Prediction Using Support Vector Regression: Case Study

2020 ◽  
Author(s):  
Avinash Wesley ◽  
Bharat Mantha ◽  
Ajay Rajeev ◽  
Aimee Taylor ◽  
Mohit Dholi ◽  
...  
Keyword(s):  
Support Vector Regression ◽  
Hydraulic Fracture ◽  
Data Analytics ◽  
Support Vector ◽  
Fracture Geometry
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