Research Trends and Features of Robotics Studies in Educational Technology and STEM Education: Data Mining on ERIC Sample [SCHOLARLY ARTICLE - Sakarya University Journal of Education, December 2022]

Title:

Research Trends and Features of Robotics Studies in Educational Technology and STEM Education: Data Mining on ERIC Sample 

Author:

Emre Çam

 

Published:

Sakarya University Journal of Education, 12(3), 15 December 2022

https://dergipark.org.tr/en/download/article-file/2704572

 

Abstract:

In this study, publications in ERIC about Robotics, Educational Technology in Robotics (ET-in-Robotics), and STEM in Robotics (STEM-in-Robotics) have been reached through data mining. The reached studies were analyzed in terms of their release year, titles, abstracts, and ERIC descriptions. In this process, it aimed to put forward its research trends and features. The analysis of the 1339 publications that were published between 01/01/1973 and 31/12/2021 and available in ERIC has been made by using several Python libraries. These analyses are presented in the form of tables and word clouds. The results showed that the number of publications available in ERIC was the highest between 2017 and 2021. Also, in the last five years, the number of publications available on Robotics in ERIC has gradually increased. In addition, the words "learning", "robotics", and "technology" are important for all three topics whereas the words “child”, "science", “programming” and "teacher" for ET-in-Robotics, and the words "school" and "engineering" for STEM-in-Robotics come to the fore. Moreover, the most frequently assigned descriptor by ERIC staff to these publications has been found to be "teaching methods". When evaluated in general, in the STEM-in-Robotics field, more specific topics were focused, and robotic activities are taken as a type of instructional technology while in the ET-in-Robotics field robotic activities were taken as a type of educational technology. As a result, a publication that will serve as a guide for new research in the field of robotics has been presented.

 

University of Innsbruck, Austria - Reading old handwriting with an AI platform [Tech Xplore, October 2022]

Title:

Reading old handwriting with an AI platform

 

Author:

Christian Flatz, University of Innsbruck

 

Published:

Tech Xplore, 11 October 2022

https://techxplore.com/news/2022-10-ai-platform.html

 

From the article:

Using artificial intelligence, computers can decipher handwritten texts and make them readable for everyone. The Transkribus platform, co-developed at the University of Innsbruck, Austria, makes this technology available to scholars and the general public. An ever-growing group of people are using Transkribus to research their family history. Recently, users from all over the world met in Innsbruck.

 

Note from blog owner:

The author of this article also mentions that "a recent study by the University of Edinburgh revealed that more than 400 scientific publications have now been produced with the help of Transkribus." 

ALSO SEE

Title:

Machine learning and big data are unlocking Europe's archives

By: 

Horizon Magazine, Fintan Burke, Horizon: The EU Research & Innovation Magazine

Published:

Tech Xplore, 11 December 2020

https://techxplore.com/news/2020-12-machine-big-europe-archives.html

Challenges to Use Machine Learning in Agricultural Big Data: A Systematic Literature Review [Scholarly Article - Agronomy, March 2022]

Title:

Challenges to Use Machine Learning in Agricultural Big Data: A Systematic Literature Review

 

Authors:

Ania Cravero1, Sebastian Pardo1, Samuel Sepúlveda1 & Lilia Muñoz2

 

1 Department of Computer Science and Informatics, Center for Software Engineering Studies, Universidad de La Frontera, Temuco 4780000, Chile 

 

2 Faculty of Computer Systems Engineering, Universidad Tecnológica de Panamá, Panama City 32401, Panama

 

Published:

Agronomy, 21 March 2022

https://www.mdpi.com/2073-4395/12/3/748

 

Abstract:

Agricultural Big Data is a set of technologies that allows responding to the challenges of the new data era. In conjunction with machine learning, farmers can use data to address different problems such as farmers' decision-making, crops, weeds, animal research, land, food availability and security, weather, and climate change. The purpose of this paper is to synthesize the evidence regarding the challenges involved in implementing machine learning in Agricultural Big Data. We conducted a Systematic Literature Review applying the PRISMA protocol. This review includes 30 papers, published from 2015 to 2020. We develop a framework that summarizes the main challenges encountered, the use of machine learning techniques, as well as the main technologies used. A major challenge is the design of Agricultural Big Data architectures, due to the need to modify the set of technologies adapting the machine learning techniques, as the volume of data increases.

Higher Education Policy Institute (HEPI) - Drowning in data? Is there a ‘tyranny of metrics’ in education?

Title:

Drowning in data? Is there a ‘tyranny of metrics’ in education? 

 

Author: 

Nick Hillman 

 

Published:

Higher Education Policy Institute, 9 February 2022 

https://www.hepi.ac.uk/2022/02/09/drowning-in-data-is-there-a-tyranny-of-metrics-in-education/

 

From this blog post: 

HEPI Director Nick Hillman:  

* considers the arguments for and against the use of big data in higher education;

* looks at the reasons behind the growing use of metrics; 

* and ends with a discussion on the increasing demands to contexualise metrics before using them for important decisions.

 

University of Melbourne - Big data reveals we're running out of time to save environment and ourselves (Phys.org, 24 April 2020)

Title:
Big data reveals we're running out of time to save environment and ourselves

By:
University of Melbourne

Published:
Phys.org, 24 April 2020

From the article:
"Lead author Dr. Rebecca Runting from the University of Melbourne's School of Geography says that while we currently have an unprecedented ability to generate, store, access and analyse data about the environment, these technological advances will not help the world unless they lead to action."

To read this article:
https://phys.org/news/2020-04-big-reveals-environment.html

To read the scholarly article:
Runting, R.K., Phinn, S., Xie, Z. et al. Opportunities for big data in conservation and sustainability. Nat Commun 11, 2003 (2020). https://doi.org/10.1038/s41467-020-15870-0

Brown University - Big data could yield big discoveries in archaeology, scholar says

Title:
Big data could yield big discoveries in archaeology, scholar says

By:
Brown University

Published:
Phys.org, 25 February 2020

From the article:
"Centuries of archaeological research on the Inca Empire has netted a veritable library of knowledge. But new digital and data-driven projects led by Brown University scholars are proving that there is much more to discover about pre-colonial life in the Andes."

To read this article:
https://phys.org/news/2020-02-big-yield-discoveries-archaeology-scholar.html