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James Edward Hill; Catherine Harris; Andrew Clegg – Research Synthesis Methods, 2024
Data extraction is a time-consuming and resource-intensive task in the systematic review process. Natural language processing (NLP) artificial intelligence (AI) techniques have the potential to automate data extraction saving time and resources, accelerating the review process, and enhancing the quality and reliability of extracted data. In this…
Descriptors: Artificial Intelligence, Search Engines, Data Collection, Natural Language Processing
Paul Marty – Journal of Education for Library and Information Science, 2022
This article presents an overview of the iterative design and evolution of an undergraduate course at Florida State University that offers students the opportunity to explore how society's increased reliance on information technology has changed the way in which we interact with each other and the world around us. Drawing upon course iterations…
Descriptors: Search Engines, Age Groups, Undergraduate Students, Educational Technology
Ayers, Meredith – Issues in Science and Technology Librarianship, 2020
Microsoft Academic (MA) claims to be an academic search engine that uses knowledge discovery, machine learning, and semantic inference to help users search for scholarly information in new and better ways. However, this is not the first iteration of Microsoft Academic. Since its debut in 2004 as Microsoft Academic Search (MAS) (Ortega &…
Descriptors: Search Engines, Computer Software Evaluation, Research, Information Retrieval
Klopfenstein, D. V.; Dampier, Will – Research Synthesis Methods, 2021
We read with considerable interest the study by Gusenbauer and Haddaway (Gusenbauer and Haddaway, 2020, Research Synthesis Methods, doi:10.1002/jrsm.1378) comparing the systematic search qualities of 28 search systems, including Google Scholar (GS) and PubMed. Google Scholar and PubMed are the two most popular free academic search tools in biology…
Descriptors: Search Engines, Search Strategies, Databases, Information Retrieval
Niels Kerssens; T. Philip Nichols; Luci Pangrazio – Learning, Media and Technology, 2024
The 'googlization' of education is emblematic of the growing power of private tech companies in schools across the globe, challenging education as a public good. While critical scholarship has started unpacking the ideological, pedagogical and economical logics underpinning Google's digital infrastructure in schools, we have little insight into…
Descriptors: Foreign Countries, Internet, Corporations, Access to Information
Mengliyev, Bakhtiyor; Shahabitdinova, Shohida; Khamroeva, Shahlo; Gulyamova, Shakhnoza; Botirova, Adiba – Journal of Language and Linguistic Studies, 2021
This article is dedicated to the issue of morphological analysis and synthesis of word forms in a linguistic analyzer, which is a significant feature of corpus linguistics. The article discourses in detail the morphological analysis, the creation of artificial language, grammar and analyzer, the general scheme of the analysis program that…
Descriptors: Morphology (Languages), Computational Linguistics, Computer Software, Artificial Languages
Krutka, Daniel G.; Smits, Ryan M.; Willhelm, Troy A. – TechTrends: Linking Research and Practice to Improve Learning, 2021
Google is a multinational technology company whose massive advertising profits have allowed them to expand into many areas, including education. While the company has increasingly faced public scrutiny, the use of Google software and hardware in schools has often resulted in little debate. In this paper, we conduct a technoethical audit of Google…
Descriptors: Search Engines, Educational Technology, Technology Uses in Education, Ethics
Mai, Jens-Erik – Journal of Education for Library and Information Science, 2019
This paper argues that medium for information access becomes central to library and information science. The author discusses the notion of medium, medium neutrality, and personalization and suggests that the dominating paradigm of providing fast, efficient, and neutral systems and services for retrieving information has sidetracked opportunities…
Descriptors: Access to Information, Information Retrieval, Search Engines, Library Education
El Guemmat, Kamal; Ouahabi, Sara – International Journal of Information and Communication Technology Education, 2018
The objective of this article is to analyze the searching and indexing techniques of educational search engines' implementation while treating future challenges. Educational search engines could greatly help in the effectiveness of e-learning if used correctly. However, these engines have several gaps which influence the performance of e-learning…
Descriptors: Indexing, Search Strategies, Educational Research, Search Engines
Ducar, Cynthia; Schocket, Deborah Houk – Foreign Language Annals, 2018
This article addresses a key pedagogical issue of our time: the widespread yet generally unwelcome presence of machine translation (MT) in the language classroom. Studies have repeatedly shown that L2 students consult the most widely used translation tool, Google Translate (GT), in spite of the fact that its use is frowned upon by second language…
Descriptors: Computational Linguistics, Intercultural Communication, Teaching Methods, Second Language Learning
Kristopher M. Lotier – College Composition and Communication, 2016
Around 1986, inventional researchers began to presuppose an externalist philosophy of mind, thereby ushering in the postprocess era. Ecological composition and posthumanism, now understood as postprocess inventional models, present direct pedagogical applications, allowing different objects (e.g., databases, search engines) to qualify as writing…
Descriptors: Writing (Composition), Writing Instruction, Writing Processes, Cognitive Processes
Zawawi, Boshra F.; Al Abri, Maimoona H.; Dabbagh, Nada – Journal of Educational Multimedia and Hypermedia, 2017
This paper aims to analyze the affordances of the digital technology (DT) Google+. The analysis process was informed by the theory of affordances. Accordingly, this paper highlighted the different types of affordances of Google+ features, i.e., functional, cognitive, physical, sensory, emotional, and social. In addition, the authors reviewed…
Descriptors: Affordances, Web Sites, Search Engines, Technology Uses in Education
Clarke, Theresa B.; Murphy, Jamie; Wetsch, Lyle R.; Boeck, Harold – Marketing Education Review, 2018
Instructors may find it difficult to stay abreast of the rapidly changing nature of search engine marketing (SEM) and to incorporate hands-on, practical classroom experiences. One solution is Google Ad Grants, a nonprofit edition of Google AdWords that provides up to $10,000 monthly in free advertising. A quasi-experiment revealed no differences…
Descriptors: Search Engines, Marketing, Experiential Learning, Nonprofit Organizations
Phelan, Nigel; Davy, Shane; O'Keeffe, Gerard W.; Barry, Denis S. – Anatomical Sciences Education, 2017
The role of e-learning platforms in anatomy education continues to expand as self-directed learning is promoted in higher education. Although a wide range of e-learning resources are available, determining student use of non-academic internet resources requires novel approaches. One such approach that may be useful is the Google Trends© web…
Descriptors: Anatomy, Electronic Learning, Higher Education, Internet
McEneaney, Elizabeth H. – Journal of Curriculum Studies, 2015
This article offers a critique of Michael Young's perspective on the Internet as it relates to the knowledge-driven curriculum he supports. I argue that the Internet is a site of both theoretical knowledge and everyday concepts which challenges the differentiation of knowledge that premises much of Young's writing. Google searches from the…
Descriptors: Internet, Curriculum Development, Knowledge Management, Online Searching