Abstract

The web is one of the primary sources of information for finding learning oriented documents. In addition, the main suitable way to find information and documents on the Internet is by using search engines. Search engines are constantly improving in terms of selection algorithms and in terms of the Human Machine interface (HMI). Also, these search engines are the basis of a new field of research called Search-As-Learning. The Search-As-Learning explores information search environments to enhance learning during user search tasks. This work focuses on our view of the state of the art in the field of Search Engines in learning context and Search-As-Learning, stressing on the most recent research. We conclude by highlighting the current shortcomings on improvement of the learning aspect within search engines, and present next work which will be the association of a layer above the traditional search engines to promote the appropriation of content during search task for a learning context

Highlights

  • Search engines are the most popular way to find information today

  • Vakkari et al [74] found that students’ level of knowledge about their subject could predict the characteristics of search queries, in the sense that students who know less about the subject are likely to use fewer search terms more vague in their queries

  • We provide a state of the art on search engine in a learning context

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Summary

Introduction

Search engines are the most popular way to find information today. Nowadays, searching for documents via the Internet is an essential practice for Internet users, for teachers and learners. In this momentum, search engines have evolved into a refined search and sophisticated display of search results [2]. Researches on studying the layout of search results pages are ongoing. Results on this have shown that the layout of the results influences user selection [4]. From the year 2007, new results have shown that the representation in enriched snippet [6], [7] on the result page was essential for informational queries [6], [8]. In addition to traditional snippets, search engines are full of rich snippets [9], for example: home pages, events, products, job offers, Images, Tweets, Advertising, Videos, Addresses, Maps, News, Knowledge Graph

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