Dataset of Search Results Organized as Learning Paths Recommended by Experts to Support Search as Learning

Verónica Proaño-Ríos and Roberto González-Ibáñez
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Verónica Proaño-Ríos: Departamento de Ingeniería Informática, Universidad de Santiago de Chile, Avenida Ecuador #3659, Santiago 9170124, Chile
Roberto González-Ibáñez: Departamento de Ingeniería Informática, Universidad de Santiago de Chile, Avenida Ecuador #3659, Santiago 9170124, Chile

Data, 2020, vol. 5, issue 4, 1-11

Abstract: In this article, we introduce a dataset of curated learning paths (LPs) to support search as learning. LPs were obtained through an online survey delivered to experts in different domains. Data were then analyzed and described in terms of a set of variables. The resulting dataset comprised 83 LPs, each containing three web pages, for an overall collection consisting of 249 documents. The dataset is intended to provide information scientists, education researchers, and industry professionals, who provide information services in educational contexts, a valuable resource to (i) investigate patterns in the order of LPs, (ii) improve ranking models and/or re-ranking methods, (iii) explain the structure of the recommended LPs, and (iv) investigate alternative approaches to display search results based on the features of LPs.

Keywords: data mining; expert recommendations; learning object (LO); learning path (LP); search as learning (SAL); search engine results; Spanish dataset (search for similar items in EconPapers)
JEL-codes: C8 C80 C81 C82 C83 (search for similar items in EconPapers)
Date: 2020
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