On reconstructing and analyzing personal learning environments of scientific artifacts

Abstract

Reflecting one’s scientific publications, it is observable that certain papers perform better than others, i.e. having more impact on scientific communities and being cited more often. In this paper we try to examine the circumstances of successful and average publications by reconstructing the personal learning environments (PLEs) which have led to them. Precisely we harvest the authors, the literature used, the communities addressed, and the publications and researchers citing a paper, overall leading to interesting data-sets for technology-enhanced learning (TEL) and allowing an in-depth exploration according to interesting research questions. In order to show the usefulness of our data gathering approach, we examine if important papers in a scientific community are characterized by a high degree centrality in its citation network and if older publications with a similar impact are cited more often than recently published papers.