The emerging Web 2.0 applications have allowed new ways of characterizing digital educational
resources, which moves from the expert-based descriptions relying on formal classification systems such
as the IEEE Learning Object Metadata (LOM) to a less formal user-based tagging. This alternative way of
characterizing digital educational resources is commonly referred to as social tagging, whereas the col-
lection of tags created by the different users individually is referred to as folksonomy. As a result, a num-
ber of studies have been reported in the field of Technology-enhanced Learning (TeL) which provide
evidence that social tagging has the potential to enlarge metadata descriptions, as well as the formal
structured vocabularies with additional terms derived by the resulted folksonomy but more in depth
studies are needed regarding this enlargement process. Thus, one issue to investigate further is the pos-
sible influence of users’ tagging motivation to the resulted enlarged metadata descriptions. In this paper
we aim to investigate this issue by first proposing a methodology that aims to evaluate whether users’
tagging motivation can influence (a) the enlargement of educational resources possible descriptions com-
pared to the anticipated creators’ descriptions and (b) the resulted folksonomy compared with formal
structured vocabularies used by the creators of the educational resources and then, apply it to an existing
LOR with more than 3,000 science education resources, 434 taggers and 14,707 social tags. Our experi-
ments provided evidence that taggers with a specific type of tagging motivation can produce tags that
are significantly different from formal metadata generated by the creators of the educational resources.
%0 Journal Article
%1 Zervas2014
%A Zervas, Panagiotis
%A Sampson, Demetrios
%D 2014
%J Computers in Human Behavior
%K categorizer describer enlargement folksonomy information_access learning_object_repository social_tagging tag_motivation tag_quality
%P 292-300
%T The effect of users' tagging motivation on the enlargement of digital educational resources metadata
%V 32
%X The emerging Web 2.0 applications have allowed new ways of characterizing digital educational
resources, which moves from the expert-based descriptions relying on formal classification systems such
as the IEEE Learning Object Metadata (LOM) to a less formal user-based tagging. This alternative way of
characterizing digital educational resources is commonly referred to as social tagging, whereas the col-
lection of tags created by the different users individually is referred to as folksonomy. As a result, a num-
ber of studies have been reported in the field of Technology-enhanced Learning (TeL) which provide
evidence that social tagging has the potential to enlarge metadata descriptions, as well as the formal
structured vocabularies with additional terms derived by the resulted folksonomy but more in depth
studies are needed regarding this enlargement process. Thus, one issue to investigate further is the pos-
sible influence of users’ tagging motivation to the resulted enlarged metadata descriptions. In this paper
we aim to investigate this issue by first proposing a methodology that aims to evaluate whether users’
tagging motivation can influence (a) the enlargement of educational resources possible descriptions com-
pared to the anticipated creators’ descriptions and (b) the resulted folksonomy compared with formal
structured vocabularies used by the creators of the educational resources and then, apply it to an existing
LOR with more than 3,000 science education resources, 434 taggers and 14,707 social tags. Our experi-
ments provided evidence that taggers with a specific type of tagging motivation can produce tags that
are significantly different from formal metadata generated by the creators of the educational resources.
@article{Zervas2014,
abstract = {The emerging Web 2.0 applications have allowed new ways of characterizing digital educational
resources, which moves from the expert-based descriptions relying on formal classification systems such
as the IEEE Learning Object Metadata (LOM) to a less formal user-based tagging. This alternative way of
characterizing digital educational resources is commonly referred to as social tagging, whereas the col-
lection of tags created by the different users individually is referred to as folksonomy. As a result, a num-
ber of studies have been reported in the field of Technology-enhanced Learning (TeL) which provide
evidence that social tagging has the potential to enlarge metadata descriptions, as well as the formal
structured vocabularies with additional terms derived by the resulted folksonomy but more in depth
studies are needed regarding this enlargement process. Thus, one issue to investigate further is the pos-
sible influence of users’ tagging motivation to the resulted enlarged metadata descriptions. In this paper
we aim to investigate this issue by first proposing a methodology that aims to evaluate whether users’
tagging motivation can influence (a) the enlargement of educational resources possible descriptions com-
pared to the anticipated creators’ descriptions and (b) the resulted folksonomy compared with formal
structured vocabularies used by the creators of the educational resources and then, apply it to an existing
LOR with more than 3,000 science education resources, 434 taggers and 14,707 social tags. Our experi-
ments provided evidence that taggers with a specific type of tagging motivation can produce tags that
are significantly different from formal metadata generated by the creators of the educational resources.},
added-at = {2017-04-12T21:00:00.000+0200},
author = {Zervas, Panagiotis and Sampson, Demetrios},
biburl = {https://www.bibsonomy.org/bibtex/246ad01b4ab7c1b805fe02184f878ecfd/charcharbinx},
interhash = {ba6023625278712fb18d7205ea1fdf8f},
intrahash = {46ad01b4ab7c1b805fe02184f878ecfd},
journal = {Computers in Human Behavior},
keywords = {categorizer describer enlargement folksonomy information_access learning_object_repository social_tagging tag_motivation tag_quality},
pages = {292-300},
timestamp = {2017-04-13T01:57:25.000+0200},
title = {The effect of users' tagging motivation on the enlargement of digital educational resources metadata},
volume = 32,
year = 2014
}