Sequencing Wikipedia Pages: An On-the-fly Approach to Course
Building
Fabio Gasparetti, Carla Limongelli, Alessandra Milita, Filippo Sciarrone and Andrea Tarantini
Department of Engineering, Roma Tre University, Via della Vasca Navale 79, Rome, Italy
Keywords:
E-learning, Sequencing, Wikipedia.
Abstract:
With its 5, 006, 202 articles, 49 millions of registered people and on average 800 new articles per day,
Wikipedia provides a knowledge base for teachers and instructional designers to build didactic materials.
As a matter of fact, teachers often consult this encyclopaedia to arrange, integrate or enrich their courses.
Moreover, with the exponential growth of the Internet, didactic materials are freely available and usable by
teachers, instructional designers and students from Learning Objects Repositories such as Mertlot or Ariadne
and others. On the other hand, designing and delivering a new course is a crucial task for teachers, who have
to face two main problems: building or retrieving and sequencing learning materials. Retrieving or building
learning materials requires a great effort and is time-consuming, while sequencing requires an accurate didac-
tic project. In this paper we present a sequencing engine of learning materials, embedded in the Wiki Course
Builder system, a system capable of retrieving and sequencing Wikipedia web pages, taking into account both
the teacher model based on the Grasha teaching styles and on a social didactic approach. The main goal is
to support teachers building on-the-fly courses, i.e., building courses quickly, with a few clicks of the mouse.
An important feature of the system is represented by its ability to allow teachers to interact with the recom-
mended learning path through a graph-based interface where they can directly modify the proposed learning
path, adding or deleting Wikipedia pages. A first questionnaire has been submitted to a sample of teachers
with encouraging results.
1 INTRODUCTION
Nowadays, the Internet can be considered a big repos-
itory of didactic materials, strengthening the lifelong
learning era. Wikipedia
1
with its 5, 006, 202 articles,
49 millions of registered people and on average 800
new articles per day has become one of the most vis-
ited didactic repositories, due to its simplicity of use
and to its knowledge base, freely put on line by a
huge and free community of experts such as teachers,
instructional designers, scientists, and so on. Also,
most people use Wikipedia as a readily available di-
dactic material repository, quick and simple to con-
sult (it does not require a registration process). On
the other hand, if the use of Wikipedia in Education is
still very controversial and Wikipedia contents are not
always considered scientific contributions to be ac-
cepted in school, some learning experiences state that
about 87%,
2
use the online Wikipedia Encyclopedia
1
www.wikipedia.org
2
www.pewinternet.org/2013/02/28/how-teachers-are-
using-technology-at-home-and-in-their-classrooms/
in their didactic activities. Furthermore, the reliabil-
ity of Wikipedia, primarily of the English-language
edition, has been also assessed: an early study in the
journal Nature said that in 2005, Wikipedia’s scien-
tific articles came close to the level of accuracy of the
Encyclopedia Britannica.
In this paper, we propose a system, called Wiki
Course Builder, (WCB) that helps teachers to retrieve
and sequence Wikipedia HTML pages taking into ac-
count both the model of the particular teacher that
launched the query and the hypertext structure of the
Wikipedia pages. The WCB system was first intro-
duced in a previous work (Gasparetti et al., 2015c),
mainly focussing on the retrieving capabilities of rel-
evant Wikipedia pages, while here we address the
sequencing engine module. This repository forms
a huge semantic graph of relevant contents and we
chose it as the system content source for its popular-
ity among students, instructional designers and teach-
ers. Moreover, people regularly use it as the starting
point for knowledge building and for identifying gen-
eral didactic goals, especially in a lifelong learning
Gasparetti, F., Limongelli, C., Milita, A., Sciarrone, F. and Tarantini, A.
Sequencing Wikipedia Pages: An On-the-fly Approach to Course Building.
In Proceedings of the 8th International Conference on Computer Supported Education (CSEDU 2016) - Volume 1, pages 397-404
ISBN: 978-989-758-179-3
Copyright
c
2016 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved
397
context. In our system, through a suitable GUI, the
user can input one or more keywords concerning the
topic he/she is working on. Subsequently, the sys-
tem analyzes the most relevant Wikipedia pages, re-
turned by the embedded search engine, together with
a proposal of a first sequencing of them. Both the
retrieving and sequencing engines are based on the
Grasha Teaching Styles Model (Grasha, 1996), a sim-
ple teaching model based on five dimensions of teach-
ing. Each teacher registered into the WCB system
is firstly required to take a simple standard question-
naire, the Grasha-Riechmann Teaching Style Survey,
available at http://longleaf.net/teachingstyle.html and
directly linked from the WCB system, receiving in
output her teacher model. Besides, in the retrieving
process, the relevance of a Wikipedia page is related
to the set of the teaching styles tags associated to it: a
Wikipedia page used by a teacher is tagged with her
model (five dimensions). Subsequently, the sequenc-
ing is proposed by the system, basing on the links
among the retrieved pages, on the Grasha teaching
styles associated to each Wikipedia page already used
by the community and on the model of the teacher
that is building the course. In fact, each time a teacher
inserts a retrieved document into her course, the doc-
ument itself is tagged with her teaching styles, rep-
resented by an array of five real numbers, represent-
ing the Grasha model. As time goes by, this form of
knowledge is acquired and exploited so that the repos-
itory content is automatically filtered. In fact, each
Wikipedia page tagged by different users is weighed
with the average of all the five dimensions of all the
teachers that used it in a course. The well-known cold
start problem of collaborative approaches is partially
overcome by exploiting the first visits of the resources
as soon as they become available. This is a straight-
forward and lightweight approach, well suited for a
Community of Practice (CoP) (Wenger, 1998), where
multiple users access and filter Wikipedia pages, with
the common goal to quickly build a new course. The
remainder of the article is structured as follows. Sec-
tion 2 draws some important related work. Section 3
shows the teacher model the sequence engine is built
on. Section 4 shows the system, i.e., the WBC system
while Section 5 focuses on the sequencing engine. In
Section 6 a first evaluation of the system is presented.
Finally in Section 7 some conclusions are drawn.
2 RELATED WORK
Our proposal aims to sequence Wikipedia web pages
basing on the teacher model, as defined by Grasha in
(Grasha, 1996). So, Wikipedia, Grasha model and se-
quencing techniques represent the key concepts that
set up our system.
To our knowledge, there is not much literature
that considers the possibility to retrieve and sequence
Wikipedia pages to build a new course, while there is
some literature concerning the retrieval and sequenc-
ing of didactic material on the basis of the Grasha
teacher model. The use of the Grasha model can be
found in (Limongelli et al., 2015; Limongelli et al.,
2016), where the teacher model is represented by a
teaching experience and a dynamic semantic network
composed by the retrieved and used learning materi-
als by a community of teachers. In (Limongelli et al.,
2013b) a clustering of teachers is proposed for a com-
munity of teachers.
One of the first works which have investigated
Wikipedia as a learning support is (Forte and Bruck-
man, 2006). In particular, this work addresses the
following research question: Publishing on Wikipedia
encourages students towards a collaborative and in-
volving learning?. Then, (Parker and Chao, 2007)
highlights the didactic potential of wikis that actively
involve learners in their own construction of knowl-
edge, on the basis of a collaborative approach. Gas-
paretti et al. (Gasparetti et al., 2015b; Gasparetti
et al., 2015a) propose an early attempt to exploit the
Wikipedia content in order to determine prerequisite
relationships among learning objects.
However, sequencing methods and techniques
have been widely investigated. Generally, course Se-
quencing techniques can be classified in the following
two main categories (Limongelli et al., 2009; Sciar-
rone, 2013):
Sequencing that plans the entire learning path at
the beginning of a course, modifying it if the
study should not succeed as it should; e.g., Dy-
namic Courseware Generation (Brusilovsky and
Vassileva, 2003), the work of Baldoni et al. (Bal-
doni et al., 2007)(Baldoni et al., 2004), and the
IWT system (Sangineto et al., 2008; Limongelli
et al., 2013a; Sterbini and Temperini, 2013);
Sequencing obtained in an implicit way, step by
step, through adaptive navigation support tech-
niques, such as adaptive link annotation and di-
rect guidance (Brusilowsky, 2001; De Bra et al.,
2006; Limongelli et al., 2012a; Limongelli et al.,
2012b).
All the aforesaid proposals take into account the stu-
dent model required to build an adaptive sequencing
engine. Our system does not take into account the
student model but proposes the learning path on the
basis of the teacher model only. Another important
characteristic of our system is the use of Wikipedia as
the source of didactic material. Wikipedia has been
CSEDU 2016 - 8th International Conference on Computer Supported Education
398
used as a didactic source in many attempts to extract
useful information about the relevance of its contents.
In particular, in (Milne and Witten, 2013) an inter-
esting toolkit is presented to manage the Wikipedia
contents by a semantic point of view. In (Strube
and Ponzetto, 2006) a comparison between Wikipedia
and WordNet is presented in the WikiRelate! sys-
tem, to find semantic relationships among terms. In
(Gabrilovich and Markovitch, 2009) a Wikipedia-
based semantic interpretation for natural language
processing is presented. A novel method, called Ex-
plicit Semantic Analysis, for fine-grained semantic
interpretation of unrestricted natural language texts,
is presented. This method represents meaning in
a high-dimensional space of concepts derived from
Wikipedia, representing the meaning of any text in
terms of Wikipedia-based concepts. Another work
worth of mention is that of Turchi et al. (Turchi
et al., 2015) where the MediaWiki search engine,
made available by Wikimedia Foundation to search
contents among Wikipedia web pages, is used to test
a ranking algorithm based on Swarm Intelligence.
In conclusion, the characteristics of our approach
to the sequencing problem merges two research fields,
the use of Wikipedia and the use of a teacher model.
Both approaches have been used separately and in dif-
ferent contexts so far, while our proposal uses them
synergistically.
3 THE TEACHER MODEL
The teacher model is a crucial element of our proposal
because the sequencing engine is based on it and acts
accordingly. The model building process starts with
the Login module, by which the user can register and
join the community of teachers. A database of users
is built and managed by this module. When the user
registers into the system, she is required to fill in a
form with some personal data. It is in this step that the
user is required to take the Grasha-Riechmann Teach-
ing Style Survey
3
. It consists of a set of 40 5-points
Likert-scale questions, such as: Sharing my knowl-
edge and expertise with students is very important to
me and I give students negative feedback when their
performance is unsatisfactory. The questions aim at
modeling the teacher by means of the following ve
dimensions:
Expert: the teacher has the knowledge and the ex-
perience that students need;
Formal authority: the teacher maintains her/his
institutional role;
3
available at: http://longleaf.net/teachingstyle.html
Personal model: the teacher bases her/his teach-
ing on personal examples and establishes a model
for thinking and acting;
Facilitator: the teacher emphasizes personal in-
teractions between students and teacher;
Delegator: the teacher develops the students abil-
ity so that they can act autonomously.
where each dimension is measured by a real number
d [1, 5]. In this way, when the user registers into
the system, she is modelled by the set of the aforesaid
ve dimensions. Subsequently, this data will be used
by the search engine. Fig. 1 shows an example of a
teacher model as computed by the Grasha-Riechmann
survey.
Figure 1: An example of teacher model: Expert=2.875,
Formalauthorithy=3.625, Personalmodel=2.875, Facilita-
tor=3.0, Delegator=1.625.
4 THE SYSTEM
In this Section, we show the general architecture of
the system. The WBC system acts as a recommender
system supporting teachers in building new courses,
taking contents from Wikipedia, through a very sim-
ple and, above all, fast process. The teacher has the
possibility to change, discard or review the recom-
mended web pages, changing the proposed learning
path as well.
4.1 The Architecture
The system is composed of some general functional
modules (Gasparetti et al., 2015c), as shown in Fig. 2.
Here we focus on the following subsets of modules
4
:
The Login Manager Module. This module reg-
isters new users allowing them to enter into the
system. Subsequently, it proposes the Grasha-
Reichmann Survey by means the teachers can
build their own teaching model, as shown in Sec-
tion 3. Each teaching model is then stored in a
local repository, ready to be used in the retrieval
process;
4
http://blacky.dia.uniroma3.it:9080/login.html
Sequencing Wikipedia Pages: An On-the-fly Approach to Course Building
399
The Terms Manager Module. This module man-
ages the topic-terms and the context-terms in-
serted by the users during the query building pro-
cess. These sets of terms are then passed to the
search engine to retrieve relevant pages from the
Wikipedia repository. Moreover, these terms are
stored in the local repository, in order to display
them in a Google-like way, when building a new
query;
The Page Manager Module. This module is com-
posed of two sub-modules: the My Courses and
the Build Course module. Through the first mod-
ule the users can revise their courses, changing
the learning paths, export the courses, and so on.
The second module manages the sequencing en-
gine, allowing to build new courses. Worth of
mention is the capability of this module to display
the graph of the connections among the retrieved
Wikipidia pages. It helps teachers to have a sim-
ple and graphic interface to the recommended
learning path in order to modify it, by adding or
deleting learning nodes directly.
Login
Manager
Users
DB
Terms Manager
Search
Engine
Context Terms
DB
Wan
Wikipedia Pages
DB
New
Course
Query
Terms
Wikipedia
HTML Pages
Filtering
Process
Sequencing
and Ranking
Pages
Manager
Teacher
Local Wikipedia Pages
DB
Teacher
Wiki Course
Figure 2: The general architecture of the Wiki Course
Builder system.
5 THE SEQUENCING ENGINE
In this section we show the entire process of building
a learning path to insert in a new or old course. The
session starts with a teacher having the My Courses
repository empty. Subsequently, the teacher can cre-
ate a new course, as shown in Fig. 3 where a
new course, concerning the java programming lan-
guage topic, is to be created. Once inserted the
topic-terms and the context-terms, the system returns
those Wikipedia pages deemed relevant for the query.
In fact, the user, through a Google-like interface,
can specify the keywords in the first input text field
(the topic-terms) together with other terms, to disam-
biguate the context (the context-terms), in the second
text field. The system keeps track of all the topic-
terms already inserted, with their related context-
terms. Finally, clicking the Submit button, the sys-
tem returns a group of Wikipedia pages, ranked on
the basis of the distance between the teaching model
of the teacher who launched the query and the teach-
ing styles of each retrieved page, computed as an Eu-
clidean distance metric D between the user teaching
styles TS
u
k
and the generic document TS
d
i
:
D
u,d
=
v
u
u
t
5
i=1
(TS
u
i
TS
d
i
)
2
(1)
The retrieved pages, displayed in a results-table,
can be ranked also by means of the cosine similar-
ity between the query and each Wikipedia retrieved
page, by means of a TFxIDF terms-weighting tech-
nique (see for example (Baeza-Yates and Ribeiro-
Neto, 1999)). The system uses the TFxIDF tech-
nique, which is not based on didactic features, only
at the time t
0
, that is when the retrieved pages are all
cold items. Every time the teacher uses a retrieved
page in a course, this page is tagged with her teaching
styles. In this way, by the use of the system, each used
Wikipedia page (i.e., a link to it) will be stored in a lo-
cal database together with a set of the 5-tuples of the
teachers who used it in their courses: if a teacher used
a page n-times, this page will be tagged n-times with
the user teaching styles. In this way, the system keeps
track of the choices made by the members of the com-
munity, strengthening the social aspects of the page
selection process. Obviously, in the Wikipedia repos-
itory, the topics do not have a uniform distribution in
terms of number of related pages: it may be that for
different topics there is a different number of related
pages stored in the Wikipedia database. In the case
of none of the Wikipedia pages should match the user
query, other topic-terms are required. Moreover, the
retrieval process could be more or less time consum-
ing, depending on the granularity of the query. From
the results table the user can perform the following
actions:
1. Clicking the title of each page, after that the sys-
tem proposes a new window showing the web
page directly from Wikipedia. In this way the
teacher can assess more accurately its content;
2. Changing the ranking algorithm: by Title, by
Teaching Styles or by cosine similarity;
3. Clicking the process button to launch the sequenc-
ing engine. In this case, the system processes all
the links belonging to that page and returns a se-
quence of three pages. Once the teacher has given
CSEDU 2016 - 8th International Conference on Computer Supported Education
400
Figure 3: The Course Building Process. The left screen-shot shows the starting form where teachers can insert their topic-
terms; the right screenshot shows the pages returned by the search engine for the java programming language query.
Figure 4: The sequencing process: the left screenshot shows the learning path returned by the system; the right screenshot
shows the final learning path inserted into the new course (java programming language).
the new course a title and a description, by click-
ing on the Apply button, the new empty course is
added to the My Courses list of the courses owned
by her. In Fig. 4 the sequencing selection pro-
cess is shown. For each course, users can view
the details, change the title and/or description and
delete the course. To store the new course and to
make the changes effective it is then necessary to
click the save button at the top right of the screen.
Once created the course, the user can populate it
with didactic contents.
In particular, the sequencing engine parses the
Wikipedia page related to the process button, to iden-
tify its outbound links. For each linked Wikipedia
page, the system selects the more promising page,
including it in the recommended learning path. In
the case of ties, the system uses the cosine similarity
as it does in the previous phase of the search results
ranking. These operations of parsing, calculating the
Euclidean distance and selection of the most promis-
ing page are then repeated a finite and parameterized
number of times. Currently the system is set up to
compute three levels of depth, but the user can change
this parameter. The returned learning path is shown in
Fig. 4 where from the top of the list to the bottom a
learning path consisting of three pages, is displayed.
For each item of the results-set, the user can display
it, move it up or down, changing the ranked list and
delete it. After these operations, the learning path is
inserted into the new course.
5.1 The Sequencing Graph
Management
Another important feature of the system, is its capa-
bility to allow the user to visualize and to directly
interact with the graph of the course by means of a
graphical interface based on the Gephi graph man-
ager, an open source software to manage graphs
5
. The
system displays the graph formed by the learning path
together with all the Wikipedia linked pages. Click-
ing on the i icon, the user launches the graph envi-
ronment. In Fig. 5, highlighted in red, are shown
the three nodes forming the recommended learning
path. Clicking on a node, the system highlights all
the links and all the nodes directly connected with it,
5
www.gephi.org
Sequencing Wikipedia Pages: An On-the-fly Approach to Course Building
401
both inbound and outbound, as shown in Fig. 6. On
the left of the graph the system shows a frame con-
taining some important characteristics of the selected
node: the name of the page together with its link to
Wikipedia, the distances computed both by teaching
styles and cosine similarity for that node, the URLs of
all the Wikipedia pages directly connected to it. By
clicking one of these URLs, the system opens a new
browser window displaying the selected page. In this
way, the teacher can verify the quality of the learning
path suggested by the sequencing engine checking for
other topics to add to the recommended learning se-
quence, as shown in Fig. 6. To add a node to the
learning path the user just selects it in the graph and
then clicks the link on the left Add this page to list.
The system opens a dialog box confirming the inser-
tion. After having saved the course, each Wikipedia
page included in this course is tagged with the 5-tuple
of the teacher owner of the course. Moreover, when
using the same Wikipedia page in different courses,
this page is tagged with the Grasha 5-tuples of the
Figure 5: The graph with, in red color, the recommended
learning path for the java programming language course.
Figure 6: The user has clicked on the java node: the system
proposes the Programming Language node.
course owner once more. For each Wikipedia page
tagged by the system, the system stores its 5-tuples,
indicating the teaching styles of thepage and the num-
ber of contributions to its calculation. For example,
if three users are using the same Wikipedia page,
this page will be associated with the Grasha quintu-
ple [x
1
, x
2
, x
3
, x
4
, x
5
], in which each element x
i
is com-
puted as the arithmetic mean of all the values of the
three teaching styles of the users who have used it
in their courses. Moreover, the system associates to
each used page an incremental counter keeping track
of how many users have used the page. The presence
of the counter allows to obtain weighted values for the
calculation of the new tags. If a user decides to delete
a page from its course, the counter is consequently
updated. Finally, at any time the user can return to the
My Courses section to view the details of her course
with the possibility to edit or delete it.
6 A FIRST EVALUATION OF THE
SEQUENCING MODULE
In this Section we show a first evaluation of the
sequencing engine. We submitted a happy sheet
questionnaire, composed of 5 questions, to a sample
formed by 10 teachers teaching in a technical high
school with the aim to test the feeling of teachers with
respect to the sequencing process. The sample was re-
quired to create a new course on a Computer Science
topic. The following ten courses were built: mother-
board, java language, array, microprocessor, switch,
router, c language, Von Neumann, Turing and Unified
Modeling Language. A question was about the use-
fulness of the recommended sequencing: Did you find
useful the sequencing proposed by the system?. An-
other question was: How do you feel the GUI of the
sequencing module?. The answers to the first ques-
tion are shown in Fig. 7. 70% of the sample con-
sidered the system useful and very useful. In Fig. 8,
Figure 7: Do you find useful the sequencing proposed by
the system?
CSEDU 2016 - 8th International Conference on Computer Supported Education
402
are summarized the answers concerning the assess-
ment of the system GUI. Finally, the 80% of the sam-
ple judged such interface as simple and very simple to
use.
Figure 8: How do you feel the GUI of the sequencing mod-
ule?
7 CONCLUSIONS AND FUTURE
WORK
In this paper we presented the sequencing module of
the WCB system, capable of helping teachers build-
ing and managing courses composed of Wikipedia
pages. First, registered users are required to in-
sert some topic-terms and secondly to insert some
context-terms both to build the query and to help the
search engine to disambiguate the Wikipedia pages.
Subsequently, the system returns some Wikipedia
pages sequenced by means of the user teaching styles,
according to the Grasha teaching styles model. The
teacher can accept the recommended learning path
or change it both in terms of Wikipedia pages and
in terms of a different learning path. Another im-
portant feature of the system is its ability to man-
age the graph embedding the recommended learning
path proposed by the system: the user can click the
nodes, adding them to the it. All the used pages are
stored in a local database where they are tagged with
the teaching styles of the teacher who used them. In
this way, a CoP can grow and users can benefit of
each others work. Currently the system is at its very
early stage of development, running as a 3-tier web
architecture, developed in java language and using
the wikipedia-miner toolkit to interface itself to the
Wikipedia database. Future work includes a full eval-
uation of all its modules with a large sample.
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