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  <front>
    <journal-meta />
    <article-meta>
      <title-group>
        <article-title>Using Automatically Generated Students' Clickable Conceptual Models for E-tutoring</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <string-name>I. Pascual-Nieto</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>D. Perez-Mar n</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>P. Rodr guez</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>M. O'Donnell</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <aff id="aff0">
          <label>0</label>
          <institution>Universidad Autonoma de Madrid</institution>
          ,
          <addr-line>28049 Madrid</addr-line>
          ,
          <country country="ES">Spain</country>
        </aff>
      </contrib-group>
      <abstract>
        <p>Computer methods for evaluating student's knowledge have traditionally been based on Multiple Choice Questions (MCQs) or llin-the-blank exercises, which do not provide a reliable basis upon which to assess student's underlying misconceptions. Because of this lack, we have devised and implemented a procedure for automatically deriving clickable students' conceptual models from their free-text answers. A student's conceptual model can be de ned as a network of interrelated concepts associated with a con dence value that indicates how well each student knows a concept. Several knowledge representation formats are used to show the generated conceptual model to the student. Furthermore, students can click on the concepts to get more information about them. 22 English Studies students are taking advantage of this new resource to review their Pragmatics course. Initial results show that they have found it very useful and claim that it is a good support for their review of the subject.</p>
      </abstract>
    </article-meta>
  </front>
  <body>
    <sec id="sec-1">
      <title>Introduction</title>
      <p>
        According to the theory of constructivism [
        <xref ref-type="bibr" rid="ref1">1</xref>
        ], knowledge can be de ned as the
product of a learning activity in which an individual assimilates and
accommodates new information into his or her cognitive structure in accordance with
the environment as s/he understands it. Thus, in educational terms, a student
builds his or her speci c cognitive structure or conceptual model, understood
here as a network of concepts, depending on his or her particular features and
previous knowledge. Moreover, in conformity with the Meaningful Learning
Theory of Ausubel [
        <xref ref-type="bibr" rid="ref2">2</xref>
        ], students can learn new concepts only if they have a base of
previous concepts to which to link the new concepts.
      </p>
      <p>
        Therefore, it is necessary to have some reliable strategy to model the
student's conceptual knowledge. Currently, there are systems such as ConceptLab
[
        <xref ref-type="bibr" rid="ref3">3</xref>
        ] which represents the student model as a concept map that facilitates the
sharing of knowledge among students and the assessment of students'
knowledge by teachers; and STyLE-OLM [
        <xref ref-type="bibr" rid="ref4">4</xref>
        ] which interactively builds the student's
conceptual model through a dialogue between the student and the system. These
systems are at the forefront of computer-supported tutoring and assessment.
      </p>
      <p>
        In previous work [
        <xref ref-type="bibr" rid="ref5">5</xref>
        ], we devised a procedure for automatically deriving
inspectable students' conceptual models from free-text answers. The domain model
is partially generated from information provided by the teacher, and the
student's conceptual model can be de ned as a network of interrelated concepts, in
which each concept has an associated con dence value that indicates how well
it has been understood by each student according to a set of metrics. The
conceptual model can also refer to a group of students, in which case, each concept
is also associated with a con dence value that indicates how well on average the
class has understood the concept. Both the student's conceptual model and the
class conceptual model can be generated from the students' free-text answers
using a set of Natural Language Processing (NLP) tools. The generated models
are made available to both students and teachers so that they can keep track of
the students' conceptual evolution during the course, allowing them to focus on
the least understood concepts, which prevent the assimilation of new concepts.
      </p>
      <p>The procedure has been implemented in the Will Tools1, which are a set of
web-based applications that consist of: Willow, an automatic and adaptive
freetext students' answers scorer; Willov, a conceptual model viewer; Willed, an
authoring tool; and, Willoc, a con guration tool. In this paper, we present the
next step of the procedure: to give the student more control over the generated
model, with the consequence that it can be used not only for evaluation but also
for tutoring. In order to achieve this goal, the students are no longer presented
all the domain concepts in the conceptual model. Instead, only concepts with a
con dence value higher than a certain threshold are shown. In this way, students
can see how they construct their knowledge at their own particular rhythm from
a blank conceptual model to a conceptual model with all domain concepts. Each
domain concept will appear as it is correctly used in the answers provided to
Willow but only if its con dence-value is higher than the threshold (e.g. 0.1).</p>
      <p>Furthermore, the conceptual model is not only inspectable but clickable.
Students can click on each concept of their conceptual model and learn more
about it. This is useful to orient the study towards the concepts that are least
understood, and guide the student to the questions that involve these concepts.
It is also important to observe that since students can look at the conceptual
model of the whole class, they can click on a concept that does not appear in
his or her particular conceptual model, but that appears in the class conceptual
model, and which may be important to assimilate if the concept is a precondition
for assimilating other concepts.</p>
      <p>A study is being undertaken in the 2007-2008 academic year, with 22 English
Studies students using the Will Tools to review their Pragmatics course. Initial
results show that students have found this new resource useful and they claim
that it is a good support for their review of the course.</p>
      <p>This paper is organized as follows: Section 2 describes the domain and
student's conceptual models; Section 3 depicts some clickable and evolving
representation formats in which the students' conceptual models are shown; Section 4
reports the results of the experiment performed with a group of English Studies
students; and, nally Section 5 provides the main conclusions of the paper.
1 The systems are available on-line at http://www.eps.uam.es/~dperez/index1.html</p>
    </sec>
    <sec id="sec-2">
      <title>Domain and student's conceptual model</title>
      <p>The domain model contains the reference information of the course or
area-ofknowledge under assessment. The information is provided by the teachers using
the authoring tool called Willed. There may be one or more teachers using Willed
to describe a course. In particular, it would be convenient that there are more
than just one teacher as, in this way, the creation of the domain model is less
dependent on a particular individual.</p>
      <p>Firstly, teachers are asked the name of the course to model. Secondly, they
are asked the name of the lessons of the course, and thirdly, they have to provide
a set of questions per topic. The minimum information that should be given per
question is: its statement in natural language; its maximum numerical score; its
numerical score to pass the question; its di culty level in the range low (0),
medium (1) or high (2); the topic to which the question is related to and, nally,
a set of correct answers or references in natural language.</p>
      <p>
        In order to organize this information provided by the teacher in the domain
model, we have devised a hierarchical structure of knowledge into three di erent
types of concepts. The reason for using this structure is to follow the organization
of the course provided by the teachers as much as possible. The three types of
concepts devised are:
{ Area-of-knowledge-concepts (AC): It is the name of the course to assess
as indicated by the teachers.
{ Topic-concepts (TCs): They are the name of the lessons of the course as
indicated by the teachers.
{ Basic-concepts (BCs): They are the key concepts of the area of
knowledge under study. BCs are automatically extracted from the correct answers
provided by the teachers to each question of the course using an automatic
Term Identi cation module [
        <xref ref-type="bibr" rid="ref5">5</xref>
        ]. Teachers can also later review this list of
BCs and, modify it as they consider more adequate.
      </p>
      <p>
        For instance, for an \Operating Systems" course, the AC would be \Operating
Systems", one TC could be the \Concurrency" lesson and, and one BC could be
\thread ". Moreover, given that the goal is to nd out the level of assimilation of
each concept per student, all concepts are associated to a con dence-value (CV)
that re ects how well the system estimates that the student knows them. The
CV of a concept is between 0 and 1. A lower value means that the student does
not know the concept as s/he does not use it, while a higher value means that
the student con dently uses that concept. The CV is automatically updated as
the student answers questions according to a set of metrics [
        <xref ref-type="bibr" rid="ref5">5</xref>
        ]. The CV of a TC
is calculated as the mean value of the CVs of the BCs that it groups. The CV
of an AC is calculated from the CVs of its related TCs.
      </p>
      <p>Regarding the relationships between the concepts, we have devised three
types of links between them according to the type of concepts that they relate
(and following the criterion of adjusting the model as much as possible to the
traditional course provided by the teacher):
{ Type 1, between ACs and TCs: Given that a course is usually structured
into lessons, type 1 links relate the concept representing the whole course (the
AC) with each lesson (each TC). A topic-concept may belong to di erent
area-of-knowledge concepts, but as the model only represents one course,
each TC can only be related to the AC. Type 1 links are automatically
extracted from the information provided by the teachers (i.e. which lessons
correspond to each course).
{ Type 2, between TC and BC: Given that each lesson has a set of
questions with correct answers, type 2 links relate the concept representing the
lesson (each TC) with each concept treated in that lesson (each BC). A
basic-concept belongs to one or more topic-concepts. These relationships are
important because they give us information about how the basic-concepts
are grouped into topic-concepts and, how the students are able to use the
BC in the di erent questions of the topics of the course. TCs are not linked
among themselves, as the relationships between the topics are already
captured by the type 3 links. Type 2 links are automatically extracted from the
relationships between the topics and, the concepts found in the reference
answers of the questions of the topic.
{ Type 3, between two BCs: A basic-concept can be related to one or more
basic-concepts. These links are very important as they re ect how BCs are
related in the student's cognitive structure as extracted from the students'
answers. Therefore, unlike type 1 and type 2 links that are automatically
extracted from the information provided by the teachers, type 3 links are
automatically extracted from the information provided by the students.</p>
      <p>We de ne a student's conceptual model as a simpli ed representation of
the concepts and relationships among them that each student keeps
in his or her mind about an area of knowledge at a given point of
time. Conceptual models are useful both as a data model to guide the system's
assessment of the student, and also as a form of feedback to both student and
teacher, indicating the current state of progress of the student. As a resource to
the system, the order and content of questions can be selected to focus on the
misconceptions or erroneous links detected. In terms of feedback to the teacher
and student, the presentation of a student's conceptual model makes evident the
student's strengths and weaknesses. The teacher can also view the conceptual
model of the class as a whole to see the strengths and weaknesses of the class,
which may suggest that they need to spend more time teaching certain topics.</p>
      <p>
        The student's conceptual model is not introduced by the teacher or by the
student, but generated from the answers provided by the students to the Willow
system [
        <xref ref-type="bibr" rid="ref5">5</xref>
        ]. The core idea is to compare the free-text answer provided by the
student to a set of correct free-text answers provided by the teachers, such that
the more similar they are, the higher the score the student achieves. Furthermore,
the system takes the frequency of use of the concepts in the student's answer
into account in contrast to the frequency of use of the concepts in the teachers'
answers with the idea that students should not use concepts not contemplated
by their teachers in their answers, use them too frequently, or ignore concepts
that are considered important by the teachers [
        <xref ref-type="bibr" rid="ref5">5</xref>
        ].
      </p>
      <p>
        Initially, each student's conceptual model has only the area-of-knowledge
concept (AC) and the topic-concepts (TCs) as indicated by the teacher and stored
in the domain model. Both AC and TCs have been associated a 0 con
dencevalue indicating that the student has never used them. Similarly, only type 1
and 2 links are represented as extracted from the domain model. Next, when the
students start using Willow to answer the questions indicated by the teachers,
they will start providing free-text answers, and from these answers, Willow
automatically identi es the basic-concepts used. Moreover, Willow calculates the
con dence-value associated to each concept according to the frequency metrics
[
        <xref ref-type="bibr" rid="ref5">5</xref>
        ], and looks for type 3 links between BCs in the student's answer.
3
      </p>
    </sec>
    <sec id="sec-3">
      <title>Some conceptual models representation formats</title>
      <p>
        The conceptual model can be represented in several knowledge representation
formats: a concept map, a conceptual diagram, a table, a bar chart and a
textual summary. The conceptual model is always updated with the information
gathered from the students' answers. This permits the capture of the
conceptual evolution of the students, since the conceptual models generated at di erent
times can be stored and reviewed later. In our previous work [
        <xref ref-type="bibr" rid="ref5">5</xref>
        ], both students
and teachers could enter a conceptual model viewer (COMOV) to look at the
inspectable representation of the models during the course. However, as a
result of the experiments performed with the Willow+COMOV systems during
the 2005-2006 and 2006-2007 academic years, we thought that it would be more
convenient not to show the whole conceptual model to the students, but just
the concepts with a CV higher than a certain threshold so that students could
actually see how they are building their conceptual models as they answer more
questions in Willow.
      </p>
      <p>Therefore, we have changed the way the student and class models are
accessed. In particular, students can now look at their own conceptual model and
the class conceptual model in the Willow system, whereas teachers can look at
the conceptual model of any student or group of students in a new conceptual
model viewer for teachers (Willov). In this way, both students and teachers can
keep track of the evolution of the models by looking at them several times during
the course. The di erence now is that students can only see the concepts with a
CV higher than a certain threshold (e.g. 0.1, that is, the concepts that have been
mentioned at least once in their answers), while the teachers' representation is
the same as in the previous version, showing all the concepts irrespectively of
their CV. Additionally, students and teachers can see the conceptual model for
each topic under review independently of other topics, and also a global view for
all topics.</p>
      <p>Furthermore, in order to help students understand the concepts that they
have used wrongly, they can now click on each concept and be presented with
an automatically generated explanation page. That is, the models are now not
only inspectable but also clickable, and thus more power has been given to the
student to control his or her learning. This does not give more work to the
teacher. In fact, the teacher does not have to write the explanation page. It
is generated from the information provided when the course was created. In
particular, the explanation page shows all questions and the correct answers in
which the concept has been used. The concept is marked with a color background
so that the student can extract the meaning of the concept from the di erent
contexts in which it appears.</p>
      <p>Regarding the possible representation formats of the automatically generated
student's conceptual models, two will be described in this paper: concept maps
and conceptual diagrams. Concept maps are particularly useful for displaying
networks of concepts. Each node represents a concept and the links between the
nodes represent the relationships between the concepts. A web-like organization
of the map has been chosen, as it is one of the most suitable formats for the
hierarchy of concepts (BC, TC, AC) proposed. The type of node is indicated
by the size and place in the concept map: the AC is bigger and it is always at
the center, the TCs are medium-size and are placed in the second radial line,
while the BCs are smaller and are placed in the outer radials lines; and, the links
have been reorganized in an e ort to avoid crossings. The conceptual model can
also be presented as a hierarchical diagram, with the most important concept
at the top and less relevant concepts below. In this format, the focus is just on
the concepts and, the relationships among them are not explicitly represented.
Figure 1 shows a concept map and conceptual diagram representations of the
student's conceptual model for one topic.
4</p>
    </sec>
    <sec id="sec-4">
      <title>Experiment</title>
      <p>In the 2007-2008 academic year, Willow was used by 22 students out of 45
studying a \Pragmatics" course within the Department of English. Teachers provided
material for Willow, consisting of 49 questions, each with 3 correct answers and
covering four topics of the \Pragmatics" course. The use of the system was
completely voluntary and did not a ect the grade given in the subject. The goal of
the experiment was to nd out whether the students nd the new utilities in
Willow useful for reviewing their course. It is important to highlight that since
Willow is a Blended Learning tool, we do not aim to replace the teacher, but to
support both the teachers and students by providing an alternative knowledge
acquisition, assessment and representation format.</p>
      <p>The only technical knowledge needed to use Willow is the ability to use a
web browser. However, as it was the rst time the students used computers as a
support for their studies, we gave them a short tutorial on the main features of
Willow, and we organized a rst day of using Willow in class (in contrast with the
normal intention of using the system after class). As we did not want to interfere
with their manner of interaction with Willow (just the opposite, we wanted the
students to explore the system by themselves), we did not explain some new
features such as how to get more information about concepts by clicking on the
display of the conceptual model, or how to follow their progress by looking at
their conceptual model several times during the semester.</p>
      <p>Rather than basing our evaluation on user questionnaires, which requires
more work from the student, we set Willow to log each action the student
performs within the system. In this way, at the end of the rst day of using Willow
in class we had 22 logs (49% of the students volunteered to use the system in
class). These logs revealed that even though they had not been told that they
could check their progress by looking several times at the model after having
answered questions, 14 students looked at the conceptual model 44 times, as
gathered in Table 1.</p>
      <p>Regarding how the conceptual model was viewed, the concept map format
was most popular (32% of views). The conceptual diagram form was second in
popularity (27%), while the bar chart and the textual summary were the least
popular formats (possibly because they were the last options on the menu).
Regarding the use of the individual versus class conceptual model, in 52% of
the cases, students looked at only their own conceptual model, while in 48%
of the cases they looked at both their own and the class conceptual models.
When tabular presentation was used, the students were more concerned with
their own results rather than the global results of the class. It is also interesting
to observe that the number of students who looked rst their individual model
and secondly, the class conceptual model is similar to the number of students
who looked at the models in the reverse order.
5</p>
    </sec>
    <sec id="sec-5">
      <title>Conclusions</title>
      <p>The use of automatically generated students' conceptual models from the
freetext answers provided to Willow has been extended not only for evaluating
purposes but also for tutoring. Only concepts with a con dence value higher than
a certain threshold are shown in the representation of the generated conceptual
model, so that concepts that have never been used by the student do not appear
in his or her own model. The student can still see these concepts in the class
conceptual model and click on them to generate an immediate explanation page
to nd out what information is lacking in his or her answers and to improve them.
In this way, the next time that s/he answers the questions failed in Willow, if the
student uses the new information provided by the explanation page, s/he will
be able not only to pass the question but to generate a conceptual model with
more concepts marked as correctly known, indicating that s/he has achieved a
better knowledge of the subject.</p>
      <p>A study is being undertaken in the 2007-2008 academic year, with 22 English
Studies students using Willow to review their Pragmatics course. From the logs
of the use of Willow, it can be stated that one of the most popular representation
formats is the individual concept map.
6</p>
    </sec>
    <sec id="sec-6">
      <title>Acknowledgments</title>
      <p>This work has been sponsored by Spanish Ministry of Science and Technology,
project number TIN2007-64718.</p>
    </sec>
  </body>
  <back>
    <ref-list>
      <ref id="ref1">
        <mixed-citation>
          1.
          <string-name>
            <surname>Carpendale</surname>
            ,
            <given-names>J.:</given-names>
          </string-name>
          <article-title>An explanation of Piaget's constructivism: Implications for social cognitive development. The development of social cognition (</article-title>
          <year>1997</year>
          )
          <volume>36</volume>
          {
          <fpage>64</fpage>
        </mixed-citation>
      </ref>
      <ref id="ref2">
        <mixed-citation>
          2.
          <string-name>
            <surname>Ausubel</surname>
            ,
            <given-names>D.</given-names>
          </string-name>
          :
          <article-title>The Psychology of meaningful verbal learning</article-title>
          . New York: Grune and
          <string-name>
            <surname>Stratton</surname>
          </string-name>
          (
          <year>1963</year>
          )
        </mixed-citation>
      </ref>
      <ref id="ref3">
        <mixed-citation>
          3.
          <string-name>
            <surname>Zapata-Rivera</surname>
            ,
            <given-names>J.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Greer</surname>
          </string-name>
          , J.:
          <article-title>Externalising learner modelling representations</article-title>
          .
          <source>Proceedings of Workshop on External Representations of AIED: Multiple Forms and Multiple Roles</source>
          (
          <year>2001</year>
          )
          <volume>71</volume>
          {
          <fpage>76</fpage>
        </mixed-citation>
      </ref>
      <ref id="ref4">
        <mixed-citation>
          4.
          <string-name>
            <surname>Dimitrova</surname>
          </string-name>
          , V.:
          <article-title>STyLE-OLM: Interactive Open Learner Modelling</article-title>
          .
          <source>International Journal of Arti cial Intelligence in Education</source>
          <volume>13</volume>
          (
          <issue>1</issue>
          ) (
          <year>2003</year>
          )
          <volume>35</volume>
          {
          <fpage>78</fpage>
        </mixed-citation>
      </ref>
      <ref id="ref5">
        <mixed-citation>
          5.
          <string-name>
            <surname>Perez-Mar n</surname>
          </string-name>
          , D.:
          <article-title>Adaptive Computer Assisted Assessment of free-text students' answers: an approach to automatically generate students' conceptual models</article-title>
          .
          <source>PhD thesis</source>
          , Escuela Politecnica Superior, Universidad Autonoma de Madrid (
          <year>2007</year>
          )
        </mixed-citation>
      </ref>
    </ref-list>
  </back>
</article>