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  <front>
    <journal-meta />
    <article-meta>
      <title-group>
        <article-title>Adaptive Support for Educational Question Answering</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <string-name>Ivan Srba</string-name>
          <email>srba@fiit.stuba.sk</email>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Mária Bieliková</string-name>
          <email>bielik@fiit.stuba.sk</email>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <aff id="aff0">
          <label>0</label>
          <institution>Institute of Informatics and Software Engineering Faculty of Informatics and Information Technologies Slovak University of Technology in Bratislava Ilkovičova 2</institution>
          ,
          <addr-line>842 16 Bratislava</addr-line>
          ,
          <country country="SK">Slovakia</country>
        </aff>
      </contrib-group>
      <fpage>109</fpage>
      <lpage>114</lpage>
      <abstract>
        <p>Nowadays, it is possible to access almost unlimited sources of information by ubiquitous information and communication technologies. However, sometimes it is difficult to find required information by standard web search engines. In these situations, Internet users have a possibility to ask their questions in popular community question answering systems (CQA) such as Yahoo! Answers or Stack Overflow. We are interested in an idea to provide similar opportunity also for users in intra-organizational context, and more specifically for students in educational environment. On the basis of analyses of existing approaches in standard CQA systems, we concentrate in our research on the open problem how to adapt these approaches to match the specifics of intraorganizational context and particularly how to recommend newly posted questions to students who are most likely to provide the appropriate answer.</p>
      </abstract>
      <kwd-group>
        <kwd>Community Question Answering</kwd>
        <kwd>Knowledge Sharing</kwd>
        <kwd>Collaborative Learning</kwd>
      </kwd-group>
    </article-meta>
  </front>
  <body>
    <sec id="sec-1">
      <title>-</title>
      <p>
        With the development of Web 2.0, popularity of systems based on user generated
content such as Wikipedia, YouTube or Flickr is continuously increasing. One type of
these systems is Community Question Answering (CQA). CQA is a web service
where people can seek information by asking a question and share knowledge by
providing answer on the particular question [
        <xref ref-type="bibr" rid="ref13">13</xref>
        ]. One kind of CQA systems provides
users with possibility to ask any general question without any topic restriction (e.g.
Yahoo! Answers or Wiki Answers). On the other hand, there are topic-focused CQA
systems dedicated to some specific domain too (i.e. Stack Overflow where users
concern with questions related to computer programming).
      </p>
      <p>Compared with the traditional information retrieval systems, CQA systems are
based on communities of different Internet users and thus they can apply the best of
users’ collective wisdom to satisfy knowledge seekers with the most accurate
answers. This kind of systems for knowledge sharing is very effective and successful
especially when the answer cannot be found easily by standard web search engines
(e.g. when users cannot describe their information needs by keywords or when the
information is distributed in different sources).</p>
      <p>The significant part of state-of-the-art research in the domain of CQA systems falls
into knowledge sharing perspective. According to knowledge management theory,
knowledge sharing is a process in which knowledge is exchanged among members of
particular community. Furthermore, besides knowledge sharing, there is also another
interesting possibility how CQA systems can be analyzed. Searching for the answer to
the question we are asking is actually informal learning. And thus, we can consider
CQA systems also as an innovative kind of collaborative learning environments.</p>
      <p>
        Various adaptive approaches have been proposed to support collaboration among
users in CQA systems so far. In spite of huge variance of these methods in their
purpose, we are not aware of any systematic categorization of approaches employed in
CQA systems. Therefore, on the basis of extensive analyses and evaluation of more
than 70 research studies performed in the domain of CQA systems, we have proposed
views for a complex categorization of approaches supporting CQA process. In the
proposed categorization, we divided the approaches according five views, which are
related to different phases of question’s lifecycle:
1. Domain entities analyses concern with classification and evaluation of users,
questions and corresponding answers (e.g. identification of users’ intent [
        <xref ref-type="bibr" rid="ref3">3</xref>
        ] or
estimation of question/answer quality [
        <xref ref-type="bibr" rid="ref10">10</xref>
        ]). These analyses are independent on
question’s lifecycle and serve as an important input for following groups of approaches.
2. Question creation group of approaches concerns with bridging the gap between
web search and CQA, and with the assignment of questions to topics. Existing
approaches solve the problems such as the maintenance of topic hierarchy [
        <xref ref-type="bibr" rid="ref7">7</xref>
        ] or how
to automatically identify question’s topic [
        <xref ref-type="bibr" rid="ref11">11</xref>
        ].
3. Question routing refers to routing newly posted questions to potential answerers.
      </p>
      <p>
        This process is essential for successful CQA system and thus many various
approaches have been proposed for this purpose so far. They are based on different
estimations of user expertise (e.g. [
        <xref ref-type="bibr" rid="ref3">3</xref>
        ], [
        <xref ref-type="bibr" rid="ref5">5</xref>
        ]) and user activity (e.g. user authority or
availability [
        <xref ref-type="bibr" rid="ref3">3</xref>
        ]).
4. Question answering is supported by approaches concerned with voting calibration
[
        <xref ref-type="bibr" rid="ref2">2</xref>
        ] or selection of the best answer. The best answer can be selected by the asker, by
the community of answerers or by CQA system itself.
5. Question search refers to the retrieval of the best archived question-answer pairs
which provide a user with the same information as is required for answering
his/her original question. Different methods based on semantic similarity between
the searched question and archived questions are proposed (e.g. [
        <xref ref-type="bibr" rid="ref8">8</xref>
        ]).
2
      </p>
    </sec>
    <sec id="sec-2">
      <title>Intra-organizational Community Question Answering</title>
      <p>Millions of successfully answered questions in CQA systems prove that the popularity
of CQA systems rapidly increased in several last years. The rising popularity and
growing number of CQA users cause that new opportunities for supporting
collaboration constantly emerge. Therefore, CQA systems became the subject of many research
studies. However, in spite of increasing number of studies on CQA systems in recent
years, the beneficial effect of CQA systems has not been fully discovered in
intraorganizational context yet, such as in educational, business or research environments.</p>
      <p>Employing the successful and verified concepts of CQA systems inside
organizations is a complex task because organization-wide CQA differs from traditional CQA
systems in several aspects. Some of them make the knowledge sharing more
complicated, e.g. the number of users is significantly lower and thus it is more difficult to
route questions to appropriate answerers. On the other hand, there are differences
which provide new opportunities for collaboration support, such as the great amount
of accessible information about users or a possibility to manage knowledge sharing
process by a supervisor, an instructor or a team leader. As the result of these
differences, informal learning in standard CQA systems becomes non-formal or even
formal in intra-organizational environments. All these aspects make the transition of
CQA systems from the Web to intra-organizational context challenging.</p>
      <p>However, each type of organizational environment is specific. We focus on
educational organizations where students are often struggling with many problems related
to their learning process. Therefore, the idea of providing students with the possibility
to ask their questions in faculty or university CQA system seems quite promising.
2.1</p>
      <sec id="sec-2-1">
        <title>Research Questions</title>
        <p>According to the motivation stated above we formulate the research question of our
dissertation project as follows: How an intra-organizational educational CQA system
should be designed to take specific organizational conditions into consideration while
preserving well established aspects of CQA? Answering of our main research
question leads to a set of derived sub-questions:
1. What are the specific conditions in information systems employed in
intraorganizational educational environment? Especially how different students’
characteristic influence and motivate collaboration during question-answering process?
2. How can we adapt existing approaches to match specifics of intra-organizational
environment?
3. Which additional/modified functionalities should be provided by an educational
intra-organizational CQA system in comparison with standard CQA systems?
2.2</p>
      </sec>
      <sec id="sec-2-2">
        <title>Research Methodology</title>
        <p>We divided our work on the dissertation project into three phases:
1. In the first preliminary phase, we analyzed state of the art in research of CQA
systems from the perspective of knowledge sharing as well as collaborative learning.
Moreover, we performed extensive study of existing approaches which have been
proposed to support collaboration during question answering process so far. In
addition, on the basis of the results of our previous work, we examined the students’
collaboration while answering well-defined questions prepared by a teacher. The
main aim of this analysis was to determine how students’ characteristics influence
collaboration and motivate for participation in question answering process.
2. In the current second phase, we build on outputs from the first phase. From the
proposed categorization of approaches employed in CQA systems, we recognized
question routing as significantly influenced by the transition to intra-organizational
environment and thus the proposal of new method for question routing represents
the main focus of our research. Besides, the method proposal, we plan to design
and implement the prototype of educational CQA system.
3. In the next phase, we plan to evaluate the proposed method by employing the
created prototype of CQA system. We plan to start the experiment with the limited
number of students who enroll the course Principles of software engineering in
bachelor study programme Informatics. Afterwards, in a long-term experiment, we
plan to involve wider group of students moving to faculty-wide environment with
possibility to ask questions related to various topics across several courses. Finally,
we will conclude achieved results and derive implications at generic level, i.e.
suggestions which can be applied for intra-organizational environments in general.
2.3</p>
      </sec>
      <sec id="sec-2-3">
        <title>Preliminary Results</title>
        <p>
          In our previous work [
          <xref ref-type="bibr" rid="ref12">12</xref>
          ], we proposed a group formation method for automatic
creation of short-term dynamic study groups for collaborative solving of various
questions. The proposed method is based on the optimization approach named Group
Technology [
          <xref ref-type="bibr" rid="ref9">9</xref>
          ]. It takes into consideration different students’ personal and
collaborative characteristics. We implemented the proposed method as a part of collaborative
environment PopCorm (Popular Collaborative Platform) which is integrated with the
system dedicated to individual learning named Adaptive Learning Framework ALEF
[
          <xref ref-type="bibr" rid="ref1">1</xref>
          ]. PopCorm provides for task solving four collaborative tools: a text editor, a
graphical editor, a categorizer, and a semi-structured discussion (see Figure 1).
1
2
PopCorm served for evaluation of the proposed method in a long-term experiment in
which students solved the collaborative questions prepared by a teacher. The data
acquired during the experiment were used in analyses how students’ characteristics
influence their collaboration. More specifically, we focused on students’ study results,
personal characteristics determined from Big Five questionnaires and collaborative
characteristics proposed by McManus and Aiken [
          <xref ref-type="bibr" rid="ref6">6</xref>
          ]. In our analysis we consider data
of totally 129 students who actively participated in ALEF and PopCorm during one
semester of the course (12 weeks). Students were repeatedly assigned to 254 groups
in PopCorm in which totally 3,763 activities were recorded. In addition, more than
55,400 interactions with learning objects were recorded in ALEF. The results of
analyses provide us with important findings how students’ characteristics influence
overall activity, correctness of created solutions, task and time management, students'
selfregulation and motivation, and, finally, evaluation and providing feedback. These
findings represent important input for following phases of our research work.
2.4
        </p>
      </sec>
      <sec id="sec-2-4">
        <title>Adaptive Question Routing</title>
        <p>In our dissertation project, we focus on question routing which is probably the most
important part of the proposed educational CQA system. It refers to recommendation
of potential answerers who are most likely to provide appropriate answer on the
newly posted question. We propose a method for question routing on the basis of existing
methods for question routing while taking the specifics of intra-organizational
educational domain into consideration. The proposed method considers three groups of
answerer’s characteristics which are important to provide an appropriate answer.</p>
        <p>User expertise. Students’ expertise can be derived from previous activities (e.g.
asking the question, providing the answer, voting for the best answer). In addition, we
can take advantage of information about students which are available specifically in
educational environment (e.g. study results or enrolled subjects).</p>
        <p>User activity. Besides the overall students’ activity in a CQA system, we propose
to consider also students’ availability (estimation that a potential answerer will login
to the system in the time dedicated to answering the question) and authority.</p>
        <p>User motivation. On the basis of performed analyses, we found out that students
perceive reciprocity as an important motivation factor. Therefore, we suggest
recommending questions with considering the symmetry in knowledge each student
provides and receives from the CQA system.
3</p>
      </sec>
    </sec>
    <sec id="sec-3">
      <title>Conclusion</title>
      <p>Community question answering systems has become recently the subject of many
research studies. However, we suppose that their potential for supporting of
organizational knowledge sharing and collaborative learning is only to be discovered. In our
dissertation project, we concern with the transition of CQA from the Web to
educational environment. More specifically, we recognized question routing to potential
answerers as unique opportunity how information technologies can support students’
collaboration. The proposed method, which will be employed in innovative
educational CQA system, will provide students new opportunities how to solve their own
questions related to learning process at our faculty.</p>
      <p>Acknowledgement. This work was partially supported by the Scientific Grant
Agency of Slovak Republic, grant No. VG1/0675/11 and by the Slovak Research and
Development Agency under the contract No. APVV-0208-10.</p>
    </sec>
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