Maria Beatriz Piedade
School of Technology and Management, Polytechnic Institute of Leiria, 2411-901, Leiria, Portugal
Maribel Yasmina Santos
Information Systems Department, Algoritmi Research Centre, University of Minho, 4800-058, Guimarães, Portugal
Keywords: Business Intelligence, Customer Relationship Management, Data Mining, Data Warehouse, on-Line
Analytical Processing, Student Relationship Management.
Abstract: The promotion of the students’ success is usually associated to the closely monitoring of the students’
activities. This requires the implementation of mechanisms that, in the scope of the teaching/learning
process, allow the students’ academic activities monitoring, the students’ academic success/failure
evaluation and the teacher/tutor approximation to the students’ day-by-day academic activities. Although
important, the activities involved in these processes do not take place in many higher education institutions,
due to the lack of an appropriate support. To sustain these complex processes and activities, a conceptual
framework and a technological infrastructure was proposed and integrated in a Student Relationship
Management (SRM) System. The SRM System supports the SRM concept and practice and it has been
implemented using concepts and technologies associated with the Business Intelligence systems. To validate
the SRM System, several application cases were implemented in real contexts. They demonstrated the
system relevance in the process of acquisition of knowledge about the students and their academic
behaviours. The system supports the decision making process in the teaching/learning scope and facilitates
the automatic interaction with the students. The impact of the several undertaken actions are presented and
analysed in this paper.
In the generality of the Portuguese Higher Education
Institutions there still exists a high rate of failure and
abandon, mainly in the first year of the graduation
courses. Some statistical result can be seen in the
official web page
Several actions have been undertaken by the
institutions to identify and to analyse the reasons of
failure, and to propose actions to invert this trend
(Nóvoa, Curado and Machado, 2005, 2006). One of
the actions largely accepted as a way to promote the
students’ success is by implementing mechanisms
that allow the students closely monitoring, the
evaluation of their success/failure and the day-by-
day academic activities approximation by the
teacher/tutor (Pile and Gonçalves, 2007) (Pereira,
Motta and Vaz, 2006). However, the implementation
of all these tasks does not take place in many
institutions. Among the reasons, we point out the
huge number of students with failure in the first
graduation year, the huge number of new students in
some courses and the work overload of the teaching
staff, once they are involved in lecturing,
researching and management tasks. It is required the
definition of institutional practices and an adequate
technological support to these practices. To
overcome these conceptual and technological
limitations, in this work it is developed a conceptual
framework which includes a concept, a practice and
the technological infrastructure that supports the
concept and the practice. The conceptual framework
and the technological infrastructure are in this work
integrated in a Student Relationship Management
(SRM) System. To validate the SRM concept and
practice it was adopted a methodology based on the
Grounded Theory principles. To validate the SRM
system it was adopted a methodology which includes
Piedade M. and Santos M. (2010).
In Proceedings of the 2nd International Conference on Computer Supported Education, pages 46-52
DOI: 10.5220/0002793300460052
the prototype implementation and the development
of a set of application cases in real contexts. The
concretization of the application cases demonstrates
the SRM system relevance and usability in the
students’ knowledge acquisition process, in the early
identification of failure situations, in the decision-
making support in the scope of teaching/learning
processes and in the automatic interaction with the
students. The results of the implemented actions and
their impact are also presented and analysed in this
This paper is organized as follows: Section 1
summarizes the motivation for the SRM system
proposal; Section 2 includes an overview of the SRM
principles and presents the SRM concept and
practice (as it was understood in this work) and the
adopted methodology to their validation; Section 3
describes the SRM system architecture and gives
some details about the SRM system implementation.
It also describes the methodology adopted for the
SRM system validation; Section 4 describes the
application cases, analysing the impact, on the
students’ behaviour, of the several actions that were
carried out under the principles of the SRM practice;
Section 5 concludes mentioning the advantages of
the SRM system and summarizing some upcoming
tasks for future work.
The SRM system was inspired in principles
associated to the Customer Relationship
Management (CRM) systems. In short, a CRM
system is used in a business environment to support
and manage the relationship between the
organization and their customers. These systems
help to translate customer information into customer
knowledge. This customer knowledge is obtained
using the information and business transactions
available in the organizational databases. Supported
in this customer knowledge, the organization defines
strategies/activities/actions able to maintain a
stronger relationship with clients. Values like
reliance, fidelity, loyalty and durability are present
in this relationship (Payne, 2006).
The SRM system is based on the principles
described above, but supports mainly activities
related with the students and associated with the
teaching-learning processes. Underlying to the SRM
concept is the scholar success promotion, as it is
widely accepted that there exists a high correlation
between the closely monitoring of the students and
their academic success.
To exemplify the similarity between the
CRM/SRM actions, it is possible to compare the
actions developed by the customer’s manager, that
on the scope of the banking activity alerts the
customer when he/she exceeds his/her credit
account, and the actions developed by the student’s
tutor/teacher, that on the scope of the monitoring
processes sends an alert message to the student when
detects that he/she misses several lessons.
The “Student Relationship Management or SRM
or CRM in Higher Education” terms were already
used in technological/commercial environments to
refer solutions mainly dedicated to support processes
related with the students in academic areas
(students’ management information, courses and
lessons management, admissions management,
enrolment and registration management) and areas
related with available services (communications,
marketing, financial aids, accommodation) among
others (Fayerman, 2002). Moreover, these solutions
do not make possible trailing the academic path of
the students in activities concerned with the
teaching-learning processes.
In the scope of this work, it was proposed a
concept, the SRM concept, focused on the students’
academic success promotion. The SRM concept is
understood as a process based on the students
acquired knowledge, whose main purpose is to keep
an effective student-institution relationship through
the closely monitoring of the students and their
academic activities. This concept, as already stated,
was based on the premise that there exists a strong
correlation between the closely monitoring of the
students’ academic activities and their academic
success promotion. The SRM practice is defined as a
set of activities or actions that should guarantee the
student individual contact, and an effective,
adequate and closely monitoring of his/her academic
performance. To validate the SRM concept and the
set of activities included in the SRM practice, a
research methodology based on the Grounded
Theory principles was adopted. It included the
concretization of a set of interviews (Hansen and
Kautz, 2005). The selected interviewers were
teachers with institutional responsibilities (courses
directors, institution directors, council members).
Each interview was recorded, transcribed and
analysed. The interviews analysis process was done
following the Grounded Theory principles and
supported by the NVivo software (a Computer
Assisted Qualitative Data Analysis Software)
(Budding and Cools, 2007). Each interview was
guided by a script, prepared beforehand, including
also open questions (semi-structured interviews).
The interview questions included topics like:
academic success/failure, activities to promote the
success, student-institution relationship, practices to
maintain an effective student-institution relationship,
monitoring indicators, behaviour patterns,
identification of activities that can be automatically
supported, among others (Piedade and Santos,
The SRM system is the technological infrastructure
that supports the SRM concept and the set of
activities integrating the SRM practice. To undertake
an SRM practice it is necessary: (i) to have
adequate, consistent and complete information about
the students. This information must be stored in an
appropriate data repository, maintaining a single
view of the students’ data; (ii) the analysis of such
data in order to obtain knowledge about the students
and their academic behaviour; (iii) the trigger of
automatic actions over the students whenever
specific situations or behaviours are detected; and
(iv) the assessment of the impact of the undertaken
actions over the students.
The structural topics related with i) and ii)
require the implementation of a data warehouse
system and its exploration using data analysis tools.
Based on this, the SRM system is implemented using
the technological infrastructure that traditionally
supports the Business Intelligence systems, once
these systems combine data gathering, data storage
and knowledge management with analytical tools to
present integrated and useful information to support
the decision making process (Negash and Gray,
With respect to the issues related with iii) and
iv), the set of relevant indicators and the behaviour
patterns that characterize the different situations to
supervise were identified, as well as the actions to be
automatically done by the different participants in
the SRM practice (teacher, tutor, course director)
were defined and implemented. After the
implementation of a set of actions, their impact on
the students’ academic behaviour and their final
assessment results were analysed.
3.1 Architecture
The SRM system architecture aggregates four main
components: the Data Acquisition and Storage
component, the Data Analysis component, the
Interaction component, and the Assessment
component (Figure 1). The Data Acquisition and
Storage component is responsible for storing the
students’ data in a data warehouse. Data from
different data sources were gathered and were
submitted to the ETL process (Extraction,
Transformation and Loading). The Data Analysis
component, responsible for obtaining knowledge
about the students, includes appropriate data analysis
tools that allow the patterns identification. The
obtained knowledge was stored in an adequate
knowledge database. The Interaction component is
responsible for maintaining an adequate and
effective relationship with the student, using the
obtained student’s knowledge. A set of actions are
automatically triggered (with the students as target)
when it is verified a specific situation or behaviour.
The Assessment component is responsible for the
assessment of all the carried out actions and their
impact, through the monitoring of the students’
academic behaviour and, also, through the
verification of different rates (assiduity, marks, and
interactions with the e-learning platform).
Data Analysis
Data Aquisition and
External sources
Analysis Tools
ETL(Extraction, Transformation, Loading)
Data Warehouse
Data Mining Statistical Visualization Reporting Querying
Technological Tools
Actions Definitions
Tutor Teacher
Course Director
Actions Execution
Students Group
Monitoring and assessment
Monitoring Assessment
Knowledge database
Technological Tools
Statistical Analysis Visualization Reports
Course Director
Figure 1: The SRM system’s architecture.
CSEDU 2010 - 2nd International Conference on Computer Supported Education
3.2 Implementation
The SRM system prototype implementation has been
done using database management tools, Business
Intelligence tools and web development tools.
Considering the context in which this work takes
place, the selected development tools integrate the
Microsoft environment: SQL Server Business
Intelligence Development Studio (MSqlServerBIDS)
and Visual Studio .NET. The first one includes a set
of integrated components, Database Engine,
Integration Services, Analysis Services, Reporting
Services and Notification Services for developing
and managing Business Intelligence solutions
(Mundy, Thornthwaite and Kimball, 2006), and the
second one includes a set of development tools for
building ASP.NET web applications.
3.3 Validation
To validate the SRM system, a prototype was
implemented. This prototype shows the relevance of
the SRM concept and supports the SRM practice.
After the prototype implementation, demonstration
cases were carried out in real higher education
An application case implementation includes the
following tasks: (i) scenario identification; (ii) data
acquisition and storage; (iii) data analysis; (iv)
interpretation of the obtained results; (v) actions
definition; (vi) execution of the automatic actions
over the students; and (vii) impact assessment of the
carried out actions.
4.1 Application Case Description
As already mentioned, application cases were
undertaken in real contexts of Portuguese Higher
Education institutions. Due to the huge complexity
and diversity of processes related with the students
and having in attention that the “students’ academic
success promotion” is the main issue underlying this
project, this complexity and diversity was limited to
the teaching-learning process. In this application
case, it was selected a graduate course and one of its
curricular units/signatures. The relevant data were
identified and collected. These data include
information about the unit, the adopted teaching-
learning process, the adopted assessment method,
the developed activities, the students and their
interaction in the developed activities and in the
teaching-learning process. Afterwards, the data
warehouse model was designed, implemented and
loaded. The model follows a constellation schema.
Figure 2 represents the data warehouse model for
this application case.
Figure 2: Data warehouse model example.
The facts and dimension tables implementation
was supported by the Database Engine component.
The loading process followed the ETL process steps,
in which the relevant data were extracted from the
source databases, were cleaned (when errors in data
were detected) and were transformed in order to
accomplish the data warehouse format. The loading
process was supported by the Integration Services
component. The data warehouse exploration was
been done using OLAP and data mining techniques.
This data analysis process was supported by the
Analysis Services component.
OLAP techniques allow the analysis of the data
under different perspectives, using the
multidimensional structure of the data warehouse
model. Several cubes were created to analyse the
correlation between the different facts (for instance,
classes presences, e-learning platform accesses, and
results assessment) and also the influence of the
different attributes related with the student (for
instance, full-time/worker-student, registration year,
admission phase, assiduity type). Figure 3 shows an
example of a cube extract. More details about this
cube can be found in (Piedade and Santos, 2009a).
Data mining techniques allow identifying
models that exhibit patterns and trends in data. In
this particular case, the data mining main purpose
was to identify the students’ profile in order to
decrease the failure rate and the failure risk in future
unit editions. A classification task was implemented
to find a model that describes the predictable
attribute as a function of the input attributes. The
Figure 3: OLAP cube extract example.
classification task was carried out using a decision
tree algorithm.
One of the obtained models describes the mark
attribute as a function of the input attributes: phase
of admission to higher education (phase), students’
origin local (origin), theoretical classes assiduity rate
(theoretical) and unit interaction through the e-
learning platform (NumDays). Analysing the
obtained model, the students’ profile, considering
the mark results - Fail, Satisfactory, Good and Very
Good, was identified.
This process of obtaining students knowledge
follows the traditional steps of the knowledge
discovery in databases process: data selection, data
treatment, data pre-processing, data mining and
results interpretation (Fayyad and Uthurusamy,
Figure 4 shows the obtained model in a tree
form. Each tree node has a set of conditions that lead
to a specific decision. More details about this model
can be found in (Piedade and Santos, 2009b).
Figure 4: Data mining model.
OLAP and data mining analyses allow us to
verify that to decrease the failure profile it is
necessary to take special attention to the new
students differentiating them through the admission
phase and, also, by looking at origin local, since
several students are away from their familiar
The students that are at the first time in the unit
must be encouraged to go in a regular basis to the
different types of classes. These students are, in
many cases, influenced by older students that say to
them to avoid classes, mainly the theoretical classes.
For the second phase students, an additional
support must be given to them as they arrive to the
University when half semester has already passed.
Due to this situation, these students lose the initial
curricular contents explanation and the subsequent
curricular content comprehension, fact that could
help to explain their failure rate. For these cases, the
institution could adopt specific activities or
procedures, as extra classes or tutorial orientation,
providing them additional support. It is also
necessary, for all the students, to verify the evolution
of the project implementation, motivating the
students and providing them additional support
when necessary. This support can be achieved using
tutorial classes. This was not the case of the current
edition of the unit. In what concerns repeating
students, it is also necessary to motivate them to go
to the classes, although in many situations these
students have timetable incompatibilities. To
overcome this limitation, the institution could adopt
a differentiation in the schedule, like classes in the
morning for the first year students and in the
afternoon for the second year students. In
complement, it is also necessary to motivate the use
of the e-learning platform increasing the interaction
of the student with the unit. These different
situations need to be evaluated without neglecting
the students that present a “success profile”.
Regarding the students that are away from home, the
course director/coordinator must take a special
attention to these students, verifying if they have
some integration difficulties and providing them
additional support, if necessary.
The analysis of the obtained profile allows the
identification of the characteristics of the students
that fail the unit and also the ones that are approved
(positive marks) in the unit with satisfactory and
with good marks.
One of the actions identified to fight against the
fail behaviour is the presence of the students in
classes, as the students must go in a regular basis to
the different type of presential classes (theoretical,
practical and tutorial classes). This confirms that the
CSEDU 2010 - 2nd International Conference on Computer Supported Education
presences monitoring is one of the activities that
must be included in the SRM practice. Due to its
importance, this activity was already implemented
and is now supported by a web application.
The web application integrates several
functionalities related with the management of
several entities: the graduate courses, the curricular
units, the groups, the classes, the teachers, tutors, or
course directors, and the students. Figure 5 shows a
page view related with the classes presences. All the
information that could be used to identify a student
was omitted.
Figure 5: Classes page view.
As already mentioned, this application registers
the presence/absence of students in classes. An
automatic alert message is sent by email to the
students when they match certain behaviour (in this
case, a deviating behaviour related with class
The main purpose of this action is to alert the
students to the importance of their presence in
classes and to the need of a daily study.
An automatic email is also sent in a weekly basis
to the course director/coordinator and to the teacher
responsible by the unit, integrating a report with the
students’ presences. Through this process, the course
director/coordinator, and also the teacher, know how
the semester is going. In case of abnormal situations,
they can take the necessary actions to motivate the
students to be present in the classes. This procedure
also allows the detection of any problem related with
the students and that can affect their behaviour.
Figure 6 shows a view of the presences report.
Neither the student nor the institution is identified in
this example.
Figure 6: Presences report view.
The web application is now functioning by the
first time. A trial version was used on the second
semester of the 2008/2009 curricular year, during
the last five weeks. After this experience, it is
possible to confirm that the automatic e-mailing of
the alert messages has a positive effect on the
students’ behaviour, once their reaction is in general
to make a replay with a personal justification and,
also in general, they attend to the next classes.
The impact of these actions, in the students’
results (marks), could not be assessed with precision
due to fact that the web application operation was
available only during five weeks.
It is only possible to confirm that more students
were evaluated in the final exams, comparatively
with the previous curricular year. However, this
behaviour could not be associated, as a whole, to the
impact of the web application operation.
In this current curricular year (2009/2010), the
web application is already in operation (since the
beginning of the classes). It is expected, at the end of
the semester, the assessment of the results of the
undertaken actions.
Next steps in this project include: (i) the
implementation of other activities that integrate the
SRM practice and that enable the closely monitoring
of the students; (ii) the SRM practice assessment,
verifying its impact on the students’ behaviour and
on their final results.
With the implementation of the Bologna Process,
the number of contact hours between the teachers
and the students decreased. This requires, among
other things, greater student autonomy. In this
scenario, it is essential to design and to implement
mechanisms that facilitate the monitoring and the
supervising of the students’ academic activities and
that facilitate the interaction with the students. In
this context, we believe that the SRM concept and
practice implementation, supported by the SRM
system, create an advantage towards the students
success promotion, and, therefore, in the institution
success, ensuring an effective student-institution
The development of this project has occurred in
different stages. In the first stage, it was defined the
SRM concept and practice and, also, their validation
was carried out. It was also verified the lack of an
adequate technological support to the SRM concept
and practice (such as defined and understood on the
scope of this work). The second stage included the
structural framework definition and the SRM system
architecture proposal. The third stage includes the
SRM prototype implementation and validation. The
future work includes concluding the prototype
implementation and its validation.
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