NETWORKING BETWEEN LMS MOODLE AND EXTERNAL
APPLICATIONS
Mikuláš Gangur
Faculty of Economics, University of West Bohemia, Univerzitní 8, Pilsen, Czech Republic
Keywords: Prediction Market, LMS Moodle, SQL, PHP, Evaluation, Gradebook.
Abstract: The contribution introduces the use of a prediction market as a support tool in the educational process and
its networking with LMS Moodle. The prediction market FreeMarket has been running at the Faculty of
Economics as the part of the financial engineering courses. The quality of the predictions estimates depends
on the trade activity of the market participants. That’s why it’s necessary to motivate students to trade on
such a market. The paper presents one of the methods to increase the activity of students. The results of the
market trades form a supplement to the final students’ evaluation in the relevant courses in the form of
credits that are added to the total score of each student. FreeMarket points that students earn on the market
are transferred to the credits according to the declared rate. The interconnection between FreeMarket and
LMS Moodle is described together with the description of the process that transfers FreeMarket points to
LMS Moodle gradebook. These processes update the students’ assignment score automatically and
periodically. In the next the interconnection between LMS Moodle and application for exam report
generating is explained. Finally the technological solution of networking is described.
1 INTRODUCTION
The simulation game FreeMarket (FM) on the base
of virtual prediction market is presented in this
contribution. The main functionality of the system
consists mainly in predicting selected events or in
estimating parameters. A practical example of such a
market on the Faculty of Economics of University of
West Bohemia is introduced. The FM participants –
traders are especially students of the university. This
virtual market is a supplement to the financial
engineering courses at the faculty and it has become
one of the new approaches in education not only in
this type of courses.
LMS Moodle is not only system for management
and administration of education process, but it is
also very useful tool for student testing and student
evaluation (Cápay and Tomanová, 2010). LMS
allows evaluating of the assignments automatically
according to the tests results and manually by
teacher as evaluation of tasks in file uploaded by
students to LMS. LMS Moodle offers also the
offline activities of students. Teachers evaluate these
activities manually. The main purpose of this paper
is to describe the automation of this process on the
base of interconnection of LMS Moodle and external
application for student offline assignments.
The interconnection of the market with LMS
Moodle and students’ evaluation are described. This
motivation factor is very important as support of
students’ activities on the market and it is used for
improving the quality of predictions by increasing
the market liquidity. In the next the connection
between LMS Moodle and external application that
generates the exam reports with all relevant
information about activities of students is explained.
The problem of the networking between LMS
Moodle and external application is addressed in
(Sánchez and Bragós, 2007). The LMS Moodle is
used for access control, register and scheduling of
processes in remote experimental laboratories.
Similar problem is focused in (Sancristobal,Castro,
Harward, Baley, DeLong, Hardison, 2010) and
(Uran, Hercog, Jezernik, 2007). These works focus
on the use of LMS Moodle for access control or
booking to remote application. One contribution
solves the integrating of control mechanism of
remote application over web into LMS Moodle. The
mentioned contributions don’t solve the transfer of
the results from remote application to LMS Moodle
and their transformation to credits for student
271
Gangur M..
NETWORKING BETWEEN LMS MOODLE AND EXTERNAL APPLICATIONS.
DOI: 10.5220/0003958002710275
In Proceedings of the 4th International Conference on Computer Supported Education (CSEDU-2012), pages 271-275
ISBN: 978-989-8565-06-8
Copyright
c
2012 SCITEPRESS (Science and Technology Publications, Lda.)
evaluation. This paper describes the solution of these
problems.
2 PREDICTION MARKET
Prediction markets are speculative markets created
for the purpose of making predictions. Assets are
created whose final cash value is linked to a
particular event (e.g., the winner of the Czech
Parliament election will be the Civic Democratic
Party) or a parameter (e.g., the close value of PX
index on Friday 19/1/2012). Other names for these
markets are predictive markets, information markets,
decision markets, idea futures, event derivatives, or
virtual markets. The current market prices can then
be interpreted as predictions of the probability of the
event or the expected value of a parameter. People
who buy low and sell high are rewarded for
improving the market prediction, while those who
buy high and sell low are punished for degrading the
market prediction (PM, 2011).
Many prediction markets are open to the public.
Betfair is the world's biggest prediction exchange,
with around $28 billion traded in 2007. Intrade is a
for-profit company with a large variety of contracts
not including sports. The Iowa Electronic Markets
(I.E.M) is an academic market examining elections
where positions are limited to $500. This market was
opened in 1988 (IEM, 2011). The I.E.M. routinely
outperforms the major national polls. In the last four
presidential elections the I.E.M.’s election-eve
predictions were off by an average of just 1.37 per
cent.
Other prediction market, the Hollywood Stock
Exchange, which allows people to speculate on the
box-office returns, opening-weekend performance,
and the Oscars, has also been prescient. Traders’
predictions of the opening-weekend returns are more
accurate than the movie industry’s forecasts, and the
Exchange has done a good job of foreseeing
nominations as well. Last year, its traders correctly
predicted thirty-five of the forty Oscar nominees in
the top eight categories. The participants of these
markets also “decided” the results of the Iraq war
and the Sadam Hussain’s destiny. (Surowiecki,
2003)
Why do decision markets work so well? They are
extremely efficient at aggregating information and
tapping into the collective wisdom of a group of
traders, and groups are almost always smarter than
the smartest people in them. As in financial markets,
the incentive to get the better of others (whether the
reward is profit or mere satisfaction) causes traders
to seek out good information. The absence of
hierarchy - markets don’t have vice-presidents -
insures that no single person has too much influence
and that diverse viewpoints don’t get shut out.
(Surowiecki, 2003)
2.1 FreeMarket – Prediction Market
on University of West Bohemia
An electronic prediction market under the name of
FreeMarket (FM) has been running at the Faculty of
Economics, UWB in Pilsen, since November 2007
(FM, 2012). To this time 1600 users are registered
and around 450 of them, participants of financial
courses, are registered in each of the fall semesters
2009/2010, 2010/2011, 2011/2012. The shares are
divided into 4 areas:
• Politics
• Sport
• Entertainment
• Economics
The portfolio of each of the participants was
composed by an endowment of 5,000 credits (money
units, points) when registering or 10,000 credits
when he/she passes the final exam to become an FM
broker and receives an FM broker concession
number. The applicant can pass the exam together
with practical training of trading in an e-learning
course that is a supplement to the FM system.
The login to FM runs under the common
university single sign-on system. This system
ensures the creation of just one trading account for
each student and this way it prevents students from
creating the “black” trading. In the past this system
was not used and the control mechanism detected
several students that had created “black” accounts to
receive more starting points from each of those
accounts and then they transferred the points to their
official account with the help of illegal trade.
3 NETWORKING BETWEEN FM
AND LMS MOODLE
From fall semester 2009/2010 the FM system was
interconnected with the LMS Moodle. The reasons
for this connection are to increase student motivation
and to prevent some students from “black” trade
realization. The connection to LMS belongs to the
incentives of FreeMarket, proposed and
implemented by the author of this paper.
In the first case thanks to this connection the
students could transfer their earned points to
engineering courses credits in announced rate
CSEDU2012-4thInternationalConferenceonComputerSupportedEducation
272
Figure 1: Interconnections between LMS Moodle and external applications. (Source: own)
(1:5000 for inclusion and 1:10000 for exam). The
credits are put as evaluation of offline assignment in
the course. These points help to students to reach
inclusion and also were added to final result of exam
as additional credit. The students can set the amount
of transfer points in any time during semester. The
whole process is automatic without any intervention
of course teacher.
The connection to LMS Moodle with the
relevant courses allows also control the number of
created account. Every participant of FM has to be
enrolled in selected courses in LMS Moodle and
then can create only one account. The connection
between FM and LMS Moodle is shown in Figure 1
together with interconnection LMS Moodle and
external application for summarizing information
about students for exams reports.
3.1 A Practical Example of Credits
Calculations
In the relevant LMS Moodle courses two artificial
offline assignments were created
• FreeMarket credits FMC
• Bonus credits to exam BCE
The following formulas calculate the
Aggregation Course Total (ACT) of all the course
assignments credits and Bonus credits to exam
(BCE). It uses one of the useful features of LMS
Moodle consisting in defining calculation for the
gradebook by means of a math formula. The formula
follows the pattern of formulas/functions in popular
spreadsheet programs. The process of evaluating the
whole course with respect to the values of all the
course assignments (AS-n) and FMC is proposed
and implemented in LMS Moodle.
ACT=sum([[AS1]];….;[[AS-n]]; [[FMC]])
/200*100
(1)
BCE=max([[FMC]]-max(180- max(180-sum
([[AS1]];…;[[AS-n]]);0);0) *5000/10000
(2)
180 credits out of 200 credits is the minimum
amount of credits for students to become eligible for
the course. 5000 is the transfer rate for the bonus
inclusion credits and 10000 is the transfer rate for
the bonus exam credits. The ACT and BCE are parts
of the final course report of each student and serve
as basic documentation for the final course exam.
They are processed automatically by another
application (exam_report, ER) activating by teacher
that selects demanded exam term. This application
first of all connects to university information system
(STAG) and generates the list of students on
demanded exam term. Then ER connects to
gradebook of relevant courses in LMS Moodle (see
Figure 1) and it reads ACT and BCE values for
every student on generated exam list. According to
these values the ER determines information about
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273
students’ inclusions and calculates bonus points for
exam.
3.2 Technological Solution of
Applications Networking
The transfer of credits from FM participants’
accounts to gradebook of LMS Moodle is realized in
two steps.
In first steps student determines the amount of
points (money) that has to be transferred to LMS
Moodle. He/she fills the web form with the number
of credits and by this way activates the process that
controls student’s money account and rounds the
points with respect to ratio 1:5000. Then this process
saves the points to database table fm_users with all
information about participants and adds it to the total
amount of all previous transferred student points.
Finally it sets up the flag for transfer to 1.
The second step is processed by php script
points2moodle that is activated in cron process one
time per day. The script selects all users’ profiles
with transfer flag equal to 1 and then transfers total
amount all transferred points to student gradebook of
relevant course as a value of offline assignment
FMC. (see section 3.1).
Described transfer is processed with help of SQL
commands Select, Insert and Update. First of all the
Select command selects assignment id for relevant
course id and assignment name ‘FMC’ in Moodle
table grade_items. Next Select command finds the
gradebook of given user from the table
grade_grades according to the user id and
assignment id. Then the new record is inserted to the
table grade_grades if it is processed for the first
time and the gradebook record doesn’t exist for the
user and assignment or the existing record is updated
by new FMC value. In both described cases the new
record is inserted to the table grade_grades_history
that archives information about grade changes.
Finally the script regrade is activated to
recalculate ACT value (see section 3.1) for course
and every student. The script selects the values of all
assignments for user id and course id from the table
grade_grades and grade_items. Some of
assignments are calculated items (ACT, BCE). In
case of these items the process has to evaluate the
item value according to the calculation prescription
that is saved in the table grade_items. At the end the
values of all assignments are summarized according
to the final grade ACT calculation prescription and
the ACT value is set in the table grade_grades. This
value is important for next generation of exam report
in such it shows the student course inclusion.
The exam report generation is implemented as
connection to the university information system via
web service and as a connection to LMS Moodle
table grade_items and grade_grades. The
exam_report script determines the list of exam dates
via web service from university IS. Teacher can
select demanded exam term and the process requests
the list of students enrolled on exam again via web
service from IS. Then the script connects to LMS
Moodle database and it finds out ACT and BCE
assignment id for every student on list from
grade_items table and the ACT and BCE values are
determined from grade_grades table. The final
output of whole process is a table of all students on
exam term with collected information and empty
fields for exam results. This table is generated in
HTML code and it is published on web page or it is
generated as CSV file for importing to spreadsheet
application.
4 CONCLUSIONS
LMS Moodle offers several types of assignments.
One of them is offline assignment that is evaluated
and the credits are set manually by teacher. The
contribution shows the possibility of the networking
between external application, where students process
their assignments, and LMS Moodle. The functional
transfer of credits from external application to
gradebook of LMS Moodle is described as well as
the networking between reporting application that
utilizes information from LMS Moodle, is presented.
This online interconnection between applications
and every day possibility to watch results in LMS
Moodle supports students’ activities.
The interconnection and networking are realized
with straight access to LMS Moodle database tables.
The transfer of credits can be realized with import
utilities that are implemented in LMS Moodle. But
in such case it is needed to load Moodle libraries to
external host and application. Another solution is
development of universal web service server as the
part of LMS Moodle (Al-Ajlan and Zedan, 2008),
(Casany, Alier, Conde, 2009). The external
application code for credits transferring would be
simpler than current solution.
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