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104 Ahmed Ezz Awad
International Journal of Innovations & Advancement in Computer Science
IJIACS
ISSN 2347 – 8616
Volume 6, Issue 5
May 2017
Automatic Generationof Physics Questions Banksat KAU
Ahmed Ezz Awad
Faculty of Science,
King Abdulaziz University, Jeddah, KSA
ABSTRACT
Faculty of Science, King Abdul-Aziz University establishes its e-learning framework. The heart of this framework is the
questions banks. These frameworks are used to develop questions banks for varieties of faculty’s courses in different
areas: physics, biology chemistry, mathematics, statistic, biochemistry, and astronomy. This paper explains the
methodology that uses to automatethe generation process of question bank for Physics courses. The methodology
supports different types of Physics questions. This paper focus on the generation of the problems questions by altering
variables in Physics equations. The main result of this work is the developing of three successful questions banks for
three physics courses (Phys. 110, Phys. 202, and Phys. 203) in KING ABDULAZIZ UNIVERSITY (KAU). The faculty
develops electronic exam and interactive training systems that use the generated banks. These using prove that the
generated questions banks are reliable and scalable.
Keywords: questions banks, concept questions, problem questions.
1. INTRODUCTION
The Faculty of Science King Abdul-Aziz
Universityaims to build an Integrated Educational
System(FSIDS) that includes explanation, training
and electronic exams together. One of the most
important part of FSIDS is the questions banks. The
electronic examinations system and Interactive
training use the generated questions banks. Number
of interactive trainings for varieties of faculty’s
courses in different areas: physics, biology;
chemistry, mathematics, statistic, biochemistry, and
astronomy are developed and published [1]. The
details of the FSIDSis out of scope of this paper.
This paper discussestheprocessing of automatically
generate questions-banks in physic domain. The
paper introduces the used methodology and
methods to generate the banks. The developed
methods meet the requirements of different types of
Physics questions.
The question bank covers three levels of
knowledge: apply, understand and remember [2].
The problems solving questions can measure the
apply knowledge. The concept questions can
measure the understanding and remembering
knowledge. Therefore, the paper handles two main
types of Physics questions: concept and problem
solving.
The concept questions can be handled using pre-
defined templates [3]: “All possible questions are
generated by parameterized concepts from a set of
pre-defined templates.”
The problem solving questions are difficult and has
many challenges: solving method, Scientific
notation, physic units, vectors notation, figures,
physic symbols, and generating alternative options.
The main challenge is how to describe and evaluate
the solving method of the given problem.
Scientific notation refers to expressing a number as
a product of any number between 1 and 10 to the
10th power. There are needs to write an algorithm
for handle too large or too small values in results,
also to handle scientific notation data input in the
given problem. The scientific notationhas two main
parts: mantissa, and exponent. Mantissais the
integer or first digit in any scientific notation.
Exponentis the small number to the right of the 10
in scientific notation. For example in 5.3 ×106, the
mantissa is the "5" and the exponent is “6”.
Negative exponent indicates that the number is a
fraction (less than one) [4].
Learning how to measure the physics quantities is
the main objective of discovering the physics. Each
quantity has its unit, for example, meter (m) is the
unit of the quantity length. There are two main
105 Ahmed Ezz Awad
International Journal of Innovations & Advancement in Computer Science
IJIACS
ISSN 2347 – 8616
Volume 6, Issue 5
May 2017
types of units: International Standard (SI) units and
SI derived units that are defined in terms of SI units
[5]. The physical quantity can be expressed in
different units, for example, the time unitsare:
second, minute, and hour. The problem may
contains different units, for example, the problem
has speed m/sec, and time in hours, to calculate the
distance in kilometer. In this case, there are needs to
use conversation factor [5].
Avectorhas magnitude and direction [5], therefor;
there are needs to specials calculations to handle the
vector operations.
Figures play excellent roles in many physical
problems. The figure describes the problem
situation. With a huge number of questions, each
question associated with a figure,there are needs to
construct different figures for each generated
question, so the mange of the generated figures are
complicated and they need more spaces as storage.
The physic symbolsare used widely in physic
questions and answers. These symbols can handled
either be storing them as figures or writing them
using Unicode.
The multiple-choice question (MCQ) has more than
one options. One of them isthecorrect answer and is
achieved by applying the solving method on the
problem’s parameters values. Other options are
called alternative options. With manual entering
questions and answers, the instructor enters the
question’s text, the correct answer, and the
alternative options. The instructor uses his mind in
deciding the values of alternative options. With
automatic generation of questions, the constructing
of alternative options needs special processing to
get related values with correct answer.
This paper presents the using of pre-defined
templates [3] to generate the concept questions. In
addition, it introduces the formal definitions of the
problems questions and explains the algorithms that
provides solution to automatic generation of
problems questions. The resultis the generationsof
huge of questions in physic question bank.
The authors of [6] presents a feature called scalable
exams that means: “automatic generation of a large
number of different exams in order to provide an
individual test to each student”.
This aim of this paper is to satisfy this feature that
feature enables us to provide:
Huge number of questions in online
asynchronous training courses
Dissimilar exams in the same level.
Theremainder of this paper is organized as follows:
Section 2 discusses the related work. Section
3presents generating of concept questions. Section 4
introduces generating of problem questions.In
Section 5, the experimental work and evaluation.
Section 6concludesthe paper with a summary.
2. Related work
This section presents related work on question
generation and its features.
Research [3] presents a systematic template and its
algorithms that designed for automatically
generated of questions bank. It introduces a system
that:
1. Allows the instructor to describe the
learning contents
2. Generating the corresponding multiple
questions.
3. Allowing the students to use the generated
questions in education process.
The authors of [6]provides a framework (exams) for
automatic generation of standardized statistical
exams and associated self-study materials which is
especially useful for large-scale exams.
Research [7] developsa system for mathematical
tasks generation and it is implemented in Matlab.
The system consists of two subsystems that work
together: generator and problem solver. The solver
is a function with a variable number of the input
parameters depending on a particular problem. The
generator allows automatic generation of “suitable”
input data on the basis of the designated rules. The
generator output is input data collection and the
output of solver is the collection of requested output
data.
Generating questions with multiple variables on
Directed Acyclic Graph (DAG) knowledge
structures is introduced in [8]. The research
develops algorithms that are guaranteed to generate
questions that are solvable. A credit assignment
method is applied to control the complexity of the
generated questions. Theproposed approach is being
applied to several subjects: physics, electronics,
computer architecture and computer networking.
The research [9] presents a system and a set of
strategies that can be used in order to automatically
106 Ahmed Ezz Awad
International Journal of Innovations & Advancement in Computer Science
IJIACS
ISSN 2347 – 8616
Volume 6, Issue 5
May 2017
generate multiple choice questions from Semantic
Web Rule Language (SWRL) rules. The proposed
system converts SWRL rules into natural language
multiple-choice questions, in addition, it provides
techniques for generating the appropriate distracting
answers.
A system that can automatically generate factual
questions is presented in [10]. The research presents
a discussion of the computational and linguistic
challenges that arise in automatically generating
factual questions for reading assessment such as:
MappingAnswerstoQuestionWordsandPhrases
The research [11] presents an intelligent learning
environment' ILE that implements the computer-
supported collaborative work model to automatic
authoring of the self-tests for student evaluation.The
research develops a prototype automatic generator
of ac circuit exercise. This prototype proves that the
proposed approach could be used for test and
exercises in any field of science and engineering
involving quantitative analysis.
3. Generating Concept questions
This work uses the algorithms in [3] -that presents
two types of questions Concept Definition,Correct
or wrong options- to generate different types of the
concept questions in physical domain.This work
uses the two types of questions and its algorithms.
This work uses the algorithm
“onlyOneSoultion”togeneratethe “Correct and
Wrong Options” type of questions. In addition, it
uses the algorithm"termsdefinitions"to generate the
“Concept Definition Question” type of questions.
3.1Correct or wrong optionsquestion(CWOQ)
Table 1shows this example; the question text is ask
about scalar quantity, states “which of the following
quantities is a scalar quantity?” There are six
correct answers and six wrong answers.
Table 1: CWOQ example
Questions:Which of the following quantities is a
scalar quantity?
Correct answer list Wrong answers list
1) Time
2) speed
3) distance
4) Mass
5) Energy
6) Power
1) force
2) Velocity
3) displacement
4) acceleration
5) gravitational
force
6) weight
Due to the restriction of using “none of the above”,
“all of the above”, and “twoSolutions” options, the
algorithm generates only 120 versions of
questions.Figure 1shows sample of the generated
questions
Figure 1: samples of CWOQ generated questions
3.2 Example of Concept Definition (CD) question
Table 2shows example that contains links between
four quantity and its units. The engine will produces
two types of questions: in the first one gives the unit
and ask about the quantity, and in the second gives
the quantity and ask about the unit.
Table 2: CD example
Question: In the International System of Units
quantity unit
Mass Kg
Time second
Length Meter
Force Newton
The algorithm generate eight different questions.
Figure 2 shows the generated questions.
1) Which of the following quantities is a scalar quantity?
A) displacement
B) Velocity
C) time
D) force
2) Which of the following quantities is a scalar quantity?
A) Velocity
B) time
C) force
D) acceleration
119) Which of the following quantities is a scalar quantity?
A) gravitational force
B) Power
C) displacement
D) weight
120) Which of the following quantities is a scalar quantity?
A) gravitational force
B) acceleration
C) weight
D) Power
107 Ahmed Ezz Awad
International Journal of Innovations & Advancement in Computer Science
IJIACS
ISSN 2347 – 8616
Volume 6, Issue 5
May 2017
Figure 2: samples of CD generated questions
4. Generating Problem questions
This type of questions is a complicated type and it is
varied. The items of the problem question are:
1- Question Text that includes parameter variables
2- Definition of the parameter variables
3- Define the solution as equation(s) of the defined
parameter variables
4- Define the solution conditions if any
5- Define the alternative options to be nearest the
exact solution.
The problem can be defined as:
Problem = (N, T, P, O, C, A)
Where:
N: the name of the problem that is used as index for
this problem.
T: is a finite set of problem's texts. The text is the
head of the generated question. The problem
definition contains multiple texts although the
parameters and the required of the problems are the
same, to generate different questions with varied
texts. Each text includes two parts: the fixed part
that is constantly displayed in all generated
questions from this definition, and the changed part
that is the parameters names; in each generated
question, at least one value of the parameters is
changed. The changed part is included inside the
fixed part. So the parameter is written between <>.
P: is a finite set of problem's parameters where the
definition of each parameter is:
(name, type, [(lower limit, upper limit, step)], [legal
values])
The name represents parameter's name that is
written in both the head of the question and in
output definition.
The type may be integer; real; or string. If the type
of parameter is integer or real, the lower and upper
limits, and the step must be given. The generation
process uses a loop that starts from lower value and
steps by the step value till it reaches to the upper
value. If the type of the parameter is string, the legal
values of the parameter must be given. The
generation process defines array of string with
length equal to the numbers of legal values and it
uses loop from 1 to the numbers of legal values.
O: is a finite set of problem's outputs; the most
problems contain only one output. The definition of
each output is:
Output = (name, type, method, unit)
The type may be integer or real. The method is the
mathematical equations for determine the value of
the output. The unit to be written beside the result
C: is a finite set of problem's conditions; this set
may be empty if there is no condition in the
problem generation.
A: contains the method of how to determine the
alternative options. We have three alternative
options. The type of these options is the same as the
type of the output. There are two ways to assign
values for these options: the first one is a random
selection by adding or subtracting three numbers to
the outputs, these numbers ranges must be given in
the definition. The second method is to write
specific method for each option as written in the
output definition.
4.1 Problem question example
1) In the International System of Units, kg is the unit of
A) Length B) Force C) Time D) Mass
2) In the International System of Units, second is the unit of
A) Force B) Length C) Time D) Mass
3) In the International System of Units, meter is the unit of
A) Mass B) Length C) Force D) Time
4) In the International System of Units, Newton is the unit of
A) Force B) Mass C) Time D) Length
5) In the International System of Units, the unit of Mass is
A) meter B) second C) Newton D) kg
6) In the International System of Units, the unit of Time is
A) Newton B) kg C) meter D) second
7) In the International System of Units, the unit of Length is
A) kg B) Newton C) second D) meter
8) In the International System of Units, the unit of Force is
A) meter B) kg C) Newton D) second
108 Ahmed Ezz Awad
International Journal of Innovations & Advancement in Computer Science
IJIACS
ISSN 2347 – 8616
Volume 6, Issue 5
May 2017
Figure 3shows the formal definition of physic
problem for determine the work done to stretching a
spring. There are two inputs: restoring force (f) and
distance of stretching a spring (d). The range of (f)
is varying from 5 to 20 N, and the range of (d) is
varying from 0.1 to 0.9. The problem uses the
formula work = ½ force * distance.
Where (f) is varying from 5 to 20, i.e. there are 16
possible values of (f), and where (d) is varying from
0.1 to 0.9 with step 0.05, i.e. there are 16 values of
(d), therefore the number of generated questions =
16 * 16 = 256 questions.
Figure 3: XML-based formal definition of spring
problem
Figure 4: Sample of generated questions Error!
Reference source not found.
Figure 4shows samples of the generated questions.
<problem>
<name>workOfSpring</name>
<text>If the restoring force is <f> N, Then thework done in
stretching a spring, a distance of<d> m is __ </text>
<parameters>
<parameter>
<pname> f </pname><type>integer</type >
<lower>5</lower ><upper>20</upper><step>1</step>
</parameter>
<parameter>
<pname> d</pname><type>real</type >
<lower>0.1</lower ><upper>0.9</upper><step>0.05</step>
</parameter>
</parameters>
<output>
<name> w1 </name><type>real</type >
<method> 0.5 * f * x </method><unit> J</unit></ouput>
<altrnatives>
<a1><determine> 0.5 * f * x * x * x </determine></a1>
<a2><determine>random </determine>
<para> output </para><value> + 0.4</value>
<value> + 0.2</value></a2>
<a3><determine>random </determine>
<para> a1 </para><value> + 0.3</value>
<value> - 0.2</value></a3>
</altrnatives>
</problem>
1) If the restoring force is 5 N, Then the work done in
stretching a spring a distance of 0.1 m is ___________
A) 0.15 J
B) 0.25 J
C) 0.003 J
D) 0.202 J
256) If the restoring force is 20 N, Then the work done in
stretching a spring a distance of 0.85 m is ___________
A) 8.5 J
B) 6.341 J
C) 6.141 J
D) 8.4 J
109 Ahmed Ezz Awad
International Journal of Innovations & Advancement in Computer Science
IJIACS
ISSN 2347 – 8616
Volume 6, Issue 5
May 2017
Problems with scientific notation are more
complicatedtogenerate.Figure 5 show problem that
has input which expressed in scientific notation, in
addition the results expression in scientific notation.
Figure 5: Problem with scientific notation
In this case, we use two algorithms:
scientificNotationToReal and
RealToscientificNotation. The
scientificNotationToRealconvertsthe value that
expressed in scientific notation into real values by
using the mantissa and exponent in the expression.
The RealToscientificNotationconverts the valuesin
real value to scientific notation by evaluate the
mantissa and exponent from the real value and write
the resulted expression.
Problems that contains figure need special
processing. Figure 6 show sample of generated
question that includes figure.
Figure 6: Problem with figure
In this case, the system uses only one figures for all
generated problems and write variable inside figure
as input for the problem. In this example, the d1 and
d2 are in inputs in problem text. This solution
reduces the space required to store the figures and
the complicated generation of figure for each
questions.
5. EXPERIMENTAL RESULTS
The results of this work is the developing question
banksfor three physics course at Faculty of Science,
King Abdulaziz University (KAU): Phys. 110,
Phys. 202, and Phys. 203. Table 3shows the
summary of the questions bank of Phys. 110. The
bank contains 14 chapters with 179 sub topics and
977809 questions.
Table 3: Questions bank of Phys. 110 course at KAU
Section
Number Chapter Name subtopics
Generated
questions
1 Measurements 18 6756
2
2.1 Constant
Acceleration And
Constant Velocity
20 8418
3
2.2 Instantaneous
Velocity And
Acceleration
8 4444
4
2.2 Average Velocity
and Acceleration And
Speed
12 8426
5 2.3 Position And
Displacement 9 6341
6
2.4 Constant
Acceleration And
Constant Velocity 2
25 14995
7 3.1 Vectors 13 16137
8 3.2 Vector Position and
Displacement 8 4269
9
3.3 Average Velocity
and Instantaneous
Velocity
4 5036
10
3.4 Average
Acceleration and
Instantaneous
Acceleration
4 3564
11 4. Projectile Motion 13 1458
12 5. Force 28 15435
13 6. Friction 4 2571
14 7.Work and Energy 13 14494
1) A uniform electric field of 25 N/C makes an angle of 25°
with the dipole moment of an electric dipole.If the torque
exerted by the field has a magnitude of 2.5 x 10-7N.m, the
dipole moment must be:
A) 2.37 × 10-8C.m
B) 2.37 × 10-7C.m
C) 0.07 × 10-8C.m
D) 0.07 × 10-7C.m
In the given Fig., particle 1 of charge +4e is above a floor by
distance d1 = 2.00 mm and particle 2 of charge + 6e is on the floor,
at distance d2 = 6.00 mm horizontally from particle 1. What is the
x- component of the electrostatic force on particle 2 due to particle
1?
A) 1.31 × 10-22 N/s
B) 1.31 × 10-23 N/s
C) 3.52 × 10-23 N/s
D) 3.52 × 10-22 N/s
110 Ahmed Ezz Awad
International Journal of Innovations & Advancement in Computer Science
IJIACS
ISSN 2347 – 8616
Volume 6, Issue 5
May 2017
Total 179 977809
Table 4shows the summary of the questions bank of
Phys. 202. The bank contains 8 chapters with 76
sub topics and 41588 questions.
Table 4: Questions bank of Phys 202 course at
KAUA
Section
Number Chapter Name subtopics
Generated
questions
1 Electric Charge 18 5744
2 Electric Field 10 4584
3 Electric Flux 5 1538
4 Electric Potential 6 10793
5 Capacitance and
Capacitors 9 4747
6 CURRENT 10 2811
7
Magnetic Force
and Charged
Particle
8 2583
8 Magnetic Field
due to Current 10 8788
Total 76 41588
Table 5shows the summary of the questions bank of
Phys. 203. The bank contains 8 chapters with 73
sub topics and 201695 questions.
Table 5: Questions bank of Phys 203 course at KAUA
Section
Number
Chapter
Name
subtopics Generated
questions
1 Elasticity 9 17573
2 Fluids 1 7 8737
3 Fluids 2 18 12115
4 Fluids 3 7 46485
5
Simple
Harmonic
Motion
9 57126
6 Waves 8 41876
7 Temperature 6 13453
8 Images 9 4330
Total 73 201695
The faculty developed and published three training
systems for Phys. 110[11], Phys. 202[12], and Phys.
203[13]. These systems use the generated
quotations banks. Figure 7shows the site of Phys.
110 training system.
Figure 7: The site of Phys110 training system
The system provides an explanation for solve the
questions. Figure 8shows the explanation of a
question
Figure 8: Question’s explanation
The system allows the student to solve the training
of each chapter and then display his answer and the
correct answer; Figure 9shows the correctness the
student answers.
111 Ahmed Ezz Awad
International Journal of Innovations & Advancement in Computer Science
IJIACS
ISSN 2347 – 8616
Volume 6, Issue 5
May 2017
Figure 9: The correctness the student answers
In addition, the faculty developed electronic exam.
The e-exams are hold for the three courses for last
three years. Three terms per year, and three exam
per term: first, second, and final exams. The huge
generated questions help us for automatic
generation of a large number of different exams
with individual test to each student.
6. CONCLUSION
A formal definition and algorithms for altering
variables in Physics equations are developed for
automatically generated a questions bank. Three
questions banks for three physics course at Faculty
of Science, King Abdulaziz University (KAU):
Phys. 110, Phys. 202, and Phys. 203 are built. The
special requirements of physic problems: scientific
notation, figures, units, and generating alternative
options. This work overcomes the problems of
manual methods that ask the instructor to enter
questions directly and reduces the time
consuming.This work uses templates that allows the
instructor to describe the question, and then the
system generates the questions. The instructor can
modify the description and the system re-generates
the questions to correct any mistake.
The using of the generated questions banks in
training system and electronic exam system satisfy
the scalable exams feature. In addition the
feedbacks of the exams proves that the generated
questions banks are reliable.
The work in generation questions bans in physics
domain led us to build a physic ontology.
ACKNOWLEDGEMENTS
This work is done in Faculty of Science, King
Abdul-Aziz University. The author, therefore,
acknowledge with thanks Faculty of Scienceto
technical support. Also the author acknowledge the
department of Physic, Faculty of Science, King
Abdul-Aziz University to technical and materials
support.
7. REFERENCES
[1] http://sciences.kau.edu.sa/Pages-Interactive-training-
sites.aspx
[2] Bloom, B. S.; Engelhart, M. D.; Furst, E. J.; Hill, W.
H.;Krathwohl, D. R., Taxonomy of educational
objectives: The classification of educational goals.
Handbook I: Cognitive domain. New York: David
McKay Company, 1956.
[3] A. Ezz and M. Dahab “ Automatic Generation of
Question Bank Based on Pre-defined Templates”,
International Journal of Innovations & Advancement
in Computer Science IJIACS ISSN 2347 – 8616
Volume 3, Issue 1 April 2014.
[4] Frank H. Stephenson , “Calculations for Molecular
Biology and Biotechnology. “,Copyright © 2010
Elsevier Inc
[5] D. Halliday, R. Resnick, and J. Walker,
“Fundamentals of Physics Extended”, SIXTH
Edition, John Willy & Sons, Inc., 2001.
[6] Bettina Grün, AchimZeileis “Automatic Generation
of Exams in R”, Journal of Statistical Software, Vol
29 (2009) Issue 10.
[7] MikulášGangur, “Automatic Generation of
Mathematic Tasks” chapter in book:” Recent
Researches in Applied Mathematics and
Informatics”, ISBN: 978-1-61804-059-6 2011.
[8] “Automatically Generating Questions in Multiple
Variables for Intelligent Tutoring”, The Journal of
Issues in Informing Science and Information
Technology (2), 2005.
[9] Tao Li and Sam
Sambasivam,“AutomatedTransformationofSWRLRu
lesintoMultiple-ChoiceQuestions”, AAAI
Publications, Twenty-Fourth International FLAIRS
Conference, 2011.
[10] Paul CRISTEA, RodicaTUDUCE ,“Automatic
Generation of Exercises for Self-testing in Adaptive
E-Learning Systems: Exercises on AC Circuits”, 9th
International Conference on Intelligent Tutoring
Systems, ITS 2008.
[11] http://prod.kau.edu.sa/faculties/science/physics/inde
x.aspx
[12] http://prod.kau.edu.sa/faculties/science/phy202/inde
x.aspx
[13] http://prod.kau.edu.sa/faculties/science/phy203/inde
x.aspx
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