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