=Paper= {{Paper |id=Vol-3003/paper1 |storemode=property |title=Models and Software for Intelligent Web-Based Testing System in Mathematics |pdfUrl=https://ceur-ws.org/Vol-3003/paper1.pdf |volume=Vol-3003 |authors=Andrey Chukhray,Elena Yashina |dblpUrl=https://dblp.org/rec/conf/profitai/ChukhrayY21 }} ==Models and Software for Intelligent Web-Based Testing System in Mathematics== https://ceur-ws.org/Vol-3003/paper1.pdf
Models and Software for Intelligent Web-Based Testing System
in Mathematics
Andrey Chukhray and Elena Yashina
     National Aerospace University «Kharkiv Aviation Institute», Chkalova 17, 61070 Kharkov, Ukraine

                 Abstract
                 In this paper computer models and software for intelligent web-based testing system in
                 mathematics are described. The analysis of computer web-based testing systems in
                 mathematics is carried out, Parameterized mathematical models for different tasks, including
                 algebra and geometry, are synthesized, Architecture and software of intelligent web-based
                 testing system are presented. Knowledges and skills evaluation model on the base of fuzzy
                 logic is developed. Now system is working in two modes: a mode of training and a control
                 mode.

                 Keywords 1
                 Intelligent tutoring systems, e-learning, educational software, mathematical models



1. Introduction
    In the past few years e-learning experiences true boom. The driving force of it is continuous
computer potential growth: increase of processor power and memory capacity, improvement of I/O
facilities, perfection of network technologies, boost of efficiency of modern software development
tools. The Covid-19 pandemic gave a powerful impetus to the computer-aided learning growth.
    Artificial intelligence techniques allow to individualize and personalize the educational process [1,
2] and improve feedback from students [3]. At the same time scientific theory of artificial intelligence
for e-learning is developing not so fast as developers would like. Artificial intelligence techniques are
successfully used in teaching computer and mathematical sciences [4]. But today it is not possible yet
to replace a good teacher with a computer tutor system. There is insuperable complexity of synthesis of
models and methods for adaptation to mental work features, repertoire of knowledge and skills of each
learner [5].
    Therefore efforts of many developers aim at more utilitarian tasks where considerable progress is
achieved at interactive intelligent tutoring system, such as evaluation of mathematical expressions [6],
models constructing [7], solving algebra [8] and geometry [9] problems, online and web-based tutoring
systems [10, 11], web-based test systems [12].
    Within the framework of the Ukrainian project of external independent evaluation before authors
there was a task of intelligent web-based testing system creation. The purpose of it was increase of
effectiveness of school graduates preparation to external independent evaluation in mathematics by
means of availability assurance of tests examples through the Internet, introduction of interactive modes
of training and control for improvement contents of tasks and technologies of answers filling
understanding, economy of expenses for manufacture and distribution of test tasks paper collections,
    As analysis of world experience of interactive testing systems in mathematics making has shown the
most creative way is development of parameterized mathematical models for automatic generation
unique tasks, right answers and wrong but plausible answers for closed tests.


International Workshop of IT-professionals on Artificial Intelligence (ProfIT AI 2021), September 20-21, 2021, Kharkiv, Ukraine
EMAIL: achukhray@gmail.com (A. 1); o.yashina@khai.edu (A. 2);
ORCID: 0000-0002-8075-3664 (A. 1); 0000-0003-2459-1151 (A. 2);
              ©️ 2021 Copyright for this paper by its authors.
              Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
              CEUR Workshop Proceedings (CEUR-WS.org)
2. Task definition
  This article is dedicated to solving the problems.
      1. To synthesize parameterized mathematical models for automatic generation unique tasks,
           right answers and wrong but plausible answers for closed tests.
      2. On the base of fuzzy logic to develop knowledges and skills evaluation model.
      3. To create algorithms and the software for intelligent web-based testing system in
           mathematics which must work in two modes: a mode of training and a control mode.

3. Task solution
   3.1.     Parameterized mathematical models
   We described 26 different mathematical tasks, including algebra and geometry ones, were
parametrical. There were 12 tasks of closed type and 14 tasks of open type.
   Let's consider some examples of parameterization.

       3.1.1. Example I
       To solve equation
                                 √𝑥 + 1√𝑥 − 2√𝑥 − 5 = 0.                                    (1)
  In general we have
                             √𝑥 + 𝑎1 √𝑥 + 𝑎2 … √𝑥 + 𝑎𝑛 = 0.                                 (2)
  The admitted region is
                                          𝑥 + 𝑎1 ≥ 0
                                          𝑥 + 𝑎2 ≥ 0                                        (3)
                                        {
                                              …
                                          𝑥 + 𝑎𝑛 ≥ 0
  Hence it follows
                                 𝑥 ≥ − 𝑚𝑖𝑛{𝑎1 , 𝑎2 , . . . , 𝑎𝑛 }                           (4)
and
                                       𝑥 = − 𝑚𝑖𝑛{𝑎1 , 𝑎2 , . . . , 𝑎𝑛 }.                    (5)
  The model of the task consists of:
     1) n ∈ {1,2, . . . , 10}is randomly chosen;
     1) set {𝑎1 , 𝑎2 , . . . ,𝑎𝑛 }, − 100 ≤ 𝑎𝑖 ≤ 100, 𝑖 ≠ 𝑗 → 𝑎𝑖 ≠ 𝑎𝑗 is randomly chosen;
     2) variants of answer are generated by the following way:
        a. equation has no roots;
        b. 𝑥 = −𝑚𝑖𝑛{𝑎1 , 𝑎2 , . . . , 𝑎𝑛 };
        c. 𝑥 = −𝑚𝑎𝑥{𝑎1 , 𝑎2 , . . . , 𝑎𝑛 };
        d. 𝑥 = {−𝑎1 , −𝑎2 , . . . , −𝑎𝑛 }
     3) variants of answer are arranged randomly;
     4) right answer is compared with answer of graduate.

       3.1.2. Example II
  The medial line of trapezium in Ошибка! Источник ссылки не найден. is equal 7. Height is
                                           15√3
                                                .
                                             7
Figure 1: Graphical task statement

   Angle between diagonal is equal 120°. To find product gets of diagonals of base is equal L and
vertex angle is equal 120° BOC and AOD are similar triangles. Hence it follows
                                        𝐴𝐷 𝐵𝐶                                               (6)
                                           =     .
                                        𝐹𝑂 𝐸𝑂
   Also we know that
                       𝐴𝐷 + 𝐵𝐶                1                                             (7)
                  𝑆=            ∗ (𝐸𝑂 + 𝐹𝑂) = ∗ 𝐴𝐶 ∗ 𝐵𝐷 ∗ 𝑠𝑖𝑛(120°).
                           2                  2

   Therefore
                                                𝐴𝐷                                                   (8)
                                     𝐴𝐷, 𝐹𝑂 ≤         , 𝐸𝑂 < 𝐹𝑂
                                                2√3
are generated. BC is calculated as
                                                   𝐸𝑂                                                (9)
                                            𝐴𝐷 ∗      .
                                                   𝐹𝑂

   Then desired value is
                                            AD + BC 1                                               (10)
                                AC ∗ BD =          ∗    ∗ EF.
                                               2     √3

        3.1.3. Example III
   To solve equation
                                        2𝑥+2 − 2𝑥 = 96.                                             (11)
   In general we have
                   (−1)𝑏1 𝑎 𝑥+𝑐1 + (−1)𝑏2 𝑎 𝑥+𝑐2 +. . . +(−1)𝑏𝑛 𝑎 𝑥+𝑐𝑛 = 𝑃.                         (12)
   The model of the task consists of following actions:
       1) n ∈ {2,3, . . . , 10} is randomly chosen;
       2) a,x ∈ {2,3, . . . , 10} are randomly chosen;
       3) 𝑐𝑖 ∈ {0,1,3, . . . , 10}, 𝑖 = ̅̅̅̅̅
                                         1, 𝑛 are randomly chosen;
       4) 𝑏𝑖 ∈ {0, 1}, 𝑖 = ̅̅̅̅̅
                               1, 𝑛 are randomly chosen;
       5) P is calculated:
       6) right answer is compared with answer of graduate.

        3.1.4. Example IV

   Areas of bounds of rectangular parallelepiped are equal 𝑆1 , 𝑆2 , 𝑆3 . To find volume of parallelepiped.
   The model of the task includes:
   1) generation random 𝑥, 𝑦, 𝑧 ∈ {2,3, . . . ,10};
   2) calculation 𝑆1 = 𝑥𝑦; 𝑆2 = 𝑧𝑦; 𝑆3 = 𝑥𝑧;
   3) check graduate answer against x ⋅y ⋅z.
    3.2.        Knowledges and skills evaluation model
    To create evaluation model fuzzy approach was chosen because of its closeness to teacher qualitative
reasoning.
    Let us consider input linguistic variables:
                                    𝑈𝐼 =”Tasks solving speed”,
described by the term set
                                  𝑇(𝑈1 )={Slow, Medium, Fast}
as in [2];
                                     𝑈2 =”The number of errors” ,
                     𝑇(𝑈2 )={Zero, Very small, Average, Large, Very large};
and
                                         𝑈3 =”Help reference”,
                𝑇(𝑈3 )={Without help, With small help, With help, With great help}.
    For example, membership functions for 𝑇(𝑈3 ) are presented in Figure 2.




Figure 2: Membership functions for input variable Help reference

   Let
                                𝑌 = ”𝐾𝑛𝑜𝑤𝑙𝑒𝑑𝑔𝑒𝑠 𝑎𝑛𝑑 𝑠𝑘𝑖𝑙𝑙𝑠”
   be an output linguistic variable with term set
                          𝑇(𝑌)={ Excellent, Good, Satisfactory, Bad }
   T(Y)={Excellent, Good, Satisfactory, Bad}.
   Then rules can be expressed in the Mamdani form:
   If 𝑈𝐼 is Fast and 𝑈2 is Zero and 𝑈3 is Without help then Y is Excellent.
   If 𝑈𝐼 is Fast and 𝑈2 is Very small and 𝑈3 is With help then Y is Good.
   …
   If 𝑈𝐼 is Slow and 𝑈2 is Very large and 𝑈3 is With great help then Y is Bad.

4. Software
   The main task of this work is intelligent computer system for testing knowledge and skills in
mathematics software development. We have collected and analyzed the system requirements. Based
on this the architecture of system and main components software was developed.
    4.1.        System architecture
   As a result of the analysis of the system requirements, the main components and the connections
between them were identified. The system architecture model is shown in Figure 3.
   The system consists of the following levels:
   - the database level, which contains the database for accounting information about users
(registration, test results);
   - the business logic level, which includes the APP Server;
   - the communication level, that is, the level that carries out network interaction with the user;
   - presentation layer, which includes tools for development and presentation of data, such as ASP
.NET, WinForms, as well as directly displaying Web sites, that is, various browsers;
   - user level.

       DATABASE                                                                    Admin
        LAYER                                   DB                            (world leadership
                                                                                  planner)

      BUSINESS
     LOGIC LAYER                             APP Server                        Winforms / WPF



    COMMUNICATI
      ON LAYER
                                       WCF / Remoting /
                                        Web services



       PRESENTA
         TION
        LAYER
                               ASP.NET                    WinForms /
                                                            WPF


                                 IE / FF /
                                  opera


      STPD LAYER
                                               Client

Figure 3: The architecture of an intelligent computer system for testing knowledge and skills in
mathematics

    Components for generating problem conditions and answer options for them are stored in separate
library DLL files.
    To provide versatility multilevel architecture of system was developed. It consists of four levels:
database level, business logic level, communication level and presentation one. Main components of
business logic layer are presented in Figure 4.
                                                        Task                 Statement        TaskPresentation
                                                                                                  (graphic
                                                                                                presentation)

< Task Generators >                                    Control
       *.dll        Reflection ITaskGe List      Agent
                                nerator
                                                                          AnswerVariant          XML

                                                       WCF

                                Answer / Login Data

                                                                 IPresentation
                                                                   Provider

        DB                                                       Statement
                                                                                                       XML
                                 ASP.NET Pages &
                                 Controls (other UI)        ASPNetPresenta     Equation        EquationPres
                                                             tionProvider  Its presentation      entation

Figure 4: Components of business logic layer

    After an entrance of the user in system, which happens at ASP layer WCF layer begins work. WCF
represents an intermediate link witch connects parts of display and logic. WCF contacts library with
tasks and through interface ITaskGenerator by means of reflection operation receives the list of tasks.
Each element of the task list, i.e. a copy of class Task, contains a task condition, variants of answers
and a right answer as XML-code. Control agent cuts right answer leaving it on a server and directs the
remained elements (a condition and answer variants) to layer WCF. Thus, right answers in no way
cannot become accessible to the user. Therefore security is provided.
    The diagram of the main classes of an intelligent computer system for testing knowledge and skills
in mathematics is shown in Figure 5.
    The basic abstract class Task has two inheritors: the EnclosedTask class a of a closed type task; the
OpenTask class of an open type task. Both classes override the base class's Check() method and have
several constructors.
    The Task class defines a Statement class that represents a task condition. It is associated with the
AnswerVariant class, which generates answer options.
    The Statement and AnswerVariant classes through the TaskPresentation class form the expression
of the condition of the task and the options for responding to it in the form of an XML representation.
    In addition to the AnswerVariant class, there is an abstract RightAnswer – correct answer class. Its
inheritors are the classes of the correct answer to tasks of the private EnclosedRightAnswer and public
OpenedRightAnswer types.
    The Task class, through the TaskPresentation class, generates conditions and response options in
the form of XML code containing tags of a specific purpose, for example, the  tag
contains an expression for building a mathematical formula, the  tag is a directive for plotting
a function graph. ASPNetPresentationProvider class implements transformation of task XML-code for
its presentation on WEB-form. To implement tags such as a formula or graph, the
ASPNetPresentationProvider class includes the appropriate libraries to represent them graphically.
Figure 5: The diagram of the main classes of an intelligent computer system for testing knowledge and
skills in mathematics

    4.2.        System Interface Development
   The system must have an advanced user interface for visualizing formulas, graphs and other
graphical objects. One of the system components is a module for constructing mathematical formulas
designed for visual output of mathematical formulas of any complexity. The formula is specified as a
sequence of elementary instructions that determine the location of the formula elements. After the
structure of the formula is formed, the elements are arranged, the formula enters to the graphical
module, which draws it on the Bimap object and displays it on the web form. The example of formula
visualization is given in Figure 6.




   Figure 6: The example of formula visualization

  Also, a module for dynamic plotting of various mathematical functions has been implemented.
Examples of dynamic output of function graph are shown in the Figure 7.




   Figure 7: The example of function graph output

   Screenshots of the system are presented in figures 8 – 10.




Figure 8: Screenshot of the system for trigonometric task
Figure 9: Screenshot of the system for algebraic task with graphical elements




Figure 10: Screenshot of the system for stereometric task

    Through interface IPresentationProvider the task in the form of a XML-code arrives to object
ASPNetPresentationProvider where its analysis and split are executed. The task can consist of the text
and pictures with formulas and graphs. In case of formulas object EquationPresentation provides
creation of a demanded picture. Similar technology is used for creation plots of functions. Then controls
arrive to ASP.NET Pages where they are displayed. Now system is being passed beta testing in site of
Kharkov regional centre of education quality evaluation.
5. Summary
    Parameterized mathematical models, knowledges and skills evaluation model and software for
intelligent web-based testing system in mathematics are developed. The system has multilevel
architecture and flexible interface to provide versatility and security. The next step may be creation of
diagnostic models to adapt system to mental work features, knowledges and skills of each graduate
[13].
    This system joined in single complex meant for learners testing (http://zno-kharkiv.org.ua/cimt/). In
the perspective, it is planned to integrate the math web-tests system with other software tutoring
products [14].

6. References
    [1] Nkambou, Roger, Riichiro Mizoguchi, and Jacqueline Bourdeau, eds. Advances in intelligent
        tutoring systems. Vol. 308. Springer Science & Business Media, 2010.
    [2] Muangprathub, Jirapond, Veera Boonjing, and Kosin Chamnongthai. "Learning
        recommendation with formal concept analysis for intelligent tutoring system." Heliyon 6.10
        (2020): e05227. doi: 10.1016/j.heliyon.2020.e05227.
    [3] Putnam, Vanessa, and Cristina Conati. "Exploring the Need for Explainable Artificial
        Intelligence (XAI) in Intelligent Tutoring Systems (ITS)." IUI Workshops. Vol. 19. 2019.
    [4] Abu-Naser, Samy S. "Predicting learners performance using artificial neural networks in linear
        programming intelligent tutoring system." (2012).
    [5] Hasan, Muhammad Asif, et al. "The Transition From Intelligent to Affective Tutoring System:
        A Review and Open Issues." IEEE Access (2020). doi: 10.1109/ACCESS.2020.3036990.
    [6] Pacheco-Venegas, Nancy D., Gilberto López, and María Andrade-Aréchiga.
        "Conceptualization, development and implementation of a web-based system for automatic
        evaluation of mathematical expressions." Computers & Education 88 (2015): 15-28. doi:
        10.1016/j.compedu.2015.03.021.
    [7] VanLehn, Kurt, et al. "Learning how to construct models of dynamic systems: An initial
        evaluation of the dragoon intelligent tutoring system." IEEE Transactions on Learning
        Technologies 10.2 (2016): 154-167. doi: 10.1109/TLT.2016.2514422.
    [8] VanLehn, Kurt, et al. "Teaching Algebraic model construction: a tutoring system, lessons
        learned and an evaluation." International Journal of Artificial Intelligence in Education 30.3
        (2020): 459-480. doi: 10.1007/s40593-020-00205-3.
    [9] Wang, Ke, and Zhendong Su. "Automated geometry theorem proving for human-readable
        proofs." Twenty-Fourth International Joint Conference on Artificial Intelligence. 2015.
    [10]         Kefalis, Chrysovalantis, and Athanasios Drigas. "Web Based and Online Applications
        in STEM Education." Int. J. Eng. Pedagog. 9.4 (2019): 76-85. doi: 10.3991/ijep.v9i4.10691.
    [11]         Nye, Benjamin D., et al. "SKOPE-IT (Shareable Knowledge Objects as Portable
        Intelligent Tutors): overlaying natural language tutoring on an adaptive learning system for
        mathematics." International journal of STEM education 5.1 (2018): 1-20. doi:
        10.1186/s40594-018-0109-4
    [12]         Hostovecky, M., M. Misut, and K. Pribilova. "Web Based Testing in Science
        Education." Innovations and Advances in Computing, Informatics, Systems Sciences,
        Networking and Engineering 313 (2014): 247. doi: 10.1007/978-3-319-06773-5_33.
    [13]         Chukhray, A., Havrylenko, O., Mygal, V. and Mygal, G. "Models and Methods for
        Computer Support of Adaptive Training of Algorithmic Tasks Solution." ICTERI. 2020: 408 –
        415.
    [14]         Chukhray, Andrey, and Olena Havrylenko. "The engineering skills training process
        modeling using dynamic bayesian nets." Radioelectronic and Computer Systems 2 (2021): 87-
        96. doi: 10.32620/reks.2021.2.08.