=Paper=
{{Paper
|id=Vol-2920/paper_1
|storemode=property
|title=Taxonomy of Learning Objectives for the Development of Competencies of Computer Sience Teachers in a Developing Educational Environment
|pdfUrl=https://ceur-ws.org/Vol-2920/paper_1.pdf
|volume=Vol-2920
|authors=Evgenia Baranova,Irina Simonova
}}
==Taxonomy of Learning Objectives for the Development of Competencies of Computer Sience Teachers in a Developing Educational Environment==
https://ceur-ws.org/Vol-2920/paper_1.pdf
Taxonomy of Learning Objectives for the Development of
Competencies of Computer Sience Teachers in a
Developing Educational Environment∗
Evgenia Baranova Irina Simonova
ev_baranova@mail.ru ir_1@mail.ru
Herzen State Pedagogical University of Russia,
St. Petersburg, Russian Federation
Abstract
The problem of the development of students’ digital competencies in the process of achieving
learning objectives of certain classes in the field of algoritmization and programming and methods
of teaching computer science in a developing educational environment. The purpose of the study
is the system of tasks developed by the authors and based on “revised” B. Bloom’s taxonomy,
designed to develop algorithmic competence as a basis of digital competencies of students, future
computer science teachers.
As part of the study, the problems of modular education, identification and application of
Computer Science classes of problems according to “revised” B. Bloom’s taxonomy and its teaching
method, development and application of electronic learning resources that enrich the educational
environment in blended learning conditions were investigated.
The methods of the system analysis and competence approach, the Fisher method were applied
to assess statistical validity of the results and to confirm the hypothesis on the efficiency of the
use of electronic learning resources (ELR) to develop algorithmic competence of students.
The results of the study: it is proved that the development of students’ digital competencies
depends on the level of development of algorithmic competence manifested in students’ readiness to
develop algorithms and programs and to use them in teaching Computer Science in the conditions
of digital economy, development of ELR, self-education in Computer Science.
Models of factual, procedural and conceptual knowledge forming the basis of the teaching
content of the interrelated modules “Theory and Practice of Algorithmization and Programming
” and “Theories and Methods of Computer Science Teaching at School” are described. Classes of
problems for the development of algorithmic competence of students according to the “revised”
Bloom’s taxonomy which describes a hierarchical model of cognitive processes: remember, under-
stand, apply, analyze, evaluate and create are identified and described. The classes of problems
correspond to electronic learning resources (ELR) developed by the authors. The efficiency of
application of identified classes of problems and ELR for development of algorithmic competence
and digital competencies of students has been statistically confirmed.
Keywords: Taxonomy of learning objectives, digital competencies, algorithmic competence
of students, computer science teacher training, blended learning, revised Bloom’s taxonomy, elec-
tronic learning resources
∗
Copyright c 2021 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0
International (CC BY 4.0).
1
1 Introduction
The development of digital competencies of education professionals, including computer science teach-
ers, is key in the digital economy to prepare citizens who are ready to effectively solve problems in
their professional activities, social and personal life.
Developed digital competence is characterized by the willingness confidently, creatively, criti-
cally, independently (unassisted) use digital technologies and information systems in both private
and professional life.
According to the document “The Digital Competence Framework 2.0”, developed by the Eu-
ropean Commission, the term “digital competence” includes 21 components, combined in 5 groups:
Information processing, Communication, Content creation, Safety and protection, Problem solving.
The list of components includes such skills as search and selection, data extraction based on specified
criteria, data quality assessment, digital content development, effective communication with the use
of digital technologies, including in professional activities, formalization and solution of various classes
of problems with the use of digital tools, etc.
With regard to the preparation of bachelors of pedagogical education, specializing in the field
of information technology, the development of such components is based on algorithmic competence,
i.e. readiness for the development of algorithms and programs, their use in professional activities
in teaching Computer Science, the development of electronic learning resources, self-education in
Computer Science [Baranova, et al., 2020].
The problem of developing algorithmic competence, algorithmic thinking of computer science
teachers is investigated both in domestic and foreign sources. The difficulty of mastering the “algo-
rithm” concept due to its abstract, ambiguity of the definition and ways of presenting algorithms is
emphasized. Approaches to teachers training methods of developing algorithms, as a necessary stage
in the process of creating programs, are considered [Waite et al., 2020].
Algorithmic competence is considered as an important component and means of developing com-
putional thinking, which is one of the key skills of the 21st century [Tikva & Tambouris, 2021]. The
term “computional thinking” is used to describe the ability of students to solve problems through dig-
ital technologies, the level of development of their algorithmic thinking, readiness to develop program
code and characterizes the ability to abstract and analytical thinking, logical conclusions. The need
for research in the development of students’ “computional thinking” to develop digital competencies
is emphasized in [Angeli & Giannakos, 2020].
The course created and implemented by the authors, designed to develop teachers’ computa-
tional thinking through teaching the development of algorithms and programs using digital resources
and specially organized pedagogical support is described in [Kong, et al., 2020]. The analysis of the
experimental results showed the effectiveness of this approach for the development of teachers’ digital
competencies.
The focus of many works is on creating the conditions for effective programming teaching. So,
in [Scherer et al., 2020], [Tsai, 2019] there is an approach to learning based on the wide use of visual
programming environments as technological tools, and tasks of different levels from simple, repro-
ductive to metacognition instructions, aimed at developing the readiness to create an algorithm for
solving a problem and to analyze and evaluate the results.
The structure and content of learning bachelors and masters of pedagogical education in the
disciplines of information technology, aimed at developing their professional competencies, have been
created and tested by the authors for many years [Baranova Simonova, 2018]. The need to ensure
continuity of the content of training, its consistency, interdisciplinarity, first of all, with mathematics,
coherence, completeness, modularity, produceability was identified in order to replicate knowledge, for
gradual, systemic development of students’ readiness for the effective use of information technology
tools in professional activities.
Improving the efficiency of learning should be carried out through the selection of content
2
based on specified principles, the use of innovative methods such as e-learning and distance learn-
ing, blended learning, “flipped classroom”, etc., the widespread use of electronic learning resources
[Baranova, et al., 2020]. According to the authors, the key aspect of students’ algorithmic competence
development is a specially designed system of problems aimed at accumulating students’ systemic
knowledge of the subject area and developing a willingness to carry out cognitive processes that are
adequate to the problems being solved. The study of basic concepts, principles, and algorithms of
compilation theory contributes to the formation of students’ systematic understanding of the sources
of syntax errors and skills to develop syntactically correct programs [Kwon & Cheon, 2019].
The approach to constructing classes of problems developed by the authors is based on B. Bloom’s
taxonomy of educational objectives [Bloom et al., 1956] and the so-called Bloom’s “revised” taxonomy,
developed by his followers L. Anderson, D. Krathwohl and others. A two-dimensional structure is
proposed [Anderson et al., 2001] to describe the learning objectives in this approach. It is presented in
the form of a table which separates the processes of knowledge accumulation and cognitive processes,
due to which each category of taxonomy can be more accurately and deeply characterized. The
hierarchy of the knowledge category includes: factual knowledge, conceptual knowledge, procedural
knowledge and metacognitive knowledge, as the highest level. The model of the development of
cognitive processes [Krathwohl, 2002] is a hierarchy of cognitive activities, combined in the following
categories: remember, understand, apply, analyze, evaluate and create.
2 Research Methods
The systematic and competence-based approach serves as a methodological framework of the research.
The approach to constructing classes of problems is based on B.Bloom’s taxonomy of educational
objectives and Bloom’s “revised” taxonomy, developed by his followers L. Anderson, D. Krathwohl
and others. To solve the problem of the research a set of methods based on the analysis of Russian
and foreign pedagogical and psychological theory and practice in the area of training future computer
science teachers were used. Those were general scientific methods, including modeling, association,
comparison and generalization, as well as experimental methods using diagnostic toolkit, expert
evaluations and statistical processing of results of pedagogical experiment.
3 Results of Research and Discussion
An approach to constructing classes of problems for teaching students algoritmization and program-
ming on the example of basic modules for preparing an information technology cycle: “Theory and
Practice of Algorithmization and Programming” and “Theories and Methods of Computer Science
Teaching at School” will be considered
3.1 Module “Theory and Practice of Algorithmization and Programming”
Factual or basic knowledge that students should acquire is knowledge about the system-forming
terms of programming languages that form the conceptual core of the subject area. First of all,
these are such basic terms as: algorithm, information model, programming paradigm, data type,
data structure, identifier, basic control structure, class, object. The second component is detailed,
clarifying understanding of the system-forming concepts.
3
Table 1: Model of presentation of factual knowledge for the module “Theory and Practice of Algo-
rithmization and Programming”
Basic term Detailed terms
Algorithm algorithm properties, ways of expressing the
algorithm
Information model types of information models, ways of models
representation
Programming paradigm programming language,
imperative procedural, functional programming
logical programming
object-oriented programming
Program program structure, syntax errors, syntactically
correct program, program lifecycle phases,
program compilation
Data type integer, real, boolean, string, pointers, static and
dynamic data
Data structure simple and complex structures (arrays, records,
sets, lists, etc.)
Identifier description and name of the identifier
Basic control structure assignment operator, conditional operator, loop
statement
Subroutine procedure, function, module, formal and actual
parameters
Class class structure, class description, class as a set
of objects
Object object, as a representative of classes, object
field, object method, object property,
constructor, destructor, static and virtual
methods, scopes
Compilation program syntax, formal grammars, lexical
analysis, syntax analysis, code generation
Database relation, relation scheme, data type, domain,
instance variable, tuple, primary key, foreign
key, table, data query language.
Database management system data storage and retrieval in the database, data
processing, data security and integrity
4
Factual knowledge is formed in students in stages, during the entire period of studying the
module. The initial, general understanding of the system-forming concepts is clarified, detailed,
enriched by students mastering the purpose, characteristics, structure, specific properties, methods
and areas of use of objects representing the concept.
The next level in the hierarchy of knowledge categories, according to [Anderson et al., 2001] is
conceptual knowledge. This level involves the formation of students’ knowledge of relation between
the basic elements of the theory and practice of programming as a subject area. The conceptual
level involves knowledge of the categories, principles, theories, models, and approaches to classifica-
tion inherent in the subject area. With regard to programming, these are: the principles of struc-
tured programming, methods of top-down and modular programming, the concept of object-oriented
programming, including encapsulation mechanisms, inheritance mechanisms and polymorphism, con-
nections and relations and relations between the basic constructions of object-oriented programming
languages, compilation principles, methods of lexical and syntactic analysis, relational database con-
cept, etc.
The level of procedural knowledge involves mastery of algorithms, methods, techniques of the
subject area, an idea of ways to choose a toolkit that is adequate to the problem being solved.
With regard to programming, these are: basic search algorithms, sorting and processing information
presented in the form of various data structures; methods for developing information models that
describe the behavior of real and abstract objects, and modern methods for programs development,
including software implementation, debugging, testing, presentation and interpretation of results;
methods of database creation, tools for processing data in databases; methods of using computer
programs in the educational process; methods of developing syntactically correct programs.
According to [Krathwohl, 2002], the model of the cognitive processes development is a description
of the hierarchy of cognitive activities, combined in the following categories. To remember is to be
able to retrieve relevant knowledge from long-term memory, recall terms, recognize objects, concepts.
To understand is to construct meaning from definitions, illustrate, interpret, summarize statements,
classify and match the entities of the subject area, conclude, predict the behavior of objects in the
subject area under certain conditions. To apply is to carry out and implement procedures in a given
situation.
To analyze is to break material into its constituent parts, determine how the parts relate to
one another and to an overall structure, to distinguish components by specific properties, to organize
sections of the subject area, to attribute the entities of the subject area.
To evaluate is to make judgements, to check the fulfillment of certain conditions, to test. To
create is to put elements together to form a coherent whole or invent a new product, hypothesize,
plan, design. According to the authors, such hierarchy of cognitive processes corresponds to the
activities of specialists in the field of informatization of education, based on their readiness to develop
software applications and other information technology tools. This activity involves invention of a
new products based on fundamental, conceptual knowledge, experience in the analysis and evaluation
of other people’s programs, includes the stages of developing information models, algorithms and
data structures that are adequate to the problem being solved, software implementation, analysis,
evaluation, interpretation of the obtained results. The model proposed by B. Bloom’s followers is the
basis of the system of problem classes (Table 2), developed by the authors and used in the process of
students training.
5
Table 2: Model of the system of problems for the module “Theory and Practice of Algorithmization
and Programming” in the logic of the hierarchy of knowledge and cognitive processes
Classes of problems focused on achieving learning objectives in accordance with levels of knowl-
edge and categories of cognitive processes will be characterized. Classes of problems are generally
described by the authors in [Baranova et al., 2019].
The problems of the first class are aimed at consolidating factual knowledge about basic control
structures and data structures of programming languages, compilation stages, database components,
stages of designing databases and information systems. Problems are formulated in the form of ques-
tions or tasks, for example, of the following types: “Give examples of control structures that provide
repeated performing operations”, “What is the structure of control structures such as сonditional con-
structions?”, “What are variable descriptions for?”, “How are formal and actual parameters related
in procedures and functions?”, “What is the role of the lexical analyzer in the compilation process?”,
“Describe program lifecycle phases and their purpose”, “Describe the basic concepts of a relational
database”, etc.
The problems of the second class are aimed at developing students’ systematic understanding
of programming as a science, readiness to build information models, as a basis for software imple-
mentation. By comparing the purpose and capabilities of programming constructs, students learn to
select data structures, control structures that are adequate to the problem that needs to be solved.
An important type of problems in this class is related to the development of the ability to predict
the results of the execution of a specified operator, a group of operators, a procedure, a program as a
whole. First of all, this is the ability to perceive (read, see, understand) the “program” not as a text,
but as a structure, a hierarchy of interrelated entities, the interaction of which ensures the execution
of the program and the receipt of results that are uniquely determined by the input data. Example
tasks: “Describe the results of performing a specified procedure for different sets of actual parame-
ters”, “Find syntax errors in the program”, “Describe the structure and relations between database
tables to represent a certain subject area”. Another type of problems, focused on the formation of
students’ conceptual knowledge of programming, involves program development that provide a visual
representation of the studied control structures and algorithms, for example, loop structures, search
algorithms, sorting, etc.
This class of problems develops students’ readiness to perform basic data operations, including
creating, changing values, deleting data. Data are represented by different structures: arrays, lists,
sets, records, object classes, database tables.
The third-class problems are an extensive list of problems aimed at developing students’ algo-
rithmic competence. This competence is considered as systemic, conceptual knowledge of the subject
area, procedural knowledge that ensures readiness to develop algorithms and programs, which can be
6
applied in their professional activity. This is primarily the development of computational algorithms
and programs based on the known mathematical apparatus: approximate calculations, calculation
of series sum, array processing, computations of geometric figures’ parameters, etc. When solving
such problems students develop readiness to interpret mathematical models, to transform them into
information models, to create data structures corresponding to the mathematical objects’ nature, to
«translate» from mathematical language to Computer Science language. Thus, the interdisciplinary
links between informatics and mathematics are built.
A special type of this class of problems involves the development of algorithms and programs
that simulate phenomena, processes, and behavior of objects from different fields. Solving such
problems aims at verification of achieving a certain level of algorithmic competence at the practice
level, students’ readiness to solve problems in new situations based on known facts, models, and rules.
This type, as stated by the authors in [Baranova et al., 2019], includes problems on visualization of
known algorithms operation involving new interface elements, software implementation of simple
models describing phenomena from various fields of knowledge, science and technology, development
of game situation fragments, etc.
The fourth class of problems is focused on the development of the highest-level learning activities,
such as analysis, evaluation, and creation. We should note that they are inherent in the professional
activities in the field of algorithmization and programming, which involve analysis of subject domains,
creation of a new product and evaluation of product quality as mandatory stages. At the stage of
analysis, the focus is on the structuring of subject domains, identification of relationships between the
components and attribution of selected entities at a certain level of abstraction in order to create an
information model as a basis for software implementation. The class includes objectives on developing
algorithms and programs for analyzing data that are presented in different structures, data generation
according to a given scheme: algorithms for finding and sorting, forming arrays, lists of a given
structure, creating classes of objects with a specified behavior, determining the values that characterize
the data in the database table by means of the SQL language, creating linked data sets according to
a defined scheme, etc.
The “create” category in the refined taxonomy of learning activities implies the ability to produce
a new product[Anderson et al., 2001], [Krathwohl, 2002], to design a new whole from parts on the
basis of proposed hypotheses according to the developed action plan. When teaching algorithmization
and programming with such a new product, the result of students’ educational activities is a computer
program. The step-by-step process of creating software, even training ones, is inextricably linked to
the evaluation of results: during the debugging process the syntax correctness of the program is
checked, the program is tested on different sets of input data for verification of logic. A group
external evaluation can be organized during the testing process. For example, all students in the
group make a value judgment on the product quality:
• program interface – compliance with ergonomic requirements;
• the efficiency of the chosen algorithm – execution speed, the use of memory for data storage;
• the appropriateness of data structures used for the objective – representation of a set of one-type
elements in the form of an array, a set of elements of different types in the form of a record, an
unordered set of non-repeating elements in the form of a set, objects of the same structure and
with the same behavior in the form of a single class, large datasets in the form of a database
table, etc.
The problems of this class are rather complex for undergraduate students and involve the development
of modular software (information systems). Such programs simulate the behavior of objects of subject
domains from various areas of social life: production, scientific, social, and personal. Diversity of
objectives is very important, as this helps students to understand the scope and variety of application
of modern IT tools.
7
For example,
• creation of information systems: ATM, Library, Social Networks, Employment, and Dean’s
Office, simulating the relevant processes,
• development of computer programs: dynamic interactive models Properties of the Integers,
Magic Square, etc.
• development of elements of game programming.
A number of tasks are related to students’ future professional teaching activities. They include the
development of electronic learning resources on various school subjects, test systems, information
systems, and web resources for the organization and management of the educational process, etc.
L. Anderson and D. Krathwohl have introduced a fourth type which is called “metacognitive
knowledge”, the highest level of the knowledge hierarchy. According to the creators, this category
implies knowledge of cognition and self-knowledge that are necessary for carrying out research ac-
tivities. Such knowledge is primarily acquired through graduate qualification work (GQW). Mostly,
by the end of their studies students are ready to formulate their preferences for topics and tools of
their work, and while preparing GQW their understanding of research strategies and methodology
are developed, as well as individual approaches to cognitive activity are formed.
The authors believe that in this respect the GQW subject, connected with the development of e-
learning resources of various types in order to accompany the study of a school subject or information
technology discipline in higher education, is very useful. Such training and research activities include
the analysis of the subject area, development of an information model for e-learning resources, program
execution, development of methodological guidelines for the use of e-learning resources, their testing
in the learning process and evaluation based on results of such testing.
The considered approach to learning algorithmization and programming, which is based on
a specially designed system of objectives, is implemented with extensive use of electronic learning
resources developed personally by both the authors and their students while working on GQW under
the author’s guidance. The structure of all resources is similar. The content of e-learning resources
is determined by specifics of the class of problems. Classes of resources are detailed by the authors
in [Baranova et al., 2019]. These resources include:
• systematic description of programming principles and methods, algorithms and data structures
that are studied, programming language constructs, basic data access operations;
• interactive demonstration examples: software applications that simulate algorithms, illustrate
the purpose and features of the data structures being studied, professionally executed examples
of information systems, etc.;
• sets of problems and tasks for students of different complexity aimed at accumulation of fac-
tual, conceptual, and procedural knowledge and developing readiness to conduct the identified
cognitive activities in accordance with Table 2
The e-learning resources system is presented in the LMS Moodle and provides each student with the
opportunity to build a comprehended individual educational route. For teachers, it is an effective
instrument for managing both classroom-based and distance-learning educational activities.
8
Table 3: Model of conceptual knowledge presentation for module “Theories and Methods of Computer
Science Teaching at School”
Concepts Detailed concepts
Methodological system of Computer Science functions of the methodological system
teaching at school of Computer Science teaching at school
(epistemological, humanistic, design-
oriented, normative, and reflexive) and
structure of the methodological teaching
system (learning objectives, content
selection principles, methods, means, and
forms of teaching)
System of concepts constituting the content of regulatory documents, the federal list of
Computer Science teaching at school textbooks, stages of conceptualization,
intension and extension of concepts, the
generalization and abstraction of
concepts, the types of concepts'
definitions.
Methods and technologies for teaching classification of teaching methods,
Computer Science at school correlation and interconnection of
methods, techniques, and technologies
for teaching Computer Science at school,
technological development of learning
using ICT tools
Methods for evaluating knowledge and skills in approaches and methods for evaluating
Computer Science teaching at school achievement (criterion-oriented,
standard-oriented, normative-oriented),
criteria for knowledge assessment,
structure of basic state examination and
unified state examination as final
knowledge assessment, knowledge
quality assessment criteria
(completeness, systematic character,
depth, etc.)
Knowledge of the Computer Science teaching classroom system, lesson typology,
organization at school information security, safety
The knowledge that forms the content of the teaching units of sections: "information
school Computer Science course and how to present it", "basics of
9
Within the framework of theoretical education, the content of the school subject Computer
Science is analyzed using a retrospective approach. The stages of establishment of the Computer
Science content are considered in connection with the development of the science of information and
information processes, computer as a universal tool of information processing, software. The content
extracts the following concepts: “information”, “algorithm”, “model” and classes of problems whose
solution requires understanding and application of these concepts. During the classes, students must
identify topics in the content that have a stable conceptual core, reveal a set of standard problems
and exercises (for example, numerical systems, information coding, basic algorithms, etc.), justify the
relevance of these sections for the whole course, develop lesson notes, including technology maps and
tasks that help to evaluate the students’ knowledge and skills.
The introduction of research and creative methods has a positive impact on the development
of students, but this requires considerably more teaching time and time to prepare the teacher for
the lesson. They analyze and compare the texts of Computer Science school textbooks of different
authors according to different criteria: principles of content selection, visibility and accessibility of
educational material, development of universal educational activities, etc.
The algorithmic and programming line is certainly one of the most important for the devel-
opment of a specific learners’ (schoolchildren and students) thinking type, often called algorithmic.
Some sources use the term “computer thinking” [link]. One of the main goals of the Computer Sci-
ence teacher is to create the conditions for the successful acquisition of basic knowledge of this line
by schoolchildren. It is the success of solving the problems corresponding to this line that serves as
an indicator of professional ability in the field of Computer Science and information technology. The
established methodology of teaching the basic concepts of this line has the longest history of devel-
opment in our country. It corresponds to the primary, secondary and high school stages. According
to our experience, the fully implemented methodology, starting with simple algorithm executors and
ending with the production programming language at specialized schools, gives positive results in the
development of digital competencies of students.
Teaching methods and techniques have a significant impact on the development of learners’
digital skills and factual knowledge. Formally, Computer Science training uses active methods in the
form of laboratory work and workshops. The analysis of texts of these works shows that reproductive-
type problems, which do not contribute to creative development, predominate. Implementation of
research and creative methods has a positive impact on students’ development, but this takes much
more learning time and teacher’s time to prepare for a lesson.
Procedural knowledge in the methodology of Computer Science teaching ensures the implemen-
tation of the practical-oriented learning principle. This knowledge contributes to mastering of the
basic methods of solving educational problems of Computer Science school subject by students, as
well as of IT tools necessary for performing their tasks on a computer. Procedural knowledge enables
students to master methods and technologies for implementing an individual approach to students
when teaching Computer Science, ways of creating educational and methodological materials, includ-
ing lesson notes and flow charts, sets of differentiated tests and other materials (keeping the electronic
journal, updating information on a school website).
Methodology of teaching within the Theories and Methods of Computer Science Teaching at
School module, aimed at acquisition of factual, conceptual and procedural knowledge by students,
assumes the compliance with stages of development of cognitive processes defined by B. Bloom
[Bloom et al., 1956] and developed by his followers [Krathwohl, 2002]: knowledge, comprehension,
application, analysis, evaluation, creation. This approach is feasible to use in classrooms or in inde-
pendent work.
Students need to be taught how to distinguish characteristics of each stage in order to be able to
find an individual educational path, taking into account the hierarchy of learning activities, creation
of problems’ sets of certain cognitive complexity (D. Tollingerova), organization of students’ project
and research activities, including planning, evaluating, interpreting results of the research.
10
Proposed in [Krathwohl, 2002], the model is the basis for the system of problems (Table 4)
developed by the authors and used in the student training process.
Table 4: Model of the system of problems for the module “Theories and Methods of Computer Science
Teaching at School” according to the knowledge hierarchy and learning activities
We describe the classes of problems focused on the competence development of the future Com-
puter Science teacher in accordance with the knowledge levels and learning activities categories. As
noted above, the description of the learning goal includes the verb (action) and the noun (object).
The verb describes the action that is related to the cognitive process. The object describes students’
knowledge they must acquire or create.
The first class includes problems (tasks) aimed at mastering the content of the school subject
Computer Science and the ability to explain the solution of problems using schemes, drawings, com-
puter models, to remember and understand logical relationships of Computer Science key concepts:
acquisition of an understanding of content units, key concepts, teaching units and sample problems
of the school subject at all levels of formal education: primary, secondary, high. For example: “List
content lines (units) specified in the sample primary and high school curriculum”, “Create a logical
scheme of key concepts with regard to their continuity in the content units”, “Create a graphic illus-
tration of the school Computer Science course development against development stages of Computer
Science as a science; use network services to make infographics”;
solving problems that reveal the school subject Computer Science content units specified in secondary
and high school textbooks and other educational learning materials recommended for teaching at
school. For example, “Learn the content of the unit “Executor. Algorithm. Program” specified in
the Computer Science textbook for secondary school. Solve the problems given in the text of the
textbook and workshop. Compare the problems complexity level with the relevant problems in the
training materials for the basic state examination. Describe the stages of solving sample problems on
the topic. Compile instructional techniques to help students learn the topic of the lesson.
Class of problems 2 involves problems (tasks) facilitating the formation of knowledge related to
basic principles of Computer Science teaching at school, the structure and functions of the method-
ological educational system: objectives, content, forms, methods, educational resources:
tasks facilitating memorization and understanding of key concepts which develop the structure and
functions of the methodological educational system: objectives, content, forms, methods, educational
resources. These may be a retelling of a lecture or a textbook fragment proposed, or searching for
needed definitions in a printed dictionary and filling them into the table with respect to the given
structure, or answering reproductive questions on the lecture material such as “What does the term
11
“category mean?”, “What components does the methodological educational system include? What
problems do they solve? ”, “ List the functions of the methodological educational system? ”, “ At
what stages of methodical system of Computer Science teaching development is goal-setting carried
out?”, “ How do goals and objectives of Computer Science teaching correlate? ”
tasks facilitating understanding of the key stages continuity and basic principles of Computer Science
teaching at school.
For example, “List the 20th century main discoveries in Computer Science and specify which of
them were reflected in the school subject content?”, “Come up with a rationalization for the place
of algorithmization and programming in school Computer Science?”, “Express your judgment and
exemplify what impact this domain had on the content development of the school subject Computer
Science?”
This class of problems is refined and enriched in the course of studying the disciplines of the
module and is applicable in the other classes of problems [Kostousov & Simonova, 2019].
Class of problems 3 involves problems (tasks) facilitating the formation of skills related to the
analysis of regulations, educational learning materials, lessons conducted by Computer Science teach-
ers as well as developing course schedules and creating notes for Computer Science lessons, including
objectives, content, methods and educational resources; explaining problem solutions with diagrams,
figures, computer models; For example, “What is the conceptual basis of the FSES?”, “What subject
area does Computer Science relate to?” “How does the list of competencies reflect it?”, “List and jus-
tify the selection principles of content for basic and professional levels of Computer Science teaching
at the high level of education?”, “ How do materials of the basic state examination and the unified
national exam correlate?”, “What are the educational standards developed for teachers to prepare
for final exams?”, “Develop a course schedule for Computer Science for one secondary school term.
Create task sheets to support these schedules and arrange individual educational routes for students“,
“Write notes for lessons on the topic of Numeric Processing for high school professional level of the
school Computer Science course", "Create a lesson scenario on one of the secondary school Computer
Science course topics with respect to pedagogical programming techniques and implement it in LMS
Moodle (Use the Lecture network service)”.
Class of problems 4 involves problems (tasks) facilitating the formation of knowledge and skills
related to analysis, adaptation and creation of sets of educational problems for Computer Science
lessons with regard to differentiation and individualisation of learning as well as of exams, including
tests with the help of IT. For example, “Analyze the main stages and techniques of creating a set of
tasks with respect to the given cognitive complexity level (according to D. Tollingerova). Develop
a set of tasks with respect to the given cognitive complexity level on the topic of Algorithmization
for Year 9 school students”, “Develop a set of differentiated tasks for secondary school students to
strengthen their knowledge and skills on Algorithmization providing implementing tasks with the
help of training executor while facilitating the future transfer of this knowledge to other areas of
programming”, “Develop test tasks to control the acquisition of educational material on one of the
school Computer Science course topics and implement it with the help of IT resources”, “An example
from Kostousov with a link”. This class of problems involves the tasks related to developing scenarios
for electronic learning resources and their implementation in support of Computer Science teaching
at school. For example, “Develop a scenario for a lesson on one of the secondary school Computer
Science course topics with regard to the pedagogical techniques aimed to develop critical thinking and
implement it in the interactive e-learning resource (ELR) using one of the available network services
such as Learningapps”, “Develop a scenario and implement multimedia educational resource of an
informational nature to better explain theoretical material at Computer Science lessons”, “Develop a
scenario for an animation video aimed to explain problem-solving on the topic Executors of Algorithms
while playing and implement it in the context of popular cartoon characters”.
E-learning resources have been developed to support students’ educational activities in the
course of studying the module that implement individual educational routes during acquiring fac-
12
tual, conceptual and procedural knowledge in the logic of the hierarchy of cognitive activities
[Baranova, et al., 2020]. The resources are available via LMS Moodle. Acquiring the systematized
theoretical educational material on topics as well as presentations drawing students’ attention to key
concepts and topics and methodological materials containing questions and tasks for self-reflection in
line with tests contribute to the formation of students’ factual knowledge.
Solving problems related to the analysis of scholarly articles considering methods of Computer
Science teaching, articles based on concepts of writers of Computer Science school textbooks and
video clips with speeches of scientists and practitioners at thematic conferences contributes to the
expansion of students’ conceptual knowledge.
Procedural knowledge is strengthened by learning selected and systematized examples of Com-
puter Science video lessons in various conditions of equipping with IT by the use of different methods
of pedagogical techniques and certain effective methods aimed to teach schoolchildren to solve Com-
puter Science problems.
3.2 Experiment
The experiment designed to assess students’ readiness to solve the selected classes of problems aimed
at the development of teachers’ algorithmic competence, cognitive activities and digital competence
has been conducted for 6 years (since 2015). 63 students of Years 2–4, trained in the study field
of Teacher Education, specialization Computer Studies and Information Technology in Education,
Herzen State Pedagogical University, Saint Petersburg, took part in the experiment.
Table 5: Results of the survey on experts’ opinion about the correlation between the ability to solve
problems of the selected classes and the development of students’ digital competencies
Experts (teachers) working with the students participating in the experiment were surveyed in
the course of the experiment. The experts were asked to analyze the classes of problems and assess
their impact on the development of digital competencies. The table below shows the experts’ rates xij
(i from 1 to 10) of the correlation of all 5 groups of competencies that make up the digital competence
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in accordance with The Digital Competence Framework 2.0 and the selected classes of problems (j
from 1 to 5 ); the experts used the integer point system (from 0 to 4). The columns contain all
experts’ assessments of the whole group of competencies and the rows have each expert’s assessments
of each group of P competencies.
Mj = m 1
× m 1 xij - inter-rater agreement on the j group of problems; the closer the Mj rate is
to 4 (maximum possible point), the higher the experts assess the correlation of the relevant group of
competencies with students’ skills to solve the problems of the selected classes. The analysis of the
data obtained showed a high correlation of students’ skills to solve the problems of the selected classes
with the development of the information processing competencies (Mj = 3.4), a lower correlation with
digital content activities (Mj = 2.6) , problem-solving (Mj = 2.7) and communication competencies
(Mj = 2.0). Students’ skills to solve the problems of the selected classes have an even lower correlation
with competencies related to information security (Mj = 1.0).
The table 5 demonstrates the values of variance and root-mean-square deviation σj .
The inter-rater agreement key indicator was calculated according to the coefficient of variation
formula. The criterion was defined providing the closer the Vj is to zero, the higher is the level of
the agreement between the experts. It can therefore be concluded that the experts have a complete
agreement towards the 4th group of competencies (Vj = 0). The assessments of the other groups
of competencies mark a range of views (Vj ranges from 0.25 to 0.33) indicating a certain degree of
reliability corresponding to the value of the root-mean-square deviation σj .
The impact of skills to solve problems of the selected classes on the development of cognitive
activities using B. Bloom’s specific model was assessed in the experiment.
We note that prior to the experiment, both groups received initial training in Computer Science
and Teaching Methods. At the beginning of Year 2, students had to solve Computer Science and
Methodology problems of the relevant classes of problems and cognitive activities.
The next stages of experimental training were focused on the formation of skills to solve problems
of the selected classes as well as on the assessment of the degree of cognitive activities development
using B. Bloom’s specific model. The results of tasks performed by the students at the end of Years
3 and 4 are presented in Table 6. Columns with % indicate the percentage of completing tasks of the
relevant classes by students in each year.
Table 6: The results of the students’ cognitive activities formed as of the end of Years 2, 3 and 4
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The results show that solving problems related to analysis, data evaluation, creation of a software
product raises difficulties for students in the initial stage which is also observed during subsequent
training. However, mastery of these cognitive activities by students along with the rest demonstrates
an upward trend as well.
4 Conclusions
The described approach to training bachelors of pedagogical education through the system of tasks in
the logic of hierarchy of cognitive activities allows ensuring continuity in the study of special subjects
and is aimed at the formation of digital competencies of future Computer Science teachers willing to
effectively use and develop the information education environment.
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