Modeling the Results of Personnel Training for the Transport

Industry

V. S. Parshina

and T. B. Marushak

Ural State University of Railway Transport, Yekaterinburg, Russian Federation

Keywords: Modeling of educational processes, peculiarities of industry universities, Markov processes, evaluation of

learning results, management of learning processes, corrective action.

Abstract: The competencies acquired during the training are the basis for employers' assessment of the young specialists'

degree of readiness for specific activities. The purpose of the article is to develop a model of an internal

system for assessing the initial state of university applicants and the effectiveness of quantitative and

qualitative advancement of students in courses; and on their basis to determine the probability of their

successful graduation from the university. The data obtained is proposed to be used in the justification of

preventive measures to improve the quality of university graduates training. The results of the study are

presented, including the substantiation of methods for assessing the quality of training, the collection of

analytical data on quantitative and qualitative characteristics of discrete states of students for a specific

educational program. The modeling was carried out on the basis of stochastic Markov processes discrete in

time, describing the sequence of possible states of the objects of study with a certain probability. The results

obtained are of practical importance for the modernization of quantitative and qualitative results of students'

training based on their systematic assessment in the learning process.

1 INTRODUCTION

The task of increasing the level of human resource

development is determined by the economic and

social interests of society. It is implemented in the

form of competitiveness of educational institutions

graduates and personnel of organizations. Our

research on the formalization of the learning

management process at the university caused the need

to specify the target setting of the quality of training

specialists in accordance with the requirements of the

transport industry (Corporate Requirements for

Qualification of Russian Railways' Employees with

Higher and Secondary Professional Education). The

formulation of this task led to the development of a

model on the basis of which it is possible to carry out

operational and strategic management of qualitative

and quantitative components of the competitive

personnel training.

Currently, the complexity of assessing the level of

training of specialists for the industry is due to the

discrepancy between the requirements of the parties

https://orcid.org/0000-0002-3932-776X

https://orcid.org/0000-0002-4978-7137

to the components of the quality of training, which

makes it difficult to model and interpret the

assessment. The results of the analysis are presented

in more detail in (Parshina, 2013). The basis for the

formation of the competence model of an employee

of the transport industry is the condition of

compliance with state and industry educational

standards (Fig. 1).

Figure 1: Competency model of an industry worker.

170

Parshina, V. and Marushak, T.

Modeling the Results of Personnel Training for the Transport Industry.

DOI: 10.5220/0011581100003527

In Proceedings of the 1st International Scientiﬁc and Practical Conference on Transport: Logistics, Construction, Maintenance, Management (TLC2M 2022), pages 170-174

ISBN: 978-989-758-606-4

 2023 by SCITEPRESS – Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)

Currently, work is underway to form the general

requirements of the parties to the quality of graduates.

After ensuring this compliance, it is possible to adjust

the evaluation criteria.

2 MATERIALS AND METHODS

Emerging publications (with reference to employers)

about the incomplete compliance of the quality of

graduate training with the increased requirements of

the production and services sphere, put forward the

task of studying the causes of this phenomenon. At

the same time, there is a dropout of students during

training, which is reflected in the inefficient spending

of funds on training. Therefore, a comprehensive

study of the managerial impacts of the university on

the results of personnel training is relevant at the

present time. The analysis of theoretical sources

(Cripe, 2012; Mathis, 2012; Modern approaches to

knowledge management development. Collective

monograph, 2020; Bornmann, 2006; Black, 2009),

the review of modern practice in the field of education

(Sȧnchez, 2018; Alyahyan, 2020), the assessment of

the ratings of higher educational institutions and the

level of training in them by the eyes of employers

allowed us to identify problems of educational

activity that are insufficiently represented in the

literature and have specific character in this country.

Attention to the field of personnel training in the

world is initiated by the proclaimed general idea of

stable economic development. The formulated

national goals of educational processes are

complemented by intra-university systems for

monitoring and improving learning processes. The

review of modern literature demonstrates the

manifestation of the initiative of universities in

improving the quality of education. The experience of

the world's leading universities shows that the success

of an educational institution is determined by the

chosen strategy in the field of specialist’s training

quality (Care, 2018). One of the tasks is to develop

preventive measures to identify and work with

students at risk groups, which can significantly

increase the comprehensive effectiveness of training.

Such actions are conditioned by the desire to meet the

requirements of employers, students and their

parents. The effective and efficient application of

various methods of factual data analysis provides

solutions for determining the success factors of

university graduate. The study of the factors of

ensuring the quality of training, for example, in China

and Germany (Zhang, 2011), indicate the importance

of process management at various levels, including

the actions of the university.

The proposed research is aimed at developing a

methodology for analyzing the factual data of

educational processes to predict the effectiveness of

learning, keeping in mind the peculiarities of industry

education (Parshina, 2021; Parshina, 2019). With this

purpose, literature and modern information were

analyzed as part of the systematization of learning

processes. The analysis of the statistical methods used

to identify patterns, trends and probabilities using the

initial data is carried out. For data processing, the

Markov process method was chosen, which allows

predicting qualitative and quantitative indicators of

training specialists. The results obtained can be

converted into a compressed format and brought to

the involved university and corporation heads.

3 RESULTS AND DISCUSSION

To predict the quantity and quality of graduates of the

transport university an analytical review of the

students' achievements depending on the admission

score was made. Bearing in mind that the formation

of competencies occurs in the process of mastering

specific disciplines, the analysis of students' progress

in them was carried out. The general basis for

assessing the quality of education serves the progress

in educational programs for the entire period of study.

The level of students' competence is considered on

the specific educational program "Management"

(period of study in the university in 5 years). The

training standard assumes mastering 22 general

cultural and 50 professional competences.

To get the necessary basis for assessing the level

of competence formation it is proposed to use: the

results of examinations and tests on academic

disciplines, coursework design, the results of all types

of practices and defense of the graduate qualification

work. In order to formalize the quality of the achieved

competences the criteria presented in table 1 were

developed.

Table 1: Сriteria of competences formation.

An interval of a

students, estimation

The level of

competence, %

4,5-5,0 > 90

4,0-4,5 80 – 90

3,5-4,9 70 – 80

3,0-3,4 60 – 70

3,0 < 60

Modeling the Results of Personnel Training for the Transport Industry

171

Then the average score of the students of the

academic group for each discipline and the average

score of the group for each cycle were calculated. The

results of calculations and an overall assessment of

the level of competence formation within a particular

cycle are presented in fragments in Table 2.

Table 2: Estimation of the level of students, competences

formation.

Training

cycles

The

average

students

scores

Codes of

formed

competences

The level

compe-

tence for-

mation,

Humanitarian

, social and

economic

4,15 14 general

cultural

com

etencies

80 - 90

Mathematical

and natural

science

3,80 4 general

cultural

competencies

70 - 80

Professional 4,22 3 general

cultural and

professional

competencies

80 - 90

Physical

Training

4,14 1 general

cultural

com

etence

80 - 90

Training and

industrial

practices

4,68 3 general

cultural and 3

professional

competencies

90 and

above

Final State

Attestation

4,24 2 general

cultural and

professional

com

etencies

80 - 90

As follows from the table, the actual level of

competence formation among students not less than

70%. All general cultural competencies were

mastered in the learning process. Among them, the

highest level of mastering the following

competencies (more than 90%): the desire for

personal and professional self-development; the

ability to critically assess personal strengths and

weaknesses; the ability to carry out business

communication: public speaking, negotiations,

meetings, business correspondence, electronic

communications; as well as the ability to take into

account the consequences of managerial decisions

and actions from a position of social responsibility.

To a lesser extent, they have mastered: possession of

a culture of thinking, the ability to perceive,

generalize and analyze information, setting goals and

choosing ways to achieve.

To manage the process of training competitive

graduates, their modeling based on Markov processes

was used. A homogeneous Markov chain is

constructed on the basis of the results of the Unified

State Exam obtained during the differentiated

analysis of applicants for admission, students'

academic progress during the entire period of study,

and the number of students who were expelled for

failure (Fig. 2). As a result of the calculation of the

chain, a conclusion was made regarding the

probability of obtaining the necessary training of

specialists, the total risk of student expulsions and

expulsions risks for groups of students with different

school preparation and academic performance at all

stages of training were calculated.

Figure 2: General view of the Markov chain to describe the

training of students of a particular direction of training.

Here: S1 – first year students;

S2 – second year students;

S3 – third year students;

S4 – forth year students;

S5 – fifth year students;

S6 – students who achieved the final state

certification;

S7 – professionals who graduated from the

university;

S8 – university students.

We use the basic concept in the theory of Markov

processes - the state to describe the object under

study, going through the stages from the applicant to

the graduate of the university. A graph of the states of

the Markov chain relative to the learning process at

the university is compiled in a general form and its

transition probabilities are marked up. The notation p

is used to describe the transition probability. So, to

change the state of S1 for a year, it is possible to

switch to the state of S2 with a probability of Р12, etc.

The academic performance of each student over the

entire period of study was analyzed. Further, based on

TLC2M 2022 - INTERNATIONAL SCIENTIFIC AND PRACTICAL CONFERENCE TLC2M TRANSPORT: LOGISTICS,

CONSTRUCTION, MAINTENANCE, MANAGEMENT

172

the calculations carried out, the probability with

which the student will move to the n-state next year

is determined; at the same time, he has improved or

worsened his condition. Low academic progress in

the initial period is determined by insufficient school

preparation of students. Basically, students who had

difficulties mastering the educational material in the

process of learning are expelled. Timely measures

taken (additional classes, assignment of a more

qualified teacher, involvement in the creative process,

etc.) will allow keeping the contingent of students.

Based on the data obtained, calculations were made

of the probability of first- and next-year students

moving up to the next level within the allocated point

ranges (Fig. 3).

Figure 3: Matrix of probabilities of students’, transition to

the next course on groups in the distinguished intervals of

progress.

Next, the generalized values of the probability

matrix of students' advancement in a certain

educational program are calculated (Fig. 4).

Figure 4: Generalized values of the transition probability

matrix of students to the next course.

According to Figure 4, the probability of

transition of all students from the first year to the

second one is 0.73, from the second year to the third

one – 0.88, etc. There are practically no deductions in

the last year and all students defend their final

qualifying work. The analysis showed that first-year

students find themselves in a situation of the greatest

risk of expulsion. The probability of expulsion of a

fifth-year student is almost zero. Based on the logical

addition of risks, we calculate the overall degree of

risk of a student's expulsion in the learning process

(P):

Р = 0,27*0,88*0,97*1*1 + 0,12*0,73*0,97*1*1 +

0,03*0,73*0,88*1*1 + 0+ 0 = 0,32

The total risk of expulsion of a student for 5 years

of study is 0.32. Assistance to students in mastering

the educational program at any stage of preparation

will improve the quantitative and qualitative

effectiveness of the education process and increase

the efficiency of funds invested in training.

4 CONCLUSION

The process of preparing students at the university is

described in terms of the theory of Markov processes.

Modeling of learning processes and training results

with indication of stationary states and identification

of transition probabilities between them is carried out.

The data obtained is proposed to be used to manage

the quantitative and qualitative components of the

effectiveness of educational activities of the

university. The conclusions can be used by heads of

the University to implement timely and strategic

actions to optimize the level of development of

students’ competence mastering, reducing the

percentage of students’ expulsions, by students to

plan their own personal learning process and the

likelihood of graduation, and by heads of the transport

industry for the planning and selection of candidates

for training. The presented materials illustrate only a

part of the research carried out for the industry on the

improvement of the interaction of branch universities

and structural divisions of the corporation.

REFERENCES

Corporate Requirements for Qualification of Russian

Railways' Employees with Higher and Secondary

Professional Education. Approved 17.11.2009.

Parshina, V. S., Gusev, A. A., 2013. Theoretical,

methodological and organizational and

methodological aspects of training leaders based on a

preliminary assessment of their competencies in the

learning process. Yekaterinburg: UrGUPS, RF. p. 179.

Cripe, E., 2012. Competency development guide.

Workitect, Inc., p. 276.

Modeling the Results of Personnel Training for the Transport Industry

173

Mathis, R. L, Jackson, J. H., 2012. Human Resource

Management: Essential Perspectives. Cengage

Learning, p. 288.

2020. Modern approaches to knowledge management

development. Collective monograph. Ljubljana,

Slovenia ljubljana school of business. p. 542.

Bornmann, L., Mittag, S., Daniel, D., 2006. Quality

assurance in higher education – meta-evaluation of

multi-stage evaluation procedures in Germany. Higher

Education. 52. pp. 687–709.

Black, P., William, D., 2009. Developing a theory of

formative assessment. Education-al Assessment,

Evaluation and Accountability (formerly: Journal of

Personnel Evaluation in Education). 21(1), 5.

Sȧnchez, A., Paniagua, E., Simpson, O., 2018. Journal of

Interactive Media in Education. pр. 1-10.

Alyahyan, E., Düştegör, D., 2020. Predicting academic

achievement in higher education institutions: a

literature review and best practices. International

Journal of Educational Technology in Higher

Education, 17, 3.

Care, E., Kim, H., Vista, A., Anderson, K., 2018.

Optimizing assessment for all. Education system

alignment for 21st century skills. Focus on assessment.

Brookings. USA. p. 41.

Zhang, F., Fang, W., Zhou, C., Liu, Z., 2011. A brief study

on teaching evaluation system based on fuzzy rule with

scientific teaching materials. In Advances in Computer

Science, Environment, Ecoinformatics and Education.

pp. 99-105.

Parshina, V. S., Gusev, A. A., Sizy, S. V., 2021. Сorporate

governance of industry-specific education. In the

collection: AIP conference proceedings. Scientific

conference on railway transport and engineering

(RTE). p. 100006.

Parshina, V. S., Kuznetsova, E. V., 2019. Interaction

between industry higher educational institutions and the

customer of educational services. In the collection: E3S

Web of Conferences. Innovative Technologies in

Environmental Science and Education (ITESE). p.

04001.

TLC2M 2022 - INTERNATIONAL SCIENTIFIC AND PRACTICAL CONFERENCE TLC2M TRANSPORT: LOGISTICS,

CONSTRUCTION, MAINTENANCE, MANAGEMENT

174