• A
  • A
  • A
  • АБВ
  • АБВ
  • АБВ
  • А
  • А
  • А
  • А
  • А
Обычная версия сайта

Design and development of automated training systems (ATS)

Учебный год
Обучение ведется на английском языке
Курс обязательный
Когда читается:
2-й курс, 1, 2 модуль


Course Syllabus


The course "Design and development of intelligent tutoring systems (ITS)" introduces students to the main types of intelligent tutoring systems, their areas of application in various fields of activity, the architecture of the ITS and the features of its design from the standpoint of the user-centered design (UCD) concept. The fundamentals of pedagogical design are outlined, correlations between the concepts of user experience and learner experience are considered, and the main methods of researching user experience (UX) are analyzed. Considerable attention in the course is paid to the consideration of the possibilities of computational linguistics for solving various problems associated with the design of ITS, including personalized ones, and user experience research.
Learning Objectives

Learning Objectives

  • familiarization of students with the key aspects of modern teaching systems, with the main scientific areas based on bibliometric analysis with visualization, with Russian and English terminology in this field;
Expected Learning Outcomes

Expected Learning Outcomes

  • A student understands the main issues of the course, is able to formulate questions relevant to the study of the course
  • A student understands the scope of ITS
  • A student knows the main stages of ITS development, knows how to use existing ITS
  • A student knows the main approaches to the design of ITS components, is able to select the optimal set of components for a specific task
  • A student knows the basics of product design, knows how to choose methods for designing ITS as a product
  • A student knows the principles of user-centered design, is able to take these principles into account when designing ITS
  • A student knows the techniques of gamification in education, is able to apply gamification methods in the design of ITS
  • A student knows main models of pedagogical design, is able to apply them to a specific task
  • A student knows the main methods of user experience research in the field of edtech, is able to apply them to explore user experience and learner experience
  • A student knows the features of ITS user interfaces and the principles of UI/UX design of educational online courses
  • A student understands the areas of application of computational linguistics technologies in the development of ITS.
  • A student knows and can apply corpus technologies to create ITS
  • A student knows and applies ITS data collection and analysis technologies, is able to collect data in a specific subject area
  • A student is proficient in basic predictive analytics, is capable of creating AOC with personalized learning in mind
Course Contents

Course Contents

  • Topic 1.
  • Topic 2.
  • Topic 3.
  • Topic 4.
  • Topic 5.
  • Topic 6.
  • Topic 7.
  • Topic 8.
  • Topic 9.
  • Topic 10.
  • Topic 11.
  • Topic 12.
  • Topic 13.
  • Topic 14.
Assessment Elements

Assessment Elements

  • non-blocking Homework
    Homework assignments are small practical assignments that students complete outside of the classroom. It is carried out in writing, individually, extracurricularly. The completed assignment is sent to the teacher by e-mail. The teacher evaluates the independent work of students on homework given out in practical classes - at the same time, the correctness of the choice of the method for solving the problem is assessed in accordance with pre-established criteria. All elements of the current control are retaken within a period of not more than 7 days after receiving an unsatisfactory assessment. If necessary, remote support for control (issuing tasks, checking work, etc.) is carried out using e-mail. branch resources.
  • non-blocking Report
    The report is the results of an independent critical analysis of a particular problem within the course. The report is presented in the form of a presentation. At the end of the report, the student should formulate one or two questions for further discussion addressed to the audience.
Interim Assessment

Interim Assessment

  • 2023/2024 2nd module
    0.6 * Homework + 0.4 * Report


Recommended Core Bibliography

  • Osondu, O. (2021). A First Course in Artificial Intelligence. Bentham Science Publishers Ltd.

Recommended Additional Bibliography

  • Haenlein, M., & Kaplan, A. (2019). A Brief History of Artificial Intelligence: On the Past, Present, and Future of Artificial Intelligence. California Management Review, 61(4), 5–14. https://doi.org/10.1177/0008125619864925