Subject Datasheet

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I. Subject Specification

1. Basic Data
1.1 Title
Civil Engineering Automation, Modelling
1.2 Code
1.3 Type
Module with associated contact hours
1.4 Contact hours
Type Hours/week / (days)
Lecture 1
Seminar 2
1.5 Evaluation
1.6 Credits
1.7 Coordinator
name Dr. Attila László Joó
academic rank Associate professor
1.8 Department
Department of Structural Engineering
1.9 Website
1.10 Language of instruction
1.11 Curriculum requirements
Compulsory in the Construction Information Technology Engineering (MSc) programme
1.12 Prerequisites
1.13 Effective date
27 February 2023

2. Objectives and learning outcomes
2.1 Objectives

The course's primary aim is to present and apply the application possibilities of the algorithmizing

and programming competencies learned in the first semester in digitization tasks in the construction

industry. During lectures, students will learn about domestic and international design, production, and

construction-related structural application examples that increase the efficiency of various construction

companies and projects, which are updated every six months. In the exercises, the students solve small

algorithmizing and programming tasks corresponding to their BSc level.

2.2 Learning outcomes
Upon successful completion of this subject, the student:
A. Knowledge
  1. has fundamental knowledge in the areas of algorithmic procedures and programming languages
  2. knows the connection possibilities between various programming languages and software systems
B. Skills
  1. recognizes algorithmic possibilities and can develop efficiency-enhancing procedures
  2. able to generalize and extend processes for broader use
  3. professionally communicates using programming technical terms
  4. selects the best software for particular automation procedures
C. Attitudes
  1. committed to efficiency gains
D. Autonomy and Responsibility
  1. independently looking for development opportunities
2.3 Methods

Presentation of domestic and international examples of automation and efficiency improvement through

corporate relations, partly with invited lecturers. Presentation of practical digitization examples and joint

implementation in a computer laboratory. Independent task solution, homework.

2.4 Course outline
Week Topics of lectures and/or exercise classes
1. Course introduction. Tekla introduction. Tekla automation example.
2. Compulsory consultation.
3. Axis FEM software introduction. Axis FEM software python automation example.
4. Compulsory consultation.
5. Revit introduction.Revit automation example.
6. Compulsory consultation.
7. Parametric design introduction.Parametric design automation example.
8. Compulsory consultation.
9. Project work.
10. Preparation for documentation, presentations, and soft skills.
11. Group presentations of Tekla automation HW. Group presentations of Axis FEM software automation HW.
12. Consultation and extended submission.
13. Group presentations of Revit automation HW.Group presentations of parametric design automation HW.
14. Consultation and extended submission.

The above programme is tentative and subject to changes due to calendar variations and other reasons specific to the actual semester. Consult the effective detailed course schedule of the course on the subject website.
2.5 Study materials

Mandatory literature:

1. Miroslaw J. Skibniewski (Editor-in-Chief): Automation in Construction, An International Research

Journal, Elsevier (

Recommended literature:

2. Daniotti, Bruno (editor), Gianinetto, Marco (editor), Della Torre, Stefano (editor): Digital

Transformation of the Design, Construction and Management Processes of the Built Environment,

Springer Open, (2020), ISBN: 978-3-030-33570-0

2.6 Other information
2.7 Consultation

Consultation dates can be found in the schedule of the course.

This Subject Datasheet is valid for:
2023/2024 semester II

II. Subject requirements

Assessment and evaluation of the learning outcomes
3.1 General rules

The assessment of the learning outcomes is specified in clause 2. above, and the continuous evaluation of student performance occurs via homework assignments, class questions, consultations, and oral exam.

3.2 Assessment methods
Evaluation formAbbreviationAssessed learning outcomes
1. homeworkHW 1A.1-2; B.1-4; C.1; D.1
2. homeworkHW 2A.1-2; B.1-4; C.1; D.1
3. homeworkHW 3A.1-2; B.1-4; C.1; D.1
4. homeworkHW 4A.1-2; B.1-4; C.1; D.1

The dates of deadlines of assignments/homework can be found in the detailed course schedule on the subject’s website.
3.3 Evaluation system
HW 125
HW 225
HW 325
HW 425
3.4 Requirements and validity of signature

Minimum 70% presence on lectures and consultations, successfully finish the HW's and oral exam.

3.5 Grading system
GradePoints (P)
excellent (5)90%<=P
good (4)75%<=P<90%
satisfactory (3)65%<=P<75%
passed (2)40%<=P<65%
failed (1)P<40%
3.6 Retake and repeat
The home works can be re-assigned one week after the original deadline by paying the related fees. The deadlines for the home works can be found on the homepage of the subject.
3.7 Estimated workload
contact hours14x2=28
preparation for presentations22
3.8 Effective date
27 February 2023
This Subject Datasheet is valid for:
2023/2024 semester II