Proceedings of the 9th International Conference on Technical and Vocational Education and Training (ICTVET 2022)

Development of Self-blend Learning Model for Computer and Network Engineering Expertise Package Based on Website in Vocational High Schools

Authors
Oskah Dakhi1, *, Maria Magdalena Zagoto2, Firman Edi3, Ishak1, Agus Rahmad Timor4
1Faculty of Engineering, University of Padang, Padang, Indonesia
2Faculty of Teacher Training and Education, University of Nias Raya, Teluk Dalam, Indonesia
3Engineering Management, Batam Institute of Technology, Batam, Indonesia
4Electromedical, Siteba Health Polytechnic, Padang, Indonesia
*Corresponding author. Email: pemdakabnisel@gmail.com
Corresponding Author
Oskah Dakhi
Available Online 2 May 2023.
DOI
10.2991/978-2-38476-050-3_28How to use a DOI?
Keywords
Self-Blend Learning; Computer and Network Basic; Online; Face to Face; SMK
Abstract

This study aims to develop a self-blend learning model in Computer and Basic Network subjects for class X SMK Computer Engineering and Website-Based Network Expertise Package that is valid, practical and effective. This type of research is research and development Research and Development by adopting the ADDIE model through stages; 1) Analysis, 2) Design, 3) Development, 4) Implementation, 5) Evaluation. The analysis technique uses the Aiken’V test to determine the validation of the model using expert tests and focuses on group discussions. The effectiveness test was conducted through a quasi-experimental. This research produces a self-blend learning model with five syntaxes: 1). Preparation Learning Orientation, 2). Access Content and Activities, 3). Access Content and Activities, 4). Assignment, Discuss, and Implementation Face to Face & Online, 5). Evaluation of The Learning Outcomes. This research is also equipped with product results in the form of self-blend learning model books, textbooks, teacher manuals, student manuals and guidebooks for using valid, practical and effective systems. Based on the findings, this self-blend learning model has proven validity, practicality and effectiveness, so it is suitable for use in Basic Computer and Network subjects. The implications of this research can be an alternative recommendation to optimize face-to-face and online learning.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 9th International Conference on Technical and Vocational Education and Training (ICTVET 2022)
Series
Advances in Social Science, Education and Humanities Research
Publication Date
2 May 2023
ISBN
10.2991/978-2-38476-050-3_28
ISSN
2352-5398
DOI
10.2991/978-2-38476-050-3_28How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

TY  - CONF
AU  - Oskah Dakhi
AU  - Maria Magdalena Zagoto
AU  - Firman Edi
AU  - Ishak
AU  - Agus Rahmad Timor
PY  - 2023
DA  - 2023/05/02
TI  - Development of Self-blend Learning Model for Computer and Network Engineering Expertise Package Based on Website in Vocational High Schools
BT  - Proceedings of the 9th International Conference on Technical and Vocational Education and Training (ICTVET 2022)
PB  - Atlantis Press
SP  - 249
EP  - 256
SN  - 2352-5398
UR  - https://doi.org/10.2991/978-2-38476-050-3_28
DO  - 10.2991/978-2-38476-050-3_28
ID  - Dakhi2023
ER  -