DIGITAL LIBRARY
DESIGN OF ADAPTIVE MICRO-MODULES FOR AI-RELATED COURSES USING 2D DEPTH MATRIX
LuleƄ University of Technology (SWEDEN)
About this paper:
Appears in: INTED2023 Proceedings
Publication year: 2023
Pages: 7203-7207
ISBN: 978-84-09-49026-4
ISSN: 2340-1079
doi: 10.21125/inted.2023.1972
Conference name: 17th International Technology, Education and Development Conference
Dates: 6-8 March, 2023
Location: Valencia, Spain
Abstract:
One of the issues that must be addressed during the course design stage is building a flexible course that can target multiple levels of target audiences. This requirement may be much more important when developing an industry-oriented training program. In (mining, but also in other) industries, there are several roles with various requirements; as a result, people with various educational backgrounds, work experiences, and demands will be present. On the other hand, Students in academia might also benefit from this flexible design, as they have different passions for learning though they are at the same level.

The fundamental idea behind this paper is to create a micro-module matrix concept for course design, which will allow the course to be tailored to different target groups by picking certain micro-modules from the prepared micro-module bank. The availability of micromodule materials with reference depth matrix will freeing teachers from time-consuming module preparation and multiple course design for different levels. Each micro module will consist of a recorded video/lecture, a quiz with immediate feedback, a peer-reviewed assignment, and a knowledge reflection question. The recorded video will be short in time and concentrate on one idea, guaranteeing more cognitive engagement from the students. The quiz will be designed to check whether the learning objectives of the designed course have been achieved. A micro-module matrix will be designed and applied on top of the generated bank to propose a flexible course that can target audiences from different backgrounds and meet their interest.
Keywords:
Micro-modules, adaptive course design, industrial courses, reference depth matrix.