The 143rd Installment
AIIT’s Own DX Education System
by Hiroshi Hashimoto,
Professor, President of Advanced Institute of Industrial Technology
In the academic year 2021, this Institute introduced AIIT’s own “Digital Transformation (DX) Education System” as a prototype for DX skill education. I will explain this. Nowadays, we often see the term Digital Transformation (DX). In Japan, this term is used with an expanded meaning compared to the definition given in E. Stolterman and A. C. Fors, “Information Technology and the Good Life,” DOI:10.1007/1-4020-8095-6_45 (2004), in which the term is said to have originated.
It seems, however, that in either definition, DX refers to actions that change the content, quality, values and other elements of the effect on the target. AIIT was the only public university selected by the Ministry of Education, Culture, Sports, Science and Technology (MEXT) to implement "Initiative 2: Improvement of the Quality of Learning" under the FY2020 Subsidy for University Reform Promotion (Digital Education Enhancement Project).
Project title: Building Co-creative Skill Learning Platform for Skill Education Enhancement
https://aiit.ac.jp/education/dx_project/
It was in this project that we introduced AIIT’s own DX Education System. Before explaining the education, I define what we mean here by “skill.” “Skill” refers to the production of some value under the sensory-motor integration of knowledge, perception, and body movement.
For example,
Tennis: the knowledge of the rules, the somatic sensation of hitting the ball, the physical movement that embodies that image. The value to be produced is hitting a good shot.
Mirror finishing of lenses: the knowledge of optics, the perception of light and a feel during polishing, the movement of hand while polishing that can embody the image from that knowledge and experience. The value to be produced is the production of optically good lenses.
Skills also produce value in various other fields, such as traditional craft production, dance, and cooking. Skills involve perception and physical action. The human organism consists of approximately 200 bones, 400 skeletal muscles, and 20 sensory systems. The size of the bones, the motion range of the joints, and the sensory perception vary depending on the degree of growth and experience.
Furthermore, the degrees of freedom of movement are enormous. Therefore, in fact, it is impossible for even the most skilled instructor to accurately watch all the movements of the learner. This is where the tacit knowledge of the instructor inevitably intervenes, allegedly leading to inefficiencies in skill training.
Reference: Research and Demonstration of Co-creative Skill E-Learning Service Using Visualization of Experience Value
https://projectdb.jst.go.jp/grant/JST-PROJECT-13418878/
This AIIT project aims to “improve the efficiency” of skill learning of “beginners” in these areas. Here, “beginners” and “improve the efficiency” may require some explanation. The members of this project are from technical colleges (15 or older), undergraduate programs (18 or older), graduate schools (22 or older), and companies (of all ages), and each beginner has a different knowledge, different experience level, and different physical structure than the rest. Therefore, teaching methods are naturally expected to differ from one beginner to another.
Nevertheless, for some reason, in Japan, the same documents and the same content are often used for all. Improving the efficiency of education does not mean merely reducing costs. It is true that we want to reduce the time for learners to reach a certain level, but different people have different learning abilities. Therefore, if we apply a uniform time frame to all learners, some of them will drop out. This is not a good education method. The goal of education is, after all, to help learn something deeply (see, for example, Shinichi Mizokami’s argument.) To achieve this, it would be better to tailor a method, time and goal of learning to each learner. Today, this is sometimes discussed as gamification, but this has long been known in educational theory.
However, as it is difficult to put into practice, few have benefited from such education. Since I am talking about learning, I will introduce some educational theories briefly and explain how to incorporate them into this project. The term “educational learning objective” is familiar to anyone in the teaching profession. Its global standard is Bloom's Revised Taxonomy.
This also indicates education levels. However, this is a classification of educational learning objectives, so we must consider how to reach each objective separately. In our project, we examined the instruction manuals for scientific or engineering experiments used in several universities and technical colleges comparing them to the revised Taxonomy, and we found out that those manuals place emphasis on knowledge acquisition, and there were few descriptions of skill acquisition.
Furthermore, none of them focus on enhancing applicability or creativity. This led us to a hypothesis that it may be difficult to inspire today’s young beginners with interest in experiments and motivation to learn. For human learning, it is important to design the process and consider its implementation. Famous for this theory is the learning process of Y. Engeström. It consists of the following steps.
Motivation > Orienting > Internalization > Externalization > Criticizing > Controlling
Without going into details, internalization means input in learning, externalization is output, criticizing is evaluation, including self-assessment, and controlling is the ability to tackle new issues and exercise creativity. Motivation, the first step, is necessary to drive the learning process to the last step, controlling.
However, it is difficult for beginners to motivate themselves to start learning on their own. They need external motivation. To make matters worse, many instruction manuals for scientific or engineering experiments do not provide guidance for criticizing nor controlling, and consequently, we have heard of several cases in which learners have lost their motivation during the transition between one experiment and the next.
One key to successful learning is, I say, consistency in learning. The impetus to maintain consistency is the motivation toward learning. As a theoretical framework of this motivation, we introduced A. Bandura’s self-efficacy into our project.
Self-efficacy is considered an important determinant of human behavior in the context of social learning. There are several factors determining self-efficacy, but in our project, we focused on the following two:
Enactive attainment: accumulating successful experiences.
Social persuasion: generally, being approved (praised or encouraged) by others.
In this project, we have constructed an educational system utilizing IT and DX technologies, such as multimedia, multiple-perspective video, VR, chatbot and cloud, so that learners can use it at any time and from any place, and moreover, perform imagery rehearsals on their perceptions and bodies. We have found some cases in which this type of learning contributed greatly to the preparation of experiments and other activities.
Among its other benefits are giving beginners self-efficacy, allowing them to begin the learning process smoothly, and facilitating internalization at their own pace.
We have also adopted a chatbot to raise learners’ interest in reviewing the experiments they conducted. Interaction with the chatbot lowers the psychological barrier against asking questions. We came up with this idea from the above-mentioned considerations.
The feasibility study (FS) we started in the second half of the academic year 2021 led us to findings on motivation and learning methods that had not been observed in conventional learning methods. In the academic year 2022 we will be verifying these findings. We will share these results and findings with the public through academic conferences, forums, and workshops.