H. Uchida, M. Kunigami, T. Terano, A. Yoshikawa

Tokyo Institute of Technology (JAPAN)
Experiential learning is useful for business people to acquire practical skills to discover and to solve complicated problems. Case Method pioneered by Harvard Business School faculty is also an experiential learning and effective in executive education. A business case is a document with a story based on real problems in management. Practically business people, however, in addition to those documents, they also comprehend the situation by nonverbal information.
We developed an educational method, referred as Situated Intelligence Training (SIT) using MANGA (Japanese comic) case materials. The goals of learning by this method are to read and understand deeply the case described by the MANGA and texts and also to improve the problem solving abilities.
The learners in SIT gain awareness, which they cannot put into words. Our problem is how we measure the awareness. We previously measured learning effects using surveys and reports, but it is difficult to design non-leading questions.
We developed a new method to evaluate the learning effects, referred as Persona Conjoint Method (PCM). PCM measures the change of the learner awareness. PCM satisfies some conditions; including 1) to measure quantitatively the learner’s individual change of understanding, 2) to design non-leading questions, and others.

PCM consists of Persona-Based Design and Conjoint Analysis used in marketing and product development.
Persona-Based Design, proposed by Cooper (2004), is a user-centered design method. Fictional user, so-called Persona, is expressed with its specific story, which is how the persona behaves.
Conjoint Analysis is a method to measure user's preference for a product with multiple attributes. Green (1971) states that Conjoint Analysis is useful to discover a user’s implicit value worth of the product. Full Profile, a type of Conjoint Analysis, creates a set of product profiles with attributes and then respondents rank or rate these profiles. There is a method using an orthogonal array to reduce the number of profiles.
Using the array, PCM generates a set of fictional characters' profiles as Personas to substitute the character of the case. With Conjoint Analysis, PCM can detect the effective attributes of the Persona set reflected in the learner’s awareness.

We conducted two experiments by SIT using MANGA case materials to evaluate the validity of PCM. Implicit awareness is one of the results from the learning in SIT. We confirmed the changes in the learners' cognition. We detected the presence of the changes from PCM and analyze the number of subjects showing similar changes.
The first experiment was for students. As we expected, changes were not detected because the students had never worked in business yet, so it was difficult to read the case deeply.
The second experiment was for business people. We anticipated that some people would show changes because they had business experience. Around 37% of the people showed changes in the experiment.

We applied PCM to practically learn and to measure the possible changes in the learner’s understanding of the case. The results showed the obvious difference between the two experiments, but there is room for reconsidering this matter because two experiments were entirely under different environment and conditions. The application of PCM remains as a matter to be discussed and needs further experiment.