Notice bibliographique
Résumé
The purpose of this essay is to reflect on the author’s personal history of studies on technology in education and qualitative research methodologies, in order to consider the path he has followed and to discern the way ahead as a researcher. He firstly reveals that he had lots of questions about education and schools even when he was an elementary school student. He then changes the topic to his high school years. His school was newly established, and therefore had various problems. At that time, he also wondered about the educational technology installed at the elementary school affiliated with his high school, which remained unused. He was hoping to study education in college, then lost his interest in traditional “education study” while still retaining a deep interest in education itself. Around that time, he met Professor Ono and wrote a graduation thesis under his academic supervision. This led to entering the Graduate School of Education, where he began studying under Professor Ono’s exceedingly unique academic advice. He also started learning about computers at the university’s academic computing center under Professor Nakayama. Furthermore, was briefly involved in a Classroom CAI (Computer Assisted Instruction) project. Following this significant experience, he took a position at the Center for Educational Technology at the Faculty of Education, Nagasaki University. He struggled with mini-computers there, but soon started to develop various applications for personal computers in education. He also developed an original lesson analysis system with a personal computer and input Japanese transcripts into it. At the same time, he helped students in statistics. He was studying it with Professor Terasaki of the university. At that time, he identified a lot of questionable lessons in the university laboratory school, and wrote a related research article. He also worked for the removal of educational instruments, which were no longer being used in public school classrooms. The educational instruments had been installed for a big national educational technology project that had finished before he moved to Nagasaki. It seemed contradictory to him that such enormous project had completed but noshing remained except for such unused instruments. He was not satisfied with simply making positive statements about the functions of educational technologies in those days, either. He had an inherent desire to conduct his own empirical study to examine the meaning and significance of technology use in education including its negative aspects. In this frame of mind, and during his last year in Nagasaki, he met two young Canadian researchers of educational technology: Dr. Brine and Dr. Johnson. They immediately understood his research interest and offered to help. After they left Japan, they sent him their PhD Dissertations and a book written by their academic advisor Professor Ronald G. Ragsdale of the University of Toronto. His book was quite unique and full of considerations about the meaning of computer use in education from both positive and negative viewpoints. This author then moved to Nagoya University and began investigating an empirical research approach relevant to classroom computer uses and their socio-cultural aspects. He had gradually understood that qualitative research methods are the very ones that could enable him to carry out such research, and that Professor Ragsdale was the very researcher who had been engaged in such research. He visited the Ontario Institute for Studies in Education at the University of Toronto and commenced a qualitative research project on computer uses in education working with Professor Ragsdale and his team for a year funded by the Japan Foundation. Being in Canada provided him with the opportunity to see Japan’s education from the outside, and he learned a lot about educational programs and researcher training in North American graduate schools. After he had returned to Japan, he started localizing the qualitative approaches to adjust them to the socio-cultural context of Japan’s schools, while also trying to transform the relationship between schoolteachers and the researcher. He was also active in discussion with quantitative researchers. This had now become a precious foundation for him to have a comprehensive understanding of “research” which included both quantitative and qualitative methods. He also started his own qualitative research on educational computing. He was also granted an opportunity to work for an additional year at the University of Toronto, which was funded by MEXT. The purpose of the stay was the investigation of graduate programs for teachers in comparison with graduate programs of medical, legal, and ecclesiastical professions, which were the traditional professions in European culture. He also aimed at checking his own qualitative study which he had been developing by himself with the development of qualitative studies at the University of Toronto where he first engaged in it. He had opportunities to observe state-of-theart qualitative studies, such as art based/informed studies and performance ethnographies. After returning to Japan from Canada, he developed a graduate seminar focused on qualitative research methodologies. And he created an original qualitative data analysis method “SCAT” (Steps for Coding and Theorization). SCAT has been spreading to various research fields including the area where quantitative approaches were absolutely dominant previously. SCAT does not mix the codes from interviews or observations. SCAT always analyzes each interview and each observation in the same manner that class room analysis (lesson study) is done, lesson by lesson. That is, the integrity of each lesson is maintained and it is studied as a lesson. Thus, the codes from different interviews or observations are not mixed, and moreover, SCAT does not ignore the continuity and time-sequential aspect of each interview or observation. Since before his second stay at the University of Toronto, he had been participating in medical and medical education research as a qualitative researcher and as an education researcher. This aspect of his work has been undergoing development year by year. At the same time, he has been working with quantitative medical researchers to train medical doctors in their clinical research skills. This has been a precious opportunity for him to acquire a relativized perspective on quantitative and qualitative approaches in alternative context. This has also enabled him to start a “research protocol seminar and workshop in medical and medical education (health science and health professionals education)”. He has started disseminating it into humanities and social sciences. In turn, he is reflecting on the mutual influence of above mentioned elements of his research opportunities and experiences. Finally, he argues that qualitative research is such an “international research language” for nonnumeric empirical sciences that it not only enables you to exchange and share the research outcomes and cooperate with international researchers of the same research areas, but also it enables meaningful communication among even those researchers with different research areas.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,007 | 0,025 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,004 | 0,008 |
| Communication savante | 0,006 | 0,006 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».