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Record W7143785423 · doi:10.18999/nueduca.65.2.1

教育におけるテクノロジーの研究と質的研究方法論

2019· article· ja· W7143785423 on OpenAlexaboutno aff
尚 大谷, Takashi Otani

Bibliographic record

VenueInstitutional Repositories DataBase (IRDB) · 2019
Typearticle
Languageja
FieldComputer Science
TopicEducational Robotics and Engineering
Canadian institutionsnot available
Fundersnot available
KeywordsGraduation (instrument)Technology educationOrder (exchange)Educational technologyComputer technologyHigher education

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.952
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.014
GPT teacher head0.241
Teacher spread0.226 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2019
Admission routes1
Has abstractyes

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