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Online individual interviews of a minimum of 10 high-performance or experienced faculty members will be arranged via Zoom. The interviews will last a maximum of one hour each and are recorded as videos/audios and will be transcribed using the otter.ai service.
The participant can expect approximately one hours' commitment in this interview.
The university teachers should meet at least one of the following criteria:
had online teaching experience during the pandemic period; OR
received education award in the past five years; OR
received a high rating from students regarding their teaching.
There is no perceived risk for the participant in this research. By participating in the interview, high performance instructors can reflect on their teaching experience from the lens of active learning.
Being a subject is voluntary, and your free will is respected.
Even if you agree to be a subject, you can withdraw at any time during this project.
Your participation in this project is voluntary. Your withdrawal from it will not result in any disadvantageous consequences.
In case of withdrawing, please contact the principal investigator of this project by referring to the contact information in this document.
If withdrawn, the data of you obtained up to that point of your withdrawal will be discarded and will not be used in the research.
If the research results have already been submitted or published, or if the data are completely anonymized and cannot be identified, they cannot be discarded.
If you withdraw from this research project, the incentive if paid must be returned, if unpaid yet it will not be paid.
The result of this project will be published in academic publication outlets such as conferences and journal articles.
The interview data, before being shared with the joint research collaborators, will remove the identity information of the interviewee. Therefore, during the data analysis stage, interviewees of both sides will remain anonymous.
All personal information will be omitted during the writing and the reporting process. All participants will be anonymous. No data such as name or affiliation will be made identifiable to track the subjects.
For the interview research as a collaboration between TUT and HKU:
During the collaboration stage, the interview files will be shared from the HKU investigators to the TUT principal investigator via Google Cloud to import into utter.ai tool for automatic transcription generation. The identifier information from all transcripts will be removed before entering the data analysis phase.
After the collaboration stage, all data (e.g., interview files) containing personal identifiers will be kept for a maximum of five years after the publication of the first paper. For original interview files, they will be separately stored and managed by each side’ researcher(s) meaning that the TUT researcher managing the TUT interview files and the HKU researchers managing the HKU interview files. Personal identifiers will be removed for the longer-term retention of the research data. All files will have cloud storage via Google Cloud and local storage via external hard disk.
For the experiment as a research activity only at TUT:
All data containing personal identifiers will be kept for a maximum of five years after the publication of the first paper. Personal identifiers will be removed for the longer-term retention of the research data.
If you desire, you may request materials on research plans and research methods. These materials can be browsed within the range that does not interfere with the personal information of other subjects, and the securing of originality of research.
To submit such a request, please contact the principal investigator of this project by referring to the contact information at the beginning of this document.
There is no conflict to claim in this research.
Participating in this interview is totally voluntary and there is not incentive to be paid to the interviewees.
Within five years upon receiving the consent and collecting the data from the subject, if there arises some follow-up research such as comparative research with scholars at other research institutes, no further consent will be needed from the subject. However, all data collected should be anonymized to protect the personal information of the subject.
Contact for inquiries regarding the contents of the research plan
Principal Investigator:
Dr. Lin Jingjing
Assistant Professor
Center for IT-based Education, Toyohashi University of Technology
Phone: 0532-44-1308, E-mail: lin.jingjing.qc@tut.jp
Contact for research ethical review, complaints, etc.
Research Support Division, Toyohashi University of Technology
Phone: 0532-44-6982
E-mail: kensien@office.tut.ac.jp
Consent form used for interviewees at TUT 豊橋技術科学大学に被験者同意書
Conset form used for interviewees outside TUT
Step 1: Recruit interviewees by Email.
If a teacher agrees to participate, s/he needs to sign the online consent form.
Step 2: Schedule the interviews by Email.
The teacher who signed the online consent form will be contacted to arrange the interview with them.
Step 3: Conduct online individual interviews by Zoom.
On the scheduled date and time, the researcher conducts a one-hour interview with the interviewee. The interview will be conducted by using Zoom. The whole interview will be recorded, both video and audio.
Step 4: Transcribe the audio file of the interviews by otter.ai.
Once an interview is completed, the recorded conversation will be available as a video file and an audio file as the recording outputs of a Zoom meeting. The audio file will be imported to otter.ai and automatically transcribed. The TUT principal investigator will use otter.ai to automatically transcribe all interviews.
Step 5: Review and correct the transcripts manually.
In case of auto-transcription having mistakes here and there, the manual review of the transcribed files is needed to increase the precision rate of the content.
The TUT principal investigator will remove the identifier information from the transcripts of interviews at the TUT side. The HKU collaborators will remove the identifier information from the transcripts of interviews at the HKU side.
All interview transcripts, from both TUT and HKU sides, after removing the identifier information will be manually checked by Cindy and Lynn at HKU side to increase the precision of the transcripts.
Step 6: Analyse the content.
The researchers will analyse the interview transcripts in detail.