ERIC Number: EJ1377816
Record Type: Journal
Publication Date: 2023
Pages: 14
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-1539-1523
EISSN: EISSN-1945-0818
Available Date: N/A
Distributed Interpretation -- Teaching Reconstructive Methods in the Social Sciences Supported by Artificial Intelligence
Journal of Research on Technology in Education, v55 n1 p111-124 2023
This article highlights teaching and learning in reconstructive research supported by artificial intelligence (AI) and machine interpretation in particular. The focus is whether the traditional teaching of methodological competence through research workshops can be supplemented with artificial intelligence (natural language processing, NLP) implemented in computer-assisted qualitative data analysis software (CAQDAS). A case study shows that AI models can be trained to interpret texts. Thus, distributed interpretation by humans and AI becomes possible, opening up new possibilities for teaching qualitative methods. How people deal with these new possibilities is presented based on an explorative evaluation of a group discussion with young researchers. Finally, this contribution discusses the possibilities and limits of this new form of interpretation "together with a machine."
Descriptors: Artificial Intelligence, Social Science Research, Qualitative Research, Technology Uses in Education, Research Skills, Research Methodology, Workshops, Computer Software, Man Machine Systems, Researchers
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Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A
Author Affiliations: N/A