{"?xml":{"@version":"1.0"},"edm:RDF":{"@xmlns:dc":"http://purl.org/dc/elements/1.1/","@xmlns:edm":"http://www.europeana.eu/schemas/edm/","@xmlns:wgs84_pos":"http://www.w3.org/2003/01/geo/wgs84_pos","@xmlns:foaf":"http://xmlns.com/foaf/0.1/","@xmlns:rdaGr2":"http://rdvocab.info/ElementsGr2","@xmlns:oai":"http://www.openarchives.org/OAI/2.0/","@xmlns:owl":"http://www.w3.org/2002/07/owl#","@xmlns:rdf":"http://www.w3.org/1999/02/22-rdf-syntax-ns#","@xmlns:ore":"http://www.openarchives.org/ore/terms/","@xmlns:skos":"http://www.w3.org/2004/02/skos/core#","@xmlns:dcterms":"http://purl.org/dc/terms/","edm:WebResource":[{"@rdf:about":"http://www.dlib.si/stream/URN:NBN:SI:doc-CWDUEH56/769e822b-79fa-4de0-a1e4-2c8e3f2242bc/PDF","dcterms:extent":"337 KB"},{"@rdf:about":"http://www.dlib.si/stream/URN:NBN:SI:doc-CWDUEH56/9bceb910-47c0-4529-adea-8d142977e014/TEXT","dcterms:extent":"54 KB"}],"edm:TimeSpan":{"@rdf:about":"1982-2025","edm:begin":{"@xml:lang":"en","#text":"1982"},"edm:end":{"@xml:lang":"en","#text":"2025"}},"edm:ProvidedCHO":{"@rdf:about":"URN:NBN:SI:doc-CWDUEH56","dcterms:isPartOf":[{"@rdf:resource":"https://www.dlib.si/details/URN:NBN:SI:spr-T2GYXHDC"},{"@xml:lang":"sl","#text":"Socialno delo"}],"dcterms:issued":"2024","dc:creator":"Mesec, Blaž","dc:format":[{"@xml:lang":"sl","#text":"številka:3"},{"@xml:lang":"sl","#text":"letnik:63"},{"@xml:lang":"sl","#text":"str. 217-237"}],"dc:identifier":["ISSN:0352-7956","DOI:10.51741/sd.2024.63.3.217-237","COBISSID_HOST:221979139","URN:URN:NBN:SI:doc-CWDUEH56"],"dc:language":"sl","dc:publisher":{"@xml:lang":"sl","#text":"Fakulteta za socialno delo"},"dc:subject":[{"@xml:lang":"en","#text":"artificial intelligence"},{"@xml:lang":"sl","#text":"človeška inteligenca"},{"@xml:lang":"en","#text":"grounded theory"},{"@xml:lang":"en","#text":"human intelligence"},{"@xml:lang":"sl","#text":"kvalitativna analiza"},{"@xml:lang":"en","#text":"methodology"},{"@xml:lang":"sl","#text":"metodologija"},{"@xml:lang":"en","#text":"retirement"},{"@xml:lang":"sl","#text":"umetna inteligenca"},{"@xml:lang":"sl","#text":"upokojitev"},{"@xml:lang":"sl","#text":"utemeljena teorija"}],"dcterms:temporal":{"@rdf:resource":"1982-2025"},"dc:title":{"@xml:lang":"sl","#text":"Strategije komuniciranja s chatGPT pri kvalitativni analizi besedil|"},"dc:description":[{"@xml:lang":"sl","#text":"The article describes experiments in which Human Intelligence (HI) or a human researcher (HR) communicated with Artificial Intelligence (AI/UI), specifically the chatGPT programme, in analysing the text of two interviews in the field of social gerontology. The general framework of the analysis is grounded in Glaser and Strauss's theory, involving steps that range from transcribing the interviews to coding and defining relevant concepts, leading to a tentative theory. The interaction with AI followed the comparative sequence method, which means that both intelligences, HI and UI, researcher and computer programme, alternated in each sequence of analysis. The researcher prompted responses from the programme with input stimuli, evaluated them, conveyed feedback to the UI, and used it as a basis for the next sequence. It was found that the programme is a valuable tool for qualitative analysis as it provides hints and ideas to the researcher, but the guiding and directing role of the researcher (HR) is essential, especially in formulating the final tentative theory. The feedback provided by the researcher in theory formulation contributes to the programme's learning, making it a progressively better assistant over time when used in qualitative text analysis"},{"@xml:lang":"sl","#text":"Članek opisuje poskuse komunikacije humane inteligence (HI) ali človeškega raziskovalca (HR) z umetno inteligenco (UI) , programom chatGPT, pri analizi besedila dveh intervjujev s področja socialne gerontologije. Splošni okvir analize je utemeljena teorija po Glaserju in Straussu s koraki, ki vodijo od zapisa intervjuja prek kodiranja in definiranja relevantnih pojmov do tentativne teorije. Interakcija z UI je potekala po primerjalno sekvenčnem modelu, se pravi, da sta se v vsaki sekvenci analize izmenjali obe inteligenci, UI in HI, raziskovalec in računalniški program. Raziskovalec je s svojimi vhodnimi spodbudami izzval odgovore programa, ki jih je raziskovalec ovrednotil, sporočil UI in na tej osnovi spodbudil naslednjo sekvenco. Pokazalo se je, da je program koristen pripomoček kvalitativne analize, saj posreduje raziskovalcu namige in ideje za analizo, da pa je nujna vodilna in usmerjevalna vloga raziskovalca (HR), posebej pri formulaciji končne tentativne teorije. Povratno sporočilo, ki ga s formulacijo teorije posreduje raziskovalec, pripomore k učenju programa. To pomeni, da postaja program z uporabo pri kvalitativni analizi besedil s časom vse boljši pomočnik"}],"edm:type":"TEXT","dc:type":[{"@xml:lang":"sl","#text":"znanstveno časopisje"},{"@xml:lang":"en","#text":"journals"},{"@rdf:resource":"http://www.wikidata.org/entity/Q361785"}]},"ore:Aggregation":{"@rdf:about":"http://www.dlib.si/?URN=URN:NBN:SI:doc-CWDUEH56","edm:aggregatedCHO":{"@rdf:resource":"URN:NBN:SI:doc-CWDUEH56"},"edm:isShownBy":{"@rdf:resource":"http://www.dlib.si/stream/URN:NBN:SI:doc-CWDUEH56/769e822b-79fa-4de0-a1e4-2c8e3f2242bc/PDF"},"edm:rights":{"@rdf:resource":"http://creativecommons.org/licenses/by-sa/4.0/"},"edm:provider":"Slovenian National E-content Aggregator","edm:intermediateProvider":{"@xml:lang":"en","#text":"National and University Library of Slovenia"},"edm:dataProvider":{"@xml:lang":"sl","#text":"Univerza v Ljubljani, Fakulteta za socialno delo"},"edm:object":{"@rdf:resource":"http://www.dlib.si/streamdb/URN:NBN:SI:doc-CWDUEH56/maxi/edm"},"edm:isShownAt":{"@rdf:resource":"http://www.dlib.si/details/URN:NBN:SI:doc-CWDUEH56"}}}}