AI Text Generators and Text Producers

Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningpeer review


AI-generated text production is becoming increasingly important in many industries, and it has already brought about dramatic changes in the ways we write texts and generate content. The article draws on empirical data from a descriptive-analytical study involving 70 test subjects. The population comprised 115 test persons, who received an e-mail with instructions. A sample of 70 test subjects participated in the study. First, the test subjects were asked to test a specific AI text generator (ATG) and conduct three prompting operations with the same linguistic content. Second, having tested the ATG, the test subjects were asked to participate in a questionnaire with ten questions focusing on how they experienced the performance of the ATG and how they worked with the ATG. The majority of the test subjects found that the tested ATG was easy to use when producing texts. When asked about the perceived quality of the AI-generated content, the respondents were not impressed with the quality and indicated that they needed to perform several editing operations. The data also indicate that ATGs need help before, during and after. This paper presents a three-phase editing framework, which can be used when using and teaching ATGs.
TitelProceedings 2022 International Conference on Advanced Learning Technologies, ICALT 2022
RedaktørerMaiga Chang, Nian-Shing Chen, Mihai Dascalu, Demetrios G. Sampson, Ahmed Tlili, Stefan Trausan-Matu
Antal sider3
UdgivelsesstedLos Alamitos, CA
ISBN (Trykt)9781665495202
ISBN (Elektronisk)9781665495196
StatusUdgivet - 2022
BegivenhedThe 22nd IEEE International Conference on Advanced Learning Technologies. ICALT 2022 - University Politehnica of Bucharest, Bucharest, Rumænien
Varighed: 1 jul. 20224 jul. 2022
Konferencens nummer: 22


KonferenceThe 22nd IEEE International Conference on Advanced Learning Technologies. ICALT 2022
LokationUniversity Politehnica of Bucharest
NavnProceedings IEEE International Conference on Advanced Learning Technologies


  • Industries
  • Sociology
  • Education
  • Focusing
  • Production
  • Linguistics
  • Generators
  • Artificial intellegence
  • Computer aided instruction
  • Teaching
  • Text analysis
  • Text producers
  • AI-generated text production
  • Test subjects
  • Test persons
  • Specific AI text generator
  • Tested ATG
  • AI-generated content
  • AI text generators
  • User interaction
  • Editing