Transcription in Computing Education Research: A Review and Recommendations

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Title: Transcription in Computing Education Research: A Review and Recommendations
Language: English
Authors: Lutz Terfloth, Vivien Lohmer, Friederike Kern, Carsten Schulte
Source: Informatics in Education. 2025 24(2):377-405.
Availability: Vilnius University Institute of Mathematics and Informatics, Lithuanian Academy of Sciences. Akademjos str. 4, Vilnius LT 08663 Lithuania. Tel: +37-5-21-09300; Fax: +37-5-27-29209; e-mail: info@mii.vu.lt; Web site: https://infedu.vu.lt/journal/INFEDU
Peer Reviewed: Y
Page Count: 29
Publication Date: 2025
Document Type: Journal Articles
Information Analyses
Descriptors: Phonetic Transcription, Computer Science Education, Educational Research, Credibility, Bias, Accountability, Standards, Trust (Psychology), Audits (Verification), Transcripts (Written Records)
ISSN: 1648-5831
2335-8971
Abstract: Transcripts play a crucial role in qualitative research in computing education, with significant implications for the credibility and reproducibility of findings. However, unreflective and inconsistent transcription standards may unintentionally introduce biases, potentially undermining the validity of research outcomes and the collective progress of the field. In this article, we introduce transcription as a theoretically guided process rather than a mere preparatory step, illustrating its role using a case example. Additionally, through a systematic review of 107 qualitative research articles in computing education, we identify widespread shortcomings in the reporting and implementation of transcription practices, revealing a need for greater intentionality and transparency. To address these challenges, we propose a three-step framework for selecting, applying, and documenting transcription standards that align with the specific context and goals of a study. Rather than advocating for overly complex, one-size-fits-all transcription strategies, we emphasize the importance of a context-appropriate approach that is clearly communicated to foster trust and reproducibility. By advancing a more robust transcription culture, this work aims to support computing education researchers in adopting standards that enhance the quality and reliability of qualitative research in the field.
Abstractor: As Provided
Entry Date: 2025
Accession Number: EJ1477409
Database: ERIC
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  Data: Transcription in Computing Education Research: A Review and Recommendations
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  Data: <searchLink fieldCode="AR" term="%22Lutz+Terfloth%22">Lutz Terfloth</searchLink><br /><searchLink fieldCode="AR" term="%22Vivien+Lohmer%22">Vivien Lohmer</searchLink><br /><searchLink fieldCode="AR" term="%22Friederike+Kern%22">Friederike Kern</searchLink><br /><searchLink fieldCode="AR" term="%22Carsten+Schulte%22">Carsten Schulte</searchLink>
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  Data: <searchLink fieldCode="SO" term="%22Informatics+in+Education%22"><i>Informatics in Education</i></searchLink>. 2025 24(2):377-405.
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  Data: Vilnius University Institute of Mathematics and Informatics, Lithuanian Academy of Sciences. Akademjos str. 4, Vilnius LT 08663 Lithuania. Tel: +37-5-21-09300; Fax: +37-5-27-29209; e-mail: info@mii.vu.lt; Web site: https://infedu.vu.lt/journal/INFEDU
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  Data: Transcripts play a crucial role in qualitative research in computing education, with significant implications for the credibility and reproducibility of findings. However, unreflective and inconsistent transcription standards may unintentionally introduce biases, potentially undermining the validity of research outcomes and the collective progress of the field. In this article, we introduce transcription as a theoretically guided process rather than a mere preparatory step, illustrating its role using a case example. Additionally, through a systematic review of 107 qualitative research articles in computing education, we identify widespread shortcomings in the reporting and implementation of transcription practices, revealing a need for greater intentionality and transparency. To address these challenges, we propose a three-step framework for selecting, applying, and documenting transcription standards that align with the specific context and goals of a study. Rather than advocating for overly complex, one-size-fits-all transcription strategies, we emphasize the importance of a context-appropriate approach that is clearly communicated to foster trust and reproducibility. By advancing a more robust transcription culture, this work aims to support computing education researchers in adopting standards that enhance the quality and reliability of qualitative research in the field.
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        StartPage: 377
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      – SubjectFull: Computer Science Education
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      – SubjectFull: Educational Research
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      – SubjectFull: Credibility
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      – SubjectFull: Bias
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      – SubjectFull: Accountability
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      – SubjectFull: Standards
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      – SubjectFull: Audits (Verification)
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      – SubjectFull: Transcripts (Written Records)
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      – TitleFull: Transcription in Computing Education Research: A Review and Recommendations
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