DOI: 10.34894/oajpef
title: Marlies Schillings - PhD project data for study 4

description: &lt;i&gt;Title&lt;/I&gt;: Face-to-face Peer Dialogue: Students Talking about Feedback (submitted March 2021)&lt;br&gt;&lt;br&gt;
&lt;i&gt;A short description of the study set-up: &lt;/i&gt;35 second-year university students were split into 12 groups. Students wrote a scientific report and gave written peer feedback. This was followed by face-to-face peer dialogue on the feedback without teacher facilitation. Dialogues were coded and analysed at the utterance level.&lt;br&gt;&lt;br&gt;
&lt;i&gt;Analysis&lt;/i&gt;&lt;br&gt;
For data analysis, we used the coding scheme by Visschers-Pleijers et al. (2006), which focuses on the analysis of verbal interactions in tutorial groups. To assess the dialogue, the verbal interactions in the discourses were scored at the utterance level as ‘Learning-oriented interaction’, ‘Procedural interaction’ or ‘Irrelevant interaction’ (Visschers-Pleijers et al. 2006). The Learning-oriented interactions were further subdivided in five subcategories: Opening statement, Question (open, critical or verification question), Cumulative reasoning (elaboration, offering suggestion, confirmation or intention to improve), Disagreement (counter argument, doubt, disagreement or no intention to improve) and Lessons learned (an adapted version of the coding scheme used by Visschers-Pleijers et al. 2006). The first and second authors, and a research assistant coded the first four transcripts and discussed their codes in three rounds until they reached consensus. See Appendix A for a description of the coding scheme. After reaching consensus on the coding, the first author and the research assistant, individually coded four new transcripts. For these four transcripts, interrater reliability analysis was performed using percent agreement according Gisev, Bell, and Chen (2013). The percent agreement between the first author and the research assistant ranged from 80 to 92. The first author then coded the remaining eight transcripts individually. Eventually, all transcripts were analysed according to the first author’s classification.&lt;br&gt;
For each single group session, the codes for each (sub)category of verbal interaction were counted and percentages were calculated for the number of utterances. The median (Mdn) and interquartile range (IQR) of percentage of utterances for each (sub)category of code were computed per coding category for all groups together.&lt;br&gt;&lt;br&gt;
&lt;i&gt;Explanation of all the instruments used in the data collection (including phrasing of items in surveys): &lt;/i&gt;&lt;br&gt;This was a discourse analysis (see final coding scheme: separate file).&lt;br&gt;&lt;br&gt;
&lt;I&gt;Explanation of the data files: what data is stored in what file?&lt;/I&gt;&lt;BR&gt;
• Final coding scheme (in Word).&lt;BR&gt;
• Audiotapes (in MP3) and transcripts of 12 groups (in Word)&lt;BR&gt;.
• Data study 4 (in Excel).&lt;BR&gt;
• Resulting data in table (in Word).&lt;BR&gt;&lt;BR&gt;
&lt;I&gt;In case of quantitative data: meaning and ranges or codings of all columns:&lt;/I&gt;&lt;br&gt;
• Data study 4 (in Excel): numbers and percentages of interactions.&lt;BR&gt;
• Resulting data (Table in Word): per group (n=12) in percentages and medians&lt;BR&gt;&lt;BR&gt;
&lt;I&gt;In case of qualitative data: description of the structure of the data files:&lt;/I&gt;&lt;BR&gt;
Not applicable