How Does a ‘Model of Graphics’ Approach and Peer Tutoring Lead to Deep Understanding of Data Visualisation?
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Open Access
Type
ThesisThesis type
Doctor of PhilosophyAuthor/s
Alfadda, Dalal AbdulazizAbstract
This thesis describes how students with no knowledge of descriptive statistics and no experience with data visualisation software learned to produce such visualisations. It proposes a model of graphics approach that enables students to compose a description of a graph and move ...
See moreThis thesis describes how students with no knowledge of descriptive statistics and no experience with data visualisation software learned to produce such visualisations. It proposes a model of graphics approach that enables students to compose a description of a graph and move beyond standard chart types. Two quasi-experimental studies using a one-group pretest–posttest design were conducted with 62 third-year education students from two Australian universities. Intervention involved learning from exposition through an online module, including instructional videos, worked-out examples, problem-solving, and peer feedback. Participants learned to construct two chart types using the statistical software ggplot2. Participants’ utterances and screens were recorded and subjected to detailed qualitative analysis. The results suggest that the model of graphics and peer tutoring are effective learning methods for data visualisation production. Analysis of pretest to posttest gains showed significant increases in students’ scores, and the students demonstrated knowledge transfer. Qualitative analysis showed that during construction of the model of graphics, students engaged in active and constructive learning modes in terms of the Interactive–Constructive–Active–Passive (ICAP) theory. The findings suggest that having the tutor at a higher scoring level than the tutee is most beneficial. This research contributes to data science and statistics education. It is the first study to examine novices’ initial hours of learning about a theory of statistical graphs and their first use of ggplot2. It lays the ground for the model of graphics competencies and establishes a qualitative framework for analysing students’ learning and interaction. The findings contribute to the field of peer tutoring, particularly reciprocal peer tutoring. The impact of role sequence in reciprocal tutoring has been almost absent from the literature; this study emphasises the potential impact of first role (tutor or tutee) on learning and transfer.
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See moreThis thesis describes how students with no knowledge of descriptive statistics and no experience with data visualisation software learned to produce such visualisations. It proposes a model of graphics approach that enables students to compose a description of a graph and move beyond standard chart types. Two quasi-experimental studies using a one-group pretest–posttest design were conducted with 62 third-year education students from two Australian universities. Intervention involved learning from exposition through an online module, including instructional videos, worked-out examples, problem-solving, and peer feedback. Participants learned to construct two chart types using the statistical software ggplot2. Participants’ utterances and screens were recorded and subjected to detailed qualitative analysis. The results suggest that the model of graphics and peer tutoring are effective learning methods for data visualisation production. Analysis of pretest to posttest gains showed significant increases in students’ scores, and the students demonstrated knowledge transfer. Qualitative analysis showed that during construction of the model of graphics, students engaged in active and constructive learning modes in terms of the Interactive–Constructive–Active–Passive (ICAP) theory. The findings suggest that having the tutor at a higher scoring level than the tutee is most beneficial. This research contributes to data science and statistics education. It is the first study to examine novices’ initial hours of learning about a theory of statistical graphs and their first use of ggplot2. It lays the ground for the model of graphics competencies and establishes a qualitative framework for analysing students’ learning and interaction. The findings contribute to the field of peer tutoring, particularly reciprocal peer tutoring. The impact of role sequence in reciprocal tutoring has been almost absent from the literature; this study emphasises the potential impact of first role (tutor or tutee) on learning and transfer.
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Date
2021Rights statement
The author retains copyright of this thesis. It may only be used for the purposes of research and study. It must not be used for any other purposes and may not be transmitted or shared with others without prior permission.Faculty/School
Faculty of Arts and Social Sciences, Sydney School of Education and Social WorkAwarding institution
The University of SydneyShare