A multidisciplinary systematic review of the use of diagrams as a means of collecting data from research subjects: application, benefits and recommendations

BACKGROUND: In research, diagrams are most commonly used in the analysis of data and visual presentation of results. However there has been a substantial growth in the use of diagrams in earlier stages of the research process to collect data. Despite this growth, guidance on this technique is often isolated within disciplines. METHODS: A multidisciplinary systematic review was performed, which included 13 traditional healthcare and non-health-focused indexes, non-indexed searches and contacting experts in the field. English-language articles that used diagrams as a data collection tool and reflected on the process were included in the review, with no restriction on publication date. RESULTS: The search identified 2690 documents, of which 80 were included in the final analysis. The choice to use diagrams for data collection is often determined by requirements of the research topic, such as the need to understand research subjects' knowledge or cognitive structure, to overcome cultural and linguistic differences, or to understand highly complex subject matter. How diagrams were used for data collection varied by the degrees of instruction for, and freedom in, diagram creation, the number of diagrams created or edited and the use of diagrams in conjunction with other data collection methods. Depending on how data collection is structured, a variety of options for qualitative and quantitative analysis are available to the researcher. The review identified a number of benefits to using diagrams in data collection, including the ease with which the method can be adapted to complement other data collection methods and its ability to focus discussion. However it is clear that the benefits and challenges of diagramming depend on the nature of its application and the type of diagrams used. DISCUSSION/CONCLUSION: The results of this multidisciplinary systematic review examine the application of diagrams in data collection and the methods for analyzing the unique datasets elicited. Three recommendations are presented. Firstly, the diagrammatic approach should be chosen based on the type of data needed. Secondly, appropriate instructions will depend on the approach chosen. And thirdly, the final results should present examples of original or recreated diagrams. This review also highlighted the need for a standardized terminology of the method and a supporting theoretical framework

The role of nonlinear pedagogy in physical education

In physical education, the Teaching Games for Understanding (TGfU) pedagogical strategy has attracted significant attention from theoreticians and educators for allowing the development of game education through a tactic-to-skill approach involving the use of modified games. However, some have proposed that as an educational framework, it lacks adequate theoretical grounding from a motor learning perspective to empirically augment its perceived effectiveness. The authors examine the literature base providing the theoretical underpinning for TGfU and explore the potential of a nonlinear pedagogical framework, based on dynamical systems theory, as a suitable explanation for TGfU's effectiveness in physical education. Nonlinear pedagogy involves manipulating key task constraints on learners to facilitate the emergence of functional movement patterns and decision-making behaviors. The authors explain how interpreting motor learning processes from a nonlinear pedagogical framework can underpin the educational principles of TGfU and provide a theoretical rationale for guiding the implementation of learning progressions in physical education