Chris Ling (chris.ling@royalroads.ca) is an Associate Professor in the School of Environment and Sustainability at Royal Roads University, Victoria BC Canada.

Royal Roads University’s Master of Arts or Sciences in Environment and Management (MEM) has been designed as a transdisciplinary program. The concept of trans-disciplinarity that best applies is that of Klein (2004) and Robinson (2008) who imply trans-disciplinarity explicitly requires a coming together of practical, applied, and industry perspectives along with academic and theoretical perspectives. This makes the program a rich place for learning, but a challenging place for devising a teaching approach for research methods.

For those teaching research methods in single or multi-disciplinary contexts there is “a substantial body of literature at the disposal of teachers addressing the ‘how to’ of research methods, it does not adequately inform the teaching of methods” (Wagner et al., 2011, p. 75), and “very little [that] gives us a picture of what student learning looks like” (Earley, 2014, p. 248). More so is the lack of pedagogical guidance in a trans-disciplinary context.

Students and faculty in the MEM program come from a wide variety of backgrounds and there is little shared tradition in research methods. At one extreme are those with laboratory and statistical skills, and the other are those with highly qualitative interests and experiences. An indication of the trans-disciplinary nature of topics and methods covered and used by MEM students is derived from the list of theses published at Royal Roads University.

Table 1

Sample of MEM thesis topics and methods used

Rationale

The challenge is to design a course that helps students advance their research plans ideas whilst recognising that designing a course that will result in each student in the program developing all the skills they need is unrealistic. Based on observing students in the program over 12 years of teaching and supervising, what appear to unite most students in the program is a pragmatic worldview (Weaver, 2018), one that is focused on experience, the goals of the project at hand and a desire to undertake research than will make a real and immediate different to the personal and professional context in which it is taking place. This then leads to the primary goal of the research methods course – an embrace of intellectual diversity and pragmatism.

The aim of the two assignments described here are part of a suite of assignments that support the students in the development of a proposal, and how to identify appropriate literature and appropriate methodological direction.

These two assignments take advantage of the diversity of students and the wide range of interests and ideas.

Overview

Assignment 1

The first assignment in the course is a team-based discussion that aims to help student craft a research question. Unlike many graduate programs, a research proposal is not a condition of entry; students in the MEM program do not necessarily start the program with a solid idea of what research they may wish to pursue. The assignment is to frame and critique research questions that are concise and transferable to the research setting. The assignment is in the first unit of the course for which the learning outcomes are:

• understand the concept of the research paradigm;
• have a basic knowledge of the features of complex systems, and how these features might impact the research process;
• differentiate between multidisciplinary, interdisciplinary, and trans-disciplinary study; and
• explain why environmental research often requires a trans-disciplinary framework.

There is also a hidden aim: to introduce students to ideas beyond their disciplinary and professional context to challenge assumptions about what makes a good research topic.

The assignment is assessed on the degree to which students support the discussion and provide critical and constructive feedback to the proposed questions of others rather than the quality (or otherwise) of the research question posted, and on the degree to which students take on board that feedback in order to improve their question.

To support this, readings are provided that are both general research texts appropriate to environmental research such as Cresswell (2009) and Watts and Halliwell (1996). The students are asked to post their research question and brief explanation of the problem they hope to address; discuss the question, and those of others in their team.

Students are further advised to use the resources supplied to support the points they raise in the discussion and provide a critical framework for discussions and to complete the discussion with a revised question that addresses points raised by peers.

In order to ensure exposure to as broad a range of perspectives as possible, discussion groups comprise five or six students selected for maximum diversity. This ensures preconceived ideas and assumptions are more likely to be challenged; students with different, trans-disciplinary perspectives are present to discuss real-world problems posed; and the discussion may open individuals to possibilities they may not have considered both in terms of topic and also potential approaches.

Two common outcomes of this exercise are: those students from a quantitative background become open to mixed-methods and qualitative approach, and many students reframe their problem in response to perspectives put forward by colleagues.

The assignment is not assessed based on the quality of the final product, but on the degree to which student can give, receive and respond to critique. However, the assignment feedback provides the instructor with a confidential (non-forum-based) context with which to provide deeper feedback on the research question.

Assignment 2

Later in the course, after two individual assignments focused on literature review and research approach, the second team assignment is built around data analysis. A team approach allows individuals to focus on the type of data they may be collecting in their research.

The task is to analyse two data sets: one qualitative and one quantitative. The teams are presented with two options of each type of data, taken from research projects led by faculty related to the MEM program. The teams are presented with a research question to answer and a suggested analytical approach.

Table 2

Data sets for analysis

¹ Teams are advised to choose the best type of data set for the research they are proposing, with teams that are not proposing any quantitative study choosing the plant growth data as this is the straightforward data set.

The benefit of ensuring all teams must explore both types of data is that it exposes those from a physical science tradition to the challenges and requirements of qualitative data and vice versa. Even if those students are not planning on using those data types in their research, it increases comprehension of how conclusions are drawn, and enhances literacy about trans-disciplinary research methods we encourage our students to use.

Students frequently struggle with one or other of the data sets. This is normally aligned with experience, with those from more qualitative disciplines struggling with the statistics, and those with a quantitative background struggling with the qualitative data set. Common responses from students from quantitative backgrounds is they are surprised by the rigor and effort needed to analyse qualitative data, with those from qualitative backgrounds report a greater understanding of the limitations and power of various statistical tests. This increases the appreciation of analysis beyond the previous disciplinary boundaries to which the students had been exposed.

Reflection

These assignments form part of an overall assessment plan to lead students to a draft proposal that supports their goals for research. While some students do report dissatisfaction with the lack of explicit methods instruction, the course serves the purpose of leading students to the methods that work for them, rather than prescribing a narrow range of approaches. This serves to expand horizons and markedly increases the degree of trans-disciplinarity in thesis research. This is most marked in those from quantitative backgrounds who were skeptical of qualitative analysis prior to being exposed to it. Fewer students from qualitative backgrounds end up taking on quantitative analysis, but my assumption is this has more to do with a lack of mathematical confidence rather than a lack of appreciation of the potential. There are also some key advantages to taking a team approach that take advantage of the transdisciplinary nature of the participants:

• Broadening of horizons in possibility, assumptions, questioning and approaches.
• The building of networks – discussion often results in exchange of contacts and experience.
• Learning from peers – a key component of RRU’s Learning Teaching and Research Model (Royal Roads University, n.d).

Teaching research methods to a trans-disciplinary cohort to meet the demands of all students to prepare them fully for their research is simply not possible in a single course; but embracing the transdisciplinarity of the cohort and starting conversations across those disciplinary boundaries enrichens the students’ perspectives and strengthens their ability to devise their own approaches to the questions they wish to raise.

References

Creswell, J. (2009). Research questions and hypotheses. In Research design: Qualitative, Quantitative, and Mixed Methods Approaches (3rd ed.) (pp. 129-143). Sage.

Earley, M.A. (2014). A synthesis of the literature on research methods education. Teaching in Higher Education, 19(3), 242–253. https://doi.org/10.1080/13562517.2013.860105

Klein, J. T. (2004). Interdisciplinarity and complexity: An evolving relationship. Emergence: Complexity & Organization, 6(1/2).

Pierce, R. (2008). Analysing qualitative information: Classifying, coding and interpreting information. In Research methods in Politics (pp. 240-262). Sage. https://doi.org/10.4135/9780857024589

Robinson, J. (2008). Being undisciplined: Transgressions and intersections in academia and beyond. Futures, 40(1), 70–70.

Royal Roads University. (n.d.). Learning, Teaching and Research Model. https://www.royalroads.ca/about/learning-teaching-research-model

Thorpe, R., & Holt, R. (2008). The SAGE dictionary of qualitative management research (Vols. 1-0). Sage. https://doi.org/10.4135/9780857020109

Wagner, C., Garner, M., & Kawulich, B. (2011). The state of the art of teaching research methods in the social sciences: Towards a pedagogical culture. Studies in Higher Education, 36(1), 75–88. https://doi.org/10.1080/03075070903452594

Watts, S. & Halliwell, L. (1996). Chapter one: The good scientist. In Essential Environmental Science: Methods & Techniques (pp. 1-30). Routledge.

Weaver, K. (2018) Pragmatic paradigm, in B.B. Frey. The SAGE encyclopedia of educational research, measurement, and evaluation (Vols. 1-4). Thousand Oaks, CA: Sage. https://doi.org/10.4135/9781506326139.n534

Acknowledgements

The course described in this chapter was based on a course originally designed in by Drs. Ann Dale, Lenore Newman and Christopher Ling in 2007. It was extensively revised twice, first by Dr. Oksana Bartosh in 2009 and then again by Dr. Christopher Ling in 2015. These exercises are a product of the combined wisdom of those individuals. Thanks also to the many years of MEM students that also contributed to that development.