The Qualitative Report Volume 14 Number 2 June 2009 245-260
http://www.nova.edu/ssss/QR/QR14-2/krauss.pdf
Preliminary Investigation and Interview Guide Development
for Studying how Malaysian Farmers’ Form their Mental
Models of Farming
Steven Eric Krauss, Azimi Hamzah, Zoharah Omar, Turiman Suandi,
Ismi Arif Ismail and Mohd Zaidan Zahari
Universiti Putra Malaysia, Malaysia
Zanariah Mohd Nor
Universiti Darul Iman, Malaysia
The development of the interview guide is an integral aspect of the process
of conducting qualitative research, yet one that receives little attention in
the qualitative research literature. It is often assumed that interview
guides are merely a list of questions used to guide a qualitative interview.
The background analysis and preparation necessary to prepare an
appropriate and effective guide cannot be dismissed, however, as they are
integral aspects of the interview process. The current study on mental
models of Malaysian smallholder farmers employed in-depth interviews as
its primary approach to data generation. This paper details the initial
processes undertaken to develop the interview guide based on preliminary
data generation. The results included seven main steps to interview guide
development. Key Words: Malaysian Farmers, Interview Guide, and
Mental Model
Introduction
The development of the interview guide is an integral aspect of the process of
conducting qualitative research, yet one that receives little attention in the literature. It is
often stated that in qualitative research, the researcher him or herself is the research
instrument (Pyett, 2003; Fink, 2000), as it is through the researcher that qualitative data is
generated or collected, analyzed and interpreted. One important aspect of the data
collection process is the research interview; specifically the questions that the researcher
uses to probe and generate data with his or her respondents. This process is typically
guided by an interview guide or guide, which helps the researcher…
…direct the conversation toward the topics and issues you want to learn
about. Interview guides vary from highly scripted to relatively loose, but
they all share certain features: They help you know what to ask about, in
what sequence, how to pose your questions, and how to pose follow-ups.
They provide guidance about what to do or say next, after your
interviewee has answered the last question. (Kennedy, 2006, para. 1)
Steven Eric Krauss, Azimi Hamzah, Zanariah Mohd Nor, Zoharah Omar, Turiman Suandi, Ismi Arif
Ismai, and Mohd Zaidan Zahari 246
Though there is much information available for students and researchers in
qualitative research on the concept of the interview guide (Creswell, 2007; Merriam,
1998; Bogdan & Biklen, 1992; Patton, 1990), few have attempted to outline the process
undertaken to arrive at one, particularly in the context of larger, team-based qualitative
research studies. This is of concern because the interview guide is an integral tool in the
process of collecting data in qualitative research. Though the researcher is the instrument
in the research process and may stray from the guide in the midst of interviewing, the
guide is a valuable aid that provides the researcher with needed consistency, and a
pathway for using questions that can generate data. The interview guide likewise
provides the invaluable link between the research problem, research questions, past
relevant literature and the sought after data that can fill the gap identified by the
researcher.
The current paper aims to outline the interview guide development process, based
on the authors’ experiences in the context of a team-based qualitative study on the
development of Malaysian farmers’ mental models and how they influence farm
profitability and viability. Through our experiences, we outline the process and discuss in
detail our rationale for using the selected approaches along with examples from the
research itself. The paper aims to assist qualitative research students as well as other
researchers by illustrating in detail one approach for developing a useful and relevant
interview guide.
Background of the Study: Malaysian Farmers’ Mental Models
The recent revival of agriculture in Malaysia has seen the rebirth of a few megabusinesses
that implement and maximize profits by utilizing new technologies and
innovations. While this transformation is seen by many as the way ahead for the
agriculture sector in Malaysia, it is set against the backdrop of a large number of poorer
small-scale farms. As Malaysia’s agriculture sector continues to develop in line with the
nation as a whole, it is of concern to policy makers and agricultural educators to ensure
that small-scale farms and farmers are not left behind in the push for development.
Years of our own personal experiences in the field of extension education indicate
that getting a Malaysian farmer to adopt new technology and innovation can be daunting,
as the majority of farmers continue to farm using traditional methods. Among the few
highly successful small farmers, individual ingenuity appears to be the key to success, or
at least an important factor in their level of proficiency, profitability and sustainability
(Zanariah, Azimi, Turiman, & Krauss, 2008). Ingenuity enables farmers to see
possibilities, take advantage of market niches, and anticipate and solve problems. How
they put their vision into action is indicative of their mental model of farming.
Mental models have been defined by Seel (2001) as “inventions of the mind that
represent, organize and restructure domain-specific knowledge” (p. 408). According to
Holyoak (1984), a mental model is a psychological representation of the environment and
its expected behavior. Previous researchers (e.g., Eckert, 2003; Raedeke & Rikoon, 1997)
have identified the important role that mental models of farming play in farmers’
learning, decision-making, and adapting to change. For many farmers, success requires
overcoming assumptions embedded in mental models of farming that keep them tied to
their current practices and prevent them from seeing possibilities for success (Berton,
247 The Qualitative Report June 2009
2001; Eckert, 2003). For the current study, we defined mental model as a model
explaining the thought processes that incorporate one’s beliefs, values, experiences,
knowledge and subject-in-question-based perceptions that lead to decision-making.
Agriculture educators often direct programs and resources to support farmers in
adjusting their practices to improve the viability or profitability of their operations.
Because learning experiences appear to shape farmers’ mental models of farming and
mental models serve as guides for decisions and actions (Eckert & Bell, 2005),
understanding how farmers develop mental models can help educators design learning
programs and services that are better positioned to enable farmers to succeed.
The Interview Guide Development Process
In qualitative research, developing the interview guide is often referred to as a
fairly straightforward process. Merriam (1998) refers to it as a list of questions that the
researcher intends to ask in an interview. According to McCracken (1988), first, it
…ensures that the investigator covers all the terrain in the same order for
each respondent. The second function is the care and scheduling of the
prompts necessary to manufacture distance. The third function is that it
establishes channels for the direction and scope of discourse. (p. 24)
According to Reysoo and Heldens (2007), the steps for guide development
include: selecting the topic; defining all the aspects of the topic; formulating initial (openended)
questions; determining the kind of questions; determining the logical order of the
topics/questions; preparing the introduction and the end; and preparing the interviewtechnical
indications. Strauss and Corbin (1990) emphasize that the interview guide can
be revised on an ongoing basis to elicit more focused responses from participants and to
accommodate themes that emerge in the early stages of data analysis (Eckert & Bell,
2006).
In the current study, the research team felt that it was important to develop a
universal, semi-structured interview guide that all researchers in the team could use. As
the research team comprised seven researchers in all, there was a felt need to ensure some
level of consistency in the approach taken to generate data. In such a large-scale study
that makes use of multiple researchers and sites, the interview guide becomes more
important for consistency in data analysis (Bogden & Biklen, 1992).
Without a well-structured interview guide to direct the interviews with farmers,
difficulties would undoubtedly arrive at the time of data analysis. Often, as is mentioned
by Creswell (2007), the semi-structured interview guide need not be more than five or six
general questions. However, in the case of team-based, multi-site research, there may be
a need for more detail in the guide that includes cues for probing, to ensure some level of
consistency among the different interviewers. Typically, in an in-depth interview it is
nearly impossible to determine exactly how the respondent is going to answer, which
makes probing a unique adventure with each interview. However, through the process of
preliminary interviewing, indicators for probing can be identified. This tension between
allowing for each interview to be unique and maintaining “open-endedness,” while at the
same time keeping the interview “on track” in terms of the research questions is one of
Steven Eric Krauss, Azimi Hamzah, Zanariah Mohd Nor, Zoharah Omar, Turiman Suandi, Ismi Arif
Ismai, and Mohd Zaidan Zahari 248
the challenges of doing team-based qualitative research where multiple researchers are
involved in data collection.
The Challenges Posed by Mental Model Research
What makes developing an interview guide for interviews on mental model
development so challenging is the nature of mental model research itself. Mental models,
as stated, are attempts to understand the decision-making processes of subjects. The
current study, however, focuses not only on identifying the mental models per se, but to
delineate the factors and processes that contribute to their development. Along these
lines, Eckert and Bell (2005) write:
A mental model for a particular domain includes related values and
beliefs. It includes conceptions of knowledge and skills, and how to use
them. Mental models create perspectives and points of view; they serve as
both a filter and a guide for information, learning experiences, and
problem solving. Often, mental models overlap. (para. 4)
The challenge of qualitative research on mental models thus lies in understanding
and ascertaining the relevant values and beliefs, and the processes that such factors play
on an individual’s decision-making. In relation to farming, in Eckert and Bell’s (2005)
similar study conducted with farmers in the U.S., the authors found that the farmers’
mental model of farming and their mental model of family had many components in
common, and it was difficult to delineate between the two. Mental model research thus
has unique challenges that stem from understanding how basic values and beliefs
contribute to decision-making and behavior, and developing conceptual frameworks
capable of describing, explaining and predicting future actions (Klimoski & Mohammed,
1994). Furthermore, the nature of the mental model concept also makes decisions about
how to identify important mental processes of which the respondents themselves may not
be conscious difficult. Thus, choices about questions and probes that the researcher
should employ become imperative.
Questions during the interview process, therefore, must be chosen and posed in a
judicious manner. One cannot merely rely on a question such as “what are your beliefs
about farming?”. The researcher must, through his or her deep understanding of the topic,
be able to pose questions that will allow both the researcher and the respondent to explore
the topic together. This process is unique to qualitative research and is often referred to as
data generation or in some cases even “making data” (Morse & Richards, 2002). The data
is thus generated through the synthesis of the researcher’s questioning and the
respondent’s answering, which result in a type of verbal reflection where the respondent
discovers new aspects to him or herself. It is a shared process in which both the
researcher and the respondent must be active participants.
This process is particularly tricky for the researcher, who must guide the process
and know what to look for in relation to the research question, for the data may not be
explicit. The respondent will most certainly not talk directly about mental models or even
values and beliefs per se, yet the researcher must know how and when he or she is
obtaining data relevant to these topics. A team-based approach makes the process more
249 The Qualitative Report June 2009
complex as well, although having multiple perspectives about data interpretation can add
depth and richness to the findings of the study.
Background of the Research Team
Our involvement in this mental model study is due partly out of our collective
interest in qualitative research and extension education, and partly out of our sense of
responsibility to the country where we work. We are all lecturers in human resource
development, extension education, adult education and/or continuing education as all of
these fields of study fall under our academic department. Our involvement in the topic at
hand also stems from our shared interest in the renewed importance of agriculture in
Malaysia, that grew as a response to global inflation and the ensuing food shortage that
has been expressly felt in the developing and under-developed worlds. As one such
resource-rich developing nation, Malaysia relies heavily on agriculture for its food
security but has, in recent years, neglected the sector’s development due to the popularity
and wealth of ICT and technology-based emerging markets. With the Malaysian
government’s recent push to re-invest in agriculture, agricultural extension has been
called upon to reinvigorate the small-holder farming sector and help farmers progress and
become larger contributors to the nation’s agricultural wealth. With this backdrop,
researchers and educators in extension education are being mobilized to help identify the
needs of the farming sector and develop programs to aid their development.
The older members of the project team started out in extension education at a time
when extension education in Malaysia was deemed integral to the development of the
nation’s agricultural sector. However, with the growth in the country’s stake in
technology-based manufacturing, extension education became downgraded and drew less
support from the government, thus reducing the attention paid to it in the form of research
and teaching in the public universities. For the older team members, their expertise in
extension gradually shifted over to human resource development and continuing
education, even though they never lost their passion and interest for extension.
The younger members of the team are less well-versed in extension and are more
specialized towards human resource development and its related fields. Nevertheless, the
Malaysian Government’s attempt to resuscitate extension education has breathed new life
into extension-related research, which has given the younger researchers on the team an
impetus for delving into extension. The current project echoes the new buzz found within
the entire agricultural sector best captured by the Ministry of Agriculture’s new tagline:
“Agriculture as Business”. This new push for agriculture and extension as an engine for
the nation’s development is encouraging much research in a field that was just 10 years
ago labeled a ‘sunset industry’ by the government.
As a Malaysian government-sponsored research initiative under the Ministry of
Science and Technology, the current study was designed to acquire a fundamental
understanding of how Malaysian farmers make decisions about their farming practices.
As qualitative researchers, we saw the opportunity to conduct a large-scale project on
mental models as a great but exciting challenge that would expand our knowledge not
only of Malaysia’s smallholder farmers and their valuable work, but also of qualitative
research methods. We feel it is important to note, however, that there was at the outset a
certain level of apprehension about the project due to our limited background in mental
Steven Eric Krauss, Azimi Hamzah, Zanariah Mohd Nor, Zoharah Omar, Turiman Suandi, Ismi Arif
Ismai, and Mohd Zaidan Zahari 250
modeling from the perspective of cognitive psychology, which is where the concept has
its roots. Our lack of exposure, conceptually, to mental modeling has challenged us to
fully grasp its meaning and multiple applications. At the same time, however, our
apprehension has been matched by the excitement of attempting to expand the horizons
of qualitative research in this area, at least within the Malaysian context.
In Malaysia, the collective “mentality” of certain groups is often cited as an
impediment to further development, especially among occupations like farming. It is
commonly believed in Malaysian society that the only thing that holds Malaysia back
from achieving greater success as a nation is the mentality of certain sectors of the
population, who are perceived as not valuing the opportunities for development that they
have been afforded and do not strive to progress. In some ways, therefore, the current
study also aims to address commonly held beliefs such as this through formal research.
The research team felt that qualitative research using a mental model framework would
be the most appropriate place to begin to understand this phenomenon from a more
scientific perspective.
Results: Steps for Interview Guide Development
To begin understanding Malaysian farmers’ mental models, preliminary data
collection was conducted in Terengganu State, located in the northeast part of peninsular
Malaysia. Terengganu is one of the poorer states in the country that relies on agriculture
and fishing as two of its main industries. The state is comprised mainly of ethnic Malays,
alongside small minority populations of ethnic Chinese and Indians. The state currently
receives the highest amount of federal funds in support of agricultural activities.
Preliminary data collection included seven in-depth interviews with farmers in
addition to a focus group with district Agricultural Officers and Assistant Officers who
work closely with the farmers. Overall, the researchers identified six general steps in their
process of developing the interview guide for the study.
Review of Literature on Farmers’ Mental Models
Based on the study purpose as outlined above, we began by delving into the
research literature on mental models, focusing particularly on studies dealing with
farmers and mental modeling related to farming practices. Though there is a growing
body of literature on mental models, those related to farming in particular are scant. Of
those located qualitative studies on farmers’ mental models, none provided specific
insight into the development of the interview guide. This posed a problem for the
research team, for mental models relate to beliefs, values, goals and the underlying
processes that influence decision-making. The few studies located that did relate to
farmer’s mental models were based in the U.S., yet did contribute to the theoretical
background for developing the interview guide for the current study.
Analysis of the Setting Through Focus Groups
Prior to the start of the project, the research team sought permission to engage
agricultural officers, extension agents and farmers in data generation from the Terrenganu
251 The Qualitative Report June 2009
State Department of Agriculture Director. Following the Director’s approval, a focus
group with Agricultural Officers and Assistant Officers was convened for the purpose of
furthering our understanding of the farmers, their farming practices as well as key
variables related to mental model such as farmers’ worldview and core values. First, for
the sake of the questions, we convened 25 officers and assistants officers and asked them
to identify one successful, one moderately successful and one “laggard” farmer with
whom they work. Questions were then posed to them including descriptives – location,
age, commodity or crop that they grow, level of family involvement in farming, and
others. These were followed by focus group questions pertaining to: farmers’ worldview
(i.e. perceptions on the role of education, the agricultural industry, agro-entrepreneurship,
future plans); perceptions of farming; attitude toward farming; critical incidents in their
work with the farmers identified in relation to successful/unsuccessful transformation of
the farmer’s farming practices and outcomes; and SWOT
(strengths/weaknesses/opportunities/threats) analysis, asking the officers’ how the
farmers use their strengths to grasp opportunities to improve and unleash their potential
strengths while overcoming their perceived threats. From the results with the Officers,
tables were generated to obtain a profile (descriptives) of the identified farmers according
to the three levels, along with additional tables listing responses to questions related to
their values and worldviews. Another table was generated including Officer responses to
questions related to the SWOT analysis.
This exercise provided the research team with important background information
of the Agricultural Officers’ perceptions of the farmers with whom they work. It was an
important step in helping the team understand their would-be respondents, and also
helped to develop rapport with the Officers, who are responsible for working with the
farmers in their development and continuing education. Any formal recommendations
that result from the research will be passed on to them for implementation, and as such,
they were highly vested in the research from the outset.
Develop Preliminary Conceptual Framework
From the literature (Eckert & Bell, 2005, 2006; Klimoski & Mohammed, 1994)
and data obtained from the Officers, the research team then convened to develop a
preliminary conceptual framework for the study (see Figure 1). The role of the conceptual
framework in qualitative research differs from that of quantitative research, in that it is
expected that the conceptual framework will evolve as the study goes along. New data
and findings will contribute to the ongoing conceptualization of the study, thus creating
new insights in relation to the study topic. Conceptual frameworks, like other aspects of
the study, evolve during the course of the study. However, they are an important tool for
synthesizing preliminary data and the existing literature, which help to guide the research
process.
In the current study, using literature relating to mental models along with the
preliminary data with Agricultural Officers, an initial conceptual framework was
developed on farmers’ mental models. The main theoretical categories to explore in
understanding how farmers develop their mental models were identified as follows:
Steven Eric Krauss, Azimi Hamzah, Zanariah Mohd Nor, Zoharah Omar, Turiman Suandi, Ismi Arif
Ismai, and Mohd Zaidan Zahari 252
Figure 1: Preliminary conceptual framework of the study.
Farming Practices
Adopt/reject innovation
Problem solving
Seeking for information
Learning
Risk taking
Agro-entrepreneurship
Economic threshold
Agricultural technology
Crop/animal husbandry
Marketing
Farm-market-channel link
DECISION-MAKING
MENTAL
MODEL
Concepts
Values
Beliefs
Prior Knowledge
Experience
GoalsThinking
Patterns
253 The Qualitative Report June 2009
In the initial conceptual framework, the research team identified prior knowledge and
experiences as influences on farmers’ beliefs, values, goals, expectations, concepts and
thinking patterns. These and other concepts related to farming form the basis for mental
model development. These fundamental concepts guide farmers in their decision-making,
problem solving, adoption of innovation and the like (Eckert & Bell, 2005). Such
processes then lead to good agricultural and business practices, which result in farm
productivity and viability.
Eckert and Bell (2005) mention the importance of farmers’ reliance on their
assumptions about farming, based on beliefs and knowledge, as important factors
influencing mental model development. Accordingly, mental model development as well
as its transformation can occur in many ways and often results from an event that
"typically exposes a discrepancy between what a person has always assumed to be true
and what has just been experienced, heard, or read" (Cranton, 2002, p. 66). With this in
mind, it was the aim of the research team to look at multiple factors to uncover how
mental models are developed among Malaysian farmers. The next step was to develop the
preliminary interview guide based on the framework.
Develop Preliminary Interview Guide Based on Conceptual Framework, Literature
and Preliminary Data
From the initial conceptual framework, literature and focus group data with
Agricultural Officers, a preliminary interview guide was developed. In generating the
interview guide, the level of structure had to be determined, based upon the ultimate
goals of the research. Topics and interview questions then had to be selected accordingly
(Nassar-McMillan & Borders, 2002).To put together the initial guide, the team members
were each given a category from the conceptual framework (and related concepts) and
were requested to come up with five questions each. From the foundational concepts of
beliefs, values, goals, knowledge, past experiences, concepts and thinking patterns, the
team developed an initial list of approximately 30 questions. Following the initial
brainstorm, the questions were reviewed one-by-one and scrutinized by the other team
members for language, relevance and probing potential. The questions were also
regrouped to ensure that each of the main topics was adequately covered. This process of
scrutinizing by the team members was conducted to help establish trustworthiness of the
interview guide (Johnson, 1997) by acting as a form of triangulation through
corroboration by multiple investigators (Pulkinnen, 2003). This process resulted in a
preliminary interview guide of 19 questions, which was then to be tested with the first
group of farmers.
Test Preliminary Guide with Farmers
Following the development of the preliminary interview guide, interviews were
conducted with seven farmers. Interviews were arranged through the Agricultural
Officers (AO’s) in two local districts in Terengganu State. Interviews were conducted at
the District Agricultural Offices as well as, in a few cases, on site at the farms. Farmers
were selected by the AO’s and comprised of a mix of “successful,” “moderately
successful” and “laggard” farmers as determined by the AO’s. In most cases, the
Steven Eric Krauss, Azimi Hamzah, Zanariah Mohd Nor, Zoharah Omar, Turiman Suandi, Ismi Arif
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interviews were conducted one-on-one, or in two of the cases, two researchers
interviewed one farmer. In one case two farmers were interviewed simultaneously by one
researcher.
The interviews were all recorded using digital IC recorders. Data was
transcribed into Microsoft Word and then transferred into NVIVO 8 qualitative data
management software. NVIVO 8 was used to analyze the data from the seven interviews.
The seven preliminary interviews ranged in time between approximately 40 minutes to
one and a half hours. The research team was advised to include all questions from the
interview guide and make notes during the interview on issues related to question
relevance and effectiveness. Researchers were also advised to identify important areas
and prompts for further probing.
Reflect on Preliminary Data Collection and Revisit Literature
The first step following the preliminary interviews was to reflect on the
experience as it related to the interview guide questions. Even prior to coding the data,
the research team felt it would be best to discuss their experiences to help strategize for
revision of the interview guide. Reflection is a major element to qualitative research due
to the fact that the researchers themselves are the instrument of data collection and
analysis. This trust demands that the researcher continuously goes back and forth
between the experience in the research setting, the data and oneself, in an attempt to
understand what is really happening, and to determine what role the researcher is playing
to facilitate the data generation process. Additionally, qualitative research method
requires that researchers continuously consult the relevant research literature to compare
one’s current study findings with what has been done by others, and to help make sense
of findings. The literature can help the researcher frame his or her findings within the
existing body of knowledge and also identify new findings that extend contemporary
theory.
From the team’s discussion and reflection following preliminary data collection, it
was determined that the two biggest challenges were probing, followed by identifying
what aspect of the farmers’ experiences to focus on to actually ascertain their mental
model, (i.e., to arrive at consensus on the scope of the study). As mentioned previously,
mental model research is conceptually challenging and can be broad in scope unless
specific parameters are in place. As the current study was the researchers’ first experience
with mental model research, there were many uncertainties early on in the process. Team
members, therefore, expressed the need for more clarity on how to get at the heart of the
farmers’ mental model. It was thus agreed on by the team that the questions on the
preliminary guide were effective to a degree, but that probing and scope were major
concerns that needed to be addressed. The team, therefore, agreed to proceed with the
analysis of the preliminary interview data and use it to pinpoint areas for probing.
Analyze Preliminary Data and Revise Initial Interview Guide, Including Identifying
Areas and Strategies for Further Probing
Data analysis for the purpose of solidifying the study scope and interview guide
took place over several weeks as the first seven interviews had to be transcribed, resulting
255 The Qualitative Report June 2009
in many pages of data. The first round of data analysis employed an open coding
approach, where all the relevant data is coded so as to find as many textual units as
possible that are thought to be relevant to the study research questions (Giske & Artinian,
2007). Open coding resulted in an initial list of 23 codes. This list and the initially coded
data were then discussed upon which the team members decided to undertake a more
thorough analysis of the data and expand the breadth of coding. The original 23 codes
were thus placed under each of the three research questions for the study, and the data
was re-examined by the team members for additional codes. The result was an expanded
list of nearly 50 codes.
From here, the team was able to identify areas for further probing and guide
revision. It was decided that based on the initial round of data collection, a critical
incident approach was needed for follow-up interviews in order to “go deep” with the
farmers on how and why they make the decisions they do in terms of their agricultural
practices. A key consideration in this was the need to elicit the unconscious beliefs of the
farmers that influence their decision-making in farming, therefore tapping into their tacit
knowledge. This was realized from the initial set of interviews when the researchers
recognized that several of the farmers, when asked directly about their beliefs and values
in relation to farming had difficulty articulating their responses; that perhaps they were –
on a conscious level – unaware of these guiding beliefs and values. It was then decided
that to access this type of data a different approach was needed that would be based on
their actual experiences, rather than abstract concepts.
To arrive at the unconscious beliefs that the team believed was integral to
understanding the mental model of the farmers, a critical incident approach (Flanagan,
1954) was chosen as the basis for the interview framework. Critical incident approach is
“an epistemological process in which qualitative, descriptive data are provided about
real-life accounts” (Stitt-Gohdes, Lambrecht, & Redmann, 2000, para. 8). The approach
was employed by Eckert and Bell (2006) in their own study of farmers’ mental models in
the U.S. In their study, Eckert and Bell refer to the critical incident technique in the form
of key “activating events” that the farmers in their study experienced. These activating
events were “…occurrences that caused the mental model to become explicit and open to
reflection, refinement, and sometimes transformation” (Eckert & Bell, 2006, para. 15). It
was through their probing of these activating events that the mental model and how it
actually impacted their farming decisions and practices were identified. Activating events
help researchers to understand many important elements of mental models beginning
with assumptions, beliefs and values and how such concepts evolve as a result of real-life
experiences.
Using a critical incident approach in the current study, we decided to probe the
farmers’ practice-based decisions by asking them to recall two incidents: their most
“successful” farming season (self-described); and their most unsuccessful farming season
(self-described), and to recall the major steps/decisions taken along the way in relation to
farming practices. During their recollection, we would probe each major decision made,
scanning for important reactions, ideas, emotions and anything else that might explain
why they decided and did what they did. As an activating event, we believed something
like a successful/unsuccessful harvest would be much easier for the farmers to talk about
rather than asking them questions related to their beliefs, values, assumptions, goals and
the like that might be too abstract for them to elaborate. From this approach, we hoped
Steven Eric Krauss, Azimi Hamzah, Zanariah Mohd Nor, Zoharah Omar, Turiman Suandi, Ismi Arif
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that more natural opportunities for probing on different aspects of the conceptual
framework would result.
According to Norman, Redfern, Tomalin, and Oliver (1992), there are three
assumptions commonly associated with CIT that make the technique applicable: critical
incident refers to a clearly demarcated scene; if a detailed account of what actually
happened cannot be obtained, that incident is not valid; and the critical incident itself is
the basic unit of analysis. One fear we had in employing the approach was not knowing
whether the assumptions could be met, particularly as to whether the farmers could recall
their decisions and behaviors in such detail. Furthermore, there was the possibility that
the farmers’ experiences with successful and unsuccessful seasons could be difficult for
them to elaborate on, thus reducing the level of detail provided and likewise the
opportunities to probe. Nevertheless, we hoped that subsequent interviews with the
farmers would be more focused toward understanding the key factors and processes
involved in the decision-making of farmers, and thus, begin to unveil their mental models
of farming.
Conclusion
The seven-step process of guide development can be summarized as follows:
review of literature, setting analysis through focus groups, conceptual framework
development, preliminary interview guide development, preliminary data collection,
reflection on preliminary data collection and revisit of the literature, and analyze
preliminary data and revise initial interview guide, followed by identifying areas and
strategies for further probing. All or at least some of the steps will be revisited again
following subsequent rounds of interviews with the farmers, in line with the dynamic and
cyclical nature of qualitative data collection and analysis.
Understanding how to ascertain farmers’ mental models has important
implications for stakeholders, including extension education agents, policy makers,
researchers and others. Knowing how farmers think and make decisions and what
influences their farming practices can help educators, specifically, optimize the transfer
of technology with farmers, and tailor other educational interventions in an appropriate
manner. Progression to higher success levels in farming often requires the ability to
overcome incorrect assumptions, limited thinking, fear of the unknown and other barriers.
Understanding mental models helps to identify where such factors play a role in farmers’
decision making, and how educational interventions can be maximized to open up the
doors of proficiency, productivity and other areas of successful agricultural practice
(Eckert & Bell, 2006).
Finally, it is important to note that the qualitative research process is non-linear
and entails constant reflection and reframing of the study, including the revision of
interview guides and even research questions. In relation to the current study, therefore,
further additions, edits and new insights in relation to guide development will certainly
arise as the study progresses. This paper is but an encapsulation of the initial stages of the
process.
257 The Qualitative Report June 2009
References
Berton, V. (Ed.). (2001). The new American farmer: Profiles of agricultural innovation.
Washington, DC: U.S. Department of Agriculture/Sustainable Agriculture
Research and Education.
Bogden, R. C. & Biklen, S. K. (1992). Qualitative research for education: An
introduction to theory and methods. Needham Heights, MA: Allyn and Bacon.
Cranton, P. (2002). Teaching for transformation. In S. Imel, (Series Ed.) & J. M. RossGordon,
(Vol. Ed.), Contemporary viewpoints on teaching adults effectively: No.
93. New directions for adult and continuing education (pp. 63-72). San Francisco:
Jossey-Bass.
Creswell, J. W. (2007). Qualitative inquiry and research design. Thousand Oaks: Sage.
Eckert, E. (2003). Proficiency-development spirals: Occupational learning among
farmers. Unpublished doctoral dissertation, University of Connecticut.
Eckert, E., & Bell, A. (2005). Invisible force: Farmers' mental models and how they
influence learning and actions. Journal of Extension, 43(3). Retrieved from:
<http://www.joe.org/joe/2005june/a2.shtml>
Eckert, E., & Bell, A. (2006). Continuity and change: Themes of mental model
development among small-scale farmers. Journal of Extension, 44(1). Retrieved
from: http://www.joe.org/joe/2006february/a2.php
Fink, A. S. (2000). The role of the researcher in the qualitative research process: A
potential barrier to archiving qualitative data. Forum: Qualitative Social
Research, 1(3). Retrieved from: <http://www.qualitative-
research.net/index.php/fqs/article/view/1021/2201>
Flanagan, J. C. (1954). The critical incident technique. Psychological Bulletin, 51(4),
327-359.
Giske, T., & Artinian, B. (2007). A personal experience of working with classical
grounded theory: From beginner to experienced grounded theorist. International
Journal of Qualitative Methods, 6(4), 67-80.
Holyoak, K. J. (1984). Mental models in problem solving. In J. R. Anderson & S. M.
Kosslyn (Eds.), Tutorials in learning and memory: Essays in honor of Gordon
Bower, (pp. 193-218). San Francisco: W. H. Freeman.
Johnson, B. R. (1997). Examining the validity structure of qualitative research.
education, 118(3), 282-292.
Kennedy, M. (2006). A guide to interview guides. MSU Doctoral Program in Teacher
Education Website. Retrieved from: <http://ed-
web3.educ.msu.edu/digitaladvisor/Research/interviewing.htm>
Klimoski, R., & Mohammed, S. (1994). Team mental model: Construct or metaphor?
Journal of Management. 20, 403-437
McCracken, G. (1998). The long interview. Newbury Park, CA: Sage.
Merriam, S. B. (1998). Qualitative research and case study applications in education.
San Francisco, CA: Jossey-Bass.
Morse, J. M., & Richards, L. (2002). Readme first for a user’s guide to qualitative
methods. Thousand Oaks, CA: Sage.
Steven Eric Krauss, Azimi Hamzah, Zanariah Mohd Nor, Zoharah Omar, Turiman Suandi, Ismi Arif
Ismai, and Mohd Zaidan Zahari 258
Nassar-McMillan, S. C., & Borders, L. D. (2002). Use of focus groups in survey item
development. The Qualitative Report, 7(1). Retrieved from:
http://www.nova.edu/ssss/QR/QR7-1/nassar.html.
Norman, I. J., Redfern, S. J., Tomalin, D. A., & Oliver, S. (1992). Developing Flanagan's
critical incident technique to elicit indicators of high and low quality nursing care
from patients and their nurses. Journal of Advanced Nursing, 17, 590-600.
Patton, M. Q. (Eds.). (1990). Qualitative evaluation and research methods. Newbury
Park, CA: Sage.
Pulkinnen, J. (2003). The paradigms of e-education: An analysis of the communication
structures in the research on information and communication technology
integration in education in the years 2000–2001. Ph.D. Thesis. University of
Oulu. Retrieved from:
http://herkules.oulu.fi/isbn9514272463/index.html?lang=en.
Pyett, P. M. (2003). Validation of qualitative research in the “real world.” Qualitative
Health Research, 13(8), 1170-1179.
Reysoo, F., & Heldens, J. (2007). Qualitative interview. Retrieved from:
http://www.sanpad.org.za/portal/docs/rci/Qualitative%20Interview-
%20Dr%20Fenneke%20Reysoo%20&%20Dr%20Jeanette%20Heldens.ppt.
Raedeke, A. H., & Rikoon, J. S. (1997). Temporal and spatial dimensions of knowledge:
Implications for sustainable agriculture. Agriculture and Human Values, 14, 145-
158.
Seel, N. M. (2001). Epistemology, situated cognition, and mental models: Like a bridge
over troubled water. Instructional Science, 29, 403-427.
Stitt-Gohdes, W. L., Lambrecht, J. J., & Redmann, D. H. (2000). The critical-incident
technique in job behavior research. Journal of Vocational Education Research,
25(1). Retrieved from: http://scholar.lib.vt.edu/ejournals/JVER/v25n1/stitt.html.
Strauss, A., & Corbin, J. (1990). Basics of qualitative research: Grounded theory
procedures and techniques. Newbury Park, CA: Sage.
Zanariah, M. N., Azimi, H., Turima, S., & Krauss, S. E. (2008, June). Enhancing a
farmer’s progressiveness in agro-entrepreneurship. Paper presented at
AGREX08: Agricultural Sustainability through Participative Global Extension
International Conference, Bangi-Putrajaya, Malaysia.
Appendix
Interview Guide for In-Depth Interviews with Smallholder Farmers
Ice-breaking questions: (be prepared to probe)
1. What do you understand by “agriculture as business”?
2. Since when have you been involved in agriculture?
3. What type of crop do you grow?
4. Of all the potential crops to grow, why do you focus on rice?
5. Who assists you in your farming practices?
259 The Qualitative Report June 2009
Critical incident questions:
6. In rice farming, what are the major steps that you take from start to finish?
(Researcher needs to do homework prior to interview to know the steps – to
be able to probe)
7. Start with critical incident) Can you think of a past season/year when you had
a successful outcome or crop that you were truly satisfied with? Probe – why
were you successful that season, how much more successful were you that
season as compared to others? What was the difference?
8. In reference to your satisfaction with that particular season, I would like to get
more detailed information in relation to each of the steps that you took (as in
question 6).
a. Referring to question 6, E.g. choice of seed, etc. (Probe on each step taken).
9. (Start with critical incident) Can you think of a past season/year when you had
an outcome or crop that you were not satisfied with? Probe – why were you
not successful that season, how much less successful were you that season as
compared to others? What was the difference?
10. In reference to your being unsatisfied with that season’s outcome, I would like
to get more detailed information in relation to each of the steps you took.
a. Referring to question 6, E.g. choice of seed, etc. (Probe on each step taken).
11. (Future): So I can see that there are clear differences in the thinking and
approaches you used in obtaining high and low results; as such, from what
you have just told me and from what you have learned from the experiences,
what will be the basis for your decision-making in the future so that you can
advance further in your padi activities?
12. Final question, what do you think are the similarities in farming approach and
practice between Malay and non-Malay farmers, or the similarities/differences
among farmers from the three main ethnic groups in Malaysia (i.e. Malay,
Indian and Chinese)?
Author Note
Steven Eric Krauss is a Lecturer in the Department of Professional Development
and Continuing Education, Universiti Putra Malaysia (UPM). He received his B.A. from
the University of Delaware (U.S.), his M.S. from Columbia University (U.S.) and his
PhD from the Institute for Community & Peace Studies (PEKKA), Universiti Putra
Malaysia in 2005 in the field of Youth Studies. His research and teaching interests
include youth development, human resource development, Islamic religiosity/spirituality
and social work. He has authored and co-authored several articles in local and
international journals.
Azimi Hamzah is a Professor in Extension Education specializing in youth
development at Universiti Putra Malaysia. He is currently the Director of the Institute of
Extension, Entrepreneurship and Professional Development; Head, Youth Development
Studies Unit; and the National Coordinator for the Commonwealth Youth Diploma
program. He has been heading the Youth Development Centre for Excellence since its
Steven Eric Krauss, Azimi Hamzah, Zanariah Mohd Nor, Zoharah Omar, Turiman Suandi, Ismi Arif
Ismai, and Mohd Zaidan Zahari 260
inception in 1986. He has authored and co-authored several books and articles both
locally and internationally.
Zanariah Mohd Nor is a Lecturer at the Faculty of Agriculture and Biotechnology,
Universiti Darul Iman Malaysia. She is also a doctoral student/candidate in the Extension
Education program at the Department of Professional Advancement and Continuing
Education, Faculty of Educational Studies, Universiti Putra Malaysia. Her research
interests are extension education, youth studies, program evaluation and instrument
development.
Zoharah Omar is a Lecturer in the Department of Professional Development and
Continuing Education, Universiti Putra Malaysia. She holds a Bachelor degree in Law, an
M.Sc in Human Resource Development and a PhD in Psychology, specializing in
Industrial and Organizational Psychology. After being a human resource manager in a
multinational manufacturing company she embarked on a career in academia. Her
research interests are in work team design, employee performance management, and
employee well-being.
Turiman Suandi is a Professor in Extension Education specializing in youth
development at Universiti Putra Malaysia. He is currently Deputy Dean of the School of
Graduate Studies, responsible for student affairs. He has also been involved in advisory
and community services both nationally and internationally in his research interest areas
of leadership, motivation, administration and volunteerism. He has authored and coauthored
several books and articles both locally and internationally.
Ismi Arif Ismail is a Lecturer in the Department of Professional Development and
Continuing Education, Faculty of Educational Studies, Universiti Putra Malaysia. His
contributions in teaching, research and consultancy have focused on continuing education
covering the areas of extension education, youth development and leadership. He
obtained his doctoral degree in Continuing Education from the University of Warwick,
United Kingdom in 2005.
Mohd Zaidan Bin Zahari is a teacher in the Department in Agrobusiness, Kolej
Profesional MARA Beranang, Malaysia. He holds a Bachelor of Science degree in
Bioindustry from Universiti Putra Malaysia. His teaching interests include horticulture
and soil science.
Copyright 2009: Steven Eric Krauss, Azimi Hamzah, Zanariah Mohd Nor,
Zoharah Omar, Turiman Suandi, Ismi Arif Ismail, Mohd Zaidan Zahari and Nova
Southeastern University
Article Citation
Krauss, S. E., Hamzah, A., Nor, Z. M., Omar, Z., Suandi, T., Ismail, I. A., & Zahari, M.
Z. (2009). Preliminary investigation and interview guide development for
studying how Malaysian farmers’ form their mental models of farming. The
Qualitative Report, 14(2), 245-260. Retrieved from
http://www.nova.edu/ssss/QR/QR14-2/krauss.pdf