Article Title [Persian]
اگرچه انجام پژوهش کیفی کار آسانی نیست ولی آموزش طراحی و انجام آن وظیفه دشوارتری می توان باشد. هدف اصلی مطالعه حاضردرک بینش و تجربیات اعضای هیئت علمی آموزش زبان انگلیسی در مورد چالش های انجام تحقیق کیفی در محیط آموزش عالی ایران است. داده های این مطالعه کیفی با استفاده از مصاحبه نیمه ساختار یافته با 20 عضو هیئت علمی جمع آوری و از روش زمینه یابی برای تحلیل آنها استفاده شد. نتایج مطالعه نشان داد که اصلی ترین چالش های انجام تحقیق کیفی از دیدگاه اعضای هیئت علمی آموزش زبان انگلیسی شامل مواردی همچون سلطه کمی گرایی بر محیط آموزش عالی ایران ، عدم وجود درس تحقیق کیفی در برنامه درسی دوره های تحصیلات تکمیلی آموزش زبان انگلیسی، دشواری تفسیر و تجزیه و تحلیل داده های کیفی، زمان بر بودن انجام تحقیق کیفی و مهارت نوشتن بودند. اکثریت شرکت کنندگان در پژوهش حاضر بر این باور بودند که دلیل اصلی عدم رشد تحقیق کیفی در محیط دانشگاهی، وضعیت فعلی حاکم بر نظام آموزش عالی ایران است ، در حالی که عده ای نیز سلایق حرفه ای و علایق شخصی اساتید را عامل موثر می پنداشتند. محققان حاضر برای کاهش چالش های انجام تحقیق کیفی در نظام آموزش عالی ایران ، پیشنهادهای را ارائه داده اند.
The present study was conducted in Iran where currently, there are 2468 universities and higher education institutions. The website of the Ministry of Science, Research, and Technology contains a list of the different types of recognized universities and institutions. The number of Master and doctoral students are 656286 and 141077, respectively that drastically is increasing in recent years (IRNA, 2018). The Supreme Council of the Cultural Revolution is the highest authority in the area of policy and planning concerning the higher education. The Ministry of Science, Research, and Technology is responsible for all tertiary education. The higher education programs are administered in the form of credit hours for each semester (unit-based system). For entering Master’s studies, the applicants should have credentials proving the completion of a Bachelor’s degree and are required to take part in National Entrance Examination. If the applicants can get the benchmark in the examination, they can choose their preferred universities. The result of their acceptance status is announced based on the determined criteria by National Organization for Educational Testing (NOET). Master’s programs take at least two years, and the students mostly pass the related courses in 3 semesters, and they write their thesis in the last semester. Publishing paper out of thesis in Master’s studies is not obligatory in most universities.
For pursuing PhD programs, the applicants are required to have credentials proving the completion of a Master’s degree with a grade point average of at least 14 out of 20 or its equivalent for admission in doctoral programs. They should take part in PhD programs’ National Entrance Examination, if they can get the benchmark in the examination, they can choose their preferred universities. In the case of acceptance, they have to attend interview session in the accepted universities. If they can get the required score in interview session, they are allowed to register for PhD programs. Doctoral programs offered at universities and institutions have been designed for four years, being equivalent to eight academic semesters (i.e., three semesters for instruction, one semester for comprehensive examination, and four semesters for dissertation project). In PhD programs, the criterion mark for passing courses is 14 out of 20 and the grade point average should be at least 16 out of 20. For defending a dissertation, at least one paper from it should be published or accepted for publication in the journals that are approved by the Ministry of Science, Research, and Technology. But for considering the complete mark of a dissertation, two papers from a dissertation should be published or accepted for publication in the approved journals.
In recent years, research has increasingly escalated in Iran; as a consequence, the country has dramatically risen in world rankings on the basis of the number of scientific documents (Ehsani et al., 2016). Generally, more than a few decades have passed from the life of macro policies and development planning to these policies in Iran, but in particular science and technology policy has a history of nearly two decades. For the first time in the Third Development Program, a chapter was devoted to the development of science and technology to improve the scientific rank of Iran in Middle East and the world. Over the years, several upstream documents for macro policymaking in the field of science and technology including the twenty-year vision document, the country’s comprehensive scientific map, and the general policies of science and technology signified by the supreme leader have been formulated and executed (Moradipoor et al., 2017). As a result, qualitative research studies have been developed in recent years as the part of macro policies and development planning to these policies, but this development is not as fast as quantitative research studies. However, research policymakers of different societies have focused more and more on the effectiveness of research and today, their major concern is to ensure if the research studies are truly contributing to attain developmental aims (Ehsani et al., 2016). In spite of the number of scientific documents, few research studies have had practical profits (Madandar Arani, 2016). As mentioned by Moradi et al. (2013) and Mousavi and ZaerSabet (2010), the reason is that the Iranian educational system does not possess a strongly institutionalized research culture and its implementation in different sectors, such as politics, economics, culture, and education.
Qualitative research (QR) is significant as a worldview not only as an intrinsic portion of the human activities but also from the research prospect since it focuses on complexity of human experiences and the socio-cultural settings in which humans act. For this purpose, it is necessary for students in higher education to learn how to undertake the QR techniques and internalize its basics to be qualitative researchers (Goussinsky et al., 2011). In this regard, Watt (2007) contends that becoming a qualitative researcher is an endless process. On the basis of Connolly (1998), the goal of QR is to gain insights into specific social, educational, and domestic methods and practices which exist within a specific condition. Moreover, Bogdan and Biklen (2003) maintain that “one of the characteristics of QR is to describe how people negotiate meaning” (p. 6). Qualitative investigators tend to take out meaning from their data in an attempt to gain views, and investigate phenomena in their natural context and interpret them regarding the meanings people attach to them (Denzin & Lincoln, 2000). Schram (2006) depicts QR as “contested work in progress” (p. 15), and the QR nature as “embracing complexity, uncovering and challenging taken-for-granted assumptions” (p. 7) and being “comfortable with uncertainty” (p. 6). The purpose of QR is toward problem generation than problem solution (Schram, 2006). According to De Ruyter and Scholl (1998), QR is necessarily diagnostic and exploratory in nature, which makes it invaluable for developing new conceptualizations.
On the basis of Marshall and Rossman’s (1995) study, qualitative researchers confronted at least three challenges in undertaking QR. First, developing conceptual framework that is “thorough, concise, and elegant” (p. 5). Second, planning a design that is “systematic and manageable yet flexible” (p. 5). Third, being capable of incorporating these into a “coherent document that convinces the proposal reader...that the study should be done, can be done, and will be done” (p. 6). Another challenge of novice qualitative researcher is bringing the various components of QR paper into consistent textual pattern. The individual part such as, literature review, method, results, discussion, and conclusion might be built in a logical manner, even though many QR papers lack the adjustment of theses sections into a consistent form (Chenail & George, 2009).
In one study undertaken by Cooper, Fleisher, and Cotton (2012), all subjects showed that learning QR consists of experiencing a variety of negative and positive emotions. When the students subject to new methodologies and terminology, they appeared to feel confusion and anxiety and also the lengthy phase of QR data analysis appeared to cause frustration or the feeling of being overwhelmed. Some research studies (Dearnley, 2005; Hoskins & White, 2013; Johnson & Clarke, 2003) specified QR data collection challenges as follows: unwillingness of subjects to participate, being in formal or informal clothes for an interview, being inexperienced for undertaking interview, and feeling of seclusion from other investigators and peers during data collection. In another research study, Rimando et al. (2015) described the data gathering challenges in dissertation research faced by PhD students at a south-eastern United States Urban University. The results of their study showed PhD students may face unexpected challenges during the stage of data gathering in their dissertation for several reasons such as, language of data collection tools, the length of data collection, researcher exhaustion, and susceptible information.
Some research studies were undertaken in the Iranian higher education context on the challenges of QR studies. Zokaei (2008) investigated the challenges of QR in Social Sciences in Iranian context. The results showed that the challenges consisted of the prevalence of some misconceptions about QR, the dominance of quantitative research in the Iranian higher education context, paying little attention to institutionalizing theories, detachment of theory from method, partial consideration of common culture, weaknesses in describing experiences, lack of consensus on QR evaluation criteria, generalizing in macro as a common way, weaknesses in teaching method, and transferring social and communication skills, and neglecting the qualitative potential of quantitative data. Khankeh et al. (2015) conducted a research study to depict the challenges of undertaking QR. The outcomes of the study revealed that Iranian beginning researchers had some troubles to legitimatize their methodology of selection and often experienced some degree of methodological elimination. They did not have any clear realization of the inquiry process in terms of data collection procedures, data analysis, and even appropriate sampling plan, which must be identified on the basis of methodological rules. Insufficient methodological knowledge, contradiction between research question and methodology, and lack of notice to the principles of qualitative methodology were some major challenges. Kheiroddin & Dalaei Milan (2016) investigated the challenges of qualitative research reliability in Iranian Urban engineering studies. The results showed that the challenges of QR reliability can be divided into three groups: challenges of starting research, research analysis, and terminating research. To obviate the challenges the researchers recommended that the research course in Iranian higher education should be more rigorous to improve the methodology of urban engineering, and concluded that the root of challenges went back to weaknesses of higher education especially in research course. Asadi et al. (2018) conducted a study on the challenges of QR studies from Iranian faculty members’ and PhD students’ perspectives. The participants were chosen from Economy and Agricultural Development faculty of Tehran University. The results indicated that the challenges included the motivation and interest of Iranian researchers, incompatibility of course content with QR methods and inaccessibility of QR software, ambiguous nature of QR, the lack of support for conducting QR studies, and subjective nature of QR.
According to Atai et al. (2018), since the ELT researchers and mentors are dealing with human beings in their studies, mixed-methods and qualitative method could solve the ELT problems. Mirhosseini (as cited in Atai et al., 2018) contended that qualitative studies “are still overshadowed by statistical research approaches” (p. 56) and the students cannot gain in-depth knowledge in conducting QR due to focusing too much on quantitative study. Because of the significant status of QR in applied linguistics, it is integral to specify the challenges which ELT researchers in general and ELT novice researchers in particular encounter during conducting QR in higher education context. According to Kue et al. (2015), the term challenge refers to methodological and practical issues in conducting research. As a result, the operational definition of the term challenge in this study is the methodological and practical issues on the way of conducting qualitative research studies in the Iranian higher education context. Therefore, this study aimed at investigating the possible challenges on the way of undertaking qualitative inquiries from ELT faculty members’ perspectives. The findings of the present study could be helpful for the ELT professors, students, and researchers in the context under investigation. Thus, the main goal of this study is to answer the following research question,
What are the challenges of conducting QR in the Iranian ELT higher education context from the Iranian ELT faculty members’ perspectives?
A qualitative approach was selected for this study as the researchers aimed to investigate the challenges of undertaking QR from the perspectives of the Iranian ELT (English Language Teaching) faculty members. Qualitative research based in an interpretive paradigm is exploratory in nature, so enabling researchers to get information about an area in which little is known (Liamputtong & Ezzy, 2005). The method used to select the focal participants was purposive sampling, and its type was criterion sampling (Ary et al., 2019). In criterion sampling, the researcher sets some criteria and includes the cases that meet the criteria (Ary et al., 2019). The criteria that the researchers set were as follows: (a) They should be faculty members, (b) They have a considerable amount of practical experience in conducting qualitative research, (c) The sample should include assistant, associate, and full professors in the field of ELT due to having varied lengths of research experience; and (d) They should be selected from the top-tier Iranian higher education universities including, State Universities, Islamic Azad Universities, and Payam-e-Noor Universities. Considering these criteria, 35 ELT faculty members were selected as the initial sample. They were interviewed until the data saturation was reached upon interviewing 20 participants and consequently, 15 other participants were ignored. They were 13 males and 7 females. The age of the participants ranged between 36-60 years old. Their native language included Persian, Turkish, and Kurdish, and all of the participants had a good command and mastery of both Persian and English. At the time of data collection, they were teaching applied linguistics in one of the Iranian higher education universities. They had varied lengths of research experience, ranging between 7 to approximately 25 years. Pseudonyms are used in all written and published data.
The instrument for collecting data was individual interviews with the participants. The semi-structured interview was applied to gain the heart of experiences, issues, and concerns of participants. To do so, 20 ELT faculty members were interviewed to gain their standpoints regarding the challenges of qualitative studies in the ELT higher education context. It consisted of 15 open-ended questions. It was reviewed by three experts in the field, and the validity of the semi-structured interview was assured. Three participants were interviewed in a pilot phase to improve the interview questions. Then, the formal interviews were carried out with the participants. Interview sessions were held within two months during January–February 2018. They were held either face to face or through telephone based on the availability and willingness of the participants in which 13 participants were interviewed face to face and seven participants were interviewed via telephone. The average time of each interview was 30 minutes. The longest interview took 37 minutes and the shortest one was 25 minutes. Prior to holding the interview sessions, the participants were informed about the aim of the study. In the case of their consent taking part in the study, the exact time and place of the interview sessions were arranged. Due to the participants’ time pressure regarding their university classes, most of the interview sessions were held in their break times between their classes. For the face to face interviews, the place of interview was in the participants’ offices. The interview was administered by the first researcher. Qualitative researchers should make rapport in their encounter with a participant in order to create a research relationship that will let the researcher get in touch with that person’s story (Goodwin et al., 2003; Liamputtong & Ezzy, 2005). In order to ensure that the relationship between the researcher and the participant is non-hierarchical, the researcher often involved in a reciprocal sharing of his personal experiences (Liamputtong & Ezzy, 2005). All interviews were administered so as not to interrupt or impose answers on the interviewees to enhance interviewees’ active role in narration (Silverman, 2011). The participants of the study were assured about the confidentiality of the data.
The interviews were audio-recorded to preserve the spoken words with the permission of the participants and then transcribed (Emerson, Fretz, & Shaw, 1995). The process of transcription is often thought of as purely a technical practice including the transformation of the spoken word into data. The researchers in the current study preferred to undertake their own transcription, believing that this was an important first step in the data analysis whereas some researchers opted to have their transcription performed by another person.
Since grounded theory accelerates developing conceptual meanings grounded in data (Alemu et al., 2015), it is regarded as a proper method for emergent research, including this study. Grounded theory includes proven principles and procedures, such as implementation of open coding and constant comparison. In this study, data analysis and data collection were undertaken simultaneously utilizing the constant comparative method of the grounded theory approach on the basis of Charmaz (2006). The use of this method of analysis was in line with the implementation of the interpretive paradigm in this study in which the researchers and the participants co-constructed the meaning instead of verifying objectively the extant hypotheses (Mills, Bonner, & Francis, 2006). In this method, the researchers also had the chance to apply their perspectives reflecting upon the process of data analysis (Mills et al., 2006).
According to a grounded theory approach, to facilitate the development of the primary concepts, the researchers of the present study started data analysis with initial coding (Charmaz, 2006). This analysis uncovered a number of major themes in the collected data, allowing investigation of various concepts and categories within the data. Upon the completion of the initial coding stage, focused coding of the codes and concepts was employed to investigate emerging core categories. Focused coding (Charmaz, 2006) included investigating the codes and assessing relationships between the codes. In the axial coding phase, these codes were categorized (Charmaz, 2006) to show the different dimensions in the research process. In this stage, the relationships between categories and subcategories were investigated by the researchers to establish more precise and complete explanation about the phenomenon under study.
Upon finishing coding process, the main categories and subcategories of the study were extracted, which are depicted in Table 1.
The Main Categories, Subcategories and Prominent Codes
The Main Category
The Dominance of Positivism in Iranian Higher Education Context
A Good Command of Writing Proficiency as a Prerequisite of Conducting QR
Collecting the Proper Data for Initiating QR
Time-consuming Nature of QR as a Real Challenge in Iranian Academic Context
Educational System as the Main Reason of QR Underdevelopment
Lack of Qualitative Research Course in Postgraduate ELT Syllabus
Interpretation and Analysis of Data as the Main Challenges of Iranian ELT Researchers
Figure 1. The Relationships between Categories, Subcategories, and Codes
3.1. The Dominance of Positivism in the Iranian Higher Education Context
Most of the faculty members pointed out that they preferred to conduct their research studies in mixed-methods approach or quantitative method instead of qualitative one. Majority of the participants reported that QR was not the favorite research methodology in the Iranian higher educational system due to positivistic view toward research. They believed the validity and reliability of qualitative studies could not be attained same as quantitative ones that created problems regarding the credibility of QR in the Iranian academic setting. Ahmad in this regard noted,
The real sense of validity and reliability of QR studies is substantially different from the quantitative ones, which makes it a challenge for the students and faculty members undertaking qualitative research because they are used to undertaking quantitative studies and considering the quantitative studies as viable form of research.
Therefore, one of the main challenges of conducting qualitative research is the unfamiliarity of the postgraduate students and even most of faculty members with the concept and principles of QR methods due to their positivistic background. Consequently, the credibility of QR studies’ findings is under question in the Iranian higher education context. Sahar in this regard stated,
The findings of QR studies are not welcomed in the Iranian academic context due to the dominance of positivism, and in this context the findings of research should be in form of statistics to persuade the readers and the users of them. In other words, numbers are more valid than words.
From her words, it can be inferred that the findings of quantitative research studies are welcomed and regarded more valid and reliable due to the positivistic background of postgraduate students and faculty members.
3.1.1. Subjective Nature of QR Studies
Positivism is on the basis of scientific objectivity and observation than subjective and individual views. Positivism regards knowledge as observable facts and non-observable issues, such as feelings and values are not considered by positivist researchers (Mack, 2010). But qualitative research studies are subjective in nature, and the researcher is the first instrument for collecting and analyzing the data, therefore, individual views and interpretations of the researcher are the main parts of qualitative studies. Due to the positivistic view of Iranian academia, the objectivity of the research findings is very important, which the perspectives and views of the researcher are not regarded in the findings. Therefore, one of the challenges of conducting QR in the Iranian academic setting is the subjective nature of qualitative studies, which is not welcomed in the Iranian positivist context as only objective findings are credible and valid. Saeid pointed out,
The main problem of qualitative papers in this context is the voice of the researcher. The dominant view is that the researcher cannot say something from his or her views, and he/she should mention the findings based on the scientific approach in which the role of the researcher is just proving or disproving the predetermined hypotheses.
It is concluded that Iranian researchers in the academic setting are criticized if they incorporate their individual views and interpretations into their findings, and on the other hand, one of the prominent features of the qualitative studies is the individualized and subjective nature, which is not welcomed in the Iranian academic setting.
3.1.2. Paper Publication
Most of the participants argued that Iranian ELT journals mostly publish mixed-methods or quantitative research studies. As Ali noted, ‘If the research is supposed to publish, quantitative or mixed-methods studies are better but QR is more demanding and profound.’ The participants of the present study argued that QR studies are not welcomed for publication by Iranian ELT editors since they are more subjective in nature. Gaining the similar findings in quantitative research is rather straightforward as the data are in numerical form. But in QR achieving the similar results can be cumbersome and difficult. It is due to the subjective nature of the data (Zohrabi, 2013). But for the Iranian journals objectivity is more favorable and welcomed regarding the positivistic epistemological view in the Iranian educational system and journals’ editors (Atai et al., 2018). Although there are “qualitative-friendly journals in the field, hardly do they prioritize qualitative inquiry and, of course, there is no qualitative-only journal in the broad area of language education” (Mirhosseini, cited in Atai et al., 2018, p. 57). According to Atai et al. (2018), most of the reviewers’ comments of journals address the quantitative parts of the mixed-method research. Therefore, doctoral students conceived that by conducting mixed-method research, they could obviate the problems and publish their papers.
3.2. A Good Command of Writing Proficiency as a Prerequisite of Conducting QR
Duszak and Lewkowicz (2008) asserted that writing in a non-native language was considered an important task. Some of the participants noted that most of Iranian postgraduate students and novice researchers are not proficient enough to write fluently to meet the demands of QR writing. In the literature of qualitative Social Science approaches, the role, meaning, and importance of writing are rarely challenging and the assumption which needs to be examined is that QR could not really be segregated from the practice of writing (van Manen, 2006). According to Mina,
The role of writing proficiency is quite important given that qualitative research is full of descriptions, interpretations, and personal opinions in comparison with quantitative research where numbers and statistics speak.
She believed that undertaking QR requires good writing proficiency due to its hermeneutic nature. In particular, graduate studies focus on students’ undertaking research and reporting the findings of their research studies in written forms accessible to other members of their fields. Therefore, writing plays a particularly significant role in graduate contexts in terms of the values placed on communicating with others implementing proper discourse conventions as well as students’ comprehension and learning domain-specific knowledge (Anson cited in Riazi, 1997).
Sasan contended that,
Absolutely important! Diction of quantitative research is to some extent fixed, like, as the table shows or significant difference between this and that, but QR, regarding its nature, has fluid diction and one of the reasons that individuals avoid conducting such a research is its writing, and writing proficiency plays an important role here.
As stated by Corbin and Strauss (2008), qualitative investigators prefer to conduct qualitative studies since they are drawn to the fluid, evolving, and dynamic nature of this approach despite the more rigid and structured format of quantitative methods, and they enjoy playing with words, making order out of chaotic data, and thinking in terms of complicated relationships. For them, doing QR is a challenge that brings the whole self into the process. QR methods rely heavily on the power of words and images but do not contain the assimilated meanings, such as numbers and equations; rather it is an attentive search for meaning and understanding and an attempt for in-depth conception of the problems and phenomena under study. In QR, knowledge deduces from the context-specific view on the experienced phenomena, interpretations, and explanation of social experiences (Khankeh, et al., 2015). Thus, the role of the writing proficiency in undertaking QR is so significant and vital.
In this regard Maryam stated,
Writing proficiency certainly plays a role because inability to reflect the context, the participants, description, analyses, etc. will produce a poor report. In quantitative analysis, writing ability is not much important because there are cliché sentences for each section and the only part which requires good writing skills is the discussion, which is not taken seriously. Usually the analysis and results are focused on.
She believed that poor writing in undertaking QR will result in a poor report of the findings in spite of the quantitative approach that contains cliché statements to report the findings of the study.
It is not assumed that only writing proficiency is an important factor in QR. It is also a good criterion in quantitative research at the same time. Although in quantitative research we are dealing mostly with numbers or numerical data, we are dealing with the words at the same time in this type of research, too. So I think it is the matter of degree rather than the matter of absolute classification; for example, you cannot say this research as absolutely quantitative or qualitative! We can say that a research is more or less quantitatively- oriented or qualitatively- oriented. In the literature, we believe that in qualitative research we deal with words, it means that you should have a good academic writing skill, a good knowledge of words, and a good knowledge of language. This is because we say qualitative research needs a good command of language than quantitative one.
Mohsen believed that having a good command of knowledge of academic writing is very important to write QR studies. He stated that the importance of writing in conducting different types of research is the matter of degree, and in qualitative-oriented research approach, it could be more significant due to dealing with words than numbers.
A few participants also noted that they were not good writers themselves, and this hindered their ability to teach writing skill to others. But most of the participants mentioned that they are competent enough to deal with teaching advanced and creative writing skills to their students.
3.2.1. Lack of Argumentative Writing Skill
QR writing is essentially an argumentative genre. But at first glance, the description in QR writing might prevent novice from noticing its argumentative essence (Wang, 2013). According to Wang (2013),“discourse features, such as thick description, detailed narratives, expressive interpretations, vivid metaphors, and strong personal voices, often make new students neglect its argumentative and persuasive nature” (p. 643). Some of the participants noted that argumentative writing is an essential requirement for interpreting the qualitative data and the main challenge of students and novice researchers in interpreting qualitative data is low argumentative writing proficiency. Hossein in this regard pointed out,
Most of the students cannot cope with the argumentative nature of qualitative data interpretation because they do not have enough expertise in argumentative writing. Argumentative writing is different from general writing proficiency, and most of the students are used to descriptive writing, and they are not trained for argumentative nature of qualitative research.
His words implied the challenge that most of Iranian researchers and postgraduate students face in conducting QR is argumentative writing. Without argumentation, the results and reports of QR studies are not satisfactory and persuasive. As a result, argumentative writing proficiency is a requirement for the interpretation of the qualitative data.
3.2.2. Lack of Advanced Writing Course
Advanced writing course is one of the courses offered at MA level but at PhD, there is no advanced writing course. Some of the participants of the study believed that this course is very essential for postgraduate students for improving their academic writing proficiency, and it should be added to the ELT PhD syllabus. Mina in this regard noted,
Writing course in MA cannot meet the needs of postgraduate students for conducting research, especially in the case of QR studies. It is thus vital to add an advanced academic writing course to PhD syllabus. It can improve the necessary academic writing skills of the students.
She noted that an advanced writing course is a must at ELT PhD level to develop the academic writing skills of students since they need these skills to conduct QR studies.
3.3. Collecting the Proper Data for Initiating QR
Data collection is the first step in undertaking research. Data collection, commonly happening concomitantly with data analysis in QR, is regarded as the systematic collection of data for a special aim from different sources, such as interviews, focus groups, and observation. Based on the data collection method, researchers may face challenges of gaining information from participants in a study (Rimando, et al., 2015). There are few studies in reviewing of the related literature on the topics of data collection challenges faced by novice researchers (Ashton, 2014; Dearnley, 2005; Nicholl, 2010).
3.3.1. The Difficulty to find the Proper Participants and Data Elicitation
Some of the participants believed that finding the proper participants for conducting QR studies is a demanding task. Reza noted,
In conducting QR, data collection is very difficult, of course the data can be collected easily, but forcing the participants to act in such a way in accordance with the research model is a bit hard.
He believed that data elicitation is very important, and qualitative researcher should direct participants in such a way that he/she could elicit the desired data for the purposes of his/her study. Gathering rich data is another issue that was noted by Maryam, ‘finding the participants that can gather rich data from them is another challenge’.
Ahmad in this regard contended,
Data collection is a cumbersome task. People are not helpful because it takes much more time. So many people avoid taking part in qualitative research since identities are known to researchers, but in quantitative research, including surveys; people can hide their identity and even do not provide their age, gender, etc. However, in an interview or observation they have to sit face to face with the researcher.
Participants might have concerns about the confidentiality of their information if they are divulging personal information to the researcher in the interview session (Bonevski et al. cited in Rimando, et al., 2015). Therefore, another problem in data collection is identity and confidentiality of the information which leads to refusal on the part of participants to take part in QR data collection process.
3.3.2. The Length of Data Collection
Another issue that is stated by Ahmad is the length of data collection process. The data collection process could be affected by the length of the data collection instrument or by how long a participant is involved in the process of gathering data (Rimando et al., 2015). Participants may feel uncomfortable in the course of data collection and not want to fill the survey questions or may need assistance to complete the survey. In some cases, the participants might provide information, which is not efficient as they try to rush through the data collection process (Rimando et al., 2015).
3.4. Time-consuming Nature of QR as a Real Challenge in the Iranian Academic Context
Some of the participants believed that the main challenge of undertaking QR is the time taken for conducting QR, which is due to the nature of QR studies, turning to be a real challenge in the Iranian academic context. Researchers should devote a lot of time conducting a QR study, especially in the case of ethnography studies, which may take several years. As Ali stated, “it is more time-consuming and in our academic context it is not welcomed”. The major drawback of QR analysis is that this process is time-consuming (Bowen, 2006). Findings of QR could be more difficult and time-consuming to characterize visually (Anderson, 2010). According to Shakouri (2014), it should be time-consuming since as Russel and Gregory (2003) contended “much of the art of qualitative interpretation involves exploring why and how different information sources yield slightly different results” (p. 36). As noted by Atai et al. (2018), “doing qualitative research is demanding and time-consuming” (p. 45).
3.4.1. The Shortage of Time for Conducting Research in the Iranian Academic Context
Most of the participants stated that one of the main issues regarding QR studies is shortage of time. They noted that the professors in the Iranian academic setting is under pressure to publish academic articles or books in a short period of time to gain promotion; as a consequence, the time of conducting research would be an important challenge. Therefore, they prefer to conduct quantitative research since conducting QR studies can be time-consuming. In academic setting, there is an increasing pressure to publish fast, preferably shorter articles with limited words (Ledgerwood & Sherman, 2012) leading to a stress on quantity over quality (Worsham, 2011). Ali pointed out,
Conducting QR requires longer time, and in the academic context, the time of research is very important for faculty members. The shorter the time of the study, the better opportunity for publishing more papers will be. But QR studies require more time due to their data collection and data analysis.
He contended that the Iranian faculty members are under pressure to publish more papers and books to enhance their research records; therefore, the time of conducting research is very important to them. In the case of QR studies, especially ethnographies, the researcher might devote several years conducting a QR research.
3.4.2. Shortage of Time for Term Papers
Some of the participants noted that on the one hand, postgraduate students are made to publish their term papers in a short period by their professors, and on the other hand, they have to write several term papers during just a semester; that is, a paper should be written for each course. Consequently, postgraduate students prefer to conduct quantitative research than QR due to time constraint. In this regard, Ehsan pointed out,
Faculty members and professors are under pressure to announce the students’ marks upon finishing the semester; as a result, they must determine the deadline for students to deliver the term papers. Thus, the students try to conduct and write the quantitative papers to meet the deadline to get the mark for publishing papers. Otherwise, they will lose the mark for term paper.
As Ehsan noted, the students and professors are under pressure in the higher education context, and inevitably the students just resort to the quickest way to conduct and write their papers and prefer quantitative studies than qualitative ones to meet the deadline of the term papers.
3.5. Educational System as the Main Reason for QR Underdevelopment
Some of the faculty members believed that the Iranian educational system is faulty for QR underdevelopment in Iranian academic setting. Hamid, one of the experienced ELT faculty members, asserted,
This point that you say whom should be blamed, the educational system and the courses that the students passed look at QR a little, and the reason is clear because quantitative research achieved the prominence and dominance. If you look at dissertations, 95% of them are quantitative.
He noted that due to the dominance of quantitative approach in the Iranian academic setting, QR is not taken seriously by postgraduate students and faculty members. And most of the theses and dissertations at MA and PhD levels are undertaken in quantitative approach due to the predominant positivistic background in Iranian academic setting. Reza in this regard contended,
When MA students have just a two-credit research course, they cannot absolutely be familiar with QR, and they should be very smart if they learn quantitative research in this period as QR needs more time. During PhD program, QR can be presented but in MA it is not suggested.
In ELT MA programs offered by the Iranian universities of higher education, the student do not have enough time to be familiar with even the basic principles of QR and according to Reza’ words, if they learn quantitative research, it can be regarded as the good result for the research course and also for the students. But at PhD level, QR can be presented. That is the fault of the educational system since in ELT syllabus offered there is no course specified for QR. Again here Reza referred to the issue of time, ‘QR needs more time’.
Ahmad in this regard stated,
Other things, external forces should be blamed at the same time; that is, the educational system should provide equal opportunities for both qualitative and quantitative inquiries. The educational system should not say “quantitative research is enough”, emphasizing just on quantitative research and ignores QR.
He contended that the educational system should provide enough chance for undertaking QR in the academic setting and open the research gate for natural inquiry, especially in social sciences. Nahid asserted that ‘Educational system seems to play a greater role because there is usually one research course, which focuses on quantitative approach mode’. Therefore, she believed that the educational system is the main cause of minimizing QR in the academic context, and the focus of the research is mostly on quantitative approach.
3.5.1. Professors and Policy Makers as other Reasons of QR Marginalization
Some of the participants believed that professors are the main reason for marginalizing QR in the academic setting. Some of the faculty members argued that professors do not have enough knowledge to teach or conduct QR studies. Saeid in this regard noted,
The nature of QR is hard. Of course, professors are not expert in this regard, and they do not conduct QR as they are trained to do quantitative research. And after all, the nature of the major or field specifies conducting QR or quantitative research.
He emphasized that professors and mentors are in quantitative-oriented setting and do not have enough background to conduct or teach QR. Maryam stated,
But if a professor desires, there is no restriction to work on QR in a single research course. I worked on grounded theory for a PhD research course. I taught it because I believe students become familiar with quantitative at Master’s level, and there are various sources outside the class to help them.
She noted that it is up to professors if they desire to work on QR methods at PhD level because the syllabus is flexible enough to include QR course. Atai et al. (2018) argued that,
The participants believed that positivism dominates our field as long as the professors and supervisors rely on quantitative methods more, attempt to transform pure qualitative studies into mixed-methods to preserve the quantifiable perspective of the study, and increasingly develop their knowledge and expertise in it at the cost of unconsciously marginalizing the qualitative method. (p. 56)
Ali contended that ‘educational stakeholders and policymakers have the negative role here’. Policymakers might give low credibility to findings of QR methods. Sallee and Flood (2012) found that stakeholders mostly apply quantitative research when research is called upon.
3.5.2. Hermeneutic Nature of QR as Other Reason for QR Marginalization
Ali in this respect noted,
In my opinion, no one is blamable in this regard. QR has a global trend in which at first quantitative research and also numbers were prominent since they regarded trustworthy, and people prefer to deal with numbers, but QR has hermeneutic sense; as a result, the work becomes harder than quantitative research due to the lack of consensus and difficulty in writing.
He believed that conducting QR is demanding and researchers prefer to work with numbers than words due to the hermeneutic nature of QR. QR is characterized by its hermeneutic and fuzzy nature. The innate vagueness of QR regarding its fluid and interpretive essence could also make this method to research unpersuasive to a researcher who taking a well-integrated prior theory (Reisetter et al., 2003).
3.6. Lack of Qualitative Research Course in the Postgraduate ELT Syllabus
Most of the participants stated that the absence of QR course is very challenging in the postgraduate studies. They believed that QR course should be added as a separate course to the syllabus of MA and PhD courses to develop knowledge of the students to conduct QR studies. Sahar in this regard asserted that ‘for MA or PhD we can have two research courses or a two-credit course, one for qualitative and one for quantitative’. Ahmad noted,
It seems we cannot consider a separate course for QR unless we have required explanations and justifications, and should not forget this fact that the nature of ELT is applied, and the most part of our works is in quantitative research, and it is unlikely that the policymakers and stakeholders agree to offer a separate course for QR.
He believed that due to the nature of TEFL, which is applied, most of the research studies are undertaken in quantitative approach and for including QR course in ELT major, there should be some plausible reasons to persuade policymakers to add this course to the ELT syllabus. Nahid noted, ‘Absolutely, the required time for qualitative research in universities and research courses is not provided.’ Therefore, there is the lack of QR course in ELT postgraduate syllabi.
3.6.1. The Inefficiency of Research Course at Postgraduate Level
Most of the participants believed that the research course in MA and PhD programs is not sufficient to deal with the research methods and research theories. Ali in this regard contended,
We need more courses for doing research both in quantitative and qualitative approaches because the main challenge for the students is lack of knowledge in conducting research, I think we need more courses.
He believed that research course is not efficient enough to equip postgraduate students to conduct research and thus, the students suffer from lack of required disciplinary knowledge to deal with demanding process of undertaking qualitative research studies. To compensate this shortage, he suggested that more research courses can be added to MA or PhD programs.
3.6.2. Discrepancy on QR Course among Professors and Universities
Most of the participants believed that there is the lack of consensus among the Iranian higher education universities in the case of introducing QR methods and principles in research course. Reza in this regard pointed out, ‘In MA, it is not recommended, while in PhD it is based on the instructors’ interests, and universities do not deal with this issue in the same policy.’ He believed that every university has its own policy regarding this issue and there is no consensus on QR course.
Some of the participants noted that introducing QR methods in research course is up to professors, and it is absolutely selective. Maryam stated,
Introducing and practicing QR methods and principles in research course in postgraduate studies depend on the interest of the professors, and most of the professors are trained in positivistic context. Consequently, they do not prefer to incorporate QR methods in their courses. As a result, the students do not know anything about QLR methods and principles.
Therefore, one of the main challenges of conducting QR studies is professors’ preference for quantitative research.
3.7. Interpretation and Analysis of Data as the Main Challenges of Iranian ELT Researchers
Most of the participants in this study believed that data analysis and interpretation are the most demanding parts of conducting QR. The qualitative data analysis itself, naturally, becomes complicated because most of QR questions are ‘How’ or ‘What’ questions and demand complex processes, investigation, and discovery. QRdata analysis is complex and vexing and the epistemic essence of QR paves the way towards subjective view in education (Shakouri, 2014). Qualitative data analysis is less technical, less prescribed, and less linear, but more iterative than quantitative one. In fact, qualitative data analysis is often undertaken during data collection phase with emerging interpretations led by a theoretical framework.
As Majid noted, ‘I guess data analysis is more challenging. What should be done with all the words, sentences, files, pictures etc.? All depend on data analyses’. Based on Atai et al. (2018), “The doctoral students acknowledged that they do not have adequate knowledge and expertise in collecting and analyzing qualitative data.” (p. 45).
Data analysis for QR is more time-consuming compared to quantitative methods due to the loads of information the researcher may obtain during the research process. Reza mentioned,
But here you mention that which one is more challenging, I think data analysis and data interpretation are more challenging because we gather the data from interviews, but our basic problems are related to data analysis and specifically interpretation.
Because the ideology of QR appears to depend on the view of skepticism towards meta-narrativeness, finding a clear and absolute statement as to what QR in education actually is, turns out to be demanding (Shank cited in Shakouri, 2014). In fact, every phenomenon under study could not be elaborated in a definitive sense. As Sara noted, ‘absolute interpretation is challenging since it is hermeneutic work, that is, there cannot be a consensus regarding QR interpretation”. Interpretation involves a perspectival accounting for what investigator has understood or forming the meanings and perceptions of what happened from some points of view, an issue of the crisis of representation for some outsiders (Gubrium & Holstein, 1997). In social research studies, there are no ‘crucial tests of theories, [and that] we don’t prove things right or wrong, [so] the real test has always been how useful or interesting that way of looking at things is to an audience’ (Denzin, 1989, p. 1). In other words, in QR it is the task of others to reject, prove, and reinterpret the researcher’s selection of fact and the order and relationships that make the foundation of the interpretation. According to Denzin (1989), “all interpretations are unfinished, provisional, and incomplete.” (p. 64).
3.7.1. Data Analysis as an Achilles’ heel
Data analysis is regarded to be the Achilles’ heel among all the elements and processes of QR, and it is one of the most sensitive aspects of QR (Gummesson, 2005). In this regard, Hossein pointed out,
The most challenging part of QR report is data analysis, specifically when you want to extract a plan from the chaotic qualitative data. One of the problems the researcher usually face is treating loads of data and when researchers want to extract strategies from the heart of data, and the most difficult part is extracting a new pattern or framework.
As stated by Gummesson (2005), the term analysis is not actually applicable in QR since this term implies reliance on the pre-determined formulas, processes, and designs to the events that are not even appropriately defined or sufficiently investigated. Research problems are not tackling in transparent or straightforward method in QR (Gummesson cited in Kapoulas & Mitic, 2012). It is rather “a conscious search for meaning and understanding” by focusing on the “power of words and images”; therefore, it does not suggest the uniformity of meaning like numbers and equations (Gummesson, 2005, p. 311), and a quest for in-depth comprehension and awareness of the problems and phenomena is rather to be sought (De Ruyter & Scholl cited in Kapoulas & Mitic, 2012). In general, good analysis leads to a better understanding of a phenomenon under study. The term understanding of data instead of analysis of data can be used interchangeably in QR. The analysis of thick descriptions taking place throughout the course of a study often creates new views, and the analysis of interconnecting themes can make fruitful insights. Given the views of some participants, the depth of analysis in QR is the best approach for recognizing the complicated nature of a phenomenon under study. Merriam (2009), a leader in the field of QR in education, points out that “there is almost no consistency across writers in how the philosophical aspect of qualitative research is discussed” (p. 8). Merriam also stated that each researcher makes sense of the field in a personal, socially constructed method in true qualitative fashion.
3.7.2. Dealing with a Large Amount of Data
The qualitative data analysis starts with a large pool of data and inductive reasoning, sorting, and categorization must be deployed, and then key themes are extracted. Qualitative data analyst aims to make a shared understanding, which forms a coherent structure and a unified whole. Each level of analysis, from codes to categories to themes, reaches higher levels of abstraction. Some of the participants believed that dealing with a large amount of data and extracting the meanings from it is very demanding, posing a real challenge for Iranian researchers. In this regard Nahid noted,
One of the primary challenges of the students, novice researchers, and even experienced researchers is coping with a large pool of QR collected data. They might be overwhelmed facing this huge amount of data to analyze them and to extract appropriate meanings from the heart of collected data. Especially, Iranian postgraduate students and researchers mostly deal with quantitative data and consequently, they cannot keep up with QR data management and data analysis.
According to her words, qualitative data management is a real challenge for Iranian postgraduate students and due to their positivistic background (i.e., dealing with quantitative data), researchers may find dealing with QR frightening.
According to Black (2006), “how can words fully express the meaning inherent in our observations, personal interviews, and pictures when so much of it is subtle, hidden and contextually bound?” (p. 319). Qualitative researchers always face the challenge of compressing huge volumes of qualitative data into few lines of text that should be illustrative, descriptive, and explanatory all at the time of making their results presentable to audiences (Black, 2006).
Discussion and Conclusion
This study aimed at investigating the perspectives of ELT faculty members on possible challenges on the way of conducting QR in the Iranian higher education context. Drawing upon the semi-structured interviews, the results showed that the main possible challenges of conducting QR from ELT faculty members’ perspectives consisted of the dominance of positivism in the Iranian higher education context, paper publication, collecting the proper data for initiating QR, interpretation and analysis of data, dedicating a long time conducting QR, and lack of a good command of writing proficiency. Most of the participants believed that the main reason for the underdevelopment of QR in academic setting is the Iranian higher education system as the professors’ professional preference and personal interests determine the research trend in research courses in postgraduate level. The results also showed that most of the participants preferred to conduct mixed-method research since they believed that mixed-method research can be more valid and is easier.
The results are consistent with Zokaei (2008) as he found that one of the QR challenges in Iranian context is the dominance of positivism and quantitative research studies. He also indicated that research course is not sufficient to familiarize students with research skill patterns that is in harmony with the findings of this study. Asadi et al. (2018) highlighted that the subjectivity of QR studies and ambiguous nature of QR are among the main challenges of QR in the Iranian higher education context, which is in line with the finding of this research.
The findings are in line with those of Atai et al. (2018) as they found that mixed-method research is the first priority of ELT PhD students for both solving problems and publishing papers. The results of their study also showed that in choosing between pure quantitative or pure qualitative study, the former finds better ways to publication due to the dominance of positivistic epistemology in which the prestigious journals and many international journals still respect and welcome quantitative methods. These findings are in agreement with those of the present study. The findings of this study are also in harmony with Rahimi et al. (2019) as the results of their study revealed that ELT Master and doctoral students overemphasized the provision of enough time for undertaking good research, and they believed that a reasonable amount of time is required to conduct an acceptable study. The participants of their study stated that they are under the pressure of time and have stress to conduct and publish research studies. The findings of Rahimi et al. (2019) also revealed that ELT Master and doctoral students believed that academic writing skills in all sections of the research papers are important which is in line with the findings of the present study. Our findings are not in line with Rahimi et al. (2019) as they found ELT Master students, ELT doctoral students, and ELT instructors would mostly follow quantitative research since it is easier to undertake and fairly straightforward to report the results while the finding of the present study showed that most of the participants preferred to conduct mixed-method research due to its validity and reliability. The findings of this study are also in line with those Rimando et al. (2015) showing that PhD students may face unexpected challenges during the stage of data collection in their dissertation for several reasons, including the length of data collection.
As one of the main challenges is lack of QR course in postgraduate studies, the first recommendation that is offered by most of the participants of this study is including QR course in MA and PhD syllabi. For decreasing the positivistic view, the professors could teach the QR methods in their classes for encouraging students to conduct QR studies. The qualitative results in various academic levels should also be reported by the qualified and experienced professors and teachers in the form of academic lessons and also through holding specialized training courses. For obviating the challenge QR data analysis, the skilled and experienced instructors should teach the qualitative research software such as NVivo to provide students with the required knowledge to analyze QR data. Since the main challenges of QR studies are data collection and data interpretation in the Iranian higher education context, the higher education institutions and universities can hold some workshops on QR data collection and data interpretation to familiarize the students with QR methods and motivate them to conduct qualitative inquiries in their field of interest. Since one of the key roles in conducting QR is writing proficiency, advanced writing course can be added to the postgraduate syllabus, especially at MA level to boost the writing proficiency of the students to deal with argumentative nature of QR studies.
In spite of numerous problems requiring research, research priorities in Iranian context are not well-articulated and even the research has been and is being conducted mostly relies on form rather than content (Madandar Arani, 2016). Therefore, research priorities in the Iranian context should be changed by policymakers and stakeholders of the higher education system, and the research studies’ content should be emphasized than their form. Iranian educational policymakers and stakeholder should also give credibility to the findings of QR methods by dedicating extra points to QR studies, especially for faculty member’s promotions and encourage professors and researchers to conduct qualitative inquiries in all sectors in general and in social sciences in particular by dedicating required facilities and extra privileges. Some QR journals should also be established for publishing qualitative research studies in order to motivate novice researchers and postgraduate students to undertake QR. Incentives and financial supports should be provided for emerging QR researchers, students, and professors for conducting QR studies by academic centers, organizations, and research centers as performing QR is costlier than quantitative research. The Educational Deputy of higher education should provide a set of applied QR training courses for professors to enable them to present QLR methods in their classes and help their students to apply QLR methods in their studies.