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Using Grounded Theory Approach for Examining the Problems Faced by Teachers Enrolled in a Distance Education Programme


Sutapa Bose

Indira Gandhi National Open University, IN
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This study investigated the problems faced by teachers enrolling in a distance teacher education programme offered by India’s Indira Gandhi National Open University (IGNOU). Instead of review of literature, the study began with the examination of learners’ complaints about various aspects of the programme. Analysis of data extracted from the complaints led to the hypothesis that the inability of the programme’s learner support to address nonacademic problems was affecting the capacity for distance learning. Interventions provided for strengthening the learner support, lessened complaints and confirmed the hypothesis. Thus using the grounded theory approach this study extracted from data, the impact of a weak learner support on distance learning. The study cautions that learner support remains crucial even when distance learners are professionals like teachers; a robust instructional design does not guarantee learner satisfaction if learner support remains weak; and alterations in learner support need to be tried out before incorporating them in programmes with high enrolment.

How to Cite: Bose, S. (2021). Using Grounded Theory Approach for Examining the Problems Faced by Teachers Enrolled in a Distance Education Programme. Open Praxis, 13(2), 160–171. DOI:
  Published on 20 Oct 2021
 Accepted on 18 May 2021            Submitted on 18 Dec 2020


The Indira Gandhi National Open University (IGNOU) is an open and distance learning university of India. Its School of Education (SOE) has been offering several distance teacher education programmes since the last few decades but learners’ complaints about issues related to these programmes have been few. However, shortly after the Certificate Programme for Professional Development of Primary Teachers (CPPDPT) was started, many learners complained over phone, and many sent e-mails about problems related to various aspects of the programme. Such messages besides stating the problem reflected widespread dissatisfaction with the programme. Messages from many learners of the first two batches also included their decision of quitting the programme. This study began with a systematic examination of these complaints. In order to contextualise the study, this article describes the key features of the CPPDPT. It also describes the processes of data collection, and analysis. After that it states the hypothesis and examines its relation with related literature. It also describes the intervention provided in the light of the hypothesis and its impact on the number of complaints.

Key Features of the CPPDPT Programme

Distance in-service teacher education programmes offered by IGNOU train teachers without drawing them out from schools. The Kendriya Vidyalaya Sangathan (KVS), an organisation with a chain of 1,245 public schools across India and a few abroad, therefore approached IGNOU for continuous professional development of its teachers teaching at the primary level. IGNOU’s School of Education subsequently offered the CPPDPT. Since the CPPDPT’s target group comprised about 11,000 primary level teachers, batches comprising a few thousand teachers were admitted every year to IGNOU’s January and July academic sessions.

The CPPDPT’s duration was although six months but learners were allowed to complete it within a maximum duration of 18 months. The programme had 16 credits (one credit requires 30 hours of study) and its instructional framework comprised 6 theory courses and a 15-day personal contact programme (PCP). The PCP involved face-to-face instructions but instructions for the theory courses were delivered mainly through self-learning material (SLM) in print medium, with audio and video programmes supplementing it. Assignments and Term End Examination (TEE) were the means of assessing learning.

IGNOU offers instructions through the distance mode but it organises academic counselling in face-to-face mode for supporting learners. Academic counsellors carry out academic counselling. They tutor and assess assignments for providing academic support and counsel for non-academic problems (Rekkedal, 1991). IGNOU establishes study centres in conventional educational institutions for organising academic counselling for its programme and engages teachers teaching the same programme in face-to-face mode as academic counsellors. For its teacher education programmes too, IGNOU establishes study centres across India at conventional institutions/departments offering teacher education in face-to-face mode. The institution’s head/ senior functionary is appointed as the study centre in-charge, and its teacher educators, function as academic counsellors. However, while developing the CPPDPT programme for KVS teachers, study centres were established in KVS schools instead of teacher education institutions. This decision favouring schools as sites for academic counselling was based on the arguments that teacher education in India has shortcomings while KVS schools are reputed for offering high quality education (Education World, October 7, 2020); KVS teachers are known to be meritorious, and as learners they are unlikely to require much learner support; KVS’s secondary and senior secondary level teachers have the requisite academic qualification and they can create an in-house support system for their colleagues enrolling in the CPPDPT. It was also argued that an in-situ provision of learner support would eliminate learners’ need for travelling to study centres. Subsequently KVS’s secondary and senior secondary level teachers were appointed as CPPDPT’s academic counsellors. In keeping with IGNOU’s practice of orienting academic counsellors through a two-day programme, they were oriented for their roles.


Causal explanation is central to grounded theory and it can answer why questions (Dey, 2007, as cited in Rose, Spinks & Canhoto, 2015). This study too, identified learners’ problems and determined their cause. It began with data collection and analysis instead of review of related literature. Pre-formulated research questions therefore did not guide the study. Further, the study was not limited to examination of qualitative data and meaning making but it also involved examination of relation among the categories emerging from data. Therefore, it did not involve mere qualitative data analysis but the grounded theory approach (Cho & Lee, 2014). Moreover the phenomenon studied emerged from data, during simultaneous and iterative collection and analysis of data, and concretised into a research problem (identification of learners’ problems and their cause), as the study progressed. There was also no pre-planned paradigm for coding. Coding was initially open and led to the core category, which subsequently directed selective coding. Review of literature was carried out after the hypothesis emerged, to examine its alignment with existing theoretical propositions. The study thus followed the classic grounded theory approach (Glaser & Strauss, 1967).

The limitation of the study is that data about the number of dropouts could not be collected. However, a large number of messages from learners of the first few batches highlighted their dissatisfaction with the programme and their decision to quit. Furthermore, the last few batches admitted to the programme included thousands re-registering for the programme after having dropped out earlier. These events were the basis for inferring that the level of attrition during the initial phase of the programme was high. The second limitation was that it was not examined how the support system functioned after interventions were provided to strengthen it. The effectiveness of interventions was presumed on the basis of the declining number of queries, complaints and messages expressing dissatisfaction with the programme.

Data collection

Data Collection Time Line and Sample

The study did not begin with a pre-determined sample. Sampling began when the CPPDPT was started in July, 2014 and continued as long as learners’ messages with complaints continued. The last such message with a complaint was received in October 2020. In the July session of 2014 and January session of 2015, data was collected from learners’ messages through e-mails and phone calls. As learners complained individually as well as collectively, as large groups, the number of learners complaining every week was about 200. From July 2015 along with emails and phone calls, interviews during visit to study centres helped to collect data. These visits were made when learners assembled at study centres for the CPPDPT’s personal contact programme. 30–35 learners and 4–5 academic counsellors present at each of the six study centres visited were interviewed to understand the problems faced. The visits were however regulated by IGNOU and, study centre were not chosen randomly. Grounded theory however, permits such non-random sampling techniques including purposive sampling (Foley & Timonen, 2015).

During the January 2016 session the KVS shared with its primary teachers the CPPDPT’s objectives. It also declared that those passing the CPPDPT would be exempted from the mandatory face-to-face in-service programme, which requires teachers to be away from home for several weeks. This eliminated complaints about uninformed enrolment but complaints about other issues continued. However, in July 2016 session, following interventions for strengthening the support system, the number of complaints were only 4–5 in a week, and from January 2017 there were 4–5 such complaints in a month. Visit to study centres and, interviews stopped at this point but examination of emails and gist of phone calls from learners continued. In July 2017 many drop outs from earlier batches re-registered in the programme but complaints remained few. In 2019 admissions were closed but a few learners of previous batches complained about incomplete grade cards. In 2020 there was only one such complaint.

Tools for Data Collection

Texts themselves can be objects for analytic scrutiny rather than being corroborating evidence (Charmaz, 2006). Initially e-mails and phone calls provided data but from the July, 2015 session the study was extended to six study centres. Focus group interview at these centres also provided data. The interview schedule included themes for discussions instead of a set of questions. The themes were the points of discussions during interviews, and were selected in the light of the categories emerging from the data collected in 2014. In keeping with these categories, the interviews involved discussions with learners about their problems in managing time and using SLM for studying. The other themes pertained to learners’ awareness about the programme’s objectives, duration, assessment mechanisms, the personal contact programme’s duration and timing, IGNOU’s organisational structure and operations, jargons used at IGNOU, sources of information, and rules governing re-registration in the programme, credit transfer during re-registration, and rules for changing study centre. In order to get in-depth data, the interviews encouraged counter questions, discussions among participants, and detailed narratives. For example, in response to the question ‘Have you read the self learning material (SLM)?‘, participants asked questions like ‘Why do people from IGNOU call these books SLM?’ ‘What is SLM?’ ‘Are you sure all students really learn from SLM?’, … SLM teaches but so does a well written book.’

Data was also collected from academic counsellors present at the study centres but only through interviews during visit to the study centres. In addition to the themes comprising the interview schedule used for learners, the interview schedule included two more themes- academic counselling and induction. Discussions with academic counsellors were steered for assessing their understanding about the themes, their capacity to provide solution for learners’ administrative and other problems; and the way they were organising academic counselling and induction sessions.

Data Analysis

Complaints were analysed as soon as these were received. Data collection and analysis were therefore interrelated and simultaneous processes (Rose et al., 2015). Data analysis began with open coding. The relation among the categories emerging from open coding led to subsequent selective coding. Data analysis therefore comprised open coding, forming categories on the basis of open coding, and selective coding. These steps are described in the following sections.

Open Coding

Data analysis began with open coding. This involved constant comparative analysis and memo writing. E-mails being documents, their analysis involved coding (Bowen, 2009). Gist of phone calls were noted down, and interview data were examined line by line. Instances having a common central aspect were extracted during the examination and coded using in-vivo coding method. This made the code labels lengthy but communicated the participants’ view, in their words and captured the essence of the instances coded. Codes were organised into categories, representing theoretical concepts. Progressive identification of categories emerging from data helped to conceptualise the phenomenon being investigated (Willig, 2013).

Coding and categorising involved constant comparative analysis, involving three types of comparisons (Glaser & Strauss, 1967). First, apparently similar instance were compared. For example, instances of not taking term end examination (TEE) were compared. This revealed that these instances centred on lack of awareness of either the last date of submission of TEE form, or the deadline for assignment submission. These instances were segregated accordingly and coded differently. However, as these codes were about awareness of rules, they were aggregated within the category pertaining to lack of awareness of TEE rules. This helped to knit back the data that had been untangled (Glaser & Strauss, 1967). As comparison of instances continued, it was found that there were also instances of not taking TEE due to learners lacking time for studying. Since these instances did not centre on ‘rules’ but on ‘time’, these were categorised under time management.

The second type of comparison involved comparison of instances with the emerging concepts. For example, instances of request to postpone exam, not having time for assignments, not having time for study were compared with the emerging concept of time management and included in the category pertaining to time management. The third type of comparison involved comparison of concepts emerging from data. For example, comparison of the concepts – ‘incomprehension of organisational structure’ and ‘lack of awareness of rules’ clarified that the former involved understanding of IGNOU’s structure in terms of its units and their hierarchical relation, while the latter was about awareness of rules governing academic and administrative processes. Such constant comparative analysis during open coding not only generated descriptive categories but also their properties. Integration of these categories and their properties led to thematic categories (Glaser & Strauss, 1967) having a higher level of abstraction than descriptive categories.

Memo writing during open coding helped to compare and classify instances and diagnose the cause of learners’ problems. The following memo is an example of comparing and classifying instances for understanding what learners perceived as a problem.

‘There are instances of academic counsellors not providing feedback (tutor comments) on assignments. There are also instances of learners not having time for writing assignments. Both are problems regarding assignments. However, their comparison shows that learners do not perceive lack of tutor comments as a problem but not having time for writing assignments is a problem for them.’

Categories emerging from Data collected from Learners and Academic Counsellors

Codes are described by presenting data excerpts pertaining to the instances coded. The categories built with codes extracted from the data collected from learners are the following:

Inability to manage time: There were several instances of learners complaining about not having time for studying and writing assignments. During interviews too, the most commonly cited reason for incomplete assignments and procrastination of study, was not having enough time for the programme. The predominant view emerging on this aspect was that learners lacked the time required for a 6 month long in-service programme. Excerpts from data clarifying this are: ‘…. This programme demands more time than that we can spare’; ‘For our assignments do we stop assessing our students’ assignments?; ‘… if IGNOU really wants to assess learning it should give us time to learn, and hold exams later.’

Unprepared for independent study: A common concern emerging from data was about the absence of face-to-face teaching. There were also several instances of learners complaining about ‘feeling sacred’ to open the self-learning material (SLM) packet and start reading on their own. The Interviews corroborated learners’ unfamiliarity with the concept of self-learning, SLM and confusion between books and SLM. Excerpts clarifying this are- ‘… No, didn’t start studying, our colleges and universities never left us only with books … we were taught before being expected to study’; ‘Had heard of distance education but never thought that we would get a packet of books (SLM) and then the test.’

Stressed: Instances of Term End Examination (TEE) causing stress were common. Many learners said that they were quitting the programme because TEE made the programme stressful. Excerpts typifying this are- ‘Scared, worried, can neither study, nor work, can’t stop thinking about exams …’; ‘…. stressed, quitting better than failing…’; ‘The course material should be enough why should we take exams?’

Uninformed Enrolment: First few batches of learners seemed to have enrolled in response to the KVS’s instruction to enrol, and there were many instances of learners being unaware of the programme’s objectives. The data also showed that academic counsellors were not holding induction programme and academic counselling sessions. Therefore, learners’ confusion about the programme’s objectives continued even after enrolling. A learner’s comment clarifying this was ‘yet to understand why a 6 month in-service course with term end examination and 15 day contact programme’; ‘… no, there has been no induction, nor academic counselling.’

Incomprehension of Organisational Structure: Instances indicating learners’ unfamiliarity with IGNOU’s structure, and functions were common. For example, there were instances when learners said ‘IGNOU has an office at New Delhi, in the states (regional centers), and local offices (study centres) but which office should we contact for our problems?’; ‘We thought that being from KVS, we should contact KVS’s Regional Offices. Then we came to know that IGNOU’s regional office deals with CPPDPT. Not knowing whom to approach is frustrating’.

Unaware of Rules: Most of the complaints were about administrative hurdles. Interviews corroborated that learners were unaware of rules governing various processes. There were complaints like ‘I had registered last year, but didn’t take term end exam. Can I take it now?’; ‘I thought the programme would be discontinued. Didn’t bother to complete it. Can I re-register?’; ‘I had submitted a few assignments at my study centre at Mumbai. KVS transferred me here to a school at Guwahati. I have no study centre here. Where should I submit the rest?’;’ I am transferred but my study centre isn’t. How do I shift to a study centre at Guwahati?’

‘I sent assignments to our KVS regional office. After a long time they returned it. I think they didn’t know what to do with it. By then last date for assignment submission was over and I missed term end exam. Now I am told that assignments for the current session are to be written. Assignments I had written are now of no use.’

‘……. can’t take term end exam, didn’t know about the last date of submitting examination forms.’; ‘I missed PCP twice. I was on maternity leave and then on childcare leave. Someone said something about re-registration, is it possible to complete the programme through re-registration?’ ‘I didn’t attend the contact programme. I didn’t know this would lead to incomplete result.’

Unfamiliar with Jargons: The data especially that from interviews included instances of learners’ unfamiliarity with terms like academic counselling, credit, and the like, commonly used in IGNOU. There were instances of learners asking ‘What is credit?’; ‘Why do some courses have 4, and some have 3 credits?’; ‘Is CPPDPT a course or a programme?’ ‘What is academic counselling?’

Codes extracted from the data collected from academic counsellors also led to categories. These categories and data excerpts indicating the instances coded are the following:

Lack of Non-academic Support: The data included instances that highlighted academic counsellors’ lack of clarity about IGNOU’s structure, operations, rules, and terms commonly used; programme structure and objectives; concept of SLM; strategies for motivating learners; and managing time. It was also found that they were not organizing academic counseling, nor induction programmes for new learners. Data excerpts clarifying this are:

‘Counselling is not easy, especially for adults and we have never done such things …’; ‘How can IGNOU expect us to counsel? Are we trained for it?’; ‘I have been teaching math at secondary level all these years, … after training (orientation) for just 2 days, about totally new things like distance education, we are asked to do academic counselling for distance learning, …. Is it possible?’;

‘…. they (learners) don’t need teaching, but only information about rules, which we don’t have.’

Barriers to assessment: There were no complaints about academic issues. However, interviews revealed that academic counsellors could tutor but they could not offer tutor comments for assignments. They also did not understand IGNOU’s grading system. There were comments like- ‘We don’t understand IGNOU’s direct grading. We are not sure of the basis for arriving at a cumulative grade.’; ‘…. Don’t know how to write tutor comments. … we mention only good, excellent, poor handwriting and things like these.’

The descriptive categories, properties and thematic categories emerging from open coding of data collected from learners are listed in Table 1 and that from academic counsellors in Table 2.

Table 1

Codes, Categories and Properties emerging from Data collected from Learners.


Dependence Procrastination
Missing deadlines
Inability to manage time No time for writing assignments
Not studying, there’s no time
Not taking exam didn’t have time to study

Unprepared for independent study Studying using SLM seems difficult
Scared to start studying,
Scared to open SLM packet

Dejected Anxiety
Giving up
Stressed Quitting, scared of TEE
TEE causes stress

Unmotivated Unwillingness
Uninformed enrolment Don’t know why we enrolled
No induction, no academic counselling
6 month course, 15 day PCP, too long

Uninformed Confusion
Incomprehension of organisational structure IGNOU has how many offices?
No idea whom to contact

Unaware of rules There’s a maximum duration?
What is credit transfer?
How to change study centre?
Missed TEE, didn’t submit TEE form
Missed TEE, didn’t submit assignment
Missed PCP, is there a second chance?

Lacking clarity Unfamiliar with jargons What does CPPDPT stand for?
Are these books ‘SLM’?
What are credits?
What’s academic counselling?

Table 2

Codes, Categories and Properties emerging from Data collected from Academic Counsellors.


Unprepared for supporting learners Confused
Lack of non-academic support They don’t have time
What is SLM?
Not organising academic counselling
Learners don’t need teaching
Not sure of rules
Counselling not easy
Didn’t organise induction
Not sure about the programme’s objectives
Many dropping out, can’t help it
TEE stressful, can it be removed?
Do those missing PCP get a second chance?
Not sure about IGNOU’s offices
What’s credit?
Didn’t know the deadlines
Have not read the programme guide
What is maximum duration?
What does CPPDPT stand for?

Uninformed Barriers to assessment IGNOU’s grading is different
Not offering feedback

Selective Coding

On examining the thematic categories emerging from the data collected from learners it was found that none of the categories pertained to the instructional content or academic issues. Each category represented a non-academic barrier to distance learning. Some pertained to lack of information about systemic issues while some reflected unpreparedness for self-learning. Collectively these categories centred on non-academic barriers to distance learning.

The categories emerging from data collected from academic counsellors were mainly about unpreparedness for providing non-academic support including information about the program and its assessment system. This related meaningfully with the non-academic barriers to distance learning emerging from data collected from learners. As learner support involves counselling for addressing the non-academic barriers to learning, the idea that academic counsellors’ lack of preparedness for counselling was hindering learners’ capacity for distance learning, emerged as the core category.

From the July 2015 session the core category guided the processes of theoretical sampling and selective coding. Theoretical sampling requires decision as to what data to collect next and where to find it (Glaser & Strauss, 1967). Glaser and Strauss say that adequacy of theoretical sample is judged on the basis of how widely and diversely groups are chosen, and this requires multiple comparison groups, selected primarily on the basis of their theoretical relevance for furthering the development of the emerging categories. To make the theoretical sample wide and diverse, as well as theoretically relevant, the study was extended to successive academic sessions. Participants from 6 study centres in different states of India were also included. This drew in several cohorts of participants.

During selective coding the core code guided data collection and analysis. Data was therefore collected to understand the nature of learners’ problems and academic counsellors’ preparedness to address these. Data analysis was also carried out in the light of the core category. Therefore, it was ascertained whether the instances emerging from the data collected substantiated the core category. It was found that the KVS’s declaration of incentives and the programme’s objectives eliminated instances of learners declaring their intention of quitting, and their lack of awareness of programme’s purpose. However, the data was no longer producing new instances. Rather instances emerging in this phase being the same as those that had emerged during open coding, the substantive categories were substantiated and saturated. This established that lack of counseling and non-academic barriers to distance learning were two variables that could be related. The relation between these variables was expressed as the hypothesis that ‘lack of counseling was affecting learners’ capacity for distance learning’.

Review of Related Literature

The core category was the focus of literature review (Glaser & Strauss, 1967), and literature pertaining to distance learners’ needs, and role of academic counsellors was explored.

Distance learners may experience anxiety, hopelessness, boredom, disappointment and anger, and as these feelings affect distance learning, strategies are needed to help learners to overcome such feelings (Simpson, 2008). A key strategy is the development of learner autonomy, which leads to independent and self regulated learning (Wedemeyer, 1971). Self-regulated learning is necessary for successful distance learning (Jansen, 2020). It involves the capacity and willingness to exhibit goal-directed behaviour, taking control of learning, monitoring and regulating it. However, these capacities not being necessarily innate, learners may struggle to regulate learning, and need support for developing these capacities (Ding & Shen, 2019; Pintrich & Zusho, 2002; Zimmerman, 2002). Distance education institutions therefore need to develop the capacity for self regulated learning through sustained learner support for academic, administrative and personal aspects (Jansen et al., 2020; Moore, 2007; O’Rourke, 2003). Learner support is thus the much-needed interface between distance education institution and its students (Sewart, 1993). It comprises activities beyond the production and delivery of course materials and assists students to develop the capacity for distance learning (Simpson, 2013; Tait, 2000).

Learner support includes various types of support. This is because learners seek not only academic support, but also emotional and psychological support (Arko-Achemfuor, 2017; Fotiadou, Angelaki, & Mavroidis, 2017). Learner support therefore includes cognitive, affective, organisational, systemic and reflective dimensions (Atkins, 2008; O’Rourke 2003; Simpson, 2013; 2016; Tait, 2000). The cognitive dimension is about academic support that involves tutoring. This requires an understanding of adult learners, and knowledge in the subject area. Rest of the dimensions pertains to non-academic support that involves counselling. Counselling is therefore required for the affective dimension that pertains to learners’ motivation and enhances their self esteem and manages stress; systemic dimension for administrative issues; organisational dimension requiring support for organising study by managing time, and keeping pace with the course; reflective dimension that takes into account learners’ objectives and motivation. Ability for counselling however requires systemic knowledge comprising an understanding of distance learning, and the organisation’s administrative system (O’Rourke, 2003).

The data collected for this study showed that learners’ problems were not academic but were problems emerging from their incapacity for self regulated learning. This brought to fore the absence of counselling. The hypothesis was thus found to be in sync with the literature reviewed.

Intervention provided in the Light of the Hypothesis

As the hypothesis was about academic counsellor’s unpreparedness for counselling, in order to prepare them for counselling in May 2016, academic counsellors were oriented for the second time in two batches at Chandigarh and Mysore. The orientation programme was designed in the light of the substantive categories emerging from open coding. Topics like history and evolution of distance education, distance education in India, genesis of IGNOU, its role in democratising education, SOE’s functions and programmes, and the like usually covered during orientation programmes to offer a broad understanding of systemic issues were therefore included but the details were excluded. The time saved thus was used for:

  • Developing understanding about:
    1. IGNOU’s structure and functions;
    2. CPPDPT’s- objectives, instructional framework, credits;
    3. Need for breaking distance learners’ isolation through motivation and timely and authentic information
    4. Strategies for- time management, motivating learners, and developing study skills.
  • Proving information about:
    1. Contact details of functionaries;
    2. Sources of information (Programme guide and IGNOU’s website);
    3. Rules pertinent to CPPDPT;
    4. System of assessment and certification.

The pedagogy used for the orientation programme was also changed. Interactive discussions using case based method replaced lectures. Cases of CPPDPT’s learners’ problems were used for linking theoretical inputs to real life problems. Videos demonstrating counselling skills were used for introducing learners to the idea of counselling and its difference from tutoring. Hands on training were provided for orientation to IGNOU’s grading system and for writing tutor comments. The impact of interventions was evident from the declining number of complaints.

Findings and Discussions

Academic counselors although had the capacity for tutoring but they lacked the capacities required for assessing assignments. Learners however complained only about non-academic aspects. These aspects projected a weak learner support system with academic counsellors unprepared for counseling. This was found to be the reason for attrition and learners’ dissatisfaction with the programme. Even though declaration of incentives for completing the CPPDPT lessened some of the complaints, other complaints continued till the support system was equipped for counselling. Along with the incentives for completing the programme, this brought down the number of complaints and encouraged re-registration.

Results of grounded theory are probability statements about the relationship between concepts (Glaser, 1998). The result of this study was that unpreparedness for counselling affected learners’ capacity for self-regulated learning, which is essential for distance learning. The result emerged from a hypothesis, and hypothesis generation through theoretical coding rather than hypothesis-testing is carried out during qualitative studies including those involving the grounded theory approach (Chigbu, 2019). The hypothesis generated during this study about the weakness in learner support affecting distance learning was therefore not tested. However, declining complaints in the post intervention stage confirmed it. Moreover, the hypothesis fits the existing theoretical views, has relevance (for distance education) and is workable (Glaser & Strauss, 1967). However, the area of the study is neither unexplored, nor is it devoid of theoretical understanding. Moreover the finding does not qualify as a ‘new’ theory. It only reaffirms pre-existing theoretical understanding. Nevertheless, grounded theory can be used to test a logico-deductive theory (Glaser & Strauss, 1967), and this study confirms the need for counselling for distance learning. Moreover, grounded theory allows going beyond conjectures and preconceptions to study the actual underlying process of what is going on for providing interventions that resolve participants’ concerns (Glaser, 1998). Identification of cause of learners’ problems during the study and the interventions were also based on data and not on conjectures and preconceptions.

Implications of the Study

Orientation programme organised for those engaged as academic counsellors aims to develop the skills for counselling and assessing assignments and grading. However, the orientation programme had to be repeated and redesigned for capacitating academic counsellors for counselling. This study therefore validates earlier concerns regarding IGNOU’s orientation programme’s duration, curriculum and transaction (Manjulika, Reddy & Fulzele, 1996). However, notwithstanding a similar orientation programme, complaints have been low for IGNOU’s teacher education programmes that engage teacher educators as academic counsellors. The second implication of the study therefore pertains to the affiliation of academic counsellors. It can be presumed that bridging the transactional distance in distance education (Tait, 2003) is easier for teacher educators because of their experience of supporting adult learners and, better understanding of systemic issues of higher education including distance education. Therefore, not just qualification but experience of teaching adult learners is crucial for learner support. The third implication is that student satisfaction affects retention, and depends on the degree to which students’ needs and expectations are met (Jalynn & Styron, 2010; Liegler, 1997). Learners’ messages communicating their dissatisfaction with the programme and the decision to drop out indicate that quality academic inputs based on a robust instructional design may not guarantee retention without an equally robust support system. The fourth implication is that it may not be prudent to undermine the need for learner support on the basis of learner profile as mature learners including teachers may require it. The fifth implication is that incorporating alterations in learner support services without trying them out can offset high enrolment.


CPPDPT’s learners did not require tutoring. This testifies the courseware’s quality. However, they lacked the capacity for self-learning. Quality courseware with a sound instructional design thus did not compensate the weaknesses of the programme’s learner support. This study therefore reiterates that learner support is not only a necessity but a quality issue in distance education (Jung & Hong, 2014; Sánchez-Elvira & Simpson, 2018). The study thus reinforces the idea that support for non-academic issues is of overriding importance (Tait, 2000) but it has not received as much attention as academic support (Simpson, 2016). It also suggests that high enrolment programmes magnify institutional shortcomings. Hence, deviations in established practices need to be informed by theory and tried out before these are incorporated in such programmes.

Competing Interests

The author has no competing interests to declare.


  1. Arko-Achemfuor, A. (2017). Student support gaps in an open distance learning context. Issues in Educational Research, 27(4), 658–676. 

  2. Atkins, P. (2008). Transformation and integration through research and enquiry: A Centre for Excellence in Teaching and Learning perspective. In M. Weaver (Ed.), Transformative learning support models in higher education: Educating the whole student, (pp. 181–196). Facet Publishing. 

  3. Bowen, G. A. (2009). Document analysis as a qualitative research method. Qualitative Research Journal, 9(2), 27–40. DOI: 

  4. Charmaz, K. (2006). Constructing Grounded Theory: A Practical Guide through Qualitative Analysis. Sage Publications. 

  5. Chigbu, U. E. (2019). Visually Hypothesising in Scientific Paper Writing: Confirming and Refuting Qualitative Research Hypotheses Using Diagrams. Publications MDPI, 7(22). DOI: 

  6. Cho, J. Y., & Lee, E. H. (2014). Reducing Confusion about Grounded Theory and Qualitative Content Analysis: Similarities and Differences. The Qualitative Report, 19(32), 1–20. DOI: 

  7. Ding, Y., & Shen, H. (2019). Delving into learner autonomy in an EFL MOOC in China: a case study. Computer Assisted Language Learning, 1–23. DOI: 

  8. Education World. (2020, October 7). Kendriya Vidyalaya Schools, A template for government-funded education. 

  9. Foley, G., & Timonen, G. (2015). Using Grounded Theory Method to Capture and Analyze Health Care Experiences. Health Services Research, 50(4), 1195–1210. DOI: 

  10. Fotiadou, A., Angelaki, C., & Mavroidis, I. (2017). Learner Autonomy as a Factor of the Learning Process in Distance Education. European Journal of Open, Distance and E-Learning, 20(1), 96–111. DOI: 

  11. Glaser, B. G. (1998). Doing Grounded Theory: Issues and Discussions. Sociology Press. 

  12. Glaser, B. G., & Strauss, L. A. (1967). The Discovery of Grounded Theory – Strategies for Qualitative Research. Aldine Transaction. DOI: 

  13. Jalynn, R., & Styron, R. (2010). Student satisfaction and persistence: factors vital to student retention. Research in Higher Education Journal, 6. 

  14. Jansen, R. S., Van Leeuwen, A., Janssen, J., Conijn, R., & Kester, L. (2020). Supporting learners’ self-regulated learning in Massive Open Online Courses. Computers & Education, 146. DOI: 

  15. Jung, I., & Hong, S. (2014). An elaborated model of student support to allow for gender considerations in Asian distance education. The International Review of Research in Open and Distributed Learning, 15(2), 170–188. DOI: 

  16. Liegler, R. M. (1997). Predicting student satisfaction in baccalaureate nursing programs: Testing a causal model. Journal of Nursing Education, 36(8), 357–364. DOI: 

  17. Manjulika, S., Reddy, V., & Fulzele, T. U. (1996). Students opinion of counseling: The experience of Indira Gandhi National Open University. Indian Journal of Open Learning, 5(2), 19–29. 

  18. Moore, M. G. (2007). Theory of transactional distance. In M. G. Moore (Ed.), Handbook of distance education (pp. 89–103). Lawrence Erlbaum Associates. 

  19. O’Rourke, J. (2003). Tutoring in Open and Distance Learning: A Handbook for Tutors. The Commonwealth of Learning. 

  20. Pintrich, P. R., & Zusho, A. (2002). The development of academic self-regulation: The role of cognitive and motivational factors. In A. Wigfield & J. S. Eccle (Eds.), Development of achievement motivation (pp. 249–284). Academic Press. DOI: 

  21. Rekkedal, T. (1991). The personal tutor/counsellor in distance education. Paper presented at the ZIFF-Ringkolloquium, FernUniversität, Germany. 

  22. Rose, S., Spinks, N., & Canhoto, I. (2015). Management Research: Applying the Principles. Routledge. DOI: 

  23. Sánchez-Elvira Paniagua, A., & Simpson, O. (2018). Developing Student Support for Open and Distance Learning: The EMPOWER Project. Journal of Interactive Media in Education, 2018(1), 9. DOI: 

  24. Sewart, D. (1993). Open Learning: The journal of open and distance learning, 8(3), 3–12. DOI: 

  25. Simpson, O. (2008). Cost benefits of Student Retention Policies and Practices. In W. Bramble & S. Panda (Eds.), Economics of Distance and Online Learning (pp. 162–178). Routledge. DOI: 

  26. Simpson, O. (2013). Student retention in distance education: Are we failing our students? Open Learning: The Journal of Open, Distance and e-Learning, 28(2), 105–119. DOI: 

  27. Simpson, O. (2016). Student Support Services for Success in Open and Distance Learning. CEMCA EdTech Notes. 

  28. Tait, A. (2000). Planning student support for open and distance learning. Open Learning: The Journal of Open, Distance and e-Learning, 15(3), 287–299. DOI: 

  29. Tait, A. (2003). Reflections on student support in open and distance learning. International review of research in open and distance learning, 4(1). DOI: 

  30. Wedemeyer, C. A. (1971). Independent Study. In L. C. Deighton (Ed.), The encyclopaedia of education, 4. Macmillan. 

  31. Willig, C. (2013). Introducing Qualitative Research in Psychology (III Edition). Open University Press McGraw-Hill Education. 

  32. Zimmerman, B. J. (2002). Becoming a self-regulated learner: An overview. Theory into Practice, 41(2). 64–70. DOI: 

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