Analysis of Research Methods Adopted by Social Science Research Scholars during their Ph.D.: An Empirical Study

ABSTRACT
This study examines the research methods adopted by research scholars (Ph.D. – Doctor of Philosophy) in the social sciences and allied disciplines. This study was conducted in selected universities of India. A quantitative approach and descriptive research design were adopted for the present study. Data were collected from 59 research scholars through a structured and pre-tested questionnaire. The data were analysed using SPSS and MS Excel. The findings show that the majority (61%) of the research scholars adopted mixed-method research approaches in their research work. The descriptive research design was the most (45.8%) commonly adopted design by social science research scholars. A majority (64.4%) of scholars used self-developed data collection tools. Most studies (45.8%) were confined to one district. The majority (85%) of the scholars took 4 years or more to complete their Ph.D. and this is very high in the state universities. Limited use of an advanced data analysis software package by the social science researchers was also observed. The study found that the majority of the respondents expressed good or excellent satisfaction with their research work conducted in their Ph.D. There is a need for regular supervision, training in research methods, and access to research software for the research scholars. The findings provide useful insights for research scholars, guides, and universities. The study contributes to improving the quality of doctoral research in the social sciences.

Keywords: social science research, Ph.D. Research scholars & Higher education.  

Introduction 
Research is a continuous process to discover something new through a systematic approach. Research searches for facts and finds the answers and solutions to the questions that were previously unanswered. Research plays a pivotal role in advancing knowledge by systematically generating new insights and refining existing understanding. Research helps in developing theories and in testing and validating existing theoretical frameworks. Through scientific investigation and enquiry, research explains previously unexplained phenomena and expands human knowledge. Social science research is an interactive research and involves direct interaction with individuals, groups, and communities. Social science research treats society itself as the laboratory to understand and address complex social realities and social problems. In the words of Laldas (2004), social research may be described as a systematic and critical investigation of phenomena towards increasing the stream of knowledge. Research is defined as a careful consideration of study regarding a particular concern or a problem using scientific methods. It gives multiple solutions for a single problem, and there are many possible ways to do research for a single problem (AOFIRS, 2021).

Systematic research will be conducted by the researchers, scientists, academicians and research scholars. Many individuals who have an interest in doing research pursue higher education i.e. a Ph.D. degree in any university. They will select a research problem and conduct an investigation under the guidance of a research supervisor who is an associate professor or professor in the same stream (Basu & Maertens, 2012; Bennett, M., 2025). India offers wide-ranging opportunities for individuals who have an interest in doing research. There are well-established institutions, universities and funding opportunities available to pursue research. In India, four types of universities are available, those are, central universities, state universities, private universities and deemed to be universities. They structured research programmes at the Ph.D. level. The individual who is admitted to the research applies the systematic research approach, conduct an investigation and submits a thesis to the university. After thorough adjudication, the Ph.D. degree will be awarded to the individual. This study aimed to determine the type of research methodology adopted by the research scholars in universities during their Ph.D. 

Purpose of the Study
Doctoral research plays a crucial role in knowledge generation and academic advancement of an Individual. Many factors are associated with the doctoral research, like selection of research problem, research methodology, data collection and interpretation. If the guide and the scholar work together, the thesis will be completed in the stipulated time. But, it is noticed that there are delays in the completion of research, methodological rigour, and uneven research practices across institutions and disciplines. There are a few studies available on this problem. The present study provides the research practices followed by Ph.D. scholars.
 
The primary purpose of the study is to examine and understand the nature of research practices adopted by Ph.D. scholars in the Social Sciences and allied disciplines in Indian universities. The study seeks to analyse the socio-academic profile of Ph.D. researchers, the duration and completion patterns of doctoral studies, and the research methodologies employed, including the type of research, research approach, design, sampling techniques, data collection tools, data analysis software, and ethical practices. The study also aims to assess institutional variations in research practices and to understand scholars’ levels of satisfaction with their research work.

Objectives of the Study
1.	To examine the socio-economic, demographic and academic profile of Ph.D. scholars 
2.	To assess the methodological practices followed by Ph.D. scholars in their research work 
3.	To study the perceptions of the Ph.D. scholars on their research work 
4.	To provide appropriate suggestions to promote quality research in the academic setting

Methodology 
The present study was conducted in selected universities of India. A quantitative research approach was adopted, and a descriptive research design was used to systematically describe the existing conditions and viewpoints of the respondents. The study employed a purposive sampling method, through which 59 research scholars were selected as the sample for the study. The respondents have completed their Ph.Ds from different state, central, private and deemed to be universities of India. The researchers collected the responses through google form. Primary data were collected using a structured and pre-tested questionnaire to ensure clarity and reliability of the responses. The collected data were coded and analysed using Statistical Package for the Social Sciences (SPSS) and Microsoft Excel. The findings of the study were systematically presented in the form of tables for clear interpretation. In addition, the Chi-square test was applied to examine the association between selected variables included in the study.

Results and Discussions 
The data collected from the respondents through the questionnaire were systematically analysed and interpreted using appropriate statistical tools. This section discusses the key results derived from the data and interprets them in relation to the objectives of the study. The findings reflect the responses, perceptions, and practices of the respondents as captured during the data collection process. 

Table 1: Distribution of the respondents by their gender
Gender	Frequency	Percent	
Male	31	52.5	
Female	28	47.5	
Total	59	100.0	
The data in the above table show that there is a relatively balanced representation of both male and female respondents in this study. Out of the total 59 respondents, 31 (52.5%) were male, and 28 (47.5%) were female.

Table 2: Distribution of the respondents by their educational qualification
Education qualification	Frequency	Percent	
Ph.D. Pursuing	21	35.6	
Ph.D. Completed	38	64.4	
Total	59	100.0	
The data in the above table show that the majority (64.4%) of the respondents have already completed their doctoral studies. Among the 59 respondents, 38 reported having completed their Ph.D., while the remaining (35.6%)respondents were pursuing their doctoral degree at the time of the study.

Table 3: Distribution of the respondents by their type of Ph.D.
Type of Ph.D. 	Frequency	Percent	
Full Time	28	47.5	
Part Time	29	49.2	
Converted from Full-time to Part-time	2	3.4	
Total	59	100.0	
The data in the above table shows that nearly equal representation of full-time and part-time scholars. Among the 59 respondents, 28 (47.5%) were pursuing their Ph.D. on a full-time basis, while 29 (49.2%) were enrolled as part-time scholars. Additionally, a small proportion, 2 respondents (3.4%), had transferred from full-time to part-time mode.

Table 4: Distribution of the respondents by their stream of study
Stream of Study	Frequency	Percent	
Social Sciences	39	66.1	
Humanities	10	16.9	
Commerce and Management	10	16.9	
Total	59	100.0	
The data in the above table present that out of the 59 respondents, 39 (66.1%) were from Social Science disciplines, while 10 respondents each (16.9% respectively) represented the Humanities and Commerce & Management streams. 

Table 5: Distribution of the respondents by their type of university
State Central University	Frequency	Percent	
State University	40	67.8	
Central University	10	16.9	
Private University	8	13.6	
Deemed to be University	1	1.7	
Total	59	100.0	
The data in the above table show that the majority (67.8%) of the respondents are affiliated with State Universities. Central Universities accounted for 16.9%, while Private Universities contributed 13.6%. A very small proportion, 1.7%, belonged to a Deemed-to-be University. 

Table 6: Distribution of the respondents by their caste
Caste	Frequency	Percent	
OC	18	30.5	
BC	19	32.2	
SC	14	23.7	
ST	8	13.6	
Total	59	100.0	
The data in the above table reveals that the largest proportion (32.2%) of the respondents belonged to the Backward Classes (BC), followed by the Open Category (OC) 30.5%. Scheduled Castes (SC) accounted for 23.7%, while Scheduled Tribes (ST) represented 13.6%. 

Table 7: Distribution of the respondents by their religion
Religion	Frequency	Percent	
Hindu	42	71.2	
Christian	15	25.4	
Other Buddhist	2	3.4	
Total	59	100.0	
The data in the above table shows that the majority (71.2%) of the respondents are Hindus, while 25.4% identified as Christians. A small proportion, 3.4%, belonged to other religions such as Buddhism. 

Table 8: Distribution of the respondents by their born and brought up area
Area	Frequency	Percent	
Urban Area	29	49.2	
Rural Area	28	47.5	
Tribal Area	2	3.4	
Total	59	100.0	
The data in the above table show that the largest percentage (49.2%) of the respondents reported that they were born and raised in urban areas, while 47.5% of the respondents stated that they were from rural areas. Additionally, a small proportion of 2 respondents (3.4%) belonged to tribal areas. 

Table 9: Distribution of the respondents by their family income
Family Income	Frequency	Percent	
Below Poverty Line	15	25.4	
Above Poverty Line	44	74.6	
Total	59	100.0	
The data in the above table show that the majority (74.6%) of the respondents represented from the above poverty line families, while 15 respondents (25.4%) belonged to families below the poverty line. In indicates that getting higher education is associated with the economic development of the family, but a few respondents came with their hard work and reached their destination. 

Table 10: Distribution of the respondents by their family members in the teaching profession at universities
Family members in the teaching profession at any university	Frequency	Percent	
Yes	9	15.3	
No	50	84.7	
Total	59	100.0	
The data in the above table show that the majority (84.7%) of the respondents do not have such familial academic backgrounds, while (15.3%) reported having a parent or sibling employed as a university teacher. The finding indicated that the scholars admitted to higher education with their interests without family university backgrounds. 

Table 11: Distribution of the respondents by who motivated them to apply for Ph.D.
Motivated by	Frequency	Percent	
Self	37	62.7	
Parents	9	15.3	
Teachers	8	13.6	
Friends	5	8.5	
Total	59	100.0	
The data in the above table show that the majority (62.7%) of the respondents reported that they were self-motivated to join the Ph.D. programme, while 15.3% of the respondents stated that they were motivated by their parents, 13.6% encouraged by their teachers, and 8.5% influenced by friends. 

Table 12: Distribution of the respondents by their year of Ph.D. award
Year of Awarded	Frequency	Percent	
2010-2014	7	11.9	
2015-2019	14	23.7	
2019-2024	19	32.2	
Under Process	19	32.2	
Total	59	100.0	
The distribution of respondents by their year of Ph.D. award shows a varied spread across different time periods, with a significant proportion still in the process of completing their degree. Out of the 59 respondents, 7 (11.9%) were awarded their Ph.D. between 2010 and 2014, while 14 respondents (23.7%) received their degree between 2015 and 2019. The largest groups were those awarded between 2019 and 2024 and those whose Ph.D. is still in process, each comprising 19 respondents (32.2%). 

Table 13: Distribution of the respondents by years spent to complete their Ph.D. (excluding adjudication)
Years spent	Frequency	Percent	
3 Years	9	15.3	
4 Years	15	25.4	
5 Years	18	30.5	
6 Years	8	13.6	
7 Years	9	15.3	
Total	59	100.0	
The data in the above table shows that the largest proportion (30.5%) of the respondents reported that they have completed their Ph.D. in 5 years, followed by 25.4% of the respondents who completed it in 4 years. A smaller portion (15.3%) has completed their Ph.D. work in 3 years. Additionally, (13.6%) required 6 years, 15.3% required 7 years to finish their thesis writing. As per the UGC, the given time to complete a full-time Ph.D. is 3 years, and a part-time Ph.D. is 4 years. As per the data in the above table the majority of the respondents are late in the completion of their Ph.D. work. This finding is inline with the findings of Creasman (2021); Ogunleye & Adeyemi (2024) who reported that the average time to complete the Ph.D. is 4-5 years. 
Table 14: (Cross-table) Distribution of the respondents by their university and years spent to complete their Ph.D. (Excluding Adjudication)
State Central University	Years spent on the completion of Ph.D. 	Total 	
	3 Years	4 Years	5 Years	6 Years	7 Years		
State University	5	7	13	6	9	40	
Central University	0	5	4	1	0	10	
Private University	4	3	0	1	0	8	
Deemed to be University	0	0	1	0	0	1	
Total	9	15	18	8	9	59	
Pearson Chi-Square: 21.228a	Df: 12	Significance: 0.047	
The data in the above cross table shows that the majority of the respondents of State Universities have completed their Ph.D. in 5 to 7 years, while the respondents in the central universities completed their Ph.Ds. within 4 to 5 years. Private Universities exhibit comparatively shorter completion durations, mostly within 3 to 4 years, while the Deemed University representation is minimal. The Pearson Chi-Square value (χ² = 21.228, df = 12) is statistically significant at the 5 per cent level (p = 0.047). The table indicates that the scholars of central universities, private universities and deemed to be universities are completing their Ph.D. earlier than those of state universities. 
Table 15: Distribution of the respondents by adjudication time in months
Adjudication time in months	Frequency	Percent	
Less than 6 months	14	23.7	
6 Months to one year	22	37.3	
12 months to 18 Months	10	16.9	
18 Months to 24 Months	4	6.8	
More than 24 Months	9	15.3	
Total	59	100.0	
The data in the above table shows that the largest portion (37.3%) of the respondents reported that their adjudication process took 6months to one year, while 23.7% of the respondents stated that their adjudication process was completed in less than 6 months. It is found that 16.9% of the respondents stated 12 to 18 months, and 15.3% of the respondents stated that it took more than 24 months to complete their adjudication process. The study found that while most awards were granted within a year, a notable proportion faced prolonged adjudication periods.

Table 16: Distribution of the respondents by their type of research study
Type of Research 	Frequency	Percent	
Empirical	37	62.7	
Theoretical	22	37.3	
Total	59	100.0	
The data in the above table show that the majority (62.7%) of the respondents reported that they have done empirical research work, while 37.3% of the respondents stated that they have done theoretical research work in their Ph.D. 

Table 17: Distribution of the respondents by their research approach
Research Approach	Frequency	Percent	
Quantitative	12	20.3	
Qualitative	11	18.6	
Both/ Integrated / Mixed	36	61.0	
Total	59	100.0	
The data in the above table show that the majority (61.0%) of the respondents adopted a mixed-methods research approach, while 12 (20.3%) used a quantitative approach and 11 (18.6%) followed a qualitative approach in their Ph.D. research work. This indicates that most scholars preferred combining qualitative and quantitative techniques to strengthen the depth and rigour of their research.

Table 18: (Cross-table) Distribution of the respondents by their stream of the study and adopted research approach
Stream of Study	Research Approach	Total	
	Quantitative	Qualitative	Both/ Integrated / Mixed		
Social Sciences	6	5	28	39	
Humanities	2	5	3	10	
Commerce and Management	4	1	5	10	
Total	12	11	36	59	
Pearson Chi-Square: 11.274a	Df: 4	Significance: 0.024	
The data in the above cross-tabulation reveal clear differences in the choice of research approach across streams of study. Social Sciences predominantly employ mixed or integrated research approaches, while Humanities show a relatively balanced use of quantitative and qualitative methods. Commerce and Management scholars also display a preference for mixed methods, though quantitative approaches remain notable. The Pearson Chi-Square test indicates a statistically significant association between stream of study and the research approach (χ² = 11.274, df = 4, p = 0.024). This finding suggests that the selection of research approach is significantly influenced by the academic stream.

Table 19: Distribution of the respondents by their adopted research design
Research Design	Frequency	Percent	
Experimental Research Design	11	18.6	
Exploratory Research Design	11	18.6	
Descriptive Research Design	27	45.8	
Historical Research Design	2	3.4	
Explanatory Research Design	7	11.9	
Ex post facto research design	1	1.7	
Total	59	100.0	
The data in the above table show that the majority (45.8%) of the respondents employed a descriptive research design. Experimental and exploratory designs were equally represented, with each (18.6%). Additionally, (11.9%) used explanatory research, (3.4%) applied historical research, and (1.7%) adopted an ex post facto design. The study found that the majority of the respondents have used a descriptive research design in their Ph.D. research work. 

Table 20: Distribution of the respondents by number of objectives for their study
Number of objectives 	Frequency	Percent	
5-6	41	69.5	
7-8	9	15.3	
9-10	4	6.8	
Not Applicable	3	5.1	
More than 11	1	1.7	
Other	1	1.7	
Total	59	100.0	
The data in the above table show that the majority (69.5%) of the respondents had 5–6 objectives in their research study. Smaller proportions reported 7–8 objectives (15.3%), 9–10 objectives (6.8%), while 5.1% indicated it is not “Not Applicable,” and (1.7% each) reported that they have more than 11 objectives in their research study. This suggests that the typical Ph.D. study tends to be structured around a concise set of research objectives.

Table 21: Distribution of the respondents by writing hypothesis
Write Hypothesis	Frequency	Percent	
Yes	43	72.9	
No	16	27.1	
Total	59	100.0	
The data in the above table show that the majority (72.9%) of the respondents reported formulating one or more hypotheses in their research study, while (27.1%) did not formulate a hypothesis in their research study. This indicates that hypothesis formulation is a common practice in doctoral research, reflecting a structured and analytical approach to investigating research problems.
Table 22: Written research questions in their research study
Written research questions 	Frequency	Percent	
Yes	49	83.1	
No	10	16.9	
Total	59	100.0	
The data in the above table show that the majority (83.1%) of the respondents reported that they formulated research questions in their research work, while 16.9% did not formulate a research questions. It is found that the majority of the respondents formulated 5-6 questions in their research study
Table 23: Distribution of the respondents by their study area
Study Area	Frequency	Percent	
One District	27	45.8	
2-4 Districts	18	30.5	
Entire State	9	15.3	
More than one state	1	1.7	
Not Applicable	4	6.8	
Total	59	100.0	
The data in the above table show that a large percentage (45.8%) of the respondents conducted their study in one district, while 30.5% of the respondents conducted their study in 2-4 districts. It is found that 15.3% of the respondents conducted their study in the entire state, and 1.7% of the respondents conducted their study in more than one state.

Table 24: Distribution of the respondents by writing population details in the research study
Written population details	Frequency	Percent	
Yes	42	71.2	
No	8	13.6	
Not Applicable	9	15.3	
Total	59	100.0	
The data in the above table show that the majority (71.2%) of the respondents reported mentioning population details in their research studies; however, 13.6% of the respondents did not include population details. Additionally, for 15.3% of the respondents, the item was not applicable, possibly due to the nature or design of their studies. 

Table 25: Distribution of the respondents by applying the sample frame
Applied sampling frame 	Frequency	Percent	
Yes	47	79.7	
No	8	13.6	
Not Applicable	4	6.8	
Total	59	100.0	
The data in the above table show that a large majority of the respondents (79.7%) reported that they applied a sample frame technique in their studies. In contrast, 13.6% of the respondents did not use a sample frame. 

Table 26: Distribution of the respondents by number of sampling techniques applied
Number of sampling techniques 	Frequency	Percent	
1	24	40.7	
2	19	32.2	
3	7	11.9	
Not Applicable	9	15.3	
Total	59	100.0	
The data in the above table shows that the largest proportion of respondents (40.7%) employed a single sampling method in their studies, while (32.2%), of the respondents applied two sampling techniques in their studies. Only 11.9% of the respondents reported that they have used three sampling techniques in their studies. 

Table 27: Distribution of the respondents by their sampling techniques
Sampling techniques applied 	Frequency	Percent	
Simple Random Sampling	26	44.1	
Systematic Random Sampling	5	8.5	
Stratified Random Sampling	8	13.6	
Cluster Sampling	2	3.4	
Multistage Sampling	2	3.4	
Quota Sampling	1	1.7	
Purposive Sampling	7	11.9	
Not Applicable	8	13.6	
Total	59	100.0	
The data in the above table shows that a large portion (44.1%) of the respondents applied the Simple Random Sampling technique, while 13.6% of the respondents applied the Stratified Random Sampling technique (13.6%) and Purposive Sampling technique (11.9%). Systematic Random Sampling accounted for 8.5% of the responses, while Cluster and Multistage Sampling were used by a smaller proportion of respondents (3.4% each). Quota Sampling was the least utilised by (1.7%) of the respondents. 

Table 28: Distribution of the respondents by number of data collection tools used
Total data collection tools 	Frequency	Percent	
1	10	16.9	
2	23	39.0	
3	19	32.2	
Not Applicable	7	11.9	
Total	59	100.0	
The data in the above table show that the largest proportion of respondents (39.0%) employed two data collection tools in their studies, while a substantial portion of respondents used three tools (32.2%). In contrast, only 16.9% relied on a single data collection tool. 

Table 29: Distribution of the respondents by type of data collection tools
Type of Data Collection Tools 	Frequency	Percent	
Interview Schedule	16	27.1	
Questionnaire	34	57.6	
Observation	1	1.7	
Not Applicable	8	13.6	
Total	59	100.0	
The data in the above table show that the majority (57.6%) of the respondents employed the questionnaire method, while Interview schedules were used by 27.1% of the respondents. The observation method was minimally utilised (1.7%) in their research studies. 

Table 30: Distribution of the respondents by type of data collection tool
Type of data collection tool 	Frequency	Percent	
Standard tool designed by others	21	35.6	
Self-made tool	38	64.4	
Total	59	100.0	
The data in the table shows that the majority of the respondents (64.4%) used self-made data collection tools in their studies. In contrast, 35.6% of the respondents employed standard tools designed by others. 

Table 31: Distribution of the respondents by number of data collection tools
Total tools used	Frequency	Percent	
One tool for respondents	22	37.3	
Two different tools for two different respondents	16	27.1	
Three different tools for three different respondents	13	22.0	
Not Applicable	8	13.6	
Total	59	100.0	
The data in the above table indicates that the largest proportion of respondents (37.3%) used a single tool for all respondents, while a considerable number employed two different tools for two different categories of respondents (27.1%). Additionally, 22.0% of the respondents reported using three different tools for three distinct respondent groups, indicating the use of more complex and segmented data collection strategies.

Table 32: Distribution of the respondents by testing validity and reliability
Testing validity and reliability 	Frequency	Percent	
Yes	40	67.8	
No	8	13.6	
Not Applicable	11	18.6	
Total	59	100.0	

The data in the above table reveals that the majority of the respondents (67.8%) reported testing the validity and reliability of their research tools, indicating adherence to methodological rigour. However, 13.6% of the respondents did not conduct validity and reliability testing, which may affect the credibility of their findings.
 
Table 33: Distribution of the respondents by number of software packages used for data analysis
Total software packages used 	Frequency	Percent	
1	29	49.2	
2	13	22.0	
3	2	3.4	
Not Applicable	15	25.4	
Total	59	100.0	
The data in the table indicates that nearly half of the respondents (49.2%) used a single data analysis software package in their studies, while a smaller proportion employed two software packages (22.0%). Only 3.4% of the respondents reported using three different data analysis software packages in their studies. 

Table 34: (Cross-table) Distribution of the respondents by their university and the number of software packages used to analyse the data
Type of University 	Total software packages used 	Total 	
	1	2	3	Not Applicable		
State University	23	9	0	8	40	
Central University	3	3	1	3	10	
Private University	3	1	0	4	8	
Deemed to be University	0	0	1	0	1	
Total	29	13	2	15	59	
Pearson Chi-Square: 36.018a	Df: 9	Significance: 0.000	
The cross-tabulation shows notable differences in the use of data analysis software across types of universities. Scholars from State Universities predominantly used one or two software packages. Scholars from Central Universities used two or three software packages for analysing their research data. The Pearson Chi-Square test reveals a highly significant association between type of the university and the number of data analysis software used (χ² = 36.018, df = 9, p < 0.001). This indicates that access to and utilisation of data analysis software are strongly influenced by the institutional type.

Table 35: Distribution of the respondents by collection of consent forms from the respondents
Collected consent forms 	Frequency	Percent	
Yes	44	74.6	
No	4	6.8	
Not Applicable	11	18.6	
Total	59	100.0	
The data in the above table shows that a substantial majority of the respondents (74.6%) reported they have collected consent forms from participants, while a small proportion (6.8%) did not obtain consent forms. 

Table 36: Distribution of the respondents by translation of the data collection tool into the local language
Translated questionnaire 	Frequency	Percent	
Yes	30	50.8	
No	16	27.1	
Not Applicable	13	22.0	
Total	59	100.0	
The data in the above table indicates that just over half of the respondents (50.8%) translated their questionnaires into the local language, however, 27.1% did not translate the questionnaire

Table 37: Distribution of the respondents by total chapters in their thesis
Total chapters 	Frequency	Percent	
5	24	40.7	
6	21	35.6	
7	6	10.2	
8	8	13.6	
Total	59	100.0	
The data in the table show that the largest proportion (40.7%) of the respondents stated that their thesis has 5 chapters, while 35.6% of the respondents stated that their thesis has 6 chapters. A smaller share of respondents reported having seven chapters (10.2%), while 13.6% structured their studies into eight chapters. The study is inline with the study of Mauch & Park (2003); Galvan & Galvan (2017), who reported that the majority of the researchers follow the 5-chapter model in their research. 

Table 38: Distribution of the respondents by total pages in thesis
Total pages 	Frequency	Percent	
150-200	8	13.6	
200-250	15	25.4	
250-300	21	35.6	
300-350	8	13.6	
350-400	7	11.9	
Total	59	100.0	
The data in the table show that the highest proportion of respondents (35.6%) stated that their thesis fell within the 250–300 pages, followed by 25.4% of the respondents stated that their theses ranged between 200–250 pages. Smaller proportions of the respondents were reported in the 150–200 pages and 300–350 page ranges (13.6% each), while 11.9% extended to 350–400 pages. The study is inline with the study of Justus Randolph et al. 2023 and the report of the University of Auckland who reported that the average page numbers of theses are 200 pages. 

Table 39: Distribution of the respondents by total pages for the research methodology chapter
Number of Pages of the Research Methodology Chapter	Frequency	Percent	
16-20	24	40.7	
21-25	10	16.9	
26-30	8	13.6	
31-35	4	6.8	
36-40	7	11.9	
Not Applicable	6	10.2	
Total	59	100.0	
The data in the table show that the largest proportion of the respondents (40.7%) allocated 16–20 pages to the research methodology chapter. Smaller proportions reported 21–25 pages (16.9%) and 26–30 pages (13.6%). Only a limited number of studies extended the methodology chapter beyond 30 pages. 

Table 40: Distribution of the respondents by total pages for data collection and interpretation chapter
Total pages of data analysis chapter	Frequency	Percent	
Below 100 pages	23	39.0	
101-125 pages	9	15.3	
126-150 pages	6	10.2	
151-175 pages	6	10.2	
176-200 pages	5	8.5	
More than 201 pages	3	5.1	
Not Applicable	7	11.9	
Total	59	100.0	
The data in the above table illustrates that the largest proportion of respondents (39.0%) allocated fewer than 100 pages for data analysis and interpretation chapter. Smaller proportions of respondents reported 101–125 pages (15.3%) and 126–150 pages (10.2%), and only a few respondents exceeded 175 pages (13.6% combined) allocated for data analysis and interpretation chapter. 

Table 41: Distribution of the respondents by their satisfaction with their research work
Satisfaction on research work	Frequency	Percent	
Excellent	28	47.5	
Good	25	42.4	
Average	4	6.8	
Not satisfied	2	3.4	
Total	59	100.0	
The data in the above table presents respondents’ self-assessment of their Ph.D. work, showing that nearly half (47.5%) rated their research work as excellent, reflecting high confidence in the quality and rigour of their study. A substantial proportion (42.4%) considered their work good, indicating overall satisfaction with their research outcomes. Only a small number of respondents rated their work as average (6.8%) or expressed dissatisfaction (3.4%). The study is inline with the study of nature (2025), and Yang & Cai (2022), who reported that a large majority of Ph.D. candidates report high satisfaction with their research experience and outcomes. It may be a reason that they spent more time on their work. 

1.	The study found that the majority of the scholars adopted mixed-method approaches and descriptive research designs and self-developed tools. Scholars should be encouraged to adopt advanced designs where appropriate and ensure proper validation and reliability testing of tools.
2.	The study found that the majority of the research scholars completed their research between 4-5 years or more. It is beyond UGC-prescribed timelines. Scholars should prepare realistic research timelines, periodically review progress, and adhere to structured work plans to avoid prolonged durations.
3.	Since most studies were confined to one district, scholars should be encouraged to widen their study area where feasible, to improve generalizability and policy relevance.
4.	Limited use of the data analysis software suggests a need for greater proficiency in statistical and qualitative analysis tools. Scholars should actively seek training in advanced software and analytical techniques to strengthen data interpretation.
5.	Scholars must consistently follow ethical research practices, including informed consent, confidentiality, and cultural sensitivity, such as translating tools into local languages when required.
6.	Research guides should hold regular review meetings to monitor progress, address methodological gaps, and prevent delays in completion.
7.	Research supervisors should motivate scholars to move beyond conventional descriptive studies and explore experimental, explanatory, and interdisciplinary approaches where suitable.
8.	The study found that the majority of the scholars do not come from academic family backgrounds, guides play a crucial role in academic socialisation, confidence building, and professional development.
9.	Universities, especially State Universities, should provide licensed research software, digital libraries, and methodological support systems to increase the technological accessibility to the research scholars.
10.	The majority of the research scholars stated that their adjudication process took nearly one year. The universities should establish a transparent adjudication process to reduce delays in Ph.D. completion and evaluation.
11.	Regular workshops on research methodology, advanced statistics, qualitative analysis, ethics, and academic writing should be organised.

Conclusion 

The study concludes that successful research among scholars is strongly influenced by clarity of research problems, well-defined objectives, sound and innovative methodology, and adherence to research ethics. Continuous guidance from experienced supervisors, maintaining a positive researcher–guide relationship, and engaging in discussions with senior professors significantly enhance research quality and timely completion. Scholars must demonstrate self-motivation, dedication, passion, and continuity of work while following systematic and organised research plans from the initial stage. Selecting novel and socially relevant topics, identifying research gaps, avoiding plagiarism, and acquiring updated technical and methodological knowledge are crucial for value-added research outcomes. Intensive literature review, thorough framing of objectives, effective use of research tools, and strict adherence to timelines further strengthen research productivity. 

COMPETING INTERESTS DISCLAIMER:
Authors have declared that they have no known competing financial interests OR non-financial interests OR personal relationships that could have appeared to influence the work reported in this paper.

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