Design And Implementation of a Mentoring Program for Postgraduate Students: A Case Study of Qualitative Analysis Mentoring

Design And Implementation of a Mentoring Program for Postgraduate Students: A Case Study of Qualitative Analysis Mentoring

Ani Munirah Mohamad^1*, Eshaby Mustafa², ‘Ain Husna Mohd Arshad³, Nur Aili Hanim Hanafiah⁴, Nurhazlina Mohd Ariffin⁵, Syarifah Rohaniah Syed Mahmood⁶

^1,2,3,4,5Universiti Utara Malaysia, Malaysia.

⁶International Islamic University Malaysia

DOI: https://dx.doi.org/10.47772/IJRISS.2025.903SEDU0206

Received: 03 April 2025; Accepted: 07 April 2025; Published: 12 May 2025

ABSTRACT

A well-designed mentoring program is found to be highly facilitative for postgraduate students. The process of supervision is normally related to the main contents of research. Therefore, a mentoring program may provide an opportunity for the postgraduate students to develop skills that are normally not acquired from supervision. This paper discusses the twelve-steps process in designing and implementing a mentoring program for postgraduate students. Case study design was employed in this research, focusing on a qualitative analysis mentoring program conducted at one of the higher learning institutions in Malaysia, with specific reference to computer-assisted qualitative data analysis software known as ATLAS.ti. The discussion includes stages of mentoring on the use of ATLAS.ti for qualitative data analysis process. It is found that the mentoring on the use of computer-assisted software, particularly ATLAS.ti, has been able to facilitate students’ understanding on the process of qualitative data analysis. Future research could be conducted to larger scale population and the mentoring of different software so as to generalize the findings of the study. Hopefully this paper will become a focal reference for similar mentoring programs for other areas and topics in the future.

Keywords: Designing, implementing, mentoring, qualitative analysis, CAQDAS, ATLAS.ti

INTRODUCTION

Mentoring is very important in the teaching and learning process, especially in higher education. [1] explained coaching and mentoring could inspire people or learners “to want to” if provided skillfully. Skillful coaching and mentoring also can inspire learners by enhancing engagement [2]-[3], motivation [4]-[5] and autonomy [6]. These practices support skill acquisition, well-being, and professional development, making them valuable tools in educational and professional settings. Mentoring is the most important thing to be considered in preparing university students, especially at the postgraduate level to maintain, sustain, and endure with their study and research. Similarly, [7] found that mentoring can be a change agent but will require readiness from mentors to effectively guide mentees in a specific subject area.

Mentoring postgraduate students in their analysis studies presents a range of challenges that can significantly impact the students’ academic and personal development [8]. These challenges stem from various factors, including inadequate mentorship structures, cultural and language barriers, and the lack of effective communication between mentors and mentees [9].

Based on the abovementioned problems, this paper aims to deliberate on the process of designing and implementing a mentoring program for postgraduate students, focusing on one of the skillsets of postgraduate studies, namely qualitative analysis. A qualitative analysis skill was chosen to illustrate the design and implementation of a mentoring program. It follows that data analysis is one of the important skills for postgraduate students undertaking a postgraduate program. This is where postgraduate students present their analytical skills in processing the data that has been gathered in fieldwork. Accordingly, [10] suggested that there is a need to have a sophisticated tool in qualitative analysis to facilitate students to interpret the data. Therefore, the method of computer-assisted qualitative data analysis [11] has been created to help postgraduate students accomplish their task in a more facilitative way.

LITERATURE REVIEW

This section provides an account of the literature review on the key concepts engaged in this study, namely mentoring program, problems in mentoring postgraduate students, qualitative analysis and strategies to overcome the problems.

Mentoring Program

Mentoring is a multi-dimensional concept that is critically important to both general and postgraduate education contexts. It is a developmental relationship in which one person (the mentor) empowers another (the mentee) by sharing their knowledge, skills and experience. It is also known as an interaction, in which an experienced person (mentor) can help a less experienced person (mentee) through guidance, support, and feedback [12]. Both sides learn and grow further in this relationship. Mentorship matters in the field of postgraduate education as it promotes the academic, professional, and personal development of students, which prepares them for future career obstacles. The subsequent sections outline some of the key elements of mentoring, particularly in relation to postgraduate students.

Mentoring is a two-way street; both the mentor and mentee win. The mentor feels fulfilled and possibly more productive, and the mentee obtains desirable new expertise and insight [13]-[14]. Mentorship is not limited to formal education, as it can play a role in many other areas of professional and personal development. It is a career-long process that creates a culture of lifelong learning [14]. Mentoring is employed in several fields, which include but is not limited to education and business, as well as medical training, and it nurtures strategic partnerships, creative activity, and the growth of professional skills [15].

Within the context of postgraduate students, students are influenced by mentoring, which contributes to their employment because their academic competence, personal quality competence, and employment capital help them in employment. As a result, this increased employment-related psychological well-being [16]. Mentoring not only helps postgraduate students become independent and build experience as they transition into leadership themselves, but it also prepares them for their careers by helping them obtain professional characteristics through effective mentorship. It also includes mentoring others, like undergraduate students, which improves their leadership skills [17]. Mentoring offers support in overcoming common academic challenges, like rejection and publish-or-perish, by building resilience and providing career guidance [18]. It has also been made possible with the introduction of online education, facilitating students to receive proper virtual mentoring. Mentoring receives its power from openness to change, feedback, and accountability [17].

Problems In Mentoring Postgraduate Students

Students without sufficient mentoring may experience feelings of isolation, neglect, and stress, which can compromise their academic and social well-being. University structures that do not adequately facilitate mentoring relationships cause this issue to be compounded, and students are often able to “fall through the cracks” without the support they need to guide them to their next steps [8] In some areas, particularly Africa, subpar infrastructure and inadequate remuneration create an obstacle to the effective mentoring of graduate students, underscoring the importance of institutional reform and resource pooling [19].

We acknowledge that the academic writing and research process can be complex, especially for international students, who often have to deal with cultural and language-related differences. These students were already struggling, and the move to remote supervision during the pandemic has made it harder still for them to get the help they need [9]. Mentor-mentee communication is critical, but many students report the absence of clear guidance and support from supervisors. In some cases, several factors, including the graduate students’ level of preparedness and emotional well-being may lead to misunderstandings and unmet expectations which can adversely impact their research journey [20]. The faculty selects and trains graduate students in the mentoring relationship, which can be a complex professional dilemma [21].

Indeed, supervisors rarely receive specific training (for example, in mentoring students on writing, networking, or career matters), nor are they held accountable if they do not do so. Lack of support can deprive students of the requisite tools to help them excel in postgraduate studies [20]. Supervisors in certain cases are overloaded with their own workloads, which restricts their ability to give the required support and guidance to the mentee.

Qualitative Analysis Skillsets Among Postgraduate Students

Qualitative research methods are increasingly acknowledged and taught, yet there are also significant gaps in students’ understanding and application of them. The situation is exacerbated by different levels of curriculum coverage and individual talents. Here are the different aspects of postgraduate students’ qualitative analysis skillsets. Postgraduate programs, particularly in psychology, social work, and other fields, often lack dedicated courses around qualitative research or are integrated within research methods courses that focus heavily on quantitative research [23]. For example, in India the amount of content on qualitative research is limited by the lack of a separate course in most universities, which has an implication for students [23].

While the number of institutions offering qualitative research courses has increased considerably, the breadth and depth of these courses vary widely from institution to institution, and as a result, so do the skillsets of the students [24]-[25]. Thus, for postgraduate students, qualitative research methods are considered much more difficult compared to quantitative methods in general, especially in considering how to determine sub-research problems and create a conceptual framework [26]. Students who belong to an underrepresented group experience additional hurdles in the form of impostor syndrome and stereotype threat that can inhibit confidence and persistence when developing qualitative research skills [27].

Despite this, some students report that qualitative research works for them in a meaningful way, aligning with their epistemological and philosophical stances [28]. Students’ past research work and individual learning styles sometimes constrain practical use of qualitative research methods Some students use ethnographic studies and other qualitative methods to enhance their skillset, but access to resources and experience can be inconsistent, which can impact the quality of their education [27]. Note that students can use their personal competence to withstand the perils of qualitative research in these cases [26].

Cultural and institutional contexts (especially in contexts of disciplines and regions: some are more supportive of qualitative, some less [24]-[25] influence how qualitative research methods are taught and implemented. In fields where qualitative research is showing more international growth, such as in education, health and social services, more training and support is needed to help postgraduate-level students develop systematic approaches to it [24]-[25].

Strategies to Overcome the Problems

Postgraduate students often face challenges in developing qualitative analysis skillsets due to the complexity of qualitative research methods and the lack of adequate guidance. Therefore, effective mentoring and guidance can play a crucial role in overcoming these challenges by providing emotional support, practical skills, and academic advancement. Various forms of mentorship, including peer mentoring, formal mentoring relationships, and online tools, can be employed to support postgraduate students in qualitative analysis. These approaches can enhance students’ confidence, motivation, and ability to conduct qualitative research successfully.

Peer mentorship programs, such as the buddy system piloted in New Zealand, have shown significant benefits for postgraduate students. These programs involve forming groups led by doctoral students to support pre-doctoral students, fostering improved social resources, expanded skillsets, and increased confidence and motivation. Participants reported improvement in well-being, academic attainment, and resilience, suggesting that peer mentorship can be a cost-effective way to support postgraduate students in qualitative analysis [29]. Peer mentoring experiences can provide guidance and support, helping mentees learn from those who have previously navigated similar paths. This relationship can be consistent with advisor-student dynamics, helping and learning opportunities [30].

Establishing formal mentoring relationships is crucial for novice researchers in qualitative research. Mentoring involves caring, role-modeling, emotional support, and long-term development, which are essential for successfully completing qualitative inquiries. Institutions are encouraged to support mentors and address failed mentoring liaisons to ensure effective mentorship [31]. Supervisors play a vital role in postgraduate students’ scholarly development, providing career mentoring, networking, and emotional support. However, students often desire more hands-on help with methodology and writing, indicating a need for enhanced supervisory support [20].

A study conducted by [32] proposed another initiative to ensure an effective learning process, which is by establishing mentoring centers for postgraduate education. The model for developing mentorship centers for postgraduate education is founded on the concept of cooperation, dialogue, and partnership, considering the need to maximize the unique aspects of individual students while maintaining collective interaction between members of this mentoring center.

With these strategies, postgraduate students will have more valuable and meaningful learning experience throughout the process of research. [12] shows that mentoring programs in universities not only increase the level of compliance of students who are struggling with the challenges but also help to boost the number of graduates. In addition to this, mentoring can also promote the research product of students.

METHODOLOGY

For the purpose of this paper, case study was chosen as the approach for illustrating the steps in the design and implementation of a mentoring program. The chosen program was particularly for the mentoring of qualitative analysis skills using the computer-aided qualitative data analysis software ATLAS.ti version 24 for a group of postgraduate students at one of the higher learning institutions in Malaysia.

Process For Designing And Implementing A Mentoring Program

Based on the above aims and objectives of enhancing the qualitative analysis skills among postgraduate students, a mentoring program was designed following twelve steps which can be summarized in the following Figure 1. This section deliberates on each of the twelve-steps process for the design and implementation of a mentoring program for postgraduate students.

Figure 1. Twelve-steps process for designing and implementing a mentoring program

First step – Defining the community

The first step is defining the community that the mentoring program serves, and a group of postgraduate students and researchers have been identified to become the targeted community for the mentoring program. The reason for this choice is primarily because there is a growing number of postgraduate students in the chosen institution particularly, and nationwide generally. Accordingly, there is a growing need for mentoring on research skills and methodologies among these postgraduate students.

Second step – Identifying the mentors

The second step is to identify the types of individuals, and the criteria used to recruit the mentors. In this case study, the appropriate person to become the mentor in this program must be a person with adequate knowledge and skills to teach and mentor students on qualitative research and analysis with ATLAS.ti [32]. Accordingly, the mentor for this program was chosen based on the grounds that she engaged in full qualitative research during her PhD studies and had used the ATLAS.ti software extensively for her research projects. In addition, she is officially certified to teach ATLAS.ti by ATLAS.ti Scientific Software Development GmbH, based in Germany.

Third step – Determining the type of mentoring

The third step is to determine the type of mentoring the program will offer – and a program called: “Qualitative data analysis with ATLAS.ti 8” was planned. The reason for this choice is that the chosen institution is a management university and dominated by quantitative researchers. Albeit having a growing supporter of qualitative researchers in the institution, the learning expectancy of qualitative research skills and analysis strategies is scarce. Hence, it was intended to fill in this huge gap by planning and delivering a mentoring program on qualitative research and analysis, focusing on the use of the computer-aided qualitative data analysis software (CAQDAS) called ATLAS.ti. Its main function is to assist the analysis process of qualitative data by way of conceptualizing and integrating pieces of evidence from the data and forming interpreted forms of findings for reporting purpose [11].

Fourth step – Structuring the mentoring

The fourth step is to structure the program as a standalone program or part of an existing organization. For this study, the mentoring program was designed to be a standalone program, as it focused on qualitative data analysis strategies by using the ATLAS.ti software, which can be joined by a participant without being subject to any prerequisites. A participant in this mentoring program may choose to participate in this program solely.

Fifth step – Defining the nature of the mentoring

The fifth step is to define the nature of the mentoring sessions. The mentoring was planned to be one of personal mentoring to a small group of participants, approximately 10 participants – with the aim to maintain a high level of interaction between the mentor and the mentees [34]. Another reason for this choice of small group mentoring is because the learning curve of the software itself is technical, hence the session was expected to require a lot of focus and attention from the mentees during the mentoring session.

Sixth step – Determining the mentoring outcomes

The sixth step is to determine what the program will accomplish, in terms of the mentoring program outcome. The following learning outcomes for the mentoring program was concluded:

To learn the basic functions of ATLAS.ti for understanding qualitative data through integration and reporting

To practice (hands-on) how to analyse different data formats (textual, images, audio, video, maps) using thematic coding.

Seventh step – Determining the details of the mentoring

The seventh step is to determine the details of the mentoring program, particularly when the mentoring will take place, and the facilities needed. This step is highly pertinent because the mentoring program would require participants to be interested in learning as mentors to the mentoring session. Since it was a ‘bring your own device’ (BYOD) program in which the mentoring participants would bring their own computers for the mentoring, there is no need for the target location to be in a computer lab.

Eighth step – Determining the timeframe for the mentoring

The eighth step is to determine how often mentors and mentees would meet, and how long the mentoring matches should endure. The mentoring program was planned to be a one-off session during the agreed date and time, with possible appointments being scheduled subsequent to the session, if desired by the mentoring participants. The time would be from 8.30 am until 4.30 pm, which was sufficient to cover all the five modules in the mentoring program.

Ninth step – Deciding the matching of the mentoring

The ninth step is to decide the mechanism to ensure the mentoring matches the capabilities of the mentor and the needs of the participants. For this purpose, the name the program is stated clearly as “Qualitative data analysis with ATLAS.ti 8”, hence excluded potential participants were: those who are quantitative postgraduates, those aiming to do literature review, and those wanting to learn another CAQDAS program other than ATLAS.ti. In essence, the contact information of the persons in charge of registration were published in the advert – so that any questions regarding the mentoring program could be directed to these persons. In addition, promotional efforts would be structured to gauge the needs/attention of qualitative postgraduates and researchers who might need to learn the qualitative analysis strategies by using CAQDAS, namely ATLAS.ti.

Tenth step – Identifying the mentoring stakeholders and promotion

The tenth step is to identify the program stakeholders and to determine how to promote the program. In this regard, the mentoring program stakeholders were:

One of the research centers at the institution – as the organiser of the program, handled all the matters of registration, coordination of the venue, meals and mentoring kits.

The mentor – as the person who would play the active role of imparting knowledge on ATLAS.ti for the purpose of qualitative analysis and guiding the mentoring mentee participants during the mentoring session.

The mentee participants – as the potential participants of the mentoring program, who need guidance and mentoring of their qualitative data analysis

On the other hand, it is highly pertinent to have a promotional strategy in place for the purpose of promoting the mentoring program to potential mentees. Accordingly, the strategies to promote the mentoring program include the sharing of adverts using offline medium, such as pasting the adverts on the walls of postgraduate rooms within the institution, sharing of adverts using online medium, and the e-mailing of the advert to neighboring institutions.

Eleventh step – Deciding the mentoring evaluation

The eleventh step is to decide how to evaluate the program’s success – by finding suitable rubrics for evaluating its effectiveness. For the purpose of this mentoring program, it was decided to do both quantitative and qualitative evaluation, as well as an online quiz. First, quantitative evaluation forms were administered to the participants at the end of the mentoring session, in the form of five-point Likert scale evaluation. For the qualitative evaluation, an online tool called TodaysMeet.com was engaged for the purpose of gathering feedback from the mentoring participants as to their takeaways from the mentoring session. As for the online quiz, the Kahoot! Game was used. By carrying out the three-pronged evaluation methods, it is submitted that the rich data collected from the participants would be highly beneficial in assessing their level of takeaways from the mentoring session, as well as serving as improvement strategies for our upcoming mentoring sessions.

Twelfth step – Establishing a management protocol for mentor-mentee relationship

The twelfth and final step is to establish certain management protocols and tools to ensure that the program keeps regular progress reports on the mentor-mentee relationship. Because the mentoring style for this program is a one-off session during the agreed date and time, with possible appointments being scheduled after the session, hence there would be no structured progress reports on the lessons imparted during the mentoring session [35]. However, the mentor invited the mentoring participants to a closed social media group on Facebook for the researcher’s employing ATLAS.ti in their research. The Facebook group is growing day by day particularly connecting people with the same learning needs and serves as an excellent learning community for researchers adopting ATLAS.ti in their research [36]-[37].

CONCLUSION

Designing a mentoring programmed is an important component among lecturers or educators. It helps lecturers or educators to be well prepared in organizing meetings with their students in the context of mentoring. Postgraduate students also play part as a researcher, they can choose to use quantitative, qualitative method or mix-method in research methodology. In our case study, qualitative analysis with ATLAS.ti for postgraduate students has been chosen as one of the subject tools in this exercise of designing a mentoring program.

Moving forward, direction for future research stemming from the findings of the study would be to duplicate the mentoring process and implementation to larger population, as in other institutions, as well as to diversify the mentoring programs by entending to other software packages, too. This is to ensure generalisation of the findings of the study, in terms of the design and implementation of the twelve-steps mentoring process outlined in this paper.

Additionally, future research should also encompass the feedbacks or reflections from students and teachers, too,  so that a more comprehensive finding could be drawn from the entire design and implementation of the mentoring program for postgraduate students. Such feedbacks or reflections could be either quantitative survey at the end of the mentoring program, or qualitative feedback/reflections from both teachers and students, or a combination of both quantitative and qualitative approaches.

Hopefully, this paper will become a focal reference for future research and the implementation of a mentoring program in other areas and topics. By building on the insights and findings presented here, scholars and practitioners can develop more effective and tailored mentoring strategies. This will ultimately contribute to the growth and success of individuals and organizations alike.

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