Qualitative research is a rich and diverse discipline, yet novice qualitative researchers may struggle in discerning how to approach their qualitative data analysis among the plethora of possibilities. This paper presents a foundational model that facilitates a comprehensive yet manageable approach to qualitative data analysis, and it can be applied within an array of qualitative methodologies. Based on an exhaustive review of expert qualitative methodologists, along with our own experience of teaching qualitative research, this model synthesises commonly-used analytic strategies and methods that are likewise applicable to novice qualitative researchers. This foundational model consists of four iterative cycles: The Inspection Cycle, Coding Cycle, Categorisation Cycle, and Modelling Cycle, and memo-writing is inherent to the entire analysis process. Our goal is to offer a solid foundation from which novice qualitative researchers may begin familiarising themselves with the craft of qualitative research and continue discovering methods for making sense of qualitative data.

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The interpretative and flexible nature of qualitative research is one of its hallmark strengths, yet this can pose a significant obstacle for researchers who wish to incorporate computer-assisted qualitative data analysis software (CAQDAS), especially for educators of CAQDAS and researchers who may have abandoned CAQDAS following past frustrations. We seek to help qualitative researchers and teachers by illustrating how CAQDAS can be used to follow specific analytic strategies (e.g. inductive and deductive analysis, category identification and synthesis, and qualitative model building). To bridge the gap between qualitative methodology and CAQDAS, this article provides guidelines for researchers to familiarise themselves with widely used qualitative analysis strategies, and learn how ATLAS.ti, MAXQDA, and NVivo can be used in each phase of the qualitative analysis process. By effectively translating analytic strategies into CAQDAS features, CAQDAS can greatly facilitate data management, analysis, and collaboration when software features are harnessed to realise analytic strategies.

Learning to conduct qualitative research and use computer-assisted qualitative data analysis software (CAQDAS) can be challenging, which is why it may be more effective to introduce the craft of qualitative research to undergraduate students who have the time and space to learn, even make mistakes, and ultimately build a better understanding for their future studies and careers. There are relatively few published studies sharing insights on teaching qualitative research and CAQDAS to undergraduate students. This descriptive qualitative case study explores students’ experiences in a qualitative research course for undergraduate psychology students, with the aim of discerning how feasible learning both qualitative research and CAQDAS was for these students as well as how they perceived learning about these contents. Data was collected from an online open-ended survey from two consecutive generations of students that completed the course. Students found the course to be a challenging but worthwhile experience: new knowledge and skills were gained that they felt would be useful for their professional and even personal lives. These students recognized that the qualitative research course was an important complement to their predominantly quantitative curriculum. By teaching undergraduate students about qualitative research and CAQDAS, professors can teach their students in a lower-stakes environment and provide them with valuable hands-on experience so that students may later make better-informed decisions about which research approach to use in their own projects and continued studies or work.

Any country embarking upon a political transition to democracy faces a complex period of change. While many factors influence successful democratization, political leadership remains a relatively unexplored phenomenon. This research presents a theoretical framework that is corroborated with data gathered from 65 semi-structured interviews with people involved in the transition processes of Spain and Lithuania along with the main political leaders themselves: King Juan Carlos I, Adolfo Suárez, Algirdas Brazauskas and Vytautas Landsbergis. The four leaders presented a similar political leadership style – based on their vision, decision-making, negotiation and power – which positively influenced the success of each transition to democracy.