Universities in Australia and around the world are looking for ways to improve their attraction to and engagement of students, and particularly those from non-traditional university backgrounds such as lower socio-economic status backgrounds, first in their family to attend university, and older students.  One approach an increasing number of universities are exploring is to offer compressed courses taught one at a time, rather than semester-long courses  taught concurrently with other courses.  Various terminology has been used to describe this newer approach.  In this paper, we will use the term, “Block Model” or “Block Mode”.  Konjarski et al. (2023) argue that the Block Model can be differentiated from other accelerated or intensive courses in that the former typically consists of three-to-four week-long courses, with usually the same number of contact hours as traditional 12-or 16-week semester courses.  In addition, the Block Model generally involves small classes, frequent meetings for extended periods (Konjarski et al. 2023), and a ‘flipped classroom’ pedagogical approach whereby activities traditionally conducted in the classroom, such as content delivery, are done by students prior to class time (e.g., through reading material), with class time focused on things such as discussion, problem solving, and group activities (Akçayır & Akçayır 2018).

Most Block Model approaches have been implemented at the undergraduate level.  As a result, almost all of the research on the Block Model is also focused on undergraduate courses (see Testa & Van Dyke 2024).  Victoria University (VU), with main campuses in Melbourne, Australia, is a public, dual-sector research university providing courses in both higher education and technical and further education (TAFE).  It has approximately 45,500 students, of whom about 16,500 are undergraduates and 5,000 are postgraduates. VU began implementing the Block Model with first-year undergraduate courses in 2018, subsequently rolled out to all undergraduate courses.  In 2021, it began offering some postgraduate courses in Block Mode.

While pedagogical approaches to teaching and learning have some similarities at the undergraduate and postgraduates levels (Artino & Stephens 2009; Willems 2011), important differences exist and have potential implications for the success of the Block Model at this higher level.  For example, expectations regarding depth of learning are higher at the postgraduate level, as are expectations around the extent to which instructors are familiar with current and emerging research in the field (Bamber et al. 2017; Lindsay et al. 2002; Brewer 2017).

We have approached this work using two different but complementary theoretical frameworks – critical realism and social constructivism.  The former argues that there is an objective reality that exists independently from what can be observed, and our understanding of reality is shaped by social, cultural, and historical contexts.  Therefore, our knowledge of reality is always partial and fallible (Zhang 2023).  The latter posits that human knowledge and understanding are largely shaped by social interactions, cultural contexts, and shared experiences rather than being solely an individual, innate process. It posits that people construct their understanding of the world through collaboration with others, and these shared meanings become embedded in the fabric of society over time (Amineh & Asl 2015).

The aim of this study was to understand, using a mixed-methods approach consisting of individual interviews and institutional data, postgraduate students’ perceptions and outcomes of the Block Model.  In the case of the quantitative data, results for students undergoing Block Mode vs. the traditional mode are compared.

This study was approved by the Victoria University Research Ethics Committee. This study used a mixed-methods approach. Integrating the philosophical frameworks of both post positivism and interpretivism, the theory of mixed methods research involves integrating both quantitative and qualitative data to provide a more comprehensive understanding of a research problem (Dawadi et al., 2021; Johnson & Onwuegbuzie, 2004). This approach is rooted in the belief that neither quantitative nor qualitative methods alone can fully capture the complexities of a research question. By combining numerical data and statistical analysis with rich, contextual insights from interviews, using a mixed method approach allows for data triangulation, in turn enhancing the validity and reliability of the findings (Dawadi et al., 2021; Neuman, 2006). The mixed method approach also enabled researchers to explore the breadth of a phenomenon as well as affording the opportunity to delve deeply into the data’s underlying causes or meanings. Participants in both the qualitative and quantitative components of this study were postgraduate students at a single Australian university. Semi-structured interviews with 19 postgraduate students were conducted via Zoom between March and August 2022. Postgraduate students enrolled in a 4- or 8-week Block model, with or without prior Block mode experience, in postgraduate courses with large enrolments, were invited by email to participate. Each interview went for approximately 30 minutes and was audio recorded with the permission of the participant. Thematic analysis was employed (Braun & Clarke 2023). QSR NVivo 10 software was used for data management and to assist with the analysis. An inductive approach was used, whereby themes were generated by coding data, and reliability was ensured by comparing codes between the second author and other research members. The quantitative data was drawn from two sets of student-level institutional data from 2019-2022 and includes student outcomes and results from the Student Evaluation of Unit (SEU) survey. Data from a total of 1,167 students were included in the analysis. Student outcomes were measured by marks (grades) and pass/fail rates. SEU data included questions about the reasonableness of the workload, helpfulness of learning activities, extent to which learning resources were up-to-date; clarity of expectations, alignment of tasks to assessments; and overall satisfaction. Descriptive and inferential statistics were applied.

We identified three themes from the qualitative and quantitative data: Outcomes and assessments, Delivery, and Content. Several of the key findings are discussed below. The quantitative data generally showed better outcomes for students in the Block Model as compared with the traditional model (overall marks: Block (M=73.36, SD = 16.52) vs. Semester (M = 68.24, SD = 15.47); t(-20180.5) = -28.5, p<.001; pass/fail rates: χ2 (1) = 49.12, p<.001). Despite this, both the qualitative and quantitative data suggested mixed opinions regarding assessment of learning in Block Mode. There were also mixed opinions regarding the benefits – both academic and social -- of collaborative group work – another pedagogical hallmark of the Block Model. A second theme identified was the delivery of Block Mode, with 12 weeks of content across several subjects in the traditional mode condensed into either 4 or 8 weeks of either one or two subjects. For some interview participants, the pace and intensity of Block mode was a challenge, and the quantitative data supported this finding, with the survey question about reasonableness of the workload showing higher scores for traditional mode than for Block mode (t(4887.6) = 8.55, p<.0001). Other participants found this intensity beneficial. Several mentioned the ability to focus on one subject at a time as a strong positive of the Block Model. The final theme identified from the data was around course content with the Block model versus the traditional model. Several of the participants felt that depth of learning was sacrificed to some extent with the Block Model. The quantitative data showed that students felt that the traditional model worked better for providing them with activities that helped them learn, as compared with the Block model (t(5250.9) = 2.05, p<.05). In contrast, several interview participants discussed the positives of the Block approach.

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