This presentation discusses the role of the European Credit Transfer and Accumulation System (ECTS) as a key instrument for determining student workloads in the European Higher Education Area (EHEA) countries. The central premise of the work is the ECTS system's assumption of a predefined amount of study time to achieve certain learning outcomes, usually ranging from 25 to 30 hours per ECTS credit (European Commission, 2015; Wagenaar, 2019). In particular, the aim is to compare the views of teaching staff on the workload determination practices with students' experiences of workload in studies, and their use of time. 

An important added value of the project compared to previous research is that it considers the perspectives of both teaching staff and students. In the case of students, there is already an established tradition of research on the subject. However, this literature has been characterized by a particular disagreement on the definition of workload: while in credit systems such as ECTS, workload is mainly understood as a function of time spent studying (Wagenaar, 2019), other literature has emphasised that time spent studying and students’ perceived workload are not the same (Bowyer, 2012; D'Eon & Yasinian, 2022). Despite the broad acceptance of ECTS, the system's performance has faced increasingly serious challenges: firstly, the actual time spent on studies does not seem to correspond to the time allocated to studies as expressed in ECTS (Souto Iglesias & Baeza Romero, 2018). Time use also appears to be weakly related to students' experience of workload in their studies (Kember, 2004; Smith, 2019). Moreover, time itself is an unreliable indicator of learning: instead, both student time use and perceived workload (Herrero-de Lucas et al., 2021) and other relevant factors such as the quality of time use and student ability (Masui et al., 2013) need to be considered if we are to present reliable models of student success in higher education. 

As for the teachers' perspective, previous research has been less extensive and more scattered than the interest in the students' perspective. There has been however, some guiding literature on how the workload for studies should be determined (e.g. Bowyer, 2012; Northup-Snyder et al., 2020). In addition, some comparative studies have shown that the study time estimated by teachers does not properly align with the actual time use of students (Alshamy, 2017; Scully & Kerr, 2014). Individual studies have also explored teachers' perceptions of ECTS as part of their work (Gleeson et al., 2021). Beyond these, there seems to have been little attention paid to teachers' specific ways and practices of determining course workloads and, for example, the challenges they perceive to be associated with this work. 

In relation to this framework, the current study aims to: 

1) map the practices, experiences and perceptions of teaching staff in determining course workloads; 

2) map students' perceptions of these practices for determining workload, and their relationship to students' time use, perceived workload, and academic performance; and 

3) compare how the views of teaching staff relate to data collected from students on the workload determination practices, time use, and their perception of workload. 

In sum, the project aims to build a more holistic and up-to date data and theory on workload determination practices in higher education. As such, the study is part of a wider research project whose main objective is to examine problems of time in higher education theory, policy and practice. 

The study is based on an ongoing survey-type data collection that is being conducted between January and March 2024 in two Finnish higher education institutions, one a research-intensive university and the other a university of applied sciences. These two educational institutions comprise around 2,750 teaching and research staff members and 23,200 students (PhD-level excluded) from a wide range of disciplines, including but not limited to humanities, education, social sciences, business, technology, engineering, natural sciences and health. In practice, there are two parallel data collections, one for teaching staff and one for students. In addition to key background variables (i.e., educational background and teaching experience), the survey for teaching staff explores teachers' experiences of the determination of course workloads, along with their views on the effectiveness, experienced challenges, meaningfulness, and the factors perceived as important for successful course workload estimations. In contrast, the survey prepared for students, in addition to background variables (i.e., the respondent's field of study and degree level), maps students' current number of ongoing studies as expressed in ECTS credits, total weekly time use (e.g. time spent on contact teaching, independent study and paid work), perceived workload in studies, opinions concerning the course workload estimations, and self-assessed academic performance. The data collection on students includes a 7-week follow-up period covering one teaching period in spring 2024. The current response rate (30.1.2024) is 8% (n=223) for teaching staff and 3% (n=706) for students in the first round of data collection. Both the teaching staff and student surveys are mainly based on Likert-scale items, which are to be used in the analysis phase as a basis for confirmatory factor analysis (CFA) and structural equation modelling (SEM) performed via SPSS and AMOS. In addition, some variables, such as time use and number of credits, were measured in continuous scales (i.e., hours and credits). The quantitative data collection is complemented by open-ended questions, from which the data will be processed by means of qualitative content analysis. The aim is to have some of the main results ready for presentation at the conference.

If successful, this research could prove useful for higher education theory, policy and practice in a number of ways. Firstly, it can provide information on the ways in which higher education is designed, particularly in relation to the practices of credit allocation and workload determination practices. Ideally, research can inform the development of curriculum systems and practices from the perspectives of both teachers and students. It can, for example, provide new insights into the challenges teachers face in determining student workloads and how to design them more appropriately and equitably in the future. Secondly, this research can provide a more up-to-date understanding of the relationship between time and workload and academic performance in the context of higher education students. Although the current study is a case study of two higher education institutions based on data collected in Finland, it can serve as a valuable example and inspiration for similar studies in other regional HE systems in EHEA countries. In addition, the results of the study can be compared with already existing data collections and studies, such as EUROSTUDENT (n.d.) project, which has been collecting data on students' time budgets for more than 20 years. Overall, this study could at best help to develop more appropriate workload determination practices on higher education institutions, in particular in relation to the diversity of student workloads, time use and life situations.

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