Background, aim and theoretical approaches

Physical attendance at university lectures has been declining internationally (Nagappan et al. 2025), despite long‑standing evidence linking attendance to improved learning and achievement (Ancheta et al. 2021). Class attendance is generally not mandatory at Finnish universities, reflecting Finland’s autonomy-based education model (Ursin 2019), which often allows students to choose whether to attend lectures or study independently.Finnish universities are tuition-free which, in theory, reduces financial pressure for students, enabling them to focus on their studying. However, because students do not incur high personal costs for their education, there is less perceived financial ‘loss’ from skipping lectures, which may lower the incentive to attend lectures regularly. 

Students’ limited engagement with lectures highlights the need to understand what drives their attendance and research has identified motivation as a key predictor of lecture attendance (Fryer et al. 2018). Given this fact, it’s important to understand more clearly the motivations associated with classroom attendance.

The aim of this qualitative study is therefore to explore university students’ motivation to attend on-site lectures at two universities in Finland. The theoretical frame chosen for the study is the expectancy–value theory (EVT) (Eccles and Wigfield 2020, Wigfield and Eccles 2020; 2023). The study focuses specifically on the values students associate with certain tasks as well as the costs that come with the choices students make (Wigfield and Eccles 2023). Task value is composed of four main factors: a) utility value, referring to how useful a certain task is for a student, b) attainment value, referring to the perceived personal importance that a student attaches to a given task, c) intrinsic value, referring to the enjoyment or interest derived from performing the task itself and d) extrinsic value, defined as the perceived value of a task based on external rewards (Eccles and Wigfield 2020). Research indicates that value beliefs are strong predictors of interest, persistence, and achievement across educational levels (cf. Wigfield and Cambria 2010). 

In addition to values, the EVT model incorporates a cost component, reflecting the perceived negative implications of engaging in a task. The three cost dimensions most commonly discussed in research literature are: (a) effort cost, which refers to students' perceptions of the amount of effort or time needed to complete a task; (b) emotional/psychological cost, which relates to students' fear of failure or perceptions of the negative emotional impact of engaging in a task (Wigfield and Eccles 2000), and (c) opportunity cost, which involves students' perceptions of the activities they must forsake in order to focus on a task (Flake et al. 2015). 

Students’ task values and costs are in turn shaped by beliefs formed through prior educational and sociocultural experiences (Wigfield and Cambria 2010). Socializers—especially teachers and peers—play a central role in shaping these beliefs and behaviours (Wigfield and Eccles 2023). Similarly, teachers’ pedagogical methods matter: interactive methods such as group discussions consistently increase lecture attendance in higher education (Bukoye and Shegunshi 2016).

Our research questions are therefore; 1) What are the values and costs the students attribute to their attendance in class? and 2) What is the impact of socialisers and teachers’ pedagogical methods on how students value lectures?

Design and approach. We adopted a qualitative, exploratory design using semi‑structured interviews to capture lived experiences of lecture attendance motives across disciplines. EVT served as a sensitising framework, guiding initial deductive codes for task values (utility, intrinsic, extrinsic, attainment), costs (effort, emotional/psychological, opportunity/time), and the (non‑salient) expectancy for success construct. Setting and participants. The study took place at two Finnish universities (one large research-focused; one specialised business school) where attendance is generally voluntary. We recruited 28 students (aged 21–40; 23 female/5 male) from medicine (n=10), economics (n=11), and educational sciences (n=7), reflecting distinct disciplinary cultures and common urban commuting patterns. Convenience sampling was employed due to accessibility and timelines. Ethics. The study followed national ethical principles for human sciences research in Finland; formal institutional review was not required given adherence to informed consent, confidentiality, and anonymisation. Pseudonyms were used, identifying details were removed, and interviews were scheduled outside formal teaching contexts to mitigate power dynamics. Participation was voluntary and without grading implications. Data collection. We conducted 24 semi‑structured interviews (including two small group interviews) in Swedish or Finnish during 2023–2024, lasting 10–30 minutes, either online or face‑to‑face. The interview matrix (developed collaboratively and piloted with five students) covered demographic/context questions and core prompts on attendance behaviour, perceived lecture value, enjoyable aspects, activity levels, and discouraging factors. Transcripts were produced with university‑licensed tools, verified against audio, and anonymised. Analysis. Guided by Braun and Clarke’s six steps, analysis proceeded abductively. We loaded transcripts and theory‑aligned code definitions into Atlas.ti, independently double‑coding ~10% (three interviews) to establish coding reliability (~80% agreement), resolving discrepancies by consensus. Subsequent coding was performed collaboratively by authors ÅM and CB, with iterative discussion to maintain consistency. Triangulation compared thematic convergence/divergence across individual versus group interviews. Inductive refinement addressed data that resisted initial categories: notably, time and opportunity were merged; logistical/financial/safety aspects were nested under effort cost as contextual expressions affecting feasibility. A decision trail documented code evolution, merges/splits, and adjudication of competing interpretations.

Findings This study clarifies how students reason about attending on-site lectures in voluntary‑attendance settings. Utility value emerged as the strongest motivator for students to attend lectures. They preferred lectures that gave them more than they could get from self-study —for example, clear explanations, helpful examples, and guidance on future professional practice. Students were also more likely to show up when they simply found the topic interesting, even if the teaching style varied. External incentives mattered too: when attendance earned points, students often described their decision as a straightforward calculation to avoid losing marks. The main reasons for not attending (costs) were practical and emotional. Students were less likely to attend lectures when attending required extra time or when they felt they could learn the same material faster on their own. Emotional barriers—such as fear of being put on the spot or discomfort in tense classroom environments—further discouraged attendance. Students judged whether the time, energy, or stress involved in attending was justified by the benefits of the lecture. When the drawbacks felt greater than the benefits, skipping the lecture seemed like a reasonable choice. Socialisers influenced students’ motivation in various ways. Teachers who created a safe atmosphere, encouraged participation, and showed how course content connects to real situations made lectures feel more worthwhile. Guest lecturers were especially motivating because they helped students see the relevance of what they were learning. Peers also played a role: having friends in class, hearing about discussions, or not wanting to miss out made attending feel more appealing. In addition, teaching methods mattered mainly because they shaped students’ perception of a lecture as useful or enjoyable. Students preferred lectures where they could participate, work through examples, or discuss in pairs or groups.

Ancheta, R. F., D. Daniel, and R. Ahmad. 2021. “Effect of Class Attendance on Academic Performance.” European Journal of Education Studies 8 (9). https://doi.org/10.46827/ejes.v8i9.3887. Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa Bukoye, O. T., and A. Shegunshi. 2016. “Impact of Engaging Teaching Model (ETM) on Students’ Attendance.” Cogent Education 3 (1). https://doi.org/10.1080/2331186X.2016.1221191. Eccles, J. S., & Wigfield, A. (2020). From Expectancy-Value Theory to Situated Expectancy-Value Theory: A developmental, social cognitive, and sociocultural perspective on motivation. Contemporary Educational Psychology, 61, 101859. https://doi.org/10.1016/j.cedpsych.2020.101859 Flake, J. K., K. E. Barron, C. Hulleman, B. D. McCoach, and M. E. Welsh. 2015. “Measuring Cost: The Forgotten Component of Expectancy-Value Theory.” Contemporary Educational Psychology 41: 232–244. https://doi.org/10.1016/j.cedpsych.2015.03.002. Fryer, L. K., P. Ginns, M. Howarth, C. Anderson, and S. Ozono. 2018. “Individual Differences and Course Attendance: Why Do Students Skip Class?” Educational Psychology 38 (4): 470–486. https://doi.org/10.1080/01443410.2017.1403567. Nagappan, P. G., Tan, S. R. X., Absar, S., Brown, S., Sayers, S., McManus, A., … Tulinius, C. (2025). Changes in medical student attendance at in-person teaching sessions: A systematic review. BMJ Open, 15(5), e091768. https://doi.org/10.1136/bmjopen-2024-091768 Ursin, J. 2019. “Student Engagement in Finnish Higher Education: Conflicting Realities?” In Student Engagement and Quality Assurance in Higher Education, edited by M. Tanaka, 24–34. Routledge. Wigfield, A. 1994. “Expectancy-Value Theory of Achievement Motivation: A Developmental Perspective.” Educational Psychology Review 6: 49–78. https://doi.org/10.1007/BF02209024. Wigfield, A., and J. Cambria. 2010. “Students’ Achievement Values, Goal Orientations, and Interest: Definitions, Development, and Relations to Achievement Outcomes.” Developmental Review 30 (1): 1–35. https://doi.org/10.1016/j.dr.2009.12.001. Wigfield, A., and J. S. Eccles. 2020. “35 Years of Research on Students’ Subjective Task Values and Motivation: A Look Back and a Look Forward.” In Advances in Motivation Science, vol. 7, 161–198. Elsevier. https://doi.org/10.1016/bs.adms.2019.05.002. Wigfield, A., and J. S. Eccles. 2023. “The Relevance of Situated Expectancy-Value Theory to Understanding Motivation and Emotion in Different Contexts.” In Motivation and Emotion in Learning and Teaching Across Educational Contexts, 3–18. Routledge. https://doi.org/10.4324/9781003303473-2.