This article approaches students’ learning in higher education from the perspective of the Student Approaches to Learning (SAL) tradition. SAL-tradition identifies three qualitatively different ways of learning:  deep approach, surface approach and organised studying (Entwistle & Tait, 1990; Marton & Säljö, 1976). Several studies show that a deep approach to learning has a positive effect on learning outcomes (Marton & Säljö, 1976; Trigwell & Prosser, 1991). As a result, a deep approach is the most valued of the three approaches to learning. Researchers agree that students’ approaches to learning are related to their experiences of the learning environment. At the same time, researchers acknowledge the challenge of enhancing a deep approach to learning through traditional instruction (Baeten, Struyven, & Dochy, 2013; Marton & Säljö, 1984). An answer to what extent instructional practices can support the more favourable approaches to learning is yet to be clarified.  

This research aims at identifying characteristics of instructional designs that are related to  students’ application of different approaches to learning. The same cohort of studentsis studied in two undergraduate mathematics courses that uses different pedagogical approaches. In a preceding quantitative study (Lahdenperä, Postareff, & Rämö, 2018), three groups of students were identified: 1) students applying a deep approach to learning, 2) students applying a surface approach to learning, and 3) students applying a context-sensitive surface approach to learning. The first two groups of students applied similar approaches to learning in both course context: students applying a deep approach to learning scored high on deep approach and low on surface approach to learning, and students applying a surface approach to learning scored low on deep approach and high on a surface approach to learning. In contrast, students applying a context-sensitive surface approach changed their approaches to learning according to the course context: these students applied a surface approach to learning on one but not on the other course context.

In this study, 16 student interviews are analysed in order to deepen the understanding of the behaviour of the students in the aforementioned groups and to seek connections between the student behaviour and the learning environments of the courses. The research question is: how do students applying a different approach to learning interact with the learning environment? In addition, an interesting question is why some, but not all, of the students applying a surface approach in the other course shifted their approach towards a deep approach to learning in the other course. The study is motivated by the need to further identify effective learning environments and transfer knowledge from research to teaching practices.

This study approaches the research questions through a qualitative analysis of student interviews, in which they reflected on their learning experiences in two different undergraduate mathematics courses. The research is conducted in the mathematics department of a research intensive university in Finland. This study investigates the same cohort of students in two different course contexts. The two courses are usually taken by students during the first semester of their university mathematics studies, and they are both six-week, five-credit courses with approximately 200 students. Course A is an analysis course functioning within a traditional lecture-based course setting but including student-centred elements, such as active lectures and supporting students’ participation in mathematical discussions. Course XA is a linear algebra course taught with the Extreme Apprenticeship method having characteristics such as learning by doing, flipped learning, instructional scaffolding and continuous feedback. In practice, the main differences between the courses centred on the role of lectures, the design of the course tasks and the form of support given to the students by the teaching assistants. All participants of the prior quantitative research were invited for an interview on a voluntary basis. These students attended both courses and in the interviews they reflect on their experiences on the two course contexts. The interviews were semi-structured interviews with an average length of 1h 13 min. In this paper, the data consists of 16 student interviews. Seven of them are from the deep approach group, four from the surface approach group, and five from the context-sensitive surface approach group. The analysis process started with reading the interviews several times to familiarise with the data and to make sense of it. The analysis included both deductive and inductive content analysis. First, a deductive content analysis was used to identify elements of instructional design (lectures, weekly tasks, working on weekly tasks, guidance, course material, assessment, and mathematical content), and excerpts dealing with approaches to learning. For this, a structured categorisation matrix was developed. The data was coded based on the matrix. The coding was checked several times to ensure internal consistency and to increase reliability of the coding phase. The interview was designed these questions in mind, so the elements for coding were quite easily recognised from the transcripts. The second analysis phase consisted of inductive content analysis (Elo & Kyngäs, 2008) focusing on the instances where students link elements of course design to their approaches to learning.

The preliminary data analysis suggests that students in all three groups (deep approach, surface approach, context-sensitive surface approach) mention weekly tasks and the guidance provided while working on them most often when describing their approaches to learning in either of the course contexts. The three student groups differ mostly in their way of setting goals and in time management. Especially students applying a surface approach to learning have challenges in time management, and although they aim at systematically completing tasks every week, they feel that their effort does not pay off. The results also suggest that students’ deep approach to learning is supported by giving them responsibility over their learning, and by helping them to set goals and to achieve them. When completed, the analysis will provide further evidence on how to support positive approaches to learning through instructional designs.

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