Learning and Individual Differences
Volume 91,
October 2021
, 102056
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Abstract
In higher education, students must manage their learning on their own. When students seize the opportunity to engage in specific evidence-based learning activities, this should contribute to their achievement beyond their individual learning prerequisites (i.e., prior knowledge and motivation) and their prior achievement. In turn, students with higher motivation should use more learning activities. To test these hypotheses, two cohorts of students attending a lecture class on educational psychology participated in online-surveys at the beginning and the end of one semester (N1=112; N2=171). Using regression analyses, we found that learning activity use explained students' performance at the end of the semester beyond their learning prerequisites and prior achievement. Furthermore, students who valued educational psychology more used more learning activities. Overall, students used learning activities much less than intended at the beginning of the semester. In conclusion, the results point to the importance of students' learning behaviors and their potential to determine their own success. Further research should identify factors that help students put their intentions into practice.
Introduction
Previous research has already examined the roles that students' individual learning prerequisites and learning history play in their achievement in higher education: General cognitive ability, prior knowledge, and motivation are well-known individual prerequisites that explain achievement (for a meta-analysis, see Richardson et al., 2012). In addition, students experienced many different learning situations and established certain methods of learning or study habits. All these prerequisites and experiences are reflected in prior achievement, which students bring with them to higher education. When students enter higher education, they face new challenges because their learning circ*mstances differ from those in high school. In higher education, learning is characterized by more opportunities to choose and less external control or structure (see e.g., Morisano et al., 2010; Perry et al., 2001). For example, students often attend large lecture classes and must pass exams at the end of a semester. How they prepare for such an exam, however, completely depends on the students. These circ*mstances challenge students' ability to organize their learning: They alone must choose when, where, and how to study. When students are told that their prior achievement (i.e., their high school grade point average) is substantially correlated with their achievement in higher education (r=0.40; Richardson et al., 2012), this might be demotivating for them. They could get the impression that their achievement is predetermined and consequently that their active engagement will not make a difference for their success in higher education. One aim of the present studies is to emphasize that the actual learning situation with the learning activities that are offered and how students engage in these activities contribute to students' higher education performance in ways that go beyond students' prerequisites and prior achievement.
However, it is not only students who are challenged in higher education. One aim of higher education is to equip students with competences specific for a subject but also with competences such as the ability to self-regulate their learning and thereby prepare students for lifelong learning. Therefore, instructors are challenged by the need to decide how to design their teaching to achieve these aims concurrently. Students' individual learning prerequisites become more heterogeneous as more students achieve a high school diploma that allows them to enter higher education (OECD, 2018, OECD, 2019). Students' heterogeneous learning prerequisites and the often large numbers of students attending a course challenge instructors to design their teaching in a way that enables as many students as possible to learn as much as possible. One way to address these challenges is to implement evidence-based learning activities in courses (Boser et al., 2017). Learning activities can help students learn effectively and continuously between the sessions and give instructors the opportunity to address students' knowledge level individually. Whether and to what extent students engage in such activities in turn may be explained by individual prerequisites such as motivation (Putwain et al., 2019).
This study was designed to investigate the benefits of optional evidence-based learning activities that can be offered to students in a self-regulated learning setting (e.g., a lecture class). In a lecture class, students should learn new content and can learn something about their own learning at the same time. In this setting, evidence-based learning activities serve students' learning and concurrently give instructors and researchers the opportunity to evaluate the activities' effectiveness and improve teaching. Consequently, instruction is informed by research and simultaneously, instruction aids research by supporting it with data from the field. In this field study, the use of learning activities was optional to represent a realistic learning setting in higher education. We therefore needed to assess students' intentions and actual use of learning activities before evaluating the activities' effectiveness. Three questions guided the study. First, which learning activities do students intend to use at the beginning of the semester? Second, how much do students use the learning activities that are offered over the course of the semester? Third, does the use of learning activities explain performance beyond individual learning prerequisites and prior achievement? If specific learning activities contribute to learning success in higher education beyond more stable characteristics (e.g., prior knowledge, motivation, prior achievement), this would stress the fact that students can actively contribute to their success. At the same time, it would raise the question of which factors explain students' engagement. Engagement could be explained by looking at individual learning prerequisites, again. This was considered in the second study.
Section snippets
Supply-use model for instruction
To investigate specific learning activities that can be implemented in higher education and determine whether they benefit students' learning, it is necessary to understand the general framework within which learning takes place and the factors that influence the learning process. Several authors have presented models of instruction for different contexts as an interaction of supply and use (Brühwiler & Blatchford, 2011; Helmke, 2017; Seidel, 2014). The basic idea behind these models is that
Summary and research questions
On the basis of supply-use models of learning, we investigated the use of learning activities as a predictor of achievement in higher education (see Fig. 1). Several individual student characteristics (i.e., prior knowledge, motivation, prior achievement) can be expected to be related to performance in higher education (see also Richardson et al., 2012). Beyond this, however, self-regulated learning plays a crucial role in higher education (Larose et al., 2005). Questionnaires assessing
Procedure
The setting of the study was an introductory lecture class on educational psychology for preservice teachers and psychology undergraduates at a German university. The aim of the lecture class was to provide students with basic knowledge regarding important educational psychological topics (e.g., how to improve learning). Furthermore, as the program came rather early in the curriculum, it was also dedicated to providing students with basic statistical knowledge to enable them to interpret
Study 2
Motivation is an important predictor for achievement (see also Section 2.1 Individual learning prerequisites). In Study 2, this assumption was specified and investigated: motivation is thought to drive behavior and expectancies and values as motivational constructs are associated with achievement related behavior and choices (see e.g., Wigfield & Eccles, 2000). These motivational constructs should consequentially also explain learning behavior or, in this case, the use of specific learning
Discussion
Besides individual learning prerequisites and learning experiences that have already contributed to achievement in the past, students' engagement in self-regulated learning is essential for success in higher education (see, e.g., Zimmerman, 2008). We considered it useful to assess a proximal predictor of achievement and therefore focused on the behavioral aspect of self-regulated learning, namely, learning activities. To investigate the use and usefulness of specific learning activities, we
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We have no known conflict of interest to disclose. This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
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