This study explores students’ self-regulation in learning in three different higher education settings. Self-regulation in learning is proven to be a distinctive element between superior and average performers. Participants, 21 higher education students, evaluated their self-regulation skills using a  self-evaluation instrument modified from MSLQ (Pintrich et al., 1993). In addition, the data were collected by focused interviews, which were analysed deductively using Ruohotie’s (2000) categorisation of naïve and skilful learners in self-regulation. Participants’ self-report results and interview analyses were compared. Also, matriculation examination results were examined to see whether they could predict the stage of self-regulation in learning, and whether an on-line tutoring system can enhance awareness of self-regulated learning. The results revealed that higher education students’ phase of self-regulation in learning varies from naïve to skilful and it is not directly dependent on students’ age or amount of completed studies. In this study students’ self-report and the analysis of interviews gave coherent results about the stage of participants’ self-regulation, and furthermore in many cases the result of matriculation examination predicted the stage. The on-line self-evaluation and tutoring system activated participants to self-study, which is crucial for the initial stage of self-regulation to develop, but it was shown that for naïve self-regulators, enhancing assignments should be built into the course tasks. The more skilful self-regulators are more motivated to develop their learning strategies and voluntarily go into depth on these tasks and take advantage of the offered materials. Thus, the question that arises is, how can the naïve students in self-regulated learning be inspired to self-analyse their often poor learning strategies and begin to improve them.

The aim of this research is firstly, to examine how higher education students self-regulate learning and how the self-regulation of learning is related to success in the matriculation examination. Secondly, two assessment methods, a self-report instrument and a focused interview, are compared as means of evaluating self-regulation. Thirdly, we explore students’ conceptions on how an online self-evaluation and tutoring system enhances self-regulation in learning.

Methodology

The participants (N=21), 19 female and two male, came from three different higher education courses: firstly, Educational Science freshmen (n=12) attending an obligatory study skills and orientation course organised in face-to-face setting, secondly, vocational teachers (n=5) attending one year certifying educational studies course at Open University, mainly arranged in web-based setting. Finally, four participants were participating in a four months lasting fully webbed course of Communication studies arranged by Open University. The participants’ mean age was 31 years (S.D. 9.2). Twenty participants had completed higher education studies earlier, separate courses or a first cycle university degree.

The data were collected by focused interviews and a self-evaluation instrument, both focusing on several aspects of self-regulation theory constructed by Pintrich (2000) and Zimmerman (2000). The IQ Learn evaluation and tutoring system includes material for developing self-regulation in learning, and its questionnaires are modified (Niemi et al., 2003) from MSLQ (Pintrich et al., 1993) and include 16 dimensions to be self-evaluated by Likert-type statements. In addition the participants supplied their matriculation examination results in the interviews.

The interviews were content analysed, and analysed deductively using Ruohotie’s (2000) categorisation of differences between naïve and skilful learners in self-regulation. The categories are based on Pintrich’s theories of sub-dimensions in self-regulation and consider self-regulative learning in eleven aspects: goal setting, goal orientation, efficacy beliefs, intrinsic interest, concentration, strategies of learning, self-monitoring, self-evaluation, attribution, result expectations and adaptation. To ensure reliability, two researchers evaluated each interview. The participants were given 1 to 3 points in each aspect representing naïve, moderate or skilful skills in the aspect. Based on the sum score, students were labelled as naïve (sum 11-23 points), moderate (sum 24-29 points), or skilful (sum 30-33) in self-regulation. The limiting values were calculated using the mean ± ½ standard deviation of participants’ sum scores.

Findings

Students’ general level of self-regulation in learning defined by the deductive analysis of the interviews varied from naïve (n=4) to moderate (n=11), and to skilful (n=6). The profiles of participants were regular across dimensions, with results on different aspects varying from naïve to moderate or from moderate to skilful. However, one participant was categorised as naïve and skilful on some dimensions and moderate on others.

Ten participants’ results in the matriculation examination, passed at age of 18, were highly predictive for the level of self-regulation in learning interpreted by the researchers. Six participants’ results in the matriculation examination were not congruent with the interpreted self-regulation skills. Four of them had performed clearly below average in the matriculation examination, but were labelled skilful or highly moderate in self-regulation, and two had received good results in the matriculation examination, but were labelled naïve or barely moderate in self-regulation.

Though the results of self-evaluation paralleled the results of the interview analysis, they were in most cases slightly higher. Four students interpreted the most skilful by researchers, self-evaluated their skills clearly above the mean result of the group. The two youngest students, labelled also as skilful, evaluated their skills below the mean. However, the most naïve students self-evaluated their skills as either below or slightly above the mean level.

Seventeen participants used the IQ Learn system actively within the course assignments and four participants voluntarily alongside their studies. It became evident that participants labelled skilful in self-regulation voluntarily went into greater depth in the system. The less self-regulative students had rather superficial attitudes towards learning. They also had a fairly externally regulated approach to the tutoring system and therefore gained more from it as they were guided through its use, e.g. were given clear assignments. For them the system functioned as an activator, whereas more skilful students found it as a resource to develop their learning strategies.

Educational significance

Though self-regulation in learning is a general target of higher education and it has been proved to be a critical element in understanding what sets superior performers apart from the average, too few actions have been taken to seriously enhance students’ awareness and development of their self-regulation skills. This study proves that students’ level of self-regulation differs from naïve to skilful and it is not necessarily dependent on students’ age or earlier completed studies. This study introduces a methodological aspect for combining evaluation and development of self-regulation in learning. By using a self-evaluation instrument in an academic course to become aware of oneself as a learner, even the students naïve in their self-regulation are activated to deeply think over their learning strategies. In pursuance of promoting students’ self-study, which is required for self-regulation to start developing, the teacher receives valuable information on students and can adjust teaching to best encourage the students to develop further with self-regulation. In particular, the teacher’s role should not be neglected, as it was proven that naïve self-regulators need a teacher’s guidance as well as the tutoring system to benefit from the materials designed to enhance self-regulation.

Niemi, Nevgi & Virtanen. (2003). Towards self-regulation in web-based learning. Journal of Educational Media, 28, 49–71.

Pintrich, P. (2000). Motivation and action in self-regulated learning. In Boekarts, Pintrich & Zeidner (Eds.) Handbook of self-regulation.

Pintrich, P. et al. (1993) Reliability and predictive validity of the Motivated Strategies For Learning Questionnaire (MSLQ), Educational and Psychological Measurement, 53, pp. 801–813.

Ruohotie, P. (2000). Conative constructs in learning. In Pintrich, & Ruohotie (2000). Conative Constructs and Self-regulated Learning. RCVE: Finland.

Zimmerman, B. (2000) Attaining self-regulation. A social cognitive perspective, in: M. Boekaerts, Pintrich & Zeidner (Eds) Handbook of Self-regulation.