Motivation, self-regulation, and autonomy have been widely researched, but very few studies have examined how motivational orientations relate to self-regulation and autonomous learning behavior (Kormos & Csizér, in press). For this reason, this thesis examines the relationship between motivation, self-regulation and autonomous learning behaviour.
Background
- Motivation
- Self-regulation
- Autonomous learning behaviour
- Relationships between motivation, self-regulation and autonomous learning
- Motivation and self-regulation
- Motivation and autonomous learning behaviour
- Self-regulation and autonomous learning behaviour
- Research questions
Viewing self-regulation as self-regulatory strategies is clearly based on the “how theories” of this taxonomy. To summarize the previous research in the area, many theories and definitions of motivation, self-regulation and autonomous learning behavior have been established. What is the relationship between motivation, self-regulation and autonomous learning behavior in an EFL context in Finland.
Research design and method
- Participants
- The instrument
- Data collection procedures
- Data analysis procedures
What characterizes EFL students' self-reported behavior in Finland in relation to motivation, self-regulation and autonomous learning behaviour. The original research divides these two constructs into subscales of external regulation, enacted regulation, identified regulation, knowledge, performance, and stimulation; however, this was not done in this thesis due to limitation of the length of the questionnaire. Finally, the last three constructs were related to autonomous learning behavior and adapted from Benson (2001).
Two questions had a translation problem and these items were reformatted prior to data collection. The questionnaire was distributed by the researcher during a regular English class to 5 groups of students in January 2014. All questionnaires were anonymous and in order to get honest answers, the students were promised that the researcher would treat the data confidentially without releasing it. information to English teachers or other school staff.
All questionnaires were computer coded and the data were analyzed using SPSS (Statistical Package for Social Sciences) version 20. To perform certain procedures, such as ANOVA, the data were subgrouped based on the scores.
Results and discussion
The internal reliability of the investigated constructs
Descriptive statistics
The low average value of technology-based approaches is an indication that the students are simply not autonomous learners in this regard rather than a lack of knowledge. Technology is widely available nowadays and especially people between the ages of 16 and 19, who have grown up with technology, know its possibilities. Therefore, it can be assumed that all students have the ability to use technology for learning; however, they are unwilling to do so.
Comparing group-related differences
Finally, it is possible that women are less likely to admit that they have disturbing feelings about language learning. The reason for this may simply be social desirability or a greater association of these feelings (e.g. stress) with failure. According to age, two groups were formed: 16-17 years old as younger students and 18-19 years older students.
The result was unexpected because it was thought that younger learners would show different autonomous learning behavior and self-regulation. Younger learners have less experience and therefore have had less time to learn to use control strategies and become autonomous. In addition, the older learners are preparing for their matric exams which can be expected to at least result in the use of more self-regulatory strategies.
A possible explanation for the lack of a significant difference is the fact that the age difference was not large enough. There is probably a difference between significantly younger students and high school students.
Mean-related differences among the scales
This is possibly the result of the difference in the type of factor controlled by the strategies (i.e. whether the controlled factor originates within or outside the learner). Commitment control and emotion control are both used to manipulate factors that arise in the learner. This distinction in internal and external self-regulatory strategies may explain differences in their use.
Similar to the case of environmental control, which differs significantly from the other self-regulatory constructs, the difference in autonomy constructs may be a result of the different nature of the constructs: within and outside formal settings. Technology-based approaches are more likely to be used outside of formal settings, whereas classroom-based approaches (as the name already suggests) are used in formal settings. This dichotomy between within and outside formal settings is possibly an important defining factor of EFL learners' autonomous learning behaviour, as the significant difference between the constructs suggests.
This is not surprising because both constructs tap the same underlying motivational system. This seems to indicate that students with high use of engagement control strategies are also aware of the importance of emotion control strategies and use them to support their learning.
Comparison of motivation groups
Similarly, intrinsic motivation can override disruptive emotions and there is less need for emotion control strategies. It can therefore be assumed that no drastic change occurs in the student's use of emotion control strategies as their intrinsic motivation grows until the motivation is relatively high. This result suggests that students' intrinsic motivation can gradually increase their use of technology-based approaches.
It was found that the students with high intrinsic motivation differ significantly in their results in emotion control from those with low intrinsic motivation. This means that in relation to emotion control strategies, extrinsic motivation can overtake the effects of intrinsic motivation. Students who do have high intrinsic motivation combined with high extrinsic motivation probably use less emotion control.
Comparing the mean values of students who were placed in the high intrinsic motivation group and the high total motivation group revealed interesting results. Interestingly, in the case of environmental control, the mean values of students with high intrinsic motivation were lower than those with high total motivation.
The relationships among the scales
It is possible that those with exclusively higher intrinsic motivation prefer to use other strategies rather than environmental control. Similar to the self-regulation constructs, the means of technology-based approaches for those with high overall motivation are lower than those with high intrinsic motivation alone. This supports the self-determination theory view that autonomy is linked to intrinsic motivation.
Intrinsic motivation did not significantly correlate with the other measure of autonomy, classroom-based approaches. Intrinsic motivation was also found to have positive significant correlations with all the measures of self-regulation. This suggests that at least intrinsic motivation is closely related to self-regulation.
Furthermore, the correlation between intrinsic motivation and emotion control, and intrinsic motivation and environmental control was expected. This suggests that the relationship between motivation and autonomy exists only in the case of intrinsic motivation.
Regression analysis
In line with expectations, intrinsic motivation appears to be a better predictor of that of the students. Intrinsic motivation was found to be able to predict all constructs of self-regulation and technology-based approaches. Intrinsic motivation was found to have a significant linear relationship with all self-regulation constructs (see Tables 6a, 6b and 6c).
As mentioned above, all self-regulation constructs were found to be linearly related to intrinsic motivation. In summary, it can be argued that intrinsic motivation predicts the use of self-regulation. Regarding autonomous learning behavior, the data show that intrinsic motivation has a significant linear relationship with technology-based approaches (see Table 7).
Moreover, it is possible that intrinsic motivation can predict only one type of autonomous learning behavior. As discussed in relation to the results of intrinsic motivation and classroom-based approaches, it is possible that classroom-based approaches do not reflect true autonomous learning behavior.
Conclusion
In addition, the dichotomy in self-regulation strategies also explains the high use of environmental control strategies by highly intrinsically motivated students: their need to control external influences seems to be more important. Furthermore, the use of emotion regulation seems to increase gradually, without drastic differences, until the student's intrinsic motivation is very high. On the other hand, extrinsic motivation was found to have a smaller impact on self-regulation.
However, extrinsic control is also related to environmental control and was found to overcome the effect of intrinsic motivation in the case of emotion control of students with high total motivation. Additionally, high intrinsic motivation was found to lead to more autonomy; therefore, the extent of autonomous learning is different across all parts of the self-determination continuum. Finally, it is possible that the nature of the relationships between the concepts is circular, especially between autonomous learning behavior and self-regulation.
In addition, further research could focus on the role of mutually supportive concepts. Because students' mean scores were relatively low, the sample appears to include students with low motivation, low use of self-regulation, and minimal autonomous learning behavior.
I am studying English because to be an educated person I need to be able to speak English. Once the novelty of learning a new thing in English wears off, I easily get impatient with it. When I feel bored while learning English, I know how to regulate my mood to strengthen the learning process.
If I don't understand something in English class, I try to find the answer to my question in the textbook. 20 When the novelty of learning new things in English wears off, I get impatient easily. 29 I am learning English because I need to be able to speak English to be an educated person.
30 If I am bored while learning English, I know how to regulate my mood to stimulate the learning process. 31 If I don't understand something in English class, I try to find the answer to my question in the textbook myself.
