Effect of self-regulated learning strategies on students’ achievement in science: A meta-analysis

Effects of Self-regulated Learning Strategies

This study revealed that self-regulated learning strategies had a significant effect on students’ achievement (es=1.2, N studies = 24, N participants =7,258). Additionally, the meta-analysis performed revealed that nine SRL strategies had a high impact on students’ achievement, namely i) self-assessment (es=4.8), ii) help seeking (es=3.4), iii) self-efficacy (es=2.4), iv) organisation (es=1.2), v) task value (es=1.1), vi) rehearsal (es=1.1), vii) homework self-regulation (es=1.0), viii) academic delay of gratification (es=0.8), and critical thinking (es=0.5). Among these strategies, self-assessment had the highest effect size (es=4.8) compared to the others. Self-assessment is conceptualised as a learning regulatory strategy (Panedero et al., 2017). According to Brown and Harris (2014), self-assessment strategy is important in science so that the learners can become more independent and plan their learning.

Studies on self-efficacy strategy have revealed a link between self-efficacy and students' achievement in science subjects (Jerstice, 2017; Aslam & Ali, 2017). Students' achievement is influenced by self-efficacy strategy because of its effect on students' thought patterns, affective responses, positive beliefs, motivation, participation, autonomy, and attendance. Students who have a high level of self-efficacy to excel in science will perform better and will be interested in the subject. This finding is significant for teachers, parents, and curriculum developers because self-efficacy strategy can improve students' science achievement. Organisation strategy can influence students’ achievement in science because of its cognitive linkages between old and new knowledge (Cebesoy, 2009). A person's general understanding of a specific task is defined as task value. Students with higher achievement have been found to have more specific task values (Tas, Subaş, & Yerdelen, 2019; Alpmen, 2016). According to one study, student task value varies depending on whether the student has a moderate or high level of interest in STEM (Shahali et al., 2015).

Another significant predictor of scientific achievement found in this study was critical thinking and this finding can be attributed to the nature of the subject. Science subjects need more application and reasoning; thus, it is important to use critical thinking strategy to solve the problem in all four science subjects. This finding is in line with the one found in the study by Kaya and Kablan (2013). Additionally, Sansone, Thoman and Fraughton (2015) in their study revealed the relation between self-regulation and interest in science. The Science of Smart Communities Program (Bitara STEM), which was introduced by the National University of Malaysia as one of the STEM modules in Malaysia, aimed to promote students’ interest and self-regulated learning using four implemented modules, namely (i) energy module, ii) urban infrastructure module, iii) transportation module, and iv) wireless communication module where all 4 STEM elements were integrated (science, technology, engineering, and mathematic) in the modules. In the programme, the students were encouraged to use SRL strategies such as self-assessment, help seeking, task value, rehearsal, and critical thinking (Shahali et al., 2015; 2016). According to Shahali et al. (2019), the level of interest in STEM careers among the students remained the same two years after leaving the BITARA programme. However, due to the poor quality of teaching and learning in the classroom, interest in STEM subjects among the students was low. Rahman et al. (2011) stated that students should be supported by a teacher to plan, evaluate, and manage their metacognitive development in science to sustain their interest.

However, not all self-regulated learning strategies are effective. Extrinsic goal orientation (motivational strategy) resulted in negative effect size value (es=-0.28). This finding is parallel with a meta-analysis study by De Boer et al. (2013) who found negative effect size for management strategy (es=-0.19) and cognitive strategies (es=-6.31). Hacieminoglu (2016) in his study found that students’ achievement was negatively correlated with student’s performance goal orientation (r=-.26). Nonetheless, the findings did not prove that extrinsic goal orientation strategy does not play a role in improving students’ achievement. If the extrinsic goal orientation and performance goal orientation strategy were not included as the criteria in choosing the learning strategy, the positive value for students’ achievement would be higher and the magnitude of the effect would be smaller.

Hacieminoglu (2016) found a positive relationship between students’ attitude towards science with SRL learning strategies (performance goal orientation, learning goal orientation, self-efficacy, and science achievement). He concluded that students who value science will show their interest in learning and manage their learning to achieve good results in science. However, the study by Ismail et al. (2018) had a contrasting finding to the one in Hacieminoglu’s (2016) study, and a possible explanation could be the education system in Malaysia which is immensely exam oriented.

Effects on Moderator Influence

Categories of Self-Regulated Learning Strategies

According to Albert Cobra's social cognitive learning theory, metacognitive strategies must be used in the process of self-regulated learning. Our findings indicate that metacognitive strategies can influence students' performance in science, chemistry, and physics. Metacognitive strategy is important for these subjects for the students to manage, evaluate, and understand concepts besides learning the main ideas in science and scientific practices (Fengua & Chen, 2010; Fouche & Mark, 2011; Avargil, Lavi & Dori, 2018). Moreover, metacognitive strategies can enhance understanding in chemistry (Dike, 2017). Esen (2013) found a positive effect size for the combination of metacognitive and cognitive strategies for chemistry in higher education. Mazorodze (2012) stated that metacognitive strategies can help students solve problems in physics. The inclusion of metacognitive strategies in science can improve students’ achievement (Callan et al., 2016; Fouche & Mark, 2011).

The findings revealed that when students used metacognitive strategies frequently and precisely, they improved their learning outcomes. Science, physics, and chemistry involve conceptual understanding, process of knowledge construction, problem solving, meaningful learning, and the ability to think scientifically (Dike, 2017, Avargil et al., 2018). However, the findings indicated that behaviour strategy influenced students’ achievement in biology. This outcome is consistent with Alpmen (2016). According to Alpmen (2016), students who enjoy biology perform better than others.

Types of Science Subjects

Students’ achievement depends on their effort and process in learning. One of the most important determinants of a student's success is the use of appropriate learning strategies. Accordingly, past results revealed that effective use of learning strategies in four science subjects is important (Rovers et al., 2018; Gengle, Abel & Mohammed 2017; Berger & Karabenick, 2010). The findings revealed that task value was a significant predictor for achievement in biology (Alpmen, 2016). This result is consistent with findings in related literature (Yumusak, 2006; Fries et al., 2005). The findings showed that for chemistry, the following learning strategies should be implemented: the combination of goal setting, self-monitoring, and self-reflection, and the combination of reflective thinking and self-assessment. Self-monitoring was found to be dominant among the learning strategies. Hence, the finding indicates that self-monitoring is a major predictor for successful learning in chemistry. Additionally, Chang (2007) and Anderson et al. (2006) discovered a positive effect when self-monitoring strategies were implemented in groups with low metacognitive levels.

According to other research, implementation of self-monitoring strategies at the end of the learning process has a positive relationship with learning achievement (Azevedo et al., 2009; Greene, Moos & Azevedo, 2011). This study found that note taking strategy contributed to achievement in physics (es=0.43). However, the finding of this present study is not in agreement with Selcuk (2010) who found elaboration, organisation, and rehearsal were significant predictors for achievement in physics in his study. Meanwhile, the results for science in this study contradicted those of other studies (Hao et al., 2017; Kaya & Kablan, 2013). In this study, it was found that help seeking strategy had a high effect for achievement in science (es=3.41). In contrast, Hao et al. (2017) found that help seeking strategy had more influence on science computer students. Meanwhile, Kaya and Kablan (2013) based on their findings concluded that effort regulation strategy and critical thinking can significantly affect achievement in science.