The Relationship Between Reflectivity and Self-Regulated Learning in MA Medical Education Students of Shiraz University in 2018 and 2019

Abstract

Introduction

Reflectivity is one of the fundamental methods of education. This study aimed to investigate the relationship between reflectivity and self-regulated learning in MA medical education students of Shiraz University of Medical Sciences in 2018 and 2019.

Methods

In this descriptive study, 34 full time and virtual MA students of medical education participated, using census method. Data were collected through the Pintrich and DeGroot self-regulated learning and the Kember et al.’s reflectivity questionnaires. Descriptive and inferential statistics were used for data analysis, through SPSS.

Results

The results showed that self-regulatory learning strategies in subjects with good reflectivity were significantly higher than those with poor reflectivity; also, the scores of cognitive strategies and motivational beliefs were significantly higher in the participants with good reflectivity. There was no significant relationship between reflectivity and subscales of self-regulated learning strategies and also between reflectivity and self-regulated learning strategies in the full time and virtual courses.

Conclusion

It was found that there was a positive and meaningful relationship between reflectivity and self-regulated learning. Therefore, it is recommended that the managers and professors in medical universities should provide training programs in this field in order for the students to benefit from the advantages of reflectivity and self-regulated learning.

Introduction

One of the most important issues in higher education institutions is the evaluation and improvement of the students’ academic achievements. Providing and training specialized and experienced manpower as the basis for comprehensive development of countries is the goal of each country’s education system. In this regard, nurturing self-regulated learners seems to play a key role in achieving this goal. According to research, learners who use self-regulated learning strategies have more knowledge and skills. Learning is one of the most important topics of interest to psychologists and educational scholars, and they try to understand the dimensions of the complexities of learning and facilitate human learning [1]. In the field of medical education, due to the constant changes in information and the importance of up-to-date knowledge, it is necessary to pay attention to training students who are constantly learning during and after their studies, so identifying effective teaching methods and determining their efficiency are important to be reviewed [2]. Reflectivity has been accepted as an important learning tool in university education. It causes the learners to become aware of their learning weaknesses and to realize their learning needs, thus enhancing their lifelong learning. Given that reflectivity is a spontaneous process that can be controlled and taught, by using the principles and methods of teaching and creating it, the ability to reflect can be created and strengthened in the learners until it becomes a professional habit in them. Reflectivity is a metacognitive process that occurs before, during, and after situations with the aim of creating a deep understanding of the person and the situation in which he or she finds himself or herself in order to better deal with and be aware of the future performance and events. Its goal in the learning process is to create meaningful deep learning and improve the performance [3]. Metacognition is a self-regulatory process that selects, controls, and evaluates the cognitive process. These concepts are important in defining reflectivity because they indicate that rethinking is not a spontaneous process [4]. Rethinking requires guidance from clinical educators and professors [5]. The purpose of reflectivity is to develop not only awareness and skills, but also the habit of thinking and strengthening the immediate mechanisms for producing information and critical learning [6]. Reflectivity is one of the characteristics of self-directed learners and one of the necessities of self-directed learning and self-regulation [7]. Recording and writing rethinking has been considered as a powerful tool for strengthening and cultivating it, and in some cases, it has been shown to be more effective than oral rethinking [8]. Reflectivity models are presented in two cyclical and vertical formats. The first category is initiating the experience of the reflectivity process. The second category is also initiating the experience of the rethinking process, with the difference that it is believed by researchers that different levels of rethinking are created in relation to experience, and they consider it as a hierarchical or vertical process [1]. The evidence suggests that learning requires methods that make the individual take action and that inclusive participation in the learning process is an active learning strategy [9]. Education through reflectivity, along with methods such as problem-based learning, exploratory learning, empirical learning, and competency-based learning, which are widely used in medical education, is one of the active methods in education, and it is accompanied with the individual’s activity to improve his/her professional competence [10]. Reflectivity is an integral and essential component in teaching and learning health professions. It is a controllable process, and a variety of educational strategies can be used to reinforce and create it. Reflectivity causes learning to be profound and meaningful rather than superficial.

In educational psychology, a kind of learning called self-regulatory learning has been proposed in which the learners have personal control over the training process and in addition to faster and more accurate learning they are ahead of other learners in mastering issues such as high self-confidence, self-efficacy, and responsibility. The basic principle of self-regulation is that students learn more effectively when they are responsible for their own learning.

Self-regulation first emerged from the Bandura’s social cognitive theory, followed by the emergence of prominent theoretical models in the field of self-regulation [11]. Self-regulation of learning is one of the issues that consider the role of the individual in the process of learning. The basic principle of self-regulated learning is that students learn more effectively when they are responsible for their own learning [12]. One possible and important view is that self-regulation is a pragmatic process that helps the learner to acquire academic skills such as goal setting, strategy selection and substitution, and control of self-efficacy [13]. Self-regulation of learning means active involvement of students in their individual, behavioral, motivational, and cognitive learning efforts in order to achieve important and valuable academic goals [12]. In the field of self-regulation, different models have been presented, each one emphasizing an aspect of self-regulation. Most of these models have four common assumptions: (a) the learners actively participate in their own learning; (b) a potential power to control all models is assumed that learners can monitor, control, and adjust aspects of cognition, motivation, and behavior, as well as some features of their environment; (c) the third assumption is about goals, criteria, or standards; and (d) self-regulatory activities play a role as a mediator between personal, environmental, and actual performance factors [14]. Self-regulated learning strategies are divided into three categories: cognitive strategies, metacognitive strategies, and resource management. Zare et al. in a study entitled “reflectivity in medical education, a review of concepts, models, principles and teaching methods” concludes that teaching and strengthening reflectivity in learners is a necessity of education in health professions [1]. Granvand et al. in a cross-sectional study entitled “the relationship between self-regulation and academic achievement in students” concluded that self-regulation had a significant relationship with academic achievement which can be predicted through self-regulation [15].

This study aimed to investigate the relationship between reflectivity and self-regulated learning strategies in MA medical education students in 2018 and 2019. One of the requirements for making a country’s education more efficient is to address the issues and factors affecting the growth and academic achievement of students. Given the problems in student learning and also the importance of using known skills to increase the academic performance of higher-education students, we made an attempt to find out the relationship between reflectivity and self-regulatory learning strategies in MA medical education students of Shiraz University of Medical Sciences.

Materials and Methods

Participants

The present study is applied in terms of purpose and descriptive in terms of data collection method. To collect the data, we used a questionnaire; the census method, defined in statistics as a study on all the available members of a population, was used in this study. It is a cross-sectional study that was performed on all students studying in the master’s degree of medical education studying in the second semester of 2018 and the first semester of 2019 in Shiraz University of Medical Sciences. There were 20 students entering the MA program in 2018 and 14 starting the MA in 2019. Of them, 5 studied in the face-to-face and 29 in the virtual course. All of them were enrolled in the study. As to their gender, 9 were male students and 25 female ones. All the full-time (daily course with face-to-face or in-person classes) and virtual MA students of medical education in which the students attend only online courses and just sit for exams in person; they had entered the university in the second semester of 2018 and first semester of 2019 participated in this study using census method (34 students) were enrolled. Then, in the first face-to-face workshop of these students, which was held in September 2019 at the college, the researcher explained the objectives of the and were ensured that participation in the study is voluntary and they can leave the study whenever they wished. The students signed the consent forms; then, they were asked to fill out the questionnaires. The ethics committee of Shiraz University of Medical Sciences, Shiraz, Iran, approved the study with the code of IR.SUMS.REC1398-1138.

Instruments

Data were analyzed using two questionnaires:

1. The Pintrich and DeGroot self-regulated learning questionnaire (MSLQ) [16]: It contains two sections of motivational beliefs and self-regulated learning strategy consisting of cognitive, metacognitive, and resource management strategies. The subscales of self-regulated learning strategies include 22 items on the three dimensions (13 items on cognitive strategies including repetition and review, note-taking, summarization, organization, and comprehension and 9 items on metacognitive and resource management including planning, supervision and control, efforts and preservation, and regulatory activity). Motivational beliefs contains 25 items on self-efficiency, goal orientation, internal evaluation, and test anxiety. %-point Likert scale ranging from completely agree (5 points) to completely disagree (1 point). The total score of this questionnaire is calculated from the sum of the scores of these 47 items. The scores 47–94 is considered low self-regulation, 94–141 moderate, and higher than 141 as the high level of self-regulation. A reliability of 0.79–0.98 has been reported in different studies using Chrobach’s alpha (Pintrich and Degroot [16], Mosavinejad [17])

2. Kember et al. questionnaire [18] of the reflectivity variable:

   It contains 4 subscales consisting of performing tasks based on habit, based on comprehension and understanding, based on thinking and reasoning, based on critical thinking in 16 dimensions. It is scored based on a 5-point Likert scale ranging from completely disagree with 1 score to completely agree with 5 score. Its minimum and maximum score are 16 and 80; the higher scores show higher levels of reflectivity. The sum of the scores of the subscales are calculated by adding the score of the items in each subscale, and their sum makes the total score of the questionnaire. The higher the score, the higher the reflectivity. The validity and reliability of this questionnaire have been reported acceptable (Kember et al. [18]).

Procedures

All the students filled out the two questionnaires. The questionnaires were collected and then analyzed. The content validity and factor analysis methods were used to determine the validity of the questionnaires. In this study, Cronbach’s alpha was used to evaluate the reliability of the data obtained in the pre-test stage (36 people), and 0.85, 0.86, 0.77, 0.84, and 0.78 were obtained for self-efficacy, internal evaluation, and test anxiety subscales, using cognitive and metacognitive strategies, respectively. To analyze the data, we first described the data using descriptive statistics including “mean and standard deviation” for quantitative variables and “frequency and percentage” for categorized variables. Independent t test was used to analyze the data, and a p value of 0.5 was considered as significant. SPSS software was used to analyze the data.

Results

In the present study, a total of 34 MA students majoring in medical education in Shiraz University of Medical Sciences were studied. Nine of them were male and 25 were female (20 students of 2018 and 14 of 2019); in total, 5 full-time students and 29 enrolled in virtual course participated in the study. Based on their scores in the reflectivity questionnaire, they were categorized into weak and good reflective thinkers. In examining the relationship between reflectivity and self-regulated learning strategies, we used the independent t test, the results of which are shown in Table 1.

Table 1.

The relationship between reflectivity and self-regulated learning strategies (total)

Significance Level	Observed T	Standard Error	Standard Deviation	Mean	Number	Reflectivity level
0.045*	2.09	0.18	0.41	3.31	5	Weak
		0.04	0.26	3.60	29	Good

^*Level of significance = 0.05

According to the results, self-regulatory learning strategies in participants with good reflectivity were significantly more than those with poor reflectivity (p = 0.045).

In examining the relationship between reflectivity and the main scales of self-regulated learning, we also used independent t-test; the results are shown in Table 2.

Table 2.

The relationship between reflectivity and main scales of self-regulatory learning strategies test

Scale	Reflectivity group	Number	Mean	Standard deviation	Standard error	Observed T	Freedom degree	Significance level
Cognitive strategies	Weak	5	3.48	0.34	0.15	2.57	32	*0.015
	Good	29	3.98	3.40	0.07
Metacognitive strategies and resource management	Weak	5	3.30	0.48	0.21	0.07	32	0.93
	Good	29	3.31	0.51	0.09
Motivational beliefs	Weak	5	3.06	0.55	0/24	2.54	32	*0.016
	Good	29	3.53	0.34	0.24

^*Level of significance = 0.05

The results showed that the dimensions of cognitive strategies and motivational beliefs were significantly higher in people with good reflectivity than those with poor reflectivity (p = 0.015 and 0.016, respectively). However, there was no significant relationship between reflectivity and metacognitive strategies and resource management (0.93).

To answer the research question of the relationship between reflectivity and subscales of cognitive strategies in students, we used independent t test, and the results are shown in Table 3.

Table 3.

The relationship between reflectivity and subscales of cognitive strategies

Scale	Reflectivity group	Number	Mean	Standard deviation	Standard error	Observed T	Freedom degree	Significance level
Repetition and review	Weak	5	3.13	0/83	0.37	1.78	32	0.08
	Good	29	3.60	0.49	0.09
Note-taking	Weak	5	3.00	1.41	0.63	2.39	32	*0.02
	Good	29	4.20	0.97	0.18
Summarization	Weak	5	3.60	0.89	0.40	1.13	32	0.26
	Good	29	4.03	0.77	0.14
Organization	Weak	5	4.20	0.50	0.22	0.54	32	0.59
	Good		4.07	0.46	0.08
Comprehension	Weak	5	3.50	0.50	0.22	1.61	32	0.11
	Good	29	3.98	0.63	0/11

^*Level of significance = 0.05

From a set of cognitive strategies, including strategies for repetition and review, note-taking, summarizing, organizing and comprehension, only the subscale of note-taking was significantly different in two groups of reflectivity, such that taking notes in students who had good reflectivity was more than those who had poor reflectivity (p = 0.02). Furthermore, there was no significant relationship between reflectivity and other subscales of cognitive strategies including (repetition and review (0.08), summarizing (p = 0.26), organizing (0.59), and comprehension strategies (p = 0.11)).

In order to answer the research question of the relationship between reflectivity and subscales of metacognitive strategies and resource management in students, we used the independent t test; the results are shown in Table 4.

Table 4.

The relationship between reflectivity and subscales of metacognitive strategies and resource management test

Scale	Reflectivity group	Number	Mean	Standard deviation	Standard error	Observed T	Freedom degree	Significance level
Planning	Weak	5	3.90	0.82	0.36	0.19	32	0.84
	Good	29	3.82	0.77	0.14
Supervision and control	Weak	5	3.70	0.90	0.40	0.29	32	0.76
	Good	29	3.62	0.48	0.08
Effort and perseverance	Weak	5	3.40	1.29	0.57	0.55	32	0.58
	Good	29	3.13	0.91	0.16
Regulatory activity	Weak	5	2.20	1.30	0.58	0.81	32	0.42
	Good	29	2.68	1.22	0.22

^*Level of significance = 0.05

The metacognitive strategies and resources management consists of subscales of planning, monitoring and control, effort and perseverance, and regulatory activity. There was no significant relationship between reflectivity and subscales of metacognitive strategies and resources management (p = 0.084, 0.76, 0.058, 0. 42, respectively).

To find out the relationship between reflectivity and subscales of motivational strategies, we also used the independent t test, the results of which are shown in Table 5.

Table 5.

The relationship between reflectivity and the subscales of motivational strategies test

Scale	Reflectivity group	Number	Mean	Standard deviation	Standard error	Observed T	Freedom degree	Significance level
Self-efficacy	Weak	5	3.62	1.04	0.46	0.28	32	0.78
	Good	29	3.75	0.55	0/10
Goal orientation	Weak	5	3.40	0.82	0.36	2.28	32	*0.02
	Good	29	00.4	0.48	0.09
Internal evaluation	Weak	5	3.20	1.42	0.63	0.93	32	0.39
	Good	29	3.81	0.73	0.13
Test anxiety	Weak	5	2.05	0.75	0.33	1.31	32	0.19
	Good	29	2.57	0.82	0.15

^*Level of significance = 0.05

The subscales of motivational beliefs include self-efficacy, goal orientation, internal evaluation, and test anxiety. The results showed that the goal orientation subscale was the only factor significantly different in both groups with weak and good reflectivity, i.e., goal orientation was higher in subjects who had good reflectivity than those with poor reflectivity (p = 0.02); it was also revealed that there was no significant relationship between reflectivity and other subscales of motivational beliefs, including (self-efficacy (p = 0.078), internal evaluation (p = 0.39), and test anxiety (p = 0.19)).

We also examined the relationship between reflectivity and self-regulated learning strategies in the students of full-time and virtual courses, using independent t test; the results are shown in Table 6.

Table 6.

The relationship between reflectivity and self-regulated learning strategies among the students in full time and virtual courses

Scale	Reflectivity group	Number	Mean	Standard deviation	Standard error	Observed T	Freedom degree	Significance level
Cognitive Strategies	Full time	5	4.13	0.37	0.16	1.29	32	0.20
	virtual	29	3.86	0.43	0.08
Metacognitive strategies and resource management	Full time	5	3.22	0.66	0.29	0.43	32	0.66
	virtual	29	3.33	0.47	0.08
Motivational beliefs	Full time	5	3.35	0.50	0.22	0.65	32	0.51
	virtual	29	3.48	0.39	0.07
Self-regulatory learning strategies	Full time	5	3.54	0.35	0.15	0.14	32	0.88
	virtual	29	3.57	0.29	0.05

^*Level of significance = 0.05

As it was indicated, there was no significant relationship between reflectivity and self-regulated learning strategies among the students in full-time and virtual courses (cognitive strategies = 0.20, metacognitive strategies and resource management = 0.66, and motivational beliefs = 0.51).

Discussion

The results of the study of the relationship between reflectivity and learning strategies showed that the use of self-regulated learning strategies in people with good reflectivity was significantly more than the participants with poor reflectivity. Reflectivity influences the students’ critical thinking skills and mind habits, so that students can deepen their learning and gain the ability to make connections between the theory and practice; moreover, by strengthening their self-regulatory mechanisms, they exercise more control over their performance [19]. The results of this study are consistent with those of Moradi [20] and Pazhoman and Sarkhosh [21], indicating the positive relationship between reflectivity and self-regulated learning. However, they are not in the same line with the results of Tucci [22].

Due to their personal satisfaction and interest, self-regulated learners engage in academic activities and are behaviorally and meta-cognitively active in their learning. Active involvement in the learning process increases their academic performance. As a result, these learners are clearly successful. Successful students use some self-regulated learning strategies that include personal adjustment (organizing and transmitting information), behavioral performance (providing performance-based encouragement and punishment), and immediate resources (reviewing notes), getting help from classmates and asking for help from adults help them reach the desired level [23].

In examining the relationship between reflectivity and the three main scales of learning strategies, the results showed that the scales of cognitive strategies and motivational beliefs were significantly higher in subjects with good reflectivity than those with poor reflectivity, which is consistent with the results of Ertmer and Newby [24] and Kuiper et al. [25] Engaging in reflectivity, which is a basic condition for constructivist learning environments, had enabled the students to become aware of the process of self-construction of knowledge and had provided an opportunity for them to reflect on their current ideas, assumptions, and conceptualization, and in this way, their cognitive ability had grown [26]. Examining the relationship between reflectivity and cognitive strategies scales showed that note-taking was higher in people with good reflectivity compared with those with poor skill in this strategy. In this regard, the results of Rahimi and Haqqani [3] Abedini et al. [9], and Badri Gargari et al.’s studies were consistent with those of the present study. Note-taking was a powerful tool for creating purposeful and profound rethinking. Student-teachers who had the experience of reflectivity practice, i.e., they had had daily lessons from the classroom during multiple internship sessions, had acquired higher deductive reasoning skills than student-teachers trained in the traditional method [26].

In the study of the relationship between reflectivity and subscales of metacognitive strategies and resource management in MA medical students, the results indicated that there was no significant relationship between reflectivity and subscales of self-regulated learning strategy which was inconsistent with the studies conducted by Sandars [27] and Gagné et al. [28]. Using the dimensions of self-regulated learning strategies (cognitive strategies and metacognitive strategies), students preferred to choose the tasks that were more challenging in order to learn new things and act more accurately compared to others in the classroom, pay more attention to the teacher in class, and answer the questions correctly. In fact, in this way, by self-assessment of their learning, they test themselves and take notes, to maximize the amount of their memorization [1]. Investigating the relationship between reflectivity and motivational strategies subscales in MA medical education students showed that goal orientation was higher in subjects with good reflectivity than those with poor reflectivity; this was consistent with the results of Normand [29]. Goal orientation represents a coherent pattern of beliefs, attributes, and emotions of a person that determines his/her behavioral goals and causes him/her to be more inclined towards certain situations and act in a specific way. This orientation in educational situations indicates a student’s motivation to study, thereby influencing his desires, actions, and responses in learning situations [30].

Investigating the relationship between reflectivity and self-regulated learning strategies in the students enrolled in the full-time or virtual MA medical students revealed that there was no relationship in this regard. These results are inconsistent with those of the studies of Shamami et al. [31], Pakdaman Savoji [32], and Dastjerdi and Davarpanah [33] which indicated a positive relationship between e-learning and self-regulated learning.

Suggestions

It is suggested that a better learning environment will be provided by providing appropriate conditions in the University of Medical Sciences; such conditions include providing a creative space; giving time for creativity and flexibility; providing a free atmosphere in the organization for expressing opinions; applying material and spiritual incentives; adopting appropriate strategies as well as increasing the spirit of risk-taking; and adopting various programs for using cognitive strategies (mental review, expansion, and organization) and metacognitive strategies (planning, monitoring comprehension, and self-regulation).

Also, given that rethinking skills can be taught and trained, it is recommended that training courses in this field should held for students to use this skill in a timely manner, leading to improvement in their professional and educational life. It is also suggested that in educational decisions, more attention should be paid to the role of cognitive learning styles and methods as the best description of the differences between the learners’ individual groups in learning, which is related to academic achievement and reflectivity.

Finally, in order to teach the medical students self-regulatory skills and the importance of self-regulatory skills, the teachers need to consider all factors of self-regulation (cognitive, metacognitive, motivational, behavioral, and environmental) in future educational methods and curricula, and workshops should be held in this field. According to Arcoverde et al., learning autonomously requires students to have strategic learning techniques that involve the planning of their actions, the monitoring of their understanding, the regulation of their emotions and motivation, robust beliefs of self-efficacy for learning, and a repertoire of individualized learning and study strategies that can be intentionally and proactively used to reach learning goals [34].

Limitations

Among the limitations of the present study, we can mention the research tool which was a questionnaire; the other tools such as experimental interventions, observation, and interview are recommended to be used in future studies. The study was done on all the medical education students in Shiraz University of Medical Sciences, using census method (all available students), so the sample size was limited, and in generalizing the results to other students and universities, caution should be exercised. It is recommended that expanding the survey distribution to additional programs and students at different schools and different majors would provide more information regarding the research questions of this study.

Conclusion

According to the results obtained in this study, strategies derived from self-regulatory models have a significant role in learning. Development of cognitive, metacognitive, and motivational beliefs make the student more motivated to control and monitor his/her progress and continually assess himself/herself. Encouraging reflectivity and self-regulated learning in students requires a new look at the teaching and learning processes by the instructors, leading to students’ educational achievements and more pleasurable learning environment. As emphasized by Robbins et al., the more students are encouraged to engage in metacognition around their own learning—to actively think about how they learn, their learning goals, and strategies to improve learning—the more they may feel internally motivated and in control of their own learning process and habits (or at least not less internally motivated and not less in control) [35].

Declarations

Ethics Approval

The ethics committee of Shiraz University of Medical Sciences approved this study.

Consent to Participate

All the students gave their written informed consent.

Conflict of Interest

The authors declare no competing interests.