
In recent times, there has been significant interest in self-assessing personality using tools like the MBTI (Per-sonality Type Assessment) in South Korea. This trend has drawn attention to metacognition as a factor related to self- objectification. MBTI assists in objectifying and under-standing an individual’s personality type, while metacog-nition can contribute to developing awareness and self- perception related to this understanding.
Metacognition refers to the notion of ‘cognition about cognition’ or ‘self-awareness.’ It includes the concept of monitoring and managing one’s learning progress, signi-fying the mental process of observing, discovering, and controlling one’s cognitive processes from a higher level of perspective, which involves a heightened awareness of one’s own cognitive processes1). In essence, it is the aware-ness related to intelligence that involves calmly recogni-zing what one knows and doesn’t know, strategizing to identify and resolve issues independently, and being able to regulate one’s learning journey. It has been primarily studied in conjunction with concepts like problem-solving abilities, especially among students1).
Problem-based learning (PBL) is an instructional method predominantly used in the field of education, distinguishing itself from traditional lecture-centric teaching approaches. In PBL, students engage with real-world problems or sce-narios, embarking on a journey of self-directed and colla-borative learning to find solutions to these challenges. Throu-ghout this process, they autonomously acquire the necessary knowledge and skills2). PBL proves to be an effective edu-cational method that enhances students’ collaboration skills, critical thinking, communication skills, creativity, and applied skills2). As a result, numerous educational institutions and universities have adopted PBL to improve students’ lear-ning experiences and enhance learning outcomes.
Problem-solving ability represents the highest level of cognitive function, involving the mental process of identi-fying, collecting, and reviewing data and information to find solutions to problems in any given situation. It encom-passes the ability to judiciously select and organize specia-lized knowledge acquired through learning3). Metacognition and problem-solving ability are crucial in the sense that they involve awareness of what information is needed and what skills are required to solve problems and the ability to reflect on the outcomes obtained in the process4). Lear-ners with strong metacognitive skills are aware of when to employ metacognitive strategies and can select alternative approaches for defining problem situations and solving them.
Learning flow signifies not only the emotional content-ment associated with enjoyable learning but also the potential to enhance the quality of learning5,6). Metacognition and self-directed learning have a significant impact on lear-ning flow, with self-directed learning playing a crucial mediating role in the relationship between metacognition and learning flow7). Lee8) emphasized the significant rela-tionship between the cognitive strategies employed by individuals during the learning process and the experience of flow among students. Moreover, it was noted that the more frequently metacognition is employed, the greater the likelihood of experiencing a heightened sense of flow during the learning process.
According to prior research studies, Kang et al.9) argued that metacognition significantly influences flow and problem- solving abilities. Sternberg10) suggests that successful pro-blem-solving can be achieved by continuously monitoring during the problem-solving process, emphasizing the nece-ssity of metacognitive functions. Levine and Wang11) points out that students with well-developed metacognitive self- regulation skills consistently apply various problem-sol-ving methods while effectively utilizing previously learned concepts. In contrast, students with lower self-regulation skills tend to adhere to a single problem-solving approach regardless of its effectiveness.
Previous research in the field of healthcare and medical sciences suggests that is reported that metacognition and learning flow have a close relationship with problem- solving abilities12-14).
According to previous studies in the field of dental hy-giene, Yu et al.15) investigated general characteristics and major-related traits to understand the factors influencing dental hygiene students’ problem-solving abilities. Addi-tionally, Kim et al.16), Shim et al.17), and Jun and Kim18) con-ducted research on critical thinking tendencies and problem- solving abilities. Additionally, in the field of dental hy-giene, factors such as metacognition19), interpersonal skills20), self-efficacy21), and PBL22) have been researched for their impact on problem-solving abilities. Kang and Kim23) argued that metacognition is not only related to problem-solving abilities but also associated with learning flow, critical thi-nking, and self-directed learning. They emphasized the increasing importance of critical thinking and compre-hensive problem-solving abilities for dental hygienists in response to contemporary demands. Meanwhile, studies tar-geting dental hygiene students have primarily explored their academic achievements in relation to learning flow24,25).
Furthermore, in various fields, research on metacognition, learning flow, and problem-solving abilities among students is being conducted. However, the dental hygiene field still lacks substantial research on metacognition, learning flow, and problem-solving abilities. Therefore, there is a need to develop strategies for curriculum and teaching methods to enhance the educational environment for the advancement of dental hygiene education. Additionally, there is a need to explore approaches for cultivating the essential compe-tency of problem-solving abilities required in clinical pra-ctice as dental hygienists.
Therefore, the purpose of this study is to understand the relationship between metacognition, learning flow, and pro-blem-solving abilities among dental hygiene major students, and to identify the factors that influence problem-solving abilities. Through this research, we aim to provide funda-mental data that can contribute to the improvement of teaching methods and educational environments in dental hygiene education.
This study was conducted online from September 10, 2023, to September 14, 2023, using a convenience sample extraction method in undergraduate students in their 2nd, 3rd, and 4th years majoring in dental hygiene across the country. First-year students were excluded. The survey was conducted through an online questionnaire with indi-viduals who understood the research objectives and volun-tarily agreed to participate. The online survey involved respondents accessing the survey link via URL and provi-ding self-reported responses. This study received research approval from the Institutional Review Board of Namseoul University (202307-004).
The calculation of the required sample size for this study was performed using the G*power 3.1.9.4 program. Consi-dering a moderate effect size of 0.15, a significance level of 0.05, a power of 0.95, and the inclusion of up to 2 inde-pendent variables, the necessary sample size was estimated to be 107 individuals. However, since this study involved a non-face-to-face survey conducted via URL, accounting for unfaithful responses and a dropout rate of 10% to 20%, the final target sample size was set at 130 participants. As a result, data from 132 respondents who completed the survey were used as the final dataset for analysis.
The tools used in this study consisted of a total of 100 items, including metacognition (31 items), learning flow (29 items), problem-solving abilities (32 items), and general characteristics (8 items). Among the dental hygiene stu-dents who participated in this study, the average metacog-nition score was 2.14±0.51 points, learning flow was 2.37± 0.65 points, and problem-solving abilities were 2.26±0.53 points. Among the sub-components, self-regulation was the highest in metacognition, with a score of 2.29±0.48 points. In learning flow, the sub-components of self-loss of con-sciousness scored the highest at 2.62 ± 0.93 points, followed by self-directed experiences at 2.53±0.91 points. Among the sub-components of problem-solving abilities, self-control scored the highest at 2.58±0.50 points (Table 1).
Variables and Subfactors
Variables | Item | Score | Cronbach’s a |
---|---|---|---|
Metacognition | 31 | 2.14±0.51 | 0.907 |
Practice | 4 | 2.03±0.72 | 0.732 |
Elaboration | 6 | 1.99±0.59 | 0.652 |
Organization | 4 | 2.01±0.66 | 0.596 |
Critical thinking | 5 | 2.14±0.67 | 0.691 |
Self-regulation | 12 | 2.29±0.48 | 0.697 |
Learning flow | 29 | 2.37±0.65 | 0.940 |
Challenge-skills balance | 3 | 2.14±0.70 | 0.646 |
Clear goals | 3 | 2.10±0.79 | 0.590 |
Specific feedback | 3 | 2.17±0.78 | 0.696 |
Action-awareness merging | 3 | 2.42±0.87 | 0.703 |
Task concentration | 3 | 2.43±0.82 | 0.699 |
Sense of control | 3 | 2.39±0.81 | 0.647 |
Loss of self-consciousness | 3 | 2.62±0.93 | 0.708 |
Altered sense of time | 3 | 2.39±0.86 | 0.754 |
Autotelic experience | 5 | 2.53±0.91 | 0.849 |
Problem-solving ability | 32 | 2.26±0.53 | 0.918 |
Approach avoidance style | 16 | 2.22±0.55 | 0.849 |
Problem-solving confidence | 11 | 2.16±0.66 | 0.870 |
Self-control | 5 | 2.58±0.50 | 0.591 |
Values are presented as mean±standard deviation.
The metacognition tool used in this study was adapted from the MSLQ (Motivated Strategies for Learning Ques-tionnaire) developed by Pintrich et al.26) to measure lear-ning strategies. It was restructured to include 31 items related to the cognitive and metacognitive domains. The 5 sub-factors included practice, elaboration, organization, critical thinking, and self-regulation. Respondents rated each item on a 5-point Likert scale. Higher scores indi-cated a higher level of metacognition. In previous studies, the Cronbach’s a for each of the 5 sub-factors ranged from 0.64 to 0.80, while in this study, it was found to be Cronbach’s a=0.907 (Table 1).
The learning flow instrument consisted of a total of 29 items, as proposed by Csikszentmihalyi5), and modified and improved by Kim et al.6). It comprises nine sub-factors: chal-lenge-skills balance, clear goals, specific feedback, action- awareness merging, task concentration, sense of control, loss of self-consciousness, altered sense of time, and auto-telic experience. Participants responded to each item using a Likert 5-point scale, ranging from ‘strongly disagree’ 1 point to ‘strongly agree’ 5 points. A higher score indicates a stronger sense of learning flow. In prior research, the Cronbach’s a for each of the nine sub-factors ranged from 0.65 to 0.90. In this study, the Cronbach’s a was calcu-lated as 0.940 (Table 1).
The problem-solving ability instrument used in this study was adapted from the Personal Problem-Solving Inventory, originally developed by Heppner and Petersen3) and cul-turally adapted for our context by Kang et al.9). The ques-tionnaire comprises a total of 32 items, organized into three sub-factors: approach avoidance style, problem-solving con-fidence, and self-control. Participants responded to each item using a Likert 5-point scale. A higher score indicates a higher level of problem-solving ability. In previous research, the Cronbach’s a values for the three sub-factors were re-ported as follows: avoidance style 0.72, problem-solving confidence 0.85, and self-control 0.90. In the present study, the Cronbach’s a value was calculated as 0.918 (Table 1).
General characteristics were composed of a total of 8 items, including age, sex, school type, grade, major satis-faction, subjective academic performance, grade point ave-rage (GPA) and reasons for choosing the major.
The participants in this study, who were majoring in dental hygiene, had an average age of 21.92 (±1.49) years, with the majority being females (90.2%). Most of the participants were enrolled in universities (79.5%), with 3rd-year students comprising the largest group (49.2%), followed by 2nd-year students (37.1%), and 4th-year students (13.6%). Regarding major satisfaction, 97% expressed satisfaction or higher. Sub-jective academic performance was reported as good (47.7%), excellent (25.0%), moderate (22.7%), and poor (4.5%). In terms of the previous semester’s GPA, the distribution was as follows: 3.0 or higher but less than 4.0 (64.4%), 4.0 or higher (32.6%), and 2.0 or higher but less than 3.0 (3.0%). The reasons for choosing the major were ranked as follows: good job prospects after graduation (42.4%), suitability for the field (33.3%), influence or recommendation from parents, teachers, or others (17.4%), and alignment with academic performance (6.8%) (Table 2).
General Characteristics of the Subject
Characteristic | Division | n (%) |
---|---|---|
Total | 132 (100.0) | |
Age | ≤21 y | 58 (43.9) |
>21 y | 74 (56.1) | |
Sex | Male | 13 (9.8) |
Female | 119 (90.2) | |
School type | College | 27 (20.5) |
≥University | 105 (79.5) | |
Grade | 2nd | 49 (37.1) |
3rd | 65 (49.2) | |
4th | 18 (13.6) | |
Major satisfaction | Very satisfied | 38 (28.8) |
Satisfied | 90 (68.2) | |
Dissatisfied | 4 (3.0) | |
Very dissatisfied | 0 (0.0) | |
Subjective academic performance | Excellent | 33 (25.0) |
Good | 63 (47.7) | |
Moderate | 30 (22.7) | |
Poor | 6 (4.5) | |
Very poor | 0 (0.0) | |
GPA | ≥4.0 | 43 (32.6) |
<4.0∼≥3.0 | 85 (64.4) | |
<3.0∼≥2.0 | 4 (3.0) | |
<2.0 | 0 (0.0) | |
Reason for major choice | Based on academic performance | 9 (6.8) |
Based on the recommendation of others (parents or teachers) | 23 (17.4) | |
Due to high employment prospects after graduation | 56 (42.4) | |
Because it seemed suitable for my aptitude | 44 (33.3) | |
Other | 0 (0.0) |
GPA: grade point average.
A descriptive statistical analysis was conducted on the general characteristics of the study subjects. Independent two- sample t-tests and one-way ANOVA were used to investigate differences in metacognition, learning flow, and problem- solving abilities based on the participants’ general charac-teristics. Post-analysis was performed using Scheffe’s multi-ple comparison test. Multiple regression analysis, using the Enter method, was employed to identify factors influe-ncing problem-solving abilities, the dependent variable. The collected data were analyzed using the PASW Statis-tics version 23.0 (IBM Corp., Armonk, NY, USA) pro-gram, with a statistical significance level set at a=0.05.
The results of the comparison of the relationship among metacognition, learning flow, and problem-solving abilities based on the general characteristics of the study partici-pants are presented in Table 3. Commonly, statistically significant differences were observed in metacognition, learning flow, and problem-solving abilities based on ge-neral characteristics such as major satisfaction, subjective academic performance, GPA and reasons for choosing the major (p<0.05).
Difference in Metacognition, Learning Flow, Problem-Solving Ability according to General Characteristics (n=132)
Characteristic | Division | n (%) | Metacognition | Learning flow | Problem-Solving ability | |||||
---|---|---|---|---|---|---|---|---|---|---|
M±SD | t/F (p) | M±SD | t/F (p) | M±SD | t/F (p) | |||||
Age | ≤21 y | 58 (43.9) | 1.94±0.47 | −4.275 (0.995) | 2.00±0.65 | −6.595 (0.006) | 1.99±0.52 | −5.508 (0.199) | ||
>21 y | 74 (56.1) | 2.29±0.48 | 2.66±0.49 | 2.46±0.44 | ||||||
Sex | Male | 13 (9.8) | 2.00±0.52 | −1.048 (0.706) | 2.25±0.61 | −0.699 (0.414) | 2.17±0.57 | −0.579 (0.656) | ||
Female | 119 (90.2) | 2.15±0.50 | 2.38±0.66 | 2.27±0.53 | ||||||
School type | College | 27 (20.5) | 2.12±0.29 | −0.222 (<0.001) | 2.43±0.65 | 0.599 (0.626) | 2.21±0.40 | −0.504 (0.007) | ||
≥University | 105 (79.5) | 2.14±0.55 | 2.35±0.66 | 2.27±0.56 | ||||||
Grade | 2nd | 49 (37.1) | 2.11±0.48 | 0.875 (0.419) | 2.32±0.67 | 0.811 (0.447) | 2.21±0.55 | 1.125 (0.328) | ||
3rd | 65 (49.2) | 2.19±0.51 | 2.44±0.66 | 2.32±0.53 | ||||||
4th | 18 (13.6) | 2.02±0.57 | 2.25±0.59 | 2.14±0.47 | ||||||
Major satisfaction | Very satisfied | 38 (28.8) | 1.83±0.49b | 12.658 (<0.001) | 1.92±0.63b | 15.987 (<0.001) | 1.94±0.53a | 11.307 (<0.001) | ||
Satisfied | 90 (68.2) | 2.25±0.46ab | 2.53±0.58ab | 2.38±0.48a | ||||||
Dissatisfied | 4 (3.0) | 2.52±0.28a | 2.95±0.35a | 2.46±0.19a | ||||||
Very dissatisfied | 0 (0.0) | - | - | - | ||||||
Subjective academic performance | Excellent | 33 (25.0) | 2.00±0.60b | 3.876 (0.011) | 1.98±0.67c | 15.676 (<0.001) | 2.03±0.64b | 6.233 (0.001) | ||
Good | 63 (47.7) | 2.10±0.48b | 2.28±0.56bc | 2.22±0.50ab | ||||||
Moderate | 30 (22.7) | 2.26±0.38ab | 2.81±0.46ab | 2.50±0.33ab | ||||||
Poor | 6 (4.5) | 2.67±0.38a | 3.17±0.47a | 2.67±0.32a | ||||||
Very poor | 0 (0.0) | - | - | - | ||||||
GPA | ≥4.0 | 43 (32.6) | 1.78±0.30b | 22.481 (<0.001) | 1.89±0.52c | 27.275 (<0.001) | 1.84±0.33b | 28.753 (<0.001) | ||
≥3.0 to <4.0 | 85 (64.4) | 2.30±0.50a | 2.56±0.57b | 2.46±0.49a | ||||||
≥2.0 to <3.0 | 4 (3.0) | 2.58±0.28a | 3.32±0.50a | 2.56±0.34a | ||||||
<2.0 | 0 (0.0) | - | - | - | ||||||
Reason for major choice | Based on academic performance | 9 (6.8) | 2.01±0.48b | 22.594 (<0.001) | 2.25±0.70b | 16.165 (<0.001) | 2.15±0.46bc | 24.246 (<0.001) | ||
Based on the recommendation of others (parents or teachers) | 23 (17.4) | 2.70±0.49a | 2.96±0.57a | 2.83±0.41a | ||||||
Due to high employment prospects after graduation | 56 (42.4) | 2.17±0.39b | 2.45±0.58b | 2.31±0.45b | ||||||
Because it seemed suitable for my aptitude | 44 (33.3) | 1.83±0.39b | 1.97±0.51b | 1.91±0.41c | ||||||
Other | 0 (0.0) | - | - | - |
By t-test or one-way ANOVA.
GPA: grade point average, M: mean, SD: standard deviation.
a,b,cDifferent letter indicates are significant differenceat a=0.05 by Scheffe test.
Differences in metacognition based on general charac-teristics were found to be statistically significant for school type, major satisfaction, subjective academic performance, GPA and reasons for choosing the major (p<0.05).
Differences in learning flow based on general characte-ristics were found to be statistically significant for age, major satisfaction, subjective academic performance, GPA and reasons for choosing the major (p<0.05).
Differences in problem-solving abilities based on general characteristics were found to be statistically significant for school type, major satisfaction, subjective academic perfor-mance, GPA and reasons for choosing the major (p<0.05).
The analysis of the correlation among metacognition, learning flow, and problem-solving abilities in dental hygiene major students revealed statistically significant relationships (p<0.05). Metacognition (r=0.88, p<0.01) and learning flow (r=0.82, p<0.01) demonstrated significant positive correlations with problem-solving abilities (Table 4).
Correlations between Metacognition, Learning Flow and Problem-Solving Ability
Coefficient | Metacognition | Learning flow | Problem-solving ability |
---|---|---|---|
Metacognition | 1 | ||
Learning flow | 0.79 |
1 | |
Problem-solving ability | 0.88 |
0.82 |
1 |
By person’s correlation analysis at a=0.05, **p<0.01.
Multiple regression analysis was conducted with problem- solving ability as the dependent variable and metacogni-tion and learning flow as independent variables (Table 5). The Durbin-Watson test resulted in a value of 2.333, which is close to 2, indicating that the multiple regression model is appropriate. Furthermore, the tolerance and variance inflation factor for all variables were between 0.1 and 10, confirming that there was no issue of multicollinearity, and the regression model was statistically significant (F=290.146, p<0.001).
Factor related to Problem-Solving Ability
Factor | B | SE | b | t | p | Multicollnearity | |
---|---|---|---|---|---|---|---|
Tolerance | VIF | ||||||
(constant) | 0.229 | 0.087 | 2.632 | 0.010 | |||
Metacognition | 0.664 | 0.064 | 0.633 | 10.416 | <0.001 | 0.381 | 2.622 |
Learning flow | 0.257 | 0.049 | 0.318 | 5.223 | <0.001 | 0.381 | 2.622 |
R=0.905, R2=0.818, adjusted R2=0.815, F=290.146, p<0.001, Durbin-Watson=2.333 |
By multiple regression analysis at a=0.05.
VIF: variance inflation factor.
The analysis results revealed that both metacognition and learning flow had statistically significant positive effects on problem-solving ability (adjusted R2=0.815, p<0.05). In conclusion, it was found that problem-solving ability increa-ses as metacognition and learning flow levels increase.
In this study, we assessed the levels of metacognition, learning flow, and problem-solving ability among dental hygiene major university students. We analyzed data from 132 participants who were in their 2nd, 3rd, and 4th years of study to examine the impact of metacognition and lear-ning flow on problem-solving ability. The study uncovered key factors affecting problem-solving skills, indicating that both metacognition and learning flow significantly contri-buted to a positive impact, explaining 81.5% of the variance.
The levels of metacognition, learning flow, and pro-blem-solving ability in this study were as follows: meta-cognition 2.14±0.51, learning flow 2.37±0.65, and problem- solving ability 2.26±0.53 (Table 1). When compared to prior studies targeting engineering freshmen, where meta-cognition was at 3.14±0.41, flow was at 3.20±0.53, and problem-solving ability was at 3.19±0.38, it appears that the average scores of dental hygiene students in this study were significantly lower27). Additionally, in a study con-ducted with fourth-year nursing students, metacognition was at 3.32±1.31, learning flow was at 2.93±0.09, and problem-solving ability was at 3.37±0.0614). Once again, the scores of dental hygiene students in this study seem to be lower. Furthermore, in a study involving dental hygiene students from the first to the third year, metacognition was at 4.43±0.76 on a 7-point scale, and problem-solving abi-lity was at 2.82±0.54 on a 5-point scale28). When compared to these results, it is evident that the participants in this study had lower average scores. Since this study focused on second, third, and fourth-year students, excluding fre-shmen, it may be challenging to make direct comparisons with studies targeting engineering freshmen or fourth-year nursing students. Therefore, it may be beneficial to com-pare the levels of metacognition, learning flow, and pro-blem-solving ability by year. Additionally, considering that metacognition is sometimes measured on a 7-point scale in other studies, it is essential to make comparisons on the same scale for a more accurate assessment.
The general characteristics of the study participants in this research indicated that there was a slight discrepancy between students’ subjective and objective academic per-formance (Table 2). Although 32.6% of students achieved a GPA of 4.0 or higher, only 25.0% perceived their aca-demic performance as excellent subjectively. Conversely, while only 3.0% of students had a GPA between 2.0 and 3.0, 4.5% considered their academic performance to be poor. This can be related to metacognition. Metacognition involves the ability to objectively recognize what one knows and doesn’t know, identify and solve problems indepen-dently, and control the learning process1). In this study, dental hygiene students’ metacognition levels were relatively low, with a mean score of 2.14±0.51. Therefore, it can be inter-preted that their ability to self-assess their academic per-formance was lower, possibly contributing to the observed differences.
The analysis comparing the relationship between meta-cognition, learning flow, and problem-solving abilities based on the general characteristics of the study participants revealed statistically significant differences in metacog-nition, learning flow, and problem-solving abilities for all four factors: major satisfaction, subjective academic per-formance, GPA and reasons for choosing the major (p< 0.05; Table 3).
In the case of major satisfaction, the dissatisfaction group showed significantly higher levels of metacognition and learning flow compared to the very satisfied group (p< 0.05; Table 3). Nam and Kim14) classified major satis-faction into good, moderate, and bad categories, where the good category had higher metacognition and learning flow than the bad category, and the good category had higher problem-solving abilities than the moderate category. This differs from the results of our study. In our study, 97% of the participants were satisfied with their major, while only 3% were dissatisfied. This difference in group size may have influenced the results.
In the case of subjective academic performance, the results indicate that individuals who perceive their grades as poor and those with a previous semester’s GPA below 4.0 tend to have higher levels of metacognition, learning flow, and problem-solving abilities (p<0.05; Table 3). Park and Cho29) found that non-cognitive factors such as grit and subjective grades have a more significant impact on core competencies than cognitive factors like GPA. This suggests that even if actual grades are low, perceiving oneself as having high grades can have a positive influ-ence on core competencies. However, in the current study, it is noted that 97% of the participants had actual grades of 3.0 or above, whereas 72.7% of them perceived their grades as excellent or very excellent. This suggests that the participants in this study tend to perceive themselves as having lower grades than they actually achieve. Jeoun30) conducted a problem-solving-based college life adaptation program and found that college life adaptation, problem- solving abilities, and intrinsic motivation improved, but self-esteem did not show significant improvement. How-ever, it was argued that psychological aspects, such as self- esteem and self-efficacy, need to improve together in order to predict the continuous improvement and maintenance of metacognition. Therefore, in this study as well, it is suggested that additional research is needed to comple-ment psychological and non-cognitive aspects that allow individuals to assess themselves accurately from a lear-ning perspective.
In terms of the reasons for choosing their major, the group that chose their major based on the recommendation of others (such as family or teachers) showed significantly higher levels of metacognition, learning flow and problem- solving abilities compared to the other groups (p<0.05; Table 3). In a study conducted on dental hygiene college students regarding metacognition and problem-solving abilities, it was found that the motivation behind choosing dental hygiene and academic satisfaction had a significant impact on metacognition. However, no significant difference was observed in problem-solving abilities. Among the mo-tivations for choosing dental hygiene, those who wanted to become dental hygienists (4.66±0.70) had the highest meta-cognition scores, while those influenced by recommen-dations from others (4.08±0.81) had the lowest metacog-nition scores28). According to previous research, having a subjective goal of wanting to become a dental hygienist, rather than choosing the field due to recommendations from others, was associated with higher metacognition sco-res. However, in the current study, it was found that those who chose their major based on recommendations from others had higher scores in metacognition, learning flow, and problem-solving abilities. This discrepancy in results may be due to the diverse reasons individuals choose to study dental hygiene, and interpreting these findings solely based on these aspects may be challenging. Therefore, fur-ther research with additional variables is needed to vali-date and better understand these differences.
The dental hygiene students showed significant positive correlations among metacognition, learning flow, and pro-blem-solving abilities (p<0.05; Table 4), which aligns with previous research findings13,14). In other words, it was found that higher levels of metacognition and learning flow were associated with better problem-solving abilities, consistent with the results of previous studies.
The results of the multiple regression analysis con-ducted to identify the factors influencing problem-solving abilities, the dependent variable, showed that both meta-cognition and learning flow had significant positive effe-cts. Moreover, it was found that metacognition had a greater impact on problem-solving abilities compared to learning flow (adjusted R2=0.815, p<0.05; Table 5). It’s interesting to note that the findings of this study regarding the impact of metacognition and learning flow on pro-blem-solving abilities align with the results of Oh and Kang’s study13), which showed that only learning flow influenced problem-solving abilities. Similarly, Jeoun’s study30) also found that learning flow, metacognition, and subjective grades were factors affecting problem-solving abilities, which is consistent with the results of this study. On the other hand, Jun et al.’s study28) reported no correlation between metacognition levels and problem-solving abi-lities among dental hygiene college students, which differs from the findings of this study. These discrepancies might be attributed to differences in the study populations, me-thods, or other variables, and they highlight the comple-xity of understanding the relationships between metacog-nition, learning flow, and problem-solving abilities. Fur-ther research may be needed to explore these discrepancies and potential contributing factors. Indeed, as indicated by previous research, there is a wide range of teaching and learning methods being employed to enhance problem- solving abilities. However, the diversity in research fin-dings suggests the need for the development of effective pedagogical strategies aimed at improving problem-sol-ving abilities. Moreover, it is important to validate the effectiveness of these strategies when applied in the con-text of dental hygiene education. The field of dental hy-giene may benefit from tailored approaches that align with the specific demands and challenges of the discipline. Conducting research to assess the impact of these teaching methods on problem-solving abilities in dental hygiene students would be a valuable endeavor, potentially leading to more targeted and effective educational practices in this field. Such research could contribute to the continuous improvement of dental hygiene education and ultimately enhance the quality of care provided by future dental hygienists. Meanwhile, Kahney31) explained that metacog-nition is encompassed within problem-solving, and Heppner and Petersen3) as well as Kapa32) have demonstrated a strong correlation between problem-solving ability and metacognition, describing metacognition as a subcompo-nent of problem-solving abilities. In Jeoun’s study30), it was also argued that metacognition is not a separate element from problem-solving but rather an essential strategic com-ponent within problem-solving abilities. When compared to these previous studies, the current research findings align with the idea that metacognition significantly influ-ences problem-solving abilities.
In conclusion, it was confirmed that metacognition and learning engagement significantly influence the problem- solving abilities of dental hygiene students.
To enhance the core competency of problem-solving abilities, it is essential to improve metacognition and lear-ning flow. This can provide efficient and effective learning experiences, as well as sustain motivation and interest in continuous learning. To enhance metacognition and pro-mote learning flow, strategies such as goal setting, utili-zing effective learning methods, boosting self-efficacy, managing the learning environment, choosing activities that foster immersion, stress management, self-assessment and feedback integration, improving focus, and utilization a variety of learning experiences will be necessary.
The limitations of this study include the diverse tools used to measure metacognition, learning flow, and problem- solving abilities. Particularly, the scale points for meta-cognition varied between 7-point and 5-point scales. Add-itionally, there is a scarcity of research in the dental hygiene field that addresses metacognition, learning flow, and problem-solving abilities together, which posed limi-tations when comparing the results of this study with exi-sting literature. Future research should consider a more extensive and diverse sample of dental hygiene majors, aiming to investigate differences in results among various sub-factors.
Additionally, it should be noted that the study was con-ducted on a limited and unspecified number of participants for the purpose of this research, which may affect the generali-zability of the results. Therefore, further research should con-sider conducting comparative analyses between students from institutions that implement PBL and those that do not, to pro-vide a more comprehensive understanding of the outcomes.
Nevertheless, despite these limitations, it is evident that universities need to develop diverse educational courses and tailored programs to match the characteristics of their target audience for the advancement of the university and the support and management of adult learners. Furthermore, the significance of this study lies in the confirmation that meta-cognition and learning flow are essential for enhancing problem-solving abilities and sustaining academic perfor-mance and management among dental hygiene majors.
None.
Conflict of Interest
No potential conflict of interest relevant to this article was reported.
Ethical Approval
This study was approved by the Namseoul University Bioethics Review Committee (IRB NSU-202307-004).
Funding
None.
Data availability
Please contact the corresponding author for data availability.
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