Conference PaperPDF Available

Identifying Emotional Intelligence and Metacognitive Awareness among University Students

Authors:

Abstract and Figures

The aim of this study was to research the attitude between emotional intelligence and metacognitive awareness in a group of university students. The participants were 178 students from the departments of the Psychology and Biology of Saint-Petersburg University. There were using questionnaire: EmIn Questionnaire by Lyusin D., Metacognitive Awareness Inventory (MAI) by Schraw G. & Dennison R.S. adapted in Russian by A. Karpov & I. Skityaeva, the Self-organization of Activity Questionnaire by E. Mandrikova, The differential reflectivity test by D.A. Leontiev and E. N. Osin. Means, standard deviations, regression, correlation, factor analysis were used to analyze the data. Results indicated a significant positive correlation between emotional intelligence (EI) subscales ("Interpersonal EI", "Intrapersonal EI", "Emotion Comprehension", "Emotion Comprehension") and metacognitive awareness. The results of multiple regression analysis using meta-cognition as predicted to subscale "Interpersonal EI" and "Systemic reflection". These results mean that the Metacognitive knowledge and Metacognitive regulation is influenced by the ability to understand and control other people's emotions of the university students. The strength of the correlation indicates that a generally high level of metacognitive awareness is related to a high level of emotional intelligence.
Content may be subject to copyright.
Identifying Emotional Intelligence and Metacognitive
Awareness among University Students
2
, Byzova Valentina M.
1
Perikova Ekaterina I.
Saint-Petersburg University 1,2
ABSTRACT
The aim of this study was to research the attitude between emotional intelligence and
metacognitive awareness in a group of university students. The participants were 178 students
from the departments of the Psychology and Biology of Saint-Petersburg University. There were
using questionnaire: EmIn Questionnaire by Lyusin D., Metacognitive Awareness Inventory (MAI)
by Schraw G. & Dennison R.S. adapted in Russian by A. Karpov & I. Skityaeva, the Self-organization
of Activity Questionnaire by E. Mandrikova, The differential reflectivity test by D.A. Leontiev and
E. N. Osin. Means, standard deviations, regression, correlation, factor analysis were used to
analyze the data. Results indicated a significant positive correlation between emotional
intelligence (EI) subscales (“Interpersonal EI”, “Intrapersonal EI”, “Emotion Comprehension”,
“Emotion Comprehension”) and metacognitive awareness. The results of multiple regression
analysis using meta-cognition as predicted to subscale “Interpersonal EI” and “Systemic
reflection”. These results mean that the Metacognitive knowledge and Metacognitive regulation
is influenced by the ability to understand and control other people's emotions of the university
students. The strength of the correlation indicates that a generally high level of metacognitive
awareness is related to a high level of emotional intelligence.
This work was supported by RFBR Grant 18-013-00256А.
Keywords: meta-cognition, interpersonal emotional intelligence, reflectivity, self-organization of
activity.
Introduction
Emotional Intelligence
Emotional intelligence (hereafter EI) is one of the most recently defined categories of intelligence
in the field of psychology. The popularity of EI research relates to the concept of intelligence (IQ).
Studies of intelligence show that high IQ level by itself could not ensure success in every aspect
of life (Dulewicz & Higgs, 2000). This fact gives an opportunity for EI research. According to the
literature, EI has become one of the major evaluation targets for an individual’s workplace
outcomes including successes and failures. This has been especially valued in business over the
past 20 years. American psychologists Salovey and Mayer were the pioneers in the study of EI
(Hahn at all., 2013). They distinguished EI as the factor of ‘social intelligence’ which has been also
defined as the ability to understand and manage people (Salovey & Mayer, 1990). Nowadays EI
has different definitions in conceptualizing EI, which was analyzed by Gayathri and Meenakshi
(2013). The most popular definition is how an individual manages his/her own emotions and the
emotions of others. Gayathri and Meenakshi (2013) believed the concept of EI needs to be
researched more thoroughly in order to repel the challenges to its efficacy as a concept. The
authors addressed the need for simplified definitions and approaches used to correctly evaluate
the emotional skill set of a person.
In this study, we use the definition, that EI is an ability for management and comprehension
of one’s own and other’s emotions. Lusin (2006, 2014) describe EI, as cognitive ability and does
not include it in a personal structure. Personality traits could influence emotional understanding,
but personality traits are not the components of emotional understanding. EI includes
Interpersonal EI, Intrapersonal EI, Emotion Comprehension, Emotion Management.
MetaCognition
The first appearance of the concept of metacognition and its entrance into the field of cognitive
psychology was through the work of John Flavell at the beginning of the 1970s (Flavell, 1976).
Metacognition is defined as an activity of monitoring and controlling one’s cognition (Yong & Fry,
2008). It can further be defined as what we know about our cognitive processes and how we use
these processes in order to learn and remember (Ormrod, 2004). The main function of
metacognition is the regulation of cognitive processes using knowledge of cognitive patterns.
Researchers further conceptualize metacognition by breaking down metacognition into two
subcomponents: metacognitive knowledge and metacognitive regulation (Weinert & Kluwe,
1987; Schraw & Dennison, 1994).
Metacognitive knowledge includes the reflexive understanding of the learning process and the
role of the subject. There are three types of metacognitive knowledge: declarative, procedural
and conditional (Schraw & Dennison, 1994; Schraw & Moshman, 1995). Shraw and Moshman
describe declarative knowledge as “knowledge about things”, procedural knowledge as “know
how to do things” and conditional knowledge as “knowledge about why and when to do
something” (Schraw & Moshman, 1995). Metacognitive awareness (hereafter MA) is needed in
order to have insight into metacognitive functioning at the conscious level (Duffy et al., 2015) The
expression of insight during these life situations reinforces the metacognitive skill.
Kholodnaya identified three levels of mental experience: cognitive, metacognitive and intentional
(Kholodnaya, 2012). According to her, MA is knowledge about self-intelligent and self-cognitive
resources, as a component of a self-determination potential. Rasshchepkina showed that MA is
a component of the self-regulation system of self-determination, as well as a component of
"metacognitive experience" (Rasshchepkina, 2015). Therefore, MA is an individual resource for
self-regulation of actions and decisions
Karpov defines metacognition as the leading form of the reflexive regulation of cognitive activity
(Karpov, 2018). The author suggests that the main function of metacognition is self-regulation,
and the main form of self-regulation is self-organization.
MA allows a person to plan, monitor and control the process of their own cognitive activities
(Schraw & Dennison, 1994). MA is one of the key elements necessary for the development of
student autonomy and independence. The results of the study showed the dependency between
individual metacognitive processes with intelligence (IQ) and learning as well as the dependency
between the level of development of intelligence (IQ) and the structural organization of
metacognitive processes (Wilson & Bai, 2010; Kelly & Ku, 2010).
Statement of the Problem
Practical results of research into MA and EI could be useful in the optimization of learning
activities. Individually, EI and metacognition have appeared in the general literature and have
been described as a mature topic for over 40 years (Torraco, 2005). The studies of Shields (2010)
and Wheatley (1999) explore the integrative relationship between EI and metacognition. The
integrative, review of typology, in particular the synthesis of the literature, identifies a convincing
argument to pursue the need for additional research into the influence of EI and metacognition.
University students use metacognitive strategies and skills, which they gain in High School and
form new ones (Ohtani & Hisasaka, 2018). By the end of their stay at University, students possess
improved self-organization and learning skills, creativity, and practical activities. EI also relates to
stress among students (Arora et al., 2011). Students of the medical university who achieved
higher EI scores were found to experience higher stress during passing “unfamiliar surgical
scenario-tasks” but were also more likely to be able to respond better after the surgical task was
completed than their peers with lower EI (Arora et al., 2011).
Empirical studies have shown that the development of self-regulation and metacognitive abilities
of students is one of the most significant factors affecting academic performance (Sellen et all.,
1997). Students with the high level of MA are more successful in learning activities (Wilson &, Bai,
2010), as well as in decision making in general because they are aware of effective learning
strategies. Despite the enormous information that experience sampling methodology provides
to us, not much is known about how individual differences in EI are reflected in MA.
The study aimed at answering the following question: Is there a significant relationship between
students’ EI and their metacognition?
Methods
Participants
The population of this study consisted of 178 students enrolled in Saint-Petersburg State
University (SPbU), departments of the Psychology and Biology in the academic
year 2017/2018, and represented the second level of study. A sample of 30 males and 148
females students were chosen from the population with an age range of 18-22 years.
Instruments
Four instruments were used in the study (A), (B), (C) and (D).
(A) The Russian EI questionnaire (EmIn) developed by Lyusin (2006)
It consists of 46 items with a 4-point Likert scale response format, ranging from “completely
disagree” to “completely agree”. These items form four questionnaire scales: Interpersonal EI
(e.g., “I understand other people’s inner states without words”); Intrapersonal EI (e.g., “I know
what to do to improve my mood”); Emotion Comprehension (e.g., “Often, I can’t find the words
to describe my feelings to my friends”); Emotion Management (e.g., “If I hurt somebody’s
feelings, I don’t know how to restore a good relationship with them”); and Control of Expression
(e.g., “I could control my emotional behavior). The aggregate score of these scales provides the
assessment of General EI. The Cronbach’s alphas of the EmIn scales were reported to range from
0.84 to 0.89 (Lyusin & Ovsyannikova, 2015).
(B) Metacognitive Awareness Inventory (MAI) developed by Schraw and Dennison (1994) and
adapted in Russian by Karpov and Skityaeva (2005)
The MAI consists of 52 items rated on a five-point Likert scale. Both components of metacognition
(metacognitive knowledge and metacognitive regulation) are represented. There is only an MAI
total score of metacognitive awareness in the Russian variant of inventory. Higher scores
correspond to greater metacognitive knowledge and regulation.
The Self-Organization of Activity Questionnaire developed by Mandrikova with the
Purposefulness Index and Rationality Index (Mandrikova, 2007)
The scale is used for diagnosing the maturity of tactical planning and strategic goal-setting skills.
The questionnaire was made on the basis of the Time Structure Questionnaire TSQ (Bond &
Feather, 1988; Feather & Bond, 1983). There are questionnaire scales: “Presence of Purpose”,
"Persistence" scales, “Planning”, "Fixation", “Purposefulness”, "Self-Organization" scales and the
total score of Self-Organization of Activity. The Self-Organization of Activity Questionnaire
consists of 25 items rated on a seven-point Likert scale.
(C) Differential reflexivity test (DTR) constructed by Leontiev and Osin (2014)
This includes a 30-item questionnaire using a 4-point response scale, operationalizing Leontiev’s
3-component model of reflexive processes. According to the model, systemic reflection (a
tendency to look at oneself within the context of situations and life in general) is a productive
form of reflection conducive to dialogue with the world. DTR includes three scales: systemic
reflection; introspection; and quasi-reflection.
In this prospective study, these concepts were examined as integrated concepts of research of
integration between EI and metacognition. All quantitative data were analyzed using IBM SPSS
Statistics for Windows, version 19.
Procedures
The instruments were presented to the participants in their regular classrooms by the
researchers who explained the purpose and procedures involved and assured the participants of
anonymity, stressing the confidentiality of their responses, which would be used solely for
research purposes. The question booklets were distributed and participants instructed in how to
complete them. On completion, the participants’ responses were scored by the researchers and
entered into the computer for statistical analysis.
Results
At the first stage of the study, we calculated mean values of EI, metacognition, self-organization
of activity and reflexivity. Good scores obtained from all sub-scales of EI, including the
metacognition scale, the self-organization of activity and differential reflexivity.
Table 1. Descriptive Statistics of parameters of EI, metacognition, self-organization of activity and
reflexivity (n=178)
Instruments
Parameters
Mean
Standard
Deviation
EmIn
Interpersonal EI
45,82
10,58
Intrapersonal EI
38,01
8,98
Emotion
Comprehension
43,13
9,84
Emotion
Management
40,17
8,72
Control of Expression
9,73
3,85
MAI
Metacognitive
Awareness
192,06
29,84
DTR
Systemic reflection
39,97
5,69
Introspection
25,67
5,89
Quasi-reflection
26,85
6,10
The Self-
Organization
of Activity
Questionnaire
Planning
17,52
5,45
Purposefulness
30,06
6,95
Persistence
18,91
6,70
Fixation
18,97
5,07
Self-Organization
10,12
3,93
Presence of Purpose
7,91
2,95
Total score of Self-
Organization of
Activity
103,20
17,94
Note: * EmIn scoring ranges: Interpersonal EI: 42,9±6,72. Intrapersonal EI: 42,2±8,25. Emotion
Comprehension: 43,1±7,14. Emotion Management: 42,0±7,63. Control of Expression: 10,1±3,14.
* MAI scoring ranges: 197,12±31,27
* DTR: Systemic reflection: 39,58±5,15. Introspection: 25,11±5,68. Quasi-reflection: 27,39±5,69.
* The Self-Organization of Activity Questionnaire: Planning: 17,1±5,71. Purposefulness:
32,8±7.04. Persistence 21,2±5,89. Fixation 20±5,47. Self-Organization±8,53±4,48. Presence of
Purpose 8,90±2,87. Total score of Self-Organization of Activity 108,5±17,3.
To explore the relationship between EI, metacognition, self-organization of activity and reflexivity
the correlation coefficients (Pearson’s rank) were calculated and demonstrated in table 2.
Table 2. Correlation between EI, metacognition self-organization of activity and reflexivity
(n=178)
Systemic
reflection
Quasi-
reflection
Purposefulness
Intrapersonal EI
0,218**;
-0,172*;
0,221**;
0,004
0,021
0,003
Interpersonal EI
0,220**;
0,003
-0,316**;
0,000
0,233**;
0,002
0,208**;
0,005
Emotion
Comprehension
0,251**;
0,001
-0,181*;
0,016
0,211**;
0,005
0,328**;
0,000
Emotion
Management
0,231** ;
0,002
-0,295**;
0,000
0,293** ;
0,000
0,283**;
0,000
Table 2 shows that all components of EI (intrapersonal EI, interpersonal EI, emotion
comprehension, emotion Management) are positively related to the reflection, purposefulness
and MA (p≤0.005) and negatively related to the quasi-reflection (p<0.05).
Table 3 shows the results of multiple regression analysis using metacognition as predicted to EI.
Table 3. Results of regression analyses predicting scores of metacognition EI
Metacognition
EI, self-organization of
activity and reflexivity
R
F
β
T
MA
Interpersonal EI of
0,422
0,178
4,277
0,284
4,002
Quasi-reflection of
-
0,236
-
3,375
Systemic reflection
0,148
2,068
The results given in table 3 showed that the interpersonal EI, quasi-reflection and systemic
reflection were significant predictors of MA (R²=0.175, F=4.277, p=0.05). These results were
supported by the close moderate correlation between the third variables (r=0.671).
Approximately 17.8% of the variance of the student’s emotional knowledge was accounted for
by metacognition.
Table 4. Factor analysis: rotated factor matrix
Factors
1
2
3
4
Emotion Management
0,872
Emotion Comprehension
0,825
Interpersonal EI
0,775
0,554
Intrapersonal EI
0,772
-0,441
Metacognitive Awareness
0,440
Total score of Self-Organization of Activity
0,812
Planning
0,706
Fixation
0,552
Purposefulness
0,440
0,518
Self-Organization
0,491
Control of Expression
-0,604
Quasi-reflection
0,679
Introspection
0,612
Introspection
0,445
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. 0,604
Bartlett's Test of Sphericity Approx. Chi-Square 2317,162
df 190
Sig. 0,000
Factor analysis led to the identification of some latent variables (factors) which explain the links
between the questionnaires. After a varimax rotation, the 3 extended factors can be labels as
follows: emotional self-control and self-awareness; self-organization of activity; interpersonal EI,
reflexivity.
The first-factor includes the scale of EI, MA, and scale of self-organization of activity
(“Purposefulness”). The second factor refers to scales of Self-Organization of Activity: „Total score
of Self-Organization of Activity“, „Planning”, “Fixation”, “Purposefulness”, “Self-Organization”.
The third factor is a binary scale “Interpersonal EI” “Intrapersonal EI”. Finally, scales of
Differential reflexivity test have formed factor Reflexivity.
Discussion
The concept of metacognition was introduced by Flavell in 1976 and his definitions of the main
elements of the concept are still in use (Kelly & Ku, 2010; Martinez & Davalos, 2016; Mahasneh
2014). Data about the relationship between metacognition and emotion are unfortunately
limited and focused almost exclusively on psychopathology and medicine (Matthews & Wells,
2004; Wells, 2000; Weng et al., 2011). The primary aim of this research was to investigate the
interconnection between EI and metacognition of university students. The results indicated that
all EI components are related positively to MA.
Results of our study mean that a generally higher level of MA, systemic reflection and
purposefulness are related to a higher level of EI. The process by which an individual manages
his/her own emotions and the emotions of others is often accompanied by a host of additional
or second order thoughts relevant for perceiving, metacognition and self-organization. A higher
level of quasi-reflection is associated with lower levels of EI.
Metacognition thoughts can play an important role in understanding psychological processes
relevant to EI. Our findings matched up with other results (Alavinia & Mollahossein, 2012) which
found a positive relationship between learners’ EI and their use of metacognitive strategies.
Sharei et al (2012) found that metacognition and EI contribute significantly to the prediction of
problem-solving ability. Our results are comparable with Pluzhnikov’s theoretical conception
which describes EI like a metacognitive ability: “EI is a special metacognitive ability, which consists
of a hierarchy of organized abilities of perception, understanding, and regulation of emotions in
different life situations” (Pluzhnikov, 2010).
The indicator of MA revealed a connection with the scales of self-organization of activity, which
could mean that MA has a function which reflects its role in the target self-regulation.
Understanding one’s own goals and setting them in accordance with the available opportunities
helps one to achieve results (Perikova & Bysova, 2018).
Conclusion
Results of our study mean that the regulation, monitoring, and control of cognitive activities are
influenced by the EI of university students.
From a theoretical standpoint, the following line of research is suggested for the future: (a) The
university needs to intensify its role in increasing the effectiveness of students’ metacognition
skills through training programs. (b) The researchers are recommended to conduct further
studies in a different university.
Acknowledgment
This paper was supported by RFBR Grant 18-013-00256А.
References
[1] Alavinia, P. and Mollahossein, H. (2012). On the Correlation between Iranian EFL Learners’ Use
of Meta-cognitive Listening Strategies and Their Emotional Intelligence, International
Education Studies, vol. 5, pp. 189-203.
[2] Arora, S., Russ, S., Petrides, K. V., Sirimanna, P., Aggarwal, R., Darzi, A., & Sevdalis, N. (2011).
Emotional Intelligence and Stress in Medical Students Performing Surgical Tasks, Academic
Medicine, vol. 86, pp.1311-1317.
[3] Bond, M.J. and Feather N. T. (1988). Some Correlates of Structure and Purpose in the Use of
Time, Journal of Personality and Social Psychology. vol. 55, pp. 321-329.
[4] Duffy, M.C., Azevedo, R., Sun, N. Z., Griscom, S.E., Stead, V., Crelinsten, L., Wiseman, J.,
Manlatis, T. and Lachapelle, K. (2014). Team regulation in a simulated medical emergency: an
in-depth analysis of cognitive, metacognitive, and affective process? Instructional Science, vol.
43, pp. 401-426.
[5] Dulewicz, F. and Higgs, M. (2000). Emotional Intelligence: A Review and Evaluation Study,
Journal of Managerial Psychology, vol. 15, pp. 341-372.
[6] Feather N. Т. and Bond M.J. (1983). Time Structure and Purposeful Activity Among Employed
and unemployed university graduates, Journal of Occupational Psychology, vol. 56, pp. 241-
254.
[7] Flavell, J. H. (1976). Meta-cognitive Aspects of Problem Solving. In L. B. Resnick (Ed), The Nature
of Intelligence. Hillsdale, NJ: Erlbaum
[8] Gayanthri, N. and Meenakshi, K. (2013). A literature review of emotional intelligence,
International Journal of Humanities and Social Science Invention. vol. 2. 3, pp. 42-51.
[9] Hahn M.H., Choi D.Y. and Lee K.C. (2013). An Empirical Analysis of the Effect of Social and
Emotional Intelligence on Individual Creativity Through Exploitation and Exploration, Digital
Creativity. Integrated Series in Information Systems, vol 32. NY.: Springer.
[10] Karpov, A.V. (2018). Metasystem organization of individual qualities of personality,
Yaroslavl.: P.G. Demidov Yaroslavl State University. (In Russian).
[11] Karpov, A.V. and Skityaeva, I.M. (2005). Psychology of metaсognitive Personality Processes,
Мoscow: Institute of psychology Russian academy of sciences. (In Russian).
[12] Kelly, Y. L. and Ku, I.T. (2010). Metacognitive strategies that enhance critical thinking,
Metacognition and Learning, vol. 5, pp. 251267.
[13] Kholodnaya M.A. (2002). The Psychology of Intellect: Paradoxes in Research. St. Petersburg:
Peter. (In Russian).
[14] Leontiev, D.A. and Osin, Y.N. (2014). ”Good” and ”bad” reflection: from the explanatory
model to the differential diagnosis, Psychology. Journal of Graduate School of Economics, vol.
11, pp. 110-135. (In Russian).
[15] Lyusin, D. (2006). A new measure for emotional intelligence: EmIn Questionnaire,
Psikhologicheskaya Diagnostika, vol 4, pp. 322. (In Russian).
[16] Lyusin, D. (2014). A self-report measure for assessment of emotional states. Thinking and
speech: approaches, problems, and decisions. Proceedings of the 15th Vygotsky readings, vol.
1, pp. 140 - 143. (In Russian).
[17] Lyusin, D., and Ovsyannikova, V.V. (2015). Relationships between Emotional Intelligence,
Personality Traits and Mood. Psychology Journal of the Higher School of Economics, vol. 12, pp.
154164. (In Russian).
[18] Mahasneh A. M. (2014). Investigating the Relationship between Emotional Intelligence and
Meta-Cognition among Hashemite University Students, Review of European Studies, vol. 6, pp.
201-208.
[19] Mandrikova, Е.Yu. (2007). The Self-Organization of Activity Questionnaire, Мoscow: Smysl.
(In Russian).
[20] Martinez, S. and Davalos, D. (2016) Investigating metacognition, cognition, and behavioral
deficits of college students with acute traumatic brain injuries, Journal of American College
Health. vol. 64. №5. pp.1-7.
[21] Ohtani, K. and Hisasaka, T. (2018) Beyond intelligence: a meta-analytic review of the
relationship among metacognition, intelligence, and academic performance, Metacognition
and Learning. vol. 13. № 2. pp. 179–212.
[22] Ormrod, J.E. (2004). Human Learning. Upper Saddle River, NJ: Pearson Prentice Hall.
[23] Papageorgiou C. and Wells A. (2004). Depressive rumination: Nature, theory and
treatment. Chichester, UK: Wiley.
[24] Perikova, E.I. and Bysova, V.М. (2018). Metacognition strategies in overcoming difficult life
situations with the main focus on different levels of personal self-regulation, Novosibirsk State
Pedagogical University Bulletin, vol. 8, pp. 41-56. (In Russian).
[25] Pluzhnikov, I.V. (February 2019). Emotional Intelligence in Affective Disorders. dissertation
abstract for the degree of candidate of psychological sciences [Online] Available:
http://www.psy.msu.ru/science/autoref/pluzhnikov.pdf. (In Russian).
[26] Rasshchepkina, N.А. (2015). Common cultural competences as components of the
innovation potential of a technical university student, The Scientific Opinion. vol. 4, pp.22-28.
[27] Salovey, P. and Mayer, J. D. (1990). Emotional intelligence, Imagination, Cognition, and
Personality, vol. 9, pp. 185211.
[28] Schraw G. and Dennison R. S. (1994). Assessing metacognitive awareness, Contemporary
Educational Psychology, vol. 19. pp. 460-475.
[29] Schraw G. and Moshman D. (1995). Metacognitive Theories, Educational Psychology
Review, vol. 7. pp. 351-371.
[30] Sellen, A.J., Louie, G., Harris, J.E. and Wilkins, A.J. (1997). What brings intentions to mind?
An in situ study of prospective memory, Memory, pp. 483-507.
[31] Sharei, M., Kazemi, F. and Jafari, M. (2012). Investigation the effect of emotional
intelligence skills and meta-cognitive capabilities on student’s mathematical problem solving.
Educational Research, vol. 3, pp. 844-850.
[32] Torraco, R.J. (2005). Writing Integrative Literature Reviews: Guidelines and Examples.
Human Resource Development Review, vol. 4, pp. 356-367.
[33] Weinert, F.E. and Kluwe, R.H. (1987). Metacognition, motivation, and understanding,
Hillsdale, NJ: Lawrence Erlbaum.
[34] Wells, A. (2000). Emotional Disorders and Meta-cognition. New York: Wiley.
[35] Wilson N. S. and Bai, H. (2010) The relationships and impact of teachers’ metacognitive
knowledge and pedagogical understandings of metacognition, Metacognition and Learning,
vol. 5. pp. 269-288.
[36] Yong, A. and Fry, J., D. (2008) Metacognitive awareness and academic achievement in
college students, Journal of the Scholarship of Teaching and Learning, vol. 8, pp. 1-10.
... Bunun yanı sıra bilişötesinin ve duygusal zekanın biyolojik kökenine yönelik yapılmış çalışmalarda her ikisinde de beynin ön frontal korteksin aktif olduğu bulgulanmıştır(Krueger, ve diğerleri, 2009; Fleming ve Dolan, 2012). Tüm bunlar duygusal zeka ve bilişötesinin birbiri ile ilişkili olduğunu düşündürtmektedir.Bu alanda yapılan çalışmalar incelendiğinde, öğretmen adaylarının bilişötesi farkındalıkları ile duygusal zeka özelliklerini temel alan çalışmaların sınırlı sayıda olduğu görülmektedir(Baş ve Özturan Sağırlı, 2017;Ünlü, Çevik ve Kurnaz, 2016;Byzova ve Perikova, 2019;Wheaton, 2012).Alan yazında yer alan bu sınırlılıktan yola çıkarak bu araştırmada, okul öncesi öğretmenliği lisans eğitimine devam etmekte olan öğretmen adaylarının bilişötesi farkındalıkları ile duygusal zeka özellikleri arasındaki ilişkinin incelenmesi amaçlanmıştır. Bu amaç doğrultusunda "Okul öncesi öğretmen adaylarının bilişötesi farkındalıkları ile duygusal zeka özellikleri arasında anlamlı bir ilişki bulunmakta mıdır?" sorusu araştırmanın temel amacını oluşturmaktadır ve bu temel amaçtan yola Okul öncesi öğretmen adayların duygusal zeka düzeyleri ile duygusal zeka özelliklerine ilişkin bulundukları tahminleri arasında anlamlı bir ilişki bulunmakta mıdır?4.Okul öncesi öğretmen adaylarının bilişötesi farkındalık düzeyleri üniversiteye yerleşme puan türü, sınıf düzeyi üniversite türü ve mezun olunan lise türü değişkenlerine göre farklılık göstermekte midir?5.Okul öncesi öğretmen adaylarının duygusal zeka düzeyleri üniversiteye yerleşme puan türü, sınıf düzeyi üniversite türü ve mezun olunan lise türü değişkenlerine göre farklılık göstermekte Bu araştırma nicel araştırma desenlerinden ilişkisel tarama modeline uygun olarak yürütülmüştür.Korelasyonel çalışmaların; iki veya daha fazla değişkenin arasındaki ilişkinin herhangi bir müdahalede bulunulmadan incelendiği betimsel araştırmaların bir türü olması nedeni ile(Büyüköztürk, Kılıç Çakmak, Akgün, Karadeniz ve Demirel, 2017) öğretmen adaylarının bilişötesi farkındalıkları ile duygusal zeka özellikleri arasındaki ilişkinin incelenmesinin amaçlandığı bu çalışmada bu araştırma modelinden yararlanılmıştır. ...
Article
Bu araştırmanın amacı okul öncesi öğretmen adaylarının bilişötesi farkındalıkları ile duygusal zeka özellikleri arasındaki ilişkinin incelenmesidir. Nicel araştırma yöntemlerinden, ilişkisel tarama modeli kullanılmıştır. Araştırmanın çalışma grubunu, devlet ve vakıf üniversitelerinde okul öncesi öğretmenliği lisans eğitimine devam etmekte olan 244'ü kız 16'sı erkek ve cinsiyetini belirtmeyen bir kişi olmak üzere toplam 261 öğretmen adayı oluşturmaktadır. Öğretmen adaylarını bilişötesi farkındalıklarını ölçmek amacıyla Bilişötesi Farkındalık Envanteri ve duygusal zeka özelliklerini ölçmek amacıyla Duygusal Zeka Özelliği Ölçeği kullanılmıştır. Yapılan analizlere göre bilişötesi farkındalıkları ve duygusal zeka puanlarının sınıf düzeyi, üniversite türü ve mezun olunan lise türü değişkenlerine göre farklılaşmadığı, üniversiteye yerleşilen puan türü değişkenine göre farklılaştığı görülmüştür. Korelasyon analizleri sonucuna göre; bilişötesi farkındalıkları ve duygusal zeka özellikleri arasında ve okul öncesi öğretmen adaylarının bilişötesi farkındalıkları ile duygusal zeka özellikleri düzeylerinin bilişötesi farkındalıkları ile duygusal zeka özelliklerine ilişkin algıları arasında pozitif yönlü anlamlı bir ilişki olduğu ortaya çıkmıştır.
... From a more general perspective of the topic under review, MacCann et al. (2020) and Perikova and Byzova (2019) explored the relationships between EI and academic performance and between EI and metacognitive awareness, respectively. Both studies found positive associations between EI and the respective variables (academic performance and metacognitive awareness). ...
Article
Full-text available
Although emotional intelligence (EI) and metacognitive strategies have been addressed by different researchers across the globe, the relationship between EI and the use of metacognitive reading strategies by L2 learners needs further exploration. To fill this gap, at least partially, the present study investigated the relationship between emotional intelligence and the use of metacognitive reading strategies by EFL learners. Based on the convenience sampling method, 119 Iranian EFL learners across the age range of 18-27 were selected as the earlier subjects. These subjects were then homogenized through the administration of the PET reading test, which reduced the number of the participants to 102 intermediate EFL. The main instruments included Bar-On's (1997) Emotional Intelligence Questionnaire and Mokhtari and Sheorey’s (2002) Survey of Reading Strategies Questionnaire (SORS) that measured metacognitive reading strategies use. The results revealed a moderate and positive correlation between a) emotional intelligence and the use of metacognitive reading strategies; b) intrapersonal skills, interpersonal skills, adaptability, and general mood and global metacognitive strategies; c) intrapersonal skills, interpersonal skills, and general mood and problem-solving metacognitive strategies; and d) intrapersonal skills, interpersonal skills, and general mood and support metacognitive strategies. Furthermore, multiple regression analysis results indicated that the EI scales of general mood and interpersonal skills significantly contributed to the prediction of the use of metacognitive reading strategies by EFL learners.
Article
The article substantiates main characteristics and content of the training program for increasing metacognitive monitoring accuracy of university students’ learning activities by means of emotional intelligence. The tasks of the training program are aimed at forming the skills of perceiving emotions accurately, using emotions to facilitate thoughts, understanding emotions, and managing emotions; imparting students’ acknowledgement about the specifics of metacognitive monitoring accuracy of university learning activities; development of reflexivity, internal learning motivation, metacognitive awareness; students’ awareness of the characteristic features of their own processes of understanding, evaluating and reproducing information; formation of the skills of comprehension and analysis of tasks, understanding of the specifics of the tasks performed. The tasks of the stages of the developed training program, which consisted of seven blocks, are outlined: introduction, formation of the ability to perceive emotions, formation of the ability to use emotions to facilitate thoughts, formation of the ability to understand and analyze emotions, formation of the ability to manage emotions, formation of reflexivity and metacognitive awareness, as well as formation of skills for metacognitive monitoring accuracy of university students’ learning activities. The proposed training program will help students to perceive, evaluate and express emotions and related needs of physical and mental state and appearance; use emotions to increase efficiency of thinking and activities; understand and analyze emotional information; consciously manage emotions for personal growth and improvement of interpersonal relationships; flexibly approach the setting of the learning goals, monitor and control one’s own cognitive activity, use independent planning during learning. Moreover, the article describes the results of the testing of the training program. A strong evidence of its efficiency and effectiveness is the absence of statistically significant differences in the control group, as well as positive shifts in students’ implementation of more accurate metacognitive judgments while performing the tasks of the experiment. A promising direction of research of emotional intelligence is the study of the peculiarities of its influence on metacognitive monitoring accuracy of the learning activities in students of higher education.
Book
У збірнику представлено матеріали Міжнародної інтернет-конференції «СУЧАСНІ ДОСЛІДЖЕННЯ КОГНІТИВНОЇ ПСИХОЛОГІЇ», метою якої було висвітлення результатів сучасних досліджень у теоретичній та прикладній когнітивній психології. Для науковців, викладачів, аспірантів та магістрантів, студентів гуманітарних спеціальностей, практичних психологів, вихователів, соціальних працівників.
Article
Full-text available
Introduction. The research problem of the article is metacognition in the context of overcoming difficult life situations by young people. The aim of the study is to describe metacognitive strategies for overcoming difficult life situations used by students with different levels of self-regulation. Materials and Methods. For this study, psychological tests, questionnaires and interviews were used. The sample consisted of 172 second-year students of St. Petersburg State University aged between 18 and 22. Methods of data processing included descriptive statistics, difference analysis, correlation, cluster and variance analysis, and qualitative text analysis. Moreover, the authors used the following questionnaires: T. Y. Bazarov and M. P. Sychev 's Questionnaire on changing response styles, E. Y. Mandrikova's Self regulation questionnaire, D. V. Lyusin's Emotional intelligence inventory, D. A. Leontiev's Differential reflexivity diagnostic, and a questionnaire aimed was analyzing difficult life situations and overcoming strategies. Results. The authors identified three groups of students, depending on the level of self-regulation in learning. They also conceptualized the role of changing response styles, reflexivity and emotional intelligence in the effectiveness of overcoming difficult life situations. Students with a high level of self- regulation demonstrated an ability to manage and understand other people's emotions, maintain positive emotions, and assess situations adequately. Moreover, they are efficient in overcoming difficult life situations. On the other hand, students with a low level of self-regulation in difficult life situations show insufficient capacity for socio-psychological adaptation. Conclusions. The authors concluded that the subjective assessment of a difficult life situation determines the choice of a metacognitive strategy for overcoming it.
Article
Full-text available
This meta-analytic study estimated the correlations among metacognition, intelligence, and academic performance. Metacognition is higher order cognition and one of the most significant predictors of academic performance. The purpose of this study was to examine the degree to which metacognition predicted academic performance when controlling for intelligence. The analysis of 149 samples from 118 articles revealed that, overall, metacognition weakly correlated with both academic performance and intelligence, and that these relationships were moderated by the type of measurement of metacognition. Furthermore, it was found that metacognition predicted academic performance when controlling for intelligence. Our findings indicate the importance of metacognition in educational practice and provide guidance for assessing metacognition in future research.
Article
Full-text available
This paper traces the evolution of emotional intelligence as a theory and goes on to give a literature review of the same. It discusses the different concepts and beliefs pertaining to emotion and cognition and how it culminated in the theory of emotional intelligence. It also discusses the three major models of emotional intelligence, their contribution to the theory and finally closes with a brief discussion on future improvement of the theory. Keywords: Emotional Intelligence; Literature Review
Article
Nowadays, the role of emotional intelligence and metacognitive capabilities, as the most important and effective parameters in many ranges of science and life, is emphasized by researchers. The main purpose of this study is to investigate of the relationship between emotional intelligence and metacognitive capabilities with the ability of mathematical problem solving in the students. The statistical sample in this research includes 54 female and 60 male students who were chosen randomly from the Iranshahr high schools in Iran. The Bar-On and Panaoura et.al scales are used in order to assess the emotional intelligence and metacognitive capabilities of the students. The results showed that, there is a significant relationship between the general scores of metacognitive capabilities and emotional intelligence skills, and some of their components with mathematical problem solving ability. Regarding gender specificity of the students, the findings represent meaningful difference between males and females in three variables; in fact, the performance of male students was better than females in metacognitve capabilities and problem solving, but the score of female students was higher than males in emotional intelligence skills. Also the results of a multiple regression analysis showed that metacognition and emotional intelligence contribute significantly to the prediction of problem-solving ability. However, metacognition is a stronger predictor than emotional intelligence.The results of this study reveal that, national education system of any country must consider a specific and noticeable position to develop learners non-cognitive variables, such as metacognitive capabilities and emotional intelligence skills at all educational levels.
Article
Objective: Executive dysfunction in college students who have had an acute traumatic brain injury was investigated. The cognitive, behavioral, and metacognitive effects on college students who endorsed experiencing a brain injury were specifically explored. Participants: 121 college students who endorsed a mild TBI and 121 college students with no history of a TBI were matched on sex and ethnicity to examine potential differences between groups. Methods: Participants completed the Dysexecutive Questionnaire (DEX). Results: A Rasch analysis indicated the TBI group had significantly higher total scores on the DEX than the control group. Moreover, when compared to the control group, the students with a TBI had higher scores on all three subcomponents of the DEX. Conclusion: These findings suggest that students who endorse brain injuries may experience more difficulty with specific facets of college. Thus, the importance of academic and personal resources available for students with a TBI is discussed.
Book
Rumination (recyclic negative thinking), is now recognised as important in the development, maintenance and relapse of recurrence of depression. For instance, rumination has been found to elevate, perpetuate and exacerbate depressed mood, predict future episodes of depression, and delay recovery during cognitive therapy. Cognitive therapy is one of the most effective treatments for depression. However, depressive relapse and recurrence following cognitive therapy continue to be a significant problem. An understanding of the psychological processes which contribute to relapse and recurrence may guide the development of more effective interventions. This is a major contribution to the study and treatment of depression which reviews a large body of research on rumination and cognitive processes, in depression and related disorders, with a focus on the implications of this knowledge for treatment and clinical management of these disorders. First book on rumination in depressive and emotional disorders. Contributors are the leaders in the field. First editor is a rising researcher and clinician with specialist interest in depression, and second editor is world renowned for his work on cognitive therapy of emotional disorders.
Article
The aim of this study was to investigate the relationship between emotional intelligence and meta-cognition in a group of university students. The participants were 720 students chosen by random selection from different faculties of the Hashemite University. Means, standard deviations, regression and correlation analysis were used to analyze the data. Results indicated a significant positive correlation between emotional intelligence subscales and meta-cognition subscales, suggesting the need for an enhanced university role in improving student meta-cognition skills through theoretical and applied training programs. © 2014, Canadian Center of Science and Education. All rights reserved.
Article
The researchers in the current study were after gauging the would-be correlation between emotional intelligence (and its subcomponents), on the one hand and the use of listening metacognitive strategies by academic EFL learners on the other. The study at hand benefited from 72 female and 40 male university students from Urmia University, Urmia Azad University and Salams Azad University. The main instruments used in the study were Bar-On's emotional intelligence inventory and listening metacognitive strategies use questionnaire. Using Pearson correlation coefficient, the researchers came up with a significant amount of correlation between the use of listening metacognitive strategies and total emotional intelligence score as well as the learners' scores on the subscales of emotional intelligence (Intrapersonal, Interpersonal, adaptability, and general mood), with the mere exception of stress management. Moreover, the relationship between all the 5 subscales of emotional intelligence and the use of monitoring strategies, and the relationship between interpersonal skills and evaluating strategy were found to be significant.