Jesús de la Fuente1,2*
Jorge Amate3
María Carmen González-Torres2
Raquel Artuch4
Juan Manuel García-Torrecillas5,6,7
Salvatore Fadda8- 1School of Education and Psychology, University of Navarra, Pamplona, Spain
- 2School of Psychology, University of Almería, Almería, Spain
- 3Provincial Educational Authority, Almería, Spain
- 4School of Education, International University of La Rioja, Logroño, Spain
- 5Research Unit, Torrecardenas Hospital, Almería, Spain
- 6Instituto de Investigación Biosanitaria ibs, Granada, Spain
- 7Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública, Madrid, Spain
- 8Prevention Service, University of Sassari, Sassari, Italy
The SRL vs. ERL TheoryTM predicts that regulation-related factors in the student and in the context combine to determine the student’s levels in emotional variables, stress, and coping strategies. The objective of the present research was to test this prediction in the aspect of coping strategies. Our hypothesis posed that students’ level of self-regulation (low–medium–high), in combination with the level of regulation promoted in teaching (low–medium–high), would determine the type of strategies students used to cope with academic stress; the interaction of these levels would focus coping strategies either toward emotions or toward the problem. A total of 944 university students completed validated questionnaires on self-regulation, regulatory teaching, and coping strategies, using an online tool. ANOVAs and MANOVAs (3 × 1; 3 × 3; 5 × 1) were carried out, in a quasi-experimental design by selection. Level of self-regulation and level of regulatory teaching both had a significant effect on the type of coping strategies used. The most important finding was that the combined level of self-regulation and external regulation, on a five-level scale or heuristic, predicted the type of coping strategies that were used. In conclusion, the fact that this combination can predict type of coping strategies used by the student lends empirical support to the initial theory. Implications for the teaching–learning process at university and for students’ emotional health are discussed.
Introduction
The study of students’ emotional experiences in the teaching and learning context has yielded much research on aspects previously unconsidered by the cognitivist paradigm (Linnenbrink-Garcia and Pekrun, 2011; Goetz et al., 2014; Lüftenegger et al., 2016; Murayama et al., 2017; Duffy et al., 2018; Gentsch et al., 2018; Loderer et al., 2018; Collie et al., 2019; Harley et al., 2019; Hirvonena et al., 2019). In the present study, our effort has focused on explaining the degree to which emotional processes facilitate or interfere in cognitive processes (Rusk et al., 2011; Moffa et al., 2016; Putwain, 2018).
Academic Stress at University
In the university context, due to the difficulty of meeting the demands and requirements of study, the experience of stress is an important phenomenon that has captured research interest (Martín et al., 2003; Cabanach et al., 2007; Willcoxson et al., 2011; D’Mello, 2013; Pidgeon and Pickett, 2017; Scharp and Dorrance, 2017). Research on academic stress in this context, from the perspective of Clinical and Health Psychology, has prioritized individual predictive or explanatory factors, with particular focus on differentiating factors like personality variables, anxiety, or cognitive differences (Palmer and Rodger, 2009; Saklofske et al., 2012; Dicke et al., 2018; Cassady et al., 2019). From an Educational Psychology perspective, however, it seems reasonable to approach the study of stress as a contextualized phenomenon within the teaching-learning process (Mainhard et al., 2018). On one hand, the learning process can by accompanied by the experience of stress and by the use of resources for managing stress (coping strategies), depending on characteristics of the individual (Shaw et al., 2017; Rapillard et al., 2019). On the other hand, the context, or teaching process, can give rise to stressful experiences and to the use of stress management methods (Frenzel et al., 2018; Gentsch et al., 2018; Collie et al., 2019). The present research report adopts an interactive student-teacher approach to academic stress, analyzing stress that arises from the interaction of the student’s learning process with characteristics of the teaching process.
Coping Strategies as a Variable of the Teaching and Learning Process
Coping strategies are a psychological construction referring to knowledge, skills and strategic behaviors that people use to manage emotions occurring within a situation of stress (Fimian et al., 1989; Chartier et al., 2011; Freire et al., 2018); for this reason, they are considered meta-emotional skills (de la Fuente et al., 2017a). Multiple models have been proposed for categorizing these skills, beginning with the initial model proposed by Lazarus and Folkman (1984/1986) and Lazarus (1999). In essence, two types of strategies have been described: (1) those that seek to minimize negative emotional states, i.e., emotion-focused strategies; and (2) those that address the cause of the stressful experience or of overtaxed personal resources, i.e., problem-focused strategies. In the initial research it was assumed that stress was associated only with negative emotionality; however, the reformulated versions of the theoretical model assumed that it was possible to combine mixed coping strategies (Folkman, 1997, 2008, 2011).
Coping Strategies in the Learning Process
Prior research on motivational and affective factors of learning in university contexts has also recognized the importance of the different types of coping strategies used by university students. Some examples have addressed the role of religious coping (Francis et al., 2018), the role of health habits as a coping strategy (Tada, 2017), how coping strategies related to well-being (Park and Adler, 2003; Bhullar et al., 2014; Freire et al., 2016), types of coping and their relationship to resilience, academic coping within a religious vs. secular context (González-Torres and Artuch, 2014). The associations between coping strategies, anxiety and engagement-burnout have also been established (de la Fuente et al., 2015a).
Coping Strategies in the Teaching Process
Some prior research has analyzed coping strategies from the teacher’s standpoint: their methods of coping (Gustems-Carnicer et al., 2019), and their levels of stress (Browers and Tomic, 2000; Alson, 2019). From a complementary viewpoint, teacher effectiveness at university has been measured in terms of students’ well-being and good teacher-student relations (Lekwa et al., 2018; Aldrupa et al., 2019). Evidence has also shown the influence of teachers’ personality characteristics in effective teaching (Kim et al., 2019).
Combined Effect of Teaching and Learning Process Variables on Coping Strategies
However, the effect of this combination on types of coping strategies used by university students, as a consequence of the teaching and learning process, has not been sufficiently established (de la Fuente et al., 2016, 2017b). The present research, therefore, focuses on how combined levels of Student Self-Regulation (SR) (learning process) and Teaching Effectiveness (teaching process) determine types of coping strategies in students. This research report is part of a series of complementary papers that present evidence of the combined effects of these two types of variables on students’ emotional variables (de la Fuente et al., 2019).
SRL vs. ERL Theory as a Research Heuristic in the Teaching and Learning Process
The theory of Self- vs. Externally- Regulated Learning is founded conceptually on the assumptions below (see de la Fuente, 2017). It is a further development of the concept of self-regulated learning from B. J. Zimmerman’s model (Zimmerman, 2001, 2008; Zimmerman and Labuhn, 2012) and of Vermunt’s concept of self-regulation and external regulation (Vermunt, 1998, 2005; Vermunt and Vermetten, 2004; Vermunt et al., 2014; Vermunt and Donche, 2017). The theoretical model of SRL vs. ERL defines different types of regulation along a behavioral continuum. This continuum is useful for analyzing the teaching and learning process:
(1) With regard to the learning process, the model defines three levels of student regulation in a learning situation:
Self-Regulation represents a high degree of self-regulation or positive proactivity, that is, active and adequate regulation of one’s own behavior (level 3 of SR).
Non-Regulation (NR) refers to a lack of proactivity or a medium level of self-regulation. This is the conceptual equivalent of reactivity (level 2 of SR).
Dysregulation (DR) is negative proactivity or a low level of self-regulation. The individual actively manages his or her own behavior toward inadequate purposes (level 1 of SR).
In summary, level of SR, as a personal characteristic of the student, predisposes an equivalent level of self-regulated learning (Zimmerman, 2001, 2008; Zimmerman and Labuhn, 2012).
(2) With regard to the teaching process, this model defines several levels of regulatory teaching (RT), or levels of teaching effectiveness. The present model is more explicit than Zimmerman’s SRL model (Zimmerman, 2001, 2008; Zimmerman and Labuhn, 2012), since it specifically defines the value of each level of teaching effectiveness for predisposing self-regulated learning, an aspect not clearly defined in the previous model.
Externally Regulatory (ER) teaching or highly effective teaching. In this context, the teaching prompts students toward well-directed proactivity and SR. This type of teaching context provides many external indicators that increase the likelihood of self-regulated behavior (before, during and after) (Level 3 RT).
Externally Non-regulatory (ENR) teaching or moderately effective teaching. Whether at the beginning, middle or end of learning acts, there are no external indicators or promptings that encourage self-regulated or dysregulated behavior, or that increase the likelihood of one or the other. A non-regulatory context requires the student to engage in a moderate level of self-regulated behavior, given that contextual elements offer no direction (Level 2 RT).
Externally Dys-Regulatory (EDR) teaching or ineffective teaching. Dysregulation, that is, inadequate or negative proactivity, is actively promoted in this context. The individual who wishes to practice self-regulated learning in this type of context must make a great effort (Level 1 RT).
(3) Effects of the combined levels of self-regulation and external regulation can be predicted. Human learning takes its shape when the individual’s self-regulating ability (SR) and the external regulatory features of the context (ER) are combined. Five types of interactions are possible (de la Fuente et al., 2019). According to this principle, coping strategies are predisposed by mediating factors, both internal (self-regulation, SR: levels 1–3) and external (external regulation, ER: levels 1–3). This theoretical model requires that subject x context interactions be specified, addressing an insufficiency of the initial theoretical model of Self-Regulated Learning (Zimmerman, 2001, 2008; Zimmerman and Labuhn, 2012).
Aims and Hypothesis
Based on the models and previous empirical data, the following objectives were identified: (1) to establish whether the university students’ personal regulation levels and the regulatory levels of their context, independently of each other, determined the type of coping strategies used; (2) to establish whether the combined levels of SR and RT, as described in the interactivity model proposed above, were associated with the type of coping strategies used. Based on these objectives, the hypothesis established that a graded increase in level of regulation (internal and external) would give rise to (1) a proportionate decrease in emotion-focused strategies, and (2) a proportionate increase in problem-focused coping strategies. By contrast, a graded decrease in level of regulation (internal and external) would give rise to (1) a proportionate increase in emotion-focused strategies, and (2) a proportionate decrease in problem-focused coping strategies.
Materials and Methods
Participants
To establish interdependence relations among low-medium-high levels of SR, and RT, we used a total sample of 944 undergraduate students from two universities of Spain. The sample was composed of students enrolled in Psychology, Primary Education, and Early Childhood Education degrees; 82.7% were women and 17.3% were men. Their ages ranged from 19 to 45, with a mean age of 22.25 (σX = 6.3) years. Of the total sample, 28.3% were first-year students, 40.3% were in second year, 14.5% in third year, and 16.5% were in the fourth year of the degree program.
Instruments
Self-Regulation
This variable was measured using the Short Self-Regulation Questionnaire (SSRQ) (Miller and Brown, 1991). Previously validated in Spanish samples (Pichardo et al., 2014, 2018), it possesses acceptable validity and reliability values, similar to the English version. The original SRQ (Brown et al., 1999) evaluates subjects’ SR of behavior, understood as the ability to plan and manage their own behavior in a flexible way, according to the desired outcomes. Although the questionnaire has been adapted to educational contexts, it was initially designed within the field of addictive behaviors. The authors, using squared multiple correlation coefficients, carried out an initial design of 63 items (26 reverse) that constituted 7 scales: (1) informational input, which refers to a person’s ability to obtain information on their current state from their environment; (2) self-evaluation, where this information is compared to personal goals, rules and expectations; (3) instigation to change, the person’s perception of any existing discrepancies between their current state and their desired state; (4) search for ways to reduce discrepancies; (5) planning for change, that is, strategies or actions for carrying out the change process; (6) implementation of the change strategies; and (7) evaluation of progress toward a goal. The English version of the instrument has mainly been used with university students. Different studies have analyzed the SRQ’s psychometric properties, establishing several factorial solutions. Carey et al. (2004), using a sample of 391 American undergraduate students between the ages of 17 and 24, established a one-factor solution composed of 31 items, which led the authors to propose a new measure: the Short SRQ (SSRQ). Correlation between the two versions was strong (r = 0.96), suggesting that the short version is a good alternative to the full scale.
The Short SRQ is composed of four factors (goal setting-planning, perseverance, decision making and learning from mistakes) and 17 items (all of them with saturations greater than 0.40); the confirmatory factor structure is consistent (χ2 = 250.83, df = 112, CFI = 0.90, GFI = 0.92, AGFI = 0.90, RMSEA = 0.05). Internal consistency was acceptable for the total of questionnaire items (α = 0.86) and for the factors of goal setting-planning (α = 0.79; six items), decision making (α = 0.72; three items) learning from mistakes (α = 0.72; five items), and perseverance (α = 0.73; three items). Correlations have been studied between each item and its factor total, between the factors, and between each factor and the complete questionnaire, with good results for all, except for the decision-making factor, which showed a weaker correlation with other factors (range: 0.41–0.58). Correlations of the long and short Spanish versions (long SRQ with 32 items and short SRQ with 17 items), to the original long questionnaire, are better for the short version (short Spanish to long English questionnaire: r = 0.85 and short Spanish to long Spanish: r = 0.94; p < 0.01) than for the long Spanish version (long Spanish to long English: r = 0.79; p < 0.01). For more information, please, see: https://www.frontiersin.org/articles/10.3389/fpsyg.2019.01919/full#supplementary-material.
Regulatory Teaching (Teaching Effectiveness)
The Scales for Assessment of the Teaching-Learning Process, ATLP, student version (de la Fuente et al., 2012) were used to evaluate students’ perception of the teaching process. The scale entitled Regulatory Teaching is Dimension 1 of the confirmatory model. ATLP-D1 comprises 29 items structured along five factors: Specific RT, regulatory assessment, preparation for learning, satisfaction with the teaching, and general RT. The scale was validated in university students (de la Fuente et al., 2012) and showed a factor structure with adequate fit indices (χ2 = 590.626; df = 48, p < 0.001, CF1 = 0.938, TLI = 0.939, NFI = 0.950, NNFI = 0.967; RMSEA = 0.068) and adequate internal consistency (ATLP D1: α = 0.83; Specific RT, α = 0.897; regulatory assessment, α = 0.883; preparation for learning, α = 0.849; satisfaction with the teaching, α = 0.883 and general RT, α = 0.883). The ATLP is a self-report instrument to be completed by the teacher and the students, available in Spanish and English versions. It also includes a qualitative part where students can make recommendations for improving each of the processes evaluated. As for external validity, results are also consistent, since there are different interdependent relationships among perceptions of variables that exist in an academic environment. For more information, please, see: https://www.frontiersin.org/articles/10.3389/fpsyg.2019.01919/full#supplementary-material.
Coping Strategies
The Coping Strategies Scale, EEC (Chorot and Sandín, 1987) was used, in a short validated Spanish version, EEC-Short (de la Fuente, 2014). Although the original instrument contained 90 items, the validation produced a first-order structure of 64 items and a second order with 10 factors and two dimensions, both of them significant, with adequate fit values in the latter [χ2 = 878,75; df(77-34) = 43, p < 0.001; NFI = 0.901; RFI = 0.945; IFI = 0.903; TLI = 0.951; CFI = 0.903, RMSEA = 0.07]. Reliability measures are Cronbach alpha of 0.93 (complete scale), 0.93 (first half) and 0.90 (second half), Spearman–Brown of 0.84 and Guttman of 0.80. The scale assesses two dimensions: D1: Emotion-focused coping (0.95) and D2: Problem-focused coping (0.91). The emotion-focused strategies were: F1. Avoidant distraction (0.79); F7. Reducing anxiety and avoidance (0.88); F8. Preparing for the worst (0.80); F9. Emotional venting and isolation (0.91); and F11. Resigned acceptance (0.86). The problem-focused strategies were: F2. Seeking help and counsel (0.92); F5. Self-instructions (0.82); F10. Positive reappraisal and firmness (0.87); F12. Communicating feelings and social support (0.89); and F13. Seeking alternative reinforcement (0.80). See Table 1.
Table 1. Types of coping strategies and examples of items in the short EEC version.
Procedure
Participants voluntarily completed the scales using an online platform (de la Fuente et al., 2015b). A total of ten specific teaching-learning processes were evaluated, covering different university subjects that were taught within a 2-year period. Based on Biggs’ 3P model (Biggs, 2001), Presage variables (SR) were assessed in September-October of 2017 and 2018; Process variables (Coping Strategies) and Product variables (RT) were assessed in May-June of 2017 and 2018. The students self-reported on: (1) self-regulation characteristics (SR) at the beginning of the academic year; (2) coping strategies (CS) and RT at the end of the course. Each group of students only evaluated one teaching-learning process. The procedure was approved by the respective Ethics Committees of each university, in the context of two R&D Projects (2018–2021).
Data Analysis
Effects of Regulation Levels
Through cluster analysis, continuous independent variables were transformed into discrete dependent variables with three levels (low-medium-high). Using an ex post-facto design, a 3 K-means cluster analysis was first conducted to establish low-medium-high groups in the two variables: Personal SR and RT. For the SR variable, values of Low = 2.70; Medium = 3.48; High = 4.20 formed the centers of the clusters, and ranges were as follows: low, 1.00–3.09; medium, 3.10–3.84; and high, 3.85–5.00. For the RT variable, Low = 2.72; Medium = 3.58; High = 4.34 formed the centers of the clusters, and ranges were: Low, 1.00–2.34; Medium, 2.35–2.83; and High, 2.84–5.00. In addition, several ANOVAs and MANOVAs were carried out, in order to ascertain the effect of low-medium-high levels on the dependent variable, coping strategies. Also, using a 3-factor design (low-medium-high SR levels) × 3 (low-medium-high levels of RT), several MANOVAs were conducted, taking these levels as independent variables. Finally, based on the low–medium–high groups in both variables (SR and RT), five combinations were configured, according to the proposed theoretical model (see Table 2). MANOVAs were conducted to establish statistical suitability of these groupings, as well as the effects on the defined dependent variables, with Pillai’s trace and Sheffé test index.
Table 2. Combinations between parameters of the model hypothesized in SRL vs. ERL Theory: the Utility ModelTM (de la Fuente et al., 2019, p. 12).
A Combination Typology for Understanding Coping Strategies
The multivariate analyses (MANOVAs) showed a statistically significant main effect of the five combination types of low-medium-high levels of SR and RT (see de la Fuente et al., 2019, p.12, and Table 2):
Combination 1 presented a statistically significant low level in SR and low level in RT (1 and 1). The average of regulation levels is 1.0, and the rank is 1. The regulation range is low SR and low RT, associated with a low level of self-regulation or high level of dysregulation. Consequently, the effects are a high level of emotion-focused coping strategies and a low level of problem-focused coping strategies.
Combination 2 had a statistically significant low level in SR and medium level in RT, or vice versa (2 and 1, or 1 and 2). The average of regulation levels is 1.5, and the rank is 2. The regulation range is low-medium SR and low-medium RT, and vice versa, associated with a medium-low level of self-regulation or medium-high level of dys-regulation. Consequently, the effects are a medium-high level of emotion-focused coping strategies and medium-low levels of problem-focused coping strategies.
Combination 3 presented a statistically significant medium SR level and medium RT level (2 and 2). The average of regulation levels is 2.0, and the rank is 3. The regulation range is medium SR and medium RT, associated with a medium level of self-regulation or dys-regulation. Consequently, the effects are a medium level of emotion-focused coping strategies and medium level of problem-focused coping strategies.
Combination 4 had a statistically significant medium SR with high RT or high SR with medium RT (2 and 3, or 3 and 2). The average of regulation levels is 2.5, and the rank is 4. The regulation range is high SR-medium RT, or medium SR-high RT, associated with a medium-high level of self-regulation or medium-low level of dys-regulation. Consequently, the effects are a medium-low level of emotion-focused coping strategies and medium-high level of problem-focused coping strategies.
Combination 5 presented a statistically significant high SR and high RT (3 and 3). The average of regulation levels is 3.0, and the rank is 5. The regulation range is high SR-high RT, associated with a high level of self-regulation and low level of dys-regulation. Consequently, the effects are a low level of emotion-focused coping strategies and high level of problem-focused coping strategies.
Results
Interdependent Simple Effects of Levels of Personal Self-Regulation (SR) and Levels of Regulatory Teaching (RT) on Stress Coping Strategies
Effect of Self-Regulation on Stress Coping Strategies
A statistically significant effect was noted of the IV SR (low-medium levels) on total Coping Strategies. The statistically significant partial effect of the IV SR (low-medium-high levels) was maintained for the two dimensions of Emotion-focused Coping Strategies and Problem-focused Coping Strategies, the latter showing greater statistical significance.
A statistically significant main effect of the IV SR (low-medium-high levels) was noted on the factors of Emotion-focused Coping Strategies. Also, the statistically significant partial effect of the IV SR (low-medium-high levels) was maintained for F1 (Avoidant distraction), F7 (Reducing anxiety and avoidance), F8 (Preparing for the worst), with greater statistical significance for factors F9 (Emotional venting and isolation) and F11 (Resigned acceptance), for university students with lower levels of SR. Complementarily, a statistically significant main effect of the IV SR (low–medium–high levels), was noted on the factors of Problem-focused Coping Strategies. Also, the statistically significant partial effect of the IV SR (low-medium-high levels) was maintained for F2 (Seeking help), F5 (Self-Instructions), F10 (Positive re-appraisal and firmness), F12 (Communicating feelings and social support), F13 (Seeking alternative reinforcement). See Table 3.
Table 3. Interdependence relations between low–medium–high levels of Self-Regulation (SR) and Regulatory Teaching (RT) as independent variables, in strategies for coping with stress.
Effects of Regulatory Teaching on Stress Coping Strategies
There was a statistically significant effect of the IV RT (low–medium–high levels) on total Coping Strategies. The statistically significant partial effect of the IV RT (low–medium levels) was maintained in the dimensions of Coping Strategies. There was a statistically significant partial effect of the IV SR (low–medium–high levels) for the two dimensions of Emotion-focused Coping and Problem-focused Coping Strategies, the latter again showing greater statistical effect.
A statistically significant main effect of the IV RT (low–medium–high levels) was noted on the factors of Emotion-focused Coping Strategies. Also, the statistically significant partial effect of the IV RT (low-medium-high levels) was maintained for F1 (Avoidant distraction), F7 (Reducing anxiety and avoidance), F8 (Preparing for the worst), F11 (Resigned acceptance) and especially, in the use of strategy F9 (Emotional venting and isolation) for low levels of RT. Complementarily, a statistically significant main effect of the IV RT (low–medium–high levels) was noted in the factors of Problem-focused Coping Strategies. Also, the statistically significant partial effect of the IV SR (low–medium–high levels) was maintained for F2 (Seeking help), F12 (Communicating feelings and social support), F13 (Seeking alternative reinforcement), and with greater statistical significance for the factors F5 (Self-instructions) and F10 (Positive re-appraisal and firmness) for high levels of external regulation (RT). See Table 3.
Interdependent Complex Effects (3 × 3) of the Levels of Self-Regulation (SR) With Levels of Regulatory Teaching (RT) on Stress Coping Strategies
Effect on Total Coping Strategies and Dimensions
The IV SR (low–medium–high levels) did not show any significant effect in total Coping Strategies, but it did produce a statistically significant main effect on the dimensions or factors of coping stress. The statistically significant partial effect of the IV SR (low–medium–high levels) was maintained for the two dimensions of Emotion-focused Coping Strategies and Problem-focused Coping Strategies.
A statistically significant effect of the IV RT (low-medium-high levels) was noted in total Coping Strategies. The statistically significant partial effect of IV RT (low–medium levels) was maintained in the dimensions of Coping Strategies. The statistically significant partial effect of the IV RT (low–medium–high levels) was maintained for the two dimensions of Emotion-focused Coping Strategies and Problem-focused Coping Strategies.
Effect on Specific Factors of Emotion-Focused Coping Strategies
The IV SR (low-medium-high levels) was observed to have a statistically significant main effect on the Factors of Emotion-focused Coping Strategies. A statistically significant effect appeared of the IV RT (low-medium levels) on the Factors of Emotion-focused Coping Strategies. There was no statistically significant effect of the interaction SR × RT.
The statistically significant partial effect of the IV SR (low–medium–high levels) was maintained for F1 (Avoidant distraction), F7 (Reducing anxiety), F8 (Preparing for the worst), F9 (Emotional venting and isolation), and F11 (Resigned acceptance), where the last three factors have greater statistical significance, for students with a lower level of SR. Complementarily, a statistically significant partial effect of the IV RT (low–medium–high levels) was maintained for F1 (Avoidant distraction), F7 (Reducing anxiety), F8 (Preparing for the worst), F9 (Emotional venting and isolation), and F11 (Resigned acceptance), the last two factors having greater statistical significance, for students with a lower level of RT. There were no significant interaction effects of SR × RT for coping factors in Emotion-focused Coping Strategies. See Table 4.
Table 4. Interdependent complex effects (3 × 3) of low-medium-high levels of Self-Regulation (SR) with low–medium–high levels of Regulatory Teaching (RT) on stress coping strategies (n = 797).
Effect on Specific Factors of Problem-Focused Coping Strategies
A statistically significant main effect of the IV SR (low–medium–high levels) was noted on the Factors of Problem-focused Coping Strategies. There was a statistically significant effect of the IV RT (low-medium-high levels) on the Factors of Problem-focused Coping Strategies. There was no significant effect of the SR × RT interaction.
The statistically significant partial effect of the IV SR (low–medium–high levels) was maintained for F2 (Seeking help), F5 (Self-Instructions), F10 (Positive re-appraisal), F12 (Communicating feelings and social support), and F13 (Alternative reinforcement). Complementarily, a statistically significant partial effect of the IV RT (low-medium-high levels) was maintained for F2 (Seeking help), F5 (Self-Instructions), F10 (Positive re-appraisal), F12 (Communicating feelings and social support), and F13 (Alternative reinforcement). There were no significant interactions of SR × RT for coping factors in the Emotion-focused Coping Strategies. See Table 4 and Figures 1, 2.
Figure 1. Graphic representation of the effect of low(1)–medium(2)–high(3) levels in the IV Self- Regulation (GRUPSR) and low(1)–medium(2)–high (3) levels in the IV Regulatory Teaching (GRUPRT) on Emotion-focused Coping Strategies (EECD1); EECF1. Avoidant distraction; EECF7. Reducing anxiety; EECF8. Preparing for the worst; EECF9. Emotional venting; EECF11. Resigned acceptance.
Figure 2. Graphic representation of the effect of low(1)–medium(2)–high(3) levels in the IV Self-regulation (GRUPSR) and low(1)–medium(2)–high (3) levels in the IV Regulatory Teaching (GRUPRT) on Problem-focused Coping StrategiesEECF2. Seeking help; EECF5. Self-Instructions; EECF10. Positive re-appraisal; EECF12. Communicating feelings; EECF13. Alternative reinforcement.
Combination Typology for Understanding Stress Coping Strategies
Preliminary Analysis
The MANOVA showed statistically significant differences in the levels of SR and RT variables among the five groups, showing them to be adequately configured according to what is established in Table 4. See the statistical effects in the Table 5.
Table 5. Effects of combination types on stress coping strategies (n = 797).
Stress Coping Strategies
There was a statistically significant main effect of the five IV combinations of SR and RT on Total Coping strategies [5,4 > 3,2,1]. In the case of Emotion-focused Coping Strategies, no statistically significant effect appeared, but in Problem-focused Coping Strategies there was a statistically significant effect in favor of high levels [5, 4 > 3 > 2,1]. The statistically significant partial effect was maintained for factors of Emotion-focused Coping Strategies (F9. Emotional venting, and F11. Resigned acceptance), and for the Problem-focused Coping Strategies (all factors: 5,4 > 3,2,1). Thus, total coping behaviors progressively increased through the five levels of interaction. Overall, the clearest effects are: higher interaction levels (1–5) leading to a decrease in factors of Emotion-focused Coping Strategies (F8, F9, F11), and to an increase in factors of Problem-focused Coping Strategies (F2, F5, F10, F12, F13). See Table 5. A graphic representation of the differential progressive effect of combined SR and RT levels is shown in Figures 3, 4.
Figure 3. Graphic representation of the effects of the combination types (levels 1–5) on Emotion-focused Coping Strategies; EECTOT = Total strategies; F8 = Preparing for the worst; F9 = Emotional venting; F11 = Resigned acceptance.
Figure 4. Graphical representation of the effects of the combination types (levels 1–5) on Problem-focused Coping Strategies. EECD2 = Problem-focused strategies; F2 = Seeking help; F5 = Self-Instructions; F10 = Reappraisal; F12 = Comm. feelings and social support; F13 = Alternative reinforcement.
Discussion and Conclusion
SRL vs. ERL Theory (de la Fuente, 2017) predicted that university students’ coping strategies could be determined, jointly, by the students’ degree of self-regulation and by the level of contextual, external regulation from the teaching process. Furthermore, this type of interaction could be understood as the combination of low-medium-high levels of the two factors, as supported by prior evidence in this direction (de la Fuente et al., 2015a, 2017b).
For hypotheses 1 and 2, the results offer evidence that a (1) graded increase in level of regulation (internal and external) gives rise to a proportionate decrease in emotion-focused strategies, and a proportionate increase in problem-focused coping strategies. By contrast, a (2) graded decrease in level of regulation (internal and external) gives rise to a proportionate increase in emotion-focused strategies, and a proportionate decrease in problem-focused coping strategies. The hypothesis can be considered partially validated.
Analysis of the simple effect of the variables showed that level of SR positively determined the level of problem-focused strategies and negatively determined the level of emotion-focused strategies. Likewise, the level of RT showed a similar trend. This result is consistent with prior evidence from this line of research (de la Fuente et al., 2017b), as well as from other studies (Holinka, 2015; Collie et al., 2019). On the other hand, analysis of the combined effect of the variables showed two independent main effects, both from SR and from RT, but did not show a crossover interaction, consistently with previous evidence on the effect of these two variables on coping strategies (de la Fuente et al., 2017b, 2019). Finally, when analyzing a graded increase in the combination level (scale of 1–5), the results are very consistent with the idea that the combination of the two types of regulation (person × context) significantly predicts a decrease in emotion-focused strategies and an increase in problem-focused strategies. These results are very consistent with others that our research team has recently found and reported (de la Fuente et al., 2019, p. 14), where positive achievement emotions were found to increase with higher ranking combinations of internal (SR) and external (RT) regulation, and negative emotions increased with lower ranking combinations of internal (SR) and external (RT) regulation. Consequently, the coping behaviors analyzed here –as a variable of emotional or meta-emotional regulation—would reflect a similar response schema for managing each type of emotionality, according to the degree of SR and RT. Nonetheless, based on results from the two studies, it is not yet possible to establish a causality relationship for types of achievement emotions or coping strategies, an aspect which remains for further empirical analyses.
Theoretical Implications
These findings are important for this theoretical model because they lend support to the premise that both the student’s lack of regulation and a lack of regulation in teaching tend toward negative emotionality, and consequently, to greater use of emotion-focused strategies, to the detriment of problem-focused strategies. By contrast, higher levels of regulation in the student and higher levels of RT both contribute to positive emotionality, tending toward a greater use of problem-focused strategies, given that emotion-focused strategies for managing negative emotionality are not needed. This supports the importance of university students’ perception of the teaching process (Aldrupa et al., 2019). These tendencies are similar to those found in other studies (de la Fuente et al., 2017b, 2019), lending empirical support to the assumption that the combination of individual and contextual regulation characteristics delimits the level of stress, just as is predicted by SRL vs. ERL Theory (de la Fuente, 2017). In other words, students with a lower level of SR (non-regulation or dysregulation), who are exposed to non-RT processes (no external regulation or dysregulating), are the ones who produce the greatest stress factors and show the greatest symptomology of stress (de la Fuente et al., 2020; in review), leading to greater application of emotion-focused strategies and to reduced focus on the problem. The opposite occurs in the case of students with high SR who are exposed to highly RT.
This theoretical contribution allows us to progress to a broader view of the Theory of Self-Regulated Learning (Zimmerman, 2001, 2008; Zimmerman and Labuhn, 2012). We can infer that the context -in this case the presence or lack of effective teaching- may have an active regulatory role, promoting and aiding the student’s SR, and becoming just as important as the university student’s own SR for predicting emotional behaviors of learning and ways of coping. It also enables us to operationalize the concept of Self-regulation vs. External-Regulation (Vermunt, 2005, 2007; Vermunt and Donche, 2017; and further specified by Vanthournout et al., 2014), since external regulation is conceptualized not as the opposite of internal, self-regulation, but as something that fosters SR, thereby resolving certain recent criticisms (Hederich-Martínez and Camargo, 2019).
The coping strategy labeled F9 (emotional venting and isolation) requires special attention. It is plausible that this dysregulatory behavior is a link between students’ learning and achievement problems and certain health problems -alcohol intake, substance abuse or behavioral excesses (Freire et al., 2016; Garzón-Umerenkova et al., 2018; Kamijo and Yukawa, 2018). In other words, although the causes of learning and achievement problems can be both internal to the student (cognitive, meta-cognitive, motivational or meta-motivational in origin) and external, in the teaching process (its adjustment or maladjustment), what is certain is that the meta-emotional factors addressed here are significant in health predictions. Prior evidence has shown that negative emotionality, lack of confidence and lack of resilience correlate positively to the surface approach and negatively to the deep approach (de la Fuente et al., 2017a). It is therefore necessary to take this combination into account in the prevention of stress factors in university teaching-learning processes (Palmer and Rodger, 2009; Alonso-Tapia et al., 2018).
Limitations and Future Directions
The present research study has several limitations worth mentioning. The sample should be improved by adding university students from different degree programs. The degree to which stress factors are determined by the student’s personality variables (presage) also remains to be verified, as well as the connection between such variables and variables that explain good learning (as a process) and academic achievement (as a product). Other studies from our research team have already reported the importance of achievement emotions in different situations –in class, study time, testing (de la Fuente et al., 2019)—and upcoming studies will address these complex relations.
One especially important aspect for future investigation is the relationship of levels of self-regulation and external regulation to the concept of flexible emotion regulation (Gross, 2008, 2014, 2015a,b), with its recent important contributions (Kobyliñska and Kusev, 2019), and the coping strategies associated with each combination type. It would also be desirable to evaluate RT produced by university teachers as a function of their own emotions, given that some relationships have already been found (Frenzel et al., 2016, 2018). Another important aspect to be studied is the cross-cultural validity of these results, recognizing our limitation to a Spanish-speaking environment, and the need to expand this evidence to English-speaking samples, as well as other international groups, something to be addressed in future research. Special attention should also be given to gender differences, not analyzed in the present research study, but where important effects can be found, as shown by one recent study (Cabanach et al., 2009; Martínez et al., 2019).
Implications for the Practice of Educational Psychology at University
Applied implications from this research refer to two aspects. On one hand, students must be trained in the importance of self-regulating behavior when learning at university, not only in its meta-cognitive aspects (deep vs. surface learning approaches), but also in the relevance of emotional factors (achievement emotions), meta-emotional factors (emotion-focused vs. problem-focused coping strategies) and meta-behavioral factors (behavioral SR). On the other hand, it is essential that university teachers be trained to minimize stress factors through the design of their teaching process. The concept of effective teaching is associated with well-planned teaching, and with fostering in students a perception of control (Paris and Winograd, 2003; Putwain et al., 2019; Shannon et al., 2019). If students with a low level of SR perceive more stress factors and also experience more stress symptomology inherent to the teaching process, any innovative teaching design should take this personal factor into account.
When implementing innovations in the university teaching process, it is important to consider what type of context is being designed, within the framework of the SRL vs. ERL Theory (de la Fuente, 2017). If the context is non-regulating or dysregulating, it will probably not help students improve their learning process, especially if students have low SR. As seen in prior evidence, students with little SR require greater external regulation. Certain prior evidence has shown results consistent with this idea (Shaw et al., 2017; Bingen et al., 2019; Kassymova et al., 2019).
Data Availability Statement
The datasets analyzed in this manuscript are not publicly available. Requests to access the datasets should be directed to jdlfuente@unav.es.
Ethics Statement
The studies involving human participants were reviewed and approved by the Comité de Ética, Universidad de Navarra. The patients/participants provided their written informed consent to participate in this study.
Author Contributions
JF have made the general analysis and first version of the manuscript. MG-T has made the second review of the Self-regulation and Externally regulation sections of Coping Stress. JA and JG-T have performed a review of the data analysis. RA and SF have participated in the data collection.
Funding
This work was supported by R&D Project PGC2018-094672-B-I00 (Ministry of Science and Education, Spain), UAL18 SEJ-DO31-A-FEDER (University of Almería, Spain), and the European Social Fund.
Conflict of Interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
References
Aldrupa, K., Klusmanna, U., Lüdtkea, O., Göllnerc, R., and Trautweind, U. (2019). Student misbehavior and teacher well-being: testing the mediating role of the teacher-student relationship. Learn. Instr. 58, 126–136. doi: 10.1016/j.learninstruc.2018.05.006
Alonso-Tapia, J., Rodríguez-Rey, R., Garrido-Hernansaiz, H., Ruiz, M., and Nieto, C. (2018). Coping assessment from the perspective of the person-situation interaction: development and validation of the Situated Coping Questionnaire for Adults (SCQA). Psicothema 28, 479–486. doi: 10.7334/psicothema2016.19
Bhullar, N., Hine, D. W., and Phillips, W. J. (2014). Profiles of psychological well-being in a simple of Australian university students. Int. J. Psychol. 49, 288–294. doi: 10.1002/ijop.12022
Biggs, J. (2001). The reflective institution: assuring and enhancing the quality of teaching and learning. High. Educ. 41, 221–238.
Bingen, H. M., Steindal, S. A., Krumsvik, R., and Tveit, B. (2019). Nursing students studying physiology within a flipped classroom, self-regulation and off-campus activities. Nurse Educ. Pract. 35, 55–62. doi: 10.1016/j.nepr.2019.01.004
Browers, A., and Tomic, W. (2000). A longitudinal study of teacher burnout and perceived self-efficacy in classroom management. Teach. Teach. Educ. 16, 239–253. doi: 10.1016/s0742-051x(99)00057-8
Brown, J. M., Miller, W. R., and Lawendowski, L. A. (1999). “The self-regulation questionnaire,” in Innovations in Clinical Practice: a Source Book, Vol. 17, eds L. Vandecreek and T. L. Jackson (Sarasota, FL: Professional Resources Press), 281–293.
Cabanach, R. G., González, P., and Freire, C. (2009). El afrontamiento del estrés en estudiantes de ciencias de la salud. Diferencias entre hombres y mujeres [Coping with stress in health science students. Differences between men and women]. Aula Abierta 37, 3–10.
Cabanach, R. G., Rodríguez, S., Valle, A., Piñeiro, I., and Millán, P. G. (2007). Metas académicas y vulnerabilidad al estrés en contextos académicos [Academic goals and vulnerability to stress in academic contexts]. Aula Abierta 36, 3–16.
Carey, K. B., Neal, D. J., and Collins, S. E. (2004). A psychometric analysis of the self-regulation questionnaire. Addict. Behav. 29, 253–260. doi: 10.1016/j.addbeh.2003.08.001
Cassady, J. C., Pierson, E. E., and Starling, J. M. (2019). Predicting student depression with measures of general and academic anxieties. Front. Educ. 4:11. doi: 10.3389/feduc.2019.00011
Chartier, I. S., Gaudreau, P., and Fecteau, M. (2011). From dispositional affect to academic goal attainment: the mediating role of coping. Anxiety Stress Coping 24, 43–58. doi: 10.1080/10615801003725360
Chorot, P., and Sandín, B. (1987). Escalas de Estrategias de Coping. [Scales of Coping Strategies]. Madrid: UNED.
Collie, R. J., Granziera, H., and Martin, A. J. (2019). Teachers’ motivational approach: links with students’ basic psychological need frustration, maladaptive engagement, and academic outcomes. Teach. Teach. Educ. 86:102872. doi: 10.1016/j.tate.2019.07.002
de la Fuente, J. (2014). Confirmatory Structural Equation Model of Coping Strategies Scale (EEC). Almería: University of Almería.
de la Fuente, J. (2017). Theory of self- vs. externally- regulated learningTM: fundamentals, evidence, and applicability. Front. Psychol. 8:1675. doi: 10.3389/fpsyg.2017.01675
de la Fuente, J., Fernández-Cabezas, M., Cambil, M., Vera, M. M., González-Torres, M. C., and Artuch-Garde, R. (2017a). Linear relationship between resilience, learning approaches, and coping strategies to predict achievement in undergraduate students. Front. Psychol. 8:1039. doi: 10.3389/fpsyg.2017.01039
de la Fuente, J., García-Torrecillas, J. M., and Rodríguez-Vargas, S. (2015a). “The relationships between coping strategies, test anxiety and burnout-Engagement behaviour in university undergraduates,” in Coping Strategies and Health, ed. M. Bachman (New York, NY: Nova Science Publisher), 27–41.
de la Fuente, J., González-Torres, M. C., Martínez-Vicente, J. M., Peralta-Sánchez, F. J., Sander, P., and Amate, J. (2020, in review). Effects of self-regulation and regulatory teaching on the factors and symptoms of academic stress in undergraduate students. Assess. Eval. High. Educ.
de la Fuente, J., López, M., Zapata, L., Sollinas, G., and Fadda, S. (2015b). “Improving mental health through an online self-assessment and self-help e-utility in university students,” in Progress in Education, Vol. 33, ed. R. V. Nata (New York, NY: Nova Publisher), 63–74.
de la Fuente, J., Martínez-Vicente, J. M., Peralta-Sánchez, F. J., Garzón-Umerenkova, A., Vera, M. M., and Paoloni, P. (2019). Applying the SRL vs ERL theory to the knowledge of achievement emotions in undergraduate university students. Front. Psychol. 10:2070. doi: 10.3389/fpsyg.2019.02070
de la Fuente, J., Sander, P., Cardelle-Elawar, M., and Pignata, S. (2016). “Effects of level of regulatory teaching on achievement emotion in the learning process: anxiety and achievement emotions on higher education,” in Teaching and Learning, ed. M. Vargas (New York, NY: Nova Science Publishers, Inc), 131–151.
de la Fuente, J., Sander, P., Martínez-Vicente, J. M., Vera, M. M., Garzón, A., and Fadda, S. (2017b). Combined effect of levels in personal self-regulation and regulatory teaching on meta-cognitive, on meta-motivational, and on academic achievement variables in undergraduate students. Front. Psychol. 8:232. doi: 10.3389/fpsyg.2017.00232
de la Fuente, J., Zapata, L., Martínez-Vicente, J. M., Cardelle-Elawar, M., Sander, P., Justicia, F., et al. (2012). Regulatory teaching and self-regulated learning in college students: confirmatory validation study of the IATLP scales. Electron. J. Res. Educ. Psychol. 10, 839–866.
Dicke, T., Marsh, H. W., Parker, P. D., Pekrun, R., Guo, J., and Televantou, I. (2018). Effects of school-average achievement on individual self-concept and achievement: unmasking phantom effects masquerading as true compositional effects. J. Educ. Psychol. 110, 1112–1126. doi: 10.1037/edu0000259
D’Mello, S. (2013). A selective meta-analysis on the relative incidence of discrete affective states during learning with technology. J. Educ. Psychol. 105, 1082–1099. doi: 10.1037/a0032674
Duffy, M. C., Lajoie, S. P., Pekrun, R., and Lachapelle, K. (2018). Emotions in medical education: examining the validity of the Medical Emotion Scale (MES) across authentic medical learning environments. Learn. Instr. (in press). doi: 10.1016/j.learninstruc.2018.07.001
Fimian, M. J., Fastenau, P. A., Tashner, J. H., and Cross, A. H. (1989). The measure of classroom stress and burnout among gifted and talented students. Psychol. Sch. 26, 139–153. doi: 10.1002/1520-6807(198904)26:2<139::aid-pits2310260205>3.0.co;2-e
Folkman, S. (1997). Positive psychological states and coping with severe stress. Soc. Sci. Med. 45, 1207–1221. doi: 10.1016/s0277-9536(97)00040-3
Folkman, S. (2008). The case for positives emotions in the stress process. Anxiety Stress Coping 21, 3–14. doi: 10.1080/10615800701740457
Folkman, S. (2011). “Stress, health, and coping: synthesis, commentary, and future directions,” in The Oxford Handbook of Stress, Health, and Coping, ed. S. Folkman (Oxford: Oxford University Press), 453–462.
Francis, B., Singh-Gill, J., Yit-Han, N., Petrus, C. F., Azhar, F. L., Ahmad-Sabki, Z., et al. (2018). Religious coping, religiosity, depression and anxiety among medical students in a multi-religious setting. Int. J. Environ. Res. Public Health 16:E259. doi: 10.3390/ijerph16020259
Freire, C., Ferradás, M. M., Núñez, J. C., Valle, A., and Vallejo, G. (2018). Eudaimonic well-being and coping with stress in university students: the mediating/moderating role of self-efficacy. Int. J. Environ. Res. Public Health 16:E48. doi: 10.3390/ijerph16010048
Freire, C., Ferradás, M. M., Valle, A., Núñez, J. C., and Vallejo, G. (2016). Profiles of psychological well-being and coping strategies among university students. Front. Psychol. 7:1554. doi: 10.3389/fpsyg.2016.01554
Frenzel, A. C., Becker-Kurz, B., Pekrun, R., Goetz, T., and Lüdtke, O. (2018). Emotion transmission in the classroom revisited: a reciprocal effects model of teacher and student enjoyment. J. Educ. Psychol. 110, 628–639. doi: 10.1037/edu0000228
Frenzel, A. C., Pekrun, R., Goetz, T., Daniels, L. M., Durksen, T. L., Becker-Kurz, B., et al. (2016). Measuring enjoyment, anger, and anxiety during teaching: the Teacher Emotions Scales (TES). Contemp. Educ. Psychol. 46, 148–163. doi: 10.1016/j.cedpsych.2016.05.003
Garzón-Umerenkova, A., de la Fuente, J., Amate, J., Paoloni, P. V., Fadda, S., and Fiz, J. F. (2018). A linear empirical model of self-regulation on flourishing, health, procrastination, and achievement, among university students. Front. Psychol. 9:536. doi: 10.3389/fpsyg.2018.00536
Gentsch, K., Loderer, K., Soriano, C., Fontaine, J. R., Eid, M., Pekrun, R., et al. (2018). Effects of achievement contexts on the meaning structure of emotion words. Cogn. Emot. 32, 379–388. doi: 10.1080/02699931.2017.1287668
Goetz, T., Frenzel, A. C., Hall, N. C., Nett, U. E., Pekrun, R., and Lipnevich, A. A. (2014). Types of boredom: an experience sampling approach. Motiv. Emot. 38, 401–419. doi: 10.1007/s11031-013-9385-y
González-Torres, M. C., and Artuch, R. (2014). Resilience and coping strategy profiles at university: contextual and demographic variables. Electron. J. Res. Educ. Psychol. 12, 621–648. doi: 10.14204/ejrep.34.14032
Gross, J. J. (2015a). Emotion regulation: current status and future prospects. Psychol. Inq. 26, 1–26. doi: 10.1080/1047840X.2014.940781
Gross, J. J. (2015b). The extended process model of emotion regulation: elaborations, applications, and future directions. Psychol. Inq. 26, 130–137. doi: 10.1080/1047840X.2015.989751
Gustems-Carnicer, J., Calderon, C., Batalla-Flores, A., and Esteban-Bara, F. (2019). Role of coping responses in the relationship between perceived stress and psychological well-being in a sample of Spanish educational teacher students. Psychol. Rep. 122, 380–397. doi: 10.1177/0033294118758904
Harley, J. M., Pekrun, R., Taxer, J. L., and Gross, J. J. (2019). Emotion regulation in achievement situations: an integrated model. Educ. Psychol. 54, 106–126. doi: 10.1080/00461520.2019.1587297
Hederich-Martínez, C., and Camargo, U. A. (2019). Critical review of J. Vermunt’s learning pattern model. Rev. Colomb. Educ. 77, 1–25. doi: 10.17227/rce.num77-9469
Hirvonena, R., Yli-Kivistöa, L., Putwain, D. W., Ahonena, T., and Kiuru, N. (2019). School-related stress among sixth-grade students – associations with academic buoyancy and temperament. Learn. Individ. Differ. 70, 100–108. doi: 10.1016/j.lindif.2019.01.012
Holinka, C. (2015). Stress, emotional intelligence, and life satisfaction in college students. Coll. Stud. J. 49, 300–311.
Kamijo, N., and Yukawa, S. (2018). The role of rumination and negative affect in meaning making following stressful experiences in a Japanese sample. Front. Psychol. 9:2404. doi: 10.3389/fpsyg.2018.02404
Kassymova, K. G., Tyumaseva, Z. I., Valeeva, G. V., Lavrinenko, S. V., Arpentieva, M. R., Kenzhaliyev, B. K., et al. (2019). Integrative model of student and teacher stress coping: the correction of relations in educational, profesional and personal interaction. Bull. Natl. Acad. Sci. Repub. Kazagistan 3, 169–179.
Kim, L. E., Jorg, V., and Klassen, R. M. (2019). A meta-analysis of the effects of teacher personality of teacher effectiveness and burnout. Educ. Psychol. Rev. 31, 163–195. doi: 10.1007/s10648-018-9458-2
Kobyliñska, D., and Kusev, P. (2019). Flexible emotion regulation: how situational demands and individual differences influence the effectiveness of regulatory strategies. Front. Psychol. 10:72. doi: 10.3389/fpsyg.2019.00072
Lazarus, R. S., and Folkman, S. (1984/1986). Estrés y Procesos Cognitivos. Barcelona: Martínez Roca.
Lekwa, A. J., Reddy, L. A., and Shernoff, E. S. (2018). Measuring teacher practices and student academic engagement: a convergent validity study. Sch. Psychol. Q. 34, 109–118. doi: 10.1037/spq0000268
Linnenbrink-Garcia, L., and Pekrun, R. (2011). Students’ emotions and academic engagement [Special issue]. Contemp. Educ. Psychol. 36, 1–3. doi: 10.1016/j.cedpsych.2010.11.004
Loderer, K., Pekrun, R., and Lester, J. C. (2018). Beyond cold technology: a meta-analytic review of research on emotions in technology-based learning environments. Learn. Instr. (in press). doi: 10.1016/j.learninstruc.2018.08.002
Lüftenegger, M., Klug, J., Harrer, K., Langer, M., Spiel, C., and Schober, B. (2016). Students’ achievement goals, learning-related emotions and academic achievement. Front. Psychol. 7:603. doi: 10.3389/fpsyg.2016.00603
Mainhard, T., Oudman, S., Hornstra, L., Bosker, R. J., and Goetz, T. (2018). Student emotions in class: the relative importance of teachers and their interpersonal relations with students. Learn. Instr. 53, 109–119. doi: 10.1371/journal.pone.0201442
Martín, M. O., Trujillo, F. D., and Moreno, N. (2003). Estudio y evaluación del estrés académico en estudiantes de grado de ingenierías industriales en la universidad de Málaga [academic stress evaluation in industrial engineering in the university of Malaga]. Rev. Educ. Hekademos 13, 55–63.
Martínez, I. M., Meneghel, I., and Penalver, J. (2019). Does gender affect coping strategies leading to well-being and improved academic performance? Rev. Psicodidáctica 24, 111–119. doi: 10.1016/j.psicoe.2019.01.002
Miller, W. R., and Brown, J. M. (1991). “Self-regulation as a conceptual basis for the prevention and treatment of addictive behaviours,” in Self-Control and the Addictive Behaviours, eds N. Heather, W. R. Miller, and J. Greeley (Sydney: Maxwell Macmillan Publishing Australia), 3–79.
Moffa, K., Dowdy, E., and Furlong, M. J. (2016). Exploring the contributions of school belonging to complete mental health screening. Educ. Dev. Psychol. 33, 16–32. doi: 10.1017/edp.2016.8
Murayama, K., Goetz, T., Malmberg, L.-E., Pekrun, R., Tanaka, A., and Martin, A. J. (2017). “Within-person analysis in educational psychology: importance and illustrations,” in British Journal of Educational Psychology Monograph Series II: Psychological Aspects of Education – Current Trends: The Role of Competence Beliefs in Teaching and Learning, eds D. W. Putwain and K. Smart (Oxford: Wiley).
Palmer, A., and Rodger, S. (2009). Mindfulness, stress and coping among university students. Can. J. Couns. 43, 198–212.
Paris, S., and Winograd, P. (2003). The Role of Self-Regulated Learning in Contextual Teaching: Principals and Practices for Teacher Preparation. Washington, DC: Office of Educational Research and Improvement.
Park, C. L., and Adler, N. E. (2003). Coping style as a predictor of health and well-being across the first year of medical school. Health Psychol. 22, 627–631. doi: 10.1037/0278-6133.22.6.627
Pichardo, M. C., Cano, F., Garzón-Umerenkova, A., de la Fuente, J., Peralta-Sánchez, F. J., and Amate-Romera, J. (2018). Self-regulation questionnaire (SRQ) in Spanish adolescents: factor structure and Rasch analysis. Front. Psychol. 9:1370. doi: 10.3389/fpsyg.2018.01370
Pichardo, M. C., Justicia, F., de la Fuente, J., Martínez-Vicente, J. M., and Berbén, A. B. (2014). Factor structure of the self-regulation questionnaire (SRQ) at Spanish universities. Span. J. Psychol. 17:E62. doi: 10.1080/02699931.2016.1204989
Pidgeon, A. M., and Pickett, L. (2017). Examining the differences between university students’ levels of resilience on mindfulness, psychological distress and coping strategies. Eur. Sci. J. 13, 103–113.
Putwain, D. W. (2018). An examination of the self-referent executive processing model of test anxiety: control, emotional regulation, self-handicapping, and examination performance. Eur. J. Psychol. Educ. 34, 341–358. doi: 10.1007/s10212-018-0383-z
Putwain, D. W., Pekrun, R., Nicholson, L. J., Symes, W., Becker, S., and Marsh, H. W. (2019). Control-value appraisals, enjoyment, and boredom in mathematics: a longitudinal latent interaction analysis. Am. Educ. Res. J. 55, 1339–1368. doi: 10.3102/0002831218786689
Rapillard, S., Plexico, L. W., and Plumb, A. M. (2019). Influence of graduate speech language pathology student’s learning style and coping strategies on training and development. Teach. Learn. Commun. Sci. Disord. 3, 2–24. doi: 10.30707/TLCSD3.1Rapillard
Rusk, R., Tamir, M., and Rothbaum, F. (2011). Performance and learning goals for emotional regulation. Motiv. Emot. 35, 444–460. doi: 10.1007/s11031-011-9229-6
Saklofske, D. H., Austin, E. J., Mastoras, S. M., Beaton, L., and Osborne, S. E. (2012). Relationships of personality, affect, emotional inteligence and coping with student stress and academic success: different patterns of association for stress and success. Learn. Individ. Differ. 22, 251–257. doi: 10.1016/j.lindif.2011.02.010
Scharp, K. M., and Dorrance, E. (2017). Examining the relationship between undergraduate student parent social support-seeking factors, stress, and somatic symptoms: a two-model comparison of direct and indirect effects. Health Commun. 34, 54–64. doi: 10.1080/10410236.2017.1384427
Shannon, M., Suldo, S. M., Storey, L. D., O’Brennan, L. M., Shaunessy-Dedrick, E., Ferron, J. M., et al. (2019). Identifying high school freshmen with signs of emotional or academic risk: screening methods appropriate for students in accelerated courses. School Ment. Health 11, 210–227. doi: 10.1007/s12310-018-9297-9
Shaw, M. P., Peart, D. J., and William, O. J. (2017). Perceived stress in university students studying in a further education college. Res. Post Compulsory Educ. 22, 442–452. doi: 10.1080/13596748.2017.1362534
Tada, A. (2017). The associations among psychological distress, coping style, and health habits in Japanese nursing students: a cross-sectional study. Int. J. Environ. Res. Public Health 14:E1434. doi: 10.3390/ijerph14111434
Vanthournout, G., Donche, V., Gijbels, D., and Van Petegem, P. (2014). “(Dis)similarities in research on learning approaches and learning patterns,” in Learning Patterns in Higher Education, eds G. Gijbels, V. Donche, J. Richardson, and J. Vermunt (London: Routledge), 9–32.
Vermunt, J., Bronkhorst, L. H., and Martínez-Fernández, J. R. (2014). “The dimensionality of student learning patterns in different cultures,” in Learning Patterns in Higher Education, eds G. Gijbels, V. Donche, J. Richardson, and J. Vermunt (London: Routledge), 33–55.
Vermunt, J. D. (1998). The regulation of constructive learning processes. Br. J. Educ. Psychol. 68, 149–171. doi: 10.1111/j.2044-8279.1998.tb01281.x
Vermunt, J. D. (2005). Relations between student learning patterns and personal and contextual factors and academic performance. High. Educ. 49, 205–225.
Vermunt, J. D. (2007). The power of teaching-learning environments to influence student learning. Br. J. Educ. Psychol. Monogr. Ser. 4, 73–90.
Vermunt, J. D., and Donche, V. (2017). A learning patterns perspective on student learning in higher education: state of the art and moving forward. Educ. Psychol. Rev. 29, 269–299. doi: 10.1007/s10648-017-9414-6
Vermunt, J. D., and Vermetten, Y. J. (2004). Patterns in student learning: relationships between learning strategies, conceptions of learning, and learning orientations. Educ. Psychol. Rev. 16, 359–384. doi: 10.1007/s10648-004-0005-y
Willcoxson, L., Cotter, J., and Joy, S. (2011). Beyond the first year experience: the impact on attrition of student experiences throughout undergraduate degree studies in six diverse universities. Stud. High. Educ. 36, 331–352. doi: 10.1080/03075070903581533
Zimmerman, B. J. (2001). “Theories of self-regulated learning and academic achievement: an overview and analysis,” in Self-Regulated Learning and Academic Achievement: Theoretical Perspectives, 2nd Edn, eds B. J. Zimmerman and D. H. Schunk (Mahwah, NJ: Erlbaum), 1–35.
Zimmerman, B. J. (2008). “Goal setting: a key proactive source of academic self-regulation,” in Motivation and Self-Regulated Learning, eds D. H. Schunk and B. J. Zimmerman (New York, NY: Erlbaum), 267–295.
Keywords: SRL vs. ERL theory, academic stress, coping strategies, university, students
Citation: de la Fuente J, Amate J, González-Torres MC, Artuch R, García-Torrecillas JM and Fadda S (2020) Effects of Levels of Self-Regulation and Regulatory Teaching on Strategies for Coping With Academic Stress in Undergraduate Students. Front. Psychol. 11:22. doi: 10.3389/fpsyg.2020.00022
Received: 30 August 2019; Accepted: 07 January 2020;
Published: 31 January 2020.
Edited by:
Lawrence Jun Zhang, University of Auckland, New ZealandReviewed by:
Norzarina Mohd-Zaharim, University of Science Malaysia, MalaysiaDušana Šakan, Faculty of Legal and Business Studies Dr Lazar Vrtakiæ, Serbia
Copyright © 2020 de la Fuente, Amate, González-Torres, Artuch, García-Torrecillas and Fadda. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Jesús de la Fuente, jdlfuente@unav.es