Skip to main content

REVIEW article

Front. Psychol., 07 March 2024
Sec. Educational Psychology

Classic and modern models of self-regulated learning: integrative and componential analysis

  • Department of Developmental and Educational Psychology, University of Santiago de Compostela, Santiago de Compostela, Spain

Self-regulated learning (SRL) is considered a construct of great heuristic value and has attracted the attention of numerous researchers and inspired influential theoretical models. The objective of the present study was to provide an up-to-date, comparative and integrated description of the theoretical models of SRL used in current empirical research. For this purpose, we conducted a critical review of the scientific literature referring explicitly to any SRL model and we described, compared and integrated the processes and personal and situational dimensions considered in each model. The models have clearly evolved from focusing on cold self-regulation, conscious activity and individual functioning, to emphasising hot self-regulation and considering implicit activity and interindividual functioning. Among empirical research lines based on the most recent models, the following stand out: detailed analysis of SRL during its progress, the manifestation of SRL in diverse instructional formats and the role of affective/motivational self-regulation.

1 Introduction

Self-regulated learning (SRL) has been defined as an active constructive process, in which students’ thoughts, feelings and actions are self-generated and deliberately oriented to achieving personal learning goals, and which is influenced by environmental factors (Boekaerts, 1996a,b; Pintrich, 2000; Zimmerman, 2000). Students use different types of learning strategies (e.g., cognitive, motivational, etc.) that they select, execute and adapt according to their aims and depending on their personal dispositions and characteristics. It is a situated process, in which various distant (e.g., family educational patterns and school climate) and proximal (e.g., instructions and resources regarding a task in process) contextual factors play a key role, thus determining the acquisition and implementation of learning strategies (Ben-Eliyahu and Bernacki, 2015).

The historical origin of the SRL construct is usually considered to have occurred in 1986, when the American Educational Research Association organized a symposium with the aim of combining contributions of particular importance regarding what were then judged to be the essential components of strategic functioning in the educational field: learning strategies, metacognition, self-concept, volitional strategies and self-control (Zimmerman, 2008). Numerous research studies have since been conducted in relation to SRL, yielding a multitude of articles and monographs (see, e.g., Boekaerts et al., 2000; Schunk and Green, 2018). These reports aim to clarify the nature and development of SRL, its relationship with academic achievement and the role of personal goals in self-regulation processes, among other aspects. The importance that SRL has acquired is demonstrated by the attention given to the construct in current Educational Psychology handbooks and by the international recognition of the value of self-regulation as a basic skill that should be promoted in educational systems (Ananiadou and Claro, 2009).

The construct has undoubtedly been of great heuristic value, inspiring global theoretical models in which phases and components (processes and personal and situational dimensions) are delimited. The proposed SRL models, from the earliest to the most recent, differ in aspects such as their theoretical background and the detail and emphasis with which the SRL phases and components are treated. Critical reviews by Panadero (2017) and Puustinen and Pulkkinen (2001) have helped to reveal common points and differences in the various models. By taking these reviews into consideration and adopting a similar approach to analyze the most recent theoretical proposals, the main aim of this study was to provide an up-to-date, comparative and integrated description of the main SRL models, i.e., those referred to in the scientific literature as valuable for exploring the nature of the SRL components and their interrelationships and conditioning factors. More precisely, we aimed to undertake the following:

- Compile the main theoretical models of SRL that guide empirical research on the construct, including graphical representations.

- Describe the main assumptions of the models and the essential characteristics of the representations, highlighting the contributions of each.

- Disentangle the SRL components (processes and personal and situational dimensions) considered in each model and compile a comprehensive, integrated list of these components.

This critical review addresses the following research questions:

RQ1: What are the essential characteristics and components of existing theoretical models on SRL?

RQ2: How have theoretical models of SRL evolved?

2 Method

We conducted a literature search in the WOS and PsycInfo databases, using the expression “self-regulated learning AND model*,” for the period from 2015 to the present. In order to encompass the diversity of theoretical developments and empirical lines of research inspired by SRL models, we decided to prioritize the sensitivity of the search strategy over its specificity. Thus, we selected generic search terms. The search expression used was “self-regulated learning AND model*.” In total, we compiled 705 references, 11 of which were duplicates. The reports retrieved consisted of 688 peer reviewed articles and 6 book chapters.

We examined the theoretical basis of the reports retrieved, selecting those that explicitly referred to an SRL model or review of SRL models (total, 198). Exclusion criteria were not applied. The complete text of each study selected was screened for theoretical background and citations of theoretical models of SRL. Finally, we compiled the original publications reporting each of the models referred to in the reports reviewed and proceeded to summarise them. Focus was placed on the components and processes of the models as well as on the assumptions about their interrelations.

3 Results

The number of reports published, expressly based on SRL models, has increased gradually, with 2021 and 2022 being the most productive years. Most of the reports selected (51%) were explicitly based on the cyclical phase model developed by Zimmerman (1998b, 2000). The model of Winne and Hadwin (1998) was the second most cited (35%), followed by those of Pintrich (2000) (31%) and Boekaerts (2006, 2007) (12.6%). Unsurprisingly, given that there will be a time lag before the publication of relevant research findings in relation to the theoretical proposals, the most recent models were the least commonly cited. In addition, the review article by Panadero (2017) was cited in 16.6% of the reports, while that by Puustinen and Pulkkinen (2001) was less frequently cited (5%).

Below we present a summarised description of the characteristics and central assumptions of the SRL models selected. For this purpose, we have included figures representing the models and we have focused on emphasising the characteristics of each in the text. Thus, the reader can observe the evolution and status of SRL construct, which have been shaped by the most outstanding authors in the field.

3.1 Classic models

We consider the models included in this section as classic, as they have served to forge a body of assumptions shared by different psychological perspectives, which constituted an important stimulus for the research on SRL (Zeidner et al., 2000; Usher and Schunk, 2018).

The proposals of Zimmerman (1989, 1990, 1994, 1998a,b, 2000) are some of the first and most widely recognised in relation to SRL. Specifically, in the Triadic Analysis of SRL, Zimmerman (1989, 1990) adopts the assumptions of the social cognitive perspective of human self-regulation and proposes multidimensionality as its essential characteristic. This model considers three sources of reciprocal influence involved in self-regulation and that should be considered in the field of education: personal (covert beliefs, such as self-perception and knowledge of one’s own regulatory processes, and affective processes), behavioural (covert and overt conduct) and environmental (physical and social context). Projection of these sources of influence on the agentic functioning of students led (Zimmerman, 1994, 1998a) to distinguish different dimensions of self-regulation related to fundamental research questions: motivational (why is the individual taking part in the learning process), methodological (how the individual approaches the learning process), temporal (when the different steps of the personal action plan are applied), behavioural (what overt conduct is initiated/modified), contextual (where the learning takes place, in terms of the physical environment) and social (who the student can and would like to count on for support during the learning process).

Finally, the cyclical phase model (Zimmerman, 1998b; Zimmerman and Moylan, 2009) delimits three recursive stages of SRL (see Figure 1):

1. Forethought, which includes processes that precede and form the basis of the learning effort and the development of the self-regulation process, particularly to establish objectives.1

2. Performance, related to the processes that take place during the learning task and that affect attention and the course of action.

3. Self-reflection, which involves processes posterior to task execution, and accounts for cognitive and motivational reactions in response to the learning experience and that form the basis of the forethought phase in subsequent trials of the learning cycle.

Figure 1
www.frontiersin.org

Figure 1. Zimmerman and Moylan's cyclical model. From Zimmerman and Moylan (2009, p. 300). Copyright (© 2009) and Imprint. Reproduced by permission of Taylor & Francis Group.

The models developed by Boekaerts (1991, 1995, 2006, 2007) have also had an important influence in the field of educational psychology. This author focuses on the role of the motivational dynamics that drive the individual within the SRL cycle. Her adaptable learning model (see Figure 2) considers two alternative processing modes (mastery and coping), which correspond to the preponderance of one or other type of the principal motives of the student when confronted with a learning task.

Figure 2
www.frontiersin.org

Figure 2. Boekaerts' adaptable learning model. WM = working model. From Boekaerts (1996a, p. 456). Copyright (1996) by John Wiley & Sons, Inc. Reproduced with permission.

The mastery mode originates in the aspiration to expand the personal repertoire of knowledge and skills and entails activation of learning strategies. On the other hand, the coping mode is brought about by the desire to preserve well-being and prevent any possible loss, damage or distortion of this state (Boekaerts, 1991, 1995) and involves activation of self-defence strategies, which may hamper learning. The balance between these modes depends on the appraisal based on an internal model of the learning situation (working model, WM), conformed according to three sources of information: (1) the characteristics of the task in question (demands and conditions in which it is presented); (2) the domain, declarative and procedural information that the student possess relative to the task, and (3) the contents of the self-system which are activated by the task (motivational values and beliefs). The appraisal may involve the perceived congruence between the value attributed to and the resources available for conducting the task, which will produce positive affective reactions and direct the student towards the mastery mode. On the other hand, appreciation of incongruencies, which may threaten personal well-being, will generate negative affective states and direct the individual towards the coping mode. The individual’s actions linked to a task may be initiated by either of these routes and then change depending on successive appraisals of the task being undertaken.

After the initial formulation of her model, Boekaerts showed increasing interest in the circumstances that determine the transition between the two alternative routes of processing and the role of the satisfaction of basic psychological needs and also in volitional processes that maintain or, where applicable, return the student to the mastery mode (see, e.g., Boekaerts and Niemivirta, 2000). The author further explored theoretical arguments in support of her view of SRL, compiled empirical evidence and finally presented her a dual-processing model (Boekaerts, 2006, 2007) (see Figure 3). This model includes a volitional self-regulation path, which ranges from the coping pathway (now denominated well-being) to the mastery pathway (now growth) and which reflects the student’s attempts to remain focused on the task, despite any obstacles or distractions that may arise. This would involve the use of different strategies aimed at controlling affective and motivational reactions associated with the difficulties found in undertaking the task.

Figure 3
www.frontiersin.org

Figure 3. Boekaerts´dual processing model. WM = working model. From Boekaerts (2006, p. 350). Copyright (2006) by John Wiley & Sons, Inc. Reproduced with permission.

Coinciding with publication of the previous models, Winne and Hadwin (1998) also made an influential proposal, elaborated from the perspective of information processing. In the proposal, the student’s monitoring of their own cognitive activity acquires a central role, as a key process that guides control of the activity in each of the phases of SRL (see Figure 4). Illustrative examples of the way in which monitoring is manifested in the different phases of SRL are given in the original release of the model and in later publications by Winne and colleagues (Winne and Perry, 2000; Winne, 2001, 2011; Winne and Hadwin, 2008).

Figure 4
www.frontiersin.org

Figure 4. Winne and Hadwin's COPES metacognitive monitoring and control. From Winne and Hadwin (1998, p. 329). Copyright (© 1998) and Imprint. Reproduced by permission of Taylor & Francis Group.

The planning phase identified in Zimmermann’s model (Zimmerman, 1998b, 2000) is divided into (1) task definition and (2) goal setting and planning. The available information about the task conditions, including the specifications provided for execution (e.g., materials and knowledge required, individual or group learning method, etc.), is processed in the first phase. These appear in Figure 4 as standard (s). The student can decide to monitor this initial representation of the task, ensuring correct understanding of the demands. In the second phase, the student generates a personal profile of selected standards, i.e., a set of objectives in terms of ideal, optimal or satisfactory states to achieve, regarding behaviour, cognition or motivation. Once this profile has been established, the operations (tactics and strategies) that constitute the plan of action are activated. The plan can be monitored metacognitively (mentally tested), which may lead to redefinition of the task or of the plan of action. In the third phase (enacting tactics), the student carries out the plan, the results of which are also monitored and, in this case, checked against the personalized standards. This internal feedback will be complemented by any external feedback provided and can also lead to changes in the profile of standards and the plan of action. Optionally, on completing the task, in a fourth (adaptation) phase, the student monitors the overall way that the procedure has occurred, generating an improved representation of the task features and the best way of acting, which can later be applied to similar tasks.

The phases are implicitly included in the diagram of the model (Figure 4), in which a series of boxes that include essential components of SRL stand out. We will consider these components in the following section.

Finally, any review of the classic models must include mention of those developed by Pintrich (2000, 2004), who, also inspired by a social cognitive view, integrated both phases and areas of self-regulation, which are, respectively, placed in the columns and rows of a representative table (see Table 1). The model subdivides the performance phase into two (monitoring and control) and subsumes the 6 dimensions of self-regulation differentiated by Zimmerman in four areas (cognition, motivation/affect, behaviour and context). Pintrich also adds specifications about the personal processes and dimensions involved, based on metacognitive and motivational notions.

Table 1
www.frontiersin.org

Table 1. Pintrich’s phases and areas model.

Regarding the metacognitive facet, in the first phase of SRL (forethought, planning and activation) the model of Pintrich (2000) includes efficacy judgements and ease of learning judgements, derived from the knowledge about the task and its context and self-knowledge in relation to the task (in the table, metacognitive knowledge). The monitoring phase includes feelings of knowing and judgements of learning, the latter being related to the fluidity of task processing and impediments that arise during its execution.

Regarding the motivational facet, the model includes self-efficacy, attributions, task value and affective reactions; the activation, monitoring and control of these are explicitly contemplated in the different phases of the model. The inclusion of self-regulation of motivational dimensions is, in fact, one of the distinctive features of the model. The so-called goal orientations deserve special mention for the special role that the author confers them in SRL. Thus, the author conceives these as general motives explaining why the student engages in academic tasks, which originate from the representations of desired results and/or states, and which condition the monitoring and control processes used during task execution (Pintrich, 2000).

Indeed, Pintrich’s interest in both the (meta) cognitive and motivational facets of learning is patent in studies published prior to the model, and it is projected in the Motivated Strategies for Learning Questionnaire (MSLQ; Pintrich et al., 1991), which is probably the questionnaire most widely used internationally to evaluate SRL. Pintrich’s model has been given visibility by its integrative nature as it explicitly includes cognitive, motivational, behavioural, and contextual dimensions and thus highlights the multidimensionality of SRL (Limón et al., 2004).

3.2 Modern models

In general, the models presented below can be characterized as derivations of the classic models in four directions: from a macro (generic) to a micro (detailed/situated) focus; from cold to hot self-regulation (by the gradual weighting of affective-motivational states and their self-regulation); from conscious to implicit activity; and from individual to interindividual functioning.

The Metacognitive and Affective Model of Self-Regulated Learning (MASRL) developed by Efklides (2011, 2018) is a clear example of the first three tendencies. This model distinguishes two levels of processing, which include three types of metacognitive phenomena differentiated by Flavell (1979) (see Figure 5). Thus, the macro or Person level, comprising stable characteristics of the individual that transcend specific learning episodes, includes metacognitive knowledge. This refers to declarative information about oneself, academic tasks and learning strategies stored in memory and that form the basis of performance of academic tasks. The micro or Task x Person level includes online processing of the task, in which metacognitive experiences become important. These experiences include judgements and feelings generated during task monitoring, in the three phases of SRL contemplated in the model (task representation, cognitive processing and task performance) and the active knowledge related to the task. Finally, metacognitive skills condense procedural knowledge (represented in the macro level) and the practical application (represented at the micro level) of strategies for controlling cognition (executive processes), understood as conscious and intentionally displayed procedures.

Figure 5
www.frontiersin.org

Figure 5. Efklides’ metacognitive and affective model of self-regulated learning. metacognitive knowledge; MS = metacognitive skills; ME = metacognitive experiences. From Efklides (2011, p. 7). Copyright © by Division 15, American Psychological Association. Reproduced by permission of Informa UK Limited, trading as Taylor & Francis Group, www.tandfonline.com on behalf of Division 15, American Psychological Association.

The author considers in detail the role of metacognitive experiences, regarded as manifestation of metacognition in everyday situations, and she emphasizes the role of metacognitive feelings (e.g., confidence in carrying out a task correctly or satisfaction with having achieved an established objective). These feelings emerge unconsciously and transmit the personal relevance attributed to a particular learning task, endowing the cognitive act with affective load (pleasant or unpleasant emotions) associated with the cognitive act. The author of the model also contemplates the possibility that unconscious heuristic processes, i.e., routines established by experience with other similar tasks, also participate in SRL processes. On the other hand, Efklides (2011) draws attention to the role of metacognitive experiences in the social shaping of cognition, as well as in teaching SRL and in collaborative learning dynamics, aspects which this author studied prior to publication of the MASRL model (Salonen et al., 2005; Efklides, 2008).

The model developed by Hadwin et al. (2011), Järvelä and Hadwin (2013), and Hadwin et al. (2018) illustrates precisely the necessary social nature of SRL and differentiates three modes in which this can be manifested, in an interactive and collaborative learning environment (see Figure 6).

Figure 6
www.frontiersin.org

Figure 6. Hadwin et al.'s model of socially shared regulated learning. From Järvelä and Hadwin (2013, p. 29). Copyright © Division 15, American Psychological Association. Reproduced by permission of Informa UK Limited, trading as Taylor & Francis Group, www.tandfonline.com on behalf of Division 15, American Psychological Association.

First, self-regulated learning, which refers to the functioning of each student separately, regarding the same task. The authors emphasize that, even in this case the SRL process is a socio-historic and environmentally situated process, in the sense that it is shaped by personal and group beliefs and experiences, by the context of the task and by the involvement, along with others, in its execution. Second, co-regulated learning, consisting of the stimulation produced by the self-regulated learning experience of another, giving rise to exchange or internalization of self-regulation processes. Third, socially shared regulation, produced when the self-regulation processes are interdependent and/or jointly constructed during episodes of cooperative learning.

We consider the motivational regulation model of Schwinger and Stiensmeier-Pelster (2012) a clear example of the gradual incorporation of hot aspects of self-regulation. This model directs our attention towards the role of the strategies that the students use to regulate their motivation, as an essential factor determining their performance. Such strategies are activated in response to the realization that the motivational state is insufficient for continuing with a task once initiated (see Figure 7).

Figure 7
www.frontiersin.org

Figure 7. Schwinger and Stiensmeier-Pelster's model of motivational regulation. From Schwinger and Stiensmeier-Pelster (2012). Copyright (2012) by Elsevier Inc. Reproduced with permission.

Once the deficit has been perceived, the student deduces the cause, which may be situational (transitory) or fundamental (stable). Taking these aspects into account, the student will select which strategies of motivational self-regulation to apply and the way of doing so (either maintaining the activity or elevating the basic motivation). The efficacy of the process is assumed to depend on the student’s skill in detecting a possible deficit in motivation and adjusting the strategy accordingly. Regarding the latter, the contribution made by Schwinger’s group can be considered essential, i.e., design of the Motivational Regulation Questionnaire (MRQ; Schwinger et al., 2009), a tool that has been well received by the scientific community.

Miele and Scholer (2018) provide a more recent, detailed conceptualization of motivational self-regulation in their Metamotivational Model (see Figure 8).

Figure 8
www.frontiersin.org

Figure 8. Miele and Scholer’s model of motivational regulation. From Miele and Scholer (2018, p. 2). Copyright (© 2017) by Division 15, American Psychological Association. Reproduced by permission of Informa UK Limited, trading as Taylor & Francis Group, on behalf of Division 15, American Psychological Association.

In this model, the initial motivation to engage in a task is understood to be formed as a function of a specifically established objective (oval G in Figure 8; e.g., getting a good mark in an exam), which in turn depends on some type of aspiration of a higher order (oval F; e.g., performing well throughout the course). The self-efficacy and the task value are specified as motivational dimensions to be monitored and controlled (box B1 in Figure 8), at the start and throughout execution of the task. The state of these dimensions is assumed to be bidirectionally associated with the processing mode used in the task (box B2); this association is modulated by the predicted cost and obstacles that will occur during execution (box A). Monitoring the motivational state (metamotivational monitoring; routes between C and D) can occur in a downwards direction, when it is controlled by executive processes, such as, e.g., when the student evaluates whether their motivation is sufficient to allow a plan of action to be carried out. On the other hand, it can occur in an upwards direction when it is guided by metamotivational feelings (phenomenological experiences such as pleasure or frustration), indicative of the state of the motivational components and, when applicable, of the possible risk of abandonment or change in the initial objective. This process is sustained in metamotivational knowledge (oval H), i.e., that related to the motivational requisites of the task, the motivational self-regulation strategies and the personal ability to execute the strategies. Finally, the motivational self-regulation strategies play a key role in the metamotivational control (route from box E to B), i.e., in maintaining or increasing the level of motivation for carrying out a specific task, with an established objective. The model authors point out that metamotivational monitoring and control can proceed in a conscious or automatic manner.

Both of these modes of processing are specifically represented in the interactive layers model recently proposed by Wirth et al. (2020) (Figure 9). The authors include sensorial memory as a necessary explanatory structure, through which information from the environment and that activated by the task in the individual student enters the cognitive system. The information may be of three types (learning content, cognitive procedures and metacognitive procedures) corresponding to three simultaneous layers of processing. The authors provide a representative figure for each of the layers. The figure including the learning content layer is shown below by way of example.

Figure 9
www.frontiersin.org

Figure 9. Wirth et al.’s interactive layers model. From Wirth et al. (2020, p. 1132). Copyright (2020) by Springer. CC-BY-NC.

If the information that the sensory memory accesses coincides with that stored in the long-term memory, resonance occurs, i.e., the coincidental information is reinforced and acquires prominence in the learning process, which can proceed unconsciously. However, if the resonance is sufficiently intense or lasting, a conscious process may occur, whereby the resonant information is intentionally processed in the short-term memory. On the other hand, the non-resonant information is discarded, except when it is sufficiently strong, in which case a search is initiated for concordant information in the long-term memory.

A common feature of all of the models described is that they all have a dynamic view of SRL, i.e., they propose a cyclical sequence of events that form a prototypical generic learning episode (Zeidner and Stoeger, 2019). Different interdependent components come into play throughout the sequence (processes, dispositions, states and environmental conditions). As an alternative mode of analyzing the nature of SRL, some authors have considered differentiating and classifying these components, proposing what have come to be known as static or componential models (Wirth and Leutner, 2008; Sitzmann and Ely, 2011), in contrast to the models described so far, distinguished as dynamic. Below we present an analysis of the treatment of SRL components in both types of proposals.

3.3 Components analysis

We have compiled five published classifications of SRL components, which we present in Table 2, with the aim of facilitating comparison of the similarities and differences. As can be observed, the first two classifications subdivide the components depending on whether they correspond to motivation or cognition, understood as domains of self-regulation in the approach used by Garcia and Pintrich (1994) and as regulatory systems in that used by Boekaerts (1996b). A coincident transverse organization can also be noted, which corresponds to the facets of metacognition differentiated by Flavell (1979) and specifically recognised in the dynamic models of Pintrich (2000, 2004) and Efklides (2011, 2018): metacognitive knowledge, skills and experiences. However, the last type of component is only included in the last three classifications, giving these a more situated nature than the first two.

Table 2
www.frontiersin.org

Table 2. Components of self-regulated learning (SRL) considered in static models.

The proposal of Winne and Hadwin (1998) deserves special mention. This model includes five componential categories (represented by the acronym COPES), which we understand are also similar to the metacognitive facets. Thus, the category conditions groups components that determine the personal representation of the task, including the available resources and restrictions, derived from the external context (e.g., instructional clues and social dynamics of the classroom) and internal conditions (e.g., prior knowledge of the learning strategies and styles); this is therefore the equivalent of metacognitive knowledge. The operations category combines the different modes of cognitive manipulation of the information (tactics and strategies) and thus corresponds to metacognitive skills. These generate products, a third category that includes the cognitive, motivational, affective and behavioural results of the operations. These products constitute new conditions for successive phases of SRL. In fact, in the dynamic model of Winne and Hadwin (1998), the phases take the names of the characteristic products generated: (1) task definition, (2) goals and plan (s), (3) study tactics and (4) adaptations. The category evaluations includes the judgements and feelings generated during execution of the task, thus coinciding with the metacognitive experiences. Finally, the category standards combines attributes, in terms of ideal, optimal and satisfactory states, which the student aspires to in the task being executed. These constitute the task objectives and serve as reference points for successive evaluations. In this respect, the standards can be considered part of metacognitive knowledge.

With the aim of evaluating the importance attributed to the SRL components and localizing their position in the cyclical sequence reflected in the dynamic models, we have elaborated a comparative table (Table 3), in which we list the components that explicitly appear in the models.

Table 3
www.frontiersin.org

Table 3. Components of self-regulated learning considered in dynamic models.

In the dynamic models, the components corresponding to metacognitive knowledge are located systematically in the phase prior to the start of task execution, except in the model of Miele and Scholer (2018). This model emphasizes that self-efficacy and the task value are modulated by metamotivational monitoring and control throughout the whole SRL cycle. The authors thus adopt a componential approach that we can qualify as “state-based,” complementary to the view of the components analysis in terms of traits, which prevail in the models.

The components related to metacognitive skills are linked to execution of the task, although in the model of Miele and Scholer (2018) motivation is controlled from the start to the end of the learning episode.

The components related to metacognitive experiences reflect the monitoring process that takes place during task execution. However, in the model of Miele and Scholer (2018), this process extends to the phase(s) prior to task execution, while those of Zimmerman and Moylan (2009) and Winne and Hadwin (1998) also explicitly includes self-evaluation after finalization of the task.

Finally, we can see that the dynamic models delimit SRL processes and states. However, the degree of detail varies depending on the metacognitive facets. Thus, metacognitive and metamotivational knowledge and beliefs are very detailed (particularly the latter). The learning strategies are generally referred to in a global way in the dynamic models, with the exceptions of the detailed cognitive strategies included in the models of Zimmerman and Moylan (2009) and Wirth et al. (2020), of resource management strategies in the model of Zimmerman (1998a) and of the motivational strategies in the model of Miele and Scholer (2018). Metacognitive experiences are also not detailed, although the model of Pintrich (2000) refers to metocognitive judgements and feelings, and the model of Miele and Scholer (2018) includes metamotivational feelings.

4 Discussion and conclusions

Our aim in the present study was to provide an up-to-date, comparative and integrative description of the major models of SRL proposed to date. Two research questions were posed. The first referred to delimiting the essential characteristics and components of the theoretical models on SRL. In this regard, we demonstrated that all of the models considered share a framework of ideas related to intellectual and affective-motivational functioning, interconnected in a prototypical recurring temporal sequence. However, each model provides a particular focus within the common framework, in a similar way to a camera scanning an unknown landscape with a zoom that enables visualization of the underlying ecosystem.

The model of Zimmerman (1998b, 2000), which adopts a distant focus, established the structural basis of the representation of the SRL construct: 3 basic process stages (before, during and after performance of a task/learning episode), in which essential processes and dimensions are located. Unsurprisingly, this is the model most frequently cited in the scientific literature. Boekaerts (1991, 2006) and also Winne and colleagues (Winne and Hadwin, 1998; Winne and Perry, 2000) adopted a more closely focused approach and directed attention to the role of experiences and representations generated in response to a task, which would give rise to the development of action-reaction loops, advances and backwards steps throughout the basic phases of self-regulation. Pintrich (2000) adjusted the zoom to an intermediate distance, considering the different areas of self-regulation (cognition, motivation/affect, behaviour and context), while still detailing processes and dimensions. As discordant feature of Pintrich’s model relative to the others, although he recognises the role that the monitoring the student carries out of their own action of learning, this is circumscribed to a phase concurrent to the control phase (selection, application and adaptation of learning strategies), both corresponding to the execution of the learning task.

Regarding delimitation of the SRL components, theoretical elaborations in the field of metacognition and information processing have been fundamental, generating a consistent list of notions of fundamental personal and situational processes and dimensions. However, the location of the different components in specific phases of the SRL cycle, as considered in some of the classic dynamic models, may be misleading. Although the weight of some components (such as monitoring or self-schemes) may vary between phases, these can be manifested throughout the SRL cycle and in the different feedback loops generated during execution of the task (Bakhtiar and Hadwin, 2021). This aspect is clearly reflected in the modern dynamic models.

We have been able to identify various components of a common organizational framework; however, we have observed that the components are unequally weighted. While the components related to metacognitive knowledge are usually detailed in the models, those related to skills and metacognitive experiences are referred to more globally. The literature on SRL includes investigations on specific categories of the components, which complement the list that we have extracted from the models considered. These studies must be considered in order to obtain an overall view of the complex framework of processed and dimensions involved in SRL. Thus, regarding metacognitive knowledge, we have available analytical studies on epistemic beliefs (Schommer-Aikins, 2004; Muis and Singh, 2018), on motivational beliefs (Eccles and Wigfield, 2002) and on contextual conditions (Ben-Eliyahu and Bernacki, 2015; De la Fuente-Arias, 2017). Regarding metacognitive skills, classifications of (meta) cognitive and affective-motivational learning strategies have been proposed (Dresel et al., 2015; Martínez-López et al., 2021). The microprocesses executed by students in response to complex tasks, making use of hypermedia environments, have also been explored (Winne, 2017). Finally, the studies by Efklides (2002, 2006) can be highlighted in regard to the analysis of metacognitive experiences.

Our second research question considered the evolution of theoretical models of SRL. In comparison with classic models, the modern models are characterized by a focus that is relatively close to the action of learning. Although their relationship to the classic models is evident, the recent models generally provide a more recognisable view of the complexity and multidimensionality of the processes involved in SRL. Affective-motivational regulation is also given the necessary prominence in these models, along with the role of contextual conditions and attitudes and routines shaped in the personal history of learning experiences.

In summary, SRL has appeared as a central topic in Educational Psychology in the past few decades, and a series of shared assumptions regarding the nature of the construct have since been consolidated and a legacy has been built consisting of the processes and dimensions involved. Without these achievements it would be difficult to account for the large number of studies conducted in the field of SRL. The models have inspired recent lines of study including detailed analysis of online SRL (during its course) (Rovers et al., 2019), its manifestation in diverse instructional formats (e.g., collaborative learning, virtual environments, etc.) (Winne, 2017; Hadwin et al., 2018) and the role of affective/motivational self-regulation (Wolters, 2003; Pekrun and Stephens, 2009).

Thus, appreciable advances have been made in bridging the gap between the abstractions represented in SRL models and the reality of the phenomenon under study, in itself complex, multidimensional and contextual. However, as already pointed out by Jakešová and Kalenda (2014) regarding the classic models, the precision of the causal mechanisms involved in SRL remains limited; on the other hand, we can assume that at least some parts of the mechanisms represented by the models are bidirectional. Thus, the following are proposed as priority lines of further research in the field of SRL: (1) modelling the dimensions and processes involved in SRL in more precise terms, taking into account possible reciprocal causalities; and (2) reviewing the empirical evidence to support or, where appropriate, question new, more detailed models. Regarding the educational applications of the present and future theoretical analyses of SRL, their potential for inspiring general guiding principles and enhancing the effectiveness of programmes aimed at providing training in learning skills should be highlighted.

Author contributions

CT: Conceptualization, Formal analysis, Methodology, Project administration, Supervision, Writing – original draft. MEM: Investigation, Methodology, Visualization, Writing – review & editing. EV: Conceptualization, Investigation, Methodology, Writing – original draft. ZM-L: Methodology, Visualization, Writing – review & editing.

Funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This publication is part of Project PID2021-126981OB-I00, funded by MCIN/ AEI/10.13039/501100011033/ and by ERDF “A way of making Europe” and by Xunta de Galicia (ED431C 2022/17).

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.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Footnotes

1. ^In this case, we use the term “objective” rather than “goal,” as we consider the former is more in keeping with the aims pursued in a task execution. We use the term “goal,” throughout the text, to refer to more general purposes.

References

Ananiadou, K., and Claro, M. (2009). “OECD education working papers 41” in 21st century skills and competences for new millennium learners in OECD countries (Paris: OECD Publishing). doi: 10.1787/218525261154

Crossref Full Text | Google Scholar

Bakhtiar, A., and Hadwin, A. F. (2021). Motivation from a self-regulated learning perspective: application to school psychology. Can. J. Sch. Psychol. 37, 93–116. doi: 10.1177/08295735211054699

Crossref Full Text | Google Scholar

Ben-Eliyahu, A., and Bernacki, M. L. (2015). Addressing complexities in self-regulated learning: a focus on contextual factors, contingencies, and dynamic relations. Metacogn. Learn. 10, 1–13. doi: 10.1007/s11409-015-9134-6

Crossref Full Text | Google Scholar

Boekaerts, M. (1991). Subjective competence, appraisals and self-assessment. Learn. Instr. 1, 1–17. doi: 10.1016/0959-4752(91)90016-2

Crossref Full Text | Google Scholar

Boekaerts, M. (1996a). Handbook of coping. Theories, research, applications. eds. M. Zeidner and N. S. Endler (Oxford: John Wiley & Sons), 452–484.

Google Scholar

Boekaerts, M. (1996b). Self-regulated learning at the junction of cognition and motivation. Eur. Psychol. 1, 100–112. doi: 10.1027/1016-9040.1.2.100

Crossref Full Text | Google Scholar

Boekaerts, M. (1995). The interface between intelligence and personality as determinants of classroom learning. International handbook of personality and intelligence. eds. D. H. Saklofske and M. Zeidner (Plenum Press), 161–183. doi: 10.1007/978-1-4757-5571-8_9

Crossref Full Text | Google Scholar

Boekaerts, M. (2006). “Self-regulation and effort investment” in Handbook of child psychology: child psychology in practice. (5th ed., vol. 4, p. 350). eds. K. A. Renninger, I. E. Sigel, W. Damon, and R. M. Lerner (Oxford: John Wiley & Sons). 4:350. doi: 10.1002/9780470147658

Crossref Full Text | Google Scholar

Boekaerts, M. (2007). “Understanding students’ affective processes in the classroom” in Emotion in education. eds. B. Schulz and R. E. Pekrun (San Diego, CA: Academic Press), 37–56.

Google Scholar

Boekaerts, M., and Niemivirta, M. (2000). “Self-regulated learning: finding a balance between learning goals and ego-protective goals” in Handbook of self-regulation. eds. M. Boekaerts, P. R. Pintrich, and M. Zeidner (San Diego, CA: Academic Press), 417–450.

Google Scholar

Boekaerts, M., Pintrich, P.R., and Zeidner, M. (Eds.) (2000). Handbook of self-regulation. San Diego, CA: Academic Press.

Google Scholar

De la Fuente-Arias, J. (2017). Theory of self- vs. externally-regulated learning: fundamentals, evidence, and applicability. Front. Psychol. 8:1675. doi: 10.3389/fpsyg.2017.01675

PubMed Abstract | Crossref Full Text | Google Scholar

Dresel, M., Schmitz, B., Schober, B., Spiel, C., Ziegler, A., Engelschalk, T., et al. (2015). Competencies for successful self-regulated learning in higher education: structural model and indications drawn from expert interviews. Stud. High. Educ. 40, 454–470. doi: 10.1080/03075079.2015.1004236

Crossref Full Text | Google Scholar

Eccles, J. S., and Wigfield, A. (2002). Motivational beliefs, values, and goals. Annu. Rev. Psychol. 53, 109–132. doi: 10.1146/annurev.psych.53.100901.135153

Crossref Full Text | Google Scholar

Efklides, A. (2002). “The systemic nature of metacognitive experiences. Feelings, judgments, and their interrelations” in Metacognition: process, function and use. eds. P. Chambres, M. Izaute, and P. J. Marescaux (Boston MA: Springer), 19–34.

Google Scholar

Efklides, A. (2006). Metacognition and affect: what can metacognitive experiences tell us about the learning process? Educ. Res. Rev. 1, 3–14. doi: 10.1016/j.edurev.2005.11.001

Crossref Full Text | Google Scholar

Efklides, A. (2008). Metacognition: defining its facets and levels of functioning in relation to self-regulation and co-regulation. Eur. Psychol. 13, 277–287. doi: 10.1027/1016-9040.13.4.277

Crossref Full Text | Google Scholar

Efklides, A. (2011). “Interactions of metacognition with motivation and affect in self-regulated learning: The MASRL model” in Educational Psychologist. ed. A. Efklides (Routledge: Taylor & Francis Group), 46:2011. doi: 10.1080/00461520.2011.538645

Crossref Full Text | Google Scholar

Efklides, A. (2018). Affect, epistemic emotions, metacognition, and self-regulated learning. Teach. Coll. Rec. 119, 1–22. doi: 10.1177/016146811711901302

Crossref Full Text | Google Scholar

Flavell, J. H. (1979). Metacognition and cognitive monitoring: a new area of cognitive-developmental inquiry. Am. Psychol. 34, 906–911. doi: 10.1037/0003-066X.34.10.906

Crossref Full Text | Google Scholar

Garcia, T., and Pintrich, P. R. (1994). “Regulating motivation and cognition in the classroom: the role of self-schemas and self-regulatory strategies” in Self-regulation of learning and performance: Issues and educational applications. eds. D. H. Schunk and B. J. Zimmerman (New York: Routledge), 127–153.

Google Scholar

Hadwin, A. F., Järvelä, S., and Miller, M. (2011). “Self-regulated, co-regulated, and socially shared regulation of learning” in Handbook of self-regulation of learning and performance. eds. B. J. Zimmerman and D. H. Schunk. 2nd ed (New York: Routledge), 79–98.

Google Scholar

Hadwin, A. F., Järvelä, S., and Miller, M. (2018). “Self-regulation, co-regulation and shared regulation in collaborative learning environments” in Handbook of self-regulation of learning and performance. eds. B. J. Zimmerman and D. H. Schunk. 2nd ed (New York: Routledge), 65–84.

Google Scholar

Jakešová, J., and Kalenda, J. (2014). Self-regulated learning: critical-realistic conceptualization. Procedia. Soc. Behav. Sci. 171, 178–189. doi: 10.1016/j.sbspro.2015.01.105

Crossref Full Text | Google Scholar

Järvelä, S., and Hadwin, A. F. (2013). New frontiers: regulating learning in CSCL. Educ. Psychol. Routledge/Taylor & Francis Group 48:29. doi: 10.1080/00461520.2012.748006

Crossref Full Text | Google Scholar

Limón, M., Mason, L., Sinatra, G. M., Winne, P., Montero, I., de Dios, M. J., et al. (2004). En homenaje a las contribuciones de Paul R. Pintrich a la investigación sobre Psicología y Educación. Electron. J. Res. Educ. Psychol. 2, 157–210. doi: 10.25115/ejrep.3.127

Crossref Full Text | Google Scholar

Martínez-López, Z., Villar, E., Castro, M., and Tinajero, C. (2021). Autorregulación de las emociones académicas: investigaciones recientes y prospectiva. An. Psicol. 37, 529–540. doi: 10.6018/analesps.415651

Crossref Full Text | Google Scholar

Miele, D. B., and Scholer, A. A. (2018). The role of metamotivational monitoring in motivation regulation. Educ. Psychol. Routledge/Taylor & Francis Group 53:2. doi: 10.1080/00461520.2017.1371601

Crossref Full Text | Google Scholar

Muis, K. R., and Singh, C. A. (2018). “The three facets of epistemic thinking in self-regulated learning” in Handbook of self-regulation of learning and performance. eds. B. J. Zimmerman and D. H. Schunk. 2nd ed (New York: Routledge), 434–456.

Google Scholar

Panadero, E. (2017). A review of self-regulated learning: six models and four directions for research. Front. Psychol. 8:422. doi: 10.3389/fpsyg.2017.00422

PubMed Abstract | Crossref Full Text | Google Scholar

Pekrun, R., and Stephens, E. J. (2009). Goals, emotions, and emotion regulation: perspectives of the control-value theory. Commentary on Tyson, Linnenbrink-Garcia, and hill. Hum. Dev. 52, 357–365. doi: 10.1159/000242349

Crossref Full Text | Google Scholar

Pintrich, P. R. (2000). The role of goal orientation in self-regulated learning. Contemp. Educ. Psychol. eds. M. Boekaerts, P. R. Pintrich, and M. Zeidner (1st ed., p. 454), Elsevier Academic Press doi: 10.1016/B978-012109890-2/50043-3

PubMed Abstract | Crossref Full Text | Google Scholar

Pintrich, P. R. (2004). A conceptual framework for assessing motivation and self-regulated learning in college students. Educ. Pscyhol. Rev. 16, 385–407. doi: 10.1007/s10648-004-0006-x

Crossref Full Text | Google Scholar

Pintrich, P., Smith, D., Garcia, T., and McKeachie, W. (1991). A manual for the use of the motivated strategies for learning questionnaire (MSLQ). University of Michigan. Retrieved Oct 2, 2023, Available at: https://eric.ed.gov/?id=ED338122

Google Scholar

Pintrich, P. R., Wolters, C. A., and Baxter, G. P. (2000). “Assessing metacognition and self-regulated learning” in Issues in the measurement of metacognition. eds. G. Schraw and J. C. Impara (Lincoln, NE: Buros Institute of Mental Measurements), 43–97.

Google Scholar

Puustinen, M., and Pulkkinen, L. (2001). Models of self-regulated learning: a review. Scandinavian J. Edu. Res. 45, 269–286. doi: 10.1080/00313830120074206

Crossref Full Text | Google Scholar

Rovers, S. F. E., Clarebout, G., Savelberg, H. H. C. M., Bruin, A. B. H., and van Merriënboer, J. J. G. (2019). Granularity matters: comparing different ways of measuring self-regulated learning. Metacogn. Learn. 14, 1–19. doi: 10.1007/s11409-019-09188-6

Crossref Full Text | Google Scholar

Salonen, P., Vauras, M., and Efklides, A. (2005). Social interaction—what can it tell us about metacognition and coregulation in learning? Eur. Psychol. 10, 199–208. doi: 10.1027/1016-9040.10.3.199

Crossref Full Text | Google Scholar

Schommer-Aikins, M. (2004). Explaining the epistemological belief system: introducing the embedded systemic model and coordinated research approach. Educ. Psychol. 39, 19–29. doi: 10.1207/s15326985ep3901_3

Crossref Full Text | Google Scholar

Schunk, D.H., and Green, J.A. (Eds.) (2018). Handbook of self-regulation of learning and performance (2nd ed). New York: Routledge.

Google Scholar

Schwinger, M., Steinmayr, R., and Spinath, B. (2009). How do motivational regulation strategies affect achievement: mediated by effort management and moderated by intelligence. Learn. Individ. Differ. 19, 621–627. doi: 10.1016/j.lindif.2009.08.006

Crossref Full Text | Google Scholar

Schwinger, M., and Stiensmeier-Pelster, J. (2012). Effects of motivational regulation on effort and achievement: a mediation model. Int. J. Educ. Res. 56, 35–47. doi: 10.1016/j.ijer.20l2.07.005

Crossref Full Text | Google Scholar

Sitzmann, T., and Ely, K. (2011). A meta-analysis of self-regulated learning in work-related training and educational attainment: what we know and where we need to go. Psychol. Bull. 137, 421–442. doi: 10.1037/a0022777

PubMed Abstract | Crossref Full Text | Google Scholar

Usher, E. L., and Schunk, D. H. (2018). “Social cognitive theoretical perspective of self-regulation” in Handbook of self-regulation of learning and performance (New York: Routledge), 19–35.

Google Scholar

Winne, P. H. (2001). “Self-regulated learning viewed from models of information processing” in Self-regulated learning and academic achievement: Theoretical perspectives. eds. B. J. Zimmerman and D. H. Schunk (New York: Lawrence Erlbaum Associates), 153–189.

Google Scholar

Winne, P. H. (2011). “A cognitive and metacognitive analysis of self-regulated learning” in Handbook of self-regulation of learning and performance. eds. B. J. Zimmerman and D. H. Schunk. 1st ed (New York: Routledge), 15–32.

Google Scholar

Winne, P.H. (2017). Learning analytics for self-regulated learning. In Lang, C., Siemens, G., Wise, A., and Gašević, D. (Eds.) (2017). Handbook of learning analytics (pp. 241–249). Beaumont, AB: Society for Learning Analytics Research.

Google Scholar

Winne, P. H., and Hadwin, A. E. (1998). “Studying as self-regulated learning” in Metacognition in educational theory and practice. (1st, p. 239). eds. D. J. Hacker, J. Dunlosky, and A. C. Graesser (New York: Routledge).

Google Scholar

Winne, P. H., and Hadwin, A. F. (2008). “The weave of motivation and self-regulated learning” in Motivation and self-regulated learning: Theory, research, and applications. eds. D. H. Schunk and B. J. Zimmerman (New York: Lawrence Erlbaum Associates), 297–314.

Google Scholar

Winne, P. H., and Perry, N. E. (2000). “Measuring self-regulated learning” in Handbook of self-regulation. eds. M. Boekaerts, P. R. Pintrich, and M. Zeidner (San Diego: Academic Press), 531–566.

Google Scholar

Wirth, J., and Leutner, D. (2008). Self-regulated learning as a competence: implications of theoretical models for assessment methods. J. Psychol. 216, 102–110. doi: 10.1027/0044-3409.216.2.102

Crossref Full Text | Google Scholar

Wirth, J., Stebner, F., Trypke, M., Schuster, C., and Leutner, D. (2020). An interactive layers model of self-regulated learning and cognitive load. Educ. Psychol. Rev. 32, 1127–1149. doi: 10.1007/s10648-020-09568-4

Crossref Full Text | Google Scholar

Wolters, C. A. (2003). Regulation of motivation: evaluating an underemphasized aspect of self-regulated learning. Educ. Psychol. 38, 189–205. doi: 10.1207/S15326985EP3804_1

Crossref Full Text | Google Scholar

Zeidner, M., Boekaerts, M., and Pintrich, P. R. (2000). “Self-regulation directions and challenges for future research” in Handbook of self-regulation. eds. M. Boekaerts, P. R. Pintrich, and M. Zeidner (San Diego: Academic Press)

Google Scholar

Zeidner, M., and Stoeger, H. (2019). Self-regulated learning (SRL): a guide for the perplexed. High Abil. Stud. 30, 9–51. doi: 10.1080/13598139.2019.1589369

Crossref Full Text | Google Scholar

Zimmerman, B. J. (1989). “Theories of self-regulated learning and academic achievement: an overview and analysis” in Self-regulated learning and academic achievement: Theoretical perspectives. eds. B. J. Zimmerman and D. H. Schunk (New York: Routledge), 1–37.

Google Scholar

Zimmerman, B. J. (1990). Self-regulating academic learning and achievement: the emergence of a social cognitive perspective. Educ. Psychol. Rev. 2, 173–201. doi: 10.1007/BF01322178

Crossref Full Text | Google Scholar

Zimmerman, B. J. (1994). “Dimensions of academic self-regulation: a conceptual framework for education” in Self-regulation of learning and performance: Issues and educational applications. eds. D. H. Schunk and B. J. Zimmerman (New York: Lawrence Erlbaum Associates), 2–21.

Google Scholar

Zimmerman, B. J. (1998a). Academic studying and the development of personal skill: a self-regulatory perspective. Educ. Psychol. 33, 73–86. doi: 10.1207/s15326985ep3302&3_3

Crossref Full Text | Google Scholar

Zimmerman, B. J. (1998b). “Developing self-fulfilling cycles of academic regulation: an analysis of exemplary instructional models” in Self-regulated learning: From teaching to self-reflective practice. eds. D. H. Schunk and B. J. Zimmerman (New York: Guilford), 1–19.

Google Scholar

Zimmerman, B. J. (2000). “Attaining self-regulation. A social cognitive perspective” in Handbook of self-regulation. eds. M. Boekaerts, P. R. Pintrich, and M. Zeidner (San Diego: Academic Press), 13–39.

Google Scholar

Zimmerman, B. J. (2008). Investigating self-regulation and motivation: historical background, methodological developments, and future prospects. Am. Educ. Res. J. 45, 166–183. doi: 10.3102/0002831207312909

Crossref Full Text | Google Scholar

Zimmerman, B. J., and Moylan, A. R. (2009). “Self-regulation: where metacognition and motivation intersect” in The educational psychology series. Handbook of metacognition in education. eds. D. J. Hacker, J. Dunlosky, and A. C. Graesser (New York: Routledge) 300, 299–315. doi: 10.4324/9780203876428

Crossref Full Text | Google Scholar

Keywords: components, phases, models, review, self-regulated learning

Citation: Tinajero C, Mayo ME, Villar E and Martínez-López Z (2024) Classic and modern models of self-regulated learning: integrative and componential analysis. Front. Psychol. 15:1307574. doi: 10.3389/fpsyg.2024.1307574

Received: 04 October 2023; Accepted: 15 February 2024;
Published: 07 March 2024.

Edited by:

Benito León Del Barco, University of Extremadura, Spain

Reviewed by:

Xindong Ye, Wenzhou University, China
Carolina Bringas Molleda, University of Extremadura, Spain

Copyright © 2024 Tinajero, Mayo, Villar and Martínez-López. 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: Mª Emma Mayo, ZW1tYS5tYXlvQHVzYy5lcw==

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.