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Self-regulation, executive function, working memory, and academic achievement of female high school students

ProQuest Dissertations and Theses, 2011
Dissertation
Author: Roberta Kathryn Halloran
Abstract:
Self-regulation, executive function and working memory are areas of cognitive processing that have been studied extensively. Although many studies have examined the constructs, there is limited empirical support suggesting a formal link between the three cognitive processes and their prediction of academic achievement. Thus, the present study hypothesized that working memory performance would predict students' self-report of executive function and self-regulated learning strategies which would subsequently predict academic achievement. The sample consisted of 155 freshman and sophomore female high school students at a private school in New York City. Students electronically completed questionnaires about their self-regulated learning strategies (i.e., The Motivated Strategies for Learning Questionnaire) and their executive functioning (i.e., The Behavior Rating Inventory of Executive Function--Self Report). Additionally students' working memory abilities were assessed with the Automated Operation Span task (AOSPAN); a computer-adapted task requiring dual processing of simple math operations and the recall of letters. Results from multiple regression analyses revealed that students' working memory performance did not predict students' report of self-regulation, executive functioning, or academic achievement as measured by final grades and PSAT scores. However, students' reports of self-regulated learning strategies, or cognitive engagement, were found to significantly predict academic achievement in English. Cognitive engagement was not found to predict math achievement nor did it predict critical reading or math PSAT percentile score. It appears that self-regulated learning strategies are most predictive of achievement when the ultimate goal is mastering the content of verbal material in English classes. Therefore, by creating an environment that encourages the use of regulatory and organizational behaviors, teachers can begin to facilitate a change in cognitive strategies, which could subsequently lead to increased retention of mathematical information in the classroom and on standardized testing. Since the results indicate that working memory did not predict academic achievement, the construct should not be considered as a sole predictor of students' ability to succeed academically. These results are promising for students who demonstrate weaker working memory skills. Since working memory does not directly impact academic achievement, students can compensate for working memory difficulties by employing other cognitive engagement strategies that successfully impact achievement.

TABLE OF CONTENTS Page PERMISSION TO USE COPYRIGHTED MATERIAL i NOTICE OF COPYRIGHT ii ACKNOWLEDGMENTS iii DEDICATION iv LIST OF TABLES ix LIST OF FIGURES x CHAPTER I. THE PROBLEM 1 Introduction 1 Self-Regulation, Executive Function, and Working Memory 2 Self-Regulation 2 Executive Function 3 Working Memory 5 Statement of the Problem 9 Hypotheses 10 Definition of Terms 12 Significance of the Study 14 Limitations 15 CHAPTER II. REVIEW OF RELATED LITERATURE 17 Self-Regulation 17

VI TABLE OF CONTENTS (continued) Development of Self-Regulation 18 Theories of Self-Regulation 19 Relation to Achievement, Executive Function and 27 Working Memory Executive Function 29 History of Executive Function 30 Individual Differences 33 Relation to Achievement 35 Working Memory 36 Theories of Working Memory 36 Working Memory as a Component of Executive Function 39 The Link of Working Memory with Self-Regulation 39 Working Memory Individual Differences 40 Relation of Working Memory to Achievement 41 Summary of Related Literature 42 CHAPTER III. PARTICIPANTS, MATERIALS, AND PROCEDURES 45 Participants 45 Ethical Considerations 46 Materials 47 Self-Regulation 47 Executive Function 48 Working Memory 51

Vl l TABLE OF CONTENTS (continued) Self-Regulation 58 Executive Function 59 Working Memory 59 Relation Among Variables 59 Chapter IV. RESULTS 61 Data Analysis 61 Preliminary Analyses 62 Assumptions 65 Descriptive Statistics 66 Test of Hypotheses 69 Correlations 69 Achievement Regression on Self-Regulated Strategy Use and 70 Executive Function Achievement Regression on Working Memory Performance 71 Path Analysis 76 Chapter V. DISCUSSION 89 Findings 80 Prediction of Performance on Standardized Assessment 81 Implications for the Classroom 82 Prediction of Cognitive Engagement by Working Memory Performance 84 Prediction of Working Memory by Cognitive Engagement 85 Prediction of Executive Function by Working Memory Performance 85

TABLE OF CONTENTS (continued) Implications of No Significance between Working Memory and 87 Other Variables Developmental Considerations 87 Limitations 98 Recommendations for Future Research 99 Conclusion 102 REFERENCES 106 APPENDIX A- PARENT CONSENT 119 APPENDIX B- STUDENT ASSENT 121 APPENDIX C- BEHAVIOR RATING OF EXECUTIVE FUNCTION 130 APPENDIX D- MOTIVATED STRATEGIES FOR LEARNING 132 QUESTIONNAIRE ABSTRACT 134 VITA

IX LIST OF TABLES Table Page 1. Component Loadings for Executive Function Subscales on BRIEF 63 2. Descriptive Statistics for Achievement, Executive Function, 68 Self-Regulated Strategy Use, and Working Memory Performance Variables (AT=109) 3. Intercorrelation Matrix Comparing 21 Variables With English 73 Self-Regulation and Achievement Variables 4. Intercorrelation Matrix Comparing 21 Variables With English 75 Self-Regulation and Achievement Variables 5. Simultaneous Regression Model for English Achievement, Critical 77 Reading Percentile, Math Achievement, and Math Percentile on Self- Regulated Strategy Use, Executive Function, and Working Memory Performance 6. Regression Model for Working Memory Performance on Global 89 Executive Composite (GEC) and Self-Regulated Strategy Use (SRSU) 7. Regression Model for Self-Regulated Strategy Use (SRSU) and EF on 90 OSPAN and Total Correct

X LIST OF FIGURES Figure Page 1. Proposed Path Analysis Diagram between WMP, SRSU, EF, and 11 Academic Achievement 2. Scree Plot Examining Eigenvalues for 8 Subscales of BRIEF-SR 64 3. Path Analysis for Direct Effects of Working Memory Performance 79 (i.e., OSPAN and Total Correct), Executive Function (i.e., GEC), and SRSU (i.e., SRLEnglish, RehearsalEnglish, OrganizationalEnglish) on English Achievement 4. Path Analysis for Direct Effects of Working Memory Performance 80 (i.e., OSPAN and Total Correct), Executive Function (i.e., GEC), and SRSU (i.e., SRLEnglish, RehearsalEnglish, OrganizationalEnglish) on Critical Reading PSAT Percentile 5. Path Analysis for Direct Effects of Working Memory Performance 81 (i.e., OSPAN and Total Correct), Executive Function (i.e., GEC), and SRSU (i.e., SRLMath, RehearsalMath, OrganizationalMath) on Math Achievement 6. Path Analysis for Direct Effects of Working Memory Performance 82 (i.e., OSPAN and Total Correct), Executive Function (i.e., GEC), and SRSU (i.e., SRLMath, RehearsalMath, OrganizationalMath) on Math PSAT Percentile 7. Path Analysis for Direct Effect of WMP on English Achievement 83 with EF and SRSU contributing Indirect Effects 8. Path Analysis for Direct Effect of WMP on Critical Reading PSAT 84 Percentile with EF and SRSU contributing Indirect Effects 9. Path Analysis for Direct Effect of WMP on Math Achievement with 85 EF and SRSU contributing Indirect Effects 10. Path Analysis for Direct Effect of WMP on MATH PSAT Percentile 86 with EF and SRSU contributing Indirect Effects

1 CHAPTER I THE PROBLEM Introduction Self-regulation, executive function, and working memory are areas of cognitive processing that have been studied extensively. Many researchers have demonstrated that these constructs lead to positive outcomes including academic achievement (Bull & Scerif, 2001; Daneman & Carpenter, 1980; Schunk, 2005; Zimmerman & Martinez-Pons, 1986). Executive function is often characterized as higher order cognitive process and represents an umbrella construct including a set of interrelated cognitive abilities responsible for purposeful, goal directed, and problem- solving behavior (Gioia, Isquith, & Guy, 2001). Both self-regulation and working memory are thought to comprise executive functions (Weyandt, 2005; Brownell, 2009; Pennington, Bennetto, McAleer, & Roberts, 1996). Although many studies have examined the relation between these variables individually, there is limited empirical support suggesting a formal link between the three cognitive processes of executive function, self-regulation, and working memory and their prediction of academic achievement. Additionally, few studies have integrated the three constructs of self-regulation, executive function, and working memory in a study sampling adolescents, despite evidence to suggest that executive function, including self- regulation and working memory continue to develop into late adolescence and early

2 adulthood (Demetriou, Christou, Spanoudis, & Platsidou, 2002; Dumontheil, Apperly, & Blakemore, 2010). Self-Regulation, Executive Function, and Working Memory Self-Regulation Self-regulation refers to self-generated thoughts, feelings, and actions that are planned and cyclically adapted to the attainment of personal goals (Schunk & Zimmerman, 1994). Some researchers state that self-regulation may be the most important human quality because it enables self-awareness and provides an adaptive edge for the human species. The development of self-regulatory processes can be acquired from social and self-sources of influence. Individuals develop the complex, cognitive process of self-regulation, by progressing through a hierarchy of regulatory skills (e.g., observation, emulation, and self-control) before they ultimately arrive at a self-regulated level of skill. Self-regulation enables learners to systematically adapt their performance to changing personal and contextual conditions (Zimmerman, 2000). Self-regulation is comprised of specific subprocesses. Learners often engage in four phases of self-regulation in their environment: planning, monitoring, control, and reaction / reflection (Pintrich, 2000). When learning, active self-regulation entails initiation and direction of an individual's own efforts to acquire specific knowledge and skills (Zimmerman, 1989). Additionally, self-regulated learners employ specific learning strategies. These strategies (e.g., goal setting, self-evaluating, and self- monitoring) are actions and processes directed at acquiring information or skill in

3 which learners have a sense of agency and purpose (Zimmerman & Martinez-Pons, 1986). A social-cognitive learning perspective is often utilized in providing a framework for self-regulation. Bandura's (1977, 1986) social-cognitive learning theory grounds self-regulated learning in the reciprocal causation of three influential components: personal, environmental, and behavioral determinants. Social-cognitive theorists further defined self-regulated learning as comprised of three sub processes: self-observation, self-judgment, and self-reaction (Schunk, 1989). An individual's self-regulation can be often described as cyclical because the feedback from prior performance is used to make adjustments during subsequent efforts. Such adjustments are necessary because the three environmental processes (i.e., personal, environmental, and behavioral determinants) are ever changing while an individual learns. As such, an individual must monitor and observe the factors through the use of self-oriented feedback loops. Executive Function Self-regulation is a component of executive function. Executive function refers to the volitional and controlled aspect of attention that enables individuals to resolve conflicts and situations appropriately by utilizing cognitive control (Posner & DiGirolamo, 1998). Executive function is often characterized as higher order cognitive process and represents an umbrella construct including a set of interrelated cognitive abilities responsible for purposeful, goal directed, and problem-solving behavior (Gioia et al., 2001). Although researchers have conceptualized executive function as a broad construct comprised of individual cognitive processes, no

4 empirical evidence demonstrates this overarching framework. Thus, for the purpose of this study, executive function is examined as a separate cognitive process and is distinguished from self-regulation and working memory. Executive functioning is controlled by the frontal system of the brain, particularly the frontal and prefrontal cortices which are often associated with regulatory control of human action. Because executive functions are complex cognitive skills, it takes a longer time for them to develop and mature in comparison to other basic cognitive functions (Welsh & Pennington, 1988). Research suggests that executive functions continue to develop into adolescence and early adulthood due to the continued myelination of axons, which is similar to the sophistication and maturation of the prefrontal cortex (Diamond, 2002). Barkley (2001) stated that executive functions are the self-directed actions individuals engage in during self-regulation. Thus, self-regulation is composed of multiple aspects of executive functioning (i.e., the internalization of actions, self- speech, and emotion and motivation) that lead to purposive, intentional behavior and function to alter the future. For example, Barkley purported that executive function is comprised of inhibition, or actions that individuals undertake to modify behavior and change future outcomes. Inhibition, or delaying a response or behavior, is one necessary prerequisite for self-regulation to take place. Researchers have hypothesized that the neural mechanisms underlying self- regulatory processes are directly connected to the executive attention network. Self- regulating one's behavior involves a conscious detection of errors, inhibition of unwanted behaviors, and resolution of conflicts. These mechanisms of control are

5 also essential to the executive function network, highlighting an important link between self-regulation and executive function. Additionally, a similar region in the brain (i.e., the anterior cingulate cortex, ACC) is a central component to the executive attention network. The ACC is part of the limbic system in the brain and plays a role in activating self-regulation of behavior, maintaining executive control, and processing emotions. Specifically, research suggests that the ACC is involved in the detection and monitoring of mental conflict (Rueda, Posner, & Rothbart, 2004). These data suggest that aspects of executive function, such as effortful control, may lead to the development of self-regulation. Working Memory Working memory is also described as a key aspect of executive function (Miyake et al., 2000; Pennington et al., 1996). Working memory is a cognitive processing system that underlies the human thought process and allows for the temporary storage and manipulation of information. It is a limited capacity system that temporarily maintains and stores information and acts as an interface between perceptions, long-term memory, and action. An individual's ability to manipulate information in working memory distinguishes contemporary from traditional models of short-term memory, which do not include the manipulation aspect of cognitive functioning (Baddeley & Hitch, 1974). An individual must utilize executive control to maintain, manipulate, and act on the information stored in working memory (Welsh, 2001). Baddeley's (1990, 1993) model of working memory has been extensively researched, both empirically and theoretically. His four-part model of the construct is

6 renowned as a good approximation of the architecture underlying working memory (Caplan & Waters, 1999; Engle, 2002; Morra, 2000). The model suggests that a central executive, the first part of the model, provides attentional control and is responsible for three key processes: monitoring and coordinating the operations of two slave systems (i.e., the phonological loop and visuospatial sketchpad), strategy selection, and coordinating the information in working memory with information in long-term memory. The slave systems comprise the next two parts in Baddeley's model. The first slave system is a phonological loop, which refreshes one's memory through rehearsal of information. Additionally, an individual with a faster rehearsal of information in the phonological loop is able to hold more information than an individual with a slower processing phonological loop. The visuospatial sketchpad is the second slave system in Baddeley's (1990, 1993) model and is responsible for the retention and manipulation of visual or spatial information. Finally, Baddeley and Hitch (2000) added a fourth component to their working memory model known as the episodic buffer. The buffer is believed to be a limited capacity storage component controlled by the central executive. Therefore, the buffer binds and integrates information from the two slave systems in order to form a coherent understanding. Efficient working memory results in a lower cognitive load for an individual. Cognitive load refers to the amount of attention and cognitive processing a novel or strenuous task imposes on an individual. When cognitive load demands are lowered, learners have an increased working memory capacity to relate and process information, which results in better long-term retention (Schwartz, Andersen, Hong,

7 Howard, & McGee, 2004). Studies have supported the idea that increasing an individual's cognitive load is related to a systematic decrease in the amount of information that can be held and accessed in working-memory (Barrouillet, Bernardin, & Camos, 2004). Working memory has often been explored in terms of individual differences and developmental differences when studying higher-level cognitive abilities (Bayliss, Jarrold, Gunn, & Baddeley, 2003). Recently, studies have demonstrated that there is a developmental aspect to working memory suggesting that nonverbal memory span continues to improve in adolescents up to 13-15 years of age (Luciana, Conklin, Hooper, & Yarger, 2005). Another longitudinal research study by Demetriou et al. (2002) confirmed that working memory continues to develop into adolescence. Further, the researchers concluded that external agents (e.g., environmental opportunities, self-regulatory processes) may be drivers of change in cognitive processes; that a change in self-regulation impacts one's working memory ability. Working memory also has been linked to self-regulatory efficiency. Based on the research findings that individuals with better inhibitory capacity have higher working memory, researchers explored whether working memory was positively related to self-regulatory efficiency (Calero, Garcia-Martin, Jimenez, Kazen, & Araque, 2007). Higher working memory skills were found to be positively related to one's self-regulation. The researchers also found, however, that motivation was an important factor in the ability to regulate one's actions. Researchers have found that both self-regulated strategies (Zimmerman & Martinez-Pons, 1986) and working memory abilities have a substantial effect on

8 academic achievement. Self-regulated learning is viewed as a means to explain achievement differences among students and a facilitator of academic success (Schunk, 2005). Researchers have concluded that students who display more adaptive self-regulatory strategies display better learning and higher motivation for learning (Pintrich, 2000). Pintrich and De Groot (1990), for example, found that self- regulation and self-regulation strategy use were positively correlated and predicted achievement in science and English. Thus, researchers emphasize that education should strengthen self-regulation awareness in students (Montalvo & Torres, 2004). Similarly, researchers have demonstrated that working memory is correlated to and predicts achievement (Bayliss et. al., 2003; Daneman & Carpenter, 1980; Gathercole, Pickering, Knight, & Stegman, 2004; Just & Carpenter, 1992). These researchers have demonstrated that working memory ability predicts reading and math ability, and language comprehension. Research has further demonstrated that low achieving students have a diminished working memory capacity (Aguiree-Perez, Otero-Ojeda, Pliego-Rivero, Ferreira-Martinez, 2007). Children with lower working memory performance were found to have more academic and attentional/behavioral difficulties at school than children with good working memory performance (Aronen, Steenari, Salmi, & Carlson, 2005). Research suggests there should be a close relation between self-regulation, executive function, and working memory. Data confirm that the underlying neural correlates activated when one engages in self-regulation, working memory, and executive function are all located in the prefrontal cortex (Kane & Engle, 2002; Marsh et al., 2006). Few studies, however, have formally examined the link between

9 these three cognitive processes. Further, available research focuses on child populations or undergraduate populations (Calero et al., 2007; De Bruin, Rikers, & Schmidt, 2005; Pintrich et al., 1991). Given that working memory and executive function continue to develop into adolescence, it is important to explore the nature of these skills in early adolescence because research may inform possible interventions aimed at increasing working memory, executive function, and/or self-regulation. Research findings from the study may serve as a basis to increase self-regulation, executive function, and working memory skills in the high school classroom. Statement of the Problem Though theory suggests a connection, there are limited data that substantiate a link between self-regulated strategy use, executive function, and working memory. Though literature supports working memory as a central component to executive function, there is an absence of data that specifically demonstrates this relation. Additionally, some researchers demonstrate a relation between self-regulation skills and working memory, but past research has not investigated these constants with an adolescent population. Finally, there are no published studies that have examined the impact of self-regulated learning strategies and executive function on working memory performance, or the extent to which working memory, self-regulation, or executive function skills predict academic achievement. Thus, the current study addressed gaps in past research.

10 Hypotheses The relation between students' self-regulated strategy use (SRSU), executive function (EF), working memory performance (WMP) and academic achievement were examined. Specifically, the study explored the following hypotheses: 1. Students' perceived SRSU will be positively correlated with WMP, perceived EF will be positively correlated with WMP, and perceived SRSU and EF will be positively correlated with each other. 2. Perceived SRSU and EF will have a direct, positive effect on academic achievement. 3. Students' WMP will have a direct effect on academic achievement. 4. Student's WMP will directly affect SRSU, EF, and subsequently achievement, while also directly affecting achievement (See Figure 1.).

Figure 1 Proposed Path Analysis Diagram Between WMP, SRSU, EF, and Academic Achievement Z2 Perceived Executive Function Zl Working Memory Performance Z3 Perceived Self-regulated Strategy use 11 Academic Achievement

12 Definition of Terms Working Memory Performance The term working memory refers to a mental workplace, including many interacting temporary memory systems, in which information can be stored and processed for brief periods of time in the course of demanding cognitive activities (Baddeley & Hitch, 1974). Working memory is a limited-capacity processing system and individuals will vary in terms of how much information they can effectively control and perform cognitive operations on (Baddeley, 1986). Thus, WMP refers to students' scores on cognitive measure of working memory, specifically their performance on the Automated Operation Span Task (AOSPAN) (Unsworth, Heitz, Schrock, & Engle, 2005). Self-Regulated Strategy Use Self-regulated strategy use (SRSU) refers to students' use of different cognitive and metacognitive techniques to improve their learning. Three scales within the Motivated Strategies for Learning Questionnaire (MSLQ) (Pintrich, et al., 1991) were utilized to gather data about students' cognitive and metacognitive strategies. Specifically, students rated how often they engage in rehearsal, organization, and metacognitive self-regulation. When conceptualizing these components individually, basic rehearsal strategies are often used for simple tasks and activation of information in working memory rather than acquisition of new information in long-term memory. Strategies are thought to influence attention and encoding, but they do not appear to help students construct internal connections or integrate the information with prior knowledge (e.g.,

13 reciting or naming items from a list to be learned). Organizing, however, is a more active and effortful cognitive action, and results in an individual being more involved in a task. Examples of organizing strategies are clustering, outlining, and selecting the main idea while reading passages (Pintrich et al., 1991). Metacognition refers to the awareness, knowledge, and control of cognition (Pintrich et al., 1991). Planning, monitoring, and regulating are three processes that comprise self-regulatory activities that are explored within the metacognitive self- regulation scale. Planning activities such as goal setting and task analysis help to activate relevant aspects of prior knowledge so that a student can better organize and comprehend the material. Monitoring activities assist the student in understanding the material and integrating it with prior knowledge. Examples of monitoring activities can include tracking one's attention and self-testing and questioning. Lastly, regulating refers to the fine-tuning and continuous adjustment of cognitive activities. Regulating activities are believed to improve performance by assisting learners in checking and correcting their behavior as they proceed on a task (Pintrich etal., 1991). Executive Function Executive function refers to a collection of interrelated functions that are responsible for purposeful, goal-directed, problem-solving behavior (Guy et al., 2004). This study defined executive function as an individual's ability to inhibit their impulses and behavior, shift both behaviorally and cognitively to environmental demands, control emotions appropriately, monitor behavior, hold information in their working memory, plan and organize consequences and behavior, organize materials

14 and school work, and complete a task. Data on students' executive functions were collected from a self-report measure of executive function, the Behavior Rating Inventory of Executive Function-Self-Report Version (BRIEF-SR). Therefore, inferences made regarding these functions referred to students' perceptions of their executive functions. Significance of the Study Data collected on the independent and dependent variables may prove useful for the fields of school and educational psychology in several ways. A positive relation between self-reports and performance on working memory tasks could lead to interventions aimed at increasing working memory efficiency. Research on the developmental nature of working memory suggests that the cognitive system continues to form into adolescence (Diamond, 2002). If SRSU and EF are positively correlated with more efficient WMP, the data could have implications in the development of working memory interventions by increasing self-regulation and executive functioning. The existing literature on working memory was expanded based on the findings of the study. In particular, the data provided insight into whether the proposed factors (self-regulation and executive functioning) contributed to the efficiency of working memory. Additionally, the limited research on adolescents' use of self-regulation, executive function, and working memory (Brown, 2007; Calero, et al., 2007; Luciana, et al., 2005; Pintrich, et al., 1991;) were broadened.

15 Limitations of the Research The present study was the first to investigate the relation between student's WMP, SRSU, EF, and academic achievement. It should be noted that data referring to students' Self-Regulated Strategy Use and Executive Functioning were analyzed from students' perceptions on questionnaires. Although this data constitute a valid form of research, it varies greatly from the objective measurements and data collection of students' working memory performance and their academic achievement. Students may have answered self-regulation and executive function questionnaires in inaccurate ways. For example, even though responses were anonymous, students may have inflated their responses to highlight a more positive view of themselves. Conversely, students may have underrepresented the true level of self-regulation or executive functioning behaviors that they actually engage in. Therefore, although still valid, the data referring to Self-Regulated Strategy Use and Executive Functioning relying on student perceptions may be slightly less accurate than the objective measurements of Working Memory Performance and Academic Achievement. Further, the Working Memory Performance assessment (i.e., the Automated OSPAN, or AOSPAN) and Self-Regulated Strategy Use questionnaire (MSLQ) were originally developed for a slightly older population (i.e., undergraduates). Nonetheless, current research supports their use with an adolescent population. Both the MSLQ and AOSPAN have resulted in psychometrically sound properties with young adult populations including internal reliability, coefficient computations, factor analyses and correlations (Pintrich, Smith, Garcia & McKeachie, 1991; Unsworth, Heitz, Schrock, & Engle, 2005) their use with an adolescent population has also

16 demonstrated reliable results. Researchers have used the AOSPAN task with adolescents and found encouraging results. For example, in one study, it was found that over 95% of the sample (i.e., 14- and 15-year-olds) had reliable, usable data (Keating, personal correspondence). The results indicated that the task is a viable instrument to assess working memory abilities with adolescents. Similarly, the MSLQ was developed for MidWestern college students. Though an additional version exists for students in grade 7 and 8 (Pintrich & de Groot, 1990), there is not currently a published version designed to use with high school students. However, researchers have used the MSLQ with high school populations and have obtained adequate psychometric properties thus far (Zusho & Barnett, under review).

17 CHAPTER II REVIEW OF THE RELATED LITERATURE This chapter provides a review of the related literature on self-regulation, executive function, working memory, and their relation with achievement. First, research on self-regulation and its relation to student achievement is explored, with an emphasis on Bandura's (1986) social cognitive learning theory. Second, executive function is examined from developmental and biological theories with Barkley (2001) Posner, Rueda, Rothbart, Miller, and Cohen (2004) contributing research in this area. Lastly, literature on working memory is explained with an emphasis on Baddeley (1986) and Baddeley and Hitch's (2000) model of the cognitive skill. Attention is also described as a necessary skill for the constructs of executive functions and working memory. The relation between self-regulation, executive function, and working memory and academic achievement will be discussed based on current research. Self-Regulation Self-regulation, self-regulated learning, and metacognition are related terms within the field of psychology but researchers do not use standard definitions of the terms and therefore they are sometimes used interchangeably (Dinsmore, Alexander, & Louglin, 2008). Metacognition is defined as knowledge or mental activity that involves cognition about cognition (Flavell, 1985), while self-regulation refers to the process of influencing the external environment by engaging in self-observation, self- judgment, and self-reaction (Bandura, 1986). Further, many researchers utilize

18 Bandura's (1986) social cognitive learning theory of human behavior to explain self- regulated learning, or the process by which students activate and sustain cognitions, behaviors and affects which are directed toward the achievement of their goals (Schunk & Zimmerman, 1994). Students with elevated levels of self-regulation appear to be active participants in the learning process. Self-regulated students do not appear to rely solely on teachers, parents, or other external factors to learn (Alexander, 1997). Instead, they activate their learning by engaging in deliberate and nondeliberate forms of cognitive engagement (Winne, 1995). Teachers have often described students with increased levels of self-regulation as self-starters who demonstrate obvious persistence, are capable of overcoming problems, and are reactive to the outcomes of their performance (Zimmerman, 1997). Zimmerman (1989) qualifies students as self- regulated learners if they apply specific strategies, based on self-efficacy perceptions, to achieve their goals. Therefore, if a student perceives him or herself capable of completing a task successfully, they may engage in self-regulated learning strategies such as organizing and transforming information, self-consequating, seeking information, and rehearsing or using memory aids (Zimmerman & Martinez-Pons, 1986). Development of Self-Regulation The development of self-regulation can be understood in terms of social cognitive theory, as discussed below. Schunk and Zimmerman (1997) utilize a social cognitive framework when they explain how self-regulatory abilities emerge from four phases of development: observation, imitation, self-control, and self-regulation.

19 During the observation level of self-regulation, an individual watches a model and then incorporates the behavior, activity, or learning strategy into their own behavior. At the imitative level of self-regulatory competence, a learner attempts to approximate the general form of the model. The distinction between these two phases is that a learner must be motivated to actually imitate a skill after observing it in order to progress to a higher level of self-regulation (Schunk & Zimmerman, 1997). Whereas the observation and imitation levels of self-regulation stem from the social influences of others, the more advanced stages (i.e., self-control and actual self- regulatory behaviors) are propelled by factors within the individual. At a self- controlled level of self-regulation, an individual is capable of using a strategy independently when transferring the skill to a novel situation (Schunk & Zimmerman, 1997). With more complex learning scenarios, an individual must employ specific self-regulatory skills, which allow them to systematically adapt their learning strategies so that personal and contextual conditions are altered (Bandura, 1986). At this stage, individuals initiate learning strategies, make adjustments to their behaviors or environment, and maintain motivation based on their self-efficacy perceptions from successes (Schunk & Zimmerman, 1997). Theories of Self-Regulation Social cognitive theory (Bandura, 1986) serves as the basis or conceptual framework for multiple theories of self-regulation. An overview of social cognitive theory is provided and three theoretical views utilizing this perspective (i.e., Pintrich & Degroot, 1990; Winne, 1995; Zimmerman, 1989) are discussed. Bandura (1986) posited that human functioning is a series of reciprocal interactions between

20 behavioral, environmental, and personal variables such as cognitions and affects. Bandura also emphasized the importance of self-efficacy beliefs as a personal variable. He believed that it influenced the choice of tasks, amount of effort exerted, and level of persistence among students (Schunk 1996). The triadic relation between behavioral, environmental, and personal variables can often be observed in the classroom. For example, a teacher may introduce an unusual stimulus or a novel experience (i.e., a behavior), and students' attention is oriented to the event. Reciprocally, behavior can affect environmental variables in that, if students' behavior conveys confusion about a topic, a teacher may alter their approach to teaching or tailor the instruction in some way, which encompasses an environmental change. Personal and environmental variables also reciprocally interact with each other. For example, when students encounter a distracting environment, they may increase effort and concentration. Conversely, environmental variables can influence personal variables by feedback received from others. For example, a teacher's praise or criticism may increase or decrease a student's self- efficacy beliefs, or how competent the students feel about a task (Schunk & Zimmerman, 1997). Human agency is another central component to Bandura's social cognitive theory (1986) and refers to the idea that individuals intentionally make things happen by their actions (Bandura, 2001). The notion of agency suggests that people do not simply undergo experiences nor are hosts of internal happenings in the body, initiated by external factors. Rather, they become agents of their experiences by deliberately constructing events from input derived from sensory, motor, and cerebral systems

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Abstract: Self-regulation, executive function and working memory are areas of cognitive processing that have been studied extensively. Although many studies have examined the constructs, there is limited empirical support suggesting a formal link between the three cognitive processes and their prediction of academic achievement. Thus, the present study hypothesized that working memory performance would predict students' self-report of executive function and self-regulated learning strategies which would subsequently predict academic achievement. The sample consisted of 155 freshman and sophomore female high school students at a private school in New York City. Students electronically completed questionnaires about their self-regulated learning strategies (i.e., The Motivated Strategies for Learning Questionnaire) and their executive functioning (i.e., The Behavior Rating Inventory of Executive Function--Self Report). Additionally students' working memory abilities were assessed with the Automated Operation Span task (AOSPAN); a computer-adapted task requiring dual processing of simple math operations and the recall of letters. Results from multiple regression analyses revealed that students' working memory performance did not predict students' report of self-regulation, executive functioning, or academic achievement as measured by final grades and PSAT scores. However, students' reports of self-regulated learning strategies, or cognitive engagement, were found to significantly predict academic achievement in English. Cognitive engagement was not found to predict math achievement nor did it predict critical reading or math PSAT percentile score. It appears that self-regulated learning strategies are most predictive of achievement when the ultimate goal is mastering the content of verbal material in English classes. Therefore, by creating an environment that encourages the use of regulatory and organizational behaviors, teachers can begin to facilitate a change in cognitive strategies, which could subsequently lead to increased retention of mathematical information in the classroom and on standardized testing. Since the results indicate that working memory did not predict academic achievement, the construct should not be considered as a sole predictor of students' ability to succeed academically. These results are promising for students who demonstrate weaker working memory skills. Since working memory does not directly impact academic achievement, students can compensate for working memory difficulties by employing other cognitive engagement strategies that successfully impact achievement.