2.+Literature+Review

//(Existing research and its relevance for my topic, relevant theoretical perspectives, key ideas or constructs in my approach, possible lines of inquiry to pursue.)//


 * __3. LITERATURE REVIEW __**

__ PART A: Influences on the field of self-regulation __

Strategies to help people learn go back to figures such as Socrates (Novak 1985). Throughout modern research literature a multitude of terms have been used in at least the last four decades to try and capture what has proved to be an elusive and shifting concept around the field of what we may term ‘student approaches to learning’ (Duff et al, 2004), where boundaries are constantly re-shaped and blurred depending on the focus of the study.

The work of early theorists such as Piaget, Vygotsky, Dewey and Bruner has had an enormous influence on subsequent research in the field of education. Piaget (1952) proposed that it is the continual adaptation to an environment that shapes and moulds the schema or frameworks upon which our thinking is based with new experiences being integrated into the schemata. Dewey (1952) stressed that it is the unexpected that challenges and extends our thinking. Vygotsky(1962) emphasized the importance of language in the development of thinking as an integral part of the process of restructuring situations and environmental factors cognitively. This examination of the field of student approaches to learning begins with the exploration in the 1960s and 1970s of how to best teach students to complete the academic tasks they were given.

MODELS OF LEARNING AND STUDY HABITS

Much of the debate around terminology arose from the development of inventories or models for student learning. One of the first study method inventories in the field by categorised effective ‘study methods’ into work methods (effective study procedures), delay avoidance, teacher approval and educational acceptance. The focus was on a description of effective study techniques.

The seminal works by Ausubel (1968) distinguishing between rote and meaningful learning and reception and discovery learning and the importance of relating new experiences to what the learner already knows, Wittrock’s (1974a; 1974b) model of generative learning, Pask’s (1976) exploration of ‘holistic and serialist learning strategies’ with the distinction between ‘style’(general preferences rooted more in personality differences) and ‘strategy’(preferences for tackling a particular task), and Marton and Saljo’s (1976) examination of how students learn and the categorizations of ‘deep’ and ‘surface’ processing, greatly influenced subsequent investigations in this area with the research moving away from describing study techniques to looking at the processes behind them and the development of models and inventories in an attempt to measure students’ approaches to learning. Gijbels et al (2005, p.328) explains: // “The concept of deep learning is associated with students’ intentions to understand and construct the meaning or the content to be learned, whereas the concept of the surface approach refers to students’ intentions to learn by memorizing and reproducing the factual contents of the study materials”. //

Marton and Saljo (1976) propose the concept that the ‘process of learning’ is exhibited by what the student does in order to learn something. Although the teacher may be focused on a particular outcome, what actually happens will depend on how the student perceives the task and their subsequent choice of approach to the task – whether a deep or surface approach is taken. This new approach to thinking about student learning was the catalyst for the conceptual framework of ‘student approaches to learning’ (SAL) theory (Biggs 2001).

A useful diagram by Novak and Gowin (1984, pp.8) illustrates the relationships between these.

INVENTORIES AND THE MOTIVATIONAL FACTOR

These perspectives inspired and influenced new learning and study inventories and the development of study strategy questionnaires in an attempt to take a quantitative approach to measuring and describing student differences in learning. The purposes of these inventories varied from predicting academic performance to identifying students in need of individual help.

During the 1970s and 1980s these inventories focused not just on ‘study methods’ as per the initial inventories, but incorporated research from the fields of motivation, personality types and the interplay of these with learning processes. These inventories were influenced by the focus of research at that time, namely, the importance for academic achievement of the students own efforts determined by their levels of motivation and their subsequent study habits (Entwistle & McCune 2004).

The relationship between motivation and ‘study habits’ became a popular research topic explored by Entwistle, Thomson and Wilson (1974), Thomson (1976), who examined prediction of college success using the Student Attitude Inventory (SAI) to assess study methods.

Schmeck, Ribich and Ramanaiah (1977) developed an Inventory of Learning Processes (ILP) in 1977 and this was soon followed by Biggs’ work whose questionnaires assessing approaches to learning, the Learning Process Questionnaire (LPQ) (Biggs 1987c) for school students and the early form of Study Process Questionnaire (SPQ) (Biggs 1987a;, 1987b) for tertiary students to assess students’ use of these approaches, revised in 1987 with an added third dimension of an ‘achieving’ approach, to that of deep and surface learning. The ‘achieving’ approach is characterized by a desire for recognition of efforts prompting highly organized learning processes. Biggs’ approach was heavily based on the cognitive psychology work of Marton and Saljo.

This was a theoretically similar approach to that of the Approaches to Studying Inventories (ASI) by Entwistle and Ramsden (1983), based on the work of Entwistle, Hanley and Hounsell (1979), aimed to measure ‘study methods’ and ‘orientations to studying’ – taking into account the ‘strategic’ approach students (similar to Biggs’ achieving approach) take to studying, their approaches vary depending on a variety of factors such as the course, assessment, the lecturer. Combining study methods with theories about learning processes, Schmeck et al (1977) developed an Inventory of Learning Processes (ILP), subsequently revised in 1991 and 1996 also aiming to describe the way students approached their academic work.

New inventories continued to be proposed with new ways of classifying learning outcomes and approaches: Structure of the Observed Learning Outcome (SOLO) taxonomy by Biggs and Collis (1982), Weinstein, Palmer and Schultz, (1987) Learning and Study Strategies Inventory (LASSI) which used the results of the inventory in the tailoring of a study skills training program, Tait, Entwistle, and McClune’s (1998) Approaches and Study Skills Inventory for Students (ASSIST). Not to mention the multiple revisits and reworks of existing inventories both by original authors and those expanding on ideas previously outlined such as Entwistle and Tait’s (1995) Revised Approaches to Studying Inventory (RASI), Bigg, Kember and Leung’s (2001) Revised two factor version of the Study Process Questionnaire (R-SPQ-2F).

The next phase of study strategy inventories brought in mental models, metacognition and self-regulation such as Vermunt’s (1998) Inventory of Learning Styles (ILS) and Motivated Strategies for Learning Questionnaire (MSLQ) developed by Pintrich et al (1991). This instrument focuses primarily on deep learning and self-regulation but also includes consideration of motivation and recognition of collaboration (Entwistle and McClune 2004).

PARALLELS IN MANAGEMENT EDUCATION FIELD

These developments were also influenced by the advances in the field of management education, Kolb’s (1976) theory of learning styles in management education and the introduction of the Learning Style Inventory (LSI). Kolb (1984) defined a four-stage cycle of learning by doing: acquisition of concrete experience (CE), reflective observation (RO) on that experience, theory building or abstract conceptualization (AC), theory is then put //to// the test through active experimentation (AE). Honey and Mumford (1992) continued this work with the Learning Style Questionnaire (LSQ) which indicated preferences for active, reflective, theoretical or pragmatic learning. Subsequent studies evaluated the effectiveness of such inventories or in the case of Allinson and Hayes (1988) compared these and concluded that although LSQ was more capable of actually measuring something there is no conclusive evidence that the results were significant. This field followed a similar path towards the concept of self-directed learning with the development by Guglielmino (1992) of a self-directed readiness scale and the discussion by Robothham (1995) on the importance of developing ‘foundation skills’ such as self-directed learning.

PERSONALITY FACTORS

Throughout the investigations on study habits runs a parallel and sometimes overlapping stream of research on the effects of personality on academic performance. Kuethe (1961) examined personality traits independent of intellectual capacity that were related to academic achievement. Entwistle (1979) reviewed the work of a number of theorists in the field emphasizing the importance of personal development models in the field of teaching and learning. Chamorro-Premuzic and Furnham (2003) reviewed the previous findings in the field as background to their longitudinal study in this area, an excerpt of which follows to illustrate the breadth of research available:

// “Although past research has explored the relationship between personality and academic // // performance (Cattell & Butcher, 1968; Eysenck, 1967; Kline & Gale, 1977),academic achievement has been typically associated with intelligence rather than personality(e.g., Elshout & Veenman, 1992; Harris, 1940; Neisser et al., 1966; Sternberg& Kaufman, 1998)…There is, however, longstanding empirical evidence indicating that both personality and intelligence are important predictors of academic performance as both have been known to be related to learning (Busato, Prins, Elshout, & Hamaker, 1999; Eysenck,1981; Furnham, 1992). Mayer (1955), and Vroom (1960) believed general performance to be a multiplicative function of intelligence and motivation, where motivation can be conceptualized in terms of personality characteristics (Rindermann & Neubauer, 2001)…..It has been recently claimed that personality measures on their own are powerful enough to explain a moderate percentage of the variance in academic performance (Blickle, 1996; Cacioppo, Petty, Feinstein, & Jarvis, 1996; De Raad & Schouwenburg,1996; Goff & Ackerman, 1992; Rindermann & Neubauer, 2001, p.320)”. //

For the purposes of this study, it is enough to accept Duff et al (2004)’s investigation suggesting that approach to learning is a subset of personality.

LEARNING STRATEGY RESEARCH, ‘LEARNING TO LEARN’ & METACOGNITION

In addition to the search for ways to measure student approaches to learning, there were also many attempts to remove the ambiguity in much of the terminology.

This issue is raised by Laurillard in a section of work titled ‘Styles and Strategies of Studying’, “terminological problems abound in this area because none of the frequently used terms, “style”, “strategy”, “process”, have been rigorously defined, nor are there any universally agreed definitions” (1979, p.396). Laurillard goes on to craft her own definition for the process of learning bringing together concepts from both Pask (1976) and Marton and Saljo (1976) to blend a two-fold perspective ( ‘executive style’ to refer to the way the student thinks about the subject matter and ‘strategic approach’ referring to the manner in which the student approaches the task) into a cohesive definition of the learning process as “a decision-making process in which the student chooses his methods of working on the basis of his response to the conditions” (1979, p.408).

Weinstein and Mayer’s definition leans more towards the strategic perspective: “Learning strategies can be defined as behaviours and thoughts in which a learner engages and which are intended to influence the learner’s encoding process” (1983). Dansereau states that “an effective learning strategy can be defined as a set of processes or steps that can facilitate the acquisition, storage and.or utilization of information. Learning strategies may vary along a number of important dimensions”. (1985, p.210)

Weinstein later defined learning strategies as a sub-area of learning to learn: “Learning strategies are considered to be any behaviours or thoughts that facilitate encoding in such a way that knowledge integration and retrieval are enhanced. More specifically, these thoughts and behaviors constitute organized plans of action designed to achieve a goal. Examples of learning strategies include actively rehearsing, summarizing, paraphrasing, imaging, elaborating and outlining” (1988, p.291). The implication is that strategies is a broader term than 'skills' implying the ability to use it for a variety of tasks. Weinstein also conceded that the breadth of studies, while enriching the field, has created definitional problems. So despite these attempts at defining the boundaries of student approaches to learning, the ambiguity continued.

Attempting to define and measure student approaches to learning inevitably leads to looking at ways to improve and develop these approaches. Early attempts to improve student approaches to learning were mainly through the means of ‘learning-to-learn’ interventions (Hounsell 1979) or the explicit teaching of cognitive strategies. Developing and evaluating materials such as booklets like Georgiady & Romano’s (1994) Focus on Study Habits in School for Middle Year Students (commissioned by the US Department of Education) or Walker and Antaya-Moore ‘s Make School Work For You (a teaching guide for teachers in Alberta Canada to implement a study skills curriculum in the classroom) became a focus of the research field. Further research led to the realization that teaching students strategies did not guarantee successful engagement with the strategies – and one of the factors for this was found to be motivation.

The focus on motivation to learn led to a new focus on meta-cognitive skills (Brown 1978; Flavell and Wellman 1977). Brown (1988) later describes metacognitive skills as what one knows about the process of learning and oneself in the role of a learner while to Novak (1985) “metacognitive strategies are strategies that empower the learner to take charge of her/his own learning in a highly meaningful fashion.” Part of this process is ‘thinking about thinking’ (Kuhn 2004), a self-reflexive process where the learner reflects on the effectiveness of their approach and the way they think about what they are learning.

Others make a different distinction. Veeman and Spaans (2005) cite a variety of previous research from 1978-1995 to come up with this definition that is a clear foreshadowing of the concepts central to self-regulated learning: “Metacognitive skills are often distinguished from metacognitive knowledge. The latter concept refers to the declarative knowledge one has about the interplay between personal characteristics, task characteristics and available strategies in a learning situation. Metacognitive skills, on the other hand, concern the procedural knowledge that is required for the actual regulation and control over one’s learning activities. Task analysis, planning, monitoring, checking and reflections are manifestations of such skills” (2005, p. 160). Advocates of inventories explored the ideas of metacognition and self-regulation and a more strategic and contextual approach to studying. The results of these works include, but are not limited to, SLQ Strategies for Learning Questionnaire, (Pintrich 1991), Self-Directed Learning Readiness Scale (Guglielminor, 1992), RASI (Revised Approaches to Studying Inventory, (Entwistle & Tait, 1995).

Metacognitive work has also spawned fields such as cognitive load theory which looks at how to develop instructional materials that make efficient use of our cognitive processing capacity (Sweller 1988; Paas et al 2003).

__ PART B: Self-regulated learning: The state of play __

Bandura’s social cognitive theory (1977; 1986) and work on self-efficacy (perception of one’s ability to reach a goal) has contributed significantly to the development of self-regulated learning theory.
 * SELF REGULATED LEARNING **

(More on Bandura)

“Self-regulated learning theorists view students as metacognitively, motivationally, and behaviourally active participants in their own learning process. Metacognitively, self-regulated learners are persons who plan, organize, self-instruct, self-monitor and self-evaluate at various stages during the learning process. Motivationally, self-regulated learners perceive themselves as competent, self-efficacious, and autonomous. Behaviorally, self-regulated learners select, structure, and create environments that optimize learning.” (Zimmerman 1986, p.308).

Early definitions of self-regulated learning such as Corno and Mandinach (1983) were influenced equally by works on memory and cognitive architecture, motivation and metacognition. Self-regulated learning was characterized by students’ conscious attempts to strengthen the associative network through efforts, monitoring and improvements. Corno (1986) explains that even a motivated student with a repertoire of effective cognitive strategies, metacognitive control is needed for academic success.

In a seminal work, Zimmerman expanded on his earlier definition to explain that a self-regulated learner requires three elements. “To qualify specifically as self-regulated, students’ learning must involve the use of specified strategies to achieve academic goals on the basis of self-efficacy perceptions.” (1989, p.329). Zimmerman and Martinez-Pons (1986,1988) categozied student self-regulated learning strategies into fourteen categories derived from student descriptions of how they approach their work.

Bandura (1986)’s theory of social cognition and the importance of three sub-processes: self-observation, self-judgment and self-reaction, formed the basis for Zimmerman’s (1989) model of triadic reciprocality between self, the environment and behavior in an attempt to capture the relationships between these factors in determining a self-regulated learning approach.

From the social cognitive viewpoint, one cannot consider the concept of self in isolation as sufficient for ensuring self-regulation. Relationships between these different factors was a large component of the concept of self-regulated learning that was developing – in contrast to earlier conceptions of student learning where context was not a factor and strategies were taught in isolation.

An example of this is Pintrich (1989) who suggests an overarching framework for self-regulated learning as three domains: cognitive learning strategies, meta-cognitive learning strategies, resource-related learning strategies. Cognitive strategies are those related to students learning, encoding and retrieval of information, metacognitive domain relates to planning, monitoring and modifying, while resource-related strategies relate to effective control of resources. The concept of self and motivation is certainly downplayed in this approach.

(Need to get book: Self-Regulated Learning and Academic Achievement: Theory, Research and Practice, Zimmerman and Schunk, 1989) Paris and Newman (1990) cite an advantage considering the concept of self as part of the domain of self-regulaton is the dual focus on both the processes and consequences of learning. This is also evident in Zimmerman’s conclusions about self-regulated learning definitions. In reviewing the research to this point, he concluded that the common features of these definitions are “use of self-regulated learning strategies, responsiveness to self-oriented feedback about learning effectiveness, and their interdependent motivational processes” (1990, p.6).

McCombs & Marzano (1990) outline two areas to help promote the development of self-regulated learning: for the learner, developing students’ understanding of choice and their metacognitive and cognitive processing strategies.

Zimmerman’s (1994) conceptual framework (below) is an excellent summary of the dimensions of academic self-regulation. The focus of research at this point in time was to identify and learn more about self-regulated students and to teach and evaluate processes hypothesized to enhance students’ self-regulation of learning.
 * // Scientific Questions // || // Psychological Dimensions // || // Task Conditions // || // Self-Regulatory Attributes // || // Self-Regulatory Processes // ||
 * Why? || Motive || Choose to participate || Intrinsically or self-motivated || Self-goals, self-efficacy, values, attributions etc ||
 * How? || Method || Choose method || Planned or automized || Strategy use, relaxation etc ||
 * What? || Performance Outcomes || Choose performance outcomes || Self-aware of performance outcomes || Self-monitoring, self-judgment, action control, volition, etc ||
 * Where? || Environmental (social) || Control social and physical setting || Environmentally/socially sensitive and resourceful || Environmental structuring, help seeking, etc. ||

(Find more on Michigan Group: McKeachie, Pintrich & Lin, 1985, Pintrich & Garcia 1993) – MSLQ – Motivated Strategies for Learning Questionnaire, to measure students reported cognitivestrategy use (eg cognitive engagement, time, place & effort regulation), their reasons for engaging in a task (value component) and their beliefs about their own capacity to perform specific strategies and to control the learning situation (expectancy component).) Some of the key findings of this period to inform our understandings of the complexity of self-regulated learners are as follows.

Meece (1994) examined self-regulated learning with respect to goal orientation and found that learning-oriented students used self-regulation strategies significantly more than performance oriented students. This is linked of course to motivational aspects. Borowski and Thorpe (1994) found that to counter underachievement, children need to be encouraged to metacognitively integrate their self-regulation, affect and motivation. Self-efficacy is also demonstrated to be an important factor in a study by Schutz (1994) who found that perceptions of self-efficacy influence many of the choices students made.

Garcia and Pintrich (1994) integrate prior cognitive (“how”) and motivational (“why”) models of self-regulated learning using self-schemas to bridge the gap. Framework: · goal orientation · personal interest · classroom norms Self-schemas · affect · temporal sign · efficacy · value/centrality || Conceptual knowledge · content knowledge · disciplinary knowledge Metacognitive knowledge · regarding tasks · regarding strategies || · self-handicapping · defensive pessimism · self-affirmation <span style="color: black; font-family: Symbol; mso-bidi-font-family: Symbol; mso-bidi-font-size: 10.0pt; mso-fareast-font-family: Symbol; msobidifontfamily: Symbol; msobidifontsize: 10.0pt; msofareastfontfamily: Symbol; msolist: Ignore;">· attributional style || Cognitive learning strategies <span style="color: black; font-family: Symbol; mso-bidi-font-family: Symbol; mso-bidi-font-size: 10.0pt; mso-fareast-font-family: Symbol; msobidifontfamily: Symbol; msobidifontsize: 10.0pt; msofareastfontfamily: Symbol; msolist: Ignore;">· rehearsal <span style="color: black; font-family: Symbol; mso-bidi-font-family: Symbol; mso-bidi-font-size: 10.0pt; mso-fareast-font-family: Symbol; msobidifontfamily: Symbol; msobidifontsize: 10.0pt; msofareastfontfamily: Symbol; msolist: Ignore;">· elaboration <span style="color: black; font-family: Symbol; mso-bidi-font-family: Symbol; mso-bidi-font-size: 10.0pt; mso-fareast-font-family: Symbol; msobidifontfamily: Symbol; msobidifontsize: 10.0pt; msofareastfontfamily: Symbol; msolist: Ignore;">· organisation || <span style="color: black; font-family: Symbol; mso-bidi-font-family: Symbol; mso-bidi-font-size: 10.0pt; mso-fareast-font-family: Symbol; msobidifontfamily: Symbol; msobidifontsize: 10.0pt; msofareastfontfamily: Symbol; msolist: Ignore;">· amount of effort Self-Schema Activitation/Restructuring Choice Persistence || Quality of effort <span style="color: black; font-family: Symbol; mso-bidi-font-family: Symbol; mso-bidi-font-size: 10.0pt; mso-fareast-font-family: Symbol; msobidifontfamily: Symbol; msobidifontsize: 10.0pt; msofareastfontfamily: Symbol; msolist: Ignore;">· deeper processing Knowledge Activation/Restructuring Academic Performance || In both Zimmerman and Garcia and Pintrich’s framework the emphasis is on the importance of ‘self’ as opposed to emphasizing ‘regulation’. This resonates with the phenomological approach to self-regulated learning argued for by McCombs (1989), emphasizing personal constructions and meaning. Researchers had realized it is the concept of self that provides the impetus to undertake regulation activities. Baekaerts (1995) approaches self-regulated learning with a similar perspective, deconstructing the different types of self-regulation skills into categories that include metacognitive skills and metamotivational skills (motivation control and action control).
 * || Motivational Components || Cognitive Components ||
 * Knowledge and beliefs || Beliefs about task / class
 * Strategies used for regulation || Motivational strategies
 * Outcomes || Quantity of effort

Winne’s (1995) provocative discussion on how learners exercise and develop self-regulation in the absence of scaffolding provided by teachers, peers or technology, provoked widespread discussion. Winne’s premise was that self-regulated learning entails both willed and inherent cognition, and is formed incrementally as the learner engages with instructional experiences. Thus self-regulation can be automated once the learner has procedural knowledge that recognizes when and how to regulate. Winne’s view is that learners inherently self-regulate and it is the individual’s knowledge base about self-regulation that is a determining factor. This hypothesis sparked a number of debates. Is social interaction intrinsic to self regulated learning? Do novices self-regulate? What is the role of goals and effort?

A major criticism of Winne’s work is that he begins with the premise of a motivated learner (Boekaerts 1995). Boekaerts also contends that self-regulated learning is domain-specific, although no evidence is given to support this opinion, and that Winne may have been over-optimistic in his portrayal of the transferability of self-regulation strategies. Schunk’s (1995) response to Winne emphasizes student perceptions, in addition to motivation, as important elements of self-regulation. Alexander (1995) uses Winne’s article as stimulus for a discussion of domain learning where the individual interest of the learner is a potent variable. Alexander also argues that a true delineation of self-regulation should consider not just the solitary learner as discussed by Winne, but also the socially-situated and subject-specific manifestations. In an attempt to broaden Winne’s work, Alexander proposes a three stage model of acclimated, competent and proficient learner through which to view self-regulation, as opposed to Winne’s view that much of self-regulated learning is inherent. Pressley (1995) argues that Winne has neglected the importance of self-regulation as a thoroughly social and inherently long-term process.

Pressley also discusses the issue of transferable competence and contends that there are a number of reasons why students do not routinely apply newly acquired conceptual self-regulation knowledge. Pressley summarises these reasons as follows. New strategies compete with deeply engrained older and neutrally connected strategies that require much less effort to initiate and are more easily accessible. Procedural or ‘how to’ knowledge is ineffective without understanding of when or where to apply this knowledge, the utility of the strategy or how to adapt the procedure to differing circumstances.

Pressley also makes explicit eight instructional principles extracted from Winne’s discussion. These instructional principles provide practical guidance for classroom teachers in implementing the research on self-regulated learning into their classroom.

These principles include: providing diverse opportunities for students to learn the payoff of effort, requiring students to practice procedures to the point of proceduralization before expecting self-regulated use of these strategies, encouraging epistemological belief that learning can be hard for all types of learners, knowledge is not absolute and there are always alternative strategies, encouraging students’ understanding of utility of strategies being acquired, having students learn and practice several procedures simultaneously, ensuring original practice of a strategy permits ready and achievable execution of it, raising awareness that self-monitoring can be flawed and that monitoring will need to occur in diverse ways, and encouraging students to monitor in detail their mastery of each lesson.

As an article to stimulate debate and thought, Winne’s work is exemplary. This debate clarified the direction of self-regulated learning as a complex process that occurs in diverse settings, and involves a variety of factors apart from cognition and knowledge of strategies: self-efficacy, personal agency, motivational and behavioural processes are all essential components (Zimmerman 1995). Self-regulated learning is affected profoundly by social and contextual factors.

(Need Weinstein Model of Strategic Learning) Although Weinstein (1996) tends to focus on the strategic approach to learning, she also presents a wide-covering view of the directions for future research from the importance of developing conceptual models and frameworks, clarity of definitions and terms, assessment of self-regulation, development and acquisition of self-regulation, contextual effects and interactions, interactions with knowledge, disciplines and content domains, helping students improve their self-regulation, and developing materials for instruction and teacher/training professional development.

(Need to add in from : Zimmerman, B.J.,Boner, Kovack, 1996 Developing Self-Regulated Learners: Beyond Achievement to Self-Efficacy (Psychology in the Classroom) ** A comprehensive examination of self-regulation in context is offered by Boekaerts (1997). Her paper reinforces the concepts that there are both cognitive and motivational aspects to self-regulation. These are examined through the perspective of prior knowledge with the construction of a six component model. For each of the cognitive and motivational aspects, the model considers the domain specific knowledge needed, the strategies for these and the regulatory strategies or goal dimension. This leads to the recommendation that teachers be made aware of the different types of prior knowledge in order to ensure students activate their own prior knowledge. Awakening to one’s prior knowledge is only one step towards the process of attaining self-regulation. Zimmerman (2000) outlines the four developmental levels in self-regulated learning. Students begin by observing a proficient model, this leads to emulation where the student attempts to imitate the performance. The third phase is self-control where the skills can be displayed under structured conditions. The learner than moves to self-regulation when the skills can be adapted across different situations and conditions. For this development to occur, students can follow Zimmerman’s (cited by Murray 2000) phases of self-regulation. Forethought which involves goal setting and self-efficacy processes, Performance where students adopt ‘powerful’ learning strategies, and Self-Reflection to evaluate alignment between strategies and goals and make adjustments accordingly. <span style="color: black; font-family: 'Calibri','sans-serif'; font-size: 11pt; line-height: 115%; mso-bidi-font-weight: bold; mso-fareast-font-family: 'Times New Roman';"> Still to write up: Readings on SRL from 2000-2009 plus: <span style="color: black; font-family: 'Calibri','sans-serif'; font-size: 11pt; line-height: 115%; mso-fareast-font-family: 'Times New Roman';"> <span style="color: black; font-family: 'Calibri','sans-serif'; font-size: 11pt; line-height: 115%; mso-fareast-font-family: 'Times New Roman';">
 * <span style="color: black; font-family: 'Calibri','sans-serif'; font-size: 11pt; line-height: 115%; mso-fareast-font-family: 'Times New Roman';">Baumeister, R., F., 1996 Handbook of Self-Regulation: Research, Theory, and Applications
 * <span style="color: black; font-family: 'Calibri','sans-serif'; font-size: 11pt; mso-fareast-font-family: 'Times New Roman';">BOOK: Zimmerman, B.J.,& Schunk, D.H, (Eds.),2001, Self-Regulated Learning and Academic Achievement: Theoretical Perspectives (2nd edn.) Mahwah, NJ: Erlbaum **
 * <span style="color: black; font-family: 'Calibri','sans-serif'; font-size: 11pt; mso-fareast-font-family: 'Times New Roman';">BOOK: Schunk, D.H., & Zimmerman, B.J., 2007,Motivation and Self-Regulated Learning: (Re) Theory, Research, and Applications **


 * <span style="font-family: 'Arial','sans-serif';">.................................................................................................................................................................. **
 * PART C: 21st Century context and digital generation learners**

<span style="font-family: 'Arial','sans-serif';">CHARACTERISTICS OF THE CURRENT DIGITAL GENERATION LEARNERS (//<span style="font-family: 'Arial','sans-serif';">To consider: dangers of stereotyping all learners in this way, effects of social-economic background of students determining access or barrier to anything digital, what students perceive to be learning or entertainment or both (and the effect of this on motivation levels) and the rigidity of these perceptions.) //

The current generation of adolescents has grown up engulfed and immersed in all forms of technology. They are connected 24/7 and have moved on from the Generation Y label to be called the ‘Millennium Generation’ or ‘Net-Geners’ or the ‘Digital Generation’ (Huntley 2006). These are students who have never known a world without remote controls, CDs, cable TV, mobiles and computers.

Prensky (2004) divides the world into digital natives, those who have grown up in the digital world, and digital immigrants, those who did not grow up in the digital age and either do not speak the language or perhaps speak it with a distinct accent. Prensky states that due to technology, digital natives are experiencing life in ways that are different from digital immigrants in so many aspects of their experiences: in the way they are communicating, sharing, buying and selling, exchanging, creating, meeting, collecting, coordinating, evaluating, gaming, learning, searching, analyzing, reporting, programming, socializing, evolving, and growing up. This is quite a comprehensive list and certainly gives an indication of the extent to which technology has evolved and changed for today’s adolescents. 5 key characteristics of technology use by adolescents today are discussed below.


 * <span style="font-family: 'Arial','sans-serif';">Social networkers and constant communicators **

Bensmiller (2005) in a report commissioned by Yahoo and OMB on global youth, media and technology, states that a defining characteristic or primary motivation of the way adolescents approach socialization is their desire to be part of a community and the value they place on the relationships in their life. This then is a driving force in their desire to be connected 24/7.

Huntley points out that this is the world’s first generation to grow up thinking itself global and benefiting from this outlook. Despite the initial fears that computers and the Internet would turn adolescents into solitary friendless geeks with technology swallowing culture, viewpoints expressed forcibly by Talbot (1995), Huntley explains that adolescents are actually benefiting from the use of the Internet to connect to and build online communities and interact with others. This form of communication has not, as it was feared, replaced face to face experiences but is simply allowing adolescents to communicate more often and in different ways with their peers. Communication tools are essential for adolescents to maintain friendships and co-exist in social networks and ensure they are not isolated socially. It is the connectedness of technology that appeals to them – they are able to communicate at all times and receive immediate responses. They don’t mind structure within this context on condition that their freedom and flexibility are not compromised.

Boyd (2006) explains that it is this structured and organized mechanism of interaction that has led to the huge popularity of social networking sites. The participants want to be public in a way that allows others to view their presence and to allow them to interact directly with those with similar interests.

The Centre for Educational Research and Innovation (2001) examines a number of trends that are contributing to the way in which students are interacting with technology. One of the trends they cite was identified in the Kerrey Report (2000) of pervasive computing and digital convergence. This means that there is a trend towards small multi-purpose devices linked by wireless technologies with a broad spectrum of technologies being merged into interactive devices making communication easier and more seamless. The more portable, the more seamless the tools for communication, the more adolescents will integrate these tools into their daily life. These tools will contribute to the ability of students to be able to mine their digital and social networks for their information needs (Anderson & Balsamo 2003).


 * <span style="font-family: 'Arial','sans-serif';">Multi-taskers and media-meshers **

Bensmiller’s report also found that adolescents are under a lot of stress and time pressure to do more things in a day than they actually have time to accomplish. This then is one of the reasons for the high incidences of multi-tasking and media-meshing. Media-meshing refers to the process of shifting between different media in order to supplement or complement information or perspective. Adolescents have little patience to delve to any great depth in a particular media. If they cannot find what they are looking for, they are quick to switch to an alternative media or follow a different lead.

This is supported by a report by the Kaiser Family Foundation (2005). The report tries to establish just what role media of all types plays in young people’s lives, and found that in the US around a quarter of the time adolescents are using one media they are also doing something else media related at the same time. This is particularly prevalent when students are working on homework, with students failing to devote the kind of single-minded attention their teachers would like students to give to their homework. They work on homework while watching TV or while using instant messaging with their peers.

One of the key findings of the report was that while the amount of time students have spent using media has remained almost identical to the amount of time spent in the study also conducted by the Kaiser Family Foundation 5 years ago, ie. around 6.5 hours a day, the amount of time spent using more than one media at a time has increased resulting in the amount of actual media being absorbed by students increasing by around 20%. The report found that as new media is introduced adolescents don’t give up the old media (for example TV watching has not declined) nor do they increase the hours spent on media (perhaps this is a case of the fact that they can’t increase the amount of hours as they are already operating at maximum levels in the time available) so instead they become media multi-taskers (ie they watch TV while also using their laptop). There is still research needed to determine the impact of becoming a multi-tasking learner. Tucker (2005) suggests proficiency in multi-tasking may also relate to this generation being known for attention problems and inability to delay gratification.


 * <span style="font-family: 'Arial','sans-serif';">Technologically savvy **

Another characteristic Huntley discusses is that these adolescents are technologically savvy and this has fundamentally altered the way they view time and space. In all aspects of their lives they expect the immediacy they receive when interacting with technology, and the consequence of this is that they have little patience for delays and at the same time feel there is no point planning too far ahead as everything changes so quickly anyway.

This means that technology for the Net-Geners is not limited to one or two specific applications or devices. Oblinger and Oblinger (2005) emphasise that these teenagers are highly digitally literate and can intuitively and competently use a variety of IT devices. They are eager to explore new technologies and can transfer skills effectively between various forms of technology. While other generations might find this onslaught of multiple inputs highly distracting, Net-Geners are great multi-taskers, at times to the detriment of focus and accuracy.


 * <span style="font-family: 'Arial','sans-serif';">Prefer to learn through discovery **

Part of the reason why these students are so adaptable with new technologies is that as Oblinger and Oblinger (2005) point out these students prefer to learn through discovery rather than instruction. They are eager and willing to experiment and much more likely to start pointing and clicking than read a user’s manual! This exploratory style helps them to retain information more effectively as they tend to investigate areas and follow directions that are of immediate interest to them. Anderson and Balsamo (2003) refer to the concept of ‘just-in-time’ learners. Past experiences have given these students the confidence that when they need to find something, they will.


 * <span style="font-family: 'Arial','sans-serif';">Identity expressed through technology **

For the Net-Geners (or Generation Y as the subset Huntley is examining) their personal technologies are more than just functional tools used to perform particular tasks. Huntley (2006) believes that for these adolescents, these devices symbolize and are a reflection of their own personality and individuality. The irony is that this is the same for all adolescents, a case of ‘we are all individuals in the same way but different’. They all want to be seen as individuals but they are essentially conformist as they all want their individuality to be expressed in the same way. In the end, they all want to fit in.

Further evidence of the importance of technology in adolescents’ identity development is given by Huffaker and Calvert (2005) who examine a specific use of technology, ie how adolescents use weblogs to explore their identity. While their study supports the social interactionist perspective that adolescents can take on different roles and create alternative public selves and perspectives to explore their own identity, particularly given the potential for anonymity in virtual worlds, their data suggested that adolescents tended to create a consistent public face and a cohesive set of representations of who they actually are, or who they perceive themselves to be. In this sense, the Internet has provided a new approach for adolescent identity exploration. By thinking, considering, defining and attempting to articulate their attitudes, thoughts and beliefs, adolescents are undergoing a valuable experience in the process of determining who they really are and what they stand for.


 * Words of Warning **

Bennett, Maton and Kervin (2008) challenge the widely accepted notion of a digital generation with a set of accepted characteristics. Their argument is based on the lack of empirical evidence, sound research agenda and the dramatic and descriptive language. The call is not to reject the concept, but to investigate these claims more deeply before accepting them. Mayes (2000) argues that it is not inevitable that new technologies will automatically lead to change in education.

While we may not accept Prensky’s (2001a) divergent viewpoint that the differences are so significant, radical and fundamental changes are urgently called for as the educational system was not designed to meet the needs of these students, it is difficult to challenge the notion that this group of students has observable characteristics and it is not unreasonable to be cautious in making dramatic educational policy changes without an informed research basis.

Bennet, Maton, Kervin (2008) also make a valid point that although students use a wide range of technologies in their lives, it is dangerous to assume that they are all competent in the use of all forms of technology – context and individual experiences must be taken into account. Without this awareness of possibly flawed assumptions and the complexity of the digital native implications, less adept students may be disadvantaged.


 * Implications for Learning? **

Anderson and Balsamo (2003) raise a number of questions regarding the students of the future: how do this generation’s students assess information that comes in such a variety of different media – this can be expanded on looking at how do students organize these media, and select from the multitude of information available what they need. They advocate a move from critical thinking skills to skills of creative and critical synthesis. For the students of the future their “ most important literacy will be the ability to create knowledge by harvesting information from diverse sources”.p245 The critical aspect refers to the ability to assess the reliability and veracity of the information, and synthesis refers to the ability to integrate information from different sources in different formats.

McGlynn (2005) highlights a number of factors of millenials’ preferences for learning: they like to work collaboratively, learning in their own time on their own terms about ‘real-life’ issues that are important to them. The challenge is keeping them actively engaged through structured activities that permit creativity and individual expression. Kinchin (2004) found that overwhelmingly students have a preference for a constructivist leanrning environment. TO DO: Dates back to Piaget, Vygotsky 1978, Dewey 1938 Bruner (Smith 2005) Brower and Dettinger 1998 – what is a learning community Callahan, Schenk, White – importance of developing collaboration skills Davies et al 2005 – peer learning communities for students Kilpatrick, Barrett, Jones Wenger 1999
 * New Approaches to Learning Communities **


 * ROLE OF TECHNOLOGY**


 * <span style="font-family: 'Arial','sans-serif';">Potential advantages of using technology for learning **

Sendag and Odabas discuss how the rapid changes in the nature of information has led to fundamental changes in today's working conditions and "the need to equip individuals with skills to conduct research, use and transform information, think critically and reflectively, and make higher order decisions" (Sendag & Odabas 2009, p132). <span style="color: black; font-family: 'Arial','sans-serif'; font-size: 10pt; line-height: 115%; mso-ansi-language: EN-US; mso-bidi-language: AR-SA; mso-fareast-font-family: Calibri; mso-fareast-language: EN-US;"> Rose and Meyer (2002) point out that one of the great powers of digital media is the flexibility and versatility of these forms of interaction– learner styles can be catered to through providing a variety of different options capitalizing on the strengths of different students. The same material can be presented to students in a number of different formats even allowing students the option to choose the style that best suits their needs at that time. Another strength is that digital media are transformable and can be stored and presented in a variety of media. A huge advantage, given the speed at which information changes, is that digital media can be easily updated and expanded upon, allowing instructors to react in a timely way to students’ needs. It can also be easily networked and accessed and allow interaction between participants. It is this diversified palette that helps improve communications with and between adolescents.

The role of the social networking site Myspace in the school environment is explored by Harris (2006). He raises a valid point that it is unreasonable to think that these sites will go away, and instead of simply banning these sites proposes that schools need to take steps to involve themselves in this area instead and use students’ interests in them to promote learning. He suggests, for example, that schools could use Myspace as a springboard to discuss relevant issues such as copyright infringement and dialogue on what is appropriate text and imagery for public and private display. The idea is that educators need to take technologies that interest and engage adolescents and integrate these into learning activities in the school environment. The potential power of technology to aid in motivating students to learn must be taken into consideration when looking at the possible advantages of using technology for learning.

Futurelab examines the advantages of the current social software that allows users to communicate, collaborate and publish in a number of ways, in a variety of media. This software helps learners act together to build knowledge bases that fit their specific needs. The use of social software in education is still in its infancy but has the potential to allow educators to deliver communication between groups, enable communication between many people, provide gathering and sharing of resources as well as collecting and indexing of information. Most importantly it can provide new tools for knowledge aggregation and creation of new knowledge, delivering this knowledge to many platforms in a way that is appropriate to the creator, recipient and the context in which it is being applied.

One of the cogent arguments for the power of technology is discussed by Breck (2002). Since 1996 Breck has been actively engaged in digitizing academic knowledge for students through the interface of the Internet. Breck suggests that the increasing use of technology means that more people are getting access to learn about more things and that technology is simply the vehicle for this transmission, not the passenger. Breck believes that the questions asked about technology are misguided. Instead of asking if all students can learn through the medium of technology we should be asking how can we direct students into productive activities on the Internet.

The flexibility of the online environment also has potential advantages for learning. For example, Dalacosta, et al., (2009) found that cartoons in the multimedia application are an effective aid to teaching and learning.


 * <span style="font-family: 'Arial','sans-serif';">Students' use of technology **

Breck outlines an interesting perspective with respect to technology use. Perhaps the reason why we have difficulty in understanding and exploiting technology outside of the classroom is that up to this point we have let students determine the direction and use of technologies in this environment. It is the digital generation who has grown up with technology and is confident and capable in its use. But they do not necessarily have the maturity, life experience or understanding of teaching and learning to make informed decisions about how the technology could best be used and integrated. Unfortunately those with this understanding about learning experiences often lack the knowledge and in-depth understanding of the technologies.

It seems that students spend a large amount of time simply using and experiencing technology in an instinctive manner without spending time reflecting on the advantages or disadvantages of what they are doing with the technology, or the amount of time they are spending on these activities, or whether they are using the technology in a way that aids in their learning. This is only to be expected with adolescents so the importance of parents and teachers in helping students with this meta-cognitive process in evaluating their technology use is paramount. It can also be difficult for students to distinguish between formal and informal learning with technology.


 * <span style="font-family: 'Arial','sans-serif';">Concerns about adolescents, technology and learning **

Oblinger and Rush (1997) cite a number of common fears about technology apart from the traditional safety and privacy of personal information issues. There have been concerns that technology will dehumanize interaction and lead to a decline in literacy. There are concerns that differing levels of access to technology will cause potential equity gaps in experience and opportunities. And it is not just parents that have had these concerns. Schrum and Berenfeld (1997) point out that schools have often lagged behind society in adopting technological innovations and believe this could be due in a large part to dominant social beliefs about what proper teaching and learning should entail. This belief was reinforced at the 2006 World Computer Congress where it was acknowledged that many teachers are still more comfortable and effective with traditional face-to-face teaching methods without the integration of technology (Chen, Frempong & Cudmore 2006). Kay (2009), when exploring gender differences in attitudes towards interactive classroom communications systems, points out that two main challenges have been associated with the use of an ICCS that are relevant, the technology itself and difficulty of students in adjusting to a new method of learning.

Another big issue concerning integrating technology usage outside of the classroom environment is that the Internet and other technologies can be very addictive to some adolescents, even leading to the identification of the existence of an Internet Addiction Disorder (IAD) by Ferris (2004). Butterfield (2005) points out that if a student spends 30-40 hours a week on the Internet on top of their school time all aspects of their life - school, friends and family, will suffer. Students may then need professional support to bring back balance between the virtual and real worlds that they inhabit.

Cranmer (2006) examined young people’s use of the Internet for homework in the UK. She found that young people have embraced the Internet for homework, extensively using it and viewing it as a helpful tool to find and retrieve information. However, her study showed that it seemed as though the majority of young people actually made quite limited use of the Internet. Cranmer explains that the main use of the Internet by children and young people was simply to locate information using similar methodologies as they would for more traditional research options (with of course the same associated issues of copying and plagiarism, although prevalence was greater in online research due to ease of copying and pasting). Although young people sometimes used revision sites to prepare for exams, they seldom used email to seek advice or took advantage of other possibilities on the Internet to help them with their learning. Her conclusion is that in some ways the Internet has simply become a new reference tool for students, or alternatively for parents if they felt their own subject knowledge was inadequate to help their students. Parents were clearly concerned that with the ease of searching and copying information the learning taking place was not as deep as with traditional approaches and that students often completed their work on a more superficial level when using the Internet as their source of information.

A contrasting and different viewpoint comes from Watson (2006) who obviously would view these concerns as unfounded. Watson points out that as Jonassen (2000) previously indicated, a shift in perspective has occurred, students are now learning //<span style="font-family: 'Arial','sans-serif';">with // the software instead of //<span style="font-family: 'Arial','sans-serif';">from // the software. Watson takes this idea further and states that therefore we can begin to categorise technology use by the nature of the learning that they are enabling. For example, many software applications can now engage learners in critical thinking, creating categories of use such as semantic organizers or dynamic modelling tools as opposed to the lower order tasks students may have previously utilized technology for. This idea is expanded upon in Warlick’s (2006) hypothetical discussion of how the latest social networking and other web-based tools used by adolescents could be harnessed to transform the learning experience in the school environment.

Another factor to take into account is gender differences and attitudes in computer-related behaviour. Kay (2008) found that comfort level with technology plays a role in these gender differences while Smarkola (2008) and Wu & Tsai (2006) propose that students with higher self-perceived confidence and expectations of using the Internet may have more success with computer and internet-related tasks.

TO DO: <span style="font-family: 'Arial','sans-serif'; font-size: 10pt; line-height: 115%; mso-ansi-language: EN-US; mso-bidi-font-family: 'Times New Roman'; mso-bidi-font-size: 11.0pt; mso-bidi-language: AR-SA; mso-fareast-font-family: Calibri; mso-fareast-language: EN-US;">Hartley 2007 (how tech affects different types of learning and teaching) <span style="color: black; font-family: 'Arial','sans-serif'; font-size: 10pt; line-height: 115%; mso-ansi-language: EN-US; mso-bidi-language: AR-SA; mso-fareast-font-family: Calibri; mso-fareast-language: EN-US;">

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