«Facilitating Higher-Order Thinking: Synthesizing Pedagogical Frameworks for the Development of Complex and Coherent Conceptual Systems Michael A. ...»
Noddings (1984) wrote that those who care for others should manifest the specific intention to acculturate others into an ethos of caring, in order "to preserve and enhance caring" (p. 172) in oneself and others. "This quite naturally becomes the first aim of parenting and education" (p. 172), an aim that should never be superseded by rationality, which, "while important and prized, must serve something higher... The primary aim of every educational institution and of every educational effort must be the maintenance and enhancement of caring" (p. 172). This ethical perspective on education should be of interest to every educator; thinking is instrumental to our values, our intentions and our goals, and education should be designed to serve the creation and maintenance of beneficent goals and purposes, manifestations of our commitments to provide benefits to others as well as to ourselves.
Attitude Learning Gagne & Driscoll (1988) have provided a highly insightful, and very useful, dynamic model for the instructional techniques and conditions that facilitate the development of an attitude, which they define as "a learned capability that affects the learner's choice of personal action... an internal state that originates processes of executive control" (p. 97, original emphasis). This definition describes our tendencies and dispositions, constructs which represent the behavioural manifestations of our intentions and motives. On the question of how to teach students to develop new attitudes, their description comprises three dimensions of learning and teaching. First, learners must come to realize that an attitude (which they do not habitually manifest) would be of value to them. "The establishment of an expectancy [of success] is a particularly critical feature in the learning of an attitude" (Gagne & Driscoll, 1988, p. 98). To learn this, one may observe a role model, with whom they identify, perform an action that is representative of a particular attitude, and experience a successful outcome; or they may be reminded of a time when they performed such an action (contrary to their old habits) and were rewarded. They must also be provided with opportunities themselves to perform actions that are consistent with the new attitude, and "the expectancy that is activated must be confirmed" (Gagne & Driscoll, 1988, p. 99). That is, the learners must be rewarded for their actions, or they must observe a successful outcome for the role model. These authors have suggested that new attitudes, which are more adaptive, and more facilitative of learning outcomes, may be developed if the appropriate techniques and conditions are implemented in our instructional environments. This implies that these techniques can be applied to support our students in developing the affective dispositions that lead to higher-order cognitive development.
Inferences Regarding Higher Cognitive Development I infer that deep (or achievement) motivation is required for advanced cognitive development, and that the motivation to learn is manifested through a variety of attitudes (dispositions or commitments to intellectual work). Attitude development can be facilitated through educational processes; however, not all students do the work, or manifest the commitments, that enable the development of higher-order, complex, and coherent sets of ideas.
Self-Regulation and Learning Metacognition and Metalearning Flavell (1979) described metacognition as higher-order thinking processes which actively control knowing and learning. Biggs (1985) used the term metalearning to describe awareness and control of one's learning; for each of us, metalearning requires knowledge of how we learn, motivation to monitor and regulate our learning, and the capacity to regulate our actions with regard to learning and cognitive development.
Academic and practical understandings of these two hypothetical constructs are useful in developing methods to facilitate instruction in the recognition, definition, and resolution of complex and ill-defined (academic or practical) problems.
Self-Regulated Learning Pintrich and Zusho (2002) reviewed theories of self-regulated learning (SRL), pointing out that four areas of human functioning are subject to self-regulative control during learning: cognition, affect (and motivation), behaviour, and learning contexts.
These authors describe self-regulation as being driven by a complex of knowledge and skills that take time to learn (so older students are more capable in this area than younger ones). SRL develops through a positive feedback cycle: more learning leads to more selfregulation, which leads to more learning. Schunk (1989) agrees that students contribute actively to their learning goals and exercise a large degree of control over their attainment, writing, "People are motivated to learn behaviors that they value and that they believe will lead to rewarding consequences" (p. 85). Corno (1986) specifies various forms of control that can be developed; attention control (which describes the value of attending to task-relevant information and resisting distractions); motivation control for "state orientation," including self-reinforcement and penance), emotion control and environmental control (e.g. asking for help).
Paris and Paris (2001) reviewed classroom research on self-regulated learning, describing the relevance of a variety of factors, and presenting some interesting conclusions with regard to effective educational practices. They noted that observable actions could indicate the operations of three different sets of factors, including (a) cognitive engagement (interest in the task, determined by the type of task and the student's personal interests), (b) self-assessment (which has profound effects on motivation to continue working on a problem, or to take interest in similar problems in the future), and (c) the use of strategies in reading and writing. In particular they stressed the importance of learning how, and when, to use strategies, and to attribute success or failure respectively to proper or improper strategy use (rather than to luck or to personal inability to learn). They noted that peer support, planning, and practice are important elements of success in learning to self-regulate, and learning to internalize standards of effort and performance. Paris and Winograd (2001) have emphasized the need for teachers to learn self-regulative skills, so that they might model self-regulated learning (SRL) during instruction. "[TJeachers must be reflective and analytical about their own beliefs and practices and they must acquire a deep understanding of cognitive and motivational principles of teaching" (Paris & Winograd, 2001, p. 1). Teachers can be taught to analyze their own learning styles, and to evaluate their own understandings, in order to manage their own learning. Students, including pre-service teachers, can learn to recognize when they are thinking well (clearly and coherently), in contrast to thinking poorly (making errors in analysis or justification). Schunk (1989) posits that effortattributional feedback also promotes self-efficacy, and "The belief that one is capable of learning is an important part of the self-regulation process" (p. 106).
The idea of SRL is closely tied to the theory of learner-centred instruction. As Zimmerman and Schunk (1989) have remarked, "As an organizing concept, SRL describes how learners cognitively, motivationally and behaviourally promote their own academic achievement" (p. ix). Zimmerman (1989) noted, "[F]or learning to occur, students must become proactively engaged at both a covert as well as an overt level" (p. 22). Zimmerman (1990) notes that "self-regulated students" consistently use metacognitive, motivational and behavioural strategies, and are especially responsive to feedback; he emphasizes that self-regulation involves the planning, goal-setting, organizing, self-monitoring, and self-evaluating mechanisms that are part of the individual's approach to learning.
Winne (1995a) describes SRL as self-regulative cognitive engagement, which requires a deliberate, judgmental and adaptive attitude towards self-development.
Processes include seeking and retrieving information, monitoring engagement, tuning strategic plans, and revising knowledge of oneself (as well as knowledge of the domain
being studied). Four basic ingredients are required for teaching students to self-regulate:
content knowledge of the domain; conditional knowledge of which cognitive strategies are applicable in various learning situations; action knowledge (cognitive, metacognitive and behavioural skills involved in learning); and motivation to learn effectively. Winne (1995b) notes that SRL is expanded through social processes, and that novices might (mistakenly) focus on objectives, and assessment criteria, that are relevant to them (rather than those that their instructors prescribe). Winne also suggests that the nature of mental effort is not well understood, and that research should focus on such problems as determining: how goals are formed and how they guide SRL, how understanding is proceduralized in tacit forms, and how individual differences in cognition can be accommodated through instructional methods.
Winne (2005) points out that learners are agents who construct knowledge, therefore they always self-regulate their own learning. However, effective SRL is not automatic; effective instructional scaffolding can enable students to "bring SRL into mindful focus" (Winne, 2005, p. 562); to recognize when SRL is needed; to be informed (through process feedback) about the qualities of their results; and to keep track of what they learned and how they learned it.
Measuring Self-Regulatory Processes Measures of metacognitive self-regulation have received some attention in recent history from researchers in psychology and education. Most of the metacognitive selfregulation measures that are reported in academic journals ask respondents to rate their use of behaviours that are designed to regulate cognitive functions (e. g., study habits and problem solving methods).
Schraw and Dennison (1994) constructed a 52 item self-ratings inventory to assess adults' metacognitive awareness (the Metacognitive Awareness Inventory, or MAI), pointing out, "metacognitive awareness allows individuals to plan, sequence and monitor their learning in a way that directly improves performance" (p. 460). They used a one hundred millimetre rating scale (from never to always) to indicate self-rated levels of identification with inventory items based on eight theoretical dimensions: metacognition, declarative knowledge of cognition, procedural knowledge, conditional knowledge, use of information management strategies, monitoring, debugging strategies and evaluation.
Factor analysis of the scores (using both varimax and oblique rotation) revealed six factors, which did not correspond closely with the eight theoretical dimensions, and the researchers opted for a forced two-factor solution: knowledge of cognition (what students know about themselves, strategies, and the conditions under which strategies are most useful), and regulation of cognition (knowledge about the ways that students plan, implement strategies, monitor, correct comprehension errors and evaluate their learning).
Sperling, Howard, Miller and Murphy (2002) developed and tested the Jr. MAI for students in grades three through eight; similar results were reported.
A group at Western Illinois University (Gordon, Lindner, & Harris, 1996; Harris, Lindner, & Gordon, 1996) developed the Self-Regulated Learning Inventory (SRLI) for
university undergraduates, in order:
... to help researchers and teachers better understand the construct of selfregulation as it relates to academic success,... to provide a tool for use in identifying behaviours, skills and attitudes students need to help achieve academic success, and....to provide diagnostic insight into the needs or learning problems of particular individuals. (Gordon et ah, 1996, p. 2;
The SRLI measured five cognitive skill dimensions: metacognition, learning strategies, motivation, contextual sensitivity and environmental utilization and control;
the instrument asks respondents to rate (on a five-point scale from "not at all typical of me" to "almost always typical of me") their identification with effective study habits, motivating and de-motivating factors, help-seeking, and reflective practices. According to these researchers, "we... arrived at the working conclusion that metacognition, although mediated by, and dependent upon, the other components we had so far identified, represents the key to self-regulation of the learning process" (Gordon et al, p. 4).
Researchers at the NASA Classroom of the Future at Wheeling Jesuit University (Howard, McGee, Hong, and Shia, 2000) categorized self-regulation skills applied by science students in a computer-based learning environment. Their self-rating test items asked respondents to rate (on a five point scale from never to always) their use of particular problem solving skills, reflective strategies and self-efficacy. Their test instrument (the Inventory of Metacognitive Self-Regulation, or IMSR), examined five metacognitive skill dimensions: Knowledge of Cognition (the understanding of one's cognitive processes), Objectivity, Problem Representation, Subtask Monitoring and Evaluation. Regression analysis showed that total score on the IMSR significantly predicted Content Understanding and Problem Solving. Three of the five factors (Knowledge of Cognition, Problem Representation and Objectivity) were significant predictors of Content Understanding; these three skill dimensions, and Evaluation, predicted Problem Solving at significant levels.
Sperling, Howard, Staley and DuBois (2004), studied undergraduate students' metacognition (as measured by the MAI), motivation (using the Motivated Strategies for Learning Questionnaire, developed by Garcia and Pintrich, 1995), study strategies (using the Learning Strategies Survey, developed by Kardash and Amlund, 1991) and achievement (Scholastic Aptitude Test, courses dropped, and high school Grade Point Average). They found that metacognition scores correlated inversely with courses dropped (which was expected), but also correlated inversely with math scores (a surprising result). No correlation was found between the MAI scores and high school grades, but study strategy use and metacognition scores were significantly related (r =.60, p.001). The correlation between the motivation and metacognition measures was moderate, but statistically significant (r =.40, p.05).