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«Facilitating Higher-Order Thinking: Synthesizing Pedagogical Frameworks for the Development of Complex and Coherent Conceptual Systems Michael A. ...»

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For example, Spector (2001) discussed how to support learning in and about complex domains. He recommended that instructors adopt an integrated and holistic view of instructional design, which includes applying theories to practice. To create instruction that supports learning (defined as persistent changes in ideas, beliefs, attitudes and skills), instructors must carefully, and ongoingly, assess the effectiveness of their work (and that of their students). Spector emphasizes the epistemic components of instructional design, underlining the importance of recognizing and understanding the limits of reasonable justification (the "bounds of sense"). He recognizes that theories of truth have been demonstrated to be "problematic," and that meanings are determined by usage in social contexts. He also notes that higher cognitive development requires the adoption of a sceptical perspective: persistent questioning (of oneself as well as of others), a detachment from the certainty of any conclusion, and the recognition that perception (direct evidence) trumps conception (belief). Spector promotes an Integration Principle, which holds that experience is not compartmental, multiple approaches to leaning are beneficial, and whole-task activities should be preferred to part-task activities. He also formulates an Uncertainty Principle for instructional design, which claims that knowledge of instructional principles is always incomplete, and (reminiscent of Schon's reflection-in-action) instructors must discover what works best in each situation.

According to van Merrienboer (1997), understanding complex cognitive skills is a process of "describing relationships of different aspects of environments, learning processes, and learning outcomes. A good understanding of those relationships is believed to be helpful to the instructional design process" (p. 6). van Merrienboer points out that instructional design models may be descriptive (of the interactions between learning processes and instructional environments), prescriptive (goal-oriented and method-driven), or both. He recommends the last approach for training complex skills, and he combines descriptive and prescriptive elements in a four-component model for instructional design, which comprises skill decomposition; analysis of constituent skills and related knowledge; selection of instructional methods; and developing learning environments.

Elaborating on early work by Bruner (1966), Willis and Wright (2000) describe the possibility of reflective and recursive design and development, in contrast to the classic sequence of defining instructional goals, designing the instruction, development, and implementation. Their scheme requires that these steps be iterated as needed, providing a flexible cycle of design, implementation, assessment and redesign (a "spiral" model). Learning objectives emerge as the process develops, and all the steps are iterated repeatedly. Multiple problems are progressively solved in context; this requires "cooperative inquiry," the ongoing gathering of data to ongoingly assess and improve teaching and learning processes; this includes developing and clarifying a team vision of intended results, and considering feedback from students.

In consonance with the perspective of recursive design, Lee and Park (2008) describe the possibility of adaptive instructional systems, which are designed to "accommodate the needs and abilities of different learners... The development of computer technology has provided a powerful tool for developing sophisticated instructional systems from diagnostic assessment tools to tutoring systems generating individually tailored instructional prescription" (p. 470). Baek, Cagiltay, Boling and Frick (2008) promote user-centred design and development, which is intended "to place users at the centre of the design process from the stages of planning and designing the system requirements to implementing and testing the product" (p. 660). Although these two teams focused on the design of computer-assisted instruction, the principles of learnercentred instruction (which require adapting instruction to the needs of learners) are important guidelines for all kinds of educative processes (American Psychological Association, 1995).

Winn (2002) describes the current era of instructional design as the "age of simulations," in which interactivity allows for learner control of learning environments, including "authentic" applications that emphasize social learning. The focus is on (natural or artificial) safe learning environments, with limited freedom to act (so as to limit any damage that might result from learners' mistakes). The use of "inscriptional systems," representations such as models, datasets and virtual environments, allows for deep learning and mastery of subject materials. Peer support and discourse analysis can be used to understand students' thinking; teachers must understand, explain, and clarify the use of reifications and metaphors. Technology should be supplemented by clear purpose and face-to-face communication. The social context of instruction should provide students with the freedom to err, and the freedom to modify the learning environment.

We can locate, within this context, the theory of problem-based learning, which provides opportunities to learners to solve authentic problems. "During the problem-solving process, students construct content knowledge and develop problem-solving skills as well as self-directed learning skills while working towards a solution to the problem" (Hung, Jonassen and Liu, 2008, p. 486).





Other educational researchers have provided valuable insights into techniques for facilitating higher-order thinking. For example., Azevedo (2005b) described computerassisted instruction that aids learners in developing metacognitive self-regulation. His

description of these "metacognitive tools" includes the following six characteristics:

1. It requires students to make instructional decisions regarding instructional goals... 2. It is embedded in a particular learning context that may require students to make decisions regarding the context in ways that support successful learning... 3. It is any computer-based environment that (to some degree) models, prompts, and supports a learner's selfregulatory processes... 4. It is any environment that (to some degree) models, prompts, and supports learners to engage or participate (alone, with a peer, or with a group) in using task-, domain-, or activity-specific learning skills... 5. It is any environment that resides in a specific learning context where peers, tutors, humans or artificial [intelligence] may play some role in supporting students' learning by serving as external regulating agents... 6. It is any environment where the learner's use and deployment of key metacognitive and self-regulatory processes prior to, during, and following learning are critical for successful learning

–  –  –

While these descriptions were developed as being applicable to technological tools, the same principles can be useful to any educator who intends to design instruction that supports and facilitates metacognition and higher-order thinking.

Adopting a dynamic systems approach to educational psychology, Young (2004) promotes an "ecological psychology" of instructional design, which describes learning and thinking by "perceiving-acting systems." This model is consistent with contemporary philosophical schemes that concentrate on the dynamic complexity of interacting "psycho-physico-chemo-biologic learning systems" (p. 169). Ecological psychology interprets behaviour as an emergent result of self-organizing learning systems; learners are self-directed, creating "goal spaces" which contain potential trajectories from current states to potential future states. This allows for consideration of their intentionality and their intentions. Practicing with the materials changes learners' perceptions, including their perceptions of their environments. Feedback allows for transfer of "action and control parameters" from teacher/model to learner/cognitive apprentice; learning (a process of discrimination and differentiation) results from continuous, dynamic, embodied learner/dynamic-environment interactions (coupled feedback associated with control and action parameters). Learning attunes our intentions and our attention with regard to invariant properties of learner-world systems. We learn to detect affordances (Gibson, 1986), or possibilities for action, which represent opportunities to act that are provided by the environment. Effectivities represent an agent's skills or abilities to use the affordances that the environment provides. To create effective instructional designs, educators must understand how goals organize behaviour. Instead of adding information to learners' stores, educators can focus attention on available affordances. In this framework, it is essential to induce students to adopt learning goals that are related to the learning materials and environment. Barab and Roth (2006) extended this idea, describing the purpose of learning processes as "increasing possibilities for action in the world... Transfer can occur when individuals begin to see different contexts as having similar underlying affordance structures—even in the context of differing contextual particulars. In the best cases, individuals appreciate the power of, or adopt commitments with respect to, a particular effectivity set and begin to assert this 'toolset' in multiple situations even when the affordances are not readily apparent on the surface" (p. 11).

Emphasizing the social networking aspect of cognitive development, and building on Bruner's idea that four principles govern learning relationships (agency, reflection, collaboration and culture), Brown (1997) set about creating a social mentality of support for inquiry, reflection, and collaborative learning. The evidence that she describes with regard to the benefits of this type of thinking can inspire educators to create educational

environments which take into account various crucial aspects of learning and teaching:

that education is a cultural process, that reflection is essential to accommodate to the process, and that deep learning requires collaborative work. Educators have emphasized the relevance of the social processes that facilitate learning; sharing the affective and cognitive processes involved in restructuring our ideas is an essential part of cognitive development, and building our relationships with mentors and peers is a powerful way to support learning processes. The power of our learning networks is affected by the administration of the institutions that govern our educational systems; the following section describes some of the relationships between learning and teaching processes within institutional power structures.

Institutional Factors Scanzoni (2005) presents a series of attestations, from university faculty and administrators, who agreed that most institutes of higher education in America had not yet come to grips with the "profound changes" that society has undergone in the past few decades. To overcome the deep resistance to change that pervades the academic world, Scanzoni has called for social scientists to "engage public officials, citizens and students in exploring [socially useful] innovations" (Scanzoni, 2005, p. xi). He recommends that social scientists take the lead in reforming education, switching from a [teacher-centred] instructional paradigm to an inquiry-based learning paradigm. He also recommends that instructors and students engage in action research in order to engage students in their studies, to increase the value that universities bring to education, and to "contribute to a more thorough and comprehensive understanding of the social world"(Scanzoni, 2005, p.

xii).

Scanzoni's review of scholarly literature on the quality of undergraduate education in the United States concludes that students need not accomplish very much to obtain As and Bs. However, the core cognitive skills generally have received little attention. "More than anything else, say the critics, professors have the moral obligation to cultivate students' human capital skills, including the capability to analyze, evaluate and synthesize, and thereby to demonstrate their problem-solving capabilities" (p. 7).

Scanzoni claims that social scientists have been failing in their obligation to contribute value to society at large. "[SJocial scientists have faltered by failing to take the lead in this regard. Coming up with inventions for resolving social issues, that is, creating a more just and equitable society, is after all a matter that falls squarely within the domain of social sciences" (pp. 11-12). Scanzoni recommends that less emphasis be placed on research and more on teaching undergraduates, and that faculty should be required to justify and defend their contributions to students. Universities should continue to attend to the business of education, but they should do so in ways that contribute more directly to society-at-large.

–  –  –

[HJigher education needs to be redesigned. Virtually every variable in the higher education equation is changing at a rapidly accelerating rate.

Change is hard, and universities do not take kindly to it... A successful pedagogical philosophy that will serve as a basis for learning must incorporate understandings about the way in which learners acquire and organize information. This philosophy must address how students represent knowledge internally, the way they store it (that is, keep it in their minds), the way these representations change, and the way they resist change over time. (Halpern, 2002, p. 41) Furthermore, "[M]ost professors have gained relatively little from cognitive psychology. Even cognitive psychologists apply very little about what they know about their own discipline in their own teaching" (p. 42). Halpern concludes that higher education faculty "can do a better job" (p. 43) in their "most important task": enhancing student learning.



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