Computers as Metacognitive Tools for Enhancing Learning

A Special Issue of Educational Psychologist

Roger Azevedo

• Publisher: Routledge
• Year: 2018
• eBook ISBN:
  9781317960089
• Topic: Education
• Subtopic: Education General

First published in 2005. This Volume 40, No 4 of Autumn 2005 of the Educational Psychologist. The articles appearing in this special issue of Educational Psychologist reflect a growing interest by researchers from various fields in examining the use of computers as metacognitive tools for enhancing learning. This topic has become increasingly important as computer-based learning environments become ubiquitous and students use them extensively both in and out of school to learn about conceptually rich domains.

A Theoretical Framework and Approach for Fostering Metacognitive Development

Barbara White

Graduate School of Education
University of California at Berkeley

John Frederiksen

College of Education
University of Washington

This article provides an overview of our work on the nature of metacognitive knowledge, its relationship to learning through inquiry, and technologies that can be used to foster and assess its development in classrooms as students engage in collaborative inquiry. To illustrate our theoretical ideas, we present examples from our Inquiry Island software. It provides learners with advisors, who contain knowledge, advice, and tools aimed at supporting students’ metacognitive development in the context of doing inquiry projects. Our pedagogical approach includes having young learners take on the roles of various cognitive, social, and metacognitive advisors as a way of enacting and internalizing the forms of expertise they represent. We describe a sequence of learning activities and indicate how students respond to them, using examples and findings from a 5th-grade class. Our work shows how such learning tools and activities can foster the development of metacognitive knowledge and skills needed for collaborative inquiry and reflective learning.

We are pursuing a vision of learning in which students work together on inquiry projects, guided by software advisors, such as a Planner and a Reflector, which become an important part of the students’ learning community. In this vision, students reflect on and try to improve the cognitive models of expertise that are embedded in the software advisors, so that the advisors can provide better advice and tools in the future. They also try to internalize the advisors’ expertise through activities such as taking on the role of one of the advisors in a class discussion or group work. Our premise is that by working with, modifying, and taking on the roles of software advisors, students will develop the various capabilities needed for collaborative inquiry and reflective learning that are initially conveyed by the software advisors. Further, through developing this expertise, students and classrooms will be transformed into self-aware, self-improving systems; that is, they will create theories about what they are doing and why as they constantly engage in cycles of planning, monitoring, reflecting, and improving.

To achieve this vision, we argue that developing metacognitive expertise is crucial. It is crucial in fostering an individual’s learning through inquiry and in their learning how to improve their learning processes though inquiry. It is also crucial to groups who are learning how to work together and trying to improve as a team. Furthermore, in our software environment, it is crucial to being able to choose appropriate software advisors for a given task, as well as to making good use of and learning from the guidance and tools they provide. Thus we argue that everyone in a learning community needs to speak and do metacognition. This includes being able to talk about the different cognitive, social, and metacognitive capabilities that are needed, and when and why they are useful. It also means developing what are often called regulatory skills, like planning, monitoring, and reflecting. Finally, it includes what we refer to as “developmental expertise,” that is, expertise about how you improve your capabilities through inquiry and reflection.

Unfortunately, little emphasis is placed on metacognitive knowledge and skills as critical goals for learning in the national curricular standards. The science standards, for example, emphasize developing knowledge of a domain through inquiry, but they place far less emphasis on metacognitive knowledge and skills (National Research Council, 1996). Yet, increasingly, research has shown that metacognitive expertise is needed in developing knowledge through inquiry (Frederiksen & White, 1997; Georghiades, 2004; Hogan, 1999; Kuhn & Pearsall, 1998; White & Frederiksen, 1998, 2000) and is critical in transferring ones’ capabilities for learning in one domain context to learning in new domains, as well as taking charge of one’s own learning (Bransford & Schwartz, 1999; Brown & Campione, 1996; Scardamalia & Bereiter, 1991). There is also evidence that feelings of self-efficacy in learning play a strong role in students’ motivation and interest in learning (Pintrich & de Groot, 1990; Schunk & Schwartz, 1993). Building metacognitive knowledge of oneself as a learner contributes to viewing oneself as an able learner, which influences not only success in learning, but also motivation to learn (Brown, 1988; Corno, 1986; Zimmerman, 1989; Zimmerman & Schunk, 2001).

In this article, we will reflect on our work on learning through inquiry, on the nature of metacognitive knowledge, and on how technologies can be used to foster their development in classrooms, as students engage in collaborative inquiry and reflective learning. We will begin by presenting a theory of the nature of metacognitive knowledge and processes, how they foster learning across domains of study, and how they are linked to students’ views of themselves as learners. To illustrate aspects of metacognition, we will use samples of cognitive models and tools that are incorporated in our Inquiry Island software. Inquiry Island was designed to provide learners with a source of information, advice, tools, and work environments that support their development of metacognitive and inquiry expertise in the context of doing research projects, such as science-fair projects, which engage students in creating and testing theories. Our pedagogical approach emphasizes how the curriculum should also include learning activities away from the software environment, where students, working together in groups, take on cognitive, social, and metacognitive roles as a way of enacting and internalizing the expertise represented in the software advisors. Following the theoretical discussion, we will describe a sequence of learning activities we have developed, and illustrate how students respond to and benefit from these activities using examples from classroom research. We will end the article by arguing that technologies of the future will increase the need for students and their software advisors to be able to talk about and employ metacognition.

A THEORY OF METACOGNITIVE KNOWLEDGE AND SKILL

Our theory seeks to identify, model, and teach the kinds of metacognitive knowledge and skills that will enable students to develop strong capabilities to learn via inquiry in new domains. In outline, our theory emphasizes three types of knowledge: (a) knowledge about the capabilities and goal structures needed for learning through inquiry, (b) knowledge of how one organizes and manages one’s inquiry processes in the course of learning, and (c) knowledge of how to apply inquiry to improve one’s cognitive, social, and metacognitive capabilities for inquiry learning. We will argue that students need to develop explicit cognitive models of capabilities needed for inquiry. Such models help students learn how to do inquiry, as well as to understand its nature and purpose. For example, they allow students to think and talk about the characteristics of different capabilities, such as questioning and analyzing, and why they are useful. Being able to engage in this type of metacognitive thinking and talk makes it easier to manage these processes. Furthermore, one needs explicit models of processes used in inquiry to reflect on, or conduct research about, how to improve them.

In the following, we will frame our arguments in terms of students learning through inquiry in (a) science and (b) reading, the areas in which we have carried out our work. However, we don’t see the arguments—or the approaches to using technology—as specific to these domains of learning.

Knowledge About Learning Through Inquiry

Knowledge of how theories and models are formulated, evaluated, and revised through investigation and analysis is a critical aspect of metacognitive knowledge. If students are to develop a general cognitive theory of how to do inquiry, they need access to knowledge of the varieties of goals and purposes that inquiry entails, as well as the strategies and methods needed to achieve them. Such specifications of the processes needed for inquiry are cognitive models that represent target competencies for students to develop. To support students’ acquisition of these competencies, the cognitive models of inquiry processes need to be readily available to students in a form that makes them accessible and usable in the course of their inquiry, much as a tutor might present useful ideas to students, while they are engaged in a difficult task, and then explain how to use them.

We have developed a learning environment for guiding students’ inquiry (Eslinger, 2004; Eslinger, White, & Frederiksen, 2004; Shimoda, White, & Frederiksen, 2002; White, Shimoda, & Frederiksen, 2000). It includes a community of software advisors who “live” on Inquiry Island. This learning environment, illustrated in Figure 1, has been designed to scaffold and support students’ learning in a number of ways as they carry out inquiry projects.

The inquiry cycle: The top-level goal structure. As students carry out their inquiry projects, they record their ideas and findings in a research notebook, shown at the left of Figure 1. It is structured around a series of phases or steps of inquiry, referred to as the Inquiry Cycle, which is illustrated in Figure 2. Each notebook page represents a step in the Inquiry Cycle. This cycle provides a top-level goal structure for inquiry. In using this Inquiry Cycle, students (a) develop their research question, (b) generate hypotheses, (c) design an investigation, (d) record and analyze their data, (e) create a model, and (f) evaluate the utility and limitations of their model, as well as their research processes, and identify new questions to investigate.

FIGURE 1 A screen from the Inquiry Island learning environment, which includes the Research Notebook (left), in which students record work for their research projects; the Goal Sliders (far left), in which students evaluate their work; the Advisory Window (top left), in which advisors indicate when they have relevant advice; and the Advice Window (right), in which advisors present their advice. Inquiry Island can be downloaded from http://thinkertools.soe.berkeley.edu/ and its successor, the Web of Inquiry, can also be accessed from this Web site.

Task advisors: Cognitive models for inquiry processes. There are a number of important subtasks associated with each step of the Inquiry Cycle, which correspond to the workspaces within each page of the notebook. For instance, the Investigate step includes creating a logical design for your investigation, planning how you will carry it out, collecting and recording data, and keeping track of problems you encountered that might affect your conclusions. To support this finer grain aspect of learning how to carry out inquiry, Inquiry Island includes a set of software advisors, called inquiry-task advisors, one for each of the steps of the inquiry cycle. Inquiry-task advisors house knowledge of goals for that inquiry step, strategies for accomplishing them, and criteria for monitoring their effectiveness. To make it easier for students to keep the advisors straight, each has a name, such as Quentin Questioner and Ivy Investigator. As an example, Ivy Investigator has six goals to work toward: (a) choosing an appropriate situation in which to observe the phenomenon you are studying, (b) making sure it will allow you to test your hypotheses, (c) planning carefully how you will carry out the investigation, (d) making sure you have the resources to carry it out, (e) checking that you have an adequate sample of data, and (f) fully documenting your research, including any changes or problems that occurred. The inquiry-task advisors provide detailed cognitive models for students to employ in performing all of the subtasks of each inquiry cycle step.

FIGURE 2 An inquiry cycle.

General-purpose advisors: Models of cognitive, social, and metacognitive competencies. In addition to developing an understanding of the inquiry task at hand, such as analyzing or modeling, students need to think about how that task is related to other inquiry tasks, and also about how their general cognitive, social, and metacognitive competencies can contribute to working on that task. To represent this idea, each page in the research notebook has a team of advisors who can offer relevant advice. These teams typically include task advisors for related inquiry steps, as well as an important addition: general-purpose cognitive, social, and metacognitive advisors, who have expertise that may be useful in working on that inquiry step. Examples of cognitive advisors include Ingrid Inventor (who has strategies for coming up with new ideas) and Sydney Synthesizer (who is concerned with fitting different ideas together). Examples of metacognitive advisors include Pablo Planner (who has strategies for effective planning) and Molly Monitor (who is concerned with monitoring the efficacy of work processes and the quality of products). Examples of social advisors include Keiko Collaborator (who has strategies to help people collaborate well with one another) and Manny Mediator (who helps members of a group work out their differences). The faces that appear above the students’ work area in Figure 1 reveal the team of advisors for the question step of the inquiry cycle. By clicking their mouse on them, students can consult any member of the current advisory team for each step in the inquiry cycle. When they consult an advisor, it presents its advice in a browser window (shown at the right of Figure 1).

The learning environment has been designed to make advisors’ cognitive models as explicit and transferable as possible. This is achieved through (a) housing the advice in functional units, like the Planner and Inventor; (b) presenting advice in labeled categories, such as Goals, Plans, Strategies, and Motives; (c) providing advice in a generic, domain-independent form alongside several examples set in different domains; and (d) encouraging users to reflect on the quality and utility of the inquiry products and processes that result from using these models.

Managing and improving one’s inquiry processes depends on students’ having full knowledge of the cognitive, social, and metacognitive capabilities that are needed for learning via inquiry. Inquiry Island has been designed to provide a structure for acquiring knowledge of these processes. To help students understand and keep track of the full system of advisors, we have adopted the social metaphor of a community of advisors living on Inquiry Island, each of whom has particular competencies and who call on one another in carrying out inquiry. Task advisors focus on organizing and accomplishing particular phases of work, and cognitive, social, and metacognitive advisors have general strategies that are useful in many situations. This personification of advisors’ roles allows students to think of the orchestration of their competencies as similar to organizing a group of experts for carrying out an inquiry task. In fact, when students carry out collaborative inquiry projects in their class, the community concept is actually more than just a metaphor; it is a way of organizing roles that students can take in managing and carrying out their group’s work. The metacognitive tasks of planning, monitoring, reflecting, and revising are activities of the group, and the social competencies become crucial in their accomplishment. There is no...

Table of contents

• Cover
• Title Page
• Copyright Page
• Table of Contents
• Computer Environments as Metacognitive Tools for Enhancing Learning
• Using Hypermedia as a Metacognitive Tool for Enhancing Student Learning? The Role of Self-Regulated Learning
• A Theoretical Framework and Approach for Fostering Metacognitive Development
• Scaffolding Deep Comprehension Strategies Through Point&Query, AutoTutor, and iSTART
• A Framework for Supporting Metacognitive Aspects of Online Inquiry Through Software-Based Scaffolding
• Toward Teachers’ Adaptive Metacognition
• Fostering the Intelligent Novice: Learning From Errors With Metacognitive Tutoring
• Can Computer-Based Learning Environments (CBLEs) Be Used as Self-Regulatory Tools to Enhance Learning?
• List of Reviewers for Volume 40, Number 4
• Author Index to Volume 40
• Instructions to Authors