Computer Environments as Metacognitive Tools for Enhancing Learning

Download Computer Environments as Metacognitive Tools for Enhancing Learning

Post on 14-Feb-2017

214 views

Category:

Documents

1 download

Embed Size (px)

TRANSCRIPT

<ul><li><p>This article was downloaded by: [Duke University Libraries]On: 05 October 2014, At: 03:40Publisher: RoutledgeInforma Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House,37-41 Mortimer Street, London W1T 3JH, UK</p><p>Educational PsychologistPublication details, including instructions for authors and subscription information:http://www.tandfonline.com/loi/hedp20</p><p>Computer Environments as Metacognitive Tools forEnhancing LearningRoger AzevedoPublished online: 08 Jun 2010.</p><p>To cite this article: Roger Azevedo (2005) Computer Environments as Metacognitive Tools for Enhancing Learning, EducationalPsychologist, 40:4, 193-197, DOI: 10.1207/s15326985ep4004_1</p><p>To link to this article: http://dx.doi.org/10.1207/s15326985ep4004_1</p><p>PLEASE SCROLL DOWN FOR ARTICLE</p><p>Taylor &amp; Francis makes every effort to ensure the accuracy of all the information (the Content) containedin the publications on our platform. However, Taylor &amp; Francis, our agents, and our licensors make norepresentations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of theContent. Any opinions and views expressed in this publication are the opinions and views of the authors, andare not the views of or endorsed by Taylor &amp; Francis. The accuracy of the Content should not be relied upon andshould be independently verified with primary sources of information. Taylor and Francis shall not be liable forany losses, actions, claims, proceedings, demands, costs, expenses, damages, and other liabilities whatsoeveror howsoever caused arising directly or indirectly in connection with, in relation to or arising out of the use ofthe Content.</p><p>This article may be used for research, teaching, and private study purposes. Any substantial or systematicreproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in anyform to anyone is expressly forbidden. Terms &amp; Conditions of access and use can be found at http://www.tandfonline.com/page/terms-and-conditions</p><p>http://www.tandfonline.com/loi/hedp20http://www.tandfonline.com/action/showCitFormats?doi=10.1207/s15326985ep4004_1http://dx.doi.org/10.1207/s15326985ep4004_1http://www.tandfonline.com/page/terms-and-conditionshttp://www.tandfonline.com/page/terms-and-conditions</p></li><li><p>AZEVEDOINTRODUCTION</p><p>Computer Environments as Metacognitive Tools forEnhancing Learning</p><p>Roger Azevedo</p><p>Department of Human Development</p><p>University of Maryland, College Park</p><p>Thearticlesappearing in this special issueof EducationalPsy-</p><p>chologist reflect a growing interest by researchers from vari-</p><p>ous fields in examining the use of computers as metacognitive</p><p>tools for enhancing learning. This topic has become increas-</p><p>ingly important as computer-based learning environments be-</p><p>comeubiquitousandstudentsuse them extensivelyboth inand</p><p>out of school to learn about conceptually rich domains. It is ar-</p><p>gued that the effectiveness of these environments will only be</p><p>achieved if learners regulate their learningthat is, if they de-</p><p>ploy the metacognitive and self-regulatory processes neces-</p><p>sary to effectively learn about the relevant topics. Using com-</p><p>puter environments to learn about conceptually rich domains</p><p>involves a set of complex interactions between cognitive, mo-</p><p>tivational, affective, and social processes (Anderson &amp;</p><p>Labiere, 1998; Collins, Brown, &amp; Newman, 1989; Derry &amp;</p><p>Lajoie, 1993; Jonassen &amp; Land, 2000; Jonassen &amp; Reeves,</p><p>1996; Lajoie, 2000; Pea, 1985; Shute &amp; Psotka, 1996; Solo-</p><p>mon, Perkins, &amp; Globerson, 1991; Wenger, 1987). Current re-</p><p>search on learning with computer environments from the</p><p>fields of cognitive science, learning sciences, psychology, ed-</p><p>ucation, and artificial intelligence (AI) in education provides</p><p>evidence that learners of all ages experience certain difficul-</p><p>ties when learning about conceptually rich domains such as</p><p>science, math, and social studies. This research indicates that</p><p>learning about these domains with computer environments is</p><p>particularlydifficultbecause it requiresstudents toanalyze the</p><p>learning situation, set meaningful learning goals, determine</p><p>which strategies to use, assess whether the strategies are effec-</p><p>tive in meeting the learning goals, and evaluate their emerging</p><p>understanding of the topic. Learners also need to deploy sev-</p><p>eral metacognitive processes to determine whether they un-</p><p>derstand what they are learning and to modify their plans,</p><p>goals, strategies, and effort as necessary, all in response to</p><p>changing contextual conditions (e.g., their cognitive states,</p><p>motivational level, and social support). Further, depending on</p><p>the learning situation, they may need to reflect on their learn-</p><p>ing and modify aspects of the learning context.</p><p>Researchers have previously used cognitive theories (e.g.,</p><p>Anderson &amp; Labiere, 1998) or constructivist models of learn-</p><p>ing and instruction (e.g., Collins et al., 1989; Cognition and</p><p>Technology Group at Vanderbilt [CTGV], 1990; Greeno,</p><p>1998; Resnick, 1991; Rogoff, 1997) to explain different as-</p><p>pects of learning with computer environments. However, due</p><p>to the complexity in learning about conceptually rich domains</p><p>with computer environments, several researchers have re-</p><p>cently extended these theories and models by advancing mod-</p><p>els of metacognition (Bandura, 1986; Brown, 1975, 1987;</p><p>Flavell, 1979, 1985; Hacker, 1998; Hacker, Dunlosky, &amp;</p><p>Graesser, 1998; Schraw &amp; Moshman, 1995) and self-regu-</p><p>lated learning (SRL; Butler &amp; Winne, 1995; Corno &amp;</p><p>Mandinach, 1985; McCaslin &amp; Hickey, 20001; Paris, Byrnes,</p><p>&amp; Paris, 2001; Pintrich, 2000; Schunk, 2001; Winne, 2001;</p><p>Zimmerman, 1986, 2000, 2001) to describe the complex inter-</p><p>action of mediating cognitive, metacognitive, and social pro-</p><p>cesses involved instudentslearningofcomplex topicsanddo-</p><p>mains. These new models have been advanced to account for</p><p>the various phases (e.g., planning, metacognitive monitoring,</p><p>strategy use, and reflection) and areas (e.g., cognitive, af-</p><p>fect/motivation, behavior, and context) of SRL. Although</p><p>there is a wealth of research in various areas of academic</p><p>achievement (for recent reviews see Boekaerts, Pintrich, &amp;</p><p>Zeidner, 2000; Zimmerman &amp; Schunk, 2001), these frame-</p><p>worksare in their infancyin termsof their explanatoryandpre-</p><p>dictive adequacy for using computers as metacognitive tools</p><p>for enhancing learning. Therefore, much more research is</p><p>needed on the conceptual, theoretical, empirical, and design</p><p>issues related tousingcomputersasmetacognitive tools to fos-</p><p>ter learning about conceptually rich domains.</p><p>COMPUTER ENVIRONMENTS ASMETACOGNITIVE TOOLS</p><p>I broadly define a computer environment as a</p><p>metacognitive learning tool as one that is designed for in-</p><p>EDUCATIONAL PSYCHOLOGIST, 40(4), 193197</p><p>Copyright 2005, Lawrence Erlbaum Associates, Inc.</p><p>Correspondence should be addressed to Roger Azevedo, Department of</p><p>Human Development, University of Maryland, 3304 Benjamin Building,</p><p>College Park, MD 20742. E-mail: razevedo@umd.edu</p><p>Dow</p><p>nloa</p><p>ded </p><p>by [</p><p>Duk</p><p>e U</p><p>nive</p><p>rsity</p><p> Lib</p><p>rari</p><p>es] </p><p>at 0</p><p>3:40</p><p> 05 </p><p>Oct</p><p>ober</p><p> 201</p><p>4 </p></li><li><p>structional purposes and uses technology to support the</p><p>learner in achieving the goals of instruction. This may in-</p><p>clude any type of technology-based tool, such as an intelli-</p><p>gent tutoring system, an interactive learning environment,</p><p>hypermedia, multimedia, a simulation, microworld, collab-</p><p>orative learning environment, and so on. The characteristics</p><p>explicitly stated by Lajoie (1993, p. 261) and several others</p><p>(see Derry &amp; Lajoie, 1993; Jonassen &amp; Reeves, 1996;</p><p>Lajoie, 1993, 2000; Lajoie &amp; Azevedo, in press; Pea, 1985;</p><p>Perkins, 1985) serve as the foundational basis for the meta-</p><p>phor of computers as metacognitive tools(a) assist learn-</p><p>ers to accomplish cognitive tasks by supporting cognitive</p><p>processes, (b) share the cognitive load by supporting lower</p><p>level cognitive skills so that learners may focus on higher</p><p>level thinking skills, (c) allow learners to engage in cogni-</p><p>tive activities that would be out of their reach otherwise be-</p><p>cause there may be no opportunities for participating in</p><p>such tasks (e.g., electronic troubleshooting, medical diag-</p><p>nosis; see Lajoie &amp; Azevedo, in press), and (d) allow learn-</p><p>ers to generate and test hypotheses in the context of prob-</p><p>lem solving.</p><p>As such, a metacognitive tool is any computer environ-</p><p>ment that, in addition to adhering to Lajoies (1993)</p><p>characteristics of cognitive tool, also has the following addi-</p><p>tional characteristics:</p><p>1. It requires students to make instructional decisions re-</p><p>garding instructional goals (e.g., such as setting learning</p><p>goals; sequencing instruction; seeking, collecting, organiz-</p><p>ing, and coordinating instructional resources; deciding</p><p>which embedded and contextual tools to use and when to use</p><p>them to support their learning goals; deciding which repre-</p><p>sentations of information to use, attend to, and perhaps mod-</p><p>ify to meet instructional goals).</p><p>2. It is embedded in a particular learning context that may</p><p>require students to make decisions regarding the context in</p><p>ways that support successful learning (e.g., how much sup-</p><p>port is needed from contextual resources, what types of con-</p><p>textual resources may facilitate learning, locating contextual</p><p>resources, when to seek contextual resources, determining</p><p>the utility and value of contextual resources).</p><p>3. It is any computer-based environment that (to some de-</p><p>gree) models, prompts, and supports a learners self-regula-</p><p>tory processes, which may include cognitive (e.g., activating</p><p>prior knowledge, planning, creating subgoals, learning strat-</p><p>egies), metacognitive (e.g., feeling of knowing, judgment of</p><p>learning, evaluate emerging understanding), motivational</p><p>(e.g., self-efficacy, task value, interest, effort), or behavioral</p><p>(e.g., engaging in help-seeking behavior, modifying learning</p><p>conditions; handling task difficulties and demands)</p><p>processes.</p><p>4. It is any environment that (to some degree) models,</p><p>prompts, and supports learners to engage or participate</p><p>(alone, with a peer, or with a group) in using task-, domain-,</p><p>or activity-specific learning skills (e.g., skills necessary to</p><p>engage in online inquiry and collaborative inquiry), which</p><p>also are necessary for successful learning.</p><p>5. It is any environment that resides in a specific learning</p><p>context where peers, tutors, humans or artificial may play</p><p>some role in supporting students learning by serving as ex-</p><p>ternal regulating agents.</p><p>6. It is any environment where the learners use and de-</p><p>ployment of key metacognitive and self-regulatory processes</p><p>prior to, during, and following learning are critical for suc-</p><p>cessful learning.</p><p>Several researchers have recently questioned the educa-</p><p>tional potential of such computer environments because of</p><p>students failure to show learning gains. This criticism is</p><p>based on learners failure to deploy the key metacognitive</p><p>and self-regulatory skills necessary to regulate their learning</p><p>(see Azevedo, 2002; Azevedo &amp; Hadwin, in press; Clark,</p><p>2004; de Jong et al., 2005; Lajoie &amp; Azevedo, in press;</p><p>Mayer, 2003; Shapiro &amp; Neiderhauser, 2004). This new met-</p><p>aphor using computers as metacognitive tools should follow</p><p>Mayers (2003) proposal for the scientific investigation of</p><p>how people learn with environments. Our research must in-</p><p>clude three basic elementsevidence, theory, and applica-</p><p>tions. Mayers proposal renews our concern about the lack of</p><p>theoretical and empirical evidence necessary to advance re-</p><p>search on open-ended electronic environments such as</p><p>Web-based learning environments, hypermedia, and hyper-</p><p>text in educational psychology and other related fields. Given</p><p>the strong interest in these new technologies for teaching and</p><p>learning, there is a need to extend our current theoretical</p><p>frameworks and establish a solid research base of replicated</p><p>findings based on rigorous and appropriate research methods</p><p>(Mayer, 2003; Winn, 2003).</p><p>The goal of this special issue was to bring together cogni-</p><p>tive scientists, psychologists, and educational researchers to</p><p>both synthesize and advance our current understanding of the</p><p>role of metacognition and self-regulated learning (SRL) re-</p><p>lated to using computers as metacognitive tools for enhanc-</p><p>ing student learning (Azevedo, 2005; Graesser, McNamara,</p><p>&amp; VanLehn, 2005; Lin, Schwartz, &amp; Hatano, 2005; Mathan</p><p>&amp; Koedinger, 2005; Quintana, Zhang, &amp; Krajcik, 2005;</p><p>White &amp; Frederiksen, 2005). The authors in this issue have</p><p>articulated how their programs of research (and their respec-</p><p>tive theories and conceptualizations of metacognition and</p><p>SRL) can provide evidence about computers acting as</p><p>metacognitive tools for enhancing students learning. The re-</p><p>searchers contributing to this special issue were invited to</p><p>provide scholarly reviews and critical analyses of both exist-</p><p>ing research and their own research. In their programs of re-</p><p>search, they have used different frameworks, research meth-</p><p>odologies, and quantitative and qualitative methods to</p><p>address issues related to students metacognitive and SRL.</p><p>The result is a group of articles that we feel has the potential</p><p>to define the emergence of a new paradigmusing comput-</p><p>ers as metacognitive tools for enhancing student learning.</p><p>194 AZEVEDO</p><p>Dow</p><p>nloa</p><p>ded </p><p>by [</p><p>Duk</p><p>e U</p><p>nive</p><p>rsity</p><p> Lib</p><p>rari</p><p>es] </p><p>at 0</p><p>3:40</p><p> 05 </p><p>Oct</p><p>ober</p><p> 201</p><p>4 </p></li><li><p>The contributing authors were asked to explicitly address</p><p>five issues: (a) Provide an overview of the context in which</p><p>computer-based learning environments (CBLEs) are used to</p><p>study and foster studentsmetacognitive and/or SRL; (b) pro-</p><p>vide an overview of their theoreticalconceptual framework</p><p>and the underlying assumptions, and an explanation of how</p><p>the particular theory/model addresses students</p><p>metacognitive processes and SRL (e.g., which specific</p><p>phases and areas are being targeted); (c) review and summa-</p><p>rize the findings from their own studies using quantitative,</p><p>qualitative, and mixed methods as they related to how CBLEs</p><p>have been used to study and foster/develop students</p><p>metacognitive and/or SRL; (d) describe how effective their</p><p>existing CBLEs are in detecting, tracing, and monitoring</p><p>learners metacognitive and self-regulatory behaviors during</p><p>learning; (e) discuss the implications for the design of</p><p>metacognitive tools to support learning, and which of these</p><p>components and/or aspects of metacognition and SRL can</p><p>and should be modeled and why? (f) Assess whether their ex-</p><p>isting framework can be extended into a unifying</p><p>metacognitive or SRL framework for studying the various</p><p>phases and areas of learning with CBLEs.</p><p>OVERVIEW OF ARTICLES IN THIS ISSUE</p><p>Azevedo describes the importance of self-regulation in learn-</p><p>ing about conceptually challenging science topics using</p><p>hypermedia learning environments. Based on a wealth of</p><p>contemporary research on academic achievement and SRL,</p><p>he advances SRL as a theoretical framework with which to</p><p>examine the complex and dynamic processes that mediate</p><p>the relationships between learner characteristics, the features</p><p>of hypermedia learning environments, and the learning con-</p><p>text. The article i...</p></li></ul>