|
...the two hypermedia learning tasks explore whether the goal structure of the learning task is related to the use of SRL variables. Participants were randomly assigned to one of three conditions (mastery goal structure, performance-approach goal structure, or performance-avoidance goal structure) and participated in two 20-minute learning tasks in which they used hypermedia to learn about the circulatory system in one learning task and the respiratory system in another learning task. Results indicate that a mastery goal structure and a performance-approach goal structure are related to undergraduates' use of similar proportions of SRL variables in two hypermedia learning tasks, whereas a performance-avoidance goal structure is related to undergraduate's use of different proportions of SRL variables, specifically planning, in two similar hypermedia learning tasks. Based on these results, the implications for the design of hypermedia learning environments are discussed.
**********
Computer-based learning environments (CBLEs) are becoming commonplace in the classroom (Alexander, Graham, & Harris, 1998). Recent CBLEs provide an environment in which students can pursue personal goals and solve challenging problems (Jonassen & Reeves, 1996; Lajoie, 2000; Lajoie & Azevedo, in press). Hypermedia, an example of a type of CBLE that allows students to pursue personal goals, presents information in a nonsequential and nonlinear manner which allows students to access information of their choosing (Jacobson & Archodidou, 2000; Jonassen, 1989). Though this learning environment should foster a student's participation in the construction of knowledge structures (Hartley, 1985), research has begun to question the effectiveness of these CBLEs (Williams, 1996; White & Frederriksen, in press).
Empirical research has produced mixed results on the effectiveness of such learning environments. Most of this research has compared student-controlled and program-controlled treatment conditions (Williams, 1996). Student-controlled CBLEs offer students the provision of choice in accessing information, whereas program-controlled CBLEs present information in a predetermined manner. For example, while researchers such as Morrison, Ross, and Baldwin (1992) found that program-controlled treatments were superior to student-controlled treatments with respect to the posttest achievements of 6th graders learning about mathematical concepts, other researchers such as Ellermann and Free (1990) found that student-controlled instructional contexts fostered higher levels of learning with adults learning about phonetics. These mixed results suggest that some individuals can effectively use CBLEs such as hypermedia, whereas other students have difficulty using these CBLEs to learn.
Recent research has begun to shed light on why some students have difficulty effectively using student-controlled CBLEs, such as hypermedia environments. While these environments may offer a student the opportunity to choose which information to access, the multiple navigational choices may present the student with cognitive overload and disorientation (Muller-Kaltjoff & Moller, 2003). In order to address these potential hurdles to learning with these environments, the design of hypermedia often incorporates navigational aids such as graphical overviews (Muller-Kaltjoff & Moller) and scaffolds (Brush & Saye, 2001). However, some researchers suggest the provision of support tools does not guarantee that students will effectively use them while learning with hypermedia (Clarebout, Elen, Johnson, & Shaw, 2002). In order to better account for why some students have difficulty learning with hypermedia, other researchers have focused on individual student factors that may affect learning with hypermedia.
For example, Azevedo, Guthrie, and Seibert (2004) demonstrated that students need to regulate their learning when using a hypermedia environment to effectively navigate through the multiple representations and control the sequencing of nonlinear information. Using self-regulated learning theory (SRL) as a theoretical framework to examine learning with a hypermedia environment, these researchers identified specific SRL variables that are related to learning complex and challenging science topics in a hypermedia environment. Students who regulate their learning by planning and monitoring tend to perform better than those students who do not deploy these self-regulatory processes while learning with hypermedia (Azevedo & Cromley, 2004).
Self-Regulated Learning: Theoretical Framework
To account for the complexity of learning with hypermedia, research has adopted the SRL theoretical framework (Winne, 2001; Winne & Hadwin, 1998). When using the SRL theoretical framework to examine learning with hypermedia, several theoretical and empirically-based assumptions are made (Pintrich, 2000). First, an underlying assumption is that students actively construct their own strategies, goals, and meaning from information available in their own minds as well as from the external world. Second, most SRL models assume that students can potentially regulate and monitor certain aspects of their cognition, behavior, and motivation. However, due to the influence of contextual variables, individual differences, and developmental constraints, individuals do not consistently monitor and control their cognition, behavior, and adoption of goals in all learning contexts. Third, most SRL models assume that all human behavior is goal-directed and that self-regulated students modify their behavior to achieve a desired goal. That is, individuals set goals for their learning, monitor their progress towards these goals, and then adapt and regulate their behavior, cognition, and motivation to reach those goals. Lastly, most models assume that self-regulatory behavior is a mediator between (a) an individual's performance, (b) contextual factors, and (c) personal characteristics.
Self-Regulated Learning with Hypermedia
To effectively use hypermedia environments to learn about complex topics, it may be necessary to deploy certain SRL variables (Azevedo, Winters, & Moos, 2004). Because hypermedia is structured in a nonlinear fashion, students are required to regulate their learning, including making decisions about which information to access, how much time to spend in the different representations of information, and when and how to modify strategies (Hadwin & Winne, 2001; Shapiro, 1999; Williams, 1996). Through identifying specific SRL variables that foster learning with hypermedia, recent research has begun to examine how students regulate their learning while using a hypermedia environment (Azevedo, Guthrie, & Seibert, 2004). However, it is also crucial to address why students regulate their learning.
Recent research examining how students regulate their learning while using a hypermedia environment has been primarily cognitive in nature (Azevedo & Cromley, 2004). That is, the interactions between motivational factors and the use of specific SRL variables in hypermedia environments have been largely unaddressed (Lajoie & Azevedo, in press; Lepper, Woolverton, Mumme, & Gutner 1993). However, as suggested by Lepper et al., learner characteristics such as motivational factors can distinctly affect how students regulate their learning. For example, though a student may have the capacity to engage in specific SRL activities, such as monitoring their time and effort, the student's motivation may determine if this specific SRL is used in a particular context (Lepper et al.). Thus, while it is important to understand how students regulate their learning while using a hypermedia environment (Azevedo, Guthrie, & Seibert, 2004), it is also crucial to examine students' motivation when using hypermedia because this line of research will help explain why students choose to regulate their learning with hypermedia (Corno & Mandinach, 1983, 2004).
Motivation and Hypermedia Environments
Literature examining the relationship between hypermedia and motivation suggests that students' use of hypermedia can increase their motivation toward learning (Liu & Pederson, 1998). Two theoretical camps have used different theories to explain the relationship between motivation and learning with hypermedia (Wishart, 2000). In one theoretical camp, cognitive theories suggest that hypermedia environments present intriguing intrinsic motivators (Wishart, 2000). For example, research has suggested that the most important cognitive factor in students' perception of CBLEs was their perception of control and ability to choose which information is accessed (Wishart, 1990). Studies have suggested that provision of choice, as offered in hypermedia environments, is linked to increased intrinsic motivation because this aspect of the learning context increases the self-relevance of the activity (Cordova & Lepper, 1996). In the second theoretical camp, classical behaviorist theories originating from the work of Thorndike (1898) suggest that CBLEs such as hypermedia present extrinsic rewards. In these environments, students have access to multiple forms of information, including video, audio, animation, and text (Jonassen & Reeves, 1996), and these entertaining animations and graphics can be compelling and related to increased motivation (Wishart, 2000). For example, Wishart (2000) used structured interviews and surveys to ascertain students' motivation in learning with multimedia encyclopedias on CD-ROMs. Results from these surveys and interviews suggested that the learning environment of multimedia and hypermedia, in which graphics, video, and sound are integrated, is related to high levels of student motivation.
While this line of research suggests that students' use of hypermedia is related to increased motivation towards learning, the relationship between motivation and SRL during learning with hypermedia remains largely unaddressed. To better understand students' regulation of their learning in hypermedia, it is crucial to address how (i.e., the SRL processes) and why (i.e., the motivation underlying these SRL processes) students regulate their learning. To begin to address both of these issues, findings that have examined the role of different goal structures on learning should be considered (Ames, 1992). This line of research has been previously used to examine the role of motivation in SRL, but has not extensively examined the role of motivation in SRL within the context of learning with hypermedia.
Goal Structure and Self-Regulated Learning
When considering how and why students self-regulate their learning in a hypermedia environment, it is important to address the influence of the hypermedia's goal structure. Goal structure has been defined as the expectation embedded in the design of learning activities (Ames, 1992). It has been suggested that the design of learning activities can influence the motivation underlying how a student learns (Ames). Ames suggested that there are salient structures in the learning activities and that the way in which students experience these structures can affect their learning. For example, she suggests that students' perception of structures in learning activities can influence students' willingness to apply strategies, their feelings of satisfaction, and how they approach learning. More specifically, she suggests that learning activities, which are focused on developing understanding of the activity's content are much more likely to promote learning that is distinct from environments that include an external criterion for performance.
Other researchers have also supported this assertion that different goal structures within a learning activity can affect learning. For example, Elliot and Harackiewicz (1996) advocated that an environment can have three goal structures, mastery, performance-approach, and performance-avoidance. In this goal structure framework, performance-avoidance goal structure refers to an environment that presents normative references with the underlying emphasis of avoiding failure or demonstration of incompetence (Wolters, 2004). Performance-approach goal structure refers to an environment that presents normative references with the underlying emphasis of demonstrating competence relative to others (Wolters). Mastery goal structure refers to an environment that downplays normative references and emphasizes mastering of material through increasing the level of competence and learning as much as possible (Wolters). Elliot and Harackiewicz examined how these three distinct goal structures differentially impacted the learning process by randomly assigning 54 undergraduate students to one of three conditions (mastery, performance-approach, or performance-avoidance). These students completed four problem-solving activities under one of these distinct goal structures. The results of this study suggest that the three goal structures distinctly affect learning (Elliot & Harackiewicz). Specifically, the findings suggested that a performance-avoidance goal structure undermined learning, while the performance-approach condition and mastery condition were related to increased intrinsic motivation and higher learning outcomes.
In summary, research examining learning in environments with different goal structures suggests that these contextual variables can distinctly affect why and how students learn. Generally, when a student learns in an environment with a mastery goal structure, they tend to use more effective cognitive processes, while a student learning in an environment with performance goal structures typically use more superficial processes. However, as some recent...
NOTE: All illustrations and photos
have been removed from this article.
Looking for additional articles?
Search our database of over 3 million articles.
Looking for more in-depth information on this industry?
Search our complete database of Industry & Market reports by text, subject, publication
name or publication date.
About Goliath
Whether you're looking for sales prospects, competitive information, company
analysis or best practices in managing your organization,
Goliath can help you meet your business needs.
Our extensive business information databases empower business
professionals with both the breadth and depth of credible,
authoritative information they need to support their business
goals. Whether it be strategic planning, sales prospecting,
company research or defining management best practices -
Goliath is your leading source for accurate information.
|
