Self-Regulated Learning
during Non-Linear Self-Instruction

 

Deborah Alpert Sleight
Educational Psychology
Michigan State University
sleightd@msu.edu

November 1997


Table of Contents

 

Introduction

Self-Instruction

The Advantages and Disadvantages of Self-Instruction
Non-Linear Self-Instruction

Self-Regulation of Learning

The Components of Self-Regulation
Problems Regulating Learning during Non-Linear Self-Instruction

Selecting Links
Structuring Knowledge
Orientation

Electronic Performance Support Tools

How EPSS Might Facilitate Regulation of Learning during Non-Linear Instruction

References


INTRODUCTION

The cost of training in business and industry is rising at the same time the need for it is increasing. These increases in both cost and need are caused by the rapid growth in the amount of information the worker is expected to use on the job, by the rapid turnover of employees, and by the quickening pace of production.

Often self-instruction can lower the cost of training, because it allows the worker to take the training at the worksite rather than traveling a distance, an instructor need not be paid to teach each course, and any revisions to the instruction can be made immediately available. For these reasons, the use of self-instruction for training purposes is increasing. Much of this self-instruction is being designed as non-linear to take advantage of the the expanding technical capabilities of the World Wide Web and corporate intranets.

A common assumption is that learners will have little problem using non-linear self-instruction, however, one potential problem is that learners must regulate their own learning; there is no teacher to help them. This regulation of learning is made more difficult when the training material is used in a non-linear manner. Because of this non-linearity, the organization of the content may not be clear, yet learners must learn its structure in order to understand and remember it, according to information processing theory (Miller, 1993). In linear instruction the learner can look to the linear order to see the structure, but this order may be obscured in non-linear hypermedia. Thus, learning may be more difficult from non-linear instruction.

Some people are able to learn the structure of non-linear self-instruction without help, while others need help with this task. This help could be provided by electronic performance support systems, although little research has been done to identify appropriate performance support tools for this purpose, and the factors that make certain tools appropriate.

One major area of research in educational psychology is how people regulate their learning, particularly how they create structural knowledge. Much research has been done on regulation and structural knowledge during academic classroom learning and linear self-study, but little has been done on the regulation of learning and creation of structural knowledge during non-linear self-instruction in business and industry, and even less on performance support tools for regulation.

This paper describes how people regulate their learning to create structural knowledge of non-linear self-instructional content, and what performance support tools might be useful in aiding deficits in creating structural knowledge.


SELF-INSTRUCTION

The Advantages and Disadvantages of Self-Instruction

Self-instruction is more efficient than classroom instruction in terms of development and teaching time. Once a self-instructional course is developed, only minimal time needs to be spent on it to maintain it. Instructors may spend some time coaching or mentoring learners taking the self-instruction, but even then they have more time to spend on other training projects.

One of the benefits of self-instruction is the capability of providing learners some control over the instruction. The type of learner control can range from simply controlling the pace of the instruction to letting learners set their own learning goals and find their own instructional materials. In computer-based training (CBT) learner control has often meant letting learners control only the pace of instruction. In hypermedia-based instruction it often means letting learners not only set their own pace of instruction, but also decide what part of the instruction to take, and in what sequence. Self-instruction that permits learners to control the sequence of instruction is called non-linear instruction.

A disadvantage of self-instruction is the lack of an instructor to facilitate learning and the lack of other students with whom to share ideas. Self-instruction by its nature requires more from a learner than teacher-led instruction, since the learner must motivate him- or herself to begin and continue the instruction, let alone makes sense of it.

Another disadvantage is that the instruction is often static, that is, it does not adapt to the learner's progress. Research is being done on intelligent tutors that can adapt the instruction to the learner's needs, but currently this is not easily done.

The linearity of self-instruction may range in degree from linear to non-linear. In linear self-instruction the designer or teacher organizes the instructional materials in a certain way, such as hierarchically, chronologically, categorically, etc., and the learner must follow that organization. Learner control might mean controlling the pace of instruction, or deciding to repeat or skip some instruction, but it does not mean controlling the sequence of instruction; in linear self-instruction, learners may not change the structure of the instructional materials.

Non-Linear Self-Instruction

In non-linear self-instruction the topics may or may not be organized in a linear nature, but the learners "decide which topics they will view, in what order they will view the topics, how the topics are related, how long they will spend on each topic, etc." (Sweany, et al., 1996). Their control of the order in which they take the instruction may make it difficult for learners to see how the topics are related to one another. Thus, non-linear instruction requires more regulation, more self-direction from learners than classroom-based instruction, where a teacher is present to answer questions, guide the learners, and help them organize the knowledge. According to Winne (1995), "...solitary study lacks the dynamically responsive scaffolding and guidance that can be made available when learning proceeds in the context of social interaction...or intelligently interactive media..." (p. 186).

There appear to be two variables that determine the degree of linearity of instruction: its design and its use. Design linearity has to do with how the instructional topics are related, and how necessary the concepts presented earlier in the instruction are for understanding the concepts presented later. Instruction may be designed as linear, in which its organization is part of the instruction, meant to illustrate how the concepts being taught are related. An example of self-instruction designed linearly is a textbook where understanding of the content depends on concepts presented earlier in the book.

Instruction may also be designed in a non-linear fashion, where the concepts presented are discrete from one another, that is, they may be understood without first learning prerequisite concepts. An example of self-instruction designed non-linearly is a dictionary, in which each word defined is a discrete topic that does not depend on previous words defined in the dictionary in order to be understood. Although the information is organized--in the case of the dictionary, alphabetically--earlier words are not prerequisite to later words.

Use linearity has to do with the type of control the instruction provides to the learners, either the capability of moving only in a linear fashion from first topic to last, or the capability of moving in a non-linear fashion to different parts of the instruction, without first passing through earlier parts. Use linearity is based on how a self-instructional program may be used, not how it is used. Learners without control over sequence may only proceed linearly through the instruction, but even learners who do have control over sequence may decide to go through the instruction linearly. Messing (1990) found that learners tend to use a linear path when exercising control in non-linear instruction, although learners with some experience in using word processing or hypermedia programs are more likely to make use of the non-linear nature of the instruction (Reed and Giessler, 1995).

Use does not necessarily depend on design. If the instruction does not give learners control over sequence, then use is linear, without regard for how the instruction is designed. If the instruction does give learners control over sequence, then use may be linear or non-linear, again without regard for how the instruction is designed. In fact, any instruction that may be used non-linearly is called non-linear, no matter how it is designed. Thus, design and use are not necessarily related, although ideally they should be. If the instruction has prerequisites, it should either force linear use, or must present the prerequisites some other way. Conversely, if the topics are discrete, then non-linear use should be enabled to allow learners to look at topics of interest to them.

Because of the popularity of hypermedia and the World Wide Web, and the popularity of constructivist learning theories, in which learner control is important, instruction designed in a linear fashion is often presented in a non-linear fashion, simply to provide learner control of sequence, even if that type of control does not help learners learn.

Some linearity is forced by the medium of delivery. Linear media such as audio or video tapes force learners to start at the beginning of the tape and move through the tape linearly, even though they may fast forward through the tape and so not go through earlier parts of the instruction. Media that allow both linear and non-linear access, such as laser discs, books, and hypermedia programs, are called random access, a synonym for non-linear.

SELF-REGULATION OF LEARNING

The Components of Self-Regulation

Self-regulation of learning means monitoring and controlling one's own learning. Regulation appears to have multiple components, such as motivation, the learner's epistemic beliefs, metacognition, learning strategies, and prior knowledge. Motivation helps the learner put forth the effort required to monitor and control learning. Epistemic beliefs are what the learner believes about the nature of learning. Metacognition is thinking about thinking, "the capability to understand what needs to be done in a given circumstance" (Reed and Giessler, 1995, p. 582). Metacognition aids regulation by, for example, providing the learner with the knowledge of what learning strategies should be employed.

Learning strategies are "mental activities that people use when they study to help themselves acquire, organize, or remember incoming knowledge more efficiently" (Park, 1995, quoted in Williams, 1996). A categorization of learning strategies suggested by Weinstein and MacDonald (1986) includes:

Prior knowledge of the subject matter or the learning environment can help learners regulate by providing a ready scaffold for new knowledge, or by making the learning environment easier to use so it doesn't displace the subject matter as the object of study (Reed and Giessler, 1995). It can also help learners create a mental model of the organization of the instructional content by providing an example of organization.

Problems Regulating Learning during Non-Linear Self-Instruction

Constructivist and adult learning theories suggest that having control over instruction promotes learning (Miller, 1993), but according to Cho (1995):

Selecting Links

The problem of what to study and in what sequence is unique to non-linear self-instruction because there is no teacher available to give advice; it is the learner's responsibility to decide selection and sequence. In essence, learners need to have a teacher's knowledge of the instructional material in order to select and sequence properly. Since there is no teacher in self-instruction, this sequencing knowledge should be provided with the instruction.

Santiago and Okey (1992) studied this topic. They provided learners with computerized advice on the amount and sequence of instruction they needed based on their current performance in a computer-based instruction program. This advisement resulted in learners studying more and achieving higher test results than learners who were advised only on how much more instruction they needed, not on the sequence.

Also important to learners being able to decide what to study and in what order is learners' feelings about locus of control (LOC), i.e., feelings of being or not being in control of outcomes of situations. Learners who feel they have some control over their learning (internal LOC) are probably more likely to make an effort to make good decisions about selection and sequence, whereas those who feel they have little or no control (external LOC) may give up or expend little effort in making decisions. In Santiago and Okey's (1992) study, students who felt they had some control over the outcome of a situation achieved higher post-test scores than learners who felt that outcomes were beyond their control; this held true no matter what type of advisement the learners received. The researchers found that internal LOC learners were more ready to learn than external LOC learners, and were more efficient processors of information.

Structuring Knowledge

The second problem identified by Cho was the inability of learners to monitor their own learning from non-linear instruction because of a lack of appropriate metacognitive ability. This assessment ability involves being able to determine the organization of the instruction in order to build a schemata of the new knowledge, and to recognize when it is coherent (Anderson, R.; Pichert, J. & Shirey, L., 1983). Although this ability is necessary for both linear and non-linear instruction, it may be more difficult in non-linear instruction, because learners may have to determine the organization of the instruction themselves.

The knowledge structure of a domain, such as the content of an instructional course, is determined by how its ideas, concepts, rules, and terms are related. A domain's knowledge structure is defined by the written documents in the domain, such as textbooks, articles, and manuals, and by the mental structures of the domain held by domain experts (Goldsmith and Kraiger, 1997). Individuals' knowledge structures are called cognitive structures. "From this perspective, education and training can be viewed as the process of acquiring a cognitive structure that matches the domain's knowledge structure" (Shavelson, in Goldsmith and Kraiger, 1997, p. 76).

Some learners are better able to determine a domain's structure than others. In a study by Liu and Reed (1994), learners with a field-independent (FI) learning style seem to have less difficulty understanding the structure intended by the designer of the instruction than those with a field-dependent (FD) style. Field-dependent (FD) learners approach a problem in a global and spectator way, whereas field-independent (FI) learners are more involved and focused, and can identify relevant from irrelevant information.

Epistemic beliefs (beliefs about learning) are also important in how successful regulation in non-linear instruction is. Jacobson and Spiro (1994) studied the learning of complex subject matter in hypermedia learning environments, and found that students with simplistic epistemic beliefs prefer direct and structured learning material, and were unable to transfer the new knowledge of the non-linear complex subject matter to novel situations. Students with epistemic beliefs which are characterized by "an appreciation of complexity, flexibility and nonlinearity," however, were able to make flexible interpretations of the material, and could transfer their knowledge to novel situations. It may be possible to change learners' epistemic beliefs through instruction, but it may also be necessary to accommodate both simplistic and complex beliefs in the design of the instruction and in the provision of support tools.

Orientation

McCombs notes that many students have problems adjusting to a non-linear environment because they don't know or use the strategies that would help them succeed (1988). These problems may be alleviated by training learners to use strategies specific to non-linear instruction, such as selecting the sequence of instruction, organizing their knowledge, and navigating within the courseware to avoid disorientation (Greiner & Karoly, 1976, in Sweany et al., 1996).

Summary

In summary, three tasks learners must accomplish during non-linear instruction are: 1) selecting the sequence of instruction, 2) structuring their knowledge, and 3) navigating within the courseware. Those who achieve the most from non-linear instruction:


ELECTRONIC PERFORMANCE SUPPORT TOOLS

The components of regulation might usefully be supported by computerized tools called electronic performance support systems (EPSS). An EPSS is, according to Gloria Gery (1989), "an integrated electronic environment that is available to and easily accessible by each employee and is structured to provide immediate, individualized on-line access to the full range of information, software, guidance, advice and assistance, data, images, tools, and assessment and monitoring systems to permit job performance with minimal support and intervention by others" (p. 21). An EPSS might be used to show procedures and processes for doing a task, to help people find desired information in databases, or to present alternate forms of knowledge representation (such as video, audio, text, and graphics).

EPSSs display most of the following characteristics:

This last characteristic is important. It tells us that EPSSs are useful only for tasks which do not need extensive prior training or practice, such as filling out a form, as opposed to surgery, which needs a great deal of prior training and practice. EPSSs allow people to successfully perform such tasks who do not already know how to do the tasks. Thus, people who do not know how to regulate their learning may be helped to do so through appropriate online support tools.

How EPSS Might Facilitate Regulation of Learning during Non-Linear Instruction

Regulation of learning is a task like any other, and its performance may be improved with the proper knowledge and tools. Thus, performance support tools should help learners improve their regulation skills. Winne concludes from his and other research that regulated learning is a combination of beliefs, knowledge and learned skills, and that, because regulation skills are formed incrementally during instruction, they may be changed by the learning environment (Winne, 1995). If this is true, then providing tools during instruction to support the regulation of learning should improve the learner's skill in regulating learning.

Support tools that help learners select information, navigate in the courseware, and structure their knowledge should help learners regulate their learning. The support tools described by Kinzie and Berdel (1990) that proved useful in non-linear learning were a notepad, a glossary, a system map, and concept maps. The notepad allows learners to take notes to mentally structure their knowledge, the system map should help learners both sequence the instruction and navigate within the courseware, and the glossary and diagrams should help learners relate new knowledge to prior knowledge.

Eklund (1995) suggests using advanced navigational devices such as concept maps, providing on-line help, and offering adaptive advice that would suggest a path through the instruction. Sweany et al. (1996) felt that training students to use learning strategies correctly in hypermedia instruction should improve achievement. To this end, the researchers provided the learners with online tools (notepad, concept map, and bookmarking ability) to help them regulate their learning, but the sample size was too small to find any relationship between tool use and achievement.

Learning styles should be taken into account when deciding which support tools to provide. Liu and Reed (1994) found that hypermedia foreign language instruction designed to provide both holistic and componential representations and support tools enabled learners with field-dependent and field-independent learning styles to achieve equally well on the vocabulary test. Field-dependent learners (who take a more global and spectator view) tended to use tools that gave them a more holistic look at the instruction, such as video clips showing the language used in context. Field-independent learners (more analytical and able to pick out relevant from irrelevant information) tended to use tools that dealt with components of language, such as an index.

According to Bar-Tal and Bar Zohar (as quoted in Santiago and Okey, 1992, p. 48), learners with internal LOC seek ways to manipulate their environment, and that in order to do this, they must be able to collect and use relevant information. Performance support tools that provide this relevant information may help learners with internal LOC regulate their learning from non-linear instruction. Learners with external LOC may be helped by structuring the learning and providing sequence and selection advisement.

To summarize, learners who are successful in learning from non-linear instruction:

Research has indicated that the performance support tools that may be effective in improving regulation of learning from non-linear environments:

These performance support tools are listed in Table 1 below.

Non-Linear Regulation Tasks
Sequencing Instruction
Navigating through the Courseware
Structuring Knowledge
Performance Support Tools
- system map
- adaptive advice
- system map
- concept map
- online help
- notepad
- concept map
- bookmarking capability

Table 1: Online Tools to Support Non-Linear Regulation Tasks

 

THEORETICAL FRAMEWORK

Humans, like computers, manipulate symbols or information to create something new. This manipulation can take the form of filtering, analyzing, recognizing, transforming, and searching. Information Processing researchers study the flow of information through the human cognitive system that manipulates the symbols. This cognitive system uses control processes for organizing information, encoding information for storage in long term memory, rehearsal of knowledge stored in long term memory, strategies used for retrieving knowledge from long term memory, and monitoring one's level of understanding. A person's control processes regulate the flow of information throughout his or her information processing system, determine the learner's strategies for generalizing and problem solving, and influence the quality of the learner's thought. Self-regulation of learning, then, is one of the control processes of the human cognitive system.

Learning involves meaningfully encoding new information in order to move it into long term memory. Information Processing Theory postulates that this meaningful encoding takes the form of creating relationships between data. Related pieces of information are organized into structures called schematas, which specify a pattern or sequence of steps associated with a certain event, concept or skill. Information thus encoded becomes knowledge, and is easier to retrieve from long term memory than unrelated data. As new information is learned, it is linked to prior knowledge in schematas, or is the beginning of a new schemata.

Thus, a particularly important factor that influences learning, according to Information Processing Theory, is how one organizes the knowledge learned, because this organization predicts how well one has learned, i.e., how easily one can retrieve knowledge from long term memory. Retrieval is easier if:


REFERENCES

American Psychological Association (1995). Current issues in research on self-regulated learning: A discussion with commentaries. Educational Psychologist, Special Issue, 30(4).

Ayersman, D.J. (1993). An overview of the research on learning styles and hypermedia environments. Paper presented at the Annual Convention of the Eastern Educational Research Association, September 16, 1993.

Beasely, R. & Waugh, M. (1996). The effects of content-structure focusing on learner structural knowledge acquisition, retention, and disorientation in a hypermedia environment. Journal of Research on Computing in Education, 28(3).

Bloomenfeld, P.; Soloway, E.; Marx, R.; Krajcik, J.; Guzdial, M. & Palinczar, A. (1991). Motivating project-based learning: Sustaining the doing, supporting the learning. Educational Psychologist, 26, 369-398.

Brown, M.; Doughty, G.; Draper, S.; Henderson, F. & McAteer, E. (1996). Measuring learning resource use. Computers in Education, 27(2), 103-113.

Cho, Y. (1995). The nature of learner's cognitive processes in learner- and program-controlled hypertext learning environments. Unpublished doctoral dissertation, University of Texas at Austin.

Cohen, E. (1994). Restructuring the classroom: Conditions for productive small groups. Review of Educational Research, 64, 1-35.

Corno, L. & Mandinach, E.B. (1983). The role of cognitive engagement in classroom learning and motivation. Educational Psychologist, 18, 88-108.

Duchastel, p. (1992). Towards methodologies for buildng knowledge-based instructional systems. Instructional Science, 20(5-6), 349-58.

Eklund, J. (1995). Cognitive models for structuring hypermedia and implications for learning from the world-wide web. http://www.scu.edu.au/ausweb95/papers /hypertext/eklund/.

Gay, G, (1986). Interaction of learner control and prior understanding in computer-assisted video instruction. Journal of Educational Psychology, 78(3), 225-227.

Gay, G., Trumbull, D., & Mazur, J. (1991). Designing and testing navigational strategies and guidance tools for a hypermedia program. Journal of Educational Computing Research, 7(2), 189-202.

Gery, G. (1989). The quest for electronic performance support, CBT Directions.

Gery, G. (1991). Electronic Performance Support Systems: How and Why to Remake the Workplace through the Strategic Application of Technology. Boston, MA: Weingarten Publications.

Goldsmith, T. & Kraiger, K. (1997). Structural knowledge assessment and training evaluation. In J. K. Ford, S. Kozlowski, K. Kraiger, E. Salas. and M. Teachout (Eds.), Improving Training Effectiveness in Work Organizations (pp. 73-98). Mahwah, NJ: Lawrence Erlbaum Associates.

Greiner, J.M. & Karoly, P. (1976). Effects of self-control training on study activity and academic performance: An analysis of self-monitoring, self-reward, and systematic-planning components. Journal of Counseling Psychology, 23, 495-502.

Hannefin, M.J. (1984). Guidelines for using locus of instructional control in the design of computer-assisted instruction. Journal of Instructional Development, 7(3), 6-10.

Heller, R.S. (1990, Summer). The role of hypermedia in education: A look at the research issues. Journal of Research on Computing in Education, 431-441.

Jacobson, M.J. & Spiro, R.J. (1994). Learning and applying difficult science knowledge: Research into the application of hypermedia learning environments. http://

Jih, H.J. (1991). The relationship among the structure of interfaces, users' mental models, and performance in computer-based insteractive courseware. Unpublished doctoral dissertation, Athens, GA: University of Georgia.

Jonassen, D. (1992). Designing hypertext for learning. In E. Scanlon and T. O'Shea (Eds.), New Directions in Educational Technology. Berlin: Springer-Verlag.

Kinzie, M.B. & Berdel, R.L. (1990). Design and use of hypermedia systems. Educational Technology Research and Development, 38(3), 61-68.

Knussen, C. et al, (1991). An approach to the evaluation of hypermedia. Computers and Education, 17(1), 13-24.

Liu, M. & Reed, M. (1994). The relationship between the learning strategies and learning styles in a hypermedia environment. Computers in Human Behavior, 10, 419-434.

Mayer, R.E. (1988). Learning strategies: An overview. In C.E. Weinstein, E.T. Goetz, and P.A. Alexander (Eds)., Learning and Study Strategies: Issues in Assessment, Instruction, and Evaluation (pp. 141-165). San Diego: Academic Press.

McCombs, B.L. (1988). Motivational skills training: Combining metacognitive, cognitive, and affective learning strategies. In C.E. Weinstein, E.T. Goetz, and P.A. Alexander (Eds.), Learning and Study Strategies: Issues in Assessment, Instruction, and Evaluation (pp. 141-165). San Diego: Academic Press.

McManus, T. Testing learner regulation in a web-based learning environment. URL: http:// www.edb.utexas.edu /coe/depts/ci/it/multimedia/students/McManus/srltext.html.

Messing, J. (1990). The use of content and teaching strategy control features in computer-assisted learning courseware. Charles Sturt University. Riverina. (ERIC document ED 59246).

Miller, P. (1993). Theories of Developmental Psychology, Third Edition. New York: W.H. Freeman & Co.

Misanchuk, E. & Schwier, R. (1992). Representing interactive multimedia and hypermedia audit trails. Journal of Educational Multimedia and Hypermedia, 11(3), 355-72.

Oltman, P.; Raskin, E. & Witkin, H. (1971). Group embedded figures tests. Palo Alto, CA: Consulting Psychologists Press.

Park, S. (1995). Implications of learning strategy research for designing computer-assisted instruction. Journal of Research on Computing in Education, 41(3), 63-85.

Pintrich, P.R. & Garcia, T. (1991). Student goal orientation and regulation in the college classroom. In M.L. Maehr and P.R. Pintrich (Eds.), Advances in Motivation and Achievement: Goals and Self-regulatory Processes, 7, 371-402.

Reed, W.M. & Giessler, S.F. (1995). Prior computer-related experiences and hypermedia metacognition. . Computers in Human Behavior, 11(3-4), 581-600.

Santiago, R. & Okey, J. (1992). The effects of advisement and locus of control on achievement in learner-controlled instruction. Journal of Computer-Based Instruction, 119(2), 47-53.

Spiro, R.J., Coulson, R.L., Feltovich, P.J., & Anderson, D.K. (1991). Cognitive flexibility, constructivism, and hypertext: Random access instruction for advanced knowledge acquisition in ill-structured domains. Educational Technology, 31(5), 24-34.

Sweany, N., McManus, T., Williams, D., & Tothero, K. (1996). The use of cognitive and metacognitive strategies in a hypermedia environment. Paper presented at EdMedia, Boston, MA, June, 1996.

Verheij, J.; Stoutjesdijk, E. & Beishuizen, J. (1996). Search and study strategies in hypertext. Computers in Human Behavior, 12(1), 1-15.

Weinstein, C.E. & McDonald, J.D. (1986). Why does a school psychologist need to know about learning strategies? Journal of School Psychology, 24, 257-265.

Weller, H.; Repman, J.; Lan, W. & Rooze, G. (1995). Improving the effectiveness of learning through hypermedia-based instruction: The importance of learner characteristics. Computers in Human Behavior, 11(3-4), 451-465.

Williams, D.C. (1996). The relationship between the availability of cognitive tools and achievement in a hypermedia environment. http://www.edb.utexas.edu/coe/depts/ ci/it/multimedia/students/Williams/.

Winne, P. (1992). State-of-the-art instructional computing systems that afford instruction and bootstrap research. In M. Jones & P.H. Winne (Eds.), Foundations and Frontiers of Adaptive Learning Environments (pp. 349-380). Berlin: Springer-Verlag.

Winne, P. (1995). Inherent details in self-regulated learning. Educational Psychologist, special issue, 30(4), 173-188.

Zimmerman, B.J. (1994). Dimensions of academic regulation: A conceptual framework for education. In D.H. Schunk & B.J. Zimmerman (Eds.), Self-Regulation of Learning and Performance: Issues and Educational Implications (pp. 3-21). Hillsdale, NJ: Erlbaum.


(c) Deborah Alpert Sleight, 1997
Permission is given to reprint for non-profit use providing credit is given.

Deborah Alpert Sleight
Educational Psychology
Michigan State University
East Lansing, MI 48824
sleightd@msu.edu

Return