CALICO Journal, 27(2)
Mei-Mei Chang
Effects of Self-Monitoring on Web-Based Language Learner’s Performance and Motivation Mei-Mei Chang National Pingtung University of Science and Technology
ABSTRACT This study examined the effect of a self-monitoring strategy on EFL online learners’ academic performance and motivational beliefs. A total of 90 college freshmen participated in the study, and instruments used in the study included two general English proficiency tests, a course-based reading comprehension test, and a modified version of the Motivated Strategies for Learning Questionnaire (MSLQ). Students were randomly assigned to a control group and an experimental group. Scores of the first general English proficiency test were used to verify students’ starting points. The students in the experimental group employed a self-monitoring strategy during the semester. At the end of the semester, a course-based comprehension test and the second general English proficiency test were administered. During the semester, data from the modified MSLQ were collected at two points in time—the third week and the sixteenth week. Data analyses revealed that adopting a self-monitoring strategy resulted in better academic performance and a generally positive pattern of motivational beliefs, including adaptive levels of control of learning beliefs and perception of task value.
KEYWORDS Self-monitoring Strategy, Motivational Beliefs, Control of Learning Beliefs, Task Value
INTRODUCTION As the use of the Internet has become an extraordinarily popular distribution channel for information, web-based language learning continues to increase (e.g. Lin & Hsu, 2002; Liou, 1997, 2001; Liou & Yang, 2002). Learning, according to Leonard (1968), takes place when learners interact with their environment. Researchers in second language acquisition (SLA) also emphasize the importance of interaction. Gass and Varonis (1994) claimed that interaction allows learners to comprehend target language input and thus is crucial for SLA. Leonard affirmed that interaction takes place when the learner can control the learning environment, that is, Students prefer being in control of the learning process rather than being on the receiving end of it. Theoretically, web-based instruction should be a suitable environment for students to take charge of their own learning because of its authentic, functional, interactive, and constructive characteristics. In other words, web-based CALL should promote the development and the exercise of learner autonomy. However, White (1995) argued that not all distance learners are able to meet the demands of self-directed learning in a web-based instructional environment, which becomes a cause of high attrition rates for students learning in cyberspace (Carr, 2000; Chang, 2005; Kubala, 1998). Online learners’ motivation can easily decline when the materials fail to attract and hold their attention, when they get lost in the instruction, or when they fail to stay on schedule (Chang & Lehman, 2002). Strategies that encourage students to develop self-regulation clearly need to be implemented. In order to increase the retention rate and success of online learning, Blin (2004) provided a multilevel CALICO Journal, 27(2), p-p xx-xx.
© 2010 CALICO Journal
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CALICO Journal, 27(2)
Effects of Self-Monitoring on Learners’ Performance and Motivation
approach to CALL and the development of learner autonomy by applying activity theory. For individual actions, Blin suggested that instructors can support sense-making actions within an activity and make learning tools and procedures visible and comprehensible.
Motivational Beliefs and Self-Regulated Learning Researchers and education experts have pointed out that learners’ affective domain, their motivational orientations (Brown, 1994; Pintrich & de Groot, 1989), and their learning strategies (Brown, 1994; Keller & Suzuki, 1988) play significant roles in language instruction and comprehension. Research has also suggested that EFL teachers should assist students to take charge of their own learning process because learners’ motivation can quickly suffer if the process of learning does not become self-sustaining for them (Zimmerman, Bonner, & Kovach, 1996). Dörnyei and Csizér (1998) conducted a study to compile a set of 10 motivational macrostrategies for motivating language learners and found that motivated learners tend to take responsibility for their own learning; that they perceive that their learning success and failures depend on their own efforts rather than factors outside their control, and that these macrostrategies are the characteristics of autonomous, self-regulating language learners. Self-regulated learning has emerged as an important construct in education. It has become clear that one of the key issues in self-regulated learning is the learner’s ability to select, combine, and coordinate cognitive strategies in an effective way (Boekaerts, 1999). Zimmerman and Schunk (1989) defined self-regulated learning in terms of self-regulated thoughts, feelings, and actions that are systematically oriented toward attainment of students’ own goals. Winne (1995) described self-regulated learning as a constructive and self-directed process. Boekaerts, Zimmerman and Schunk, and Winne all share the same assumption that students can actively regulate their own cognition, motivation, or behavior. Self-regulated students know how to use the resources available to them; they have control of their learning. They know how to plan, allocate resources, seek help, evaluate their own performance, and revise and correct their own work. Through these various regulatory processes, students achieve their goals and higher levels of performance (Zimmerman, 1989). Self-regulated learning includes cognitive processes such as attending to instruction, processing and integrating knowledge, and rehearsing information, as well as learners’ motivational beliefs. The motivational beliefs measured in this study include control of learning beliefs and the perception of task value. Control of learning refers to students’ beliefs that their efforts to learn will result in positive outcomes and that outcomes are contingent on their own effort, in contrast to external factors such as the teacher. Task value refers to a student’s evaluation of the importance of the task, the intrinsic interest in the task, and the usefulness of the task (Pintrich, 1989). Research has indicated that if students believe that their efforts to study make a difference in their learning and what they have learned is important and useful, they are more likely to study more strategically and effectively (Pintrich, Smith, Garcia, & McKeachie, 1991). Self-regulated learning not only enhances students’ academic performance in many fundamental ways but also helps to foster their interpretation of results that indicate personal growth. When it occurs, students’ perceptions of self-efficacy will grow, and their motivation to persist in learning will also be sustained. Therefore, assisting students to acquire self-regulatory skills, such as organizing, planning, and monitoring their learning, will directly foster higher levels of perceived control and focus students’ attention on the importance of effort for successful learning. Results from research have showed that improvement occurs as a result
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Mei-Mei Chang
of instruction in the use of a single self-regulatory strategy, such as self-monitoring (e.g. Harris, Graham, Reid, McElroy, & Hamby, 1994).
Self-Monitoring Self-monitoring is crucial to self-regulation. Self-monitoring functions through self-awareness and focuses on students’ ability to monitor their progress towards learning goals. This can lead to faster and more appropriate control of intervention strategies which can contribute to the success of staying on task and task completion during learning activities. In addition, “self-monitoring is the process of having individuals record data regarding their own behavior for the purpose of changing its rate” (Coleman & Webber, 2002, p. 103). According to Zimmerman (1995), there are three forms of self-monitoring: monitoring associated with (a) self-evaluation, (b) strategy implementation, and (c) efforts to adapt the strategy from outcomes. Self-monitoring training can be effective in improving adaptive goal-setting and learning. Several empirical studies also have shown that students benefit from being taught self-monitoring skills; by observing and recording their own behavior, students comprehend the material more thoroughly (Coleman & Webber, 2002; Zimmerman, 1995). For example, Lan’s (1996) study on 72 graduate students in a distance learning program showed that students in the self-monitoring group performed academically better than those in the instructormonitored and control groups. White (1995) conducted a comparative study to investigate the learning strategies of 417 foreign language learners (143 classroom learners and 274 distance learners). Her results showed that distance learners made much greater use of the monitoring than classroom learners. Among the monitoring strategies used, distance learners were particularly concerned with comprehension monitoring and problem identification. They checked on their understanding of the target language and identified problems that hindered their efforts. Coleman and Webber (2002) also pointed out that self-monitoring has consistently produced improved academic performance and classroom behavior. Zimmerman (1995) has indicated that self-monitoring activities enhance not only learners’ learning but also their selfefficacy in the learning process. Self-monitoring activities give students a sense of personal control that has been shown to be a major source of intrinsic motivation to continue learning on their own. Researchers have claimed that self-monitoring skills aid learning in any instructional method (e.g., Linder & Harris, 1993; Zimmerman, 1990). It is therefore obvious that, as students move toward a more flexible mode of tertiary education, self-monitoring is one of the essential skills that students must acquire. Monitoring activities include tracking of attention while reading a text or listening to a lecture, self-testing to check their understanding of the material, and the use of test-taking strategies (e.g., predicting test scores and adjusting time spent on text preparation) (Chang, 2005). All of these monitoring strategies alert learners to breakdowns in attention or comprehension that can then be repaired through the use of regulating strategies (Garcia & Pintrich, 1994). In this study, a self-monitoring form for recording study time and environment and for predicting test score—a test-taking strategy—was used as a treatment. It was assumed that students’ monitoring of their time and the actual place they chose to study would help their efforts at completing the academic task and that the test-taking strategies would provide students opportunities to evaluate their own learning and make a prediction. Hopefully, the self-monitoring learning strategies would help students adapt to their learning environment and improve their learning and motivation.
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CALICO Journal, 27(2)
Effects of Self-Monitoring on Learners’ Performance and Motivation
Monitoring has been shown to be critical in distinguishing effective from ineffective learners (O’Malley, Chamot, & Küpper, 1989), but the use of this strategy has not been explored in relation to effects from the learning context. The present study aimed to investigate effects of the use of self-monitoring learning strategy on academic performance and motivational beliefs in a web-based learning environment. The research was designed to answer the following questions: 1. Does the self-monitoring strategy help online learners improve their academic performance including performance on course-based test and on a general English proficiency test? 2. Does the self-monitoring strategy help online learners improve their motivational beliefs including their perception of control of learning beliefs and their perception of task value?
METHOD The study explored the effects of the use of self-monitoring strategies for study time, study environment, and predicting test score in a web-based course. The course was a one-semester English reading and grammar class. At the beginning of the course, a total of 106 students were invited to participate in the study, but in the final analysis, only 90 sets of data were complete. A test of general English proficiency was administered to verify the homogeneity between two groups of students. A modified version of the modified Motivated Strategies for Learning Questionnaire (MSLQ; Pintrich et al., 1991) was administered at two points in time (the third week and the sixteenth week). A reading comprehension test based on the course materials and a second general English proficiency test were administered at the end of the course. The study employed one independent variable, self-monitoring, and two dependent variables, academic performance and motivational beliefs. Participants in the experimental group used the self-monitoring strategy, and those in the control group did not. Students’ academic performance was measured by their scores on the course-based reading comprehension test and the general English proficiency test. The modified version of the MSLQ was used to assess learners’ motivational beliefs, including their perception of control of learning beliefs and their perception of task value. It was hypothesized that (a) the difference in means on the reading comprehension test between the control group and the experimental group would be significant, (b) the difference in means between the first general English proficiency test and the second general English proficiency test would be significant for experimental group, and (c) the mean difference between time 1 MSLQ administration and time 2 MSLQ administration would be significant for experimental group.
Subjects Data from a total of 90 EFL university freshmen were included in this study. The students represented different academic majors, including engineering, agriculture, and management, and all were enrolled in English classes. The participants were between 19 and 22 years old and had been studying English for at least six years, including three years in junior middle school and three years in high school.
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Mei-Mei Chang
Web-Based Instruction The system used for the course provided the following functions: (a) Profile Management (b) Reading Material Display (c) Course Information Display (d) Discussion Board, and (e) Personal Record (see sample screen displays in Figures 1-3). Figure 1 Profile Management
Figure 2 Reading Material Display
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Effects of Self-Monitoring on Learners’ Performance and Motivation
Figure 3 Course Information Display
The web-based interactive instructional materials were adapted from materials in textbooks, grammar books, newspapers, and magazines. Hyperlinks to external related websites were provided in each chapter. In the web-based materials, students were able to read texts and listen to oral instruction. They could also ask teacher questions through a discussion board and discuss topics from the materials with individual classmates or in small groups. After each chapter, students took a comprehension quiz for practice. Students turned in their homework through an “assignment panel” in the Reading Materials Display. Teacher and students could communicate with each other privately through a “talk to each other” window, and teachers could easily access students learning records in the student record database.
Self-Monitoring Instrument The self-monitoring instrument used for treatment group was the Self-Monitoring Recording Form. When logging in the course website, students in treatment group were asked to record the time they entered, the place where they were studying, and the names of the students with whom they were studying. They were also directed to predict their on the current chapter quiz. When students logged off the website, they were asked to record their logout time and the actual score they received on the quiz. Students could easily see their study record on the screen when they logged out (see Figure 4).
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Mei-Mei Chang
Figure 4 Flowchart of Students’ Actions on the Website Login
View history
readings grammar
Fill in the form
practice discussion
View record
quiz
Logout
Each time students logged in the course website, they saw their learning history. They could review their time and place of study and also compare their predicted quiz score to their actual score to evaluate their own learning (see Figure 5). Figure 5 Self-monitoring Record
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Effects of Self-Monitoring on Learners’ Performance and Motivation
Self-monitoring Strategy Measures Students’ use of the self-monitoring strategy was measured by the modified MSLQ. The MSLQ is a self-report questionnaire designed to assess student’s motivation and cognition and focuses on self-efficacy, test anxiety, cognitive strategy use, and regulatory strategy use. In this study, subscales with items designed to assess students’ perception of control of learning beliefs and task value for the course were used. The MSLQ subscale scores for each participant were constructed by taking the mean of the items that make up that scale. For example, the task value subscale had six items; an individual’s score for task value was computed by summing the six items and taking the average. For negatively worded items, the ratings were reversed; thus, the higher the score, the more positive the responses to the items. The internal consistency reliability was .89 for task value subscale and .74 for the control of learning beliefs subscale.
Procedures At the beginning of the semester, the English proficiency test was administered to the students in both groups. The students in the experimental group were then given the self-monitoring form to record their time of study, place of study, and test score prediction; those in control group were not given this form. The students in the experimental group were asked to record the three pieces of information above each time they entered the website to read the course content or to participate in discussion board activities. For the first 2 weeks of the course, the instructor met face to face with the students to orient them to the web-based instruction. After that, students were expected to study the course material on the website on their own time. However, students needed to come to the classroom to take the mid-term exam and the final exam. In week three, the modified MSLQ was administered for the first time. On the week sixteen, all participants completed a coursebased reading comprehension test, a general English proficiency test, and the modified MSLQ a second time. The data collected were analyzed at the end of the semester. T tests were conducted to determine the effect of self-monitoring strategies on learners’ academic achievement and motivational beliefs.
RESULTS The experimental and control groups each contained 45 students. The t-test results for the general English proficiency test administered at the beginning of the course showed no significant difference between the groups (see Table 1). Table 1 T-Test Results of General English Proficiency Test Administered at the Beginning of the Course
Group
M (SD)
df
t
Control
49.84 (8.28)
88
1.95
Experimental
46.37 (8.8)
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CALICO Journal, 27(2)
Mei-Mei Chang
The t-test results in Table 2 show that the mean scores between the English proficiency test administered at the beginning of the course and the one administered at the end of the course were significantly different for the experimental group (t = 3.67, p = .001) but not for the control group (t = .845, p = .403). These results indicate that the self-monitoring strategy helped online learners improve their English proficiency. Table 2 T-Test Results for pre/post English Proficiency Test for Control and Experimental Groups Control M (SD) Pretest
49.84 ()
Posttest
50.97 ()
Experimental df
t
44
0.845
M (SD) 46.38 ()
df
t
44
3.67*
52.47 ()
*p < .01 (NEED SDs FOR BOTH GROUPS. ALSO, PARAGRAPH ABOVE SAYS p = .001, BUT NOTE TO THE TABLE SAYS p < .01. SHOULD THE NOTE TO THE TABLE SAY p < .005? In terms of motivational beliefs, results from the mean score comparison of Control of learning belief subscale show that for experimental group, the difference between time 1 and time 2 was statistically significant (t = 3.00, p = .004), while the difference between Time 1 and Time 2 for control group was not (t = -1.42, p = .163). The mean score for experimental group increased by 0.82 while that for control group decreased by 0.49 (see Table 3). The students in the experimental group improved their control of learning beliefs. Table 3 T-Test Results for Control of Learning Beliefs between Time 1 and Time 2 for Control and Experimental Groups Control
Experimental
M (SD)
df
t
M (SD)
df
t
Time 1
15.20 (2.16)
44
-1.42
15.51 (1.34)
44
3.00*
Time 2
14.71 (2.36)
16.33 (1.57)
*p < .01 (SAME QUESTION AS FOR TABLE 1. PARAGRAPH ABOVE SAYS p = .004, but note says p < .01. SHOULD THE NOTE TO THE TABLE SAY p < .005? Table 4shows the comparison of the task value subscale between time 1 and time 2 for the two groups. For experimental group, the mean score increased by 1.11 between time 1 and time 2, and the difference was statistically significant (t = 3.27, p = .002). For control group, on the other hand, the mean score did not show a significant difference between time 1 and time 2 (t = .201, p = .84). The experimental group improved in terms of perception of task value, but not the control group. Table 4 T-Test Results for Task Value between Time 1 and Time 2 for Control and Experimental Groups Control
Experimental
M (SD)
df
t
M (SD)
df
t
Time 1
21.40 (3.36)
44
0.201
22.47 (2.70)
44
3.27*
Time 2
21.51 (3.27)
*p < .01
25.58 (3.01) 9
CALICO Journal, 27(2)
Effects of Self-Monitoring on Learners’ Performance and Motivation
Finally, the mean score of the course-based reading comprehension test for experimental group was not significantly higher than that for the control group (69.07 vs. 65.07; see Table 5). Table 5 T-Test Results for Course-based Reading Comprehension Test for Control and Experimental Groups Group
M (SD)
df
t
Control
65.06 (12.00)
88
1.72
Experimental
69.07 (9.98)
DISCUSSION The purpose of the current study was to examine the effect of the use of a self-monitoring strategy in web-based English learning on EFL learners’ academic performance and motivation. The first research question concerned the effect of the use of the self-monitoring strategy on academic performance on a general English proficiency test and a course-based test for EFL learners in a web-based learning environment. The results indicate that the students who adopted the self-monitoring strategy performed academically better than those who did not on the test of general English proficiency but not on the course-based test. Self-monitoring seemed to contribute to students’ improvement in general English proficiency. The second research question examined whether students’ use of the self-monitoring strategy could help them improve their motivational beliefs, including the control of learning beliefs and the perception of task value. Result show that the students who used the selfmonitoring strategy reported a significantly higher level of control of learning beliefs and task value by the end of the course. On the other hand, students who did not use the self-monitoring strategy did not show gains in either area. The students who applied the self-monitoring strategy positively viewed the importance of the course materials; they believed that the materials were useful, and they could use what they learned from this class in other classes. In addition, the students believed that their learning depended on their own effort. These results corroborate previous research findings that students perceived the outcome of their learning to be their responsibility and that if students believe that their efforts to study make a difference in their learning, they are more likely to study more strategically and effectively (Pintrich et al., 1991). Previous research findings have also shown that students’ motivation is linked to their successful learning in the content domain (Chang, 2001; Etmer et. al., 1996). Results of this study indicate that incorporating self-monitoring strategies into web-based instruction helps students improve their motivation beliefs, including adaptive levels of control of learning beliefs and task value perception, and thereby benefited their academic performance.
CONCLUSION Self-monitoring is the process of having individuals record data regarding their own behavior for the purpose of changing their original rates of learning (Coleman & Webber, 2002). In this study, the effects of the use of a self-monitoring strategy on students’ academic performance and motivational beliefs support previous research indicating that the self-monitoring strategy benefits learning and motivation perception. By observing and recording their own
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Mei-Mei Chang
behavior, students comprehended the material more thoroughly. Their recording of attention while reading texts, doing assignments, and participating in discussions and their predicting test scores (and adjusting their amount of study time) contributed to their understanding of the learning process and the material to be learned. Self-monitoring helped the students to complete academic tasks, alerting them to breakdowns in attention or comprehension, and gave them opportunities to evaluate their own learning. Self-monitoring also help improve students’ motivational beliefs (e.g., control of learning beliefs and the perception of task value). Thus, applying self-monitoring strategies in a web-based learning environment should be strongly encouraged as a way to build greater learner autonomy.
REFERENCES Blin, F. (2004). CALL and the development of learner autonomy: Towards an activity-theoretical perspective. ReCALL, 16, 377-395. Boekaerts, M. (1999). Self-regulated learning: Where we are today. International Journal of Educational Research, 31, 445-457. Brown, H. D. (2007). Principles of language learning and teaching. White Plains, NY: Pearson Education. Brown, H. D. (1994). Teaching by principles: An interactive approach to language pedagogy. Englewood Cliffs, NJ: Prentice Hall. Carr, S. (2000). As distance education comes of age, the challenge is keeping the students. [Electronic version]. Chronicle of Higher Education, 46(23), A39-A41. Chang, M. M. (2005). Applying self-regulated learning strategies in a web-based instruction—An investigation of motivation perception. Computer Assisted Language Learning, 18, 217-230. Chang, M. M., & Lehman, J. D. (2002). Learning foreign language through an interactive multimedia program: An experimental study on the effects of the relevance component of the ARCS model. CALICO Journal, 20, 81-98. Coleman, M. C., & Webber, J. (2002). Emotional and behavioral disorders. Boston: Pearson Education Company. Dörnyei, Z., & Csizér, K. (1998). Ten commandments for motivating language learners: Results of an empirical study. Language Teaching Research, 2, 203-229. Etmer et al (1996) MISSING; NEED COMPLETE REFERENCE. Garcia, T., & Pintrich, P. R. (1994). Regulating motivation and cognition in the classroom: The role of self-schemas and self-regulatory strategies. In D. H. Schunk & B. J. Zimmerman (Eds.), Self regulation of learning and performance: Issues and educational applications. (pp. 127-153). Hillsdale, NJ: Lawrence Erlbaum Associates. Gass, S. M., & Varonis, E. M. (1994). Input, interaction and second language production. Studies in Second Language Acquisition, 16, 283-302. Harris, K. R., Graham, S., Reid, R., McElroy, K., & Hamby, R. (1994). Self-monitoring of attention versus self-monitoring of productivity: A cross task comparison. Learning Disability Quarterly, 17, 121-139. Keller, J. M., & Suzuki, K. (1988). Use of the ARCS model in courseware design. In D. H. Jonassen (Ed.), Instructional designs for microcomputer courseware (pp. 401-434). Hillsdale, NJ: Lawrence Erlbaum Associates.
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Kubala, T. (1998). Addressing students needs: Teaching on the Internet [Electronic version]. T.H.E. Journal, 25(8). Retrieved January 20, 2005, from http://www.thejournal.com/magazine/vault/ A2026.cfm Lan, W. Y. (1996). The effects of self-monitoring on students’ course performance, use of learning strategies, attitude, self-judgment ability, and knowledge representation. Journal of Experimental Education, 64, 101-115. Leonard, G. (1968). Education and ecstasy. New York: Dell. Lin, C. C., & Hsu, H. C. (2001) EFL students’ perceptions of web-based reading-writing activities. In EDITOR?? (Ed.), Proceedings of the 10th International Symposium on English Teaching, Taipei, Taiwan, R.O.C. (pp. 525-533). PLACE OF PUBLICATION??: PUBLISHER??. Linder & Harris, 1993 MISSING; NEED COMPLETE REFERENCE Liou, H. C. (1997). The impact of WWW texts on EFL learning. Computer Assisted Language Learning, 10, 455-478. Liou, H. C. (2001, March). Computers, classroom culture, and the social contexts: A study of integrating CALL into college EFL curriculum. Paper presented at CALICO 2001, University of Central Florida, Orlando, Florida. Liou, H. C., & Yang, C. Y. (2002). Building a virtual community MOO for pre-service English teachers. In EDITOR?? (Ed.), Proceedings of the 19th International Conference on English Teaching & Learning in the Republic of China, Taipei, Taiwan, R.O.C. (pp. 337-349). PLACE OF PUBLICATION??: PUBLISHER??. O’Malley, J. M., Chamot, A. U., & Küpper, L. (1989). Listening comprehension strategies in second language acquisition. Applied Linguistics, 10, 418-437. Pintrich, P. R. (1989). The dynamic interplay of student motivation and cognition in the college classroom. In C. Ames & M. L. Maehr (Eds.), Advances in motivation and achievement: Vol. 6. Motivation-enhancing environments (pp. 117-160). Greenwich, CT: JAI Press. Pintrich, P. R., & de Groot, E. V. (1990). Motivational and self-regulated learning components of classroom academic performance. Journal of Educational Psychology, 82, 33-40. Pintrich, P. R., Smith, D. A. F., Garcia, T., & McKeachie, W. J. (1991). A manual for the use of the motivated strategies for learning questionnaire (MSLQ). (Tech. Rep. No. 91-B-004). Ann Arbor: University of Michigan, National Center for Research to Improve Postsecondary Teaching and Learning. White, C. (1995). Autonomy and strategy use in distance foreign language learning: Research findings. System, 23, 207-221. Winne, P. H. (1995). Self-regulation is ubiquitous but its forms vary with knowledge. Educational Psychologist, 30, 223-228. Zimmerman, B. J. (1989). A social cognitive view of self-regulated academic learning. Journal of Educational Psychology, 81, 329-339. Zimmerman, B. J. (1990). Self-regulated learning and academic achievement: An overview. Educational Psychologist, 25, 3-17. Zimmerman, B. J. (1995). Self-efficacy and educational development. In A. Bandura (Ed.), Self-efficacy in changing societies (pp. 202-231). New York: Cambridge University Press. Zimmerman, B. J., & Schunk, D. H. (Eds.). (1989). Self-regulated learning and academic achievement: Theory, research, and practice. New York: Springer-Verlag. Zimmerman, B. J., Bonner, S., & Kovach, R. (1996). Developing self-regulated learners: Beyond achievement to self-efficacy. Washington, DC: American Psychological Association.
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ADKNOWLEDGMENT This study was partially funded by the National Science Council (Effects of Self-Monitoring on Motivational Beliefs and Self-Regulated Learning in a Web-Based Instruction, Project Number: 93-2411-H-020-003).
AUTHOR’S BIODATA Mei-Mei Chang is currently a professor in the Department of Modern Languages at National Pingtung University of Science and Technology in Taiwan. Her research interests include multimedia-based language teaching, learning motivation, and language learning strategies. She teaches classes on web-based language learning and English reading and writing.
AUTHOR’S ADDRESS Mei-Mei Chang Department of Modern Languages National Pingtung University of Science and Technology No. 1, Shuehfu Rd., Neipu, Pingtung, 912 Taiwan email:
[email protected]
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