A new approach to supporting reflective,
self-regulated computer learning

Margaret M Ropp
Michigan State University

Teacher preparation programs in colleges of education around the country are engaged with the challenge of preparing graduates to teach with technology in our nation's schools. This challenge is, and will become increasingly, an important issue for teacher preparation programs as they respond to demands for technologically prepared teachers in schools. These demands have come from a variety of sources: from recommendations and legislation at the federal level (Goals 2000: Educate America Act (P.L. 103-277), to individual state and local initiatives (Office of Technology Assessment, 1995). For preservice teachers, these expectations for learning to teach with technology will require continuous learning throughout their inservice careers, particularly in light of the rapid pace of technological innovations in education. In fact, the Office of Technology Assessment (1995) found that the majority of inservice teachers who successfully integrate technology into their teaching were not taught how to do this in their teacher preparation programs. These practicing teachers have learned about new technologies, learned how to use them, and then adapted them for use in their classrooms after entering the work force. Often, this process required extensive individual work, even if the teachers were provided with some inservice training, further underscoring the independent nature of developing proficiency.

The need for self-directed learning is additionally impacted by the knowledge that networked computers have particular affordances and constraints. Most current computer interfaces assume interactions with a single individual who controls the mouse, keyboard and menu selections or commands. Learning to work with such individualistic interfaces typically requires hands-on experience and most learners would work alone for the majority of these experiences over the course of a three-year program in teacher preparation and in the years to follow. This kind of environment assumes that a learner who knows how to be self-directed and independent will be more successful than one who is dependent on structured guidance. Independent learning settings do, however, offer the learner more choice and control over the process and pace of learning.

Given the centrality of self-directed lifelong learning to any acceptable model for preparing teachers to use technology, it is essential that the model be grounded in theoretical perspectives that can be used to inform the discourse about continued learning. Research on self-regulated learning in academic settings has provided new directions for theory and practice that show promise for application to settings beyond the K-12 classroom. In defining self-regulated learning, most theorists would agree with Zimmerman's (1986) portrayal of students as "metacognitively, motivationally, and behaviorally active participants in their own learning process" (p. 308). Much of the research on self-regulated learning has derived from the study of expert learners in a variety of domains and the subsequent distillation of the knowledge and skills that these individuals possess. As these qualities were explored and identified, researchers attempted to develop ways to teach students how to become more self-regulated. Although students in K-12 schools have been the focus of this teaching, the enduring benefits of self-regulated learning are especially well-suited for transfer to teachers who are learning to use computers and technology in their teaching for several reasons.

According to Ertmer and Newby (1996), metacognition and self-regulated learning strategies are essential to the performance of expert learners who are faced with solving problems in new domains. In novel situations, an understanding of "how" to learn by using specific cognitive skills and strategies distinguishes expert learners from novices who may have an equal unfamiliarity with the content of the domain. If learning to use computers, new software, and information technologies in teaching is considered to be a domain that inservice teachers should be comfortable with, it is also an area that is uniquely fraught with novel learning situations and therefore may be particularly responsive to self-regulated learning strategies.

Perhaps one of the most compelling reasons for the encouragement of self-regulated learning is the potential to enhance perceptions of self-efficacy or control over the learning process (Zimmerman, Bonner, & Kovach, 1996). As new technologies such as the World Wide Web emerge quickly, no one, including teachers, will have had experience with them. For some teachers, the gap between their perceived technology competence and learning to use computers in their teaching is often threatening and overwhelming. Given the knowledge that many teachers are also novice computer users, teachers who are reflective and self-regulated in their efforts to learn to use computers in their teaching, regardless of their level of technology proficiency, may be more likely to engage this task rather than avoid it altogether.

At this point, a further exploration of self-regulated learning with a particular emphasis its metacognitive elements is warranted. In Zimmerman's (1986) three-part model of self-regulated learning, metacognition, motivation, and behaviors or actions all play significant and interrelated roles:

Metacognitively, self-regulated learners are persons who "plan, organize, self-instruct, self-monitor, and self-evaluate at various stages of the learning process." Motivationally, self-regulated learners perceive themselves as "competent, self-efficacious, and autonomous. Behaviorally, self-regulated learners select, structure, and create environments that optimize learning" (p. 308).

According to this definition, metacognition is viewed as one of the component processes of self-regulated learning. It also provides the second theoretical perspective that frames this research. In a paper that addressed continuing motivation to learn, McCombs (1984) proposed one way to view the relationships between self-regulated learning, motivation, and metacognition.

In order to maintain learning interest and implement specific self-directed or self-motivated learning skills and strategies, it is necessary for students to know themselves, what's important to them, and their learning competencies and abilities. ....That is, a metacognitive self-awareness is an integral component of continuing intrinsic motivation to learn. This self-awareness contributes to perceptions of personal competency and control in both a general and a specific sense (p. 200).

As defined by Flavell (1976), who figured prominently in initiating this line of research with work on metamemory, "`Metacognition' refers to one's knowledge concerning one's own cognitive processes and products or anything related to them, e.g., the learning-relevant properties of information or data" (p. 232). Furthermore, Flavell (1981) proposed that metacognition can be differentiated into metacognitive knowledge, experience, and strategies (p. 38).

If self-regulated learning is particularly applicable to learning in new domains such as technology, then teacher preparation programs should conceive of ways to support preservice teachers as they develop the relevant knowledge, skills, and strategies for this kind of learning. Essentially, there must be a focus on fostering those characteristics and habits that will endure in domains of continuous change and innovation such as learning to use technology. To that end, the present study details the development of an innovative approach used during a one-semester course that might be replicated and expanded for use in teacher preparation programs spanning several semesters.

Of all the possible metacognitive and self-regulated learning constructs and strategies, metacognitive knowledge and experiences were selected as the primary foci of this research for two reasons: (a) metacognitive knowledge and experiences can precede and initiate metacognitive actions (Flavell, Miller, & Miller, 1993) and self-regulated learning strategies (McCombs, 1984), and (b) metacognitive knowledge and experiences also may require less explicit instruction and time than the more action-oriented elements, a feature that is a good match for the limited amount of time that teacher educators have with students during a one-semester course.

The potential for metacognitive constructs and theories of self-regulated learning to inform practice rests heavily on their application during the preservice teacher preparation years when there are opportunities to teach and support the habits of self-directed learning. To that end, this study sought to investigate ways in which individual characteristics associated with learning to use computers could be used as pedagogical tools for metacognitive reflection once preservice teachers are aware of them. Although many studies over the last two decades have investigated a variety of individual characteristics, five sets of characteristics were selected for their potential to change through experience and instruction. The characteristics that were studied were (a) computer attitudes, (b) computer anxiety, (c) computer self-efficacy, (d) self-report of computer confidence, and (e) computer coping strategies. While many of these characteristics have been studied alone or with other correlates (Bandalos & Benson, 1990; Delcourt & Kinzie, 1993, Hudiburg, 1996; McInerney, McInerney, & Sinclair, 1994, Violato, Marini, & Hunter, 1989), this particular constellation of individual characteristics is unique in the literature and represents a new, pedagogically-based framework of constructs.

Method

The fifty teacher candidates who participated in this research came from two sections of the same teacher preparation course. One section was reserved for elementary education majors and the other for those interested in teaching subject matter at the secondary level. The individual characteristics of preservice teachers associated with levels of computer competence were measured at the beginning and end of this one-semester class in a pretest-posttest design. The instruments assessed the five sets of "changeable" individual characteristics and included four openly published instruments and three others that were newly developed for this study. About a week after the surveys were returned to the instructors, the data were analyzed and the scored surveys were given back to students and the group data for the class was presented during a class session. Students were asked to compare their individual scores on the surveys and to try and find where they fit in the distribution of class scores that were represented in the graphical displays of data. The instructors led class discussions that emphasized how the surveys could be used as tools for goal setting and reflection. Students generated ideas and talked about ways in which they could help themselves and their colleagues learn to use computers in teaching subject matter. During the semester, students also participated in hands-on technology activities and the surveys were readministered to students at the end of the semester. The results of the data from Time 1 and Time 2 were again shared with students in a brief class discussion.

Three different sources of data were used to investigate candidates' metacognitive awarenesses, experiences and strategies. At the completion of first survey administration, the class discussion, and the hands-on activities, students were asked to complete a "fast write" which is a one-page set of open-ended questions that can be completed in about five minutes. The majority of the fast write questions assessed metacognitive constructs. In addition, all 50 teacher candidates participated in short, semi-structured interviews and 7 of the students were selected for in-depth interviews as case studies.

Results

Results from the fast write data, brief interviews, and in-depth conversations revealed that the technology-based instructional activities provided many of the teacher candidates with metacognitive knowledge about themselves and others as well as initiated metacognitive experiences in a variety of contexts. Metacognitive experiences are described by Garner (1987) as awarenesses, realizations, or "ahas," and these experiences often flow from metacognitive knowledge. The three different methods of data collection provided different facets and layers of depth to the awarenesses and experiences that were the primary metacognitive constructs investigated in this study. Although evidence of metacognitive activity initiated by instructional opportunities is but one of the theorized components of self-regulated learning, it is a promising first step toward supporting the development of self-directed computer learning.

A selection of responses from the fast writes that were given after the survey completion activity, the class discussions, and the hands-on technology sessions indicate that these activities triggered metacognitive experiences and knowledge.

I always knew that I would have to improve my technology skills to be able to integrate it into my teaching, but completing the survey helped me expand my horizons as to how much technology is really used. (Candidate #9, Survey)

I learned that I am actually on the high end of attitudes and aptitudes, which surprised me. I like working with computers, but sometimes I feel overwhelmed. (#26, Discussion)

I have been "surfing" the Internet for teaching ideas for some time. But we did find an idea which integrated "use" of the Internet in class with the students, which I have wanted to learn how to do. (#26, Hands-on)

I plan on using the Internet for my lesson plans in my classes as well as ideas for my collaborating teacher's classroom when I have to teach again! (#39, Hands-on)

The short interviews given to all 50 students provided them with opportunities to describe metacognitive knowledge and experiences that occurred in contexts that included but were not limited to the activities tapped by the fast writes. For example, knowledge gained from the Computer Coping Strategies scale was instrumental in the computing experiences of a student who believed it changed the nature of her subsequent interactions with computers.

I noticed that after taking the first questionnaire, I thought about the fact that I do use the help buttons or balloons more often. Sometimes I'll just pull the balloons out and say "Okay, let's run through the icons and figure out what things are in programs." I'm much more likely to open up new programs that are just on the hard drive and see what they are. Maybe it'll help me. So I've learned that those things are there, why don't I just use them? (#44)

One student expressed an awareness that he was becoming less anxious as he continued to work with computers.

I always feel like I'm always going to somehow break the computer if I type in the wrong command and I feel less and less like that now. I've learned to be more patient. Just realizing that other people are struggling with the same things through this class and my interaction with you. That's comforting and I don't panic as much because I realize that happens to even the experts. (#33)

The final source of data were the case studies of students who were systematically selected to represent diverse computing experiences. One of these students believed that the Technology Proficiency Self-Assessment that was developed for this study was particularly valuable, not only as a benchmark for initial computer competence, but also as an example of how technology could be used in the classroom.

The proficiency survey actually did a number of things for me. It showed me the things that I've been taking for granted that I was able to do with computers. It gave me a sounding board to see where I was situated in terms of the technology requirement. It provided ideas for how I can use technology as a teacher and as a teacher candidate and it showed me how much I still have to do. It definitely helped me pinpoint areas that I need more practice in and things that I would like to learn how to do. ("Jean")

Implications for Education

This research has enriched the field of education in two ways: (a) by developing a pedagogical approach that provides an immediate and adaptive application of research, and (b) by extending research on self-regulated learning to the domain of learning to teach with technology. As an innovative approach to teaching at the preservice level, this study opens the door for a new line of research that combines psychometric measurement and qualitative research methodology with the direct intent of application to educational goals for learning. Although the examples of metacognitive knowledge and experiences triggered by the technology-related activities presented in this paper are but a small selection of a much larger body of evidence, they clearly show that these activities were successful in their application. Ideally, more time would be allotted to class discussions, reflection, and hand-on instruction during the semester than the four total hours provided in this study. It is encouraging, however, to note the compelling evidence that students reported increased metacognitive knowledge, awarenesses, and experiences given these time constraints. Although metacognitive knowledge and experiences are components of the more comprehensive and long-term processes that support self-regulated and self-directed technology learning, this new teaching approach shows promise for successful elaboration and integration in multi-semester teacher preparation programs.

References

Bandalos, D., & Benson, J. (1990). Testing the factor structure invariance of a computer attitude scale over two grouping conditions. Educational and Psychological Measurement, 50 (1), 49-60.

Delcourt, M. A. B., & Kinzie, M. B. (1993). Computer technologies in teacher education: The measurement of attitudes and self-efficacy. Journal of Research and Development in Education, 27 (1), 35-41.

Ertmer, P. A., & Newby, T. J. (1996). The expert learner: Strategic, self-regulated, and reflective. Instructional Science, 24, 1-24.

Flavell, J. H. (1976). Metacognitive aspects of problem solving. In L. B. Resnick (Ed.), The nature of intelligence (pp. 231-235). Hillsdale, NJ: Erlbaum.

Flavell, J. H. (1981). Cognitive monitoring. In W. P. Dickson (Ed.), Children's oral communication skills (pp. 35-60). New York: Academic Press.

Flavell, J. H., Miller, P. H., & Miller, S. A. (1993). Cognitive development (3rd ed.). Englewood Cliffs, NJ: Prentice Hall.

Garner, R. (1987). Metacognition and reading comprehension. Norwood, NJ: Ablex Publishing Corporation.

Goals 2000: Educate America Act. Pub. L. No. 103-227, 20 USC 5897.

Hudiburg, R. A. (1996). Coping with computer stress. In Paper presented to the SIG/Stress in Education Group at the 1996 American Educational Research Association Annual Meeting, New York, NY.

McCombs, B. L. (1984). Processes and skills underlying continuing intrinsic motivation to learn: Toward a definition of motivational skills training interventions. Educational Psychologist, 19, 199 - 218.

McInerney, V., McInerney, D. M., & Sinclair, K. E. (1994). Student teachers, computer anxiety and computer experience. Journal of Educational Computing Research, 11 (1), 27-50.

Office of Technology Assessment. (1995). Teachers and Technology: Making the connection. (OTA-EHR-616). Washington, DC: U.S. Government Printing Office.

Violato, C., Marini, A., & Hunter, W. (1989). A confirmatory factor analysis of a four-factor model of attitudes toward computers: A study of preservice teachers. Journal of Research on Computing in Education, Winter, 199-213.

Zimmerman, B. J. (1986). Becoming a self-regulated learner: Which are the key subprocesses? Contemporary Educational Psychology, 11, 307 - 313.

Zimmerman, B. J., Bonner, S., & Kovach, R. (1996). Developing self-regulated learners: Beyond achievement to self-efficacy. Washington, DC: American Psychological Association.