Citekey: @Zimmerman1986-vd

Zimmerman, B. J., & Pons, M. M. (1986). Development of a structured interview for assessing student use of self-regulated learning strategies. American Educational Research Journal, 23(4), 614–628.



High achieving students displayed significantly greater use of 13 cate- gories of self-regulated learning (p. 1)

Recently, several theoretical articles have sought to relate various views of self-regulated learning to academic moti- vation and achievement (Corno & Mandinach, 1983; McCombs, 1984; Schunk, 1984). In the present account, the term self-regulation will be used to describe this general theoretical approach. (p. 2)

By self-regulated learning strategy we mean actions directed at acquiring information or skill that involve agency, purpose (goals), and instrumentality self-perceptions by a learner. (p. 2)

They included goal-setting, environmental structuring, self-consequences (self-rewarding and self-punishment), and self-evaluating. Several other categories were included on the basis of closely allied theoretical formulations—namely, the strategies of organizing and transforming (Baird, 1983; Corno & Mandinach, 1983), seeking and selecting information (Baird, 1983; Wang, 1983), and rehearsal and mnemonic strategies (McCombs, 1984; Paris, Newman, & Jacobs, 1984). Also included were the strategies of seeking social assistance and reviewing previously compiled records such as class notes and notes on text material (Wang, 1983). (p. 2)

The present study investigated student use of 14 self-regulation strategies in nonclassroom as well as classroom contexts using a structured interview procedure. (p. 3)

a second goal of the study was to determine the relationship between students’ reported use of these strategies and an omnibus measure of scholastic accomplishment: their achievement track in school. (p. 3)

It was hypothesized that students selected from a high achievement track in a public high school would display greater use of self-regulation strategies than students chosen from other (lower) achievement tracks. Greater use of a non-self-regulated strategy was expected by students from the lower achievement tracks. (p. 3)

METHOD (p. 3)

Sample (p. 3)

Self-Regulated Learning Interview Schedule (p. 4)

On the basis of prior research and theory, 14 classes of self-regulated behavior were identified. In addition, a single category of non-self-regulated behavior (labeled “other”) was included. (p. 4)

Based on pilot interviews with high school students from a different community, six different learning contexts were identified: in classroom situations, at home, when completing writing assignments outside class, when completing mathematics assignments outside class, when preparing for and taking tests, and when poorly motivated. (p. 4)

TABLE I Self-Regulated Learning Strategies (p. 5)

This table is super important. One possibility for the MOOC project is to derive a set of measures for each of those SRL strategies. Even focusing on one would be interesting. (Start from the easier ones…) (p. 5)

Categories of strategies Definitions 1. Self-evaluation 2. Organizing and transform- ing 3. Goal-setting and planning 4. Seeking information 5. Keeping records and moni- toring 6. Enviromental structuring 7. Self-consequences 8. Rehearsing and memoriz- ing 9-11. Seeking social assistance 12-14. Reviewing records 15. Other Statements indicating student-initiated evaluations of the quality or progress of their work, e.g., “I check over my work to make sure I did it right.” Statements indicating student-initiated overt or cov- ert rearrangement of instructional materials to im- prove learning, e.g., “I make an outline before I write my paper.” Statements indicating student setting of educational goals or subgoals and planning for sequencing, timing, and completing activities related to those goals, e.g., “First, I start studying two weeks before exams, and I pace myself” Statements indicating student-initiated efforts to se- cure further task information from nonsocial sources when undertaking an assignment, e.g., “Be- fore beginning to write the paper, I go to the library to get as much information as possible concerning the topic.” Statements indicating student-initiated efforts to re- cord events or results, e.g., “I took notes of the class discussion.” “I kept a list of the words I got wrong.” Statements indicating student-initiated efforts to se- lect or arrange the physical setting to make learning easier, e.g., “I isolate myself from anything that distracts me.” “I turned off the radio so I can concentrate on what I am doing.” Statements indicating student arrangement or imag- ination of rewards or punishment for success or failure, e.g., “If I do well on a test, I treat myself to a movie.” Statements indicating student-initiated efforts to memorize material by overt or covert practice, e.g., “In preparing for a math test, I keep writing the formula down until I remember it.” Statements indicating student-initiated efforts to so- licit help from peers (9), teachers (10), and adults (11), e.g., “If I have problems with math assign- ments, I ask a friend to help.” Statements indicating student-initiated efforts to re- read tests (12) notes (13), or textbooks (14) to prepare for class or further testing, e.g., “When preparing for a test, I review my notes.” Statements indicating learning behavior that is initi- ated by other persons such as teachers or parents, and all unclear verbal responses, e.g., “I just do what the teacher says.” (p. 5)

The protocols were coded by two graduate students. Each of the strategies was assigned by a primary judge to one of the 15 categories Hsted in Table I. (p. 6)

Three different procedures were used to summarize these categorical data. (p. 7)

At the most elemental level, each self-regulation strategy was scored dichoto- mously as having occurred or not during any of the six learning contexts. This measure was called strategy use (SU). A second, more comprehensive measure was termed strategy frequency (SF). This measure consisted of the number of times that a particular strategy was mentioned. (p. 7)

At the most comprehensive level, the students’ consistency of strategy use was scored. Each method (i.e., self-regulation or other strategy) was weighted by the student’s estimate of its freqency of use, a measure termed strategy consistency (SC). (p. 7)

RESULTS (p. 7)

To determine which of the three measures of strategy use was optimal in distinguishing between the two achievement groups, a discriminant function analysis (Tatsuoka, 1971) was performed using the total self- regulation scores for each of the usage measures. (p. 8)

he measures revealed substantial differences between the high and low achievement groups, x^ (3) = 81.49, p < .00} It was found that 91 % of the students in the sample could be correctly classified into the high and low achievement groups on the basis of their self-regulated learning measures. (p. 8)

These statistical results indicate that the SC measure was the most effective, although all three disciminant function coefficients were significant (p. 8)

Ninety-three percent of the students could be correctly classified into their respective achievement group on the basis of their use of these 15 categories of self-regulated learning. (p. 9)

These canonical correlation coefficients indicated that the two achieve- ment groups of students were differentiated most by their mention of the self-regulation strategies of “seeking information,” “keeping records and (p. 9)

monitoring,” and “organizing and transforming.” (p. 10)


The present results indicate that a structured interview procedure de- signed to measure student use of self-regulated learning strategies in non- classroom as well as classroom contexts displayed substantial correlation with academic achievement. (p. 11)

~~University of Minnesota Libraries on September 12, 2016~~ (p. 11)

It was found that an interview procedure could provide reliable evidence concerning students’ self-regulation reports. (p. 12)

The data indicate that the SC measure was superior to the other two measures in distinguishing between the two achievement groups of stu- dents. (p. 12)

Evidence that low achieving students reported significantly more non- self-regulated other responses (particularly will power statements) than high achievers indicates that the Self-Regulated Learning Interview in fact assessed individual differences in use of learning strategies, not merely in verbalness. Although it was anticipated that high achievers would be more verbal, the probe procedure was designed to accommodate students who felt reticent about discussing these matters, and the procedure appeared informally to work. Furthermore, the SC measure, which proved to be most effective in differentiating the two achievement groups of students, did not rely simply on verbal description. It differed from the SF measure in its dependence on data from a nonverbal rating scale. Clearly, the results cannot be attributed simply to student verbal fluency. (p. 13)

In conclusion, the Self-Regulated Learning Interview Schedule appears to have promise for describing students’ use of these strategies in natural- istic settings. Like all instruments based on a posteriori self-descriptions of performance and reasoning, it needs to be validated ultimately against students’ actual performance on academic tasks in naturalistic settings. (p. 13)

The present results suggest that theoretical conceptions of students as initiators, planners, and observers of their own instructional experiences have empirical and practical merit. (p. 13)

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