QUEST, 1988, 40, 63-73

Instructional Time Research in Physical Education:

Contributions and Current Issues

Amelia M. Lee and Carol Poto

The study of instructional time in classrooms and in physical education has a long history with several modifications along the way. Tracing this histo- ry, starting with its roots in models of the classroom teaching process, helps to explain why instructional time has gained the interest of so many in physi- cal education. Instructional time is generally studied with the goal of learn- ing more about and improving the teaching process. The historical perspective increases awareness that research on instructional time will be most valuable when integrated with findings from the study of other variables affecting the teachingllearning process in the physical education setting.

During the past decade, much attention has been given to the use of student- engaged time as a variable in pedagogical inquiry. Engaged time, a proximate measure of student involvement with subject matter, has been the focus of many theses and dissertations in physical education and has helped explain some of the complexities of teaching and learning in the gymnasium. In reviewing the history of time as an educational variable, it becomes evident that engaged time simply emerged as a refinement of instructional time. The phrase instncctional time has been used to refer to the number of days in the school year, number of hours in the school day, minutes of time scheduled for instruction, and amount of time a student is engaged in learning, which is the primary focus of this paper. The nuts and bolts of time research are observing, sorting, and categorizing teacher and student activities to determine which teacher behaviors are related to desired student behaviors, and ultimately to student achievement of curriculum objectives.

A key concept of the model of time and learning is that the influence of teaching on student learning is indirect; teacher behavior affects student behavior, and student behavior (what the student does during class time) is directly related to student achievement (Doyle, 1978). If the student is unable or unwilling to behave as directed, or if he or she follows instructions that are unrelated to cur- ricular goals, little measurable learning will occur. The purpose of this paper

About the Authors: Amelia M . Lee and Carol Poto are with the School of Health, Physical Education, Recreation, and Dance, Louisiana State University, Baton, Rouge, LA 70803.

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is to trace the evolution and present the current status of the concept of engaged time as a measure of student learning in physical education. Since the anteced- ents of instructional time research in physical education include the work done in classroom research, the classroom research is an appropriate place to begin this discussion. After a brief historical review, issues involved in using instruc- tional time as a variable in process-product designs in physical education will be discussed. Finally, comments are offered regarding the future of this line of research in the study of pedagogy.

Instructional Time as a Variable in Early Classroom Research

An early model of school learning in which many of the basic concepts could be measured in time was proposed by Carroll (1963). The time needed to learn in this model was believed to be quite different for each student and could be predicted by an aptitude test. The degree of learning then was dependent on the opportunity to learn relative to the student's aptitude, the quality of instruc- tion, and the student's ability to understand the instruction. Carroll's model pro- vided the basis for Bloom's (1974) work on mastery learning. Bloom reasoned that if the teacher could provide the time and help needed and could motivate the student to use the time available, most students could be brought to the level of achievement targeted by the curriculum.

Although most researchers agreed that time was a necessary ingredient for learning, some suggested that the passage of time or the mere quantity of schooling was valuable, regardless of how that time was spent (Wiley & Har- nischfeger, 1974). These views helped to promote time as an indicator of overan school quality. Even though the time-like variables continued to be accepted as a valuable educational construct and the work of Carroll and Bloom was widely known, it was not until the late 1970s that the use of student-engaged time as a measure of learning drew the attention of a wide spectrum of classroom and physical education researchers. To understand why instructional time did not emerge as an important variable in teaching research earlier, it is instructive to look briefly at other models of classroom research that existed at about the same time that Carroll's (1963) model did but that did not employ measures of student- engaged time.

Other Variables in Early Teaching Research

The criterion-ofeffectiveness paradigm was the dominant model in teaching research until 1963 (Gage, 1963). The criteria of teacher effectiveness used in this model were typically teacher ratings by administrative personnel, pupil gain in achievement test scores, and pupil ratings of teachers. Researchers looked for teacher characteristics and behaviors that could correlate highly with the crite- rion variables; student behaviors were not considered. The process-product research design was an improvement over criterion of effectiveness designs in that teaching activities were directly observed and measured using formal, quan- titative observation systems. Researchers looked for teacher behavior variables (process variables) that would correlate with student achievement test scores (prod-

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uct or outcome variables). Some of the observation systems included student be- haviors, but student-engaged time was generally not one of the variables studied.

Additional variables were summarized by Doyle (1978), who advocated studying the student responses and psychological processes that govern learning: such mediating processes as attending, translating, segmenting, rehearsing, task persistence, time utilization, and pupil engagement with the learning tasks. These types of student process variables were thus incorporated into the process-product paradigm in the following manner: teaching process -- student process -- stu- dent product (Gage, 1978). Within the framework of this modified process-product design, student-engaged time emerged as a quantitative measure of student cog- nitive processes leading to learning.

Instructional Time as a Variable in Process-Product Designs for Classroom Research

The first large-scale research effort employing instructional time as a student mediating variable in a teaching process-student process-student product design was the Beginning Teacher Evaluation Study (BTES) (for an overview, see Fish- er et al., 1978). Based on the work of Carroll (1963) and on Bloom's (1974) concept of mastery learning, Fisher et al. theorized that the amount of time a student was engaged with the subject matter was the crucial variable underlying successful teaching styles; that is, certain teacher behaviors allowed more time for appropriate student engagement. Classroom learning can be measured more directly and immediately by looking at student behavior in the classroom than by looking at distant achievement test scores. The time measure used as a substi- tute for student achievement was called Academic Learning Time (ALT), de- fined as the amount of time a student spends engaged in an academic task that can be performed with high success. The hypothesis suggests that the more ALT a student accumulates, the more the student is learning. It was always under- stood that ALT and learning would vary widely within a given classroom.

To confirm the hypothesis that ALT was a valid substitute measure for achievement test scores, it was necessary to test the relationship between ALT and achievement test scores. In the reading and math curricula covered in the BTES (second and fifth grades), ALT did prove to be a significant predictor of student achievement (Fisher et al., 1981). Engaged time at a low success rate was negatively associated with achievement. Since ALT had been shown to predict student achievement, the BTES investigators suggested that ALT could replace achievement test scores as a more reliable measure of student learning, one that was also more closely related to teacher behavior.

Current Status of ALT as a Variable in Classroom Research

Thus, the role played by classroom ALT research was to focus attention on student mediation of instruction at a time when most other process-product researchers were attempting to relate teacher behavior directly to student achieve- ment. Gage (1978) and others went further in noting the need to formulate vari- ables and processes that should be observed and measured within ALT. To give

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meaning to the observed student behavior, researchers began to consider how student perceptions of teaching and instruction might mediate student achieve- ment. In fact, study of student thought processes became a viable area of research in itself (Wittrock, 1986). The trend has been to make quantitative measures of time on task more meaningful by incorporating more detailed descriptions of teacher and student cognitive and affective processes into explanations of student learning in the classroom.

Instructional Time in Physical Education Research

Adhering to a long tradition of observational research in classroom settings, physical educators began to focus on the development and standardization of systematic observation instruments for recording and analyzing teacher and stu- dent behaviors in the gymnasium (Locke, 1977). One contribution was the modifi- cation of the observation system used in the BTES for use in physical education. Siedentop, Birdwell, and Metzler (1979) adapted the ALT model and presented a series of papers explaining how the ALT-PE concept could be used as a process measure in physical education. The original ALT-PE coding instrument was re- vised and simplified by Siedentop, Tousignant, and Parker (1982).

Although other observation systems have been designed to describe how students spend time in physical education (e.g., Laubach, 1983), the ALT-PE instruments have been used more often. Using a variety of sampling procedures and observation techniques, several descriptive-analytic researchers have studied time-on-task learning behaviors of students in physical education classes (Auf- derheide, Olson, & Templin, 1981; Costello & Laubach, 1978; Godbout, Bur- nelle, & Tousignant, 1983; Metzler, 1980; Placek, Silverman, Shute, Dodds, & Rife, 1982; Silvennan, Dodds, Placek, Shute, & Rife, 1984). In general, find- ings from these studies indicate that time in physical education for most students is not spent engaged in a movement task at an appropriate level of difficulty.

Using Instructional Erne in Process-Product Designs in Physical Education

The researchers who devised the ALT-PE coding instrument were satis- fied that results from classroom research would generalize to the gymnasium (Siedentop et al., 1982); it was deemed unnecessary to demonstrate the link be- tween ALT-PE (student process) and motor skill achievement test scores (stu- dent product). However, Dodds, Rife, and Metzler (1982), in a review of ALT-PE studies up to that time, recommended that ALT-PE be validated through corre- lation with achievement test scores before being used further, and many agreed with this idea. As of this writing, reported correlations between ALT-PE and achievement test scores have tended to be low and insignificant (see Dugas, 1984; McEwen & Graham, 1982; PiCron, 1982; Silverman, 1983, 1985a), perhaps be- cause there has been no large-scale research effort in physical education com- parable to the BTES. Although ALT has correlated with student achievement in classroom research, the time measure in physical education has not shown simi- lar predictive qualities. The correlations found in the BTES were not particularly strong to begin with even though they were statistically significant, so minor devi-

INSTRUCTIONAL TIME RESEARCH 67

ations in methodology could make the difference between significant findings in classroom research and nonsignificant findings in the physical education setting. If persons attempting to demonstrate a relationship between ALT-PE and stu- dent achievement test scores are to be successful, some standardization seems warranted in the areas of length of experimental teaching units (ETUs), statisti- cal method, and type of behavior designated as ALT.

Length of ETU. An important methodological concern is that the BTES researchers used ETUs to match instructional content with achievement test con- tent more closely. They experimented with ETUs of 6, 10, and 40 instructional days, recommending 40 days, with 10 days being a lower boundary in most cases and 6 days sufficient only in some content areas (Filby, 1977). Attempts were made to replicate their findings using several ETUs over the course of the year. Most researchers in physical education have used mini-ETU formats, which in- volve shorter periods of time and smaller classes (Graham, 1983). The length of ETUs in physical education has ranged from a single 20-minute lesson (e.g., Yerg, 1977) to three 3-hour classes (Wurzer, 1983). When very short ETUs are employed, testing to determine whether the gain from pre- to posttest is statisti- cally significant is a necessary first step. As pointed out by Filby (1977), in order to show statistically powerful relations between ALT and student achievement, it is important to have large mean gains to predict any large but variable amounts of instructional time.

Besides concern over whether the ETU is long enough to allow significant improvement in student performance, there is the issue of whether the time studied is sufficient to capture stable student and teacher behaviors. This is an important issue directly related to generalizability of study findings, and to whether teacher behaviors can be correlated with ALT-PE in the same study in which ALT-PE correlates with achievement. Yerg (1981) noted that very short ETUs allow greater experimenter control than would be possible in a field setting, but the single- ETU format requires replication and eventual follow-up by a full field study.

In a recent classroom study of on-task student behavior, Karweit (1985) systematically investigated the number of days required to produce reliability of the time-on-task measure. On-task behavior was a significant predictor of residu- alized achievement (at the .05 level) over 9 or 18 days of observation, but not over 5 days. Karweit suggested that more systematic investigation of reliability of time-on-task measures be conducted, since learning rate can vary within an instructional session and from session to session with a unit. Leinhardt (1985) reports generalizability studies that showed 20 hours of observation time were needed for some estimates of student behavior to stabilize. Lomax (1982) sug- gested that a generalizability analysis should be an integral part of the process of devising an observational system, so that more accurate measures of behavior would result. These findings suggest that validating a link between ALT-PE and achievement should be approached with a more realistic assessment of the time and effort required to produce consistent results.

Statistical Method for Correlating ALT-PE With Achievement. Regarding choice of statistical method, the part correlation method for analyzing change from pretest to posttest has proven to be a logical, reliable, and stable method for calculating change in the BTES. This technique or an analogous multiple regression method is therefore preferable for analyzing process-product correla- tional data in physical education (see Silverman, 1984).

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Behaviors Designated as ALT-PE. A question in physical education re- search that was not an issue in classroom ALT research is whether to include student cognitive activities as well as physical activities when reporting time on task. On the methodological level, this is a question of whether there is a better chance of finding significant correlations between ALT-PE and achievement test scores when just content-related motor engagement is used for ALT-PE, or when cognitive and motor engagement are combined and used as the measure of ALT- PE. In a summary of ALT-PE work up to that time, Dodds, Rife, and Metzler (1982) stated that although some researchers report both content-related cogni- tive engagement and motor engagement as ALT-PE, motor engagement (ALT- PE-M) "is now considered the best evidence of students' opportunity to learn in physical education" @. 4). On a methodological level this may be good ad- vice; on a theoretical level, however, the implications are that unless students are moving (and accumulating ALT-PE-M) they are not learning motor skills. Certainly students cannot be expected to improve unless they practice executing the appropriate movements, but accumulating cognitive knowledge concerning the skill is an integral part of skill acquisition, especially in the early stages.

In fact, models of motor skill learning explicitly include cognitive com- ponents. Fitts and Posner (1967) proposed a model that includes three stages: cognitive, associative, and autonokous. Progression is from high cognitive in- volvement early in learning to very low cognitive involvement in later stages, so that skilled performance eventually requires little conscious attention to the movement itself. Adams (1971) proposed a two-stage model, with a verbal-motor stage that includes Fitts and ~osner's cognitive and associative stages, and a mo- tor stage corresponding to their autonomous stage. A third model of motor skill acquisition, specifically designed for application to teaching, was proposed by Gentile (1972). Gentile suggested ways in which the teacher could intervene in several stages of the learning process to facilitate skill acquisition. These authors agree that motor learning progresses in stages that can be differentiated on the basis of the amount and nature of cognitive activity associated with production of the motor response.

Several investigators have coded and analyzed cognitive engagement in physical education classes (e.g., De Knop, 1986; Graham, Soares, & Harring- ton, 1983; Silverman, 1983, 1985a; Wurzer, 1983; Young & Metzler, 1982); Silverman (1985a) found significant negative correlations between cognitive en- gagement and achievement test scores. That is, more time spent in cognitive en- gagement was related to lower achievement test scores. One interpretation might be that time spent in cognitive engagement takes away from the motor engage- ment time that produces gains in skill. Other interpretations are possible: (a) the observation period may have been too brief, since there is often a lag between increase in cognitive understanding of a skill and ability to translate this knowl- edge into improved performance (French & Thomas, 1987), or (b) the cognitive instruction provided by the teacher may have been erroneous or not related to skill test content. An example would be a tennis teacher who focuses instruction on proper form for the forehand drive, although the skill test simply measures the percentage of forehand drives landing on a designated target. This issue of the best balance between cognitive and motor engagement is extremely complex and is an area of investigation in its own right (e.g., Thomas, French, & Hum-

INSTRUCTIONAL TIME RESEARCH 69

phries, 1986), which nevertheless should be considered in designing instruction- al time research in physical education.

Contribution of Lesson Content to Achievement Test Scores. Leinhardt (1985) has reported some findings from classroom research indicating that some of the correlation between teacherlstudent variables and student achievement is actually due to the match between curricular content and achievement test scores. In a study of reading and math achievement in first and third graders, the best predictor of residualized achievement was the degree to which the curriculum included what the achievement test measured. This effect was stronger than the other constructs that included motivators (curricular factors and interpersonal be- haviors assumed to encourage learning), teacher behaviors (content, frequency, quality, and duration of instructional interactions), and structure (level of organi- zation of cumculum, specificity of objectives, and match between student and curriculum). Content covered in a particular lesson area should be tracked and controlled before achievement test results can be attributed to time-on-task variables.

In the physical education area, Metzler, De Paepe, and Reif (1985) have likewise expressed a concern for tracking content-specific aspects of student- engaged time. These authors point out that the ALT-PE coding system uses "generic" movement categories, with no provision for noting content-specific engagement. The suggestion that "wild card" categories be included in the sub- ject matter content area so that users can enter skill-specific categories is a good one. In the BTES, content area engagement categories were specified in minute detail. One can only speculate on the degree to which a good match between cur- riculum content and achievement test content contributed to the significant corre- lations found in the BTES.

High Success Rate and Student Achievement. A final issue that has bearing , on efforts to replicate classroom findings on ALT in physical education is the role that high success rate played in making ALT a si@icant predictor of residu- alized achievement in the BTES. Recall that the definition of ALT was "time a student spends engaged in an acdemic task that he or she can perform with high success" (Fisher et al., 1981, p. 2). In a summary of the BTES findings, Marliave and Filby (1985) point out that student success is a learning behavior of equal or greater importance than allocated time or student-engaged time in predicting achievement. High success is defined as student performance of an instructional task with no errors other than careless errors; speed is not essential.

Recent studies in physical education have defined success as the number of practice trials in which correct technique was used. Silverman (1985b) found that for college students in a swimming class, number of correct practice trials was a significant predictor of achievement. At least one other study (Ashy, Lee, & Landin, 1988) has supported the notion that high success or correct perfor- mance is a significant predictor of achievement in physical education. Perhaps a measure such as number of correct trials will prove to be more generalizable across studies than broader measures of engaged time because it is more closely related to lesson content.

At the theoretical level, however, the issue of difficulty level/success rate is a troublesome one. Fisher et al. (1981) had originally proposed that degree of student success at a task would reflect both student aptitude and quality of in-

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struction. Their notion that engagement at a high success rate was a good indica- tor of learning was derived from principles of programmed instruction, with concern for control of error rates. However, evidence suggests that subjects learn- ing via a prompted or errorless strategy have an advantage at the end of practice trials over those employing a trial-and-error strategy, but that the trial-and-error subjects performed better when subsequently tested on a related version of the task (Edwards & Lee, 1985; Prather, 1971; Singer & Gaines, 1975). Apparently, learners who are required to discover solutions to problems can more effectively adapt what has been learned to a new but related situation. Lee and Magill (1985) have summarized evidence in the motor domain suggesting that practice condi- tions that require learners to re-solve a motor problem (rather than merely remem- ber the solution) will depress acquisition performance, yet enhance long-term retention of the skill.

ALT-PE as a Variable in Physical Education Research

The ways in which students and teachers spend time during instruction periods will always interest those who want to improve the teachingllearning process. The current trend is to look beyond overt behavior, to try to discover the motives and thoughts underlying behavior. Investigators using the qualitative research paradigm have shown that people construct working understandings of the social world, and that these personal understandings determine and explain behavior in social contexts such as physical education classes (Locke, 1987). The influence of this work on process-product research has been to focus interest on time spent in specific behaviors, not just global time on task. The ongoing value of the modified process-product paradigm is that the design allows testing of the relation between student behavior and student achievement and between teacher behavior and student behavior, in the same study. Since only a small portion of the total variability in student achievement test scores can be attributed to teacher behavior, it is important to study student process variables that are subject to teacher influence. Instructional time is one variable over which teachers have some control, and it will therefore continue to be a useful indicator of successful teaching and learning.

In summary, as the function of time is better understood, there may be a need to address more carefully a host of methodological issues involved in research on time and learning. To obtain the stable generalizable estimates of ALT-PE needed to validate the link with achievement, longer time periods and extremely well-defined variables should be considered. Current evidence suggests that some thought should be given to the complex issue of a balance between cognitive and motor engagement. As definitions of behaviors and tasks become more precise, the ability to connect them might improve.

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