EDUCATIONAL ERGONOMICS: EDUCATIONAL DESIGN AND EDUCATIONAL PERFORMANCE

Thomas J. Smith

Human Factors Research Laboratory Division of Kinesiology University of Minnesota Minneapolis, MN 55455

"The main challenge in the science of human learning is to understand the requirements of

educational design at all levels" (K.U. Smith and Smith, 1966, p. 478). Educational ergonomics is defined as that field of human factors/ergonomic science concerned with the interaction of educational performance and educational design. The premise of educational ergonomics is that student performance to a substantial degree is context specific---specialized in relation to specific design factors---and that ergonomic interventions directed at design improvements therefore can benefit education. This report introduces the field, delineates evidence for performance-design interaction at different educational system levels, and identifies a number of research issues and questions.

INTRODUCTION Educational ergonomics is concerned with the interdependence of educational performance and educational design. The premise of educational ergonomics, embodied in the above quote, is that the performance of students and educational systems to a substantial degree is context specific---specialized in relation to specific design factors---and that ergonomic interventions directed at design improvements therefore can benefit education. Scientifically, the field is concerned with how and why design characteristics of the educational process and system influence variability in performance of participants in the system and of the system as a whole. We assume that the scope of educational ergonomics encompasses all modes and levels of performance-design interaction that may occur in educational environments and systems. To illustrate this point, Table 1 specifies seven different classes of educational system design factors that may influence student learning, namely design features related to the academic program, the classroom, the organization and scheduling of classes, the management of the educational system, the teaching process, personal factors, and the student family and community. In the broadest sense therefore, as suggested in Table 1, the ‘design’ of the educational process refers to physical designs of instructional materials, environments, and technologies (e.g., classroom implements and equipment, textbooks, audiovisual materials and systems, work stations, computer hardware and software, school classrooms and buildings), to designs of different skills, tasks, classes of knowledge, and curricula targeted for learning, to social and interpersonal designs of the interactions of participants in the system with one another (e.g., student-teacher-staff-management relationships), and to the design, management, and administration of jobs, supervisory relationships, organizations, policies, and programs of educational systems, as well as to the designs of communities in which education occurs. ‘Variability’ in human performance not only has a strict scientific meaning (the statistical variance in dependent measures of cognitive, motor, or physiological performance), but also a practical meaning related to variable consistency, reliability, or reproducibility in learning, as well as to errors,

Table 1. Classes of educational system design factors that may influence student learning. Academic Program Classroom and Building Ergonomics Class Design Organizational Design & Management of the Educational System Teaching Factors Personal Factors Community & Family Factors ----------------------------------------------------------------------------------------------------------------------- accidents, poor quality, inefficiencies, reduced productivity, and/or lack of competitiveness in performance of students and educational systems that may arise as a consequence of poor design. From the perspective of performance-design interaction, educational ergonomics has its scientific origins in an extensive body of differential learning research dating back to the last century demonstrating that much of the variability in cognitive performance (whose development and refinement is a primary focus of education) is attributable, neither to innate ability nor to learning ability, but to specific design features of the learning environment. For some time now a passionate debate has been raging regarding the performance of the educational system in the U.S. Critics point out that SAT scores of U.S. students have dropped markedly from levels achieved in the sixties and early seventies, that U.S. students perform poorly in math and science relative to students from many other industrialized countries, and that recent national tests in geography and history show dismal results. Others counter with statistics showing that the percentage of U.S. students graduating from high school is at an all time high, as are student scores on other national achievement tests. One point of common agreement appears to be that the performance of U.S. schools can be improved. Sadly lacking in this debate has been any meaningful recognition of the contributions that human factors/ergonomic science might make to improving the performance of the educational system, relative to student and teacher participants as well as overall system management. The application of human factors/ergonomic principles and techniques, and the implementation of ergonomics programs, have achieved proven success in improving performance, productivity, competitiveness, and safety and health in many private sector, military, and public sector organizations. Unfortunately however, the benefits that the application of human factors/ergonomic science might bring to the performance of educational systems have yet to be widely recognized, although some research has been done documenting performance benefits associated with ergonomic improvements to classrooms and to computer-based educational work stations. The relevance of human factors/ergonomic principles and approaches to evaluating and upgrading educational system performance receives little or no attention in many recent analyses devoted to problems with U.S. education (Berliner and Biddle, 1995; Carnegie Foundation for the Advancement of Teaching, 1995; U.S. Department of Education, 1983; Wilson and Daviss, 1995). A possible reason for this situation was suggested by K.U. Smith and Smith (1966, p. 1): "Factors of human design long have been ignored in experimental psychology. It has been believed that learning could be studied as a general process." Although a large body of evidence regarding context

specificity in performance and learning can be cited to contradict generalized learning theory (T.J. Smith, 1994; T.J. Smith, Henning, and Smith, 1994), it is likely that the latter viewpoint still plays an influential role in educational policy development and decision-making. This is not to suggest that innate neurobiological and learning attributes do not contribute to variability in educational performance. Rather, the empirical record points to an equally prominent contribution of design factors to such performance. The 1966 Smith and Smith text remains one of the most distinctive efforts to apply a well-defined human factors/ergonomic perspective to education. The authors evaluate a broad range of design factors (such as audiovisual techniques, textbook design, training program design, programmed instruction methods) that can be expected to influence learning and educational performance. Given the publication of this work some three decades ago, the time is long overdue to explore whether the educational process and educational systems of today can benefit from the application of human factors/ergonomic principles and techniques, as has been the case with many other human systems and areas of human performance. To this end, reports in this symposium introduce the topic and address a number of different basic and applied issues in educational ergonomics. To establish terms of reference for the field, the following sections of this report outline: (1) a theoretical perspective; (2) evidence and questions regarding performance-design interaction at different levels of educational system organization; and (3) conclusions.

THEORETICAL PERSPECTIVE Conceptual understanding how and why educational performance and educational design are interdependent is informed by four theoretical models of human-system interaction: (1) behavioral cybernetics (T.J. Smith and Smith, 1987; K.U. Smith and Smith, 1966); (2) sociotechnical systems (Emery, 1969); (3) macroergonomics (Hendrick, 1986); and (4) balance theory (M.J. Smith and Carayon-Sainfort, 1989). As applied to designing complex human systems, these theories of human-system interaction all are embodied in an emerging thrust of human factors/ ergonomics termed ergonomic systems engineering (ESE)---the application of ergonomic principles and techniques to promote human factored engineering design of complex human-technological-social-institutional systems. A good example is community ergonomics (Cohen and Smith, 1994; Newman and Carayon, 1994; J.H. Smith and Smith, 1994; M.J. Smith, Carayon, Smith, Cohen, and Upton, 1994)---the application of ESE to rebuilding the inner city. Given the evident complexity of the educational system (Caldwell, 1992), it is to be hoped that educational performance likewise can benefit from the application of ergonomic systems principles and practices. All four theories cited above assume that participants in a system should have some degree of control over their interaction with system design features. Sociotechnical and macroergonomic theories both stress the participatory approach---individual participation in decision-making governing system design and direction---as key to effective system performance. Balance theory views people as the center of the system and advocates that other system elements be designed (human factored) to enhance human performance. Behavioral cybernetic theory views self-control of behavior as a biological imperative, and assumes that context specificity in performance arises as a biological consequence of closed-loop interaction between behavioral control of sensory feedback from design factors in the performance environment. System designs that assume participant interaction with the system can be controlled externally (by managers, by limiting information and/or involvement) are judged as fundamentally flawed from a biological perspective, because they ignore the essential self-regulatory nature of behavior. From this perspective, the ability of system participants to self-govern the nature and extent of their interaction with the system is the linchpin of successful system performance. Figure 1 illustrates this point with a depiction of the behavioral cybernetics of the educational system from the perspective of the student. The figure specifies an extensive series of educational system

design factors, categorized using the classification scheme in Table 1, that have the potential to influence the nature and extent of student learning (next section). The inward pointing arrows in the figure symbolize that this influence is mediated by sensory feedback to the student from different design factors. However, the figure also dramatizes a fundamental difficulty that most students in educational systems face. From a behavioral cybernetic perspective, learning is most effective if the learner not only is provided with but is able to control sensory feedback from design factors in the performance and learning environment (K.U. Smith and Smith, 1966). It may be argued that most students are unable to achieve any meaningful level of control over sensory feedback from most educational system design factors. Indeed, Figure 1 suggests that the only learning-relevant design factors which the student can control to a substantial degree are of a personal nature: native language, health status, substance abuse, and nutritional status. For some students, because of peer pressure (such as gang influence), different household and school languages, and/or impoverished family status, it is possible that even these personal factors cannot be effectively controlled. A behavioral cybernetic model of educational system performance, comparable to that shown in Figure 1, also could be developed from the perspective of the teacher. A further fundamental difficulty confronting most educational systems is that the latitude of most teachers for control of sensory feedback from system design factors does not extend much beyond that of their students. Of the design factors categorized in Table 1 and specified in Figure 1, it may be argued that teachers are only able to levy direct control over teaching factors (pedagogic style, learning theory employed, etc.) and perhaps some elements of classroom ergonomics. We may speculate therefore that the learning process in most educational systems by and large is open- rather than closed-loop, in that most design-related sources of sensory feedback expected to influence learning cannot be effectively controlled either by those targeted by or by those guiding the learning process. In behavioral cybernetic terms, it is unrealistic to expect optimal learning performance under such open loop conditions.

INTERDEPENDENCE OF PERFORMANCE AND DESIGN IN EDUCATION As noted above, educational ergonomics is concerned with all modes and levels of interaction between educational performance and educational design. Three basic questions can be raised for each type of interaction: (1) Is educational performance context specific---is there evidence for interdependence of educational performance and educational design?; (2) Can educational design be improved, and if so in what manner?: and (3) Does improved design benefit educational performance? As summarized below, there is strong affirmative support for the first question, but ample opportunity for further investigation. Student Learning and Task Design Education is defined as the acquisition of knowledge and skill. For education of the child, acquisition of general knowledge and skill in different areas may be considered the principal objective. For education and training of the adult, this objective may be combined or replaced with that of skill development for specific tasks or types of knowledge. For all ages, improvement in cognitive performance and ability is a prominent theme in education and training.

Figure 1. Behavioral cybernetics of educational ergonomics. Sensory feedback from diverse series of educational system design factors has the potential to influence the nature and extent of student learning (inward arrows). However, the student can effectively control feedback (outward arrows) from only a limited subset of these factors. What factors determine variability in cognitive performance and learning? According to conventional wisdom in experimental psychology, the two prime suspects are biological differences in innate intellectual ability, or individual differences in learning ability. If such variability depends primarily on innate differences, then skill should transfer from one cognitive task to the next, and practice should affect the degree but not the pattern of variability among subjects after learning. Conversely, if such variability is determined primarily by learning, then practice should improve performance without changing the relative distribution of scores among subjects. Findings from numerous differential cognitive learning studies dating back over one hundred years confirm neither of these predictions. Instead, the findings implicate design of the task (rather than innate or learning ability) as a major determinant of specialization in performance and learning of many types of cognitive tasks. In particular, various studies show that variance in cognitive performance attributable to task design (environmental) factors: (1) is about 30% for IQ with identical twins reared apart; (2) is less than 50% for inconsistent tasks; (3) approximates 50% for a variety of psychomotor tasks with identical twins reared apart; (4) exceeds 50% for consistent tasks; and (5) may exceed 90% for occupational tasks. Thus, variance attributable to design-specific factors is itself dependent upon task design. This work has been reviewed from different perspectives by Ackerman (1987), Adams (1987), Jones (1966, 1969), K.U. Smith and Smith (1991), and T.J. Smith, Henning, and Smith (1994). More broadly, context (design) specificity in performance represents the basic focus of ecological psychology (Gibson, 1966), and has been advanced as the defining theme of human factors/ergonomic science (T.J. Smith, 1993, 1994).

As noted above, educational ergonomics may be considered to have its empirical origins in this body of differential learning research. There are two important caveats however: (1) the research does not indicate which specific task design factors have the greatest influence on cognitive performance variability; and (2) most of the findings are based on studies of young and mature adults---the degree to which cognitive performance in children is context specific is less well defined. Student Learning and Design of the Teaching Process For our purposes, the critical issue here is how social interaction between the student/trainee and the teacher/trainer is structured or designed to mediate and promote learning. Effective student-teacher interaction requires the teacher to provide well-designed modes, sources, and levels of sensory feedback to the student in the form of instrumental, symbolic, language, and nonverbal modes of communication, and also to maintain effective behavioral control of sensory feedback that students may provide in return. Key social interactive design factors in the classroom that may influence learning include teaching "style," effective use of language and speech by the teacher, primary language of the student, degree of emphasis on reading and writing, appropriate use of visual, auditory, verbal, nonverbal, and/or symbolic modes of communication, reliance on audiovisual aids and/or computerized technology as social surrogates for teaching purposes, and the student/teacher ratio. To human factor the training process, K.U. Smith and Smith (1966, p. 466) propose two broad social interactive principles that teachers should observe: (1) encourage student self-control over the learning environment and the learning process; and (2) tailor teaching of specific knowledge and skills to the specific development stage of the student. They suggest that no one educational technique is superior to a number of techniques used in an integrated fashion, and cite evidence from educational research to support this conclusion. It is fair to say that a primary focus of educational academic programs worldwide is in this area of "how to teach." From an educational ergonomics perspective however, there are a number of provocative questions that merit closer attention. Which design feature(s) of the teaching process most critically influence student learning? Is design of the teaching process the most important human factors determinant of effective learning? What design factors most critically influence teacher performance? Student Learning and Design of Educational Materials Findings from educational research indicate that student learning may be influenced by design of educational materials (K.U. Smith and Smith, 1966, Chap. 13). For example, accompanying verbal text with appropriate visual illustrations facilitates learning by helping the student organize the material to be learned. These authors point out however that textbook design has received little attention from behavior science. With the advent of new technologies for designing and presenting educational materials that complement or replace textbooks, there is obvious need for systematic human factors/ergonomic research in this area. Student Learning and Environmental Design of the Classroom Caldwell (1992) has addressed this question in relation to the physical design of university classrooms. His research identifies chair design, air quality, and noise as primary design factors needing improvement, and provides estimates that poor classroom design and maintenance can lead to decrements of 10-25% in student performance. It is tempting to conclude that Caldwell's findings also apply to classrooms in elementary, middle, and high schools. Further research is required to ascertain which design features of the classroom environment most critically influence student performance in different types of classrooms, and for students of different ages and personal characteristics. Student Learning and Design of Educational Technology

Of all concerns of educational ergonomics, this area probably has received most attention from the human factors/ergonomics community (Eberts and Brock, 1984, 1987; K.U. Smith and Smith, 1966, Chaps. 10-12). The 1987 review by Eberts and Brock of computer-aided and computer-managed instruction technologies cites 39 educational performance areas that may be influenced by interface and/or software design features. Given the explosive growth in the use of different computers, software packages, and computer-based technologies in the classroom, there is pressing need for further research on how and to what extent student interaction with these technologies will influence student performance and learning. Are computer workstation design guidelines tailored for children needed, and if so how should they differ from adult guidelines (Grandjean, 1986)? How will designs of emerging technologies now being deployed in the classroom---presentation software, multimedia, CD-ROMs, distance learning, distributed training, the internet, the worldwide web---influence both teacher and student performance? How should teachers be trained in the effective application and use of these technologies? Which technological design features most effectively complement, and which most severely compromise, the teaching process? Relative to the latter question, delayed response feedback problems with educational computer systems cited by Eberts and Brock (1987) merit particular attention. Displaced sensory feedback, exemplified by feedback delay, is inherent to computer interfaces and has the most immediate and profoundly disruptive effects on interactive performance of any interface design feature (T.J. Smith, 1993; T.J. Smith, Henning, and Smith, 1994). There is anecdotal evidence suggesting that performance with teleconferencing systems also is disrupted by delay problems. How significant is displaced feedback as a major design source of decremental student performance with technological systems used for educational purposes? Student Learning and Educational System Design Much of the debate over education in the U.S. today focuses on design issues and problems with the educational system---that is, system policies, programs, and organizational design and management. Across a range of observers, there is a reasonable level of consensus that the following system design factors benefit student performance: decentralized control over educational decisions by individual schools; committed school principals; teacher self-responsibility for classroom management; small class size; safe, nurturing school environment; emphasis on academic core curriculum; hands-on learning; assessment approaches other than standardized tests; high performance standards and expectations; and student community service and occupational internship opportunities. A more global theme is that the system, particularly public education, needs to be made more accountable in terms of validating its policies and programs, documenting its performance, and demonstrating return on investment. There is evident overlap between a number of system design factors cited above and total quality management (TQM) principles. Although some universities have explored the implementation of educational TQM (Caldwell, 1992), use of TQM to improve system design and performance has yet to achieve meaningful acceptance in pre-university schools. This represents an obvious opportunity for human factors/ergonomic research and intervention at the system level. Educational Ergonomics and Community Quality We have now progressed from task design to community design factors as possible determinants of student performance. Among community factors, high parental involvement in schools and formation of school-community alliances are linked to good educational performance, whereas low socioeconomic and educational status of parents and poor nutrition of children are linked to poor performance. Improving the latter conditions, often encountered in urban center communities, represents a major objective of community ergonomics (M.J. Smith et al., 1994). Dramatic evidence implicating the critical influence of community design on educational performance has recently emerged with results from

standardized tests of mathematical ability and reading comprehension administered to 8th graders in public and private school districts throughout the State of Minnesota. The findings show a high correlation between test performance and poverty levels in different districts. Results for 38 Minnesota urban and suburban public school districts in the Twin Cities metropolitan area are summarized in Figure 2. The graph in Figure 2 plots the linear regression of test scores for 8th graders in different Minnesota Twin Cities metropolitan area school districts (average of mathematics and reading scores combined) as a function of poverty level, expressed as the percentage of students in different districts receiving free or low-price lunches (Saint Paul Pioneer Press, 1996). The regression is highly significant with an R-squared value of 0.77, meaning that 77 percent of variance in test scores is accounted for by regression on poverty index. The findings in Figure 2 support a number of compelling conclusions. First, poverty is manifestly a design factor, varying in a manner that is largely independent of biological factors such as race, gender, and IQ. Second, it is rare in socio-educational science to be able to account for over three-fourths of the variance in a dependent performance variable with a single independent variable. That such a high degree of dependence of test performance on poverty level is in fact observed implies that remedial strategies unrelated to underlying prevailing poverty conditions will at best address only 23 percent of the variance in test scores for Twin Cities area 8th graders. This point underscores a key conclusion regarding the interaction of educational performance and community design, which is that the aims and objectives of educational ergonomics and community ergonomics are intimately coupled. The primary aim of community ergonomics is to reduce poverty in the inner city through application of principles and methods of ergonomic systems engineering directed at improving socioeconomic design characteristics of inner city communities (Cohen and Smith, 1994; Newman and Carayon, 1994; J.H. Smith and Smith, 1994; M.J. Smith et al., 1994). Community ergonomic interventions that yield improved quality in community conditions and thereby reduce community poverty levels therefore also should yield improved educational system performance in community schools.

Figure 2. Average 1996 math/reading scores for Minnesota 8th graders by school district, in relation to poverty index for different districts (based on data reported in Saint Paul Pioneer Press, 1996).

DISCUSSION AND CONCLUSIONS The underlying premise of educational ergonomics is that educational performance, to a substantial degree, is context specific. The foregoing analysis suggests that student performance in educational systems is linked to design factors at every level of system organization, from the task to the classroom to the institution to the surrounding community. This in turn implies that problems and issues confronting education today should be amenable to human factors/ergonomic approaches and interventions. From a behavioral cybernetic perspective however, as depicted in Figure 1 and discussed earlier, a primary obstacle to the success of such interventions is constraints on the abilities of both students and teachers to effectively control sensory feedback from the preponderance of design factors that may influence learning. To demand effective performance from these primary participants in the learning process, while denying them the opportunity for closed-loop control over so many of these factors, almost guarantees a dysfunctional system. We may speculate that many problems with education and educational systems may be attributable, at least in part, to this lack of system cybernetics. A major objective of educational ergonomics therefore should be to promote more extensive and diverse modes of closed-loop interaction between system participants and system design factors at all levels. There are numerous unanswered questions regarding educational ergonomics that provide ample opportunity for further research. From a scientific perspective, the major challenge for educational ergonomics is to delineate which design factors are the most critical contributors to variability in educational performance at the individual and system levels. From a practical perspective, the challenge

is to target human factors/ergonomic intervention strategies for improving such performance. From a systems perspective, the challenge and mission of educational ergonomics is to target improvements in educational system designs that facilitate education and learning for students of all ages in a continuous process of life-span development. Relative to both of these perspectives, a series of questions can be specified directed at both scientific and practical issues that remain unresolved. Scientific Issues and Questions 1. What physical design factors related to the learning environment (e.g., textbook, audiovisual,

work station, technology, classroom, and/or school ergonomics) have the greatest influence on variability in student and teacher performance?

2. What design factors related to the learning task (e.g., skill and proficiency requirements, classes of

knowledge, curriculum) have the greatest influence on variability in student and teacher performance?

3. What social and organizational design factors related to the learning environment (e.g., student-

teacher-staff-management-system interactive relationships) have the greatest influence on variability in student and teacher performance?

4. What educational system design factors (e.g., educational jobs, supervisory relationships,

organizations, policies, and programs) have the greatest influence on variability in student and teacher performance?

5. What poverty-linked community design factors have the greatest influence on variability in student

and teacher performance? 6. Relative to cognitive and learning performance of adults, to what degree is cognitive and learning

performance of children context specific and influenced by design factors? 7. To what degree is context-specific cognitive and learning performance in children influenced by

such innate factors as gender, age, and cultural and ethnic differences? Practical Issues and Questions 1. Can practical benefits in educational performance of students and teachers be demonstrated by

making ergonomic improvements in educational design? 2. Will the educational performance of students and teachers benefit from the application and

implementation of principles and techniques of quality management in educational systems? 3. How can students and teachers be provided broader control over different design factors known

to influence learning performance? What design factors should be prioritized and targeted for such control?

4. Is improved educational performance of students and teachers one of the practical benefits of a

community ergonomics program? If so, what ergonomic improvements in community design will have the greatest influence on such performance?

5. In practical applications, should educational and community ergonomics initiatives be introduced in an integrated fashion? If so, what is the most effective approach to achieve such integration?

6. How can principles, techniques, and potential benefits of human factors/ergonomics be most

effectively communicated to the education community?

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