Behaviorism Instructional Applications

Skinner (1954, 1961, 1968, 1984) wrote extensively concerning the application of his tenets to the resolution of educational quandaries. He maintained that an undue reliance was placed upon aversive control. Whilst students are seldom subjected to corporal chastisement, their application to assignments oft proceeds not from a desire for erudition or intrinsic enjoyment, but rather from an aversion to punishments such as pedagogic censure, deprivation of privileges, and summons to the Principal's office.

A further concern resides in the infrequency of reinforcement, and its oft untimely bestowal. Educators devote but a modicum of time to each student daily. Whilst students are engaged in solitary pursuits, a considerable interval may elapse between the completion of an assignment and the receipt of pedagogic feedback. Consequently, students may imbibe incorrect notions, necessitating the expenditure of further pedagogical effort in the provision of corrective feedback.

A third contention is that the compass and sequence of curricula do not ensure the acquisition of skills by all students. Students do not assimilate knowledge at a uniform pace. In an effort to encompass the totality of the material, educators may advance to the subsequent lesson prior to the complete mastery of the preceding one by all students.

Skinner averred that these, and other, impediments, are not amenable to resolution through the augmentation of educators' remuneration (albeit a desirable outcome!), the extension of the school day or year, the elevation of standards, or the stringent enforcement of teacher certification requirements. Rather, he advocated a more judicious utilisation of instructional time. Given the impracticality of expecting students to progress through the curriculum at a uniform rate, the individualisation of instruction would enhance efficacy.

Skinner posited that pedagogy necessitates the proper orchestration of reinforcement contingencies. No novel principles are requisite in the application of operant conditioning to education. Instruction is rendered more efficacious when (1) educators present the material in graduated increments, (2) learners actively engage, rather than passively attend, (3) educators furnish feedback immediately following learners' responses, and (4) learners progress through the material at their own volition.

The fundamental process of instruction entails shaping. The objective of instruction (desired behaviour) and the students' initial behaviour are identified. Substeps (behaviours) conducive to progression from the initial to the desired behaviour are formulated. Each substep represents a modest modification of its predecessor. Students are guided through the sequence utilising diverse approaches, encompassing demonstrations, small-group endeavours, and individual seat work. Students actively respond to the material and receive immediate feedback.

This instructional methodology necessitates the precise specification of learners' extant knowledge and desired objectives in terms of learners' actions. Desired behaviours are oft specified as behavioural objectives, a matter to be shortly addressed. Individual variations are accommodated by commencing instruction at learners' current performance levels and permitting progression at their own pace. Given the prevailing pedagogical practices within our educational system, these aims may appear impractical: Educators would be compelled to initiate instruction at disparate junctures and encompass material at varying rates for individual students. Programmed instruction circumvents these difficulties: Learners commence at the point in the material commensurate with their performance levels, and progress at their own volition.

The remainder of this section delineates certain instructional applications that incorporate behaviouristic tenets. Not all of these applications are derived from Skinner's, or other, theories covered in this chapter, but they all reflect, to some extent, key notions of behaviourism.

Behavioral objectives are unambiguous declarations delineating the intended student outcomes ensuing from instruction. Objectives may span a spectrum from the general to the remarkably specific. General or ill-defined objectives, such as 'to augment student awareness,' may be satisfied by virtually any form of pedagogy. Conversely, objectives of excessive specificity, documenting each minute alteration in student conduct, prove time-consuming to formulate and may obscure the paramount learning outcomes for educators. The most efficacious objectives, thus, reside betwixt these extremes.

A behavioral objective delineates the actions students undertake in demonstrating their attainments, and the means by which educators ascertain student progress (Mager, 1962). The constituent elements of a sound objective are fourfold:

1. The specified cohort of students.
2. The manifest behaviours students are to enact as a consequence of instructional activities.
3. The conditions or contexts wherein the students are to execute the behaviours.
4. The criteria for assessing student conduct, to ascertain whether objectives have been satisfied.

A specimen objective, with its constituent parts identified, is thus: 'Given eight addition problems involving fractions of dissimilar denominators (3), the fourth-grade arithmetic student (1) shall inscribe the correct sums (2) for at least seven of these (4).'

Behavioral objectives may serve to determine the cardinal learning outcomes, which aid in lesson schematisation and testing to assess learning. The formulation of objectives further assists instructors in determining the content students are capable of mastering. Given unit-teaching objectives and a predetermined temporal allotment for their coverage, instructors may adjudicate which objectives are paramount, and focus their efforts accordingly. Although objectives for lower-level learning outcomes (knowledge, comprehension) are generally more facile to specify, sound behavioral objectives may yet be penned to assess higher-order outcomes (application, analysis, synthesis, evaluation).

Research indicates that students furnished with behavioral objectives exhibit superior verbatim recall of verbal information, in contrast to students without such objectives (Faw & Waller, 1976; Hamilton, 1985). Objectives may cue students to process the information at the apposite level; thus, when students are furnished with objectives necessitating recall, they engage in rehearsal and other strategies conducive to this mode of recall. Research further suggests that providing students with objectives does not enhance the learning of material unrelated to said objectives (Duchastel & Brown, 1974), implying that students may concentrate on learning material relevant to the objectives, and disregard other material.

The impact of objectives upon learning is contingent upon students' prior experience with them, and upon the perceived importance of the information at hand. Training in the utilisation of objectives, or familiarity with criterion-based instruction, engenders superior learning compared to the absence of such training or familiarity. When students are capable of independently determining which material is of import to learn, the provision of objectives does not facilitate learning. Informing students of the objectives appears more critical when students are unsure as to which material is of import. Furthermore, Muth, Glynn, Britton, and Graves (1988) ascertained that textual structure may moderate the effect of objectives on learning. Information rendered salient by virtue of its prominent placement (e.g., early in a text, or highlighted) is recalled with fidelity, even in the absence of explicit objectives.

Operant theory doth presage that environmental variables exert an influence upon the scholastic endeavours of students. A cardinal environmental variable is that of learning time.

Carroll (1963, 1965) did formulate a model of school learning, placing primary emphasis upon the instructional variable of time spent in learning. Students do successfully learn to the extent that they allocate the requisite time to the task at hand. Time, in this context, doth signify academically engaged time, or time spent attending and endeavouring to learn. Albeit time is an environmental (observable) variable, this definition is cognitive, extending beyond a simple behavioral indicator of clock time. Within this framework, Carroll postulated factors influencing both the time required for learning and the time actually devoted thereto.

Time Required for Learning. One such influence upon this factor is aptitude for learning the task. Learning aptitude doth depend upon the extent of prior task-relevant learning and upon personal characteristics, such as abilities and attitudes. A second, related factor is the ability to comprehend instruction. This variable doth interact with instructional method; for example, some learners comprehend verbal instruction well, whilst others benefit more from visual presentations.

Quality of instruction referreth to the efficacy with which the task is organised and presented to learners. Quality doth encompass that which learners are apprised of regarding what they shall learn and how they shall learn it, the extent to which they have adequate contact with the learning materials, and the quantum of prerequisite knowledge acquired prior to learning the task. The lower the quality of instruction, the more time learners shall require to learn.

Time Spent in Learning. Time allowed for learning is one influence upon this factor. The school curriculum includeth so much content that time allotted for a particular type of learning is oft less than optimal for certain students. When teachers present material to the entire class concurrently, some learners are more likely to experience difficulty grasping it and shall require additional instruction. When students are ability grouped, the amount of time devoted to different content doth vary depending upon the ease with which students learn.

A second influence is the time the learner is willing to expend in learning. Even when learners are afforded ample time to learn, they may not devote that time to productive endeavour. Whether due to low interest, high perceived task difficulty, or other factors, students may not be motivated to persist at a task for the duration required to learn it. Carroll incorporated these factors into a formula to estimate the degree of learning for any student on a given task:

degree of learning = time spent/time needed

Ideally, students should spend precisely the time required to learn (degree of learning = 1.0), yet learners typically spend either more time (degree of learning > 1.0) or less time (degree of learning < 1.0) than is requisite.

Carroll’s model doth highlight the importance of academic engaged time required for learning and the factors influencing time spent and time needed to learn. The model doth incorporate valid psychological principles, albeit only at a general level, as instructional or motivational factors. It doth not explore cognitive engagement in depth. Carroll (1989) admitted that further research was needed to complete the details. As discussed in the next section, mastery learning researchers, who have systematically investigated the time variable, have furnished greater specificity.

In accordance with that which Skinner (1968) contended, many educators have decried the manner in which time is misspent (Zepeda & Mayers, 2006). The time variable is central to current discussions on means to maximise student achievement. For example, the No Child Left Behind Act of 2001 greatly expanded the role of the federal government in elementary and secondary education (Shaul & Ganson, 2005). Albeit the act did not specify the quantum of time to be devoted to instruction, its requirements for student achievement and its accountability standards, combined with sundry writers calling for better utilisation of time, have led school systems to re-examine their employment of time to ensure improved student learning.

One consequence is that many secondary schools have abandoned the traditional six hour schedule in favour of block scheduling. Albeit there exist variations, many employ the A/B block, wherein classes meet on alternate days for extended periods per day. Presumably block scheduling doth permit teachers and students to explore content in greater depth than was often possible with the traditional shorter class periods (e.g., 50 minutes).

Given that block scheduling is yet relatively novel, there is not a surfeit of research assessing its effectiveness. In their review, Zepeda and Mayers (2006) found that block scheduling may improve school climate and students’ grade-point averages, yet studies showed inconsistent results for student attendance and scores on standardised tests. As block scheduling becomes more common, we may expect more research that shall clarify these inconsistencies.

Another means for increasing time for learning is through out-of-school programs, such as after-school programs and summer school. Compared with research on block scheduling, research on the effects of out-of-school programs doth exhibit greater consistency. In their review, Lauer et al. (2006) found positive effects for such programs on students’ reading and mathematics achievement; effects were larger for programs with enhancements (e.g., tutoring). Mahoney, Lord, and Carryl (2005) found benefits of after-school programs on children’s academic performances and motivation; results were strongest for children rated as highly engaged in the after-school program’s activities. Consistent with Carroll’s model, we might conclude that out-of-school programs are successful to the extent that they focus upon student learning and furnish supports to encourage it.

Carroll's model doth presage that if students do vary in aptitude for the learning of a subject, and if all receive the same quantum and type of instruction, their achievements shall differ. Yet, should the quantum and type of instruction be varied, contingent upon individual differences amongst learners, then each student hath the potential to demonstrate mastery; the positive relation betwixt aptitude and achievement shall vanish, for all students shall demonstrate equal achievement, irrespective of their aptitudes.

These notions form the very bedrock of mastery learning (Anderson, 2003; Bloom, 1976; Bloom, Hastings, & Madaus, 1971). Mastery learning doth incorporate Carroll's tenets into a systematic instructional plan, encompassing the defining of mastery, planning for mastery, teaching for mastery, and grading for mastery (Block & Burns, 1977). Mastery learning doth harbour cognitive elements, albeit its formulation doth seem more behavioural in nature, when compared to many a current cognitive theory.

To define mastery, teachers shall prepare a compendium of objectives and a final (summative) examination. The level of mastery shall be established (e.g., where A students typically perform under traditional instruction). Teachers shall cleave the course into learning units, mapped against course objectives.

Planning for mastery doth imply that teachers shall plan instructional procedures for themselves and their students, to include corrective feedback procedures (formative evaluation). Such evaluation typically doth assume the form of unit mastery tests, that set mastery at a given level (e.g., 90%). Corrective instruction, which is employed with students who fail to master aspects of the unit's objectives, is given in small-group study sessions, individual tutorials, and supplemental materials.

At the outset of teaching for mastery, teachers shall orient students to the mastery procedures and provide instruction, using the entire class, small groups, or individual seat work activities. Teachers shall administer the formative test and certify which students achieve mastery. Students who fall short mayhap work in small groups, reviewing troublesome material, often with the aid of peer tutors who have mastered the material. Teachers shall afford students time to labour on remedial materials, along with homework. Grading for mastery doth include a summative (end-of-course) test. Students who score at or above the course mastery performance level shall receive A grades; lower scores shall be graded accordingly.

The emphasis on student abilities as determinants of learning mayhap seem uninteresting, given that abilities generally do not alter much as a result of instructional interventions. Bloom (1976) also stressed the importance of alterable variables of schooling: cognitive entry behaviours (e.g., student skills and cognitive processing strategies at the outset of instruction), affective characteristics (e.g., interest, motivation), and specific factors influencing the quality of instruction (e.g., student participation, type of corrective feedback). Instructional interventions can improve these variables.

Reviews of the effect of mastery learning on student achievement are mixed. Block and Burns (1977) generally found mastery learning more effective than traditional forms of instruction. With college students, Péladeau, Forget, and Gagné (2003) obtained results showing that mastery learning improved students’ achievement, long-term retention, and attitudes toward the course and subject matter. Kulik, Kulik, and Bangert-Drowns (1990) examined more than 100 evaluations of mastery learning programs and found positive effects on academic performances and course attitudes among college, high school, and upper-grade elementary school learners. They also found that mastery learning may increase the time students spend on instructional tasks. In contrast, Bangert, Kulik, and Kulik (1983) found weaker support for mastery learning programs. They noted that mastery-based instruction was more effective at the college level than at lower levels. Its effectiveness undoubtedly depends on the proper instructional conditions (e.g., planning, teaching, grading) being established (Kulik et al., 1990).

Students participating in mastery instruction oft spend more time in learning, compared with learners in traditional classes (Block & Burns, 1977). Given that time is at a premium in schools, much mastery work—especially remedial efforts—must be accomplished outside of regular school hours. Most studies show smaller effects of mastery instruction on affective outcomes (e.g., interest in and attitudes toward the subject matter) than on academic outcomes.

An important premise of mastery learning is that individual differences in student learning decrease over time. Anderson (1976) found that when remedial students gained experience with mastery instruction, they gradually required less extra time to attain mastery, because their entry-level skills improved. These results imply cumulative benefits of mastery learning. There remains, however, the question of how much practice is enough (Péladeau et al., 2003). Too much repetitive practice might negatively affect motivation, which will not promote learning. These points require further research, but have important instructional implications.

Programmed instruction (PI) doth refer to instructional materials develop'd in accordance with operant conditioning principles of learning (O’Day, Kulhavy, Anderson, & Malczynski, 1971). In the 1920s, Sidney Pressey did design machines to use primarily for testing. Students were presented with multiple-choice questions, and they press'd a button corresponding to their choice. If students responded correctly, the machine presented the next choice; if they responded incorrectly, the error was recorded and they continu'd to respond to the item.

Skinner reviv'd Pressey’s machines in the 1950s and modified them to incorporate instruction (Skinner, 1958). These teaching machines presented students with material in small steps (frames). Each frame requir'd learners to make an overt response. Material was carefully sequenc'd and broken into small units to minimise errors. Students receiv'd immediate feedback on the accuracy of each response. They mov'd to the next frame when their answer was correct. When it was incorrect, supplementary material was provided. Although errors did occur, the programs were design'd to minimise errors and ensure that learners typically succeeded (Benjamin, 1988).

There art many benefits when students generally perform well, but as noted earlier, research suggests that preventing errors may not be desirable. Dweck (1975) found that an occasional failure increased persistence on difficult tasks more than did constant success. Further, constant success is not as informative of one’s capabilities as is occasionally having difficulty because the latter highlights what one can and cannot do. This is not to suggest that teachers should let students fail, but rather that under the proper circumstances students can benefit from tasks structur'd so that they occasionally encounter difficulty.

PI doth not require the use of a machine; a book by Holland and Skinner (1961) is an example of PI. To-day, however, most PI is computeris'd and many computer instructional programs incorporate principles of behavioral instruction.

PI incorporates several learning principles (O’Day et al., 1971). Behavioral objectives specify what students should perform on completion of the instruction. The unit is subdivid'd into sequenc'd frames, each of which presents a small bit of information and a test item to which learners respond. Although a lot of material may be included in the program, the frame-to-frame increments art small. Learners work at their own pace and respond to questions as they work through the program. Responses may require learners to supply words, provide numerical answers, or choose which of several statements best describes the idea being presented. Feedback depends on the learner’s response. If the learner is correct, the next item is given. If the learner answers incorrectly, additional remedial information is presented and the item is tested in slightly different form.

Because PI reflects shaping, performance increments art small and learners almost always respond correctly. Linear and branching programs art distinguish'd according to how they treat learner errors. Linear programs art structur'd in such a way that all students proceed through them in the same sequence (but not necessarily at the same rate). Regardless of whether students respond correctly or incorrectly to a frame, they move to the next frame where they receive feedback on the accuracy of their answer. Programs minimise errors by covering the same material in more than one frame and by prompting student responses.

Branching programs art set up so that students’ movement through them depends on how they answer the questions. Students who learn quickly skip frames and bypass much of the repetition of linear programs, whereas slower learners receive additional instruction. A disadvantage is that branching programs may not provide sufficient repetition to ensure that all students learn concepts well.

Research suggests that linear and branching programs promote student learning equally well and that PI is as effective as conventional classroom teaching (Bangert et al., 1983; Lange, 1972). Whether PI is us'd instead of traditional instruction depends in part on how well existing programs cover the requir'd scope and sequence of instruction. PI seems especially useful with students who demonstrate skill deficiencies; working through programs provides remedial instruction and practice. PI also is useful for independent study on a topic.

Programmed instruction in computer format is a type of computer-based instruction (CBI). Until a few years ago, CBI was the most common application of computer learning in schools (Jonassen, 1996; to-day it is the Internet). CBI often is us'd for drills and tutorials. Whereas drills review information, tutorials art interactive: They present information and feedback to students and respond based on students’ answers (e.g., branching programs).

Studies investigating CBI in college courses yield beneficial effects on students’ achievement and attitudes (Kulik, Kulik, & Cohen, 1980). Several CBI features art firmly grounded in learning theory and research. Computers command students’ attention and provide immediate feedback, which can be of a type typically not given in class (e.g., how present performances compare with prior performances to highlight progress). Computers individualise content and rate of presentation.

Although drills and tutorials place strict limitations on how students interact with material, one advantage of CBI is that it can be personalis'd: Students enter information about themselves, parents, and friends, which is then included in the instructional presentation. Personalisation can produce higher achievement than other formats (Anand & Ross, 1987; Ross, McCormick, Krisak, & Anand, 1985). Anand and Ross (1987) gave elementary children instruction in dividing fractions according to one of three problem formats (abstract, concrete, personalis'd):

(Abstract) There art three objects. Each is cut in half. In all, how many pieces would, there be?
(Concrete) Billy had three candy bars. He cut each of them in half. In all, how many pieces of candy did Billy have?
(Personalis'd for Joseph) Joseph’s teacher, Mrs. Williams, surpris'd him on December 15 when she presented Joseph with three candy bars. Joseph cut each one of them in half so that he could share the birthday gift with his friends. In all, how many pieces of candy did Joseph have? (pp. 73–74)

The personalis'd format led to better learning and transfer than the abstract format and to more positive attitudes toward instruction than the concrete format.

A contingency contract doth represent an agreement 'twixt teacher and student, specifying what work the student shall accomplish and the expected outcome (reinforcement) f'r successful performance (Homme, Csanyi, Gonzales, & Rechs, 1970). A contract can beest madeth verbally, though 't beest usually written. Teachers can devise the contract and asketh if 't beest true the student agrees with 't, but 't beest customary f'r teacher and student to formulate 't jointly. An advantage of joint participation is yond students may feeleth moo committed to fulfilling the contract’s terms. When folk doth participate in goal selection, they oft art moo committed to attaining the goal than when they art excluded from the selection process (Locke & Latham, 1990).

Contracts specify goals or expected outcomes in terms of particular behaviours to beest displayed. The “contingency” is the expected outcome, which oft can beest reduced to, “If thee doth this, then thee shall receiveth yond.” The behaviours should beest specific—f'r example, “I shall complete pages 1–30 in mine own math book with at least 90% accuracy,” or “I shall stayeth in mine own seat during reading period.” General behaviours (e.g., “I shall worketh on mine own math” or “I shall behave appropriately”) art unacceptable. With young children, time frames should beest brief; howev'r, objectives can cov'r moo than one time, such as successive 30-minute periods or during each social studies period f'r one week. Contracts may includeth academic and nonacademic behaviours

Developing contracts with students and monitoring progress is time consuming. Fortunately, most learners doth not require contracts to behave appropriately or accomplish work. Contracts seemeth especially helpful as a means of assisting students to worketh on assignments moo productively. A lengthy, long-term assignment can beest subdivided into a series of short-term goals with due dates. This type of plan helps students keepeth up with the work and turn in material on time.

Contracts art bas'd on the principle yond goals yond art specific, temporally close at hand, and difficult but attainable shall maximize performance (Schunk, 1995). Contracts eke conveyeth information to students about their progress in completing the task. Such information on progress raiseth student motivation and achievement (Locke & Latham, 1990). Contracts shouldst promote achievement if 't beest true they reinforce student progress in learning or in accomplishing moo on-task behaviour.

Behaviorism, as epitomised in conditioning theories, held sway over the psychology of learning for the initial half of the twentieth century. These theories elucidate learning by recourse to environmental occurrences. Mental processes are deemed unnecessary to account for the acquisition, maintenance, and generalisation of behaviour.

The learning theories propounded by Thorndike, Pavlov, and Guthrie are of historical significance. Albeit these theories diverge, each posits learning as a process of forming associations between stimuli and responses. Thorndike averred that responses to stimuli are bolstered when succeeded by gratifying consequences. Pavlov experimentally demonstrated how stimuli could be conditioned to elicit responses by being paired with other stimuli. Guthrie hypothesised that a contiguous relation between stimulus and response established their pairing. Though these theories are no longer tenable in their original guise, many of their tenets are evident in current theoretical perspectives. These theories, coupled with the research they engendered, aided in establishing the psychology of learning as a legitimate field of study.

Operant conditioning, the learning theory formulated by B. F. Skinner, is predicated on the assumption that features of the environment (stimuli, situations, events) serve as cues for responding. Reinforcement strengthens responses and augments their future likelihood of occurring when the stimuli are present. It is not requisite to invoke underlying physiological or mental states to explicate behaviour.

The basic operant conditioning model is a three-term contingency involving a discriminative stimulus (antecedent), response (behaviour), and reinforcing stimulus (consequence). The consequences of behaviours determine the likelihood that persons shall respond to environmental cues. Consequences that are reinforcing augment behaviour; consequences that are punishing diminish behaviour. Sundry other salient operant conditioning concepts are extinction, generalisation, discrimination, primary and secondary reinforcers, reinforcement schedules, and the Premack Principle.

Shaping is the process employed to alter behaviour. Shaping entails reinforcing successive approximations of the desired behaviour toward its desired form or frequency of occurrence. Complex behaviours are formed by chaining together simple behaviours in successive three-term contingencies. Behaviour modification programmes have been commonly applied in diverse contexts to promote adaptive behaviours. Self-regulation is the process of bringing one’s behaviours under self-selected stimulus and reinforcement control.

The generality of operant conditioning principles has been challenged by cognitive theorists who contend that, by ignoring mental processes, operant conditioning proffers an incomplete account of human learning. Stimuli and reinforcement may explicate some human learning, but much research demonstrates that to explicate learning, and especially higher-order and complex learning, one must take into account persons’ thoughts, beliefs, and feelings.

Operant principles have been applied to many aspects of teaching and learning. These principles can be discerned in applications involving behavioural objectives, learning time, mastery learning, programmed instruction, and contingency contracts. Research evidence generally evinces positive effects of these applications on student achievement. Irrespective of theoretical orientation, one can apply behavioural principles to facilitate student learning and achievement.