model of affective learning for nonformal science education facilities

Model of Affective Learning for Nonformal Science Education Facilities

Joyce E. Meredith,1 Rosanne W. Fortner,2 Gary W. Mullins2

1West Virginia University, 611 Knapp Hall, P.O. Box 6031, Morgantown,West Virginia 26506-6031

2The Ohio State University, 210 Kottman Hall, 2021 Coffey Road, Columbus, Ohio 43210

Received 22 May 1996; revised 6 May 1997; accepted 29 May 1997

Abstract: Objective setting and evaluation for learning in the affective domain are often neglected ineducational programs, largely because affective learning is a poorly understood phenomenon. This is par-ticularly problematic in nonformal science education facilities, which are uniquely suited to facilitate af-fective learning. To address this problem, a heuristic model of affective learning in nonformal education-al facilities was developed. The model, referred to as the Meredith Model, displays a sequence of eventsoccurring in the affective responses of learners in nonformal educational experiences and identifies factorswhich may influence individual events within this sequence. The model is proposed as a conceptual frame-work for gaining an increased understanding of affective learning and for making recommendations forpractice of nonformal science education and for further research. J Res Sci Teach 34: 805–818, 1997.

Introduction

Science centers, zoos, nature centers, parks, and other nonformal science education facili-ties offer excellent opportunities for science learning outside the formal classroom. However,nonformal science education facilities are inherently different from the formal science class-room, and hence must be addressed differently with respect to objective setting, teachingmethodology, evaluation strategies, and research to inform practice. The literature on nonformaleducation documents many such differences. Visitors to nonformal science education facilitiesare often elective learners engaged in a blend of leisure and learning. They may be intergener-ational family groups, other social groups, or groups of schoolchildren of all ages. They maylive within the same region as the nonformal science education facility, or they may hail froma diversity of geographic locations. As Busque (1991) and Falk, Koran, and Dierking (1986)noted, these learners display considerably more heterogeneity with respect to age, social group-ing, and background than do learners in formal educational settings. Bitgood (1988) enumer-ated other differences between formal and nonformal learning. He noted that formal educationfeatures a sustained exposure to learning material, while exposures in nonformal education areusually short in duration. Nonformal learners may visit the learning setting for no more than an

JOURNAL OF RESEARCH IN SCIENCE TEACHING VOL. 34, NO. 8, PP. 805–818 (1997)

© 1997 John Wiley & Sons, Inc. CCC 0022-4308/97/080805-14

Correspondence to: J.E. Meredith

hour or two, while formal learners are likely to revisit the same classroom for a semester orschool year. Bitgood also noted that learning in nonformal settings is usually free choice so thatwhat is learned is prescribed by the learner rather than the educator. Another difference notedby Bitgood is the structured, unchanging environment of the formal classroom versus the vari-able, novel setting of the nonformal educational setting. Indeed, even same-age school studentswho visit such facilities as part of their formal, prescribed educational program (field trips, etc.)will likely respond to the educational stimuli in these novel and highly sensory settings quitedifferently from the way they do stimuli in the formal classroom (Flexner & Borun, 1984). Falkand Balling (1978), in their study of the novel field trip phenomenon, demonstrated that “nov-elty, and the very powerful needs for exploration it generates, is an extremely important educa-tional variable” (p. 133).

The task of determining and meeting the learning needs of the diverse population servedby nonformal science education facilities presents an enormous challenge for nonformal educa-tors. Nonformal education is a professional field still in its youth, and has suffered since its be-ginnings from a lack of effective evaluation strategies and clearly defined goals (Mullins, 1984).A good example of this lack of knowledge was revealed when curators at the Children’s Muse-um of Indianapolis, Indiana, learned that many of their visitors experienced the museum as moreentertaining than educational (Ault, 1987). To begin to address the problem of setting clear ob-jectives in nonformal education, all domains of learning which occur in nonformal educationalsettings must be addressed.

Krathwohl, Bloom, and Masia (1964) found that most educational objectives can be placedinto three major learning domains: cognitive, affective, and psychomotor. Learning in nonfor-mal science education facilities may potentially span all three learning domains. However, thereis both professional opinion and empirical research which suggest that the major advantages oflearning activities in nonformal educational settings over those in formal settings may lie in theaffective domain. For example, Miles and Tout (1979) speculated, “the affective aspects of thelearning process . . . perhaps carry slightly more weight in the museum than in formal educa-tion” (p. 212). Koran and Baker (1979), in a review of the literature, reported “that field tripsusually do not exceed classroom learning on measures of knowledge gained or content learned. . . but that the major justification for field trips should be unique outcomes that arise from thefield trip setting (for example, interest, motivation, psychological rejuvenation for teachers andstudents, and so forth)” (p. 56). Flexner and Borun (1984) found that the fifth and sixth gradersthey studied did not demonstrate more cognitive learning at a participatory science museum ex-hibit, but did describe the experience as more enjoyable and interesting than the related class-room lesson.

Affect was broadly defined by English and English (1958) as “a class name for feeling,emotion, mood, temperament” (p. 15). Krathwohl et al. (1964) described affective learning ob-jectives as those which “emphasize a feeling tone, an emotion, or a degree of acceptance or re-jection” (p. 7). Ellis and Fouts (1996) defined the affective domain as “the area of education thatfocuses on the attitudinal/emotional development of students” (p. 9). While some obvious over-lap exists between these definitions, affect has historically been notoriously difficult to define,and equally difficult to measure. Roberts (1990) wrote, “The role of affective modes of know-ing in learning processes remains an elusive, fragmented area of study. Not only does researchcross many disciplinary boundaries, but language about affect changes from one individual tothe next” (p. 19). The situation has improved little since Krathwohl et al. (1964) noted the dearthof evaluative tools and research-based evidence on affect which motivated them to construct theTaxonomy of educational objectives for the affective domain.

806 MEREDITH, FORTNER, AND MULLINS

If a strength of nonformal science education is to facilitate affective learning, what affec-tive goals should nonformal educators target, how can they best attain these goals, and how willthe attainment of these goals benefit the learner? To answer these questions, a better under-standing of affect as it relates to learning in nonformal science education facilities is clearlyneeded.

The problem investigated in this study was as follows: Affective learning by learners innonformal science education facilities is a highly important yet poorly understood construct.Thus, the purpose of the study was to develop a heuristic model of affect as it occurs with learn-ers in nonformal science education facilities to provide for enhanced understanding of affectwithin the profession of nonformal science education. The results model is proposed as a frame-work to guide educational objective setting, evaluation, research, and data collection in nonfor-mal science education.

Review of Literature

The complex and often difficult to define concept of affect has been approached from a va-riety of theoretical perspectives by researchers and scholars in a variety of fields. One of themost comprehensive treatments of affect in the education literature is that of Krathwohl et al.(1964), who produced a Taxonomy of educational objectives for the affective domain as a se-quel to that for the cognitive domain (Bloom, 1956) after the usefulness of the latter becamewidely apparent. The taxonomy consists of a five-category hierarchical scale: receiving, re-sponding, valuing, organization, and characterization by a value complex. While this treatmentof affect is indeed thorough, it was formulated as a framework for formal education and doesnot address the unique attributes of the nonformal educational setting. It also does little to elu-cidate the mechanism(s) or sequence of events by which affect may be stimulated.

In the psychological literature, Bull (1951) (cited by Izard, Wehmer, Livsey, & Jennings,1965) presented a sequence of events for the affective response which emphasized motor andneurophysiological processes. In Bull’s view, the first response to a stimulus is a neural predis-position which leads to a physical readiness to take action. The affect which follows is an aware-ness of this readiness to act. Action then completes the sequence.

Emotion is a term that is consistently associated with the construct of “affect” (English &English, 1958; Krathwohl et al., 1964; Ellis & Fouts, 1996). Beginning with a historical reviewand evaluation of existing theories of emotion, Arnold (1960) integrated a phenomenologicalanalysis of the human experience of emotion with empirical evidence from numerous re-searchers to form a well-developed psychological theory of emotion. In Arnold’s theory, the af-fective response begins with a perception of the stimulus, followed by a cognitive appraisal.The emotion which follows is a felt tendency toward or away from the stimulus, depending onthe appraisal that was made. Action, such as approach or withdrawal, completes the sequence.Central to Arnold’s theory is the idea that emotion is a motivational force.

Much like Arnold (1960), Plutchik (1980) saw the first event upon encountering a stimulusto be a cognitive appraisal of the stimulus. This is followed by the experience of the emotion,and then a behavioral reaction such as withdrawal or approach. Although the terminology is dif-ferent, this sequence appears virtually identical to that of Arnold. The difference is that Plutchikadded function as the end of the sequence. This is in keeping with his theory that emotions servean adaptive function (i.e., protection or reproduction) for the organism.

Buck’s (1984) model of emotion suggests a sequence of events which departs from thoseof Arnold (1960) and Plutchik (1980). Buck asserted that affective stimuli act directly on an af-

A MODEL OF AFFECTIVE LEARNING 807

fective system that is associated with neurochemical systems of the body. Thus, Buck did notaccept that a cognitive appraisal precedes the experience of emotion. Emotion was seen by Buckas consisting of adaptive and homeostatic mechanisms which produce physiological responses,expressive tendencies which lead to facial expression, body postures, and so forth, and the sub-jective experience of emotion. In referring to the affective system as a primary motivational/emotional system, Buck also asserted the motivational aspect of emotion.

In addition to the overarching theories of affect described above, many psychological con-structs can be conceptualized under the category of affect. In the free-choice, stimulus-rich en-vironment of the nonformal science education facility, certain constructs have particular rele-vance to the affective experience. Examples of such constructs include, but are not limited to,attention, curiosity and exploration, and interest. Research literature exists to support the rele-vance of each of these constructs to learning in nonformal educational settings. A more detailedexplication of these constructs follows.

Shettel (1976) proposed a model of museum exhibit effectiveness which says that an ef-fective exhibit must have attracting power, holding power, and teaching power. In other words,the exhibit must attract the attention of the visitor and hold attention long enough to commu-nicate its intended message. Attracting power and holding power are determinants of selectiveattention, “the processes that determine which elements of the stimulus field will exert a dom-inating influence over behavior” (Berlyne, 1960, p. 45). Arnold (1960) called attention the firstmovement in the desire to know, or a form of wanting that focuses and initiates perception oraction. Thus, before any response, affective or otherwise, can be made to a stimulus, that stim-ulus must command the learner’s selective attention. Berlyne (1960) asserted that variables re-lated to a stimulus such as novelty, complexity, surprisingness, and uncertainty contribute to se-lective attention. Such variables do seem to contribute to attracting power and/or holding powerin nonformal education settings. In a study involving zoo visitors, Foster, Koran, Koran, Stark,Blackwood, and Landers (1988) observed that one exhibit attracted the attention of significant-ly more visitors than the nine others studied. This exhibit had more animal species than the oth-er exhibits and had a high degree of environmental complexity and a high degree of animal ac-tivity. In a review of literature, Patterson and Bitgood (1988) found that novelty has been shownto increase exhibit viewing time.

Berlyne (1960) also sited indicating stimuli, or stimuli which visually or verbally direct at-tention (i.e., arrows, verbal instructions, etc.), as being capable of focusing selective attentionon a particular stimulus. Similarly, Koran, Koran, Foster, and Dierking (1988) showed empiri-cally that modeling, or the demonstration of a desired behavior by a peer, can be effective in in-creasing participation in museum exhibits, thus influencing the selective attention of visitors,particularly adults. Visitors have also been found to spend more time at manipulatable exhibitsthan at static ones (Koran, Koran, & Longino, 1986). In a study at the Ontario Science Centre,Gillies and Wilson (1982) found that children spent more time at fully participatory exhibitsthan at partially participatory ones. These studies suggest that the potential for participation inan exhibit contributes to its attracting and/or holding power and thus influences visitors’ selec-tive attention to the exhibit.

Some of the variables which influence selective attention are related to the learner ratherthan the stimulus. One such variable is motivational state (Berlyne, 1960). For example, Koran,Foster, and Koran (1989) found that attention, measured as the amount of time a visitor spentat a particular exhibit, was correlated with the visitor’s interest in the exhibit, measured witha Likert-type scale. Another relevant motivational state is felt involvement, a term used byCelsi and Olson (1988) to describe a subjective experience or feeling of personal relevance.The authors reported an experiment in which felt involvement was found to influence attention


in the reading of tennis product advertisements. Other factors such as object satiation andmuseum fatigue can also detract from exhibit viewing time (Patterson & Bitgood, 1988) andthus could be said to influence selective attention among learners in nonformal educationalsettings.

Much of what is known about curiosity and exploration in animals and humans comes fromthe work of psychologist D.E. Berlyne (1960). Day (1982) succinctly summarized Berlyne’s the-ory by stating, “any environmental condition that contains a moderately high level of uncer-tainty induces a state of tension (arousal) in an organism which drives it to explore its environ-ment in order to reduce the tension” (p. 19). Berlyne maintained that in addition to influencingselective attention, qualities such as novelty, complexity, surprisingness, and uncertainty stimu-late curiosity and exploration. Other theorists explain curiosity and exploratory behavior with ahuman need for variation (Fiske and Maddi, 1961; Maddi, 1961) or competence (White, 1959).These theories have implications for nonformal science education: Koran, Morrison, Lehman,Koran, and Gandura (1984) and Koran et al. (1986) found that children, and to a lesser degree,adults, prefer manipulatable exhibits as opposed to comparable exhibit materials at which theycan only look. Their interpretation is that the manipulatable materials are preferred because theypermit the use of more sensory channels with which to satisfy the arousal of curiosity. On theother hand, Falk, Martin, and Balling (1978) found that the novelty of a field-trip environmentinhibited the gain of cognitive knowledge in schoolchildren. This is consistent with Day’s (1982)explanation that too much arousal causes a diminishment in performance.

Thorndike (1935) explained that interest acts in a forward direction to dispose an individ-ual to behaviors associated with the interest, and backward to confirm positive experiences sothat the repetition of these behaviors will be favored. English and English (1958) gave a num-ber of definitions of interest, one of which is “the tendency to give selective attention to some-thing” (p. 271). Arnold (1960) defined interest as an impulse to know which becomes organizedaround one object. It seems, then, that interest may be viewed as a short-term disposition to-ward an object (much like curiosity), or a more long-term and persistent disposition. Studiesdealing with interest tend to measure it in terms of a subjective interest that is self-reported bythe subjects (Berlyne, 1970; Koran et al. 1989; Washburne and Wagar, 1972). For instance, astudy by Day (1967) indicated that the level of subjective interestingness reported by subjectstended to increase with the complexity of the figures they were viewing. Busque (1991), on theother hand, constructed a Likert-type instrument to measure the interestingness of museum ex-hibits. Interest was operationalized as the ability to (a) arouse enthusiasm, (b) bring about par-ticipation, (c) favor apprenticeship, and (d) display aesthetic quality.

Interest and curiosity seem to be highly related constructs. For example, Harty and Samuel(1986) found interest and curiosity in science among a group of 228 sixth graders to be highlycorrelated.

Methodology

The research was conducted as a developmental study aimed at developing and refining aheuristic model of affective learning in nonformal science education facilities. The model de-veloped should serve as a framework, a sort of comprehensive hypothesis, for discussion andresearch on affective learning in nonformal science education. Therefore, the focus of the re-search was hypothesis generating rather than hypothesis testing. Such an objective called forgathering open-ended information about the population and phenomena of interest from a vari-ety of sources, and using this information to synthesize the hypothetical model. Thus, natural-istic, also known as qualitative, methodology was deemed the most appropriate means to


achieve the research objectives of this study. The methodology was naturalistic in that variableswere not manipulated, hypotheses were not tested, and generalized conclusions from the re-search to the population of interest were not made. The primary researcher for this study hadexperience both as a classroom science teacher and as a nonformal science educator, as well asresearch training and experience in the biological and social sciences.

A method of hypothesis formulation known as analytic induction (Robinson, 1951/1969)was employed to carry out the research. Analytic induction consists of:

1. formulating a rough definition of the phenomenon to be explained,2. formulating a hypothetical explanation of the phenomenon,3. studying case(s) of the phenomenon to determine if the hypothesis fits the facts of the

case(s),4. if the hypothesis does not fit the facts, reformulating the hypothesis or redefining the

phenomenon, and5. repeating Steps 3 and 4 until practical certainty is reached.

In the context of this study, the hypothesis to be refined by the method of analytic induc-tion is the model explaining the phenomenon of affect in nonformal science education facilities.Specifically, the research was carried out in stages, as follows:

1. A rough definition of the phenomenon of affect was formulated through an extensiveliterature review from disciplines such as psychology, education, interpretation, muse-um studies, visitor behavior, leisure studies, and related areas. Literature reviewed inthis stage of the research included the theoretical literature related to affect, empiricalevidence from behavioral psychology, and applied research in nonformal education. Arepresentative sampling is included in the literature review above.

2. Drawing from the reviewed literature, a hypothetical explanation, a conceptual model,of affective response specifically applicable to nonformal educational settings (Model1) was synthesized. Model 1 incorporated the theories of Krathwohl et al. (1964), Bull(1951), Arnold (1960), Plutchik (1980), and Buck (1984); scholarly information onpsychological constructs related to affect; and empirical knowledge from applied re-search on learning in nonformal educational settings. The model depicted a sequenceof events resulting in affective responses among nonformal science learners.

3. Field research featuring collection of qualitative data was conducted to determine ifcases in the real world fit the hypothesis, Model 1. This field research consisted of so-licitation of review comments from a panel of expert researchers, in-depth interviewswith practitioners of nonformal education, and unobtrusive observations of learnersin nonformal educational settings. A variety of professionals work in the field of non-formal science education. Researchers in the field include psychologists, educators,and visitor behavior and museum studies experts. Practitioners in nonformal educa-tion include designers of exhibits and educational materials, and museum educatorsand natural history interpreters who plan and/or carry out nonformal science educa-tion programs. Professionals from these different areas have knowledge about learn-ers in nonformal educational settings which stems from their own professional per-spective. The field research component of this study sought to gather information froma sample of these professionals as a source of knowledge about the population of in-terest.

The sampling strategy for selecting participants in the field research componentof the study was stratified chain sampling (Patton, 1990). Chain sampling begins withasking knowledgeable individuals for recommendations of possible participants. As


recommended participants are contacted, they in turn make recommendations for ad-ditional participants. The sample included two strata: researchers with expertise in non-formal education or related fields (n 5 6) and practitioners of nonformal education (n5 8). A document was developed to describe the synthesis of Model 1 and presentModel 1 to the researcher stratum of the participant panel. Included in the documentwere background information on the research study, directions to the participant, a de-scription of the development of the model with accompanying figures, figures depict-ing the model, and a glossary of terms related to the model. The participant was directed to review the document and make comments on the appropriateness, com-pleteness, and accuracy of the theoretical aspects of the model, as well as any othercomments deemed applicable or important by the participant. A standardized open-end-ed interview schedule (Patton, 1990) was developed for the purpose of conducting face-to-face interviews with members of the practitioner stratum of the participant panel.The purpose of the interviews was to gain insight into the practitioner’s experience withthe affective responses of learners in nonformal educational settings. Model 1 was usedas a framework for question construction in that the questions focused on constructs inthe same sequence as they appeared in the flow of Model 1. The interview schedulealso included questions about the professional and educational background of the re-spondent.

The sampling strategy for observations in the field was a selection of typical cases(Patton, 1990) that were accessible to the researcher. For the purpose of this study, typ-ical cases refer to nonformal educational facilities judged to be reasonably typical inthe broad realm of nonformal educational facilities. Judgment as to what constitutedtypical cases was made by the researcher in consultation with members of an adviso-ry committee who have expert knowledge of regionally located nonformal education-al facilities. Labeling the facilities sampled as typical does not imply that they are nec-essarily representative of all nonformal educational facilities. It does imply that carewas taken to avoid unusual or atypical settings for data collection. The sample includ-ed 13 typical nonformal educational facilities (zoos, nature centers, natural history mu-seums, science museums, and so on). The observation strategy was to conduct open-ended, unobtrusive observations pertaining to learners’ affective responses innonformal educational facilities. The observations were open-ended in that no check-list of behaviors or responses to be looked for during the observational periods was es-tablished beforehand. Rather, the objective was for the observer to remain open to anybehaviors or responses that might arise in the natural setting of the nonformal educa-tional facility. Accordingly, only broad guidelines for what was to be observed were es-tablished before beginning the observations. These guidelines were to observe learn-ers’ interactions with exhibits, staff, or other learners, including quotes of things saidand description of physical behaviors whenever possible. Also to be noted when pos-sible were tone and level of voice in learners’ verbal responses and interactions, facialexpressions, gestures, and subjective judgments about learners’ affective states. A de-scription of the learning setting sufficiently detailed to provide a clear context for theobservations was also be included.

4. Model 1 was revised in light of the data collected during the field research (Stage 3),resulting in Model 2. The purpose of the field research component of the study was toexamine real world cases by gathering information about the population of interest, torefine Model 1. In addition to providing more information about the population of in-terest, the field research served to focus the thinking of the researcher on the real-worldnonformal educational setting, as opposed to the hypothetical setting of Model 1. Thisfocusing process is consistent with the emergent designs characteristic of naturalisticinquiry (Guba, 1981).


5. Model 2 was subjected to review by the same expert researchers and practitioners whoparticipated in the field research. This stage of the research constituted a form of mem-ber checks (Guba, 1981) in which patterns emerging from the data are checked againstthe perceptions of the participants in the study. Participants were provided figures ofModel 2 and summaries of findings from the field research component (Stage 3) of thestudy. They were asked to make any comments they felt were appropriate on any ofthe materials provided, and to particularly comment on whether the field research find-ings and the concepts represented in Model 2 matched their own professional experi-ence of learners in nonformal educational settings.

6. Model 2 was further revised using feedback obtained in Stage 5, resulting in the finalmodel.

7. Based on the final model (hereafter referred to as the Meredith Model), a descriptionof affective processes relating to learning in nonformal educational settings was for-mulated.

Results and Discussions

The Meredith Model illustrates a sequence of events occurring in a learner’s affective re-sponse to educational stimuli in nonformal science education facilities, and identifies factorswhich may influence individual elements within this sequence. The model is proposed as a con-ceptual framework for describing the affective response in nonformal science education, formaking limited recommendations for practice in nonformal education, and for making recom-mendations for further research.

According to the Meredith Model (Figure 1), a learner enters the nonformal educational set-ting with preheld motivations, affective dispositions, personal characteristics, and so forth. Thesetting is composed of a stimulus field of myriad stimuli impinging on the learner’s sensory or-gans. Perception occurs as the learner is attracted to a specific part of the stimulus field (an ex-hibit, lecturer, sign, animal, etc.) according to certain internal and external attraction factors(Figure 2). Examples of some of these factors are shown in Table 1. Once selective attention isfocused on a particular stimulus, the learner forms an individualized percept of the stimulus.This percept is shaped by internal and external percept factors and may be different for everyleaner. Examples of some percept factors are shown in Table 1.

Once the percept is formed, a decision to act or behave can be made (Figure 1). This deci-sion will depend on the short-term affect aroused by the percept, a cognitive evaluation or ap-praisal of it, or, most likely, an interaction between the two. Internal and external decision factors, such as preheld knowledge, experience, and motivations, will influence this interaction,and thus the action decision. Examples of decision factors are shown in Table 1. The decisionsthe learner is most likely to make are (a) sensory scanning of the stimulus field for alterna-tive stimuli, (b) changing to a completely new stimulus field, or (c) engaging in behaviorssuch as observing, reading, listening, manipulating, interacting, and so on, with the educationalstimulus.

The possibilities for short-term affective responses (Figure 3) are essentially infinite, al-though some may be more prevalent in the nonformal educational setting than others. Depend-ing on the decision factors present and the learner’s cognitions at the time, various forms of mo-tivation may be aroused. Examples are curiosity, desire to touch or manipulate objects, aestheticmotivations, and so on. Generally, the satisfaction of these motivations, or of the preexistingmotivations the learner held upon entering the experience, will lead to positive affect. Conversely,


the frustration of these motivations will lead to negative affect. Whether the learner experiencespositive or negative affect will play an important part in the action decision.

As an outgrowth of the model, it is hypothesized that the short-term affect experienced innonformal science learning may serve to influence cognitive learning and may initiate or rein-force long-term affective dispositions such as sentiments, attitudes, interests, values, and com-mitment. Since affect is held by theorists to be a motivational force (Arnold, 1960; Plutchik,1980; Buck, 1984); these forms of long-term affect could persist beyond the short-term educa-


Figure 1. The Meredith Model of affective learning for nonformal science education fa-cilities.

tional experience and serve as the motivation for extended patterns of behavior, such as volun-tarily engaging in further science learning experiences.

Recommendations

The primary value of the Meredith Model is to help practitioners and researchers achievean enhanced understanding of affect. As such, the model provides a framework for observationsand interpretations of affective learning. Such a framework can help define parameters to focusobjective setting and evaluation, research questions, and data collection in nonformal scienceeducation, which may in turn lead to modification and verification of the Meredith Model. Be-


Figure 2. Detailed view of the perception process and the factors which influence it inthe Meredith Model

Table 1Some attraction, percept, and decision factors in the Meredith Model

Factor Examples

Experience, knowledge, and intellect • Hobbies• Intellectual capacities• Level of education• Occupation• Past experience• Place of residence (rural, suburban, or urban)• Prior knowledge• Social and cultural background• Socioeconomic status• Stage of family life-cycle, etc.

Long-term affective dispositions • Attitudes (toward concepts associated with the stimulus, thesponsoring organization, learning and leisure in general, etc.)

• Enduring motivational dispositions such as motivation toachieve, etc.

• Interests• Sentiments• Values and commitments, etc.

Motivational state • Aesthetic motivations• Anticipation or readiness to learn• Curiosity• Desire for social interactions• Physical motivations like hunger and thirst, etc.

Reward value of stimulus • Degree to which the stimulus can be expected to satisfymotivations, whether intrinsic (curiosity, manipulation,aesthetic, social, need for stimulation/relief of boredom,etc.) or extrinsic (recognition of achievement by peers,satisfaction of others’ expectations, etc.)

Figure 3. Detailed view of the Meredith Model short-term affective response in nonfor-mal science learning.

cause of the heuristic nature of the model, applied recommendations for the practice of nonfor-mal science education must be considered somewhat tentative. Some limited recommendationsthat seem to have merit follow:

1. Educators should remember that each learner forms and responds to an individualizedpercept of the educational program. Factors such as differences in sensory capabilities,preferences for certain sensory modes, fatigue, motivational state, and social and cul-tural factors will affect the formation of this percept.

2. The model suggests that motivational state is crucial to every stage of the affective re-sponse, and the satisfaction or frustration of the learner’s motivation(s) is a main de-terminant of the quality of that affective experience. Thus, developing visitor profileswhich identify the motivations of visitors, in addition to more traditional demograph-ic data, could help educators structure programs that would be more satisfying to larg-er numbers of visitors.

3. A dominant pattern emerging from the field research component of this study was thatsocial interactions seem to be crucial to the nonformal educational experience. Non-formal educators should consider structuring programs to provide learning experiencesthat maximize social interactions within groups in a meaningful way.

This study also points out the need for further research:

1. Both the literature and the field research component of the study indicated an ambigu-ity of terminology associated with affective constructs. For example, practitioners in-terviewed made little apparent discrimination between the phenomena of interest, cu-riosity, attention, and enjoyment until probe questions were pursued. Indeed, as theliterature reflects, there are no standard definitions in existence for most affective con-structs. Thus, research is needed to pool the collective knowledge and wisdom of pro-fessionals in the field to arrive at a standardized terminology related to affective con-structs so that future studies can be conducted without the hindrance of ambiguity ofterms.

2. The model enumerates attraction, percept, and decision factors which are hypothesizedto influence the outcome of various events within the affective response, namely at-traction to stimuli, formation of percepts, and action decisions. More research is need-ed to support and expand upon existing evidence for the influence of these factors. Re-search should also be pursued to determine if some factors are more influential thanothers.

3. Research is needed to clarify how the affective experiences of learners in nonformaleducational settings might be enhanced. In other words, how might these experiencesbe made consistently positive and/or more intensely positive?

4. Research is needed to identify the long-term effects of affective learning in nonformaleducational settings. Several theories hold that affect is a motivational force (Arnold,1960; Plutchik, 1980; Buck, 1984). The Meredith Model proposes that the short-termaffect experienced in the nonformal science learning experience may reinforce or leadto long-term affective dispositions that could persist indefinitely and motivate and in-fluence extended patterns of behavior. Examples of such behaviors could include pur-suing more science learning experiences, adopting hobbies in the sciences, choosingcareers in science, and so on. While these are undoubtedly the types of behaviors manynonformal science educators hope to encourage, more research is needed to confirmthe role of affective learning in influencing such behaviors.


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model of affective learning for nonformal science education facilities

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