Novice and expert teachers' time epistemology: A wave function from didactics to pedagogy

Teacher & Teacher Education, Printed in Great Britain

Vol. 9, No. 2, pp. 2055218,1993

0742-051X/93 $6.00 + 0.00 @ 1993 Pergamon Press Ltd

NOVICE AND EXPERT TEACHERS’ TIME EPISTEMOLOGY: FUNCTION FROM DIDACTICS TO PEDAGOGY

A WAVE

FRANCOIS TOCHON UniversitC de Sherbrooke,

Canada

HUGH MUNBY Queen’s University,

Kingston, Canada

Abstract-This study compares how 23 novice and 23 expert teachers perceive time. The focus of the study is upon differences in time epistemologies in didactics and pedagogy. The theoretical justification for exploring these differences comes from current research on novice and expert teachers and from the distinction, in semiotics, between two fundamental ways of knowing time, diachrony and synchrony. Data for the study are interview transcripts which are coded for their various mentions of time. A cluster analysis technique is used to portray graphically different epistemologies of novices and experts, and the results suggest that it is not helpful to view the growth from novice to expert as a simple accretion of information and experience. A wave model is advanced as an alternative way to depicting what appears to be a rhythm between didactic and pedagogical thinking among experts.

The study reported here concerns differences among novice and expert teachers, specifically with how their thinking reflects differences in their perception of time. While the study is related to North American research on teaching (Clark & Peterson, 1986; Clark & Yinger, 1987; Charlier, 1989; Tochon, 1989a), and particularly to novice/expert studies (Berliner, 1988, 1989; Leinhardt, 1989) its conceptual orientation and methodology are different. The study draws on semiotics for distinctions between ways of knowing time, and on the concepts “didactics” and “pedagogy” for distinctions within the enterprise of teaching. These roots and the study’s research approach are distinctively European. Accordingly, the study can be viewed as contributing to North American research by introducing an alternative perspective on novice/expert work. In their review of novice/expert research,

Carter and Doyle (1989) show that expertise is domain-specific and is organized for interpretive efficiency. While the novice might see little in a situation, the expert uses powerful analytical tools for interpreting situations and adapting action. Novices tend to anticipate and to sequence their teaching actions in advance, whereas experts often adapt entire semantic or propositional mappings to a particular event. As Leinhardt (1986) has found, experts seem to have a larger agenda than novices and they take contextual variations into account. Among experts, anticipation is of less importance and immediate decisions are more frequent (Tochon, 1989b, 1991a). The adaptability that characterizes expert performance strongly suggests that novices and experts understand and process time differently. In brief, we can expect “time differences in novice and expert epistemologies. ”

205

206

FRANCOIS

TOCHON

Epistemology is defined here as a way of knowing and organizing thinking (Tochon, 1990). In this view, the way thinking is organized for action relates to planning and to time. Thus, the way teacher planning expresses itself is close to its epistemological roots. In planning for teaching, as in any planning, time can be processed through anticipating events or through immediate decisions related to events. The North American literature on teacher thinking distinguishes between these two types of decisions by terming them “pre-active” and “interactive”, respectively. In this study, the European terms “didactics” and “pedagogy” are employed. As shown below, these terms do not precisely match North American terminology but are more closely related to the concept of agenda (Leinhardt, 1986) and suggest a “double agenda” in teaching: anticipated sequence and the sequence modified to accommodate the varying context of teaching itself. Two fundamental but complementary ways of knowing time have been developed in the field of semiotics, diachrony and synchrony (De Saussure, 1968), which are in tune with the double agenda of the teacher. Diachrony relates to evolution in the course of time in an historical perspective. In terms of teaching, diachrony relates to content anticipation of action, hereafter termed “didactics.” In contrast, synchrony refers to present immediacy, or a state of time like here and now. The “here and now” of teaching relates to pedagogy-the immediate relationship with students. In teaching, we are accustomed to experiencing a clash between the sense of event as anticipated and the sense of event as experienced. This clash can be analyzed in terms of a contrast between didactics and pedagogy which are two ways of knowing and organizing classroom time. The study reported here investigates differences in time epistemology among novice and expert teachers. By exploring the relationship of these differences to didactics and pedagogy, the paper advances a model for the growth from novice to expert. A more detailed treatment of the theoretical approach to the study, below, is followed by a description of the qualitative empirical component of the research. The data are analyzed in two ways, the second providing a graphical representation of novice and expert time epistemologies.

and HUGH MUNBY

Theoretical

Background Pedagogy

Didactics

and

In this study, didactics and pedagogy are viewed in terms of their epistemological foundations; they are taken to represent the organization of meaning either with the mediate planning of events or in the immediate context of classroom situations. In this view, didactics is defined as the organization of subject-matter knowledge through time as a preactive or postactive anticipation (before or after the classroom interaction synchrony), whereas pedagogy stems from the interactive management of time. Didactics and pedagogy constitute what Leinhardt (1986) has called the teacher’s Didactics deals with content “double agenda”: processing which implies planning a sequential while pedagogy is concerned with time, relationships to knowledge and students’ behavioral actualization of teaching within real time. Traditionally, the interest in didactics with its role of long-term planning has been in codifying and formalizing the time accorded to the content of the school curriculum. For example, the written curriculum is an expression of didactic so didactic processing generalizes thought, potential teaching situations to an abstract plan. transposition” The concept of a “didactic (didactic transformation) in the thinking of teachers was evolved by Verret (1975). His epistemological thinking was developed by Chevallard (1978, 1985) who demonstrates that any element of knowledge has first to be transformed so that it may be taught. Conne (1981) studied ways of transposing knowledge for teaching mathematics in first and second grades; the works of Leinhardt (1986, 1989) on that issue are well known. In the approach initiated by Verret, didactic transformation of knowledge is related to the processing of time. It may appear as a progressive selection of relevant knowledge, a sequential transmission involving a past and a future, and a routine memory of evolutionary models of knowledge. Because didactics is a diachronic anticipation of contents to be taught, it is essentially propositional. It names teaching experience in propositional networks, and so involves a mediation of time. Some research on novice teachers suggests that beginners usually

Novice

and Expert

Teachers’

have abilities to plan but encounter problems during immediate interactions (Berliner, 1988). They seem to identify their role mainly as a didactical one. Their way of organizing time has no flexibility; it is not synchronic. In contrast, pedagogy is concerned with an immediate image of the teaching situation. It is live processing developed in a practical and idiosyncratic situation. Didactic goals can be written down, but pedagogical experience cannot be easily theorized owing to its unique interactive aspects. Though action-research and reflection reveal the existence of basic principles underlying practical classroom experience, no matter what rules might be inferred pedagogy still remains an adventure. There has been a considerable research on teachers’ knowledge of action arising from the work of Polanyi (1958) and represented in the work of Shulman (1987), Gudmundsdottir (1988), Connelly and Clandinin (1990a), and others. But importantly, as soon as one gives expression to pedagogical knowledge transformation, it becomes didactic. Declarative representation, in didactics, seems to relate to the story of experience: It has historical features and so is diachronic rather than synchronic. In the view adopted in this paper, the practitioner organizes in a diachronic way the didactic contents and administers them synchronically within a pedagogical social relationship. Both types of knowledge take contact in a focal point of “reflection in action” (Schon, 1987; Munby, 1989) which is a conversation between facts and their representations. The language of practice (Yinger, 1987) appears as a focal moulding of two concepts of time, with the past being embedded in the representation of the present but never able to capture its full meaning. Accordingly, it can be hypothesized that expert teachers may be more pedagogically oriented than novices. And an understanding of how teachers construct time (their time epistemologies) is needed for a fuller account of teacher thinking and of teachers’ growth. The distinction between diachrony and synchrony is of special interest in advanced cognitive modeling. Most evolved systems in artificial intelligence and cognitive science involve a parallel distribution of competing diachronic and synchronic rules; this competition explains induction and high-level inference

Time Epistemology

207

in complex domains (Holland, Holyoak, Nisbett, & Thagard, 1989), and this applies to teaching as well. Up to now, teachers’ time processing has mainly been explained in terms of planning and algorithmic didactic routines (Yinger, 1987; Leinhardt, Weidman, & Hammond, 1987), but the field of pedagogical uncertainty and problem solving probably requires the use of heuristics, which are abstract procedures that reduce the complexity of synchronic interactions (Tversky & Kahneman, 1974). There is ample evidence that, didactically and pedagogically, teachers organize time differently: planning rarely corresponds to its actualization (Shavelson & Stem, 1981; Clark & Yinger, 1987). These findings strongly suggest the need to explore the time epistemologies of novices and experts. In this study, time epistemology is viewed as metacognitive; it is taken to function heuristically and to mediate between planning and teaching. On the basis of the empirical evidence below, the paper argues that this mediation shifts, with experience, towards the pedagogical pole. Another possible view of expert teaching might explain the mediation itself as a heuristic wave function between synchronic and diachronic poles, Data Collection Data presented below are from a larger inquiry into the inadequacies of planning, and consist of interviews conducted during the school year 1988 -89 in Geneva, Switzerland. Forty-six junior high school Language Arts teachers participated in the study, 23 as novices and 23 as experts. The novices include six firstyear teachers with one or more years of experience as substitutes, and 17 suppl&znt (postulant) teachers beginning their second year of teaching. In the Genevan system, supplkant teachers have no teacher education but hold fulltime teaching positions for 2 or 3 years before being admitted to a 2-year remunerated teacher education program involving supervised teaching, observation of expert teachers, and courses in educational foundations and in general and specific didactics. The equivalent of a M.Sc. or M.A. is required of those entering secondary schools as suppkant teachers. These

FRANCOIS

208

TOCHON

suppltknts are particularly suited as novices for the current research because they have limited experience and no theoretical knowledge of teaching other than what they have constructed for themselves. The initial plan was to select the 23 experts using criteria employed in novice/expert studies in the research literature. This approach revealed unexpected problems that are detailed elsewhere (Tochon, 1991b). Briefly, the operational definitions of experts in 15 studies were found to vary from one study to the next, often reflecting different epistemological orientations to novice/expert research. Some researchers used correlational criteria characteristic to the process -product paradigm for studying teacher thinking, some followed the recommendations of peers or superiors, while others relied on the paper qualifications of the potential participants. The advantages and disadvantages of each procedure were identified so that a set of composite criteria was established for selecting the 23 experts of the present study, as follows. The purpose of the research was explained to eight resource persons whose competence was recognized by the district administration of the junior high schools of Geneva, and whose professional responsibilities gave them particular knowledge of the 450 Language Arts teachers in their schools. Each resource person was asked to recommend 5 to 10 teachers whom they considered to be the most experienced at the junior high school level. In addition, each was asked to write the criteria used to select the teachers he or she nominated. This procedure resulted in 42 names to which the following “filters” were applied. 1. Academic background: M.A., with a major in Language Arts. 2. Professional training: High School Educational Studies Degree. 3. State nomination with tenure. 4. A minimum of 7 years of teaching experience (Berliner, 1987). Thirty-eight individuals met these criteria. The number was further reduced to the required 23 by random selection. Research

Procedures

Two techniques were used to elicit information from the participants: a semi-structured set

and HUGH

MUNBY

of 24 interview questions, and a simulation exercise, both in French. The interview questions were based upon those used in studies of novice/expert teachers and in studies of teacher planning and teacher thinking. Some questions were quite general: “What are you going to do today?’ ’ (Leinhardt, 1986). Some questions were more specific: “What explains the most frequent modifications of your planning?” Other questions concerned specific classroom responsibilities events and professional (Calderhead, 1987; Ericsson & Simon, 1980; White, 1980). Examples are: “Do you have to adapt your planning when you are teaching? Do you have an example” and “What is the influence of the context on your planning? Do you have an example?” As is usual in this type of research, questions were asked only when the participant did not volunteer the relevant information. For example, one participant gave a 45minute response to the first question asked, answering many other questions without being asked to do so. The simulation exercise was developed to determine how participants would plan the content of courses, using four examples from the objectives of the junior high school curriculum in Geneva. The thinking aloud process was explained briefly with, “I will ask you to think aloud while planning. ” The English translation of the text used in the simulation is: Could you explain to me in detail how you would proceed with the following four objectives for a grade 8 Language Arts class? This will enable us to discuss some concrete examples. How do you prepare yourself? Take all the time you feel necessary. The most important thing is not to develop the perfect plan, but rather to indicate how you view your teaching routines, the way you taught last year, and the way you will teach tomorrow or next week. Explain what guides you in processing subject-matter knowledge, and give me narratives or examples of your experience in the classroom concerning these four objectives: I. Put commas in the right places when punctuating a text. 2. Conduct an inquiry for a report. 3. Develop and explore a lexical then a semantic field. 4. Analyze the structure and the dynamic relationship between the characters of a story.

Responses simulation

to the interview questions and to the were recorded and transcribed

Novice

and Expert

Teachers’

verbatim. Segments of text containing allusions to time were transferred to separate protocols for analysis. Segments were identified as relevant according to a semantic definition of time as is customary in this sort of work, rather than a simple word level of identification. Analysis The analysis of the data is presented in two parts. The first part opens with an expansion of the coding of the data and continues with descriptive accounts of the codes and their frequencies. The second part provides a deeper analysis by describing and presenting a graphical representation of the data obtained through a cluster analysis. Coding and Descriptive

Analysis

All segments of text pertaining to time were coded thematically. This coding can be illustrated by considering responses to two questions from among the set of interview questions. Here, the two codes are partially determined by the questions themselves. For instance, Question 1 asked, “What explains the most frequent modifications of your planning?” The most frequent answer was, “It is the time taken up by certain activities.” This response is coded “A” and represents the immediacy of time (synchrony) associated with pedagogy. This code

Table

209

Time Epistemology

may be compared with the coding of responses to Question 2, “What is your biggest problem when processing the curriculum?” The most frequent answer was, “It is the time needed for This is coded “B” represencertain activities.” ting a more evolutionary epistemology of time (diachrony) associated with didactics. Table 1 gives detailed results of coding responses to the above two questions as A or B. (In this and subsequent tables, both novices and experts are identified with numbers 1- 13. In Figure 1, these numbers are prefixed by 1 for novices and by 2 for experts.) Nine novices expressed A, whereas the same response is given by 13 experts. In other words, of the 22 teachers expressing A (the overall total presence of A), 41% were novices and 59 % were experts. The percentage of teachers expressing A is 47.8% (22 as a percentage of 46). (An alternative presentation of the results appears in Table 4: 39.1% of the novices and 56.6% of the experts expressed A.) It is evident that both novices and experts experience difficulty foreseeing the time needed for content interaction in teaching. While time seems to be responsible for changes to the plans of both groups, the responses (B) to the second question show that foreseeing the time needed is a problem for twice as many novices as experts. As noted above, codes A and B match two of the questions from the set used in the interviews and the meanings of the codes are partially

1

Meaning

and Results

Related

to Codes Issued from

the Interview

Protocol

Codes

Text

Novices

Total

%

Experts

Total

%

Ov. total

%I46

A

The most frequent modifications of planning are due to the time taken up by certain activities

1, 2, 5, 6, 10, 12, 13, 16, 21

9

41

1, 4, 5, 7, 8, 10, 11, 15, 17, 18, 20, 21.22

13

59

22

47.8

B

My biggest problem with planning is the time needed for certain activities

1, 2, 3, 6, 7, 8, 10, 11, 13, 15, 17, 18, 23

18

67

5, 7, 8, 9, 10, 11, 12, 16, 23

9

33

27

58.7

5, 9, 12, 16, 20,

210

FRANCOIS

Modifying

Poor

time

management

short

TOCHON

and HUGH

MUNBY

ter

Lack of tim

A certain

FI Dependency

control

205

of time

Autonomy

Adaptins oneself to the uncxpccted

Independence

;14

Novices

Experts

Flexibility

Figure

1. $’ cluster analysis. (Figure produced Pini, University of Geneva, Switzerland.)

determined from the nature of the questions. This was not the case for the other codes. These were obtained by a thematic analysis of the segments of text alluding to time that were found in responses to the interview questions and simulation exercise. These codes and segments of text illustrating them are presented in Table 2. They represent elements of meaning mentioned by the teachers in connection with the concept of time; thus, the coding system evolved from meanings contained within the speech of participants rather than from any predesigned category system. The letters of the codes in Table 2 have no significance in themselves, but the elements of meaning have been ordered according to the number of teachers mentioning them: the idea that planning is difficult (code C) was expressed by 74% of the teachers, while the idea that planning

100 and higher = 200 and higher

=

by G.

helps to gain time (code X) was expressed by 4.3 % Because elements coded RSTUVW and X were present in interviews of less than a fifth of the participants, they are regarded as weak and are not included in the cluster analysis, below. The use of the coding system is illustrated in the following excerpts. The first is from the interview with Novice 6 and shows that she has problems evaluating the time that certain activities take (Code D) and that she must prolong some activities (Code F): The speed of the students modifies my plans. An interest by the students for an activity can cause me to prolong it. The periods for giving out grade3 have an influence on me as well as, for instance, whether or not to cut out an accompanied reading. There is always a moment of suspense. There must be an adaptation to the time required by actlvitie\: I

211

Novice and Expert Teachers’ Time Epistemology always anticipate too much and have to postpone the work. There may also be a sudden discussion which is worthwhile. My greatest problem is in estimating the time needed for each activity. 1 must drop objectives for lack of time. If 1 wanted to do everything, 1 would spend two hours on each activity, which is impossible.

This may be compared with the excerpt from the interview with Expert 5. Context has a major influence. 1 rarely plan the lesson; 1 anticipate production stages, so that 1 am always ready to prolong an activity. The time necessary for each activity causes the most frequent modifications. The other day, 1 had envisaged a certain task (the laying out of their horoscopes). However, before doing this the book being studied in magisterial reading was just drawing to a climax and 1 wanted to read up to the moment of suspense and stop there in order to titillate them. The students were so interested they wanted to continue at any price (the book was You Are Not Dead by Scarmetta). 1 improvised; we spent 45 minutes reading, to the joy of the students. My biggest problem is calculating the time required for activities, for instance, when taking up a song by Renaud, if there is suddenly an interest for a problem, the plan which change, which will take more time.

This second excerpt makes plain references to codes A and B: the most frequent modifications of planning are due to the time taken up by certain activities, and the biggest problem with planning is the time needed for certain activities. Also apparent are code F (this expert must prolong certain activities), and code J (students’ motivation affects the time taken up by activities). Differences between novices and experts can be seen in Table 3. Here the numerical difference for each code suggests the codes ANOV most represent how time features in the thinking of experts, while codes BCEFM represent how time is expressed in the thinking of novices. Despite the differences apparent in Table 3, it is evident that foreseeing the time required for teaching specific content creates problems for novices and experts alike: Each show similar discrepancies between didactic time and pedagogic time. This is relatively easy to see in Table 4 in the codes characterizing the mentions of time by each participant. Table 4 shows, for example, that Expert 6 expressed the codes HIKP: She believes she must remain flexible and adjust to unforeseen cir-

cumstances. The attitudes of the students influence the time taken up by activities and the time-table influences her plans: The same didactics is differently received on Monday morning or on Friday afternoon. Similarly, the profiles of all participants whether novices or experts suggest a gap between planning and teaching. Conceivably, the nature of expertise may not lie so much in minimizing the gap betw :en didactics and pedagogy as it may lie in how novices and experts deal with the adaptation required by the discrepancy. In this study, all the novices expressed difficulty with time adaptation, yet all the experts reported that they felt at ease. The following are illustrative: 1 have no overall view of time. . My problem is managing to adapt, making my plan flexible. 11: 1 would like to get away from every form of planning. Planning transforms itself, it is an indication; it implies the notion of the time spent over the task. The students modify the plan. in its rhythm at first, and som&imes it is necessary to change and do something else. 13: 1 am forced to adapt, otherwise one doesn’t move ahead. 7: Certain tasks take place at the present time; if 1 see that one of them is going very well (on a subject), we continue. 10: The interest of the students has priority; if 1 notice the slightest sign of boredom, 1 change my system, and start to listen to the students. 1 modify everything, all the time. 1 improvise all the time, because if 1 do not improvise, 1 do not respond and cannot face the diversity of requests. . . The temporal constraint opposes improvisation which can incite a smile. 11: 1 work with present day concerns. 1 do not plan, 1 have a lot of material which allows me to improvise.

Novice 1: Novice

Novice Expert Expert

Expert

These quotes among many others in the data suggest that synchronic adaptation is easier for experts than for novices. According to the data, expert planning appears more contextualized and nearer to the synchronic point of teaching. Graphical Representation Analysis

i%rough Cluster

A deeper analysis of the code distribution gives some insight regarding a shift from a

212

FRANCOIS

TOCHON

and HUGH

MUNBY

Table 2

Meaning and Results of the “Time Protocol” Codification Codes

Text

Novices

Total

%

Experts

4, 9, 12, 16, 19, 23

20

59

1, 5, 7, 11, 12, 16, 17, 19, 20, 22

Total

%

Ov. total

%I46

9, 15, 18, 21,

14

41

34

74

-is dificult

C

Planning

D

I have problems evaluating the time that certain activities take

1, 2, 3, 5, 6, 8, 10, 11, 12, 13, 15, 16, 17, 18, 20, 21, 22, 23

18

53

1, 2, 5, 10, 11, 13, 14, 16, 18, 21, 23

7, 8, 12, 15, 20,

16

47

34

73.9

E

Depending on the time of the day, I adapt or make

1, 2, 3, 6, 7, 8, 10, 11, 13, 15, 19, 21, 23

4, 9, 12, 18, 22,

18

58

1, 2, 7, IO, 11, 13, 15, 20, 22,

9, 12, 19, 23

13

42

31

67.5

1, 2, 3, 6, 8, 9, 11, 12, 18, 19, 21, 22,

5, 10, 14, 20, 23

I8

58

1, 3 57, 10, 12, 3, 15, 16, 17, 18, 20,21

13

42

31

67.5

modifications

F

I must prolong

or

shorten certain activities

1, 2. 3, 5, 6, 8, 10, II, 13, 15, 17, 18, 20, 22,

G

The level and capabilities of the students influence the time taken up by activities

2, 5, 6, 7, 9, 10, 12, 18, 19, 20, 21, 22, 23

13

50

7, 8, 10, 11, 12, 14, 15, 17, 18, 20, 21, 22, 23

13

50

26

56.6

H

I must remain jlexible

1. 6, 8, 9. 10, 11, 12. 15, 21, 22

10

43

I, 6, 7, 13, 14, 16, 17, 21, 22,

12, 15, 19, 23

13

57

23

50

1

I adjust to unforseen cirrum.stance.r

1, 6, 7, 8, 9, 10, 11, 14, 19, 22

10

45

2, 5, 6, 10. 12, 14, 15, 17, 18, 19, 22, 23

12

55

22

47.8

J

Students’ motivation affects the time taken up by activities

2. 6, 7, 8, 9, 12, 15, 19, 20, 22

10

48

I, 3, 5, 10, 13, 14, 16, 20, 21, 22

11

52

21

45.7

K

The attitude of the students influences the time taken up by activities

I, 8. 9, 11, 13, 14, 15, 16, 19, 20

10

48

1. 2, 3, 5, 6, 9, 15, 19, 20, 21, 22

11

52

21

45.7

L

I must often quicken or slow down my pace

I. 2. 5, 9, II, 12, 14. 16, 17, 22. 23

11

52

1. 2, 8, 12. 13, 16, 17, 20, 22, 23

IO

48

21

45.7

Novice

and Expert

Teachers’

213

Time Epistemology

7

37

I9

41.3

9, IO, 11, 12, 13, 16, 17, I9

I1

61

18

39. I

39

1, 4, 5, 7, IO, II, 12, 14, 15, 18, 20

I1

61

I8

39. I

43

I, 6, II, 18, 20, 21, 22, 23

8

57

14

30.4

I, 4, 7, IO 11, 17, 18

64

2, 3, 5, II

36

11

23.9

8, 9, 13, 16, 23

71

9, 10

29

7

15.2

Overplanning too far ahead causes me problems

3, 17, 19, 21

67

19, 22

33

6

I3

T

I alternate my lessons, I need breaks

II,

50

11, I9

50

U

I must modify my way of teaching presenting material

6, 9

50

1.3

50

8.7

V

Time does not allow for certain activities

0

4, 8, 14, 21

100

8.7

W

I lose time explaining how to work

I8

33

3. I3

67

6.5

X

Planning helps in gaining time

-

100

4.3

M

I run short on time

4, 5, 6, 7, 8, 9, 10, II, 12, 13, 16, 23

12

63

7, 8, 15, 18, 20, 21, 23

N

A plan that is too rigid causes problems

1, 8, ll, 12, 19, 20, 21, 20

7

39

0

Time causes frequent modifications

1, 3, 4, 5, 6, 13, 21

7

P

The time-table influences my plans

3, 6, 10, 14, 16, 22

6

Q

I must often modify short-term plans

R

Planning time

s

takes

I5

predominant didactics among novices to a predominant pedagogy among experts. A Chisquare cluster analysis elaborated according to the Benzecri (1976) method, as in Figure 1, provides this insight because the statistical processing produces a mapping of the codes and the subjects. Such a mapping is especially

0

13, 23

8.7

interesting with qualitative data because each participant can be located on the map, and his or her semantic location can be interpreted by its proximity to specific codes. For example, expert 22 (number 222 on the map) is very typical of his or her flexibility, because of the proximity to code H.

214

FRANCOIS

TOCHON

and HUGH

MUNBY

Table 4 Codes

Characrerizing

Each Teacher

Novices

I ABCDEFHIKLNOQ 2 3 4 5 6 7 8 9 IO II 12 13 14 15 16 17 18 19 20 2I 22 23

BCDEFGJL ABCDEFOPS CEMOQ ABCDFGLMO ABCDEFGHIJMOU BEGIJMQ BCDEFHIJKMNR BCEFGHIJKLMRU ABCDEFGHIMPQ BCDEFHIKLMNQT ABCDEFGHJLMN ABCDEKMOR FIKLP BCDEHJKT ABCDFKLMPR BCDLQS BCDEFGQW CEFGIJKNS BCDFGJK ADEFGHNOS CDEFGHIJLNP BCDEFGLMR

Experts 1 2 3 4 5 6 7 8 9 10 I1 12 13 14 15 16 17 18 19 20 21 22 23

ACDEFHJKLOPU DEIKLQ FJKQUW AOV ABCDFIJKOQ HIKP ABCDEFGHMO ABDGLMV BCEKNR ABDEFGIJNOR ABCDEGNOPQT BCDEFGHILNO DEFHJLNWX DGHIJOV ACDEFGHIJKMO BCDFHJLN ACFGHILN ACDFGIMOP CEHIKNST ACDEFGJKLMOP ACDFGHJKMPV ACEGHIJKLPS BDEGHILPX

Quantitative cluster analysis reveals some of the differences between the ways novices and experts handle adaptation: Statistically significant differences were found for code B @ < .007) and code C (p < .044). [Code V has certain amount of discriminating power @ < .063) but, as noted above, only four participants mentioned this code.] The results of Tables 3 and 4 are confirmed by this analysis which shows that codes B and C discriminate between novices and experts. The graphical results of the cluster analysis are given in Figure 1 in which the coordinates are given semantic values according to their proximate codes. The upper part of the map corresponds to code Q (modifying short-term plans), this code being just to the right of the vertical axis. The opposite lower part indicates flexibility, which is a common feature of the proximate codes H, A, P, and 0. The left part of the horizontal axis deals with codes mainly related to dependency: M, D, B, and 0. The horizontal axis, then, represents control over time, with codes on the right of the map

Novice

and Expert

Teachers’

representing more independence in planning. This cluster analysis yields a diagonal axis from the upper left to the lower right, passing through the point NOV (the average of novices) and EXP (the average of experts). According to the cluster analysis, novices have a tendency to cluster in the upper left while expert teachers have a tendency to cluster in the lower right. The diagonal axis suggests that the growth from the novice state to the state of expertise is evolutionary: It begins with a dependency on planning in which plans are constantly modified in the short term, and evolves toward more autonomy and flexibility in planning. Time seems more problematic for novices than for experts. The latter appear to have gained a certain control over time and this appears to be paired with a sense of flexibility, of adapting to the unexpected. This increase of synchronic adaptation indicates the predominance of pedagogy over didactics among these European Language Arts expert teachers. In Figure 6, the majority of the novices are found in the upper left quadrant of the map. These have a tendency to function with frequent short-term modifications to their planning, which seems neither accurate nor sufficiently flexible. In contrast, the majority of the experts are placed in the lower right quadrant. They define themselves as teachers who have longterm overviews, while recognizing the difficulty and the relativity of planning. Their planning appears more like an open field of possibilities with which they play in synchrony and improvise. Experts’ constant reorganization of time seems smooth and less problematic, indicating the importance of long-term metamemory patterns for teaching that is more flexible and contextualized. Discussion This study has introduced the concepts of synchrony and diachrony to explore differences in the time epistemologies of novice and expert teachers with particular attention to how these differences are manifest in didactics and pedagogy. The first level of analysis of the qualitative data shows time epistemologies to vary according to individuals, yet there is a strong suggestion (Table 3) that experts use a

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more synchronic view of time. This is supported by the cluster analysis. The horizontal axis (control of time) in Figure 1 only slightly discriminates between the novice and expert participants, but the diagonal axis does discriminate: Experts appear more at ease and more flexible than novices when the pedagogical context of teaching influences didactic (or planned) time and requires some deviation from the anticipated sequence of a lesson. Importantly, the data speak plainly to the difficulty both novices and experts experience in planning and evaluating time. Experts alleviate this problem by deliberately avoiding rigid discovered (Tochon, plans, as previously 1991a). Expert didactics seem to be in closer contextual relation to pedagogy than novice didactics so that expert anticipation of time is more synchronic and involves a fusion of didactic and pedagogic processes. It is as if the knowing-in-action which comes from learning from experience consists of a flexible time epistemology that allows plans to be adapted toward one or another path of pedagogical realization at any moment, to modify the rhythm of progression, to “take shortcuts and different rhythms when they are needed” (Expert 20). In such cases, the teaching is more focused and more responsive to its context. This discussion has implications for better understanding the functions of the two aspects of the double teaching agenda, didactics and pedagogy. Although both are indispensable, we are all too familiar with the confrontation between didactics and pedagogy, and this is especially evident after teacher training when instructional theories and their resulting designs reveal themselves to be inapplicable to practice. Such didactic “misdeeds” are pictured as parasites of pedagogy, and the following surely typifies novices’ complaints about the failure of didactics to consider the full range of teaching’s contextual variables: We have not been taught how to assess our timetable, nor how to classify activities. The curriculum is so complex that we cannot even read it or understand how much time an activity can last, how to combine and organize activities. Instead, we get ready-made recipes incompatible with our context, inapplicable theories to construct sequences from the simple to the complex, as if we were capable as

216

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novices to situate what is simple plex for a preadolescent.

TOCHON

MUNBY

and what is comPedagogy

The present study and others in the literature show that novices rarely improvise but most experts do, and that experts think in terms of students and regulations (Leinhardt, 1986) while novices rarely do so. In this light, pedagogy appears to be a field of expertise while didactic organization of contents seems the one obsessional thought among novices. The growth of expertise might thus be inferred to be like a curve rising from didactics to pedagogy, as in Figure 2. A different picture of the growth of expertise is offered by the results of the present study. It is not entirely a shift from didactics to pedagogy, so the problem for the novice is not simply to add pedagogy to didactics. The transition from novice to expert is better characterized in terms of developing a balance between the two aspects of the double agenda. An appealing metaphor for describing this balance is available in quantum theory’s wave function for depicting matter as both empty and objective at the same instant. In these terms, one becomes an expert by developing and maintaining a lively “wave function” or rhythm that merges didactics into pedagogy and vice versa. Rhythm in teaching would be achieved through a focal fusion of the apparently paradoxical extremes of the double agenda. Conceivably, this rhythmic wave function with its attention to diachronic and synchronic time may explain the path to the flexibility that characterizes experts, as suggested by Figure 3. The interview excerpts and Figure 1 demonstrate that the expert participants “tune” conceptual rhythms with spatial reactions of pupils. Not only is the wave function model consistent with the data of this study, it is also consistent with the rhythmic image of the

Diachronic organizing

and HUGH

time: knowledge

Experts

/

Novices

I

/ Figure

Didactics

2. Novice/expert

teacher given by Clandinin and Connelly (1986), Clandinin (1988), and Connelly and Clandinin (1990b). As argued by Pinnegar and Carter (1988), time processing and reflection on time appear to define an important dimension of expertise. Obliged to juggle with time frames and pedagogical rhythms: The faculty of perceiving these rhythms corresponds to the perception of the moment in which the dissatisfaction arises. It varies for each class and for each level. (Expert IO)

The time epistemology of experts, focal time, seems to obey not only anticipated diachronic rules, but also a constant heuristics between long-range goals and their approximation within teaching acts. The wave function of teaching heuristics could be described as a competition, in parallel distributed processing, between two types of cognitive rules: those responsible for temporal and sequential transitions, and those atemporally governing alternate descriptions of a problem situation so as to recategorize its elements for alternative actions.

representations Focal wave

Synchronic organizing

time: space

interrelations Figure

3. The parallel

growth.

> processing

of teaching.

teaching function

Novice

and Expert

Teachers’

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Submitted 5 May 1992 Accepted 2 November 1992