Computer readiness of teachers

Computers Educ. Vol. 19, No. 3, pp. 301-308, 1992 printed in Great Britain. All rights reserved

0360- 13 15/92 $5.00 + 0.00 Copyright 0 1992 Pergamon Press Ltd

COMPUTER READINESS OF TEACHERS

MANFRED LANG

Institut fiir die Padagogik der Naturwissenschaften, Universitiit Kiel, Olshausenstrasse 62, D-2300 Kiel, Germany

(Received 27 August 1990; accepted in revised form 12 February 1992)

Abstract-Teachers’ computer readiness is introduced as a factor within the International Association for the Evaluation of Educational Achievement (IEA) system approach for innovation. It is defined as teachers’ awareness of curricular intentions and their reactions indicated by interest, motivation, willingness, attitudes and activated knowledge in a school context. In the literature on educational innovation readiness for change is assumed to be crucial for the implementation process.

A latent class analysis of data from 1123 questionnaires completed by secondary level I or II teachers was applied to develop a computer readiness scale. High, medium or low scale values differentiate between three types of teachers: affirmative, interested in learning more and skeptical.

Differences on the readiness scale are significant for teachers of different sex, their kinds of computer use at school, and their judgement about knowledge and skills for computer use at school. On the average “using” and especially male teachers gain high, “non-using” and especially female teachers low scale values. Teachers judging their knowledge and skills to be suthcient for computer use in school generally gain high values on the readiness-scale. Scale values correspond with class memberships from latent class analysis.

Teachers usually indicate the following problems related to the kind of computer use in school: not enough computers, technical limitations, lack of software, no financial support, lack of interest and readiness of other teachers, difficulty in integrating computer use into their lessons and not enough time for students/teachers. These, except for the last two, are problems related to high computer readiness.

In general teachers are motivated to learn more about computers and to deal with problems about computer use in school. A curricular infusion approach may be useful to support this motivation in order to develop a reflective mode of innovation beyond the affirmative or skeptical mode of computer use. The measurement scale for computer readiness and the analytical instrument for teachers class membership can be used to identify prerequisites for changes in computer use.

INTRODUCTION

The development of information technology represents an increasing challenge for schools to use computers and data processing systems in computer education and in traditional school subjects. Despite the growing number of computers in schools, the integration of computer use in traditional subjects remains a problem. In a survey of research results from different countries, Akker et al. [l] conclude that still few teachers are actual users, and those that are mostly give special courses. As a consequence they suggest inexperienced teachers be given the chance to use computers effectively in their classroom. This can be done by “infusion” of high quality courseware and support materials, and teacher training for reflective learning.

In this approach innovation depends primarily on the role of the classroom teacher in a supportive school environment. A central requirement for innovation is the change of teachers’ behavior, beliefs and attitudes.

At present, innovation concerning integration of computer use in different subjects meets several practical problems. Maddux[2] points at two main obstacles: one is the insufficient number of computers in a school so that they cannot be distributed in different classrooms. Another obstacle is the lack of teachers’ skills and competencies with computer use in traditional content areas. Especially with the infusion approach, he emphasizes the requirement for teachers to change their attitudes.

Computer readiness can be used as a predictor for change. Thus, Crandall[3] developed a model from an extensive analysis of different innovation projects where teachers’ readiness was a significant predictor of change in practice.

A study on readiness and change in computer use requires specification of relevant teacher and context variables. In this case the variables are defined according to the system approach of the IEA (International Association for the Evaluation of Educational Achievement) study “Computers in education”[4]. The IEA is conducting a longitudinal study in more than 20 countries to monitor

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the outcomes and changes in the educational systems. These outcomes are defined in a hierarchical model as: intended, implemented and attained curriculum at different levels of decision-making. The hierarchy implies that changes in the curriculum normally start from the top with the intended curriculum, are realized by teachers’ efforts of implementation and finally are attained by students’ outcomes. But interactions between different levels also allow deviations from this hierarchy. Teachers’ readiness may be an important focus for change close to the base of the hierarchy.

This study is being conducted in two stages. In stage one, documents from higher level administration and data from teachers and school questionnaires are analyzed. The main focus is on the degree of implementation of computer use as a separate subject or within already existing subjects. In a second stage student outcomes will be analyzed.

Teachers computer-readiness is not elaborated as a critical factor in the IEA system so that we introduce it as a primary variable in the study of teachers’ efforts at implementation. The other variables describe the context.

COMPUTER READINESS IN THE IEA SYSTEM FOR INNOVATION

The IEA system approach distinguishes between three levels of curricular output: the macro-level of the intended, the meso-level of the implemented and the micro-level of the attained curriculum (see Fig. 1). The intended curriculum is defined by the influence of government and inspectorate,

System Actors/ level influential factors

Curriculum output

Macro

. . . . . . . . . . . . . . . . . . . . . . . . . . .

Meso

Government Insoectoratel - Intended ch&acteristics, resources, etc.

Teacher training Publishers Software development

School principal - School board 4

Department/ characteristics, resources, etc.

.

Teachers/ I 1

L

--I 1 readiness 1

t-l

Implemented characteristics, resources, etc.

Micro

Attained

Fig. 1. Global model of the IEA-study ‘Computers in Education’[4] showing relations between components and information channels, with the variable ‘readiness’ inserted.

Computer readiness of teachers 303

the implemented curriculum by the influence of school principals, school boards, departments and teachers and the attained curriculum by students’ cognitions and attitudes. Readiness is introduced in Fig. 1 as a variable of teachers’ influence on the implemented curriculum. In the following the function and definition of readiness in this system will be elaborated.

Bauer ef al. [S] describe the function of readiness for change in a system with two forces tending to equilibrium. On one hand pressure for action is produced. On the other these intentions are perceived and evaluated and possible reactions for restoring the balance are generated. In a school system teachers can react to intentions with readiness or resistance in order to restore a balance. In terms of the underlying field theory developed by Lewin[6], readiness as teachers’ intentions to change is embedded in a field of congruent or divergent forces such as accepted or rejected demands by the ministry, the principal or colleagues, and considerations like responsibilities or attitudes. Readiness is assumed to be an indicator of these forces.

This description of readiness fits adequately into the IEA system approach: the “intended curriculum” on the macro-level is an equivalent of the notion “pressure for action”, the “implemented curriculum” on the meso-level is the result of teachers’ reactions to rearranging a balance. The frame of reference for action is defined by teacher training, institutional support or influence of leadership in a department or a school. On the micro-level the “attained curriculum” would be the effect of innovation measured by learning outcomes and attitudes of students.

Within the IEA system the construct of readiness has so far been described by its function of influencing equilibrium. If we want to describe readiness more precisely we have to define variables that may explain this function. Several definitions appear in the literature.

Boeshaar [7] defines computer readiness “as a state of awareness, motivation and prior knowledge pertaining to computing and computers, and the subject’s ability to apply this in the classroom setting”. I-Ie distinguishes between data about prior computing experiences, training, and affective readiness. The affective component is measured by the Computer Readiness Index CRI[8]. The scale for this index contains 11 positive items (e.g. talking and learning about computers, trying to use computers) and 12 negative items (e.g. avoiding computers). The readiness scale correlates with time spent on a computer, amount of training and current type of use of non-use. The scale is developed for use by trainers and in-service educators to develop training programs and materials. The index does not include situational factors in schools like availability of resources, organizational structures or educational objectives as mentioned in Rosenblum et al.[9]. They should be included in our study. The authors define readiness for change as the first of four steps in a process of change. These steps are: readiness, initiation, implementation and continuation. In their overview of different theories of readiness this first step is also called “awareness”, “interest” or “evaluation”. It is assumed that readiness for change is a result of different personal and situational factors: attitudes, recognition of unmet needs, clarity of goal structures, organizational structures, leadership, professionalism of staff, history of successful changes and availability of resources (money, personnel, time, material).

Crandall [ IO] defines readiness as teachers’ motivation, skills and understanding of their practice, their resources and support for change in their classroom activity.

In summary, computer readiness can be defined as teachers’ awareness of intentions at various levels in a hierarchical system and their positive or negative reactions to them. Such reactions are indicated by degree of interest or motivation to use computers, willingness to learn more and to be informed about computers, attitudes toward computer use and activated knowledge about computer use in the situational context of availability of resources, support, problems and cooperation in the school.

DEFINING THE RESEARCH QUESTION

Data for the analysis of computer readiness were gained from IEA-questionnaires of a sample of 696 schools in 9 states of West Germany at secondary level I (452) and II (244). Different questionnaires were used for school principals, computer coordinators; also for teachers at various subjects and teachers of computer education in various types of school at secondary level I (grades 7-10) and II (grade 12). The sample of 1123 teachers in the survey were given instructions to

304 MANFRED LANG

answer different parts of the questionnaires referring to computer use by students in classes or courses, computer use for demonstration, or non-use.

In 1989, the year of inquiry, 77% of the schools with secondary level I and 99% with secondary level II were equipped with computers for educational purposes.

In the computer-using schools there were on average 3 teachers for each school level giving either courses in computer education or using computers in various subjects. At secondary level I 36% of these teachers used computers in mathematics, 26% in economics/politics, 20% in science and only 11% in mother tongue. At secondary level II 24% of teachers used computers in mathematics, 16% in science and only 2% in language arts. Here computer use was concentrated in special courses for computer education (informatics).

These data lead to the following conclusions concerning integration of computer education in different subjects:

(1) The average number of 3 teachers for computer education per school is low compared with numbers of teachers for most of the other subjects.

(2) The prevailing use of computers in special computer courses or mathematics indicates no widespread use of computers in various subjects.

In spite of the relatively high supply of computers in schools, the number of computer-using teachers per school and, in subjects other than computer science of mathematics, is low. This situation justifies the research questions about computer use by more teachers and in more subjects. Answers can be found by the analysis of teachers’ computer readiness, related to conditions in the school.

CONSTRUCTING A SCALE FOR COMPUTER READINESS

Readiness, as teachers’ reactions of interest, motivation, willingness to learn and to get information about computer use, and attitudes to and activated knowledge of curricular intentions, is assumed to be represented by answers to the following items: Nine items about attitudes measured on a Spoint scale of agreement or disagreement:

(1) I would like to learn more about computers as teaching aids.

(2) I don’t mind learning about computers.

(3) I could (can) well do without the aid of a computer in my class.

(4) Working with computers in class distorts the social climate.

(5) Computers harm relations between people.

(6) Computers are valuable tools in improving the quality of a child’s education.

(7) Computers can only be useful in a few subjects.

(8) Using a computer in a classroom makes a subject more interesting.

(9) Computers in school enhance students’ creativity.

Two items about prior knowledge:

(10) Do you have access to a computer for use at home?

[ 1 yes [I no

If yes, roughly how many hours per week do you use a computer? [ ] l-5h [] 6-10h [ ] 11-15h [] 1620h [ ] more than 20 h

(11) I inform myself regularly about computers and software in special literature (never/some weeks/most weeks/every week).

One item about interest:

(12) I am interested in using computers in lessons (not at all/a bit/moderately/very much).


In order to find differences in computer readiness a latent class analysis [ 11,121 was calculated for these 12 items and for a reduced set of 8 items from the 1123 teacher questionnaires.

The latent class analysis groups teachers into the most likely classes, characterized by several variables. The membership by each individual of the latent classes is probabilistic.

For the latent classes, alternative models with different assumptions about distances between categories are calculated on the basis of ratios of the response probabilities of two neighbouring categories. As in log-linear models, it is assumed that the logarithm of this ratio is a linear function depending on variable i, category x and the latent class g to which a person u belongs.

The latent class analysis is calculated by the LACORD program (LAtent Class Analysis for Ordinal Variables)[ll]. This program estimates the parameters of eight different models with ordered categories, making different kinds of assumptions about class-specific or class-independent distances. The goodness-of-fit for a model is estimated by the BIC (Bozdogan Best Information Criterion)[l3], which is a function of the log-likelihood and the number of effective parameters in a given model.

For the analysis of our data, models with 2, 3 or 4 classes were calculated. The 3 class solution with 8 items of a model with no assumptions about category and item distances fits best for the data, indicated by the lowest BIC value.

The first class of teachers in the 3-class solution can be described as more skeptical about use of computers for school purposes. This class represents 22% of all teachers in our study. In the second class 33% of the teachers were described as affirmative to computer use and in the third class 45% of the teachers were described as generally interested in learning more about computer use.

The first two classes are best differentiated by differences in answers to items about attitudes to computers and education (items 8,9), willingness to learn more about computers (item 1) and social effects (items 4, 5) computer use at home (item lo), reading of special literature (item 11) and interest about computers (item 12). Teachers from class III give answers similar to those from class II: they are very interested in learning more about computer use in education but the intensity of private computer use and use of computer literature and the strength of attitudes toward computer use is lower (see Fig. 2).

The differences described by the three classes of teachers can be used in two different ways:

(a) To develop a readiness scale for the measurement of differences on a continuum (b) To sort teachers into three distinct classes by class membership for further analysis of types

of teachers and their computer use.

The first point is realized by a readiness scale, constructed by adding up the scores on all items representing the three classes. For items 4 and 5 the scale is reversed, so that all scales have the same direction. The readiness values are resealed so that they range from 1 to 9 with a theoretical mid-point of 5.

0 Class I A Class II * Class III 4

0.5 -

0 I I 1 A I I I I I I Interest Information Comp.

(12) (11) Learn more Enhance Subj. more Distorts Harms

at home about camp. creativity social relations (10)

interesting (1) (9) (8) climate (5)

(4)

Fig. 2. Expectation values for different classes of teachers readiness.

306 MANFRED LANG

The correlation between class membership of a teacher from the latent class analysis and computer readiness, described by q, has a high value of 0.89. This means that computer readiness is high (7, 8, 9) for teachers being affirmative in computer use (class II), medium (5, 6) for teachers being generally interested in learning more (class III) and low (1,2,3,4) for teachers being skeptical for social or educational reasons (class I).

In the next section the computer readiness scale and the teachers class membership are used to analyze variables relevant to computer education.

RESULTS

Analysis of variance was used to test differences between teachers’ computer readiness, measured by the readiness scale, and

(1) Kind of computer use in school: use by students, use for demonstration by teachers, non-use; (2) Sex: male, female; (3) School types: Hauptschule (technical), Realschule (non-academic), Gymnasium (high

school); (4) School levels: secondary level I, II; (5) Knowledge and skills about computer use in school: sufficient, insufficient; (6) Subjects taught: informatics, mathematics, science, language arts.

F-ratios are highly significant for the main effects for: kind of computer use (F = 35, d.f. = 2), knowledge and skills (F = 34, d.f. = 1) and sex (F = 11, d.f. = 1). School types, subjects taught and school level have no significant effects on computer readiness. Relatively weak interactions are found between the kind of computer use and sex (F = 3, d.f. = 2) and assumed knowledge and skills (F = 3, d.f. = 2). The overall multiple correlation is r = 0.53. In Table 1, data for main effects and significant interactions are summarized.

The mean scale value of computer readiness for teachers with courses or classes of students using computers is 0.5 points above the general mean (6.6). It is slightly higher than the mean value for teachers using computers only for demonstration. Non-using teachers have a lower mean (5.7). For computer-using teachers the mean scale value for male teachers is 0.8 points higher than for female teachers, and for teachers with knowledge and skills about computer use 1 .l points higher than for those without.

An alternative approach to the readiness scale is to think of distinct classes of teachers whose computer readiness is defined according to the Latent Class Analysis (LCA). Analysis of class memberships should not contradict results from the analysis of scale values but additional views from the combination of categories of different classes are expected.

As a result of the LCA 22% of all teachers are in class I (skeptical about computer use), 33% in class II (affirmative) and 45% in class III (interested to learn more about computer-use). These classes or types of teachers can be used for a further LCA [l l] with other variables relevant for computer use. For comparison with the analysis of variance, the same six variables are used (kind of computer-use, sex, school type, school level, judged knowledged and skills and subjects taught).

This additional LCA for 2-, 3- and 4-class models gives the best results for a 2-class solution with the best goodness-of-fit. (The BIC test criterion for this solution is lower than for the 3- and 4-class solution.)

Table I. Means, frequencies, F-ratios and significant differences of computer readiness between male and female computer using

and non-using teachers, with or without knowledge and skills about computer use in school

Variables NO

Computer use of teachers

Yes for Yes in demonstration classes/courses Total d.f.

F-ratios

(main effects)

sex male 5.8 (276) 6.6(14) 7.2 (446) 6.7(736) female 5.5 (80) 7.0 (3) 6.4 (57) 5.9(140)

I I I (ss)

Knowledge/skills yes 6.1 (145) 6.9 (14) 7.2 (473) 6.9(632) no 5.5 (211) 5.3 (3) 6. I (30) 5.5 (244)

l 34 (ss)

Total 5.7 (356) 6.7(17) 7.1 (503) 6.6(876) 2 35 (ss)


Results of the 2-class solution indicate that the three types of readiness can be differentiated in two ways:

(1) Teachers who are affirmative (class II type of readiness) are mostly male, use computers in classes or courses, and have sufficient knowledge and skills for computer use and for teaching informatics or mathematics.

(2) Teachers who are skeptical (class I type of readiness) mostly do not use computers in classes or courses, and lack knowledge and skills for computer use and teaching language arts.

An estimate of the strength of different predictors to explain the three classes of readiness is given by the index of coherence between variables, q2. The values of q2 are

0.20 for “kind of computer use” 0.10 for “estimated knowledge and skills” 0.06 for “sex” and 0.04 for “subjects taught”.

The values of the last two predictors are low indicating a small contribution to explaining computer readiness.

Teachers generally interested in learning more about computers (class III type of readiness) are not differentiated by these variables. School level and type are not relevant for differences in the 2-class solution.

These results confirm the same trend of analysis of variance for low and high values on the readiness scale. In addition there is a differentiation between subjects taught if informatics and mathematics are taken as a unit.

Since the 2-class model produced by the LCA is only based on main effects and no interactions, a special log-linear analysis for interactions with hierarchical structure (CHAID, Chi-square Automatic Interaction Detection, Langeheine [14]), was calculated in addition. This analysis confirms the trend of interactions from analysis of variance. The model for differences betwen male and female teachers using computers in school, and assuming their knowledge and skills to be sufficient, are significant (x2 = 18, d.f. = 2). This means that computer-using teachers with sufficient knowledge and skills are affirmative (class II) when male and are mostly interested in learning more about computer use (class III) when female.

It is assumed that the readiness to use computers is dependent on problems experienced. In the questionnaires teachers could confirm the presence or absence of different problems with

hardware, software, lesson planning, organization or others. Computer-using teachers have different problems while using computers, non-using teachers are trying to overcome obstacles to use.

The most often stated problems or obstacles were:

not enough computers, technical limitations of computers, lack of software, not enough time for students to learn about computer use, not enough time to prepare lessons with computer use, lack of interest and readiness of colleagues, and difficulties to integrate computer use in school practice or the curriculum.

Not all of these problems or obstacles are related to computer readiness. Pearson correlations between presence or absence of problems and scale values of computer

readiness were calculated and tested for significance. Low but significant positive correlations (with n = 755) were found between computer readiness and the problems of an insufficient number of computers (r = 0.16), technical limitations of computers (r = 0.26), not enough software for lessons (r = 0.30), insufficient financial support (r = 0.16) and lack of interest and readiness of colleagues (r = 0.28).

308 MANFRED LANG

DISCUSSION

The concept of high computer readiness indicates an affirmative view of one’s interest, attitudes and prior knowledge about computer use. Problems with computers do not limit this view, but are stated with the assumption that they can be solved. Teachers with low computer readiness are not simply rejecting computer use in school. In relatively few cases are they stating problems and being skeptical about the educational purpose. This might be due mainly to their lack of knowledge and skills but in most cases teachers agree to learn more about computer use in school.

Teachers with a medium range of computer readiness generally have some limited experience and interest in computers but are insecure about the educational purpose. They are interested in learning more about computer use in school. They are not differentiated by the predictors kind of computer use or amount of knowledge and skills for computer use.

If we follow the infusion approach to innovation, teachers are introduced to computer use by high quality courseware and materials and training to improve their knowledge and skills. This approach should have positive effects on computer use because a high proportion of teachers is interested in learning more about their use in school and in solving problems they experience when using computers. However, the reasoning that teachers first have to change negative attitudes they will not use computers is not convincing. Skeptical teachers do not refuse to learn more about computer use and do not use problems as arguments against computers.

Innovation should, however, not end with an affirmative view of computer use. The skeptical and the affirmative views could be different starting points for productive practice. It is not sufficient only to supply teachers with computers for private practice or to offer teacher training only about basic concepts and programming. Instead an infusion approach should be tried with high quality courseware and materials and teacher training with more opportunities for reflection about computer-use and education.

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REFERENCES

Akker J. van den, Keursten P. and Plomp T., The integration of computer use in education. Ini. J. Educ. Res. 17, 65 (1992). Maddux C. D., Integrating the computer into the curriculum: the need for caution. Computers in Schools 6,31 (1989). Bauchner J. E., Eisemann J. W., Cox P. L. and Schmidt W. H., People, Policies and Practices, Vol. III: Models of Change. The Network, Andover (1982). Pelgrum W. J. and Plomp T., The IEA-study ‘Computers in Education’: A Multi-National Longitudinal Assessment (Edited by Lovis F. and Tagg E. D.). Elsevier, Amsterdam (1988). Bauer K.10. and Rolff H.-G, Innovation und Schulentwicklung. Beltz, Weinheim (1978). Lewin K.. Field Theorv in Social Sciences. Harner St Row. New York (1951). Boeshaar D., Computer Readiness Index (CRI): Academic’Computing Services, Syracuse University, Syracuse. Boeshaar D., Computer Readiness Index (CRI). Education Version. Academic Computing Services, Syracuse University, Syracuse (1986). Rosenblum S. and Seashore Louis K., Stability and Change. Plenum Press, New York (1981). Loucks S. F., Cox P. L., Miles M. B., Huberman K. M. and Eisemann J. W., Portrait of the Changes, the Players, and the Context. Vol. II. The Network, Andover (1982). Rost J., LACORD, Latent Class Analysis for Ordinal Variables. IPN, Kiel (1990). Rost J., Br. J. Math1 Statist. Psychol. 44, 15 (1991). Bozdogan H., Psychometrica 52, 345 (1987). Langeheine R., 2. Sozialpsychol. 15, 254 (1984).

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Computer readiness of teachers