JVER v25n4 - A Comparison of Information Technology Training Sources, Value, Knowledge, and Skills for Louisiana's Secondary Vocational Teachers

A Comparison of Information Technology Training Sources, Value, Knowledge, and Skills for Louisiana's Secondary Vocational Teachers

Joe W. Kotrlik Louisiana State University
Betty C. Harrison Louisiana State University	Donna H. Redmann Louisiana State University

Abstract

The population for this study consisted of secondary vocational education teachers in six vocational fields. Vocational teachers see the value and usefulness of information technology in their programs; they just don't have the necessary skills and knowledge to use it effectively for instructional purposes. Vocational programs must prepare students for the workplace and society, both now and in the future. Though teachers value the Internet and other types of information technology, their full understanding of the interrelatedness of information technology to program quality may yet to be realized. Vocational teachers have average to below average levels of both general and software specific information technology knowledge and skill. Teachers use self-directed training, personal experience, written materials and in-service provided by schools or state agencies as their primary sources of training. Teachers must continue to value information technology and seek ways to connect program and instructional management with appropriate information technology, especially the Internet.

Introduction

Computers are pervasive in the workplace, in the classroom, and in the home. Technological advances and the accelerated transfer of information, along with related knowledge, skills, and abilities, are of paramount importance in an information society. Many changes have occurred in this arena, and this change is especially important to vocational programs supporting workforce development. The growth and use of computers and related technology are limited only by one's imagination. Linking the technology and the explosion of information to support human resource development and the preparedness of individuals for the workforce may begin at home; however, this linking impacts the professional educator and related responsibilities in instructional design and delivery in educational settings. The teacher is the change agent between the learner and technology, and plays a critical role in the process of teaching and learning ( Chin & Hortin, 1994 ). Therefore, it behooves the teacher to stay abreast of changing technology and current opportunities in order to assure his/her place of leadership in instructional technology. That, in turn, is supported by the cry from business and industry for better-prepared individuals for the global workforce.

Before further addressing teacher competencies in the area of information technology, it is important to address whether technology enhances learning. Dede ( 1997 ) states that new technologies promise a rich education experience. This opinion is supported by studies that have reported significant gains in learning when using technology. Goldberg ( 1996 ) reported that students who were taught using both traditional methods and the Internet performed better than two other groups who were taught using either the Internet or traditional lecture, i.e., the Internet used in combination with traditional methods enhanced learning. Day, Raven, and Newman ( 1998 ) found that students who were taught using the Internet with a laboratory achieved at a higher level than those students who were taught using the traditional classroom approach. Ganguli ( 1992 ) found that the CAI (computer assisted instruction) in mathematics instruction group experienced higher enjoyment, more motivation, and better understanding of the concepts in the course. Students taught chemistry using a computer simulation scored better than students taught using the traditional lecture method and the learning cycle method ( Jackman, Moellenberg, & Brabson, 1987 ). It is clear that improved learning can result from using technology in instruction.

During the eighties, with the inclusion of computers in classrooms becoming more prominent, the need for teachers to become more technologically literate was realized. Nagourney ( 1989 ) considered technological literacy among the new basic skills. In 1990, Pomeroy found that half of the vocational teachers in Southern Nevada were not computer literate. Of those vocational teachers who were computer literate, 62% of them were self-taught, and 71% indicated they learned their computer skills after beginning to teach. In 1997, Daulton reported that family and consumer science teachers' adoption rate for computer technology had increased from 5% in 1983 to 83% in 1993. Daulton concluded that "Although the microcomputer had not reached a 100% adoption rate by 1993, the adoption of microcomputers for educational purposes by family and consumer sciences teachers had dispelled the belief that microcomputers would eventually end in the closet like so many other pieces of audio-visual equipment" ( p.59 ).

A report from the Office of Technology Assessment ( 1988 ) stressed that the use of technology cannot be fully effective unless teachers receive adequate training and support. Keeping current has been especially critical because teachers need information technology competencies so they can transfer these competencies to students ( Sormumen & Chalupa, 1994 ).

Relatively few studies in the area of information technology were conducted in the 1990's. Garton and Chung ( 1996 ) reported that in-service training on the use of computers in classroom teaching was ranked sixth out of 50 in-service needs of agriscience teachers. They queried whether teacher unfamiliarity with selected technologies and related capabilities resulted in low acceptance/use of those technologies. Another related factor, computer anxiety, was studied by Kotrlik and Smith ( 1989 ) and Fletcher and Deeds ( 1994 ). Both studies reported that younger teachers were more likely to have higher levels of computer literacy, and that computer anxiety decreased as computer literacy increased.

A 1997 study conducted by the National Center for Education Statistics ( Heaviside, Riggins, Farris & Westat, Inc., 1997 ) found that more than 50% of schools technology training was left up to the teacher. This study also found that only 20% of teachers used advanced telecommunications for teaching.

With the explosion of technological advances in all areas has come the increased need for higher competencies in the area of information technology. The risk of not meeting workplace needs increases without it. Critical competencies in the area of instructional technology by the instructional leader in any setting can make or break a program whose goal is to prepare persons for the workplace.

Theoretical/Conceptual Base

Theories of adult learning are highly relevant to information technology training. Heerman ( 1986 ) and Zemke ( 1984 ) indicated that self-direction, intrinsic motivation, role of problem solving, and immediate value in learning activities have been shown to be critical in computer learning tasks. In the preparation of instructional leaders, including teachers, training should incorporate competencies in software knowledge versus system-specific skill ( Lammers, 1986 ).

Using computers and computer-based learning systems in education is viewed as a major contributor to increased learning. Learning theories such as those by Pask, Spiro, and Salomon are considered especially relevant to the use of information technology in learning. Pask ( 1975 ) developed the Conversation Theory, and it applies to learning of any subject matter. Information technology incorporates "teachback" which is a critical method of learning according to this theory. The "teachback" method is where one person teaches another what he/she has learned, and where students learn relationships among the concepts. The Cognitive Flexibility Theory builds upon other constructivist theories and is related to the work of Salomon in terms of media and learning interaction ( Spiro & Jehng, 1990 ). Spiro and Jehng stated, "By cognitive flexibility, we mean the ability to spontaneously restructure one's knowledge, in many ways, in adaptive response to radically changing situational demands" ( p. 165 ). This theory is largely concerned with the transfer of knowledge and skills beyond the initial learning situation. "Cognitive Flexibility Theory is especially formulated to support the use of interactive technology" ( Kearsley, 1998, p.1 ). Salomon ( 1979 ) developed the Symbol Systems Theory which is intended to explain the effects of media on learning. Included among the principles of the Symbol Systems Theory are the symbolic coding elements of particular media which require different mental transformations (that affects the mastery of specific skills), and the reciprocal relationship between media and learner (each can influence the other). In 1991, Salomon, Perkins, and Globerson reported the extension of the framework of Salomon's theory to computers.

A constructivist approach for vocational education programs ". . where learners may work together and support each other as they use a variety of tools and information resources in their guided pursuit of learning goals and problem solving activities" ( Wilson, 1995, p. 5 ) seems appropriate as a foundation for a study of secondary vocational teachers' views regarding information technologies. An "environment that is good for learning can not be fully pre-packaged and designed" ( Wilson, 1995, pp. 4-5 ). The learning environment includes computers and other technologies along with an abundance of available information. Therefore, the need for the teachers, or instructional leaders, to be competent in information technologies and to be prepared to address current and future needs of the learners is critical for the transfer of learning and for learners to transition to the workplace. Sormumen and Chalupa ( 1994 ) indicated that the use of technology can not be fully effective unless teachers receive adequate training and support.

Review of Relevant Research

Several studies have been conducted that addressed relationships between selected demographic variables and computer use. One such study was Zidon and Miller ( 1990 ) who found that weak relationships existed between demographic variables, such as age, gender, and years of teaching, with perceptions of computer use. They concluded that "such demographic variables need not be considered when planning in-service training or planning to include computers in a secondary agriculture curriculum" ( p.237 ).

Conversely, in a study of teachers perceptions of the need for computers, Princeton Research Associates, Inc. ( 1993 ) addressed technology in the classroom for the National Education Association, and found that almost two-thirds (59%) of teachers under 35 years of age believed computers in the classroom were essential while only 29% of teachers over age 55 shared this belief. Furthermore, half of the teachers in low technology schools had home computers. The report concluded that many teachers lack access to technologies they believe to be essential resources. In a related study, Martin & Lundstrom ( 1988 ) found that having a computer in the home and having taken computer coursework contributed to home economics teachers' attitudes toward computers. In an even earlier study, Yuen ( 1985 ) concluded that trade and industrial teachers had a favorable attitude toward using computers. Trade and industrial teachers who had experience in working with microcomputers, or who had training in using microcomputers, were more in favor of using microcomputers in industrial education than those who did not have this experience or training. In a more recent study, Ghomita ( 1995 ) found consistency between business teachers' attitudes toward microcomputers and their adoption of the microcomputer, and Marcinkiewicz ( 1996 ) found that self-competence and perceived relevance of information technology are highly correlated. Marcinkiewicz ( 1996 ) also found that for information technology to be adopted, there needs to be a perception generated by the professional environment that computer integration is expected.

Several studies have addressed factors related to the use of information technology by vocational teachers. McCaslin and Torres ( 1992 ) found three factors that accounted for 54% of the variance in vocational teachers attitude toward using microcomputers in in-service training, namely, their educational value, confidence in their use, and apprehension about their use. Two studies ( Kotrlik and Smith, 1989 ; Fletcher and Deeds, 1994 ) supported apprehension of using computers thorough measures of computer anxiety. Both studies reported that younger teachers were more likely to have higher levels of computer literacy and computer anxiety decreased as computer literacy increased. Golden ( 1997 ) supported these findings when he stated that teachers do not use new technology either because they feel uncomfortable with new technology or because they lack proper training. This was supported by J. A. Miller ( 1997 ) when she stated that, "As schools spend more on technology, they're budgeting even less for training teachers to use it effectively" ( p. 13 ).

Birkenholz, Stewart and Craven ( 1989 ) studied the extent to which instructional technology had been adopted in secondary programs of agricultural education. The study documented the rapid increase in the use of technology in agricultural education and found that teachers supported the development of technological advances for use in their curriculum. However, in a 1996 study of Idaho teachers, Mathews, David and Hamilton found that up to one-half of all teachers never actually used technology for any instructional purpose. Over half rated themselves as novices in all areas studied. Chin and Horton ( 1994 ) found that " … numerous recent studies have shown that teachers want to use the newest technology and to prepare their students for the world of technology outside of school. Apparently, what teachers really need is more time to acquire the knowledge and understanding of technology, and to absorb what instructional technology can do for them" ( p. 87 )

Honey & Moeller ( 1990 ) studied the relationships between teachers' beliefs and technology integration. They found that low-tech teachers tended to be more heterogeneous as a group when compared to high-tech teachers and that they could be characterized by three different characterizations:

"First, there were teachers whose educational beliefs were student-centered, like those of the high-tech teachers, but they were reluctant to use information technologies because of personal fears and inhibitions. Second, there were teachers whose classroom practices and educational objectives were much more traditionally based … . Finally, there were teachers whose practices tended to be student-centered and who would have liked to use computers, but either the equipment was not available or they had problems scheduling time in the computer lab ( p. 3 ).

Gonzenbach and Davis ( 1999 ) stated that, "Not only are new products and technologies constantly developing and changing, their impact is reshaping methods and materials used for classroom instruction" ( p. 58 ). They cited a report entitled, "Knowledge Workers in Demand Through Year 2000," when they stated that, "By the year 2000, 20% of all jobs will require knowledge workers; workers who are charged with gathering, analyzing, and disseminating information for their employers" ( p. 26 ). This is supported by the SCANS Report which calls for graduates to have competencies in the selection and application of technology ( U.S. Department of Labor, 1992 ) and by Martin and Lundstrom ( 1988 ) who concluded that preparing students for the world of work means providing them with computer experiences.

Not only is this area a concern in the United States, it is also a concern in other countries. For example, Bakar and Mohamed ( 1998 ) found that Malaysian vocational and technical teachers did not have a high level of general knowledge about computers. They were not very knowledgeable or skillful in the use of computer software. The teachers indicated they would like to attend training in using computers for instruction. Bronkhurst ( 1997 ) reported that the Netherlands is devoting 50% of student study time in teacher education programs to teach with information and communication technologies, and multimedia. The conclusions reported by Na and Barrick ( 1993 ) in their study of Korean agricultural education teachers' attitudes toward computer technology were similar to conclusions of studies in the United States. They found that several personal characteristics were related to the current study, including perceived value of computer applications, perceived need for classroom computer use, and number of information sources on computers.

Kang ( 1995 ) studied computer simulations as a framework for critical thinking instructions, and found that computer simulations were helpful in developing critical thinking skills. Computer use alone will not develop those skills but wise choice of software can enhance learning. Ingram ( 1996 ) indicated several principles to guide the thought process when considering how to apply the possibilities of information technology to educational efforts. One of those principles to keep in mind: Technologies do not teach; people do. Further, Ingram ( 1996 ) stated that the material, the audience and the instructional methods are the critical elements to consider, and once those have been effectively combined, then one can choose the technologies to deliver the message.

Kitagaki ( 1995 ) indicated that young people just beginning a career will be more concerned with learning technology at a faster pace to be proficient in their career field. For instruction to expedite the transfer of learning, teachers must adopt and integrate new technology into their instruction by whatever means are available. For example, Downing and Rath ( 1997 ) found, "…that the Internet, using the Intranet model developed by the business community, can serve as a unique and solid starting point for an electronic classroom" ( p. 287 ).

In summary, this review of research has shown that information technology is generally considered to be essential by business, industry, and education. A need for students to possess information technology competence to enter into, and succeed in, the global marketplace has been shown ( Gonzenbach & Davis, 1999 ; U.S. Department of Labor, 1992 ; Martin & Lundstrom, 1988 ). Avenues of instructional methods and delivery have been established. Support for these methods is embedded in several key learning theories, namely, the Cognitive Flexibility Theory, Symbol Systems Theory, and Conversation Theory. The need exists for instructional leaders to possess information technology knowledge and skill so they can link learning in the classroom to the workforce. Therefore, this study focused on the information technology skills, knowledge and perceptions of vocational teachers, and their use of this technology in the transfer of learning.

Purpose and Objectives

The purpose of this study was to compare the information technology training sources, knowledge and skills for Louisiana's secondary vocational teachers. The objectives were to determine: (1) their demographic characteristics (degrees held, age, gender, ethnicity, years teaching experience, area where school is located [rural, urban or suburban], school level [high school, junior/middle school, or both], participation in professional associations); (2) the value of information technology as perceived by teachers; (3) the general information technology knowledge and skill levels possessed by teachers; (4) software specific knowledge and skills possessed by teachers; (5) teachers' perceptions of the potential usefulness of information technology in program and instructional management; (6) the availability of information technology to teachers; (7) the source of information technology training received by teachers in the last three years; and (8) if differences exist in how teachers value information technology, their general information technology skill and knowledge levels, their software specific skill and knowledge levels, and their perceptions of the usefulness of information technology by vocational program area.

Research Methods and Procedures

Population and Sample

The population for this study included 2,423 secondary (grades 7-12) vocational teachers in Louisiana. Using Cochran's ( 1977 ) sample size formula, a stratified random sample of 1,126 Louisiana vocational education teachers was selected from six program areas (agriscience, business, family and consumer sciences, health, marketing, and technology). Since this study targeted vocational teachers in grades 7-12, trade and industries instructors were not included in this study because most of these instructors are employed by post-secondary institutions in Louisiana.

Instrumentation

The scales and items used in the instrument were developed by the researchers after a review of the literature guided by the theoretical base of the study. A demographics section was included to provide a description of the sample used in the study. The face and content validity of the instrument was evaluated by an expert panel of university vocational education faculty and doctoral level graduate students representing all vocational program areas in the study. The instrument was field tested with 40 vocational teachers. Changes indicated by the validation panel and field test were made. These changes occurred in the wording of items and in the instructions for completing the instrument. Internal consistency coefficients for the scales in the instrument were as follows (Cronbach's alpha): Value of Information Technology in Instruction - .87, Information Technology Knowledge and Skill - .94, Software Applications Knowledge and Skill - .94, and Usefulness of Information Technology in Program Management - .94.

Data Collection

The teachers' responses were collected using two mailings and a systematic follow-up of a random sample of non-respondents. Each mailing consisted of a questionnaire, cover letter, and stamped addressed return envelope. The systematic follow-up of non-respondents included a telephone call to the random sample of non-respondents in which they were asked to complete and return the questionnaire. As a result of the telephone contact, the non-respondents either agreed to complete and return the questionnaire or were found to be frame errors. A third questionnaire with cover letter and stamped addressed return envelope was mailed to the non-respondents. A response rate of 55% (619 out of 1126) was attained. The results of the comparisons between the mail and phone responses are presented in the data analysis section.

Data Analysis

The data were analyzed using descriptive statistics for objectives 1 - 7. Analyses of variance with Tukey's post hoc mean separation test were used to analyze the data for objective 8. The alpha level was set á priori at .05. To determine if the sample was representative of the population and to control for non-response error, the scale means for the four primary scales were considered to be the primary variables in the study and the scale means were compared by response mode (mail versus phone follow-up) as recommended by Borg ( 1987 ) and Miller and Smith ( 1983 ). There were no statistically significant differences between the means for the four scales in the instrument by response mode. It was concluded that no differences existed by response mode, and the data were representative of the population. The mail and phone follow-up responses were combined for further analyses.

Findings

Objective 1

Objective one was to describe the demographic characteristics of vocational teachers. Almost half of the respondents (47%) possessed the bachelor's degree while over half had an advanced degree (master's - 27%, specialist or +30 - 25%, doctorate - .5%). More marketing teachers had higher advanced degrees than the other teacher groups, while the health occupations teachers had the lowest percentage of advanced degrees.

Over half (61%) of the respondents were female, the agriscience and technology teachers groups were primarily male (94% and 86%, respectively), and the business, family and consumer sciences, and health occupations teachers were primarily female (92%, 100%, and 95% respectively). Eighty percent of the respondents were white with five of the teacher groups consisting of between 72 and 78% white, and the agriscience teacher group consisting of 94% white.

The average age of the respondents was 44 years, and the average years of teaching experience was 17. The agriscience and business teachers had the lowest mean age while the health occupations teachers had the highest mean age. The business teachers had the lowest mean years of teaching experience while the technology teachers had the highest mean years.

Over half (53%) of the respondents taught in rural areas, 26% taught in urban areas, and 21% taught in suburban areas. Most agriscience teachers (82%) taught in rural schools while over half of health occupations teachers (57%) taught in urban schools. Over half (57%) of the respondents and almost all (95%) of the agriscience teachers had attended the state vocational association convention in the past three years. Only the agriscience teachers had over half (61%) of their group attend each of the last three years. Only 19% had attended a regional or national Association for Career and Technical Education (formerly American Vocational Association) convention in the past three years. Over one-half (62%) of the teachers' schools were connected to the Internet and some variation existed by teacher group. The differences in Internet connections may be related to urban location of the schools. These data are presented in Tables 1 and 2 .

Table 1
Comparison of Demographic Characteristics by Vocational Program (Continuous Variables)
Demographic Characteristic	Mean/Standard Deviations
	All	Ag	Bus	FACS	HO	Mkt	Tech
Age	44.01(8.75)	41.96(9.49)	42.52(9.10)	45.05(7.79)	49.53(7.86)	43.89(7.32)	45.93(8.02)
Years teaching experience	17.39(9.08)	17.72(8.88)	15.49(8.97)	18.06(8.69)	16.71(7.79)	18.02(9.22)	19.30(10.16)
Note: N=619. All=all vocational teachers in the study; Ag=agriscience education; Bus=business education; FACS=family and consumer sciences education; HO=health occupations education; Mkt=marketing education; Tech=technology education.

Objective 2

Objective 2 was to identify the value of information technology as perceived by vocational teachers. The respondents rated 33 statements on the following scale: 1=strongly disagree, to 5=strongly agree. The data revealed that vocational teachers placed a high value on information technology by strongly agreeing that teachers should know how to use computers (M=4.69), and that teachers (M=4.70) and students (M=4.64) should have computers available for instruction. The respondents agreed with the other 22 positively stated value of information technology statements (e.g., teachers should know how to use the Internet, should have Internet connections for teachers). They disagreed with all eight "negative" value statements (e.g., is too expensive to be cost effective, creates problems for the teacher, makes learning too mechanical, will

Table 2
Comparison of Demographic Characteristics
Demographic Characteristic			Vocational Program a
			All	Ag	Bus	FACS	HO	Mkt	Tech
Highest Degree Held:
Bachelors		N=	288	54	8	62	22	16	46
		%=	47	42	53	46	65	30	51
Masters		N=	167	39	43	38	10	13	24
		%=	27	30	26	28	29	25	27
Masters+ 30 hrs./Education Specialist		N=	151	37	35	2	23	23	19
		%=	25	29	26	6	6	43	21
Doctorate		N=	3	0	0	1	0	1	1
		%=	1	0	0	1	0	2	1
Gender:
Male		N=	237	123	14	0	2	20	78
		%=	39	94	9	0	5	39	56
Female		N=	377	8	151	136	37	32	13
		%=	61	6	92	100	95	62	14
Race:
White		N=	488	123	128	101	29	41	66
		%=	80	94	78	77	74	77	73
Black		N=	117	7	33	30	10	12	25
		%=	19	5	20	23	26	23	28
Hispanic		N=	1	1	0	0	0	0	0
		%=	0	1	0	0	0	0	0
Other		N=	4	0	3	1	0	0	0
		%=	1	0	2	1	0	0	0
School Location:
Rural		N=	308	103	85	63	71	20	30
		%=	52	82	56	49	19	37	35
Urban		N=	155	12	38	32	21	21	31
		%=	26	10	25	25	57	39	36
Suburban		N=	124	11	30	35	9	13	26
		%=	21	9	20	27	24	24	30
School connected to Internet (% responding yes)		N=	356	71	94	78	25	36	52
		%=	62	57	60	62	66	71	62
Number of state vocational conferences (0 to 3) attended in the past three years.	0	N=	260	6	88	74	16	26	50
		%=	43	5	55	55	42	48	56
	1	N=	111	14	30	29	13	10	15
		%=	18	11	19	22	34	19	17
	2	N=	83	16	25	15	6	7	14
		%=	14	12	16	11	16	13	16
	3	N=	152	93	18	17	3	11	10
		%=	25	16	12	13	8	20	11
Number of Association for Career and Technical Education (A.C.T.E. b ) national or regional conventions (0 to > 3) attended in past three years	0	N c =	487	92	129	114	28	46	78
		% d =	80	71	80	84	72	87	87
	1	N=	72	16	24	11	8	4	9
		%=	12	12	15	8	21	8	10
	2	N=	25	12	7	4	0	1	1
		%=	4	9	4	3	0	2	1
	3	N=	19	8	1	6	1	2	1
		%=	3	6	1	4	3	4	1
	> 3	N=	5	2	0	0	2	0	1
		%=	1	2	0	0	5	0	1
Note: N=619. Vocational Program a : All= all vocational teachers in the study; Ag=agriscience education; Bus= business education; FACS=family and consumer sciences education; HO=health occupations education; Mkt=marketing education; Tech=technology education. A.C.T.E. b = formerly American Vocational Association. N c = Number of respondents. % d = Percentage of respondents. Percentages do not add to 100% due to rounding error.limit student-teacher interaction, has little value in vocational education, will isolate teachers from one another). Minimal differences existed in individual items by program area. These data are presented in Table 3 .

Objective 3

Objective 3 was to determine the perceived information technology knowledge and skill levels possessed by vocational teachers. The respondents rated each statement on the following scale: 1= I don't know enough to respond, 2= My knowledge and skill in this area is below average, 3= My knowledge and skill in this area is average, 4= My knowledge and skill in this area is above average, and 5= My knowledge/skill in this area qualifies me as an expert. The data revealed that the teachers rated themselves average (between 2.50 and 3.49) on the eight areas related to the use of computers in instruction. The respondents rated themselves below average (between 1.50 and 2.49) on all of the newer technologies (Internet e-mail, multimedia computers, World Wide Web, laser disc players, video conferencing, compressed video, satellite downlinks). These data may be found in Table 4 .

Objective 4

Objective 4 was to determine vocational teachers' perceived knowledge and skill levels in the use of information technology software. The respondents rated each statement on the following scale: 1= I don't know enough to respond, 2= My knowledge and skill in this area is below average, 3= My knowledge and skill in this area is average, 4= My knowledge and skill in this area is above average, and 5= My knowledge/skill in this area qualifies me as an expert. The teachers rated themselves average (between 2.50 and 3.49) or below average (between 1.50 and 2.49) in all general application software areas, with the lowest ratings typically being in the area of software that has just become commonly used in the past few years (such as Internet e-mail, World Wide Web browsers, utilities, lesson planning, file transfer, and presentation software). The software specific knowledge and skill data are presented in Table 5 .

Objective 5

Objective 5 was to determine vocational teachers' perceptions of the potential usefulness of information technology. The respondents rated each statement on the following scale: 1= not useful, 2= low usefulness, 3= undecided, 4= moderately useful, and 5= highly useful. Vocational teachers perceived that information technology was moderately useful (between 3.50 and 4.49) in each of the program and

Table 3
Value of Information Technology
Information Technology Value	Mean(sd) by Vocational Program
	All	Ag	Bus	FACS	HO	Mkt	Tech
Teachers should know how to use computers	4.69(.70)	4.58(.67)	4.87(.58)	4.59(.80)	4.68(.76)	4.79(.64)	4.60(.72)
Teachers should know how to use the Internet	4.39(.84)	4.22(.88)	4.57(.70)	4.33(.93)	4.35(1.05)	4.50(.80)	4.32(.75)
Programs should have the following technology available for use in instruction:
Computers for teachers	4.70(.69)	4.60(.68)	4.83(.60)	4.64(.80)	4.68(.76)	4.79(.64)	4.68(.65)
Computers for students	4.64(.74)	4.51(.75)	4.88(.57)	4.48(.85)	4.53(.96)	4.77(.65)	4.60(.69)
Internet connections for teachers	4.44(.82)	4.36(.78)	4.55(.70)	4.34(.92)	4.50(1.02)	4.52(.85)	4.40(.77)
Multimedia computers for teachers	4.42(.82)	4.29(.84)	4.59(.69)	4.35(.90)	4.45(.88)	4.40(.91)	4.35(.80)
Multimedia computers forstudents	4.25(.87)	4.14(.94)	4.46(.74)	4.14(.90)	4.30(1.02)	4.19(.93)	4.22(.82)
Internet connections for students	4.09(1.01)	4.01(1.02)	4.25(.93)	3.96(1.03)	4.20(1.07)	4.28(1.07)	3.98(1.04)
laser disc players for teachers	3.93(1.00)	3.91(.98)	4.04(.94)	3.78(1.09)	4.00(1.09)	4.19(.91)	3.78(1.02)
video conferencing capability for teachers	3.93(.98)	3.83(.98)	3.97(.90)	3.88(1.01)	4.28(1.03)	3.96(1.10)	3.88(.96)
satellite downlink capabilityfor teachers	3.92(.96)	3.91(.97)	4.07( .89)	3.74(.97)	3.82(1.10)	4.00(.99)	3.90(.95)
compressed video capabilityfor teachers	3.74(1.00)	3.71(.98)	3.83(.98)	3.58(1.00)	3.71(1.06)	3.92(1.10)	3.77(.94)
laser disc players for students	3.65(1.03)	3.67(1.02)	3.64(.98)	3.56(1.05)	3.87(1.07)	3.80(1.13)	3.58(1.07)
Information technology:
helps individuals apply knowledge	4.47(.70)	4.31(.75)	4.61(.60)	4.49(.74)	4.40(.82)	4.63(.69)	4.37(.65)
can improve the quality of programs	4.42(.71)	4.27(.70)	4.53(.66)	4.38(.78)	4.46(.79)	4.58(.73)	4.41(.62)
is a useful instructional tool	4.42(.76)	4.25(.74)	4.60(.67)	4.37(.80)	4.30(1.09)	4.51(.78)	4.38(.60)
is essential to prepare students for the workplace	4.41(.84)	4.14(.83)	4.66(.70)	4.38(.92)	4.38(.95)	4.55(.83)	4.30(.79)
adds interest in instruction	4.41(.71)	4.21(.69)	4.59(.66)	4.40(.74)	4.35(.89)	4.51(.70)	4.37(.63)
can improve teacher effec-tiveness	4.37(.75)	4.16(.77)	4.56(.64)	4.31(.77)	4.25(1.03)	4.57(.73)	4.38(.62)
enhances student learning	4.29(.78)	4.16(.74)	4.49(.61)	4.19(.85)	4.28(.91)	4.37(.75)	4.17(.88)
is necessary for the successof students in the workplace	4.26(.88)	3.95(.91)	4.53(.73)	4.28(.91)	4.21(.98)	4.41(.88)	4.09(.87)
is important in instruction	4.23(.76)	4.05(.72)	4.47(.57)	4.11(.85)	4.18(1.01)	4.41(.75)	4.17(.74)
encourages teacher innovation	4.20(.77)	4.10(.71)	4.33(.69)	4.13(.77)	4.18(.93)	4.28(.78)	4.16(.89)
allows teachers flexibility inplanning their instruction	4.12(.78)	3.95(.78)	4.21(.74)	4.13(.78)	4.18(.85)	4.24(.76)	4.07(.82)
promotes self-directedlearning	4.07(.80)	3.99(.72)	4.09(.82)	4.02(.80)	4.03(.99)	4.16(.81)	4.17(.79)
is too expensive to be cost effective	2.48(1.10)	2.81(1.10)	2.10(.98)	2.61(.97)	2.28(1.05)	2.18(1.11)	2.79(1.26)
creates problems for theteacher	2.27(1.06)	2.45(1.01)	2.10(1.07)	2.22(.91)	2.03(1.14)	2.26(1.15)	2.48(1.15)
will limit student-teacher interaction	2.19(1.00)	2.46(1.02)	1.90(.83)	2.32(.98)	2.25(1.17)	1.96(.92)	2.28(1.12)
makes learning toomechanical	2.18(.93)	2.40(.91)	1.92(.83)	2.30(.89)	2.28(1.10)	1.86(.85)	2.28(1.02)
will isolate teachers from oneanother	2.06(.97)	2.29(1.04)	1.78(.73)	2.22(1.02)	2.05(1.05)	1.94(1.05)	2.06(.96)
has an adverse effect on teachers	2.05(.99)	2.13(.97)	1.82(.86)	2.14(1.05)	1.78(.92)	2.12(1.09)	2.28(1.06)
causes more problems than itsolves	1.99(.91)	2.24(1.00)	1.76(.81)	2.13(.90)	1.80(.93)	1.84(.84)	2.01(.87)
has little value in vocational education	1.69(.95)	1.84(.88)	1.44(.87)	1.72(.93)	1.82(1.21)	1.51(.93)	1.91(1.05)
Scale Means	3.73(.39)	3.68(.41)	3.79(.33)	3.70(.40)	3.71(.59)	3.77(.37)	3.73(.33)
N	619	131	166	136	41	54	191
Note: All=all vocational teachers in the study; Ag=agriscience education; Bus=business education; FACS=family & consumer sciences education; HO=health occupations education; Mkt=marketing education; Tech=technology education. Scale: 1=strongly disagree, 2=disagree, 3=undecided, 4=agree, 5=strongly agree.

Table 4
General Information Technology Knowledge and Skill Levels
General Information Technology Knowledge and Skill Levels	Mean(sd) by Vocational Program
	All	Ag	Bus	FACS	HO	Mkt	Tech
Know the major components of a computer	3.33(.98)	2.94(.88)	3.90(.73)	3.02(.86)	3.00(.99)	3.59(.90)	3.32(1.21)
Know how to operate a computer	3.23(.89)	2.93(.79)	3.75(.67)	3.00(.76)	2.90(.98)	3.46(.91)	3.08(1.03)
Can integrate computer- based teaching materials	3.11(1.02)	2.77(.95)	3.62(.83)	2.85(.95)	2.88(1.09)	3.33(1.03)	3.02(1.11)
Can evaluate software for instruction	3.10(1.03)	2.75(.93)	3.60(.85)	2.86(.99)	2.93(.97)	3.25(1.11)	3.05(1.18)
Can locate computer-based teaching materials for use in instruction	3.05(1.00)	2.70(.91)	3.43(.86)	2.85(1.01)	2.95(.96)	3.35(1.05)	3.00(1.07)
Know how to prepare students to use information	2.92(1.05)	2.61(.91)	3.53(.82)	2.50(.96)	2.45(1.09)	3.13(1.10)	2.97(1.12)
Know how to select information technology that fits program needs (computers, modems, printers, laser disc players, etc.)	2.83(1.05)	2.71(.93)	3.23(.94)	2.42(.97)	2.43(1.13)	3.17(1.13)	2.87(1.14)
Can evaluate software for program management	2.80(1.05)	2.64(.93)	3.17(1.01)	2.52(.98)	2.65(1.08)	2.91(1.17)	2.76(1.09)
Know how to use…
Internet e-mail	2.26(1.17)	2.09(1.02)	2.49(1.17)	2.09(1.12)	2.25(1.13)	2.59(1.35)	2.15(1.28)
Multimedia computers	2.24(1.13)	2.20(.97)	2.53(1.15)	1.94(1.03)	2.08(1.05)	2.47(1.28)	2.14(1.25)
World Wide Web	2.17(1.13)	2.06(1.02)	2.35(1.15)	2.00(1.09)	2.20(1.14)	2.41(1.28)	2.07(1.16)
Laser disc players	2.08(1.05)	2.09(.98)	2.18(1.08)	1.86(.95)	1.88(.99)	2.37(1.23)	2.15(1.11)
Video conferencing	1.70(.80)	1.72(.71)	1.70(.77)	1.64(.77)	1.85(.86)	1.76(.99)	1.67(.85)
Compressed video	1.63(.76)	1.74(.78)	1.62(.76)	1.54(.68)	1.68(.80)	1.57(.90)	1.61(.75)
Satellite downlinks	1.63(.76)	1.67(.67)	1.61(.74)	1.61(.79)	1.70(.76)	1.52( )	1.64(.82)
Scale Means	2.54(.74)	2.39(.68)	2.84(.62)	2.32(.67)	2.39(.80)	2.72(.85)	2.48(.86)
N	619	131	166	136	41	54	91
Note: All=all vocational teachers in the study, Ag=agriscience education, Bus=business education, FACS=family and consumer sciences education, HO=health occupations education, Mkt=marketing education, Tech=technology education. Scale: 1 = I don't know enough about this area to respond, 2 = my knowledge/skill level in this area is below average, 3 = my knowledge/skill level in this area is average, 4 = my knowledge/skill level in this area is above average, 5 = my knowledge/skill level in this area qualifies me as an expert.

Table 5
Software Specific Knowledge and Skill Levels
Software Specific Knowledge And Skill Levels	Mean(sd) by Vocational Program
	All	Ag	Bus	FACS	HO	Mkt	Tech
Word Processor (Examples: WordPerfect, Microsoft Word, Microsoft Works, Appleworks, etc.)	3.31 (1.11)	2.91 (1.05)	3.99 (.76)	3.10 (1.13)	2.93 (1.03)	3.64 (1.04)	2.92 (1.19)
Windows (Examples: Macintosh, Windows 3.1, Windows95, Windows NT)	2.75 (1.12)	2.45 (1.01)	3.21 (1.01)	2.49 (1.12)	2.61 (1.05)	3.00 (1.19)	2.63 (1.18)
Graphics (Examples: Corel, Paintbrush, MacPaint, Harvard Graphics, Freehand, Print Shop, etc.)	2.57 (1.06)	2.35 (.98)	2.93 (.93)	2.40 (1.11)	2.15 (1.01)	2.57 (1.08)	2.63 (1.12)
Spreadsheet (Examples: Lotus 1-2-3, Excel, Microsoft Works, Quatro Pro, etc.)	2.54 (1.14)	2.30 (.99)	3.18 (.99)	2.17 (1.14)	2.27 (.98)	2.93 (1.16)	2.18 (1.09)
Grade Book	2.54 (1.23)	2.44 (1.11)	2.70 (1.29)	2.35 (1.21)	2.44 (1.07)	2.89 (1.44)	2.51 (1.22)
Database (Examples: Approach, dBase, Access, Microsoft Works, etc.)	2.37 (1.11)	2.15 (.88)	2.92 (1.05)	2.02 (1.08)	2.15 (.99)	2.76 (1.25)	2.10 (1.04)
Instructional Software (Examples: My Resume, Injured Engine, livestock feed ration formulation, personal or business finance, loan amortization, nutrition, house design, health diagnostics, etc.)	2.35 (1.08)	2.39 (.94)	2.30 (1.14)	2.35 (1.05)	2.24 (1.14)	2.43 (1.19)	2.36 (1.14)
Desktop Publishing (Examples: Pagemaker, Ventura, desktop publishing capabilities of WordPerfect or Microsoft Word)	2.27 (1.13)	2.01 (.94)	2.76 (1.11)	1.97 (1.08)	1.95 (.95)	2.40 (1.20)	2.24 (1.24)
Presentation Software (Examples: PowerPoint, WordPerfect Presentations, Freelance Graphics, Harvard Graphics, etc.)	2.07 (.98)	1.97 (.84)	2.33 (1.03)	1.79 (.95)	1.98 (.76)	2.25 (1.11)	2.10 (1.01)
Internet E-mail (Examples: America On-Line, Netscape, Prodigy, Juno, Compuserve, Eudora, etc.)	2.04 (1.10)	1.91 (.96)	2.32 (1.14)	1.87 (1.05)	2.02 (1.06)	2.13 (1.19)	1.93 (1.16)
World Wide Web Browser (Examples: AOL, Netscape, Prodigy, Compuserve, Internet Explorer, Mosaic, etc.)	2.02 (1.09)	1.92 (1.01)	2.14 (1.10)	1.90 (1.08)	2.02 (1.08)	2.25 (1.27)	1.98 (1.10)
Utilities (Examples: Norton, PC Tools, virus protection, Windows uninstaller, etc.)	1.95 (1.01)	1.87 (.87)	2.15 (1.05)	1.70 (.93)	1.66 (.69)	2.13 (1.19)	2.09 (1.11)
Lesson Planning (Examples: 4MATION, PET, etc.)	1.79 (.92)	1.87 (.81)	1.69 (.94)	1.78 (.93)	1.73 (.78)	1.89 (1.07)	1.87 (1.00)
File Transfer to and from Other Computers Using a Modem	1.78 (.93)	1.76 (.81)	1.90 (.97)	1.64 (.86)	1.68 (.85)	1.89 (1.05)	1.80 (1.04)
Scale Means	2.30 (.81)	2.16 (.73)	2.61 (.72)	2.08 (.80)	2.13 (.71)	2.51 (.91)	2.23 (.87)
N	619	131	166	136	41	54	91
Note: All=all vocational teachers in the study, Ag=agriscience education, Bus=business education, FACS= family and consumer sciences education, HO=health occupations education, Mkt=marketing education, Tech=technology education. Scale: 1 = I don't know enough about this area to respond, 2 = my knowledge/skill level in this area is below average, 3 = my knowledge/skill level in this area is average, 4 = my knowledge/skill level in this area is above average, 5 = my knowledge/skill level in this area qualifies me as an expert.

instructional management areas listed (e.g., student vocational organizations, instructional management). The data representing these perceptions are presented by program area in Table 6 .

Objective 6

Objective six was to determine the availability of information technology to Louisiana's vocational teachers. Over two-thirds (79%) had a computer available in their office or classroom, almost two-thirds had (63%) computers at home, and half (50%) had a computer lab available in their department. One-third had multimedia computers available in their office or classroom (34%) and at home (32%), while less than one-fourth (22%) had multimedia capacity available in a computer laboratory in their department. Less than one-fourth had the World Wide Web or Internet e-mail available at home (22%), in their office or classroom (16%), or in a computer lab in their department (10%). These data and the responses by program area are presented in Table 7 .

Objective 7

Objective 7 sought to determine the source of information technology training received by vocational teachers in the last three years. The teachers were asked to place a check mark (÷) beside each source of training if they had received training from this source in the last three years. These data are presented in Table 8 . The sources of training that were reported most often were self-directed learning/personal experience, written materials, and in-service training sponsored by school, county or state agencies. Less than one-fourth of the teachers reported receiving training from university/college workshops and courses.

Objective 8

Objective eight was to determine if differences exist by program area in how teachers value information technology, their general information technology skill and knowledge levels, their software specific skill and knowledge levels, and their perceptions of the usefulness of information technology. The results of these analyses of variance are presented in Table 9 . No significant differences existed in the values of information technology scale mean by vocational program area (F=1.33, P<.250). Significant differences existed in the teachers general knowledge and skills (F=10.36, P<.000), software skills (F=8.93, <.000), and usefulness of information technology (F=2.91, <.013).

Table 6
Usefulness of Information Technology in Program and Instructional Management
Usefulness of Information Technology	Mean(sd) by Vocational Program
	All	Ag	Bus	FACS	HO	Mkt	Tech
Instructional Management (Grade Reports, Student Records)	6.32(.90)	4.09(1.02)	4.42(.83)	4.38(.81)	4.55(.85)	4.42(.8)	4.19(.96)
Instructional Evaluation (Testing, Assessment)	4.24(.84)	4.10(.87)	4.38(.79)	4.27(.78)	4.43(.78)	4.40(.7)	3.95(.99)
Student Guidance and Career Development	4.18(.88)	3.97(.94)	4.35(.85)	4.15(.79)	4.18(.90)	4.43(.7)	4.07(.97)
Instructional Planning (Lesson/Unit/Curriculum Planning)	4.16(.91)	4.04(.94)	4.24(.85)	4.24(.84)	4.25(.95)	4.19(.9)	3.97(.97)
Program Planning, Development & Evaluation (Examples: youth organization activities, program reports, budget, equipment/maintenance, long- range planning, funding requests, fund raising, instructional material, equipment purchases, etc.)	4.14(.94)	4.08(.91)	4.25(.89)	4.24(.83)	4.22(1.08)	4.10(1.0)	3.88(1.08)
Professional Role and Professional Development	4.13(.90)	3.98(.93)	4.26(.83)	4.11(.87)	4.18(.93)	4.25(.9)	4.07(.97)
Instructional Execution (Presentation of Instruction)	4.09(.89)	3.89(.87)	4.34(.80)	4.03(.85)	4.15(1.12)	4.27(.8)	3.84(.96)
Student Vocational Organizations	4.08(.90)	4.02(.91)	4.12(.92)	4.05(.86)	4.05(.90)	4.21(.9)	4.06(.90)
Coordination of Cooperative Programs	4.04(.95)	3.85(.97)	4.19(.97)	4.01(.87)	4.03(1.07)	4.23(.9)	4.02(.92)
School Community Relations (Public Relations)	3.87(.95)	3.75(.99)	3.88(.94)	3.97(.86)	3.95(.99)	3.85(.8)	3.82(1.06)
Scale Means	4.13(.72)	4.00(.72)	4.25(.67)	4.16(.64)	4.21(.80)	4.23(.6)	3.97(.84)
N	619	131	166	136	41	54	91
Note: All=all vocational teachers in the study, Ag=agriscience education, Bus=business education, FACS=family and consumer sciences education, HO=health occupations education, Mkt=marketing education, Tech=technology education. Scale: 1 = not useful, 2 = low usefulness, 3 = undecided, 4 = moderately useful, 5 = highly useful.

Table 7
Availability of Information Technology
Information Technology	Number/Percent with Computer Technology Listed by Vocational Program
	All	Ag	Bus	FACS	HO	Mkt	Tech
Computer available in office or classroom	N=	441	98	124	95	22	40	62
	%=	79	79	89	78	59	82	72
With multimediacapabilities	N=	193	47	60	35	9	22	20
	%=	34	39	38	30	25	43	24
With World WideWeb	N=	90	16	39	14	1	8	12
	%=	16	13	24	12	3	16	14
With Internet e-mail	N=	94	19	34	15	2	9	15
	%=	17	16	22	13	6	18	18
Computer at home	N=	373	67	109	87	30	33	47
	%=	63	52	69	66	77	66	53
With multimediacapabilities	N=	175	25	58	40	20	15	17
	%=	32	21	38	36	56	33	21
With World Wide Web	N=	120	16	44	22	10	14	14
	%=	22	14	29	19	29	29	17
With Internet e-mail	N=	120	15	42	27	11	12	13
	%=	23	14	29	24	31	27	16
Computer laboratory in department:	N=	284	38	126	34	14	32	40
	%=	50	30	85	27	38	64	46
With multimediacapabilities	N=	123	15	52	12	9	17	18
	%=	22	13	32	11	24	33	21
With World Wide Web	N=	4	4	28	6	3	5	8
	%=	10	3	18	5	8	10	9
With Internet e-mail	N=	54	4	26	7	3	5	9
	%=	10	4	18	7	10	11	11
Multimedia computers in school	N=	337	82	89	72	21	28	45
	%=	57	63	56	53	54	54	53
Laser disc players in school	N=	209	40	58	51	12	18	30
	%=	35	31	36	41	30	35	35
Satellite downlink in school	N=	196	45	59	43	4	17	28
	%=	33	35	37	34	10	33	32
Video conferencing in school	N=	87	18	17	24	3	7	18
	%=	15	14	11	19	7	14	21
Compressed video in school	N=	63	18	8	20	3	2	12
	%=	11	14	5	16	8	4	14
N		619	131	166	136	41	54	91
Note: All=all vocational teachers in the study, Ag=agriscience education, Bus=business education, FACS=family and consumer sciences education, HO=health occupations education, Mkt=marketing education, Tech=technology education. Scale: 1 = yes, 2 = no.

Table 8
Information Technology Training Received by Vocational Teachers in the Last Three Years
Training Source		Number/Percent Receiving Training in Last Three Years
	All	Ag	Bus	FACS	HO	Mkt	Tech
Self-directed learning/personal experience	N=	352	52	121	71	23	38	47
	%=	58	40	73	54	58	73	52
Written materials such as informa- tion booklets, training manuals, etc.	N=	318	53	113	61	16	34	41
	%=	52	41	69	45	40	65	46
School, county or state-sponsored in-service training	N=	305	41	113	60	17	31	43
	%=	50	32	69	45	43	60	48
Professional conference	N=	214	20	89	33	14	25	33
	%=	36	16	15	25	35	48	38
Suppliers of equipment and software	N=	173	25	78	26	8	18	18
	%=	29	20	48	20	21	35	21
University/ college workshop	N=	148	15	54	29	8	19	23
	%=	25	12	34	22	22	37	26
University/ college course	N=	120	11	48	24	5	18	14
	%=	20	9	29	18	13	35	16
Industry workshop	N=	89	13	31	11	8	12	14
	%=	15	10	20	9	21	24	16
N		619	131	166	136	41	54	91
Note: All=all vocational teachers in the study, Ag=agriscience education, Bus=business education, FACS=family and consumer sciences education, HO=health occupations education, Mkt=marketing education, Tech=technology education. Scale: 1 = yes, 2 = no.

As indicated in Table 9 , marketing teachers rated their general knowledge and skill and their software skill significantly higher than agriscience teachers and business teachers rated these skills significantly higher than teachers from four programs, namely, family and consumer sciences, health occupations, agriscience, and technology. On the usefulness of information technology scale, business teachers rated themselves significantly higher than technology and agriscience teachers.

Table 9
Analysis of Variance Selected Dependent Variables by Vocational Program
Dependent Variable	SS	MS	df	F	P	Mean by Vocational Teacher Group for Those Variables Where Significant Differences Existed
Value of I.T. a						(No significant differences existed by group for this variable.)
Between groups	.99	.20	5	1.33	< .250
Within groups	83.81	.15	567
Total	84.80		572
General Knowledge/skill b						FACS e	HO e	Ag e	Tech e	Mkt e	Bus e
Between groups	26.32	5.26	5	10.36	< .000	2.32	2.39	2.39	2.48	2.72	2.84
Within groups	294.11	.51	579			Mkt Bus	Bus	Bus	Bus	FACS	FACS HO Ag Tech
Total	320.43		584
Software skill c						FACS e	HO e	Ag e	Tech e	Mkt e	Bus e
Between groups	27.18	5.44	5	8.93	< .000	2.08	2.13	2.16	2.23	2.51	2.61
Within groups	255.48	.60	584			Mkt Bus	Bus	Bus	Bus	FACS	FACS HO Ag Tech
Total	382.66		589
Usefulness d						Tech e	Ag e	FACS e	HO e	Mkt e	Bus e
Between groups	7.33	1.47	5	2.91	< .013	3.97	4.00	4.16	4.21	4.23	4.25
Within groups	281.67	.50	559			Bus	Bus				Tech Ag
Total	289.00		564
Note: Ag=agriscience education, Bus=business education, FACS=family & consumer sciences education, HO=health occupations education, Mkt=marketing education, Tech=technology education. Scales: "Value" ranged from 1 = strongly disagree to 5 =strongly agree; "General Knowledge/Skill" and "Software Skill" ranged from 1 = I don't know enough about this area to respond; to 5 = my knowledge/skill level in this area qualifies me as an expert; "Usefulness" ranged from 1 = not useful to 5 = very useful. a This variable is the grand mean of those items reported in Table 3 . b This variable is the grand mean of those items reported in Table 4 . c This variable is the grand mean of those items reported in Table 5 . d This variable is the grand mean of those items reported in Table 6 . e The group(s) listed below this group's mean are different from this group.

Conclusions

The conclusions are based on the findings of this study. These conclusions are limited to secondary vocational teachers in Louisiana.

Internet connections for use by teachers are limited. Less than one-fourth have Internet access at home and even fewer have Internet access at school, even though most have a basic computer available. In addition, relatively small numbers have multimedia and other newer technology. Therefore, a substantial number of vocational teachers do not have access to information technology, and this is especially true with the newer technologies. This does not agree with the findings reported by Heaviside et al. ( 1997 ) in their national study of telecommunications in which they reported that 65% of schools had access to the Internet in the fall of 1996. Vocational teachers in Louisiana attend the state and national vocational education conferences and conventions on an irregular basis. Just over half of the teachers had attended the state conference one to three times during the last three years, while about one-fifth had attended national or regional vocational education conventions over the past three years.

Vocational teachers place a high value on information technology. No differences exist in how vocational teachers value information technology by vocational program area. Teachers consistently agree with positive statements about information technology and consistently disagree with negative statements about information technology. This is consistent with the high value they placed on the use and availability of all types of information technology. These conclusions are supported by the findings of Birkenholz, et al.( 1989 ); Mathews, et al. ( 1996 ); and Chin and Horton ( 1994 ).

Vocational teachers have average to below average levels of general information technology knowledge and skill. When one considers that vocational instructors should be using technology both to support education methodology and to prepare students for the workforce, their information technology competency levels are clearly inadequate. Their skills are average on the use of computers in instruction, and they are weakest in the newer technologies. Differences exist in teachers' perceptions of their general skill levels by vocational program area. Business and marketing teachers' general skill levels are higher than the skill levels of family and consumer science teachers. In addition, business teachers general skill levels are higher than the skill levels of health occupations, agriscience, and technology teachers. These conclusions indicate that the lack of computer literacy reported by Pomeroy ( 1990 ) continues to be a concern in vocational education.

Vocational teachers have average to below average levels of information technology software knowledge and skill. Their level of competency is again clearly inadequate. Their skills are average on the use of software that has been on the market for many years, such as word processors and databases, but are weakest on software that has just become commonly available in the past few years, such as Internet and multimedia software. Differences exist in teacher's perceptions of their software skill levels by vocational program area. Business and marketing teachers' perceptions of their software skill levels are higher than the skill levels perceived by family and consumer science teachers. In addition, business teachers' perceptions of their software skill levels are higher than the skill levels perceived by health occupations, agriscience and technology teachers.

Given the emphasis on some types of information technology and software in business and marketing education, these conclusions appear to be logical. Even though the general information technology and software skills reported by business and marketing teachers were significantly higher than the other groups, neither the business nor the marketing teachers have an expert or above average level of general or software knowledge and skill in any of the general information technology knowledge and skills, or in information technology software.

Information technology is of moderate usefulness in all areas of instructional management. Business teachers perceptions of the usefulness of information technology is significantly higher than the perceptions of technology and agriscience teachers. Again, this is understandable given the emphasis on information technology in business education, even though their perceptions were not higher than the other vocational teacher groups.

Teachers no longer rely on any one source of information technology training. Teachers use self-directed training, personal experience, written materials and in-service provided by schools or state agencies as their primary sources of training. This conclusion supports Pomeroy's ( 1990 ) finding that a majority of teachers were self-taught in the area of computer skills. A low percentage of teachers use university/college workshops and courses for their information technology training.

Implications

Vocational teachers see the value and usefulness of information technology in their programs; they report they just don't have the necessary skills and knowledge to use it effectively for instructional purposes. Though teachers value the Internet and other types of information technology, their full understanding of the interrelatedness of information technology to program quality may yet to be realized. Vocational programs must prepare students for the workplace and society, both now and in the future. In order for teachers to do that, they must continue to value information technology and seek ways to connect program and instructional management with appropriate information technology, especially the Internet. Teachers' competency in information technology is essential if they are to be successful as instructional leaders as they use and transfer this competency to their students. Certainly, this information technology foundation is a necessity for all teachers and students.

Pre-service programs should strengthen their emphasis on the information technology knowledge and skills of pre-service vocational teachers. This is supported by Handler ( 1993 ) who stated that university faculty should serve as role models in incorporating information technology as an instructional tool. Chin and Horton ( 1994 ) also indicated that "… . teachers' attitudes could change toward technology through proper staff development" ( p. 93 ). The Louisiana Department of Education and professional associations should place a high priority on increasing the information technology knowledge and skills of in-service teachers. However, given that no significant differences existed by program area in how teachers valued information technology, and given that significant differences did exist by program area in their general and software knowledge and skill, this suggests that teachers in the different program areas may not be receiving the same amount and quality of pre and/or in-service training on information technology. Perhaps the varying availability of information technology by program area may help to explain these differences. This could result in variances in the quality of the instruction delivered to students. Therefore, additional information technology training and equipment is warranted. Teachers should seek out mentoring opportunities and business/industrial assistance in upgrading their knowledge and skills. Perhaps, the establishment of school-business partnerships for improved learning opportunities for both teachers and students needs to be nurtured. Additional research should be conducted to determine the most efficient and effective use of information technology in vocational programs.

Fiske ( 1998 ) argued that the reason information technology has failed to become central to education is that they offer no added value to the traditional "factory model" school of today. "Teaching in such schools usually takes the form of teacher talk, while computers are by nature student centered" ( Fiske, 1998, p. 12 ). Additional research should be conducted to determine why information technology has not been adopted more widely and if Fiske's claim is valid.

Many public and private sources of information technology and training exist today. The low proportion of teachers who use college/university courses and workshops as a source for their training may be reflective of changes in the public service philosophy of some universities. Historically, universities and colleges have had a substantial role in the in-service professional development of teachers. However, teachers are not as dependent on courses and workshops provided by teacher education institutions as in the past. Training source issues imply the need for answering several important questions. Is low usage of college and universities as a source of training a result of teachers not valuing those courses and workshops? Is it because colleges and universities do not place a high priority on information technology training for vocational teachers? Or, could it be a result of the limited financial support for these types of activities from Carl Perkins Technology funds for 4-year institutions? Should teacher education programs change or expand opportunities by utilizing different methods for instructional delivery, including training of teachers to be self-directed learners and increasing the use of technology as one delivery vehicle? Should teacher education recommend other avenues to improve competency levels of teachers? Further research is needed to answer these questions.

References

Bakar , Rahim bin, & Mohamed, Shamsiah. (1998). Preparing Malaysian vocational and technology teachers to integrate computer technology in teaching vocational and technology subjects. Computers and Education , 31(4), 365-372.

Birkenholz , R. J., Stewart, B. R., & Craven, J. (1989). Use of educational technology in agricultural education: A national study . Project final report submitted to the National FFA Board of Directors. Columbia: University of Missouri, Department of Agricultural Education.

Borg , W. R. (1987). Applying educational research (2nd Ed.). New York: Longman, Inc.

Bronkhurst , J. (1997). Independent learning using ICT and multimedia. Some recent developments in the Netherlands. Educational Media International , 34, 140-143.

Chin , S., & Hortin, J.A. (1994). Teachers' perceptions of instructional technology and staff development. Journal of Educational Technology Systems , 22(2), 83-98.

Cochran , W. G. (1977). Sampling techniques (3rd ed.). New York: Wiley.

Daulton , M. (1997). Microcomputer adoption by family and consumer Sciences teachers: An historical perspective. Journal of Family and Consumer Sciences Education , 15(2), 55-60.

Day , T., Raven, M., & Newman, M. (1998). The effects of worldwide web instruction and traditional instruction and learning styles on achievement and changes in student attitudes in a technical writing in agricommunication course. Journal of Agricultural Education , 39(4), 65-75.

Dede , C. (1997). Distributed learning: How new technologies promise a richer educational experience. Connection: New England's journal of higher education and economic development , 12(2), 12-16.

Downing , C. E., & Rath, G.J. (1997). The Internet as Intranet: Moving toward the electronic classroom. Journal of Education Technology Systems , 25(3), 273-279.

Fiske , E. R. (1998). Computers at the crossroads. Technos , 7(1), 11-13.

Fletcher , W. E., & Deeds, J. P. (1994). Computer anxiety and other factors preventing computer use among United States secondary agricultural educators. Journal of Agricultural Education , 35(2), 16-21.

Ganguli , A. B. (1992). The effect on students' attitudes of the computer as a teaching aid. Educational Studies in Mathematics , 23, 611-618.

Garton , B. L., & Chung, N. (1996). The in-service needs of beginning teachers of agriculture as perceived by beginning teachers, teacher educators, and state supervisors. Journal of Agricultural Education , 37(3), 52-58.

Ghomita , V. K. A.. (1995). Microcomputer technology adoption in the business education classroom: The Pennsylvania experience. Delta Pi Epsilon Journal , 37(3), 159-171.

Goldberg , M. W. (1996). CALOS: First results from an experiment in computer-aided learning . World Wide Web document (URL: http://homebrew1.cs.ubc.ca/papers/calos-res/ ).

Golden , B. (1997). Does your technology deliver. Techniques , 72(7), 16-19.

Gonzenbach , N.M., & Davis, D.C. (1999). Business employees' perceptions of content areas to be included in an informatiinformation systems technology curriculum. NABTE Review , (26), 58-62.

Handler , M. G. (1993). Preparing new teachers to use computer technology: Perceptions and suggestions for teacher educators. Computers and Education , 20(2), 147-156.

Heaviside , S., Riggins, T., Farris, E., & Westat, Inc. (1997). Advanced telecommunications in U.S. Public Elementary and Secondary Schools , Fall 1996. NCES 97-944. [Internet]. Http://nces.ed.gov/pubs/97944.html .

Heerman , B. (1986). Personal computers and the adult learner . San Francisco: Jossey-Bass.

Honey , M., & Moeller, B. (1990). Teachers' Beliefs andtechnology integration: Different values, different understandings . ERIC Document Reproduction Service No. ED 326203.

Ingram , A. L. (1996). Teaching with technology. Association Management , 48 (6), 31.

Jackman , L. E., Moellenberg, W. P., & Brabson, G. D. (1987). Evaluation of three instructional methods for teaching general chemistry. Journal of Chemical Education , 64(9), 794-796.

Kang , S. (1995). Computer simulations as a framework for critical thinking instruction. Journal of Educational Technology Systems , 23, 233-239.

Kearsley , G. (1998). Explorations in Learning and Instruction: The Theory Into Practice Database . [Internet]. Http://www.gwu.edu/~tip/spiro.html .

Kitagaki , I. (1995). Technology literacy in the immediate future and educational technology. Journal of Educational Technology Systems , 23, 369-381.

Kotrlik , J. W., & Smith, M. N. (1989). Computer anxiety levels of vocational agriculture and other vocational teachers. Proceedings National Agricultural Education Research Meeting, 1-9.

Lammers , S. (1986). Programmers at work . Richmond, WA: Microsoft.

Marcinkiewicz , H. R. (1996). Motivation and teachers' computer use . Proceedings, 18th National Convention of the Association for Educational Communication and Technology, 467-472. ERIC Document Reproduction No. ED 397 818.

Martin , R. E., & Lundstrom, K. (1988). Attitudes of vocational home economics teachers toward computers. Journal of Vocational Education Research , 13(1), 83-93.

Mathews , J. G., Davis. E. E., & Hamilton, G. H. (1996). Assessment of teacher technology needs in fifty-five southeastern Idaho school districts . Paper presented at the Annual Meetings of the National Rural Education Meeting, San Antonio, Texas. 40 pp. ERIC Document Reproduction Service No. ED 402 120.

McCaslin , N. L., & Torres, R. M. (1992). Factors underlying agriculture teachers' attitude toward using microcomputers for in-service education. Journal of Agricultural Education , 33(3), 47-52.

Miller , J. A. (1997). On-line, Off-track. Techniques , 72(7), 13-15.

Miller , L. E., & Smith, K. L. (1983, September-October). Handling non-response issues. Journal of Extension , 21, 45.

Na , Seung, & Barrick, R. K. (1993). Variables associated with attitudes of teachers toward computers in Korean secondary vocational agriculture program . Proceeding, 20th Annual National Agricultural Education Research Meeting, 416-423.

Nagourney , P. (1989). Computers: Part of a part of a larger vision. Vocational Education Journal , 64(3), 10.

Office of Technology Assessment, U. S. Congress. (1988). Power on! New tools for teaching and learning. (OTA-SET-379). Washington, D.C.: U. S. Government Printing Office.

Pask , G. (1975). Conversation, cognition, and learning . New York: Elsevier.

Pomeroy , J. L. (1990). Determining the computer literacy levels of Vocational teachers in southern Nevada and developing a computer in-service program for vocational teachers . ERIC Document Reproduction Service No. ED 324 451.

Princeton Research Associates, Inc. (1993). National Education Association communications survey . Report of Findings. ERIC Document Reproduction Service No. ED 360 953.

Salomon , G. (1979). Interaction of media, cognition, and learning . San Francisco: Jossey-Bass.

Salomon , G., Perkins, D., & Globerson, T. (1991). Partners in cognition: Extending human intelligence with intelligent technologies. Educational Researcher , 20(4), 2-9.

Sormumen , C., & Chalupa, M. (1994). Perceived pre-service and in-service technology training needs of Indiana business teachers. The Delta Pi Epsilon Journal , 36 (1), 14-23.

Spiro , R.J., & Jehng, J. (1990). Cognitive flexibility and hypertext: Theory and technology for the non-linear and multidimensional reversal of complex subject matter . D. Nix & R. Spiro (eds). Cognition, Education, and Multimedia. Hillsdale, NJ: Erlbaum.

U.S. Department of Labor. (1992). Skills and Tasks for Jobs: A SCANS Report for America 2000 . Washington, D.C.: Author.

Wilson , B. (1995). Constructivist learning environments: Case studies in instructional design . U.S.A: Educational Technology Publications.

Yuen , C. (1985). Attitudes of trade and industrial teachers toward the useof microcomputers. Journal of Vocational Education Research , 10(2), 51-64.

Zemke , R. (1984). Computer literacy needs assessment . Reading, MA: Addison-Wesley.

Zidon , M., & Miller, W. W. (1990). The perceived value of computer use in secondary agriculture programs: A national study Proceedings of the Central Region Annual Research Conference (44th) . Chicago, IL. ERIC Document Reproduction No. ED319903.

Authors

JOE W. KOTRLIK is Professor, Louisiana State University, School of Vocational Education, Baton Rouge, LA 70803-5477, [E-mail: kotrlik@lsu.edu ]. Dr. Kotrlik's research focuses on performance improvement, program evaluation, and technology implementation.

BETTY C. HARRISON is Professor, Louisiana State University, School of Vocational Education, Baton Rouge, LA 70803-5477, [E-mail: bcharri@lsu.edu ]. Dr. Harrison specializes in systems of style and instructional delivery.

DONNA H. REDMANN is Associate Professor, Louisiana State University, School of Vocational Education, Baton Rouge, LA 70803-5477, [E-mail: redmann@lsu.edu ]. Dr. Redmann focuses on job analysis and instructional design.