Effects of trade experience, teaching experience, and professional education on the classroom teaching performance of secondary school vocational industrial education instructors

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Date
1974
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Virginia Tech
Abstract

The purpose of this study was to determine the effects of years of trade experience, years of teaching experience, and semester credit hours of professional education on the classroom teaching performance of public secondary vocational industrial education instructors.

A related problem of the study was to determine the differences in the ratings given by the five groups of raters chosen to evaluate the classroom teaching performance of instructors selected for the study. Ratings were given by (1) school administrators, (2) supervisors, (3) teacher-peers, (4) teachers on a self-rating, and (5) students. Dimensions which separated the groups of raters were named as well as factors emphasized by each.

The following hypotheses were used to test the effects of these variables:

Hypothesis I. Those instructors having low trade experience will receive lower classroom teaching performance ratings than those instructors having high trade experience.

Hypothesis II. Those instructors having low teaching experience will receive lower classroom teaching performance ratings than those instructors having high teaching performance.

Hypothesis III. Those instructors having low levels of professional education will receive lower classroom teaching performance ratings than those instructors having high levels of professional education.

Hypothesis IV. There will be significant differences in the mean performance ratings of instructors as given by school administrators, supervisors, teacher-peers, teachers on a self-rating, and students.

A stratified random sample of 72 instructors, based upon low and high levels of the 3 independent variables, were selected from among a population of 453 instructors of vocational industrial education in Virginia.

Performance ratings were obtained on each of the 72 instructors by mail survey, using performance ratings developed for the study. A total of 406 of the 432 ratings mailed were returned (94 percent).

The study used four statistical analyses to test the hypotheses and assess the findings of the study: multivariate analysis of variance (MANOVA), chi-square, stepwise discriminant analysis, and factor analysis. All hypotheses were tested at the .05 level.

On the basis of these analyses the following conclusions were drawn:

  1. Classroom teaching performance of vocational industrial education instructors is not significantly influenced by varying levels of trade experience, teaching experience, and professional education when ratings by the five groups are analyzed together.

  2. Increased trade experience does significantly affect classroom teaching performance when rated by supervisors.

  3. Classroom teaching performance significantly influenced by the interaction effects of high trade experience and hours of education when rated by supervisors.

  4. Increased trade experience does significantly influence the classroom teaching performance of vocational industrial education instructors when rated by instructors on a self-rating.

  5. Classroom teaching performance of vocational industrial education instructors is significantly affected by levels of professional education when rated by instructors on a self-rating.

  6. Instructors with high levels of professional education also have high levels of vocational industrial education.

  7. There are no significant differences in the performance ratings of school administrators, supervisors, teacher-peers, teachers on a self rating, and students.

  8. Three dimensions identified as "Teaching Proficiency," "Instructor's Ability to Promote Learning," and "Relationship to Educational Surroundings" separate the performance ratings of the five groups.

  9. Administrators, supervisors, and teacher-peers rate similarly when evaluating vocational industrial education instructors. Teachers (self-rating) and students rate differently from the other groups and from each other.

  10. Performance evaluation factors can be identified which are common to certain groups and to group clusters.

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