An Analysis of Instructional Technology Use and Constructivist Behaviors in K-12 Teachers
Glenda C. Rakes, University of Louisiana at Monroe
Research Question 2: Do self-reported constructivist behaviors differ as a function of teacher self-reported level of technology skill (entry and adoption, adaptation, integration and appropriation, or invention)?
Data were analyzed with a one-way analysis of variance with the constructivist score serving as the dependent variable and the technology ranking (high/medium/low) serving as the independent variable. Table 1 presents a summary of ANOVA results. Post-hoc analysis indicated that those respondents with the "high" technology rank (M = 61.79) had significantly higher constructivist scores than those with "medium" (M = 58.95) and "low" (M = 56.28) technology rank.
The overall technology ranking included a measure of technology skill level. To determine the technology skill levels of the respondents, each was asked to select one of four statements which best described their level of technology skills:
Level 1 = Entry and Adoption
Level 2 = Adaptation
Level 3 = Integration and Appropriation
Level 4 = Invention
Data were analyzed with a one-way analysis of variance with the technology
skill level, one component of the overall technology score, serving as
the independent variable. The ANOVA indicated significant differences between
the overall constructivist score and the teachers' self-reported technology
skill level. Table 2 presents a summary of the ANOVA results. Post-hoc
analysis indicates that respondents at the "invention" skill level (level
4 above; M = 60.99) had significantly higher constructivist scores than
those at the "entry" (M = 56.85) and "adaptation" (M = 58.14) levels (1
and 2 above respectively).
Research Question 3: Do self-reported constructivist behaviors differ
as a function of teacher characteristics such as experience, degree, and
Data were analyzed with a three-way analysis of variance. A three-way ANOVA was used to protect against the inflation of alpha associated with the calculation of multiple ANOVAs. This was not a concern in the previous analyses because the follow-up ANOVAs used independent variables that were used in the calculation of the independent variable used in the first, overall ANOVA. In a sense, these were used post hoc to further decompose the significant finding in the first ANOVA. The ANOVA was used to compare the constructivist scores by each of three teacher characteristics which served as the independent variables (years of experience - 0-5 years, 6-10 years, 11-15 years, 16-20 years, 21-25 years, and over 25 years); (grade level taught - PK-K, 1-3, 4-6, middle school, 7-9, 10-12); (highest degree earned - bachelors, masters, +30 hours, specialist, doctorate). Groupings were arbitrarily chosen.
Table 3 indicates that there were significant main effects. Higher order interaction effects were suppressed due to matrix singularity. Post-hoc analysis indicated that respondents with 0-5 years experience (M = 60.89), 6-10 years experience (M = 59.69) and 11-15 years experience (M = 60.92) had significantly higher constructivist scores than those with 16-20 years of teaching experience (M = 56.56). There were no significant differences found for highest degree earned. Respondents who teach in grades 1-3 (M = 61.85) had significantly higher constructivist scores than those teaching in middle school (M = 58.84), grades 7-9 (M = 57.31), and grades 10-12 (M = 58.28).
Research Question 4: Do self-reported constructivist behaviors differ
as a function of reported student-to-computer ratio?
Data were analyzed using a one-way analysis of variance. The ANOVA indicated significant differences between the overall constructivist score by classroom student-to-computer ratios (none, >25:1, 24:110:1, 9:15:1, <5:1) which served as the independent variable. Table 4 presents a summary of the ANOVA results. Post-hoc analysis indicated that respondents with classroom student-to-computer ratios of 24:110:1 (M = 59.82), 9:15:1 (M = 61.75), and <5:1 (M = 60.19) had significantly higher constructivist scores than those with classroom student-to-computer ratios of over 25:1 (M = 55.47). Respondents with classroom student-to-computer ratios of 9:1-5:1 had significantly higher constructivist scores that those with no computers (M = 57.74) in their classrooms.
Research Question 5: Do self-reported constructivist behaviors differ
as a function of classroom arrangement?
Respondents were asked to choose one of three classroom sketches that looked most like their own (see Figure 2). Fifty-four point three percent of the respondents selected a cluster-type classroom arrangement (see A on Figure 5), 21.3% selected an open, circular-type arrangement (see B on Figure 2), and 24.4% selected the traditional lecture-type arrangement (see C on Figure 2).
Figure 2. Classroom Arrangements (D)
Data were analyzed using a one-way analysis of variance. The ANOVA indicated significant differences between the overall constructivist score based on classroom arrangement which served as the independent variable. Table 5 presents a summary of the ANOVA results. Post-hoc analysis indicated that those respondents who selected the cluster-type arrangement (see A on Figure 2; M = 61.61) and the open, circular-type arrangement (see B on Figure 2; M = 59.09) had significantly higher constructivist scores than those who selected the traditional lecture-type arrangement (M = 55.85). In addition, those respondents who selected the cluster-type room arrangement had significantly higher constructivist scores than those who indicated that their classroom was in a circular-type arrangement.
In recent years, research has shifted from the investigation of the
impact of a technology product to how technology can impact important aspects
of the teaching and learning environment, for example the nature of teacher/student
interactions, ways in which a classroom functions, or types of unique learning
experiences possible through the use of certain technology resources (McLellan,
1996; Roblyer, 1996). The primary focus
of this exploratory study was to determine if the availability and use
of instructional technology affects the use of constructivist behaviors
in K-12 teachers. This study provides some evidence that the use of technology
may provide a tool that facilitates constructivist behaviors in classroom
teachers. As the amount of technology available, the use of technology,
and technology skill levels increase, the use of constructivist practices
in the classroom appears to increase, making technology funding and training
even more important. Technology availability and skills can have a positive
impact on the overall behavior of the classroom teacher.
Despite growing concerns that the use of drill and practice type software
may produce less than the most desirable results, 66.4% of the respondents
indicated that their students use this type of software as a regular part
of the curriculum. This result may, in part, be related to the continuing
emphasis on standardized test scores as primary quality indicators for
schools and individual classrooms in most places.
Despite the emphasis on basic computer skills, 74.7% of the technology using teachers who participated in this survey say their students do not use word processing, spread sheets, or drawing programs as a regular part of the curriculum. However, 70.2% regularly use more advanced web publishing and presentation software for group work along with simulation software (77.5%). These responses present an interesting contrast. The results might indicate that teachers are concentrating on what they view as more "cutting edge" technology (i.e., the World Wide Web) that focuses on general information literacy skills instead of what may be perceive as more specifically targeted traditional technology tools such as spread sheets.
About two-thirds (66.2%) of those responding do not use CD-ROM research
resources or World Wide Web information resources regularly. Only about
half (55.1%) report the regular use of networked communications (e.g.,
email) and indicate regular individual and group use for communication
and research tools. Progress has been made toward true technology/curriculum
integration, but these results give an indication of the need for increasing
efforts in this direction. Perhaps teacher training in technology needs
to move beyond literacy skills to address more thoroughly application and
curriculum integration issues.
A surprisingly large percentage of teachers (75.2%) reported Internet
connections in their classroom, but this study provides continuing indications
that computer labs have better student-to-computer ratios than regular
classrooms with about 2/3 of the labs providing a <5:1 student-to-computer
ratio while a <5:1 student-to-computer ratio exists in less than one
fourth of classrooms. The results suggest that the investment in increasing
numbers of computers may result in academic benefits for students because
of the effects on teacher behavior. Respondents with classroom student-to-computer
ratios of less than 25:1 had significantly higher constructivist scores
than those with classroom student-to-computer ratios of over 25:1. More
computer access in the classroom does seem to provide a tool which encourages
constructivist behaviors among teachers.
Despite recent emphasis on constructivism, constructivist behaviors
as reported by the respondents were used with much less than desirable
frequency. Responses to eight of 14 behaviors on the survey indicate that
over half of the respondents never use these behaviors. Responses to three
other behaviors indicate that over 40% never use these behaviors. Respondents
who teach in the lower grades (1-3 ) had significantly higher constructivist
scores than those teaching in middle school and grades 7-12. A close examination
of the classroom practices of lower grade teachers may be beneficial in
designing training, especially technology training, for all teachers.
The results showed striking generational differences among teachers with those having 0-15 years experience having significantly higher constructivist scores than those with over 15 years of teaching experience. This may be indicative of changes that are taking place in teacher education programs - an indication that such programs are placing more emphasis on both technology and on constructivist practices. This result may indicate one criterion on which administrators may base decisions as to what type of technology-related professional development activities are more appropriate for certain groups among their teacher populations.
This study also add credibility to McKenzie's
(1997) suggestion that the arrangement of a classroom indicates the
type of activities that occur in that classroom and whether that classroom
is technology/information-ready. He describes these classrooms as constructivist/student-centered
environments with a primary focus on investigation, questioning, and research.
Interestingly, teachers who reported using the two classroom arrangements
which are more typical of classrooms in which computer technology is used
(A and B on Figure 2) also report using constructivist behaviors more than
those using the typical lecture-type arrangement for their classroom environment.
If the arrangement of a classroom environment is indicative of the activities
that take place there, perhaps teachers should be encouraged to experiment
with a variety of classroom arrangements in order to influence classroom
McKenzie (1997) sees these issues as representative of important staff development challenges if schools are to gain a significant return on their technological investments. Certainly, staff development initiatives concerning the integration of technology into the K-12 curriculum take on increased importance when viewed in this light.
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