The Influence of Teachers’ Technology Use on Instructional Practices
Rakes, G. C., Fields, V. S., & Cox, K. E. (2006). The influence of teachers’ technology use on instructional practices. Journal of Research on Technology in Education, 38(4), 409-424.
This study investigated the relationship between the use of technology and skills and the use of constructivist instructional practices among teachers in rural schools. There are two basic problems that serve as the background of this study. First, children in rural schools frequently do not have the same level of access to resources and experiences as those who live in suburban and urban areas of the United States. Second, rural schools have difficulty hiring and retaining qualified teachers because teachers in high-poverty schools are frequently paid less than those in the other types of schools. These problems arise because rural schools are faced with conditions such as inadequate administrative support, excessive intrusions on teaching time, student discipline problems, and lack of input from the faculty for decision-making regarding the schools. More research indicate nationwide low-performance in many subject areas.
As an overview of the study, it is more than sufficient to place the area and context of the study. With the two issues as I summarized above in order to give a clear picture of the research. It is the fact that there are some schools in the third world area, especially in rural schools, in which they cannot keep up with today’s racing technology.
Researchers provided two theoretical reviews as the background of the study (a) constructivism and learning, and (b) technology and constructivism as the framework foundation. They expressed that in traditional classroom, students are typically not provided with whole, dynamic learning experiences; rather, they are provided with limited, arbitrary activities. Schools frequently teach information from the various disciplines without providing adequate contextual support with opportunities for students to apply what they are taught. Therefore, constructivist teaching methods are needed as a way to increase authenticity in the classroom. Teachers are beginning to use technology as a tool to promote students’ ability to reason and solve authentic problems. Increasing the use of technology can create a vehicle through which educators can address teaching and learning opportunities for all students. The need for these opportunities is especially apparent in poor US rural areas.
Based on the topic (the relationship between technology use and skills and the use of constructivist instructional practices among teachers in rural schools), theories about constructivism, technology and learning really fit and will give more benefit in discussion. The researchers carefully (exactitude) weave statements from John Dewey (1916), Piaget (1973), Vygotsky (1978), etc. with previous research results from Dwyer (1994), Rakes et al (1999), Becker and Ravitz (1999), etc. to built the framework.
The purpose of this study is not explicitly stated in this research report. Based on the topic and the research questions, the purpose of this study is to investigate the impact of the given grant to school and teachers training toward the technology use and skills and the use of constructivist instructional practices among teachers in rural schools. This study explores whether teachers use technology, both in the classroom and for personal use, along with constructivist teaching practices. This study addresses four specific research questions: (1) What are the predominate teacher levels on the Level of Technology Implementation, Personal Computer Use, and Current Instructional Practices scales? (2) Is there a relationship between teachers’ Current Instructional Practices scores and teachers’ Level of Technology Implementation scores? (3) Is there a relationship between teachers’ Current Instructional Practices scores and teachers’ Personal Computer Use scores? (4) Is there a relationship between teachers’ Current Instructional Practices scores and teachers’ scores on both the Levels of Technology Implementation and Personal Computer Use scales? The researchers did not define the hypothesis.
On the research design, the researchers did not provide a clear description on the construction and variables, research methodology, and data collection methods. The researchers explain the sample and the population in detail. The purposive sample was comprised of 186 fourth and eighth grade teachers from 36 elementary schools, 17 middle/junior high schools, and 13 high schools from 11 rural school districts in a southern state. The 11 districts were chosen from those designated by the Delta Rural Systemic Initiative. From the total purposive sample of 186 teachers, 123 volunteered to participate. Seventy-one fourth grade teachers and 52 eighth grade teachers participated in the study; those grades were chosen because the state “high stakes testing” is done at those two grade levels.
With regards to the way the sample was determined and the way the researchers analyzed the data (will be explained), this study employed a quantitative non experimental research design. In my opinion, the following are the steps in conducting a non experimental research: first, the researchers must determine the research problem and the hypothesis to be tested; second, the researcher selects the variables to be used in the study. In this study, the researchers did not clearly define the research problem. Purposiveness is one of conditions a research referred to goodness. Though the research questions were formulated in detail, the research problem cannot be comprehended clearly. And surely, the four questions have translated the research problem into research variables. The hypothesis was not formulated clearly. It was just implicitly stated in the sample description.
The 11 districts were chosen from those designated by the Delta Rural Systemic Initiative. The purpose of this federal program was to bring about reform in delta communities in three southern states. These school districts also received a federally funded Technology Literacy Challenge grant that provided equipment and professional development for teachers in the use of technology. The total provided for equipment was $10,931,503. Each district was provided about 300 hours of professional development for teachers. The equipment and training had been in place for a year prior to collection of the survey data. (p. 413)
At the same time the researchers probably assume that the readers get the picture of the hypothesis implicitly put in that description. That after receiving a federally funded Technology Literacy Challenge Grant that provided equipment and professional development for teachers in the use of technology with professional development training, learning abilities in using technology progressively and constructivist teaching methods work. The researchers probably also assume that with the statement the intention of the research will seem implicit. As a research report, this report is less complete.
Teachers in the study responded to 40-item instrument, the Level of Technology Implementation (LoTI). The LoTI was administered to the fourth and eighth grade teachers to determine if their level of classroom technology use and personal computer use (PCU) predicted their Current Instructional Practices (CIP). The instrument generated a profile for each participant in three domains (variables): LoTI (measures the teacher’s level of classroom technology implementation), PCU (measures the skill and comfort level of teachers when using technology for personal use based on eight intensity levels), and CIP (measures teachers’ classroom practices relating to a subject-matter versus a learner-based curriculum approach based on eight elements). A Guide for Measuring Classroom Technology Use was initially tested in August of 1997 and in June of 1998. Moersch (1995, 1998) determined reliability by using Cronbach’s Alpha, which showed a reliability measure of .74 for the LoTI, .81 for PCU, and .73 for CIP. Researchers prepared three table levels of LoTI, CIP, and PCU like rubrics as measurements.
The researchers did not clearly explain the variables of the research although non experimental quantitative design with the regression or correlation research is aimed to see the relationship of dependent variable (DV) to independent variable (IV). Again, the weakness of this research is that the researchers did not follow the research procedure in order, though based on research questions, the readers can determine which one is the DV and which one is the IV. The DV is CIP and the IV is LoTI and PCU.
It’s comment using instrument previous research that was tested and determined reliability as long as that number of reliability showed. The researchers have been explaining the reliability score to be used. And surely the researchers also had prepared three tables level of three variables in the rubrics.
The researchers stated that the data was analyzed using multiple regression on results and discussion. This data analysis technique was not defined in the research methodology. Multiple Regressions is precisely selected by the researchers to analyze the data because this research was intended to see the influence of IV to DV. This research has two IV and the aim was to describe the research data phenomenon and to serve as a control to grant which have been given schools of samples and teachers followed the training. The techniques used to analyze this data have a weakness that the result of research may be not only influenced by gift grant or also not because of teacher have followed the training, but maybe by other factors (confounding effect). In this case researchers have not given the reason at the end of the research.
There is another possible technique to analyze data like post-test control design (quantitative experimental) by comparing samples of receiving schools grant and teacher followed the training with another rural school which do not accept the grant and these teachers do not follow the training. This design is also appropriate for measuring how effective the effect from governmental aid to school and affect from teacher training which have been conducted. But these research goals as a means of control are not reached. So far choosing the multiple regression as an analysis technique for data is precise.
Limitations were described before results and discussion. There are five limitations. (1) The questionnaire did not consider the complexity of software applications used at the school sites or the frequency of their use. (2) The sample is restricted to fourth and eighth grade teachers in 11 poor, rural school districts in a southern state. (3) The study explored relationships among variables; therefore, the analysis cannot establish cause and effect relationships. (4) There may exist unexamined factors affecting the relationship between technology use by teachers and their instructional practices that are not accounted for in the methodology. (5) All information in the survey is self-reported data. The information provided was based exclusively on the perceptions of the participants.
Limitations which are explained after the researchers determine the design show that researcher have sufficiently considered the possible deflect or different interpretation in this research. This indicates the carefulness (exactitude) as one of good research condition. This limitation also will give the definition in comprehending result of data analysis.
Based on question research 1, the predominate of LoTI level is O (Non-Use). This result represents an alarmingly high number of teachers who express a lack of technology used given the amount of technology training and equipment provided for these poor, rural school districts. Despite substantial grant-funded infusions of money for training and equipment, teachers in this sample still perceived their ability to use technology as extremely limited. The predominate of PCU intensity level for this sample is 3 (moderate skill levels). These disappointing results come from a population that was targeted for technology training and equipment. The levels of teacher skill and comfort levels with computers were lower than expected. The predominate intensity level for the CIP for this sample is 4 (respondents may feel comfortable supporting or implementing either a subject-matter or learning-based approach). These results were more encouraging than expected, with more than half of the respondents describing the use of constructivist teaching practices to at least a moderate degree.
This result represented with the bar diagram in three figures. The choice of the bar diagram to define predominate condition was really precise. The data interpretation has been defined clearly and consistently. These are aimed at expectations for grant which have been given by a government and the result of training which have been followed by the teachers.
Based on research question 2, results of standard multi regression on DV (CIP scores) and IV (LoTI scores) were entered into the predictive equation, revealed an R2 of .16, F = 23.07, p < .001, and the indicates there was a significant linear relationship between the DV and IV. About 16% of the variance in the CIP scores can be accounted for by the LoTI score. The results indicate that R2 is very poor (.16) and the predictive value of the LoTI score is likely to be unacceptable. The bivariate correlation (2-tailed) between CIP and LoTI is .40 (p < .01). The positive, moderate correlation between CIP and LoTI indicates that teachers who scored higher on the LoTI scored higher on the CIP scale.
Based on research question 3, results of standard multiple regression on DV (CIP scores) and IV (PCU scores), were entered into the predictive equation, revealed an R2 of .25, F = 22.83, p < .001 indicate there was a significant linear relationship between the criterion variable or DV (CIP) and the predictor variable or IV (PCU) – researchers make a mistake by write LoTI. About 25% of the variance in the CIP scores can be accounted for by the PCU score. Results indicate that the CIP score can be predicted by the PCU score. In this case, R2 is weak, but interpretable. The bivariate correlation (2-tailed) between CIP and PCU is .51 (p < .01). The positive, moderate correlation between CIP and PCU indicates that teachers who scored higher on the PCU have higher scores on the CIP scale.
Based on research question 4, results of standard multiple regression with DV (CIP score) and IV (score of LoTI and PCU) were entered into the predictive equation, revealed an R2 of .28, F = 23.84, p < .001, and indicate there was a significant linear relationship between the DV (CIP) and the set of IV. Results indicate that the CIP score can be predicted by both the LoTI score and the PCU scores. About 28% of the variance in the CIP scores can be accounted for by both the LoTI and the PCU scores. In this case, R2 is weak, but interpretable. The sample multiple correlation coefficient was .53. The positive, moderate correlations between both LoTI and PCU and CIP indicate that teachers who scored higher on both the LoTi and PCU have higher levels of CIP. Both predictors, LoTI and PCU, contributed to a slightly better prediction of CIP scores.
The results based on the research questions 2, 3, and 4 have been explained clearly. The researchers have also interpreted the statistic symbols correctly. It is interesting that on each interpretation of statistic result, the researchers always connect with the result of previous research as an argumentation comparator. For example, research results based on research question 2 are compared with results of research by Becker and Ravitz (1999) and Middleton and Murray (1999). It was expected that the positive relationship between the LoTI and CIP would be stronger. Becker and Ravitz found that teachers who used various computer technologies in the classroom, particularly student-centered, internet-based teaching activities, are more likely than other teachers to demonstrate changes associated with constructivist reforms. In this particular population, the positive relationship exists, but does not provide sufficient predictive power. This may be an additional indication that the technology-related training provided to these teachers did not provide a strong enough link between technology tools and their curriculum as indicated in the LoTI results for these teachers. From this discussion see that theoretical review was really conducted by the researchers to interpret the results of the data analysis.
The research results based on question 3 are similar to findings by Rakes et al. (1999). Teachers’ strong, basic technology skill levels appear to provide teachers with a comfort level with computers needed to support constructivist teaching practices. In this regard, the basic technology skills training provided these teachers appear to have been somewhat successful with a segment of the population. Also the results for research question 4. This result confirms Moersch’s (1999) assertion that appropriate use of technology can reinforce higher cognitive skill development and complex thinking skills as promoted through the use of constructivist teaching practices.
The researchers did not present the conclusion because possible result of this research has clear. The ultimate goal of research on the use of technology as a tool for constructivist teaching practices is to verify a link between classroom technology use, constructivist instructional practices, and improved student achievement. As demonstrated in this study’s teacher population, the availability of computers and training do not necessarily result in the widespread use of technology.
Anyway, education is a costly investment. Technological use to increase student ability in classroom instruction, that at the first becoming concentration study in our group is insufficient in the reality applied. This research gives the insight that the availability of technology and teacher professional development program in using technology did not automatically alter the paradigm and way of teaching. This research gives a lesson to me that writing a research report has to be complete.***agepe
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