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 Michael J. Weimer West Noble Middle School Ligonier, Indiana Winter 2001 Abstract Introduction Teachers try to use technology not only to manage the tasks of productivity, i.e. grading, curriculum, and correspondence, but also to open up new and exciting learning possibilities for students. Teachers need technology to have access to knowledge and information – not only for them, but also for their students (Wheeler, et al., 1999). The largest question for administrators, school boards, educators, and parents remains. What does the presence of technology in the classroom actually do for students? We do know that its absence in the classroom can have certain effects on student achievement, especially if students are not instructed using variety methods. Research also provides evidence that students learn in many different ways. Focusing on basic skills using traditional teaching methods like lecture, drill-and-practice, and simple remediation is uninteresting to most students. These methods can cause reduced potential for learning, which can lead to feelings of helplessness, unmotivated students, and less chance of success – especially with disadvantaged students (Wheeler et al., 2000). Wheeler et al. have observed that students who use technology tend to improve their performance and problem-solving abilities while increasing their motivation toward reading, writing, and math (2000). Other research has indicated that with a large range of preferred learning styles among students, utilizing a range of different processes in teaching and using technology has more appeal than using just one process (Williams, 2000). Is the presence of technology helping students "learn"? This is a specific problem in itself since learning can often be too broad in its definition and therefore difficult to measure. Gay Fawcett, Executive Director at the Research Center for Educational Technology, has observed a tendency for some to dissuade the usefulness of technology in the classroom because of their misinterpretation of the term "learning." He attributed this criticism to some individuals in the private sector who reported that students were not "learning" simple things such as making change, phonics, or the location of states. Upon further discussion with individuals in the marketplace he determined that what these employers wanted their future employees taught were problem-solving skills, use and search of information, and the ability to work well with others (Fawcett, 2000). Because of this difficulty with learning, an underlying factor has eluded researchers in determining what impact technology actually has for students. This underlying factor is the motivation of students. A basic definition of motivation is to provide a person with something that causes them to act. There is some evidence that has supported a relationship between student motivation, student performance, and their individual attributes (Atkinson, 2000). In an educational setting, it may indeed be difficult to determine what exactly motivates students. The largest problem is that the classroom is not the most conducive site for experimental research in student motivation, yet one cannot readily place a sample of students in an isolated laboratory setting. The number of variables and factors that affect students is phenomenal. Yet technology has become such a present variable in classrooms that its effect on motivation makes it very researchable. Although it seems that students enjoy using technology, it may be more interesting to determine how much it actually motivates them to learn; furthermore, little substantive research and research funding have been completed in this field (Lewis, 1999). One of the most important conclusions in the area of motivation was made by Sousan Wang, Ph.D., Central Connecticut State University. She asserts, "…one of the most important advantages [of technology] is that it may offer a unique environment for interactivy, learner control and student interest and motivation" (2000). As we determine the link between technology and motivation we may understand how it enhances learning. The Problem Procedures Sample Selection Method of Examining the Hypothesis A second project was then completed on the concepts of civilization, exploration, colonization, and revolution and the students were required to give a presentation similar to the first project. The control group from the first project became the experimental group, and the experimental group from the first project became the control group. Students completed the projects much like the first one and then completed the same survey to keep the results consistent. Data Collection Findings Table 1. The statements used and the results of students’ responses to the seven-item Likert scale test as control and experimental groups.
The Likert items contained responses that ranged from 1, which meant that the student strongly disagreed with the statement, up to 5, which meant they strongly agreed – three being neutral. The means of all the scores in Table 1 are above neutral, indicating that, even though the difference in the means is slight, all students were motivated by the projects. However, the entire set of mean scores for the experimental groups was higher except for only one of the statements. On that statement – statement four, I found the material "interesting" – one group’s mean score was 3.87 while its score as an experimental group was 3.79. As the averages for the classes on each question are examined in graphs (see Graphs 1 and 2 below), two observations are immediate. The data follow a similar pattern. In other words, the plots show that even though both groups are motivated, the experimental group in each of the trials is generally more motivated. Graph 1: Means for each Likert item are plotted for the control and experimental groups in the first project trial. The differences in the means show more motivation in the experimental group.
Graph 2: Means for each Likert item are plotted for the control and experimental groups in the second project trial. The differences in the means show more motivation in the experimental group. A qualitative analysis of student comments provided in the comment section of the survey also indicates high motivation among many of the students participating in the survey. Table 2 below shows the responses of the control and experimental groups. Generally, the comments are more positive in the experimental groups; however, the control group also shared positive comments. The comments in the experimental groups, however, seemed to be more detailed and specific to the enjoyment of the learning experience. Enjoyment suggests higher motivation to learn. Looking at the comments of the control group, however, one cannot rule out motivation among this group also. Table 2. Comments* of the experimental groups and control groups from both trials. *Comments were not edited and contain misspellings and incorrect grammar.
Conclusion Looking solely at the mean scores, it would be unlikely that the scores on the Likert scale would show more motivation on all but one item by just chance. Giving this survey to the sample without any independent variable such as a SMART Board would most likely produce results showing more motivation 50% of the time without considering extraneous variables. The motivation of the control group and experimental group only decreased on item four (see Table 1). This means that motivation increased from the control to experimental groups on every Likert item except one. This tendency in the data suggests that motivation may be affected by the use of technologies such as the SMART Board at least initially. The control groups were exposed to many different kinds of techniques for project work except for technology, while the experimental groups were only allowed to use technology such as the SMART Board. This would definitely indicate that technology is a medium suitable for classroom use, especially when completing projects. It is difficult to determine, solely from this study, whether or not the effect of the independent variable is temporary. A difficulty exists in generalizing this data to other classrooms because of the extraneous variables present in this and any classroom. Even though the sample does represent the local population well, it may not represent that in many other schools. One must look at the difference in the mean scores of the control and experimental groups with interest. Even though more research must be done in the area of motivation, the data has uncovered a link between using technology such as the SMART Board and motivation. Bibliography Brishcar, J. (1999). Impact of advanced media and emerging technology on schools and society. Learning and Technology. Retrieved December 2000 from the World Wide Web: http://llttf.ieee.org/learn_tech/issues/october99/index.html#brishcar Faucett, G. (2000). Do students learn better with technology? It depends on how you define learning! Learning and Technology. Retrieved December 2000 from the World Wide Web: http://lttf.ieee.org/learn_tech/issues/october 2000/index.html#students Lewis, T. (1999). Research in technology education- some areas of need. Journal of Technology Education, 10 (1). Retrieved December 2000 from the World Wide Web: http://scholar.lib.vt.edu/ejournals/JTE/v10n2/lewis.html Wang, S. (2000). Multimedia and some of its technical issues. International Journal of Instructional Media, 27 (3), 303-314. Wheeler, J.L., Miller, T.M., Halff, H.M., Fernandez, R., Halff, L.A., Gibson, E.G., & Meyer, T.N. (1999). Web places: project-based activities for at-risk youth Current Issues in Education. Retrieved December 2000 from the World Wide Web: http://cie.ed.asu.edu/volume2/number6/ Williams, J. (1999). Design: the only methodology of technology? Journal of Technology Education, 10 (1). Retrieved December 2000 from the World Wide Web: http://scholar.lib.vt.edu/ejournals/JTE/v11n2/williams.html Appendix History Survey
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