Integrated Technology, Mathematics, and Science Education: A Quasi-Experiment
Illinois State University
The integration of technology, mathematics, and science education has been gaining attention throughout each of the prospective fields in recent years, particularly at the middle school level. However, little research has been conducted at the high school level to probe whether an integrative approach to teaching and learning technology, mathematics, and science education is valid and worthwhile or leads to improvements in student learning (Foster, 1994; Wicklein & Schell, 1995). Moreover, various barriers at the secondary level seem to have an effect on the implementation of integrated approaches to teaching and learning (Bergstrom, 1998; Grossman & Stodolsky, 1995; Lounsbury, 1996; McCarthy, 1988). In addition, there has been no formal assessment tool to measure whether students experience an improved learning effect due to an integrative format of teaching and learning (Brusic, 1991; Childress, 1996; Integrated Mathematics, Science, and Technology, 1997; LaPorte & Sanders, 1993).
Review of Related Literature
There are several reasons why today's school systems, particularly at the high school level, do not use integrative approaches to teaching and learning. These reasons include, but are not limited to, efficiency, state goals, standardized testing, teacher-based tests, supplementary materials, and the fact that each discipline provides specialized skills and concepts directly related to the content (Jacobs, 1989). A problem with relying on traditional, stand alone curriculum areas is fragmentation. Students may have seven or eight fragmented periods of study per day, with little or no chance to make sense of the totality of their education.
Integrating the curriculum is a renewed approach to teaching and learning that more closely resembles how people learn and work in the real world. The belief that "the whole is more than the sum of the parts" is a powerful curriculum movement that is helping children make learning connections. (Kotar, Guenter, Metzger, & Overholt, 1998, p. 43)
Beane (1996) noted several broad dimensions to curriculum integration: (1) the curriculum is organized around the real world; (2) pertinent knowledge is organized without regard to subject area lines; (3) learning is not based on an eventual test, but rather the content; and (4) real application and problem solving are used to connect the content to real world applications. Each school examining curriculum integration will probably approach teaching and learning a little differently because no two schools are identical. Regardless of the integration model used, "the focus should be on designing a curriculum that is relevant, standards based, and meaningful for students. At the same time, the curriculum should challenge students to solve real world problems" (Loepp, 1999, p. 21).
Curriculum integration is not an end in itself, but a means to reach the educational goals established by the local, state, and national education systems. Nogay (1994) noted:
Integrated learning provides us a tool to establish better student learning in a relevance-based program. Curriculum integration presents an opportunity to redefine the goals of education and reorganize instructional patterns. Related knowledge and skills can provide intensified opportunities for student growth and increased exposure to the best that all teachers have to offer.(p. 17)
Curriculum integration is not easy to implement despite examples contained in the relevant literature. Curriculum integration takes time, effort, support, and financial commitment. In addition, teachers must change their belief systems about how they approach the curriculum, professional development must be obtained by teachers and schools interested in moving toward or implementing an integrated curriculum, and teachers have to better understand how to work with one another, to identify just a few barriers (Loepp, 1999). Even proponents of integration say it does not need to happen all the time in order for students to comprehend the "big picture." There are times when a specific concept must come from a specific discipline. In fact, poor integrative attempts are no better than poor lessons used in traditional teaching and learning. "Educators should consider integration a potential tool that is feasible and desirable in some situations but not all" (Brophy & Alleman, 1991, p. 66).
Technology, Mathematics, and Science Education (TMaSe)
Integration can be thought of as a puzzle with intricate shapes. Each separate shape fits into another. If one piece of the puzzle is missing, the whole is affected. Stated simply, integration is bringing the parts together to represent the whole, which in this case is the whole is technology, mathematics, and science education (TMaSe). Technology, mathematics, and science build upon one another. Many technologies were developed long before formal scientific theories and mathematical equations were developed to explain their function (Fensham & Gardner, 1994). However, in today's technological world these disciplines cannot stand alone. Recent studies (Brusic, 1991; Childress, 1996) have shown that students in integrated programs of TMaSe have increased curiosity regarding the connections between and among technology, mathematics, and science. However, the hypothesis of "improved student learning" has not been accepted. These conclusions do not mean that an integrated approach to TMaSe is not a valid curricular option. Instead, they suggest that further research is needed in TMaSe to probe the curricular, methodological, philosophical, and theoretical underpinnings of this educational approach.
One of the major reasons for investigating curriculum integration is that school subjects have been traditionally taught and constructed in isolation from other school subjects. There is value in helping students see the whole, the relationships (Kliebard, 1985). Through curriculum integration "students will understand the connections between apparently disparate bodies of knowledge and will better appreciate the inherent complexity of the world we live in" (Martin-Kniep, Feige, & Soodak, 1995, p. 227). Current research in the field of technology education by McCade and Weymer (1996) provided a simple rationale for the integration of TMaSe:
There are certain "thinking and doing" skills associated with science, mathematics, and technology that young people need to develop during their school years. These are essential skills for formal and informal learning and for a lifetime of participation in society as a whole. Taken together, skills can be thought of as habits of the mind, because they all relate to a person's outlook on knowledge and learning and ways of thinking and acting. (p. 42)
The integration of technology, mathematics, and science education at the secondary level, taught by either a team of teachers or a single teacher, is a growing national and international curricular and methodological concern. Significant questions remain, however, regarding the implementation and benefits of integrated TMaSe.
The major questions addressed in this study were:
- Does the teaching of high school level integrated TMaSe content and activities, in conjunction with mapped national standards in each of the three subject areas and taught by technology education teachers in technology education laboratories, have an immediate cognitive learning effect?
- Does the teaching of high school level integrated TMaSe help students perceive the connections between technology, mathematics, and science content and concepts?
- Is retention of TMaSe content improved over a long-term period through an integrated teaching and learning approach?
The research hypotheses for this study were:H1: High school students who are engaged in integrated TMaSe curricula taught by a technology education teacher will have an increased cognitive learning effect as compared to high school students not receiving an integrated TMaSe curricula, as measured by mean scores on the integrated energy and power technology posttest instrument.H2: Subjects participating in the integrated TMaSe curricula approach will identify more terms, phrases, and examples of how technology, mathematics, and science are connected in real-world constructs than those subjects not receiving an integrated curricula approach, as measured by the frequency of terms, phrases, and examples on the posttest instrument.H3: Subjects participating in the integrated curricula approach will show an increased content retention two and four weeks after the treatment has been completed, as measured by the mean score on the posttest retention instrument, compared to those students not receiving an integrated curricula approach.
Description of the Study
A high school located in a small suburban village in the United States was purposefully chosen to take part in this research study. The high school had an approximate enrollment of 225 students. From these 225 students, a purposive sample of 71 students who were currently enrolled in six intact technology education classes was used. The high school was chosen for this study based on its course scheduling structure. Instead of the traditional six or seven 50-minute periods in a single school day, classes were arranged on a modified block schedule. On Monday of each week the school day consisted of both A and B classes that met for 43 minutes each. Tuesday and Thursday were A days, while Wednesday and Friday were B days. Three classes met on the A days and three classes met on the B days, each for 85 minutes. The total number of contact minutes per student per week was 213.
A modified quasi-experimental nonequivalent control group design was utilized for this study. The modification of the design stemmed from the fact that the researcher used comparison groups rather than true control groups.
O X O O O
The three experimental and three comparison groups used in this study were second semester intact high school technology education classes comprised of currently enrolled students in grades 9-12. The experimental groups were those subjects that had the courses commercial design, industrial education orientation, and pre-engineering graphics on the "A" day of the week. The comparison groups were those subjects that had the courses building trades, CAD, and wood production on the "B" day of the week.
For reasons of internal validity (more specifically, implementation or implementer threat), the same technology education teacher instructed the experimental and comparison groups. An implementer effect can occur when different individuals are assigned to implement different methods, and these individuals differ in ways related to the outcome (Ary, Jacobs, & Razavieh, 1996). The technology education teacher was trained by the researcher to teach both the experimental and comparison protocols for this study.
Since the experimental design for this research utilized intact classes, the target and accessible populations were synonymous. The content and activities used in this study were implemented in place of the regular, planned curriculum for the duration of the study (two weeks). However, students were not subjected to curriculum that was unfamiliar or unrelated to the goals of technology education. No individual student was randomly selected for this study; intact classes were randomly assigned to the experimental and comparison groups based on the academic schedule (accessibility) of the school and students.
Treatment and Comparison Groups' Curriculum
Each of the six classes was randomly assigned to either the experimental (3) or comparison (3) group. On the first day (Monday), each class was issued a 100-question pretest (63 forced-choice questions and 37 open-ended questions). For the next two weeks (six block-scheduled periods or 426 minutes) of the research study, the experimental groups received the treatment (six different lessons depicting an integrated, hands-on curriculum via the Pedal 4 Power Energy Education Bicycle). The comparison groups received the identical content lessons given to the treatment groups, but did not have the integrated teaching and learning approach or the hands-on experience with the energy education bicycle. Instead, the comparison groups received activities to reinforce the curriculum content in the form of workbook exercises.
Using the concepts of integrated TMaSe, materials and activities that reinforced and were centered around energy and power technology using the Pedal 4 Power Energy Education Bicycle were created and implemented for the treatment and control groups. Six different lessons and activities were created and implemented for both groups. These lessons specifically focused on energy, power, energy efficiency, and mechanical advantage. The subjects in both groups had instructional (content) lessons in addition to activities. The treatment groups used the energy education bicycle to reinforce the instructional content presented, while the comparison groups had workbook type of activities to reinforce the content they were presented. The materials and activities used were based on ninth grade technology, mathematics, and science curricula and were instructionally time equivalent.
Data collection took approximately six weeks. It was accomplished in several ways. All instruments used by the subjects were coded with a random number. Only the researcher and cooperating teacher knew which code number represented an individual student. The code numbers were used to insure that every subject enrolled in the treatment and comparison groups completed all instruments. The pretest was administered to all groups on the first day of the research study. All subjects, to the best of the researcher's and cooperating teacher's ability, were present for each lesson. A posttest was administered at the conclusion of the treatment. Two weeks later, all groups involved were given another posttest. Two weeks after the second posttest, all groups involved were issued a final posttest.
The instruments needed for this research were field-tested, pilot-tested, validated, and deemed reliable. In order to achieve validity of the research instruments and ultimately the research study, the researcher relied on and used content-related evidence. Content-related evidence, as described by Ary, Jacobs, and Razavieh (1996) "shows the extent to which the sample of items on a test is representative of some defined universe, or domain of content" (p. 263). This evidence was gathered in two ways. First, a panel of experts on TMaSe integration, including faculty at The Ohio State University, was convened. These experts examined the content of both the curriculum used in the research study and the instruments needed to measure the dependent variable(s). In addition, secondary school teachers in technology, mathematics, and science education were selected to examine the curriculum and instruments. Both sets of expert panels were given the curriculum and instruments along with a supplementary checklist asking them to carefully and critically examine the content to determine the relationship between the test and the defined universe.
At the conclusion of the content validity evaluation and field-testing, the researcher made necessary changes and sent the curriculum and instruments back to the panels of experts. Once the validity had been established to the best ability of the researcher, a pilot test was implemented at a high school, separate from the actual research site. Two different technology education classes were used in the pilot testing. The pilot test subjects were similar to the actual research subjects on demographic data such as gender, age, year in school, and technology, mathematics, and science education course history and enrollment. The pilot test was inclusive of every instrument used in the study. To obtain reliability of the instruments, the researcher used Cronbach's coefficient alpha as the index of reliability through SPSS® Version 10.0.5 for Windows®. This pilot test yielded reliability data on the procedures, curriculum, and instruments that were used. The reliability coefficient for the 67 forced-choice questions was r=.84, and the 33 open-ended questions yielded a reliability of r=.93. Fraenkel and Wallen (1993), when discussing reliability of instruments, reported that "reliability should be at least .70 and preferably higher" (p. 149).
Data was gathered, selected, and processed using measures of central tendency, frequency and percentage, computed t-value, and measures of variability. These statistical processes were computed using SPSS, Version 10.05 for Windows, software.
H1 stated that high school students who are engaged in integrated TMaSe curricula taught by a technology education teacher will have an increased cognitive learning effect as compared to high school students not receiving an integrated curricula in TMaSe, as measured by the mean score on the integrated energy and power technology posttest instrument. For research hypothesis one, there were two levels of the independent variable: integrated technology, mathematics, and science education using the hands-on approach to teaching and learning and the non-integrated/non-hands-on approach to teaching and learning. The dependent or outcome variable for research hypothesis one was learning effect, described as the change in cognitive knowledge as measured by an increase or decrease on the posttest instrument. Learning effect and corresponding scores on this variable were treated as nominal data.
H2 stated that subjects participating in the integrated curricula approach would identify more terms, phrases, and examples of how technology, mathematics, and science are connected in real-world constructs than those subjects not receiving an integrated curricula approach, as measured by the posttest instrument. The independent variable for research hypothesis two had two levels: the integrated, hands-on technology, mathematics, and science education approach to teaching and learning and the non-integrated/non-hands-on approach to teaching and learning. The dependent variable for research hypothesis two was students' ability to identify the terms, phrases, and constructs that represented technology, mathematics, and science. These terms/phrases were treated and measured as nominal data.
H3 stated that subjects participating in the integrated curricula approach would have an increase in content retention two and four weeks after the treatment was completed, as measured by the mean score on the posttest retention instrument, than those students not receiving an integrated curricula approach. The independent variable for research hypothesis three had two levels: the integrated technology, mathematics, and science education approach to teaching and learning and the non-integrated approach to teaching and learning. The outcome variable for research hypothesis three was retention after two and four weeks. Retention was measured as the mean score on the posttest instrument and treated as nominal data.
Table 1 displays the descriptive statistics collected in response to hypothesis one for the experimental and comparison groups on the pretest and posttest1 research instruments. The statistical hypothesis (H0) stated: There will be no difference in mean scores between the experimental groups (high school students who are engaged in integrated TMaSe curricula) and the control groups (high school students not receiving an integrated TMaSe curricula), as measured by the mean score on the integrated energy and power technology posttest1 instrument.
Table 1 Group Statistics: Pre and Posttest 1 Group N Ms Mdn Mode Min. SD Max. Pretest Experimental 39 60.92 62 62 22 12.76 83 Pretest Comparison 32 62.34 65 59, 66 34 13.23 84 Posttest1 Experimental 39 71.69 74 74 37 15.40 100 Posttest1 Comparison 32 73.50 76 78 41 14.55 96
Note: The mean score (MS) was calculated based on a 100-point scale, with the higher scores indicating a higher number of items answered correctly.
Table 2 displays the statistical data required for testing hypothesis one. An independent samples t-test for both groups on the pretest and posttest1 was performed.
Table 2 Independent Samples t-Test: Pre and Posttest1 Instrument/Group N Ms SD t df Sig. (1-tailed)
Experimental 39 60.92 12.76 -.459 69 .32 Comparison 32 62.34 13.23 Posttest1 Experimental 39 71.69 15.40 -.504 69 .30 Comparison 32 73.50 14.55
No statistically significant differences were found on the pretest and posttest1 between the treatment (experimental) and comparison groups at the .05 level. Therefore, statistical hypothesis one was not rejected. In other words, the treatment did not have a statistically significant effect on student learning immediately following implementation.
Table 3 presents a summary of the findings from the data collected in response to hypothesis two. Table 3 displays the descriptive statistics for the experimental and comparison groups on the pretest, posttest1, posttest2, and posttest3. The pretest consisted of 37 terms and/or phrases that represented technology, science, and mathematics. Posttest1 consisted of 18 (of the original 37) terms and/or phrases that represented technology, science, and mathematics. Posttest2 also consisted of 18 (of the original 37) terms and/or phrases that represented technology, science, and mathematics. Posttest3 consisted of 10 (of the original 37) terms and/or phrases that represented technology, science, and mathematics. Of these open-ended terms and/or phrases, power, work, amperage, hydraulic, and thermal energy appeared on all three posttests. Therefore, these five items were the only terms and/or phrases statistically reported.
When responding to these open-ended terms and/or phrases, the research subjects were asked to choose whether they represented technology, science, or mathematics independent from one another, a combination of any two areas, or a combination of all three areas. The instrument was coded so that a "one" represented students choosing technology, science, or mathematics independently, indicating a non-integrated orientation. A "two" meant choosing a combination of two terms,
i.e., technology and science, technology and mathematics, or mathematics and science, indicating a semi-integrated orientation. A "three" meant students chose all three terms (technology, science, and mathematics), indicating a completely integrated orientation.
Table 3 displays the descriptive statistics for subjects who chose "three" or a completely integrated orientation. Examination of Table 3 reveals that the valid scores for these five terms and/or phrases started at 31.2% (experimental groups) and 38.7% (comparison groups) on the pretest and ended with 71.9% (experimental groups) and 74.8% (comparison groups) on posttest3. There was a gain for both groups of subjects as indicated by the percentage of subjects who selected an integrated orientation before, during, and after the treatment took place.
Table 3 Frequency of Integrated Terms and/or Phrases Pretest Posttest1 Posttest2 Posttest3 Exp
f % f % f % f % f % f % f % f % Pow 11 28.2 15 46.9 22 57.9 14 43.8 25 67.6 15 55.6 23 79.3 21 77.8 Work 16 41.0 13 40.6 27 69.2 19 59.4 30 81.1 20 74.1 23 79.3 23 85.2 Amp 15 38.5 11 34.4 24 61.5 22 68.8 25 67.6 17 63.0 24 82.8 19 70.4 Hyd 10 25.6 11 34.4 20 51.3 16 50.0 21 56.8 15 55.6 18 62.1 20 74.1 Th E 9 23.1 12 37.5 21 53.8 17 53.1 24 64.9 18 66.7 22 56.4 18 66.7 Total 61 31.2 62 38.7 114 58.7 88 55.0 125 67.6 88 63.0 110 71.9 101 74.8
Note: Pow = power, Amp = amperage, Hyd = hydraulics, Th E = thermal energy.
H2 stated that subjects participating in the integrated curricula approach would identify more terms, phrases, and examples of how technology, mathematics, and science are connected in real-world constructs than those subjects not receiving an integrated curricula approach. The statistical hypothesis stated that there would be no difference in the number of terms, phrases, and examples of integration identified by the experimental and comparison groups.
Table 4 displays the statistical data required for testing hypothesis two. An independent samples t-test for both groups was performed on the pretest (pre terms), posttest1 (post terms 1), posttest 2 (post terms 2), and posttest 3 (post terms 3).
Table 4 Independent Samples t-Test: Terms and Phrases Instrument/Group N Ms SD t df Sig. (1-tailed)
Experimental 39 9.66 2.66 -.298 69 .38 Comparison 32 9.87 3.23 Post terms 1 Experimental 38 11.86 3.28 .631 68 .26 Comparison 32 11.37 3.23 Post terms 2 Experimental 37 12.37 3.17 .466 62 .32 Comparison 27 12.00 3.24 Post terms 3 Experimental 29 13.17 2.60 .085 54 .46 Comparison 27 13.11 2.81
Note: The mean score (MS) was calculated based on a 15-point scale, with the higher scores indicating a higher number of terms and/or phrases selected as completely integrated.
No statistically significant differences were found among the pretest, posttest1, posttest2, or posttest3 for the treatment (experimental) and comparison groups at the .05 level. Therefore, statistical hypothesis two was not rejected. In other words, the treatment did not have a statistically significant effect on the integration orientation of the students.
Table 5 displays the descriptive statistics collected in response to hypothesis three for the experimental and comparison groups on posttest2 and posttest3. The statistical hypothesis (H0) stated that there would be no difference in mean scores between the experimental and comparison groups on content retention two and four weeks after the treatment was completed, as measured by the mean score on the posttest retention instrument.
Table 5 Groups Statistics: Posttest2 and Posttest3 Group N Ms Mdn Mode SD Min. Max. Posttest2 Experimental 37 66.54 67 81 18.18 30 93 Posttest2 Comparison 29 65.00 67 59 21.38 0 93 Posttest3 Experimental 29 65.51 70 52, 70 18.48 17 96 Posttest3 Comparison 28 64.64 65 61 11.47 43 87
Note: The mean score (MS) was calculated based on a 100-point scale, with the higher scores indicating a higher number of items answered correctly.
Table 6 displays the statistical data required for testing hypothesis three. An independent samples t-test for both groups on posttest2 and posttest3 was performed.
Table 6 Independent Samples t-Test: Posttest2 and Posttest3 Instrument/Group N Ms SD t df Sig. (1-tailed)
Experimental 37 66.54 18.18 .316 64 .37 Comparison 29 65.00 21.38
Experimental 29 65.51 18.48 .214 55 .41 Comparison 28 64.64 11.47
No statistically significant differences existed on posttest2 and posttest3 between the treatment (experimental) and comparison groups at the .05 level. Therefore, statistical hypothesis three was not rejected. In other words, the treatment did not have a statistically significant effect on the retention of student learning two and four weeks following implementation.
Conclusions and Recommendations
The following three conclusions were drawn from the findings of this study:
- The high school students engaged for the purposes of this study in an integrated, hands-on approach to teaching and learning technology, mathematics, and science education did not have significantly higher cognitive learning gains than the students who did not receive integrated, hands-on TMaSe instruction. However, both groups did experience similar and significant cognitive learning gains, as measured by the posttest instruments.
- The high school students engaged for the purposes of this study in an integrated, hands-on approach to teaching and learning TMaSe did not identify key terms and/or phrases as completely integrated at the level needed for statistically significant results. Both the experimental and comparison groups did, however, experience significant gains in the number of terms and phrases that were identified as being completely integrated on the posttest instruments.
- The high school students engaged for the purposes of this study in an integrated, hands-on approach to teaching and learning TMaSe did not have statistically significant increases in retention two and four weeks after treatment as compared to the students who did not engage in an integrated, hands-on approach to teaching and learning TMaSe. However, all groups continued to exhibit cognitive learning gains at two and four weeks after instruction/treatment.
Because of the growing attention being given to curriculum integration, additional research on the effects of integration in TMaSe is recommended. Several factors may have influenced the outcomes of this study. Based on this experience, a number of modifications are suggested for those attempting research of this kind.
Future researchers should first of all focus on the development of instruments that can provide the necessary means of assessing and comparing student learning. One possibility would be to include some questions that reflect both the affective and cognitive domains of learning, because integrated teaching and learning approaches may affect both areas in different ways. In addition, it may be fruitful to include a greater number of open-ended problem type questions to probe with greater depth the gains made using different instructional approaches.
Secondly, researchers could design studies that allow long-term integration efforts (treatment) to take place. The treatment period in this study was only two weeks long and may not have allowed the students the necessary time to fully engage themselves in integrated teaching and learning, or the teacher to become comfortable with and proficient in integrated teaching and learning approaches. For example, a nine-week, eighteen-week, or longer period of time could allow more in-depth curriculum coverage using the integrated curricula approach.
Another possible modification would be to design a study that uses three teachers, one each from technology, mathematics, and science to work cooperatively on a set of integrated themes or integrated curricula. Based on the outcomes of this study, the researcher believes that using three teachers could have enhanced the integrated teaching and learning efforts because of greater content expertise.
Additionally, despite no significant differences between the treatment and comparison groups, the instruments and curricular material used in this study could be replicated at several different high schools. This recommendation stems from the fact that the research protocol was deemed reliable and valid, but did not fully encapsulate integrated teaching and learning. Furthermore, studies could be conducted at various types of high schools (i.e., rural, urban, and suburban) to see if any differences occur.
Alternative protocols might prove useful in examining the effects of integration in greater depth. For example, a qualitative study that captures what students think about technology, mathematics, and science education could be completed. The rationale behind this recommendation stems from reasoning that a mix of qualitative and quantitative research may more fully capture how and why students interact within integrated teaching and learning approaches, thus allowing researchers to make appropriate recommendations for practice. Ex-post facto research on schools that offer integrated TMaSe curricula and examination of schools, teachers, and students involved with integrated teaching and learning may provide additional information for researchers.
Merrill is an Assistant Professor in the Department of Technology at Illinois State University, Normal, IL. This manuscript is based on Merrill's doctoral dissertation, completed at The Ohio State University.
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