Methods CASE5 - Research Paper Example

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(n= 55) of a two credit graduate statistics class. Introduction to statistics and research methodology is a mandatory course to all the students in the school. One group participated in a single…
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Research Methods Research Methods Data was combined from four single taught group (n = 47) and team taught group. (n= 55) of a two credit graduate statistics class. Introduction to statistics and research methodology is a mandatory course to all the students in the school. One group participated in a single taught survey while another participated in a team taught survey.
(Johnson & Christensen 2012) says that to ascertain levels of achievement on both the groups to be studied, two achievement measures should be used. The first was a 20 item test that included introductory concept that comprised statistical procedures and use of research data bases. The data achieved was used to measure the level of achievement in the two groups. Another measure comprised the final grades of the students in the course depicted by percentage scores.
A paired sample t –test was used to examine the achievements in the two groups. In addition, differences in pre post surveys was examined to get the differences based on formats of teaching in single taught and team taught groups, while similarly controlling the demographic variables in both the sections using MANCOVA.
The grades of the two groups were also examined based on the format of teaching by use of independent t-test. Differences in pre-post for the examined factors from the survey of the two teams were analyzed. The results showed a significant increase in research and statistics basis. However, there were no any significant differences for the other two variables.
The pre-post differences for the survey factors that are based on format of teaching in both the single and team taught groups when demographic variables are controlled showed that there was a significant difference between work, research and statistics.
The single taught students showed an increase in pre post relationship between course materials and work. The team taught group showed a pre post decline in the relationship between course materials and work.
(Sesser 2012) says that the results indicate no significant interactions statistically exist in opinion factors and demographic variables. When the final grade is used to gauge the differences in effects of this two type of learning, there is a significant variance between single taught and team taught groups.
Team taught students are observed to attain higher course grades than those of the students in solo taught groups. The standard deviation in the statistics obtained in the two groups was also examined. (Hill 2005) says that the variance in the team taught is always less than that of the solo taught group.
The results of the achievement scores showed that the group taught students scored highly in course work grades. Also the team taught group had scores that showed less variance than those of single taught team. This shows an evidence of effect of cumulative teaching in the course. That is, even though test on achievement measured only one domain in course work knowledge, team taught positive effects would still manifest themselves in the final grade of the students.
In conclusion, this research shows that the environment in which team teaching occurs often involves instruction differentiation and integrated learning activities. Even though the topics of the course and texts were consistent throughout different sections, instructors create a more interactive learning environment by being more flexible in their instructional methods which in the long run have a positive effect of boosting the scores of the students in team taught groups.
Hill, J. (2005). Introduction to Descriptive Statistics, Retrieved December 2012 from the University Of Illinois at Urbana-Champaign, Web http://www.mste.uiu edu/hill/dist/html
Johnson,. B., & Christensen, L. (n/s). Descriptive Statistics, University Of South Alabama. Retrieved December 2012, from;
Sesser, H. (2012). From Data to Conclusions: How Research is interpreted. Alternative Medicine Alert, 15(1), P6 Read More
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