Reference no: EM132345317

Question:

Researchers often writes a formal? "research plan" in which they identify a research problem and describe the study they plan to conduct to investigate it. Some type of written plan is usually required when a researcher seeks a grant from an organization and when a student proposes a thesis or dissertation.

Please see below research plan written by a student. After? you've read the research? plan, answer the following questions

a) Does the author highlight the primary objective of this? paper? Explain your answer.

b) Review the first paragraph of the research plan in light of the guidelines for effective written communication. Identify at least two places where the author could be more specific? and/or precise with her language.

The effects of technology resources on achievement in statistics

Susan McClellan

Few people would refute the huge impact of technology on what we do in our everyday lives, including the world of education. More specifically, technology has greatly influenced mathematics education over the last 30 years due to increased uses of computers and calculators in schools. Bratton (1999) indicated that the impact of technology in the teaching and learning of statistics has been especially strong since the availability of statistical software (i.e., Fathom and Minitab) and statistical calculators (i.e., TI-83) increase the possible data exploration and analyses within a classroom environment.

Ben-zvi (2000) asserted that the role of technological tools in students' statistical learning is crucial for developing statistical reasoning and conceptual understanding. One of the most important aspects of Benzvi's theory is that "multiple linked representations and simulations [improve a student's ability] to construct meanings for statistical concepts and ideas" (p. 151). Multiple linked representations refer to simultaneous presentation of more than one representation (i.e., numbers, symbols, and graphs) within a technology environment, such as on a computer or calculator screen. Through the creation, manipulation, and transformation of these multiple [visual] representations of statistical concepts, students gain more powerful statistical reasoning and conceptual understanding than by working with single representations or ones that are not multiply linked through the technological tool.

According to Ben-zvi (2000), another significant feature of current technological tools is the dynamic nature of some of the statistical software programs that are available. A multirepresentational dynamic statistical computer-based environment typically involves manipulation tools that allow a user to physically manipulate data, physical line markers (i.e., to mark the median or mode), statistics, or distributions and graphs and see the resulting effects as they occur. The linked feature further enhances the user's learning experience and deepens the user's understanding and reasoning ability because the effects from the user's manipulation of one representation (say, adding an outlier to a set of data) can be observed in the representations of the descriptive statistics and displays of the dotplot, boxplot, and histogram, for example. Some of the technological tools currently available include the TI-83 graphing calculator and two statistical software program called Minitab and Fathom. The TI-83 has statistical and graphical capabilities that rival the software programs, but the viewing screen is only a few square inches. The TI-83 links representations (like data and its graph), but they are not viewable on the screen at the same time; the user can only view one at a time. Minitab, on the other hand, features multiple linked representations and can simultaneously display many windows of data, statistics, and graphs. Minitab is only dynamic in the sense that you can change the data and rerun the commands for new displays. The other program called Fathom is fully dynamic by Ben-zvi's definition and features simultaneously displayed, linked multiple representations. The dynamic feature in Fathom allows the user to see the effects of data manipulation in continuous and real-time manner. For example, if a user drags a dot on a dotplot for a few seconds, the user can see the corresponding data number, descriptive statistics, line markers, boxplot, and histogram change in their respective effects.

This study has two objectives. One is to study the effect of technology-based multiple representations on statistical reasoning, and the other is to examine the influence of dynamic features in statistical software packages on statistical reasoning. I predict that the linked multiple representations and the dynamic features of the technology can positively impact statistical reasoning since a user's experiences with these features should lead to development of uniquely rich and powerful understanding and reasoning ability. The following two research hypotheses will be proposed:

1) Students who learn statistics by utilizing Fathom will have higher levels of statistical reasoning than those who utilize Minitab, and

2) Students who use either Fathom or Minitab will have higher levels of statistical reasoning than the students who use only the TI-83 calculator.

Methodology

The subjects will be 96 high school students enrolled in a one-semester Introductory Probability and Statistics course at a large suburban public high school. The goal of the course is oriented toward developing statistical reasoning in students and less toward developing computations and skills than the traditional introductory course in statistics. Each of the 96 students will be randomly assigned to one of three course sections of 32 students taught by the same teacher-a control group in one section and two treatment groups, one in each of the other two sections. The design will be a randomized Posttest Only Control Group Design. This design was selected in order to avoid pretest contamination.

The independent variable will be the technology (TI-83, Minitab, or Fathom) used for the lab assignments. The control group (Group C) will access the TI-83 calculators for regular use and via lab assignments. The first treatment group (Group M) will access the Minitab statistical software (via lab assignments) and the TI-83 calculators for regular use. The second treatment group (Group F) will access the Fathom dynamic statistics software (via lab assignments) and the TI-83 calculators for regular use.

The students' statistical reasoning will be measured by an instrument administered at the end of the course called the Statistical Reasoning Assessment (SRA), developed by Garfield and Konold (Garfield, 1998) as a part of the ChancePlus Project to assess high school students' levels of statistical reasoning and application of statistical reasoning. Scoring will be calculated using the test's Correct Reasoning Skills Scales and the Misconceptions Scales. The SRA is a 20-item multiple-choice test of probability and statistics items focusing on reasoning about data, representations of data, statistical measures, uncertainty, samples, and association and common misconceptions that lead to incorrect statistical reasoning. Content validity was determined through a process involving consulting with content experts, revisions of items, pilot testing and other administrations, and more revisions. Low criterion-related validity was reported, "suggesting that statistical reasoning and misconceptions are unrelated to students' performance in a first statistics course" (p. 7).

Test-retest reliability calculations were reported of .70 for the total correct score and .75 for the scores of incorrect reasoning. The test designers acknowledged that the reliability and validity analyses did not yield "impressive results" (p. 13). This instrument was chosen since it is the only one that currently exists for assessing statistical reasoning and has been used elsewhere. An additional criterion-related validity analysis could be conducted within this study, looking at the correlations of student scores from assignments, tests, labs, and the course final exam.

This research design essentially has no classical validity problems. There are no external validity problems, and mortality could potentially be a threat to internal validity if either of the treatments makes people drop out of the study. There will be some hesitation to depend on randomization to indicate group equivalence and a realization that randomization is often difficult in educational settings.

Additional potential threats to validity are also considered. The Hawthorne Effect is minimized because the treatment should be long enough to remove novelty effect. The study will be conducted by double blind method in the sense that neither the subjects nor the teacher will know the research hypotheses. All three groups will be advised that opportunities will be given after the study to work with the Minitab and Fathom statistical software packages to minimize experimental diffusion and resentful demoralization. Additionally, the groups will also be advised not to discuss the labs with students outside of a particular section of the class since separating the students completely (i.e., in different buildings) is not practical. The researcher will perform random checks of the teacher's implementation of the different labs and of the regular class instruction to deal with treatment fidelity as a possible threat. Any changes or departures from the original design will be described in the final publication of the results.