CLASSMATE #1-K. P.

The main research question for this study is, “Do shared mental models (SMMs) change over time in teams of students in a manufacturing engineering course?”(Lee & Johnson, 2008). This study was conducted to assess the concept of team based learning within a classroom (Lee & Johnson, 2008). “The researchers defined shared mental models as a knowledge structure held by members of a team that enables them to form accurate explanations and expectations for the task, and in turn, to coordinate their actions and adapt their behavior to demands of the task and other team members.” (Lee & Johnson, p.73, 2008). The study focused on three stages; preprocess, in-process and post process coordinator (Lee & Johnson, 2008). The methods used participants from undergraduate engineering courses at any southeastern university. The researchers observed 73 students in their early twenties who were randomly assigned to teams of two (Lee & Johnson, 2008). “They were instructed to analyze, test and propose ways to improve a certain product” (Lee & Johnson, 2008). Questionnaires were used to obtain data and compare similarity scores. The results displayed that team shared mental models similarity actually increased during the timeframe (Lee & Johnson, 2008). I think this study would benefit from assessing other types of students, not just engineers. Engineering students may have specific traits, such high desire to problem solve, which could be significant to the overall study. If the researchers used the same study but assessed liberal arts or marketing majors, I am curious what the results would be.

Lee, M., & Johnson, T. E. (2008). Understanding the effects of team cognition associated with complex engineering tasks: Dynamics of shared mental models, Task-SMM, and Team-SMM. Performance Improvement Quarterly, 21 (3), 73-95.

Reply Reply to Comment—————————————————————————————————————————————————————-CLASSMATE #-2—— M. R.

The focus of the study: Focused on how Team and Task SMM change in terms of their structure and degree in the process of complex problem solving.

Research question: The overall research question was: “How do Team-SMM and Task-SMM change over time (Lee & Johnson, 2008)?  Appears that the researcher’s knowledge concerning dependent samples t-test was spot on in using “within-treatment” design. According to Sukul (2013), “Yet a third alternative that is basically the same as a before/after design is the within-treatmentdesign where each participant is used across two treatment groups (usually given at two different times, which makes it the same as the before/after t-test)” (Sukul, 2013).  Because the research is interested in both Team and Task SMM change over time, the dependent-sample t-test compliments this ideal.  Both Team and Task SMM models provided their own questions

1. How do Team SMM change overtime?
2. How do Task SMM change overtime?

Hypothesis (Null):  The null hypothesis for question one is obvious but not clearly stated or mentioned from what I gathered from the reading. Therefore, the null would be, “there is no difference between increased Team-SMM structure and Task-SMM structure overtime. Note: means would be would be the same:

H0: μ1≠μ2

Hypothesis (Alternative/ directional): The alternative hypothesis expressed for both Team-SMM and Task-SMM was overtime, both Team-SMM structure and Task-SMM structure would increase overtime:

H0: μ1=μ2

Method and Study Design: The methods used in this study consisted of an initial number of 73 undergraduate students that ranged from 20 – 25 years of age.  However, due to participation issues, participants were decreased from the original number of 73 to 67 students.  The size of the samples used were 33 teams to assist with a more conservative statistical power. According to Sukul (2013), “The more powerful statistical test is the one that will most readily detect a significant difference” (Sukul, 2013).  Surveys were administer at the beginning study regarding demographics, and the number of instruments used for measuring were in total four.  Both groups were measured to “examine how participants rated the relationships among the key team and task components by pairwise ratings, and the degree of Team-SMM and Task-SMM was measured by questionnaires asking participants to respond to their teamwork and task work” (Lee & Johnson, 2008, p. 77).  The Team-SMM degree questionnaire was based off a 5-point Likert scale.

Random selection was employed regarding participants for this study.  Within-treatment designs was employed from what I was able to gather as data was collected at three time points.  Data analysis was conducted in two phases where raw data was converted into similar scares, and then the converted scores were analyzed.

Critique

In their article. “Understanding the effects of team cognition associated with complex engineering tasks: Dynamics of shared mental models, Task-SMM, and Team-SMM,” authors Lee and Johnson (2008) provided a very conservative study which represented power in statistical testing.  What I did not find within this study were the impacts of poor or effective leadership that that guides teams within any setting.  According to Kolb (1996), “Today, as American companies struggle to remain competitive in the face of increasing foreign and domestic competition, interest centers on the leader’s role in influencing performance, both in his or her subordinates and in the organization as a whole” (Kolb, 1996, p. 173).   The application the One-way repeated measures ANOVA was very precise.  The differences between both Team and Task-SMM structures were affected by time.  But, I continue to argue that leadership, potentially as a confounding variable could have some error variance.  According to Ewert & Sibthorp (2009), “For the most part, confounding variables are confounding because they serve to confuse and obfuscate both the findings from the data, as well as the conclusions drawn from the study” (Ewert & Sibthorp, 2009, p. 377). The study provided a enough detail within the analysis which ad hocs would not be necessary due to the conservativeness of this study.  What gave much confusion, was the research question. It was clear, but lead to much confusion in how the question was architect.

References

Ewert, A., & Sibthorp, J. (2009). Creating Outcomes through Experiential Education: The Challenge of Confounding Variables. Journal of Experiential Education, 31(3), 376–389. Retrieved from http://library.ashford.edu/EzProxy.aspx?url=http://search.ebscohost.com.proxy-library.ashford.edu/login.aspx?direct=true&AuthType=ip,cpid&custid=s8856897&db=eric&AN=EJ853338&site=ehost-live

Kolb, J. A. (1996). A Comparison of Leadership Behaviors and Competencies in High– and Average-Performance Teams. Communication Reports, 9(2), 173–183. Retrieved from http://library.ashford.edu/EzProxy.aspx?url=http://search.ebscohost.com.proxy-library.ashford.edu/login.aspx?direct=true&AuthType=ip,cpid&custid=s8856897&db=ufh&AN=9610110810&site=ehost-live

Lee, M., & Johnson, T. E. (2008). Understanding the effects of team cognition associated with complex engineering tasks: Dynamics of shared mental models, Task-SMM, and Team-SMM. Performance Improvement Quarterly, 21 (3), 73-95. doi: 10.1002/piq.20032

Sukal, M. (2013). Research methods: Applying statistics in research. San Diego, CA: Bridgepoint Education, Inc.

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CLASSMATE #-1—–J. P.

What is the association between involvement in high school extracurricular activities and GPAs in high school seniors in Texas? This is an ideal question for a one-way ANOVA because:

1. One-way ANOVA tests can accommodate one independent variable, divisible into as many nominal categories as required. In this case, the independent variable is the extracurricular activity the participants are involved in, divided into sports, student government (student council, yearbook committee), musical group (choir, orchestra, band), and academic groups (Mathletes, language clubs, science clubs). This fits the qualitative, nominal characteristic requirement for the one-way ANOVA independent variable.
2. The dependent variable must be a ratio or interval scale. The dependent variable in this study is GPA, which is quantitative, continuous ratio data measured from 0-4.0.
3. One-way ANOVA tests require that the groups in question have a homogeneity of variance, or that the “groups should all have reasonably similar standard deviations”(Sukal, 2013, p. 211).
4. Finally, one-way ANOVA tests work off of the assumption that the samples are pulled from a population that is normally distributed (Sukal, 2013). The population is high school seniors in Texas, and while not yet confirmed with the actual data collection, it is assumed that the population will yield a normal distribution.

The null hypothesis posits that there is no difference in GPAs across the 4 groups of extracurriculars. It is annotated in the following manner: H0=µsports= µgovt= µmusic= µacademic. Meanwhile, the alternate hypothesis, Ha=µsports ≠µgovt ≠µmusic ≠µacademics, suggests that the differences in GPAs across the extracurricular groups are statistically significant.

Running a statistical t-test with the same data multiple times (to account for the multiple categories within the independent variable) increases the potential for TypeI errors; running a single test with the ANOVA technique controls this inflation (Sukal, 2013). Granted, the ANOVA test itself will not indicate which means are significantly different, but follow-up post-hoc tests can provide that data (Sukal, 2013). Assuming that the groups are meet the homogeneity of variance and normal distribution requirements, Type I errors will be minimal and remain at the original alpha level (p=.05 in most cases) (Laerd Statistics, 2018).

Laerd Statistics. (2018). One-way ANOVA. Retrieved from Laerd Statistics: https://statistics.laerd.com/statistical-guides/one-way-anova-statistical-guide-2.php

Sukal, M. (2013). Research Methods: Applying Statistics in Research. Bridgepoint Education.

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———————————————————————————————————————————————————————————————CLASSMATE #-2—-M. R.

According to Hollenbeck and Klein (1987); Prendergast (1999), “Existing research also indicates that providing rewards for goal attainment can increase effort and strengthen individuals’ goal commitment, which can result in better performance” (as cited by, Presslee, Vance and Webb, 2013, p. 1806). The “one-way repeated measure ANOVA will address my revised question concerning whether or not financial reinforcers (i.e., monthly bonuses) increases employee performance in collection agencies.  According to Sukul (2013), “The “one” in one-way ANOVA indicates that there is just oneIVin this model” (Sukul, 2013).  In regards to my revised research question, there is a great chance that error variability could occur, brought on by other factors that are not influenced by our IV (independent variable).  The IV within my proposed research question can be identified as the financial reinforcers or “monthly bonuses.”  The DV (dependent variables) are identified as the “employees performance.”

My proposed research question is appropriate for this particular statistical test because it concerns itself with IVs with multiple groups unlike an independent t-test.  Sukul (2013) states, “he difference is that the independent t-test allows for an IVwith just two groups, but the IVin ANOVA can be any number of groupsgenerally more than two” (Sukul, 2013). For example, the IVs within my proposed research question can consist of other factors (or confounding variables) that could demonstrate error variance.  These confounding variables can be peoples level of maturity that can be associated with age.  Other confounding variables can be related to individuals level of education, experience, gender or behaviors that are influenced by intrinsic or extrinsic motivation.  Sukul (2013) mentioned that, “Behavior changes that are notrelated to the IVreflect the presence of error variance attributed by other factors known as confounding variables” (Sukul, 2013).

The samples for my research proposal consist of both male and female collectors (DV) which their attributes are considered on ratio scales; discrete as we are dealing with variances that are respectively influenced by our IVs.  For example, between both male and female collectors, what would be the ratio differences between male and female who’s level of performance is motivated by the IV.  Our IV (monthly bonuses) attributes in contrast would be considered using ordinal scales; continuous.

Null Hypothesis:

Because I am only dealing with two groups, my statistical hypothesis in one-way ANOVA is much like the independent t-test.  Depending on if our means for both populations (male and female) are the same, our null hypothesis would therefore express that with both groups, there is not a significant difference between both populations concerning monthly financial reinforcers and increased performance:

H0: μ1 = μ2

Alternative Hypothesis:

The alternative hypothesis would change drastically if I were dealing with 3 or more groups.  According to Sukul (2013), “Things have to change for the alternate hypothesis, however, because with three groups, there is not just one possible alternative” (Sukul, 2013).  Three groups would create more noise and confusion with trying to determine an alternate to reject my null.  Our null hypothesis is therefore represented as; Both male and female are influenced by monthly incentives, therefore, increasing their ongoing performance. This would indicate that there is a significant difference between our IV (financial reinforcers) and our DV (employee increased performance).  However, we predict that there is a higher mean concerning women performance as it relates to our IV, so, our alternative hypothesis would be a prediction (Directional Alternative Hypothesis:

Ha: μ1,μ2

Type of errors:

For my study, I am anticipating new variables to take into consideration which in turns presents the possibilities of type 1 errors in association with what is known as Family-Wise Errors (FWER).  This would be in the result of an inflated hypothesis. According to Sukul (2013), “The other problem is an issue of inflated error in hypothesis testing when doing multiple test known as family-wise error” (Sukul, 2013).  This is actually one of several good reasons of using an omnibus test.  It is important for me, during my study to understand that by using the ANOVA has “the assumption that the groups being compared have similar variances or spreads in their scores (this is called homoscedasticiy)” (Wall Emerson, 2017, p. 194).

References

Presslee, A., Vance, T. W., & Webb, R. A. (2013). The Effects of Reward Type on Employee Goal Setting, Goal Commitment, and Performance. Accounting Review, 88(5), 1805–1831. https://doi-org.proxy-library.ashford.edu/10.2308/accr-50480

Sukal, M. (2013). Research methods: Applying statistics in research. San Diego, CA: Bridgepoint Education, Inc.

Wall Emerson, R. (2017). ANOVA and t-tests. Journal of Visual Impairment & Blindness, 111(2), 193–196. Retrieved from http://library.ashford.edu/EzProxy.aspx?url=http://search.ebscohost.com.proxy-library.ashford.edu/login.aspx?direct=true&AuthType=ip,cpid&custid=s8856897&db=ccm&AN=121669183&site=ehost-live

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Assignment 3: Essay: Anxiety and AttentionPart I:

Compare and contrast how the anxiety-performance relationship is explained by the individual zones of optimal functioning model, multidimensional anxiety theory, and cusp catastrophe model.

More specifically trace the development of your theoretical understanding of the relationship between performance and the following:

Cognitive anxietySomatic anxietyBe sure to highlight how each of the three theoretical explanations built upon the previous explanation to extend our understanding of the anxiety-performance relationship.

Part II:

Imagine that you are a coach working with an elite-level athlete preparing for a major competition.

Applying Moran’s (2003) principles of effective concentration presented in this module, compose a four-part plan to enhance this athlete’s concentration abilities in preparation for this event. More specifically describe how you would help the athlete enhance his/her ability to focus by specifying performance goals, using preperformance routines, incorporating trigger words, and practicing mentally.

In your answer, be sure to create a hypothetical athlete in a sport of your choice, and provide specific examples and details to illustrate your understanding of the concentration principles.Write your answers in a 2–3-page essay and present it in Microsoft Word document format. Name the file

M6_A3_LastName_AnxietyAttention.doc and submit it to the

Submissions Area by the due date assigned.All written assignments and responses should follow APA rules for attributing sources.Assignment 3 Grading Criteria Maximum PointsCompared and contrasted how the anxiety-performance relationship is explained by the three theoretical constructs.

12Traced the development of the relationship between performance and cognitive and somatic anxiety.8Explained how the three theoretical models built on each other.

8Composed a four-part plan to enhance this athlete’s concentration abilities in preparation for this event.

8Described specifically how to help the athlete enhance his/her ability to focus by specifying performance goals, using preperformance routines, incorporating trigger words, and practicing mentally.

12Provided examples and details to illustrate understanding of the concentration principles.

8Wrote in a clear, concise, and organized manner; demonstrated ethical scholarship in accurate representation and attribution of sources, displayed accurate spelling, grammar, and punctuation.

4Total:60