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- 1. Running Head: REPLY TO OPINION 5.1 FOR KIMBRILEE SCHMITZ 1 REPLY TO OPINION 5.1 FOR KIMBRILEE SCHMITZ 3 Tonya Klemmer 2 posts Re:Module 5 DQ 1 What are the most effective strategies for managing quality control on quantitative methods in program evaluation? Why are they the most effective? When an evaluator is conducting a quantitative evaluation on an organization it is extremely important that effective strategies are applied to manage quality control. Key stakeholders are relying on the evaluator to provide reliable and valid information based on the data that has been gathered. As reported by Min, Ko, Cho, Jeong, Lee,Chun,and Cho (2015), systematic errors occur frequently in clinical laboratory test results and should be detected and corrected. This helps to ensure the validity and reliability of the results. Min et. al (2015) goes on to report that, in conclusion, the newly developed quantitative quality control procedure (QQCP) can analyze systematic errors quantitatively and be applied to every run. As with qualitative evaluations triangulation is another quality control method that can be applied to compare the results of the data as a way of maintaining the validity and reliability. As reported by Tonkin-Cline, Anthierens, Hood, Yardley, Cals, Francis, Coenen, van der Velden, Godycki- Cwirko, Llor, Butler, Verheij, Goossens, Little (2016), a triangulation protocol can also enhance the validity of findings and assess whether data agree (convergence), complement one another (complementarity) or contradict each other (dissonance). Once these things have been determined it makes it easier to make the necessary changes. Min, W., Ko, D., Cho, E. J., Jeong, T., Lee, W., Chun, S., &
- 2. Cho, H. (2015). A novel quantitative evaluation method for quality control results. Clinica Chimica Acta, 451(Part B), 175- 179. doi:10.1016/j.cca.2015.09.026 Tonkin-Crine, S., Anthierens, S., Hood, K., Yardley, L., Cals, J. L., Francis, N. A., & ... Little, P. (2016). Discrepancies between qualitative and quantitative evaluation of randomised controlled trial results: achieving clarity through mixed methods triangulation. Implementation Science, 111-8. doi:10.1186/s13012-016-0436-0 Shelly Gooden 1 posts Re:Module 5 DQ 2 Explain why quantitative methods would prove advantageous over qualitative methods in program evaluation. Are there drawbacks to using quantitative methods? If so, which ones are of greatest concern? Why? Quantitative evaluation methods can be less expensive than qualitative methods and allow evaluators to provide results quickly. The cost savings can be made in reduced man-hours as interviews or observations are not required replaced by surveys and questionnaires (Rao & Woolcock, 2003). The instruments used in quantitative evaluation do not require coding (Choy, 2014). Quantitative instruments provide numeric or categorical data that can be analyzed after data cleaning but coding is not necessary. Again, this saves time. Surveys and questionnaires can be distributed and returned quickly to more participants. Qualitative methods are generally more time and labor intensive as researchers interview, observe and review documents triangulating data (Royse, Thyer, & Padgett, 2016). Although cost effective quantitative data is not always appropriate. The findings provide statistical results. This may be exactly what is needed if stakeholders want a picture of statistical outcomes, such as the number of program users successfully employed. The evaluation technique is summative. However, if this outcome is already known and the stakeholders
- 3. want to know what user experiences were for those who succeeded the evaluation must be qualitative, a formative focus. The greatest consideration when selecting an evaluation method is the research question posed by the stakeholders. References Choy, L. T. (2014). The Strengths and Weaknesses of Research Methodology: Comparison and Complimentary between Qualitative and Quantitative Approaches. IOSR Journal Of Humanities And Social Science, 19(4), 99-104. Retrieved from http://s3.amazonaws.com/academia.edu.documents/37208325/N 0194399104.pdf?AWSAccessKeyId=AKIAIWOWYYGZ2Y53U L3A&Expires=1492301309&Signature=vo3boDkSApnJ%2B4db nnb%2F%2Fbxz3%2FQ%3D&response-content- disposition=inline%3B%20filename%3DThe_Strengths_and_We aknesses_of_Research.pdf. Rao, V., & Woolcock, M. (2003). Integrating Qualitative and Quantitative Approaches in Program Evaluation. In F. Bourguignon, & L. A. Silva, The impact of economic policies on poverty and income distribution: Evaluation techniques and tools (pp. 165-190). New York , NY: Oxford University Press. Royse, D., Thyer, B. A., & Padgett, D. K. (2016). Program evaluation: An introduction (6th ed.). Boston, MA: Cengage Learning. Groups & Teams
- 4. What are groups? Two or more people interacting interdependently to achieve a common goal 2 Speed Clear Accountability Efficient use of time Less conflict Knowledge & Diversity
- 5. Pooling of resources Specialization of labor Functional conflict Individuals Groups Individuals vs. groups 3 What are groups? Different types of work groups: Formal: Established by organizations to facilitate the achievement of organizational goals; defined by organization’s structure Informal: A group that emerges naturally in response to the common interests of members
- 6. 4 Groups vs. teams In general, teams are a kind of group At work: Groups primarily share information Teams are responsible for a collective product Teams have synergy: Final product is greater than sum of individual contributions Groups vs. teams Work group tasks are typically additive Group performance is just the sum of individual contributions Performance typically increases with group size
- 7. Groups vs. teams Team tasks are sometimes disjunctive Where one member’s solution is chosen to represent the whole team Performance typically increases with group size But typically conjunctive Require all group members to contribute to common product Performance typically decreases with group size Why the difference? Larger groups help when people are working in parallel Too-large groups hurt when people are working together How large is too large? Most work teams have 3-20 members
- 8. Larger teams introduce problems: Harder to communicate Harder to coordinate Optimal size depends on task Generally, avoid double digits Group cohesiveness Degree to which group members are attracted to the group and are motivated to stay in the group Increasing group cohesiveness: Make the group smaller. Increase time members spend together. Increase group status and admission difficulty. Stimulate competition with other groups. Give rewards to the group. Physically isolate the group.
- 9. 10 Group cohesiveness Cohesiveness is not always good! Cautions: Can be problematic if group’s goals are contrary to the parent organization’s goals Can blind a group to outside influences 11 Why use groups to make decisions? Higher decision quality Higher decision acceptance and commitment Group decision more acceptable to those involved Especially important in getting a decision implemented Diffusion of responsibility Ability of group members to share the burden of the negative consequences of a poor decision
- 10. Groups and decision making More complete info Sharing of expertise, experience, diversity Pooling of resources Increased quality (accuracy) Increased acceptance of the decision Ambiguous responsibility- bystander effect Slow Likelihood of intra-group conflict Pressure to conform to norms and leaders Likelihood of extreme decisions Costly Advantages Disadvantages
- 11. Groups vs. individuals When are groups better than individuals? Very complex tasks Division of labor Very simple tasks Take the best or the fastest When are individuals better than groups? Certain creative tasks (esp. if poorly structured) 14 Groups sometimes perform better than individuals Can we measure this collective intelligence?
- 12. 15 Individual Intelligence Spearman’s g Charles Spearman 16 The “g-factor”
- 13. 17 Collective Intelligence Is there evidence of a general collective intelligence (a “c” factor) in groups? Does c have predictive validity beyond individual intelligence of group members? How can we use this information to build a better science of groups? 18 Task 1 Task 2 Task 3 Task 4 Task 5 Collective Intelligence .32* .36* .72**
- 14. .57* .69* Video Game Score .51** Average IQ .08 Woolley, Chabris, Pentland, Hashmi & Malone, Science, 2010 Study 1 19 Task 1 Task 2 Task 3 Task 4 Task 5 Collective Intelligence Architectural Design Task Average IQ Woolley, Chabris, Pentland, Hashmi & Malone, Science, 2010 Study 2 .72** .79** .10 .48*
- 15. .61* .36** .05 20 Predictive value of c and g factors Woolley, Chabris, Pentland, Hashmi & Malone, 2010 21 Collective Intelligence Study 1: Video Game Study 2:
- 16. Architectural Design 0.51 0.36 Average Member Intelligence Study 1: Video Game Study 2: Architectural Design 0.0800000000000001 0.05 Maximum Member Intelligence Study 1: Video Game Study 2: Architectural Design 0.01 0.12 What predicted it? Not group satisfaction, cohesion, or motivation Not personality Proportion of females in group! 22 Woolley & Malone, 2011, Harvard Business Review
- 18. Communication Patterns Taking turns speaking: Uneven distribution of speaking is bad for c Even distribution of speaking turns (i.e., everyone gets to speak) is good for c Groups with higher proportion of women had more even speaking distribution 26 Group decision making biases
- 19. 27 1. Groupthink The capacity for group pressure to damage the mental efficiency, reality testing, and moral judgment of decision- making in groups Unanimous acceptance of decisions is stressed over quality of decisions Examples? 28
- 20. What can prevent groupthink? Leaders must avoid exerting undue pressure for a particular decision outcome. Leaders should establish norms that encourage and reward responsible dissent. Outside experts should be brought in from time to time to challenge the group’s views. 2. Group shift A change in decision riskiness between the group’s decision and the individual decision that a member within the group would make
- 21. Can be either toward conservatism or greater risk 31 32 Why do risk shifts occur? Two main factors explain the occurrence of risky and
- 22. conservative shifts: Group discussion generates ideas and arguments that individual members have not considered before. Group members try to present themselves as basically similar to other members but “even better.” 6 Common Misperceptions #1: Harmony = Better Performance Actually: Opposite is true when conflict is functional. #2: Mix it up = Good to bring in new members Actually: Longer team members together = Better performance. #3: Bigger the better Actually: Size biggest impediment to effective collaboration.
- 23. 34 6 Common Misperceptions #4: Face to face = Passé. Actually: Teams working remotely at disadvantage. #5: All depends on team leader. Actually: Leaders matter, but mostly for team launch and to create effective conditions. #6: Teamwork is magical = Gather talented people and let them work it out. Actually: Need careful thought and preparation to facilitate effective teams. 35 Group members are heterogeneous Members have complementary skills Ideas may be freely communicated Good ideas are accepted Groups are superior to even the best individuals
- 24. When are groups better? For complex problem-solving, if….. 36