1. Thomson South-Western Wagner & Hollenbeck 5e 1 Chapter Sixteen Critical Thinking And Continuous Learning

2. 2 Chapter Overview  This chapter examines the following topics: – Critical Thinking and the Scientific Process Ways of Knowing The Purposes of Science The Interplay of Theory and Data Characteristics of Good Theories and Good Data – Casual Inferences Criteria for Inferring Cause Designing Observations to Infer Cause – Generalizing Research Results Sample, Setting, and Time Facilitating Generalizations

3. 3 Introduction  Mangers used to say they hired a “hand”, today they say they hired a “mind”  In a world where minds are hired, learning becomes essential  Two primary features of learning organizations set them apart from their competitors: – Critical analysis of experiences and the experiences of others to maximize the capacity to learn from past successes and failures – Penchant for experimentation and use of the scientific method to promote innovation

4. 4 Critical Thinking and the Scientific Process: Ways of Knowing  To form a learning organization, all employees, especially managers, must become more disciplined in their thinking and pay more attention to detail  Philosophers of science have explored many ways of arriving at knowledge  The most common source of knowledge for most of us is personal experience

5. 5 Critical Thinking and the Scientific Process: Ways of Knowing  The limits of personal experience in the context of learning has led to the development of the scientific method  Objectivity or the degree to which scientific findings are independent of any one person’s opinion about them, represent the major difference between the scientific approach to knowledge and other approaches

6. 6 Critical Thinking and the Scientific Process: Ways of Knowing  Science as an enterprise is public in the sense that the methods and results obtained by one scientist are shared with others  It is self-correcting in the sense that erroneous findings can be isolated through the replication of one scientist’s work by another scientist  The public and self-correcting nature of this process when successfully practiced means that the results that are eventually accepted are cumulative in the sense that one scientist’s work often builds on another’s work

7. 7 The Purposes of Science  The basic goal of science is to help humans understand the world around us  The purpose of some research is simply description  For other scientific studies, predicting is the primary goal  Studies that focus on prediction often lead to further research in which the goal is to control the situation  The ultimate goal of science is explanation

8. 8 The Interplay of Theory and Data  Kerlinger defines a theory as “a set of interrelated constructs, definitions, and propositions that presents a systematic view of a phenomenon by specifying relationships among variables”

9. 9 The Interplay of Theory and Data  To have any practical utility, theories must prove themselves in the world of data  Through a process of deduction, researchers generate hypotheses or specific predictions about the relationships between certain conditions in the real world  Through the process of verification the accuracy of the theory and the extent to which it holds true can be checked

10. 10 Characteristics of Good Theories and Good Data  You do not have to be a scientist to create a theory  We routinely develop informal or implicit theories about the world around us  In most cases, scientific theories are developed more formally and are called explicit theories to distinguish them from implicit theories

11. 11 Characteristics of Good Theories and Good Data  John B. Miner has offered several criteria for judging the worth of theories in organizational behavior – A theory should contribute to the objectives of science – Theories must be logically consistent within themselves – A theory must be consistent with known facts – A theory must have consistency with respect to future events – Theories should have simplicity

12. 12 Characteristics of Good Theories and Good Data  Several characteristics render some measures and therefore the data they generate, better than others: – The measures must possess reliability or freedom from random errors – The measures must possess validity or assess what they were meant to assess Criterion-related validity – Measures must have standardization, which means that everyone uses the same instrument in the same way

13. 13 Causal Inferences  Knowledge is most applicable when it can be expressed in terms of cause-and-effect relationships  True learning can take place only when a person seriously reflects upon past experience and analyzes it critically

14. 14 Criteria for Inferring Cause  John Stuart Mill argued that to state unequivocally that one thing causes another, we must establish three criteria: – Temporal precedence: the cause must come before the effect – Covariation: if the cause is varied so must the effect be Test of mean variances Correlation coefficient – Elimination of alternative explanations Selection threat: the groups selected for comparison were not the same initially History threat: the real cause is not the change you made but rather something else that happened at the same time

15. 15 Designing Observations to Infer Cause  The timing and frequency of data collection affect the ability to make causal interpretations  Deciding on the timing of measurement is an important part of research design  An advantage of building alternative explanations into the design is so they can be tested for interactions

16. 16 Generalizing Research Results  Research is generally conducted with one sample, in one setting, in one time period  Generalizability is defined as the extent to which results obtained in one sample- setting-time configuration can be repeated in a different configuration

17. 17 Sample, Setting, and Time  Results of research may not generalize across all samples  Results of research must be examined across: – Samples – Settings – Time

18. 18 Facilitating Generalization  You can safely generalize from one sample to the next if the original sample is randomly selected from the larger population  Although random selection is the only way to guarantee the ability to generalize results across samples, it is often hard to achieve

19. 19 Linking Organizational Behavior Science and Practice  A wealth of research conducted by others is just waiting to be discovered  Although you may never conduct formal research yourself, you will undoubtedly find it invaluable to familiarize yourself with the large body of scientific evidence available on topics that will be crucial to you, your employer, and your employees