Understanding Mindshift Learning: The Transition to Object-Oriented Development

1. Authors: Deborah J. Armstrong Florida State University Bill C. Hardgrave University of Arkansas Presented By: DJ Susko Cleveland State University Understanding Mindshift Learning:The Transition to Object-Oriented Development

2. Introduction • IT professionals are constantly facing changes in their in their work environment. • When concepts change, we witness a shift in mindset (mindshift). • Examples: • Mainframe to Client-Server Computing • Traditional to Object-Oriented Development • People employ new technologies with old ideas, losing advantages of new mindshift.

3. Introduction • Learning during a mindshift is difficult • Why is learning difficult? • Study explores software developers transitioning to O-O development. • Seeks to understand difficulties encountered during the acquisition of fundamental O-O concept knowledge.

4. Context • Framework for classifying IS development. • Developed in 1998, 2000-01 by Iivari, Hirscheim, and Klein. • Four hierarchal levels for framework: • Paradigm: • Functionalism, Social Relativism Neohumanism, and Radical Structuralism • Approach • Methodology • Techniques

5. Definitions • O-O Software Development: • “Developing software that is centered on the concepts of cooperating objects and classes.” • Traditional Software Development: • Represents any non-object-oriented software development approach.

6. More Context • Using IS framework, shift occurs at the approach level. • Learning process begins with individuals being introduced to fundamental concepts that define the approach. • Objective: Understand the difficulty while learning fundamental concepts that underlay the new approach.

7. Past Research • Three major research themes emerged: • Semantics first, then Syntax. • Semantically vs. Syntactically Focused Knowledge Structures. • Transition from Traditional to O-O Approach.

8. The Learning Process • Knowledge Structure: • “A representation of person's knowledge that includes both a set of domain-specific concepts and relations among those concepts.” • Concept Knowledge: • “Actual ideas and information embodied in the knowledge of events or objects designated by a label.”

9. The Learning Process • Incremental Learning: • Knowledge structure most closely matching the concept is activated. • As knowledge increases, a person revises existing knowledge structures to organize knowledge. Example: Java learner, new JComboBox concept

10. The Learning Process • Mindshift Learning: • Learner activates existing knowledge structure that is only partially appropriate. • “Proactive Interference” • Knowledge that is inappropriate in new domain. • Existing knowledge interferes with learning process. • Makes it difficult to understand concept within concept of the new mindset.

11. Cognitive Processing • Novel: • Encounters situation unfamiliar or unknown. • Promotions or career changes trigger active thinking. • Discrepant: • Unexpected failure or disruption between expectations and reality. • Difference in performance review between manager and employee.

12. Cognitive Processing • Deliberate Initiative: • Response when asked to think or while being explicitly questioned. • Career planning triggers active thinking • Reflect on goals, resources, & opportunities

13. Base Theory

14. Refining the Theory • Determine concepts fundamental to O-O: • Concept's origin is important to understanding it • Some are borrowed from Traditional (attribute) • Some are new to O-O (inheritance) • Some are contradictory (encapsulation)

15. Inductive Approach to Refine Theory • 3 OO experts asked to assist with learning portion. • Sort the 9 OO concepts into 3 categories. • Each expert experienced difficulty with sorting. • Each understood novel category. • Failed sorting led to new categories: • Novel, Changed, and Carryover.

16. New Categories • Novel—Same as before. • Changed: • Any concept that had an existing meaning in traditional development, but new meaning in the O-O development context. • Carryover: • Concepts originally defined in traditional and hold the same meaning in O-O development.

17. Revised Theory

18. Hypotheses Development • Novel Concepts (high novelty): • Integrate directly into OO concept knowledge. • Traditional knowledge will have no influence. • Changed Concepts (low novelty): • Proactive interference may occur. • Existing traditional knowledge will negatively influence learner's knowledge of concept. • Carried Over Concepts (somewhere in between): • Positive influence on learner's knowledge.

19. Hypotheses Development High Carryover O-O Concept Knowledge Novel Changed Low (0%) High (100%) Degree of Novelty

20. Hypotheses • H1: A developer's OO concept knowledge score will have a U-shaped relationship with the degree of perceived novelty. • H2: A developer's carryover concept knowledge score will be greater than his/her changed concept knowledge score. • H3: A developer's carryover concept knowledge score will be greater than his/her novel concept knowledge score. • H4: A developer's novel concept knowledge score will be greater than his/her changed concept knowledge score.

21. Method • Survey sent via mail or e-mail to organizations. • Criteria: Both traditional and OO development. • Sample: • 81 software developers from 16 companies and various industries. • 39% Response Rate.

22. Sample Table

23. Instrument Development • First Section: • 9 items measuring degree of perceived novelty. • Second Section: • 27 items measuring OO concept knowledge. • Third Section: • 9 items measuring level of perceived learning difficulty for each concept. • Validation

24. Hypothesis Testing- H1

25. Hypothesis Testing- H1 • H1 is supported. OO concept knowledge score does have a U-shaped relationship with the degree of perceived novelty.

26. Data Prep for Testing H2-H4 • Necessary to categorize the concepts by subject. • Based on a degree of perceived novelty: • Carryover = 0 – 24% • Changed = 25 – 75% • Novel = 76 – 100%

27. Hypothesis Testing: H2-H4 • H2: Supported. • H3: Not Supported. • H4: Supported.

28. Looking Deeper into H3 • Why no significance between Carryover and Novel? • Study believes that novel concept knowledge improved over time making it equal to his/her knowledge of carryover concepts. • Looked at years of OO experience for answers. • Very small, but significant correlation found.

29. Years of 00 Experience

30. Do Scores Improve Over Time? Knowledge improves over time in novel and carryover. Problems caused by proactive interference tend to persist over time.

31. Experience vs. Perceived Novelty

32. Concept's Difficulty

33. Limitations/Future Research • Wasn't possible to directly test the impact of experience over time on OO concept knowledge. • Test an individual's knowledge at various points in time. • Theory has the potential to generalize to other mindshift learning situations. • Principles identified in the MLT may improve understanding.

34. Conclusion • Previous research stated mindshift learning was more difficult than incremental learning, but didn't answer why. • Our findings indicate lower scores in areas perceived as changed. • We can use results for organizations to change the training process for individuals.

35. Questions??