Research skills methodology, steps for research

Research skills methodology

1. Dr.M.Marsaline Beno 1 1 Enhancing Research Methodology Skills For Engineering Educators Dr.M.MARSALINE BENO Dean- Research PROFESSOR DEPARTMENT OF ELECTRICAL AND ELECTRONICS ENGINEERING St.XAVIER’S CATHOLIC COLLEGE OF ENGINEERING Email : [email protected] Mobile: [phone]/2024

2. Presentation Flow Introduction Understanding Research Methodology Research Design Literature Review Data Collection Techniques Data Analysis Interpretation and Reporting Enhancing Teaching Through Research Professional Development Opportunities Conclusion

3. INTRODUCTION

4. Entrepreneurship Ecosystem

5. E DUCATION 4.0

6. What is Innovation “Something new or different introduced.” Creative Problem Solving

7. SCAMPER

8. SUBSTITUTE

9. COMBINE

10. ADAPT

11. MAGNIFY

12. MINIFY

13. REARRANGE

14. Innovation Be Stupid …..

15. Importance of Research Methodology for Engineering Educators Foundation of Knowledge Guiding Principles Informed Decision Making Continuous Improvement Enhanced Student Learning Professional Development Empowerment and Impact

16. Understanding Research Methodology What is Research ? Dr.M.Marsaline Beno 16

17. Research What is Research ? A planned ,Investigation is Research Dr.M.Marsaline Beno 17

18. Research Flow Diagram

19. The categories of knowledge in research

20. Types of Research : Basic Research: This type of research focuses on fundamental principles and theories, aiming to expand our understanding of concepts without immediate practical applications. Basic research often forms the foundation for more applied research.

21. Applied Research: Applied research is conducted with the specific goal of solving real-world problems or addressing practical issues. Its findings are intended to have direct implications or applications in various fields.

22. Quantitative Research Design Quantitative research involves the collection and analysis of numerical data to identify patterns, relationships, and trends. It often employs statistical techniques to draw conclusions from the data. Characteristics:      - Emphasis on objective measurement and statistical analysis.      - Utilizes structured instruments such as surveys, experiments, or tests.      - Seeks to generalize findings to a larger population

23. Qualitative Research Design Qualitative research explores the underlying motivations, attitudes, and behaviors of individuals or groups. It relies on non-numerical data, such as interviews, observations, and textual analysis, to generate insights Characteristics:      - Emphasizes naturalistic inquiry and subjective interpretation.      - Uses methods such as interviews, observations, and focus groups.      - Aims to generate rich, descriptive data to uncover underlying meanings and patterns.

24. Mixed-Methods Research Design Mixed-methods research integrates both quantitative and qualitative approaches within a single study to provide a comprehensive understanding of a research problem. Characteristics:      - Combines quantitative and qualitative data collection and analysis techniques.      - Allows researchers to triangulate findings, validate results, and gain deeper insights.      - Offers flexibility in addressing research questions that require multiple perspectives.

25. Selecting the Appropriate Research Design for Engineering Studies Considerations for Selecting Research Design    - Nature of the research question: Determine whether the research aims to explore relationships (quantitative), understand phenomena (qualitative), or both (mixed-methods).    - Availability of resources: Assess the feasibility of data collection methods, sample size requirements, and time constraints.

26. Selecting the Appropriate Research Design for Engineering Studies Tailoring Research Design for Engineering Studies    - Engineering studies often require a combination of quantitative analysis for empirical data (e.g., performance metrics, numerical simulations) and qualitative inquiry for understanding human factors, user experiences, and socio-technical aspects.    - Researchers may employ mixed-methods designs to complement quantitative data with qualitative insights, providing a holistic understanding of complex engineering phenomena.

27. Examples of Research Design in Engineering Education Experimental Design    - Example: Assessing the effectiveness of a new teaching method on student learning outcomes in an engineering course through controlled experiments with randomized assignment of participants to treatment and control groups.

28. Examples of Research Design in Engineering Education Survey Research Design    - Example: Conducting a survey to investigate engineering students' attitudes, perceptions, and experiences related to online learning tools and technologies

29. Examples of Research Design in Engineering Education Case Study Design    - Example: Examining the implementation of a project-based learning approach in an engineering curriculum by conducting in-depth case studies of multiple courses across different institutions

30. Examples of Research Design in Engineering Education Mixed-Methods Design    - Example: Integrating quantitative analysis of assessment scores with qualitative interviews to explore factors influencing student engagement and learning experiences in a robotics engineering program

31. Key steps in the research process Research is a dynamic process that follows a structured methodology to ensure rigor, accuracy, and reliability of results. Key steps in the research process include defining research questions or hypotheses, designing a research plan, collecting data, analyzing data using appropriate methods, drawing conclusions, and communicating findings through publications, presentations, or reports. In both academia and industry, research contributes to innovation, problem-solving, policy formulation, and informed decision-making. It drives progress in various fields and fosters a deeper understanding of the complex world we live in.

32. Literature Review: New knowledge in research can only be interpreted within the context of what is already known, and cannot exist without the foundation of existing knowledge. A literature review involves gathering and analyzing existing research and publications on a specific topic. It helps researchers understand the current state of knowledge, identify gaps, and build on existing research. Often, but not always, the textbooks contain the older established knowledge and the research papers the newer work. Reading the textbooks on one’s topic provide the established knowledge and the background to be able to read the newer work usually recorded in the research papers

33. A good literature survey is typically a two-step process Generally, a good literature survey is the first expectation of a supervisor from the research student, and when done well can create a good impression that the state of art in the chosen field is well understood ( i ) Identify the major topics or subtopics or concepts relevant to the subject under consideration (ii) Place the citation of the relevant source (article/patent/website/data, etc.) in the correct category of the concept/topic/subtopic

34. literature survey The goal of literature survey is to bring out something new to work on through the identification of unsolved issues, determine the problems in the existing models or experimental designs, and present a novel idea and recommendations Technical Reading Conceptualizing Research Taking Notes While Reading Attributions and Citations: Giving Credit Wherever Due

35. The literature survey grid

36. Overview of Data Collection Methods Surveys    - Surveys involve gathering information from a sample of participants through structured questionnaires or online forms. Interviews    - Interviews entail direct communication between the researcher and participants to gather in-depth insights and perspectives. Observations    - Observations involve systematically watching and recording behaviors, interactions, or phenomena in natural or controlled settings. Experiments    - Experiments involve manipulating variables and measuring their effects on outcomes in controlled settings.

37. Considerations for Choosing Data Collection Techniques Research Objectives    - Align data collection methods with the specific research questions and objectives.    - Consider whether quantitative, qualitative, or mixed-methods approaches are most appropriate. Participant Characteristics    - Take into account the characteristics of the target population, including demographics, preferences, and accessibility. Resource Availability    - Assess the availability of time, budget, and expertise required for implementing different data collection methods. Ethical Considerations    - Ensure that data collection methods adhere to ethical guidelines, including informed consent, privacy, and confidentiality

38. Best Practices for Ensuring Data Validity and Reliability Pilot Testing    - Conduct pilot tests to refine data collection instruments and procedures before full-scale implementation. Standardization    - Standardize data collection protocols to minimize variations and ensure consistency across data collection sessions. Triangulation    - Use multiple data sources or methods (triangulation) to corroborate findings and enhance the validity of results. Data Verification    - Verify collected data for accuracy and completeness through regular checks and validation procedures. Documentation    - Maintain detailed records of data collection procedures, including any deviations or modifications made during the process. Peer Review    - Seek feedback from peers or experts in the field to validate data collection methods and interpretations.

39. Introduction to Data Analysis Techniques Descriptive Statistics       - Descriptive statistics involve summarizing and describing the characteristics of a dataset through measures such as mean, median, mode, standard deviation, and frequency distributions. Inferential Statistics       - Inferential statistics are used to make inferences and predictions about a population based on sample data. It includes techniques such as hypothesis testing, correlation analysis, regression analysis, and analysis of variance (ANOVA). Qualitative Analysis       - Qualitative analysis involves interpreting and making sense of non-numerical data, such as text, images, or observations. It includes methods such as thematic analysis, content analysis, and grounded theory.

40. Application of Statistical Software Tools in Engineering Research Examples of Statistical Software       - Statistical software tools such as SPSS (Statistical Package for the Social Sciences), SAS (Statistical Analysis System), R, and MATLAB are commonly used in engineering research for data analysis. Functions and Capabilities       - These software tools offer a wide range of functions and capabilities for conducting various statistical analyses, data visualization, and reporting results. Advantages       - Statistical software enhances efficiency, accuracy, and reproducibility in data analysis, allowing researchers to handle large datasets and complex statistical models effectively

41. Examples of Data Analysis in Engineering Education Studies Assessment of Student Performance       - Using descriptive statistics to analyze exam scores, grade distributions, and student performance trends to assess the effectiveness of teaching methods and curriculum. Evaluation of Teaching Interventions       - Applying inferential statistics to compare the learning outcomes of students exposed to different teaching interventions or instructional strategies. Qualitative Research on Pedagogical Practices       - Conducting qualitative analysis of student feedback, classroom observations, or reflective journals to explore perceptions, attitudes, and experiences related to engineering education.

42. Importance of Interpretation Interpretation is a critical component of research methodology that involves making sense of the collected data and deriving meaningful insights. It enables researchers to draw conclusions, identify patterns or trends, and evaluate the implications of their findings in the context of existing knowledge and theories.

43. Key Aspects of Interpretation Contextualization       - Understanding the broader context in which the research was conducted and how the findings contribute to advancing knowledge in the field. Critical Analysis       - Evaluating the strengths and limitations of the research methodology, data collection techniques, and analytical methods used in the study. Synthesis       - Integrating and synthesizing the findings to develop coherent explanations or theories that explain observed phenomena or relationships

44. Strategies for Interpreting Research Findings Effectively Compare and Contrast       - Compare findings with existing literature and contrasting perspectives to identify similarities, discrepancies, or areas for further investigation. Seek Patterns and Trends       - Look for recurring patterns, trends, or outliers in the data that may provide insights into underlying relationships or phenomena. Consider Alternative Explanations       - Explore alternative explanations or interpretations for the findings and assess their plausibility based on available evidence.

45. Guidelines for Reporting Research Results in Engineering Education Journals Clarity and Precision       - Present findings clearly and concisely, using appropriate language and terminology to ensure comprehension by readers. Transparency       - Provide sufficient detail on the research methodology, data collection procedures, and analytical techniques to allow for replication and verification by other researchers. Discussion of Implications       - Discuss the practical implications of the findings for engineering education practice, policy, or future research directions.

46. Enhancing Teaching Through Research Integration Student –led projects Incorporating case studies Collaborate Research with Industry Project Based Learning Research Groups Mentorship

47. Professional Development Opportunities Professional Organizations Workshops, Seminars, Conferences Collaboration & Networking

48. Research and Development vs. Product Development Research and Development is the conception phase in the  product life cycle , while Product Development is the entire process of designing, creating, and marketing new products or existing products with new features.

49. Design Thinking

50. Understanding Technology Readiness Level (TRL), Manufacturing Readiness Level (MRL) and Investment Readiness Level (IRL )

51. Innovation Skills- 7 Habits Think out of the box Always be eager in doing things(interest) Sleep with problems Suspend judgments Use analogy Decide fast Bank ideas

52. Thank You