FDP
ONE WEEK FACULTY DEVELOPMENT PROGRAMME ON "ENHANCING RESEARCH CREATIVITY: ADVANCED PROBLEM-SOLVING APPROACHES"
FACULTY DEVELOPMENT PROGRAMME
ON
"ENHANCING RESEARCH CREATIVITY: ADVANCED PROBLEM-SOLVING APPROACHES"
Date: October 21st-26th, 2024. Time: 10:00 AM
In the rapidly evolving landscape of academia, fostering research creativity and adopting advanced problem-solving techniques have become critical for the growth and innovation of higher education institutions. The Faculty Development Program (FDP) focused on “Enhancing Research Creativity: Advanced Problem-Solving Approaches” aims to equip educators with the skills and tools necessary to push the boundaries of traditional research methodologies and inspire innovative thinking.
The One Week Faculty Development Programme on “Enhancing Research Creativity: Advanced Problem-Solving Approaches” represents a significant step towards advancing the research capabilities of faculty members. By focusing on creativity, advanced problem-solving methods, and interdisciplinary collaboration, the program aims to empower educators to overcome complex research challenges and contribute to the advancement of knowledge in their respective fields. As academic research continues to evolve, such initiatives are essential in ensuring that faculty members remain at the forefront of innovation and discovery.
Important Areas:
- Innovative Research Tools and Technologies
- Advanced Problem-Solving Methodologies
- Experimental Design and Methodology
- Interdisciplinary Research Approaches
- Ethics and Responsible Research
Objective of the conference:
- Aim to equip educators with the skills and tools necessary to push the boundaries of traditional research methodologies and inspire innovative thinking.
- Advancing the research capabilities of faculty members.
- Focusing on creativity and advanced problem-solving methods.
Day 1 (11 January,2024)
Prof. (Dr.) Masood H. Siddiqui Head, Department of Statistics, University of Lucknow tells about his experience that the research topic is the foundation on which everything else rests, so it’s crucial to choose carefully. “You can’t do anything else until you figure out the basic focus of your topic,” says Dr Masood. He shares his recommendations for choosing an effective research topic.
- Develop a doable topic. Determine what resources you have available—time, money, people—and choose a topic that you can do justice. He scrapped an initial study idea of replicating another researcher’s study because it would be too resource-intensive.
- Read everything you can on the topic. He “stumbled across” systems theory, an interdisciplinary framework for understanding systems in science and society. The topic was outside her required class reading but ultimately provided theoretical framework.
- Find a theoretical basis to support your topic. The key is having an overarching theoretical context for your results. “I was really thrilled when I found these theories that fit my study like a glove,” he says.
- Make sure the topic will hold your interest. You’ll be spending at least a year on a dissertation or any large research project, so it has to be compelling enough that you’ll go the distance.
- Look for a niche in which you can make a difference … My view is that you really should be offering something new to the field,” he says.
- … but remember you can’t change the world with one dissertation. dissertation committee chair, he gently pointed out that I couldn’t change the whole world with my dissertation, but I could add to the body of knowledge,” he says.
- Let yourself shift gears. He admits that the topic she started out with was “in no way” what she ended up with.
- Fine-tune your topic based on input from others. “Take every opportunity you can to pick the brains” of experts, he recommends. “I went across disciplines. I drove people crazy. And each time, I would revise slightly based on what the last person taught me.”
The best way to choose it is not to choose.”In other words, Crawford says, “the methodology that’s used comes from the research question, not from your personal preferences for one design or another.” He recommends refraining from choosing between a qualitative or quantitative methodology until you:
- Complete the sentence: “The problem is …”
Complete the sentence: “The purpose of this study is …”
Formulate your research questions. - Let your answers guide you.
- Determine what kind of design and methodology can best answer your research questions. If your questions include words such as “explore,” “understand,” and “generate,” it’s an indication that your study is qualitative. Whereas words such as “compare,” “relate,” or “correlate” indicate a quantitative study. The design comes out of the study, rather than being imposed on the study.
- your study design. Once you become clear whether you’re going in a quantitative or qualitative direction, you can begin to look in more detail at the methodology. This will be determined by figuring out “from whom you’re going to collect data, how you’re going to collect the data, and how you’re going to analyze it once you collect it,” says Crawford.
- Be crystal clear. For a qualitative study, you might use focus groups and interviews, for example, to collect data, whereas a quantitative study may use test scores or survey results. Either way, the methodology should be so clear that any other trained researcher should be able to pick it up and do it exactly the same way.
- Be honest about your abilities. Ask yourself, “This is what the study demands—do I have the skills to do it?” says Crawford. If not, determine if you can develop the skills or bring together a research team.
- Take your time with the planning process. “It’s worth consulting other researchers, doing a pilot study to test it, before you go out spending the time, money, and energy to do the big study,” Crawford says. “Because once you begin the study, you can’t stop.”
Day 2, 12 January 2024
Dr. Ashish Kaushal said that we aimed to integrate two different views on insight during problem-solving and explore how they each highlight different aspects of the problem-solving process. Looking back, applying both problem-solving and creativity models on to the experts’ and novices’ work reveals and explains different aspects of the student’s problem-solving processes. While the problem-solving model helps us analyze and understand parts of the problem-solving process, there are crucial aspects of the student’s work that it does not explain. In this study, we observed what we claim to be the occurrence of cognitive flexibility, cognitive fixation, and more importantly, sudden, and seemingly unconscious, insight during the problem-solving process—for both experts and novices. The results of this study therefore dovetail with what the Gestaltists said all along: Sudden and unconscious insight seems to be crucial to the problem-solving process, and the occurrence of such insight cannot be fully explained by standardized problem-solving models and an analytic view of insight.
Day 3, 13 January 2024
Ms. Rashmi Sachan said that Researching advanced problem-solving approaches involves a blend of tools and techniques designed to enhance creativity, structure inquiry, and generate actionable insights. Below, I’ll detail specific tools and techniques commonly used in research for advanced problem-solving, focusing on their practical application and relevance to complex challenges.
Tools for Advanced Problem-Solving Research
- Mind Mapping Software
- Examples: XMind, Miro, MindMeister
- Purpose: Visually organize ideas, identify connections, and explore problem dimensions.
- Application: Researchers can map out a problem (e.g., urban sustainability), branching into subtopics like energy use, transportation, and policy. This aids in spotting gaps or synthesizing insights from diverse data sources.
- Strength: Encourages non-linear thinking and collaborative brainstorming.
- Data Analysis Platforms
- Examples: Tableau, R, Python (with libraries like Pandas or SciPy)
- Purpose: Analyze quantitative data to uncover patterns or test hypotheses.
- Application: A researcher studying supply chain inefficiencies might use Python to model bottlenecks, then visualize results in Tableau to identify creative optimization strategies.
- Strength: Provides empirical grounding for creative solutions.
- Simulation and Modeling Tools
- Examples: MATLAB, Any Logic, Simulink
- Purpose: Simulate complex systems to predict outcomes or test solutions.
- Application: In climate research, simulations can model carbon reduction scenarios, helping researchers devise innovative mitigation strategies.
- Strength: Allows experimentation without real-world risks.
Day 4, 15 January 2024
Dr. Manish Sharma (Sidharth University said that the techniques for Advanced Problem-Solving Research) Told that-
- Divergent Thinking
- Description: Generate a wide range of ideas without immediate judgment.
- Process: Use brainstorming sessions, free writing, or "what if" questions (e.g., "What if energy were free?").
- Application: A researcher exploring education reform might list 50+ ways to improve learning outcomes, then narrow it down to feasible innovations.
- Benefit: Expands the solution space beyond conventional limits.
- Convergent Thinking
- Description: Evaluate and refine ideas into practical solutions.
- Process: Apply criteria like feasibility, impact, and cost to prioritize options.
- Application: After brainstorming, a team might score ideas on a matrix to select the best approach to reducing urban congestion.
- Benefit: Ensures creative ideas are actionable.
- Analogical Reasoning
- Description: Draw inspiration from unrelated domains.
- Process: Identify a problem’s core elements and find parallels elsewhere (e.g., how nature solves it—biomimicry).
- Application: Researching efficient water systems might borrow from how trees transport nutrients, leading to novel pipe designs.
Day 5, 16 January 2024
Dr. Anand kumar Rai said that As we end our journey exploring how Artificial Intelligence (AI) is shaping the world of tomorrow, one thing is sure: the future is looking brighter than ever before. From healthcare to finance, transportation to manufacturing, we have witnessed the incredible potential of AI to revolutionize industries and improve our lives in countless ways.
As we have discussed, AI has the potential to revolutionize healthcare by improving patient outcomes, reducing costs, and increasing efficiency. AI automates various processes in finance, such as loan underwriting and account reconciliation, which can help reduce costs and improve efficiency. In transportation, AI enhances traffic flow, reduces accidents, and makes transport more efficient. In manufacturing, AI is used to optimize production processes, improve supply chain management, and reduce costs.
But as we marvel at the potential of AI, we must also acknowledge the ethical and societal implications of this powerful technology. But fear not, for as we have seen, these implications can be mitigated by considering the societal impact of AI, investing in retraining and reskilling programs, incorporating diversity, implementing robust privacy and security measures, fostering transparency and accountability in AI systems, and taking a holistic view to ensure that the technology serves to benefit all members of society.
Valedictory session
