Here are some techniques or disciplines that should be strengthened when training new researchers:

• Critical thinking and problem-solving skills: New researchers need to be able to think critically about the research literature and identify the strengths and weaknesses of different approaches. They also need to be able to solve problems creatively and independently.
• Data analysis skills: New researchers need to be able to collect, analyze, and interpret data effectively. This includes skills in using statistical software and data visualization tools.
• Communication skills: New researchers need to be able to communicate their research findings effectively to both technical and non-technical audiences. This includes skills in writing, presenting, and networking.
• Collaboration skills: New researchers need to be able to collaborate effectively with other researchers, both within their own field and across disciplines. This is essential for conducting interdisciplinary research and for getting research published.
• Ethical awareness: New researchers need to be aware of the ethical implications of their research and to conduct their research in an ethical manner. This includes issues such as informed consent, data privacy, and the responsible use of animals in research.

In addition to these specific techniques and disciplines, it is also important to train new researchers in the following general skills:

• Time management: New researchers need to be able to manage their time effectively in order to meet deadlines and complete their research projects.
• Self-motivation: New researchers need to be self-motivated and able to work independently.
• Resilience: New researchers will face setbacks and challenges during their research careers. It is important for them to be resilient and to be able to bounce back from these challenges.

Here are some trends in training for new researchers:

• Increased emphasis on interdisciplinary research: In order to address complex problems, researchers need to work across disciplines. Training programs are increasingly incorporating interdisciplinary approaches to research.
• Greater use of technology: Technology is playing an increasingly important role in research. Training programs are incorporating training in the use of research software, data analysis tools, and visualization tools.
• Focus on transferable skills: In addition to discipline-specific skills, training programs are increasingly focusing on transferable skills such as critical thinking, problem-solving, communication, and collaboration.
• Greater emphasis on ethics: Training programs are increasingly incorporating training in ethical issues such as informed consent, data privacy, and the responsible use of animals in research.

First and foremost is to define the research question properly. It must be stated in a way that it can be answered clearly with a well-structured research program. Many people start out choosing a research method (survey or case study, for example) before they know what question they want to answer. Some institutions (universities) will only allow one research method, and that severely restricts the credibility of the results. For example, many research projects on Critical Success Factors only use surveys, which is a useless method. You may receive a degree but the result of the research is useless because the answer you think you have cannot be verified without a longitudinal study, which may take many years. Also, many research programs are based on the application of a particular theory, but the theory is misapplied. For example, in Critical Success Factor research, many researchers claim their work is based on the theory of John Rockart, but nearly all of it is not. If you want to explore this further you can reach me at [email protected].

In my opinion it clear includes the following modules:

1.Research paper writing

2. Basic and Advanced Research methodology

3. Use of SPSS software

4. Use of statistical test

5. Module on Research literature search

6. Module on research methodology and writing in collaboration with Artificial intelligence