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This is a general discussion forum for the following learning topic:
Developing New Programs: Research and Selection --> Learn from the Data
Post what you've learned about this topic and how you intend to apply it. Feel free to post questions and comments too.
Analyzing and learning from the collected data is pertinent when considering adding a new program. It is important to pay attention to what the data shows and not cast it aside. It may show it would not be beneficial to add the program, you may find a different program you want to consider adding instead, or you may find you just want to add continuing education opportunities.
Es importante saber quién es tu competencia y cuál es tu ventaja competitiva.
Data analysis and the process of collecting, analyzing, and interpreting the information is important, but only a portion of the process. Because without the data, development of a program is limited at best, but with the data you can determine a program's efficacy and if there is any other value that can be extracted from the data as well.
Data analysis is very important to see where the institution is standing, doesn't matter if it needs a new career or needs adjustments and modernize our current careers
Being a new Executive Assistant, in the education field, this has been great to help me understand the launch of new programs.
In the process of developing new programs, learning from data is a crucial step that guides informed decision-making. Here's a summary of key insights and potential applications:
Identifying Trends and Patterns:
What: Analyzing data to identify trends and patterns.
Why: Recognizing trends helps in understanding the evolving needs and demands in education, ensuring that new programs align with current and future requirements.
Assessing Program Effectiveness:
What: Evaluating data on existing programs.
Why: Examining program effectiveness helps in identifying areas of success and improvement, informing decisions on whether to continue, modify, or introduce new programs.
Understanding Student Demographics:
What: Analyzing demographic data of enrolled and prospective students.
Why: Understanding the demographics informs program customization to meet the diverse needs of the student population.
Adapting to Industry Changes:
What: Monitoring data related to industry changes and demands.
Why: Adapting programs based on industry data ensures graduates are equipped with skills relevant to the current job market.
Responding to Employer Needs:
What: Collecting data on employer needs and expectations.
Why: Aligning educational programs with employer requirements enhances graduates' employability and strengthens partnerships with industry stakeholders.
Analyzing the data and understanding it is very important as it will help determine what next steps to take.
it is very important to know your competitors and also to learn your community need as well.
Data collection is necessary for the institution and it will allowed you make the necessary changes
Making changes to an existing program can be a low cost alternative to creating a new program, if your market research supports this.
Data will provide justification for 'the ask' when it comes funding. Data can also be manipulated any which way to support whatever it is you are pitching. It's a sales ally.
This is why I'm a mixed methodologist as it relates to research because quantitative data only reveals WHO & WHAT is occurring and HOW often. Qualitative data reveals the WHY which, to me is far more interesting and actionable.
When collected properly, the data will not lie. Whatever the data tells us should be followed, even if it is not the outcome we wish for. Even if the data shows that a new program would be contraindicated, it may teach us things about existing programs or processes we can improve.
Careful analysis of the data may help establish the following:
Competition
Competition thru co-ordination
Availability of resources
Identification of critical success factors
Regulatory requirements