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Pages:
1 page/≈275 words
Sources:
2 Sources
Level:
APA
Subject:
Technology
Type:
Essay
Language:
English (U.S.)
Document:
MS Word
Date:
Total cost:
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Topic:

Data Analysis and Dissemination (Essay Sample)

Instructions:

“I don’t know.” Not knowing something is difficult for many people to admit for a variety of reasons: they don’t want to look unknowledgeable, they want to impress someone, or they are afraid of the truth. However, admitting what you do not know is a critical component of being a reflective practitioner. If you only focus on the things you know, you will stagnate. You will never explore new ideas, read innovative research, or improve your practice. In other words, you can never become stronger unless you focus on recognizing and developing your weaknesses.
In this Discussion, you complete a self-reflection regarding areas in program evaluation about which you feel confident and those in which you are not as confident. You will explain how you will use these weaker areas as catalysts for professional development and what resources you need to complete the task.
To Prepare
This week’s Learning Resources outline techniques that may be used for data analysis and outcome dissemination in program evaluation. You are asked to complete a self-reflection this week regarding areas in these two steps of program evaluation about which you feel confident and those in which you feel you need more professional development.
Post a description of at least two areas related to data analysis and outcome dissemination about which you would like to further professionally develop beyond the course. Explain how you will use these interests or challenge areas as catalysts for professional development and how you will grow your knowledge in these areas, or what resources you might use to complete tasks cooperatively as an evaluation team.
Regards

source..
Content:


Data Analysis and Dissemination
Institution
Name
Date
Data Analysis and Dissemination
The areas which I feel confident about program evaluation includes the analysis of quantitative data such as tallying responses from various population, counting of the program activities carried pout during evaluations, and the interpretations of data. Qualitative analysis involves looking at the shared stories by the people surveyed during interviews and data collection.

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