It's not that different in a job search. The first question to ask yourself should be: "What are you seeking in a job?"
Taking some time to think about what is important to you will help you be more selective in where you apply, interview, and hopefully end up working. This will also be a great source of energy, enthusiasm and passion for you when you are asked, "Why do you want this job?"
Using interview questions as your guide, try flushing out what is important to you and what is not. In the end hopefully you will have your own "Wish List" of job requirements.
Interview Question - "When have you been most motivated?"
This is more than an interview question; it is a question that you should be asking yourself before the interview.
When have you been most satisfied in your work? When did you feel like you were making a difference or making a contribution? Basically, what would you like more of in your next job?
This simple exercise will help you answer this question will also help you look inside yourself to think about what you want "more of," and what you want "less of" in your next job. People usually perform at a higher level if they are satisfied with the work that they do - and as a result are more motivated to give 100% - plus.
Exercise to Find the Answer
Begin by making a list of the tasks at your last job - the tasks that you were particularly proud of, or were energized by. In other words, "when your job turned you on." Think about the last time you were so involved in a project or task that you woke up thinking about how you could improve the situation. Write those experiences down and try to determine what the factors were that were satisfying for you.
Let's say you were a "Project Leader." The tasks list would read something like - "Led a team - Coordinated and monitored project progress - Assured the flow and completion of work on schedule - Monitored expenditures and budget."
What were the stimulating tasks of this job? Was it the leadership aspect? Or, was it the challenge of coordinating the details, and people? Was it completing the project on time or below budget? Were there customers involved (internal or external) - if so, is that what you found most challenging?
What didn't you like, and hope that you will do less of in your next job?
After you have written this list for your current job, try doing the same thinking about previous jobs. If you recently graduated from college, use the classes that were most stimulating and interesting for you, or the projects you worked on with teams.
By making lists of motivating experiences from your last two or three jobs, you will hopefully begin to see patterns of projects and tasks that stand out. Analyze what you did before. Do you want more of this type of responsibility in your next job? The answer to this question will give you the answer to the motivation question as well as possibilities for fulfillment in future jobs that have similar responsibilities.
Take this list of motivating experiences and script an answer to the question, "What motivates you?"
This is the start of building your "wish list." It may take time, but little by little you will begin to see the picture. Like the job posting written by employers some of your requirements may be more flexible and some may be fixed.
This will be your task to determine which factors are of the highest importance to YOU.
There is no such thing as the "perfect" answer to this question. Your answer will be individual and based on your own satisfaction and dissatisfaction. No one can do this for you. Only you have the answer.
"What is it that you want in your next job?"
Knowing what you want will make you feel more confident about finding the right job.
Job Search Engines List
The closest search engines have come to actual applications of this technology
so far is know as "Associative Indexing" and it is put in effect under Stemming,
or the indexing of words on the basis of their uninflected roots (plurals, adverbs,
and adjectival forms are reduced to simple noun and verb forms before indexing).
Latent Semantic Analysis (LSA) is a technique in natural language processing,
in particular in vectorial semantics, invented in 1990 [1] by Scott Deerwester,
Susan Dumais, George Furnas, Thomas Landauer, and Richard Harshman.
In the context of its application to information retrieval, it is sometimes
called Latent Semantic Indexing (LSI).
Here are some quick facts about Latent Semantic Indexing:
1. LSI is 30% more effective than popular word matching methods.
2. LSI uses a fully automatic statistical method (Singular Value Decomposition)
3. It is very effective in cross-languages retrievals.
5. LSI can retrieve relevant information that does not contain query words.
6. It finds more relevant information than other methods.
Latent Semantic Indexing adds an important step to the document indexing
process. In addition to recording which keywords a document contains, the
method examines document collections as a whole, to see which others do
contain some of those same words. LSI considers documents that have many
words in common to be semantically close, and ones that have few words in
common to be semantically distant. This method correlates surprisingly well
with how a human being looking at content, classifies multiple documents.
Both Carole Martin & Anne Baugh are contributors for EditorialToday. The above articles have been edited for relevancy and timeliness. All write-ups, reviews, tips and guides published by EditorialToday.com and its partners or affiliates are for informational purposes only. They should not be used for any legal or any other type of advice. We do not endorse any author, contributor, writer or article posted by our team.
Carole Martin has sinced written about articles on various topics from Interview Questions, Interview Questions and Marketing and Communications. Carole Martin, America's #1 Interview Coach has specialized in the subject of "Interviewing" for the past 15 years from both sides of the desk. She has produced a free practice interview that shows you where you are going wrong in your interview. See if y. Carole Martin's top article generates over 165000 views. to your Favourites.
Anne Baugh has sinced written about articles on various topics from Adsense, Small Business and SEO Search Engine Optimization. Jose Nuè'ez is a Scientific SEO/SEM Specialist. He also also owns and operates Search Engines By Hand an online resource focusing on Search Engines (SE) and Artificial Inteligence (AI)Find out more at:. Anne Baugh's top article generates over 3600 views. to your Favourites.
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