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modestmousktr

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I rally myself to get curious about the data, and to know/hope that the more 'tedious' steps are building an interesting picture for analysis. In other words, I have the 'end goal' in sight (ie: career aspirations, completing program requirements, satisfying intellectual curiosity, etc).

When the interest in the data collection, etc, is losing all meaning, I encourage students to:

1) re-orient towards the initial curiosity in the hypothesis (big picture)
2) 'accept' the tedium, and develop a mantra about meeting a goal (ie: career goals, publication, etc)
3) take some intentional days off (gasp), and make a plan for when you will re-engage
4) if you are learning that you do not love every aspect of research, this is good learning
5) the typical behavioral suggestions -- build in rewards for your efforts, and be specific, follow through
 
As for the research, we all reach a wall at some point. Mine was when I had to write pages of code to get E-Prime to play nicely with our EEG software. Try to boil down tasks you need to complete into sections, and just hit each section one by one. It feels good to complete something, and checking off 10 completions instead of slogging through one huge checkmark can really make a difference and make you feel like you're making headway instead of spinning your wheels.
 
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