Table 1.

Faculty ranking

Science process skills	Average score of importancea
Problem solving/critical thinking	4.9
Interpreting data: graphs and tables	4.9
Interpreting data: ability to construct an argument from data	4.8
Creating the appropriate graph from data	4.7
Communicating results: written	4.7
Ability to create a testable hypothesis	4.7
Ability to design an experiment: identifying and controlling variables	4.6
Ability to design an experiment: development of proper controls	4.6
Communicating results: oral	4.6
Knowing when to ask for guidance	4.6
Conducting an effective literature search	4.6
Reading and evaluating primary literature	4.5
Ability to design an experiment: proper alignment of experiment and hypothesis	4.5
Understanding basic statistics	4.5
Working independently when needed	4.5
Working collaboratively to accomplish a task	4.4
Being able to infer plausible reasons for failed experiments	4.4
Being able to effectively monitor their own learning progress	4.3
Creating a bibliography and proper citation of references	4.2
Interpreting data: gels, blots, microarrays, etc.	4
Being an effective peer mentor	3.6
Ability to use basic online bioinformatics tools (NCBI databases, BLAST, etc.)	3.5

^a The average score of importance was determined by converting a descriptive Likert scale to a numerical scale (5 = Very Important, 4 = Important, 3 = Moderately Important, 2 = Of Little Importance, 1 = Unimportant), and taking the average.