I have collected a questionnaire data from some 3rd graders asking about their views towards science.
The whole scale has 11 items.
The data were coded as 1 (disagree), 2 (neutral), and 3 (agree).
There are 3 negatively worded items out of the total 11 and I reverse coded them when I ran the Cronbach's Alpha.
However, the Cronbach's Alpha came out really low, and by looking at the "Cronbach's Alpha if Item Deleted" statistics, the cronbach's Alpha will increase if I deleted these three items.
Then I ran the reliability test again without reverse code these 3 items (i.e., code them the same way as the positive worded items). The CA came back higher than when I reverse coded the items, but again, if I deleted these 3 items, the CA will be even higher.
I don't know what I should do with these negatively worded items. They are worded in a way that so obviously the reverse coding is needed. But came back with poor reliability, which means they should be deleted. I wonder if there's any one knows how to handle this situation, or if I can find any solutions from the literacy.