Scoring the Survey of Faculty Attitudes Toward Information Technology (FAIT 1.1) Questionnaire
The Survey of Faculty Attitudes Toward Information Technology (FAIT 1.0) gathers data on five separate indices from respondents. FAIT is drawn from a subset of the Survey of Teachers' Attitudes Toward Computers which is a 99-199 item Likert/Semantic Differential instrument for measuring teachers' attitudes toward computers. The subset (TACv3.2a) uses 105 items to gather data on seven factors: Enthusiasm, Anxiety, Avoidance, E-mail for Classroom Learning, Negative Impact on Society, Productivity Improvement, and Semantic Perception of Computers. The FAIT (v1.0) uses 68 items on a five point Likert instrument to gather data on five factors: Enthusiasm/Enjoyment (F1), Anxiety (F2), Productivity Improvement (F6), Avoidance (F3) and E-mail Use for Classroom Learning (F4). The following sections describe how to score each scale.
Faculty Attitudes Toward Information Technology - Scoring
The recommended procedure for manual scoring is to simply sum the numeric values of the responses for the related items to produce the various subscale scores. However, some items on the FAIT have negative wording and must be reversed before adding to the others. These items are listed below in the "SPSS command application".
One simple way is to use a colored pen to circle the reflected values of the numbers marked by the respondents for these items. If the respondent circled 1, make it 5: if the respondent circled 4 make it 2. For example, the subscale Enthusiasm/Enjoyment (F1) will be the sum of 15 items (item 1 through item 15), with items 12, and 14 reversed before inclusion in the sum. To generate an average for each subscale, take the sum of the items and divide by the number of items.Reminder: The item number and the variable number (to be used with statistical packages) are the same.
Step-by-Step Scoring Procedures:
1. Reverse the items negatively worded within each subscale.
Twenty two (22) items in the FAIT (v1.0) subscales have negative wording. These items are listed below in the "SPSS command application".
To ensure that this alternate positioning does not skew scores, the scoring process must include the reversal of items negatively worded.
SPSS command example:
compute varx = 6 - varx.
(where x is the variable that represents the item in the scale and where 6 is used for any 5-position scale).SPSS command application:
COMPUTE VAR12=6-VAR12.
COMPUTE VAR14=6-VAR14.
COMPUTE VAR16=6-VAR16.
COMPUTE VAR17=6-VAR17.
COMPUTE VAR18=6-VAR18.
COMPUTE VAR19=6-VAR19.
COMPUTE VAR20=6-VAR20.
COMPUTE VAR22=6-VAR22.
COMPUTE VAR23=6-VAR23.
COMPUTE VAR24=6-VAR24.
COMPUTE VAR25=6-VAR25.
COMPUTE VAR27=6-VAR27.
COMPUTE VAR29=6-VAR29.
COMPUTE VAR46=6-VAR46.
COMPUTE VAR47=6-VAR47.
COMPUTE VAR48=6-VAR48.
COMPUTE VAR49=6-VAR49.
COMPUTE VAR50=6-VAR50.
COMPUTE VAR51=6-VAR51.
COMPUTE VAR54=6-VAR54.
COMPUTE VAR55=6-VAR55.
COMPUTE VAR57=6-VAR57.MISSING VALUES VAR12 VAR14(6)
VAR16 VAR17 VAR18 VAR19 VAR20 VAR22 VAR23 VAR24 VAR25 VAR27 VAR29(6)
VAR46 VAR47 VAR48 VAR49 VAR50 VAR51 VAR54 VAR55 VAR57(6).
2. Generate an average score for each subscale.
Add all values for each subscale and divide by the number of items.
SPSS command example:
compute J = (var1+var2+var4+ +varn)/n.
SPSS command application:
compute F1odd=(var1+var2+var3+var4+var5+var6+var7
+var8+var9+var10+var11+var12+var13+var14+var15)/15.compute F2odd=(var16+var17+var18+var19+var20+var21
+var22+var23+var24+var25+var26+var27+var28+var29+var30)/15.compute F3=(var46+var47+var48+var49+var50
+var51+var52+var53+var54+var55+var56+var57)/12.compute F4=(VAR58+VAR59+VAR60+VAR61+VAR62+VAR63
+VAR64+VAR65+VAR66+VAR67+VAR68)/11.compute F6odd=(var31+var32+var33+var34+var35+var36
+var37+var38+var39+var40+var41+var42+var43+var44+var45)/15.
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