Design-based research

How much should educational research techniques mirror natural science research techniques?

What about the research approaches of engineering? Prototyping.

Technology = Application of knowledge

Technology = Creation of knowledge

Technology = Transforming and intervening in the natural world to produce desired results

See handout

Selection skills

Pay close attention to:
1. Data being measured (nominal "categorical", ordinal "ranked", interval "scaled")
2. Number and kind of groups involved
3. Groups are compared or related

SPSS practice

(2) Estimate population mean based on sample mean when sigma is not known (t):

&

(3) Test for statistically significant difference between means (do the intervals overlap?):

SPSS, Analyze, Descriptive Statistics, Explore, Statistics, Confidence Interval
Dependent List = Scaled data variable
Factor List = Grouping variable

Graphing (SPSS, Graphs, Legacy Dialogs, Error Bar) Variable = Scaled data variable, X axis = Grouping variable


Test for statistically significant difference between means (does interval contain zero?) for (4) between groups:

SPSS, Analyze, Compare Means, Independent Samples T-test (Does the interval cross zero? If crosses zero, then no significant difference.)


Test for statistically significant difference between means (does interval contain zero?) for (5) repeated measures:

SPSS, Analyze, Compare Means, Paired Samples T-test (Does the interval cross zero? If crosses zero, then no significant difference.)

Confidence Intervals

The larger the interval range, the more the confidence percentage. People usually set the confidence percentage first and then find the range.

Confidence interval is plus or minus the z score of alpha/2 multiplied by standard error (sigma/square root of n). You can substitute t for z and sigma for s, if you do not know sigma.

"95% confident that the interval includes the parameter." Avoid the "parameter falls between the interval."

Comparing Means With Confidence Intervals

Do the intervals overlap? If yes, no statistical difference. That's it. Replaces Ho testing for between groups and repeated measures.

Confidence Interval for proportions/percentages/pearson r is not tested in this course.

Confidence Interval applications:
1. Estimate population mean based on sample mean when sigma is known (z)
2. Estimate population mean based on sample mean when sigma is not known (t)
3. Test for statistically significant difference between means (do the intervals overlap?)
4. and 5. Test for statistically significant difference between means (does interval contain zero?) for (4) between groups and (5) repeated measures

Chapter 14 Confidence Intervals

Pg (440-447 only)

Confidence intervals look like 78% (+ - 3%). The interval is 75% to 81%.

Non-parametric tests

Chi-square test of independence (two variables or groupings). The differences between groups are tested. You test the Ho and either reject or fail to reject Ho. No association between groups is called independence.





(SPSS, Analyze, Descriptive Statistics, Cross-tab, Statistics, Chi-square)








Chi-square test of goodness of fit (one variable or group). The differences between the group and your expectations (chance) are tested. You test the same way as the test of independence. Expectations of Ho are equal proporation across all choices (chance).



(SPSS, Analyze, Nonparametric Tests, Chi-square)







Chi-square test of significance of a proportion (compare 2 frequencies only like "yes" and "no"). Small case of goodness of fit test.

Chi-square homework set in blackboard.

Non-parametric tests (Chapter 13)

Chapter 13 (Pages 407-416, 431-432 only)

Parametric techniques when we have scaled data (interval or ratio) such as r, z, t, F.

Non-parametric techniques when we have non-scaled data (ranked or categorical) such as Chi-square or phi coefficient.

Chi-square test of independence (conditional probability):
This is the test of two variables (groups) that shows they are independent of each other.

Chi-square test of goodness-of-fit:
Compare proportions.