Data Analysis & Data

Visualization

Spring 2013| Nahl | LIS 665 Teaching Information Technology LiteracyUniversity of Hawaii | LIS Program

LIS 665 Teaching Information Technology Literacy 2

Assessment Cycle

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Gather Data

Plan for Improvement

Share Data & Plan

Analyze & Interpret

Implement the Plan

Radcliff et al. p. 171

Tables & Figures: Naming, Explaining, and Interpreting Results

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Figure 1. Demographics:Types of Libraries

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Figure 2. Demographics:Library Departments

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Data Presentation Exercise:Write a Complete Title for the Figure and Labels for the each pre-post bar

set

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Data Presentation Exercise:Write a Complete Title for the Table and

a Sentence about what these results mean

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IV & DV Defined Independent Variable(s)

Treatment or Intervention or Condition

Random Selection & Random Assignment

Dependent Variable(s) or Dependent Measure(s)

Measuring instrument (worksheet, clicker questions, pre-post test, single test, open-ended instrument, e.g., Muddiest point, Minute paper, session evaluation comments, etc.)

Outcome, results, data (their ratings or scores or frequencies or other result types)

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Evaluation of the Effectiveness of Two Library Instructional Videotapes

IV: Library videotape 1, Library videotape 2

DV: Effectiveness [evaluated or measured in some way]

Exercise: Identifying Independent and Dependent Variables

in Research Article Titles

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Library Jargon: Student Comprehension of Technical Language Used by Librarians

IV:

DV:

What is being measured?

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Information Literacy Skills: An Exploratory Focus Group Study of Student Perceptions

IV:

DV:

What is being done?What is being measured?

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A Comparison of Presentation Formats for Instruction: Teaching First-Year Students

IV:

DV:

What is being changed? What is being measured?

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A Longitudinal Study of the Effects of OPAC Screen Changes on Searching Behavior

and Searcher Success

IV:

DV:

What is being altered?What is being measured?

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Programmatic Assessment: Turning Process Into Practice by Teaching for Learning

IV:

DV:

What is being varied?What is being measured?

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Statistical Significance Defined

Only relevant in Experimental Designs (IV DV)

Statistical Significance: p value <.05

In 100 different samples, 95% will have the same mean or average, and only 5% of the samples will have different means

Systematic or consistent results, confidence levels

Significant results vs. Important results (size of the difference, or size of the correlation)

Size of the sample (n = 30 minimum, more depending on type of study and population size)

Allows generalizing results to a population (as defined in the study)

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Correlation Defined Relationship between two variables

Not causal (X does not cause Y) but related, multivariate, multifactorial, co-occurrence, identify trends

Intervening or confounding variables

Direction [+ positive (up) or - negative (down)]

Square the correlation (r2) to get its size in Percent (%)

Magnitude (size of the correlation)

r = .4 to .6 moderate [16% - 36% due to the X/Y variables, 84% - 64% due to other unidentified variables]

r = .6 to .8 strong

r = .9 near perfect & 1.0 perfect

Significance (p value <.05) permits applying results from one sample to the entire population (as defined in the study)

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Positive Correlation

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Figure 1. Correlation for Computer Literacy and Search Success

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Negative Correlation

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Figure 2. Correlation for Computer Anxiety and Search Success

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Correlation Matrix

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Table 1. Correlations for Computer Literacy, Computer Anxiety, Visual Acuity, and Search Success

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Correlation Results

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Table 2. Correlation for Computer Literacy and Search Success

Significant correlations (p = <.05) suggest the results are systematic and apply to the whole population (as defined in the study)

P < .0001 = 1 sample in 10,000 samples will have a different correlation

P < .001 = 1 sample in 1,000 samples will have a different correlation

P < .01 = 1 sample in 100 samples will have a different correlation

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