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Using Analytics to Tell Our Story Andrea Kincaid and Jacob Ellis Reference & Instruction Librarians Rowan-Cabarrus Community College Metrolina Library.

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Presentation on theme: "Using Analytics to Tell Our Story Andrea Kincaid and Jacob Ellis Reference & Instruction Librarians Rowan-Cabarrus Community College Metrolina Library."— Presentation transcript:

1 Using Analytics to Tell Our Story Andrea Kincaid and Jacob Ellis Reference & Instruction Librarians Rowan-Cabarrus Community College Metrolina Library Association CPCC Harris Campus | June 9, 2016

2 Session Agenda Assessment – Faculty surveys – Student surveys Statistics – Foot Traffic – Reference – Instruction Discussion

3 Assessment Andrea Kincaid

4 Why Assess? “ Evaluation and assessment of an instruction program are systematic ongoing processes that inform and guide Library strategic direction.” ACRL’s Guidelines for Instruction Programs in Academic Libraries

5 Assessment: Two Points of View Faculty Surveys Focus on the Librarian – Teaching style – Librarian’s familiarity with material – Librarian’s proficiency Post-test only Student Surveys Bloom’s Taxonomy of Learning – Knowledge – Skills – Attitudes Pre-test & post-test format

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7 Faculty Survey: Individual Comparison Aggregate DataAndrea’s Data

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9 Pre-Instruction Surveys

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11 What Do You Want to Learn?

12 Comparing Pre-Test and Post-Test Pre-InstructionPost-Instruction

13 Comparing Pre-Test and Post-Test Pre-InstructionPost-Instruction

14 Comparing Pre-Test and Post-Test Pre-InstructionPost-Instruction

15 Comparing Pre-Test and Post-Test Pre-InstructionPost-Instruction

16 Comparing Pre-Test and Post-Test Pre-InstructionPost-Instruction

17 Instruction Librarian Goals In order of priority: Boolean operators Evaluating sources Library catalog, not journals After-hours help

18 Post-Instruction Surveys: Individual Comparison Aggregate DataAndrea’s Data

19 Post-Instruction Surveys: Individual Comparison Aggregate DataAndrea’s Data

20 Post-Instruction Surveys: Individual Comparison Aggregate DataAndrea’s Data

21 Post-Instruction Surveys: Individual Comparison Aggregate DataAndrea’s Data

22 Post-Instruction Surveys: Individual Comparison Aggregate DataAndrea’s Data

23 Post-Instruction Surveys: Individual Comparison Aggregate DataAndrea’s Data

24 Post-Instruction Surveys: Individual Comparison Aggregate DataAndrea’s Data

25 Goals Comparison Andrea’s Goals In order of priority: Boolean operators Evaluating sources Library catalog, not journals After-hours help Instruction Librarian Goals In order of priority: Boolean operators Evaluating sources Library catalog, not journals After-hours help EVERYONE: Completion rates!

26 Library Statistics Jacob Ellis

27 RCCC LRC Statistics Background Start of Data Collection- July 2015 Early data collection relied on door counts, other static methods Data was spread out across different platforms, decentralized Later data collection utilized Google Forms, more centralized August 2015- Present Forms created in LibInsight Data entered goes directly into LibInsight Data can be manipulated, sets customized Data is exported and centralized on dedicated LibGuide

28 Gathering Statistics- Parameters Foot Traffic Walk through conducted hourly by Circulation staff Links to forms are saved on iPad Reference Data is entered as soon as reference transaction is completed Instruction Data is entered as soon as instruction session has concluded

29 RCCC LRC North Campus- Floorplan

30 Foot Traffic Form (Green Area)

31 Reference Form (Red Area)

32 Instruction Form (Blue Area)

33 RCCC LRC Statistics LibGuide Data is analyzed monthly and added to dedicated Statistics LibGuide Data is viewed by Director, Coordinators as needed; SACS, qualitatively demonstrate LRC abilities and services at college level, space management, resource allocation, staff scheduling, operating hours Look at current and historical data we’ve gathered: http://libguides.rccc.edu/lrcstats

34 Discussion Andrea Kincaid: andrea.kincaid@rccc.edu Jake Ellis: jmellis@waketech.edu


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