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Knowledgebase Effectiveness

Knowledgebase Effectiveness. Luis Calahorrano EDU671: Fundamentals of Educational Research Instructor Frederick Ansoff August 25 , 2014. Area of Focus. Measure effectiveness of online knowledgebase to teach/learn . Improve the quality and amount of information

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Knowledgebase Effectiveness

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  1. Knowledgebase Effectiveness Luis CalahorranoEDU671: Fundamentals of Educational ResearchInstructor Frederick AnsoffAugust 25, 2014

  2. Area of Focus • Measure effectiveness of online knowledgebase to teach/learn. • Improve the quality and amount of information • To teach new routines for employees (Professional Development) • Centralize information, making it more accessible

  3. Explanation of Problem • Difficult to locate documentation to answer questions • Existing documentation is not updated or clearly understood. • Information is there but is not complete. • Continuous article creation needed • Lack of resource or time • Information is not centralized

  4. Variables • Undergraduate and graduate admissions officers. • The support department is composed of 6 participants. • The manager of support

  5. Research Questions • What is the customer support perspective in the current quality of the company online knowledgebase? • Does improved models of knowledgebase articles increase the quality of teaching and learning? • What makes a good knowledgebase article? What should a knowledgebase article do?

  6. Locus of Control Select which clients would be considered to be participants. Pick organizations that have been with the company for many years. Filter newer clients who are currently in implementation phases. Control which articles are reviewed in study.

  7. Intervention/Innovation Online knowledgebase to meet the needs of its learners. Instill new routines to develop high quality documentation Increase awareness in importance of documentation Measurable actions to continually measure effectiveness

  8. Steps of Intervention • Determine weak articles in knowledgebase. • Determine participants suggestions for improvement. • Create improved model of knowledgebase article. • Re-assess the effectiveness by performing a post survey. • Compare survey data to analyze effectiveness of article improvement. • Introduce improved model and continual testing • Instill information across company

  9. Group Membership Provide feedback based on admissions user needs. Support members help identify ideal client participants. Admissions participants provide feedback on company knowledgebase. Rate knowledgebase articles in our company.

  10. Negotiations • Obstacles may include limited amount of knowledge. • Limited experience in utilizing knowledgebase's. • Time schedules may be another hindering factor.

  11. Ethical Concerns • Ethical concerns include confidentiality. • Sharing results to compromise job security. • Revealing internal processes. • Sharing student data. • Consent forms

  12. Timeline • Overall timeline will take 3-4 weeks for initial research • First week to gather preliminary data • Second week to analyze and perform intervention • Third week to perform interviews • Fourth week to analyze data and propose solution • Additional time needed for continual improvement

  13. Statement of Resources Online questionnaire and measurement system Consent and confidentiality forms Literature references and reviews Cloud technology Labor

  14. Data Collection Obtained through online survey system SurveyMonkey. (Quantitative Data) Data collected based on in-person interviews. (Qualitative Data) Data reflects multiple perspectives.

  15. Measuring Data with Research Questions • Would improved quality of the current knowledgebase make learning better? • Should articles be easy to understand? • Please rate the media below in which you believe a knowledgebase article should have in order to ensure learning:

  16. References Mills, G. E. (2014). Action research: A guide for the teacher researcher (5th ed.). Upper Saddle River, N.J: Merrill. Carlo, J., Lyytinen, K., & Rose, G. M. (2012). A KNOWLEDGE-BASED MODEL OF RADICAL INNOVATION IN SMALL SOFTWARE FIRMS. MIS Quarterly, 36(3), 865-A10. Nonaka, I. (1991). The knowledge-creating company. Harvard business review,69(6), 96-104. Craven, M., DiPasquo, D., Freitag, D., McCallum, A., Mitchell, T., Nigam, K., & Slattery, S. (2000). Learning to construct knowledge bases from the World Wide Web. Artificial intelligence, 118(1), 69-113. TargetX | CRM for Higher Education. (2014). Retrieved from http://targetx.com

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