This presentation was provided by Vincent Cassidy of The IET during the NISO event "Researcher Behaviors and the Impact of Technology," held on March 25, 2020.
This presentation was provided by Bert Carelli of TrendMD, during the NISO event "Researcher Behaviors and the Impact of Technology," held on March 25, 2020.
This presentation was provided by Stephanie Roth of Temple University, during the NISO event "Researcher Behaviors and the Impact of Technology," held on March 25, 2020.
Assessing Students' Information Literacy Skills Using MAP-WorksMillstein Library
Poster presented for the Association of College & Research Libraries (ACRL) Assessment in Action (AiA) program at the American Library Association (ALA) Annual Conference on Friday, June 24, 2016 in Orlando, FL
Quick reference cards for research impact metricsLibrary_Connect
When meeting with students, researchers, deans or department heads, the metrics on these quick reference cards can serve as a jumping off point in conversations about where to publish, adding to researcher profiles, enriching promotion and tenure files, and benchmarking research outputs. The cards were co-developed by librarian Jenny Delasalle and Elsevier's Library Connect program. Learn more and download poster versions as well at: https://libraryconnect.elsevier.com/articles/librarian-quick-reference-cards-research-impact-metrics
This presentation was provided by Vincent Cassidy of The IET during the NISO event "Researcher Behaviors and the Impact of Technology," held on March 25, 2020.
This presentation was provided by Bert Carelli of TrendMD, during the NISO event "Researcher Behaviors and the Impact of Technology," held on March 25, 2020.
This presentation was provided by Stephanie Roth of Temple University, during the NISO event "Researcher Behaviors and the Impact of Technology," held on March 25, 2020.
Assessing Students' Information Literacy Skills Using MAP-WorksMillstein Library
Poster presented for the Association of College & Research Libraries (ACRL) Assessment in Action (AiA) program at the American Library Association (ALA) Annual Conference on Friday, June 24, 2016 in Orlando, FL
Quick reference cards for research impact metricsLibrary_Connect
When meeting with students, researchers, deans or department heads, the metrics on these quick reference cards can serve as a jumping off point in conversations about where to publish, adding to researcher profiles, enriching promotion and tenure files, and benchmarking research outputs. The cards were co-developed by librarian Jenny Delasalle and Elsevier's Library Connect program. Learn more and download poster versions as well at: https://libraryconnect.elsevier.com/articles/librarian-quick-reference-cards-research-impact-metrics
June 18, 2014
NISO Virtual Conference: Transforming Assessment: Alternative Metrics and Other Trends
Snowball Metrics: University-owned Benchmarking to Reveal Strengths within All Activities
- Dr. Lisa Colledge, Snowball Metrics Program Director, Elsevier
This presentation was provided by Nicole Johnson of bePress during the NISO webinar, Enabling Discovery & Retrieval of Non-Traditional and Granular Content, held on June 7, 2017.
Library Services Benchmarks - Using Corporate Library Services in PharmaBest Practices
Libraries are custodians of invaluable information. The study - Library Services Benchmarks 2016: Corporate Library Services in the Pharmaceutical Industry published by Best Practices, LLC examines the trends and staffing benchmarks such as library staff per potential and actual users across companies providing access to library services across the bio-pharmaceutical space.
This study looks into staff with formal education level and the number of staff inside and outside the library who provide library services. This study can be used by bio-pharmaceutical companies to improve upon existing library services and staffing.
Download Full Report: http://bit.ly/29QZcbM
CHiR presentation measuring scholarly and public impactPlethora121
American University Library's Conference for High Impact Research presentation, Measuring Scholarly and Public Impact. Given May 15th, 2017, discusses bibliometrics and altmetrics, focusing on case uses, current trends, and disciplinary considerations.
June 18, 2014
NISO Virtual Conference: Transforming Assessment: Alternative Metrics and Other Trends
Snowball Metrics: University-owned Benchmarking to Reveal Strengths within All Activities
- Dr. Lisa Colledge, Snowball Metrics Program Director, Elsevier
This presentation was provided by Nicole Johnson of bePress during the NISO webinar, Enabling Discovery & Retrieval of Non-Traditional and Granular Content, held on June 7, 2017.
Library Services Benchmarks - Using Corporate Library Services in PharmaBest Practices
Libraries are custodians of invaluable information. The study - Library Services Benchmarks 2016: Corporate Library Services in the Pharmaceutical Industry published by Best Practices, LLC examines the trends and staffing benchmarks such as library staff per potential and actual users across companies providing access to library services across the bio-pharmaceutical space.
This study looks into staff with formal education level and the number of staff inside and outside the library who provide library services. This study can be used by bio-pharmaceutical companies to improve upon existing library services and staffing.
Download Full Report: http://bit.ly/29QZcbM
CHiR presentation measuring scholarly and public impactPlethora121
American University Library's Conference for High Impact Research presentation, Measuring Scholarly and Public Impact. Given May 15th, 2017, discusses bibliometrics and altmetrics, focusing on case uses, current trends, and disciplinary considerations.
Complete the following assignments using excel and the following tLynellBull52
Complete the following assignments using excel and the following template:
· Assignment – Statement
· Identify Business Problem -
“Define Problem statement [aka Case Analysis Assignment]”
· Analytics Tools and Models used and results
· Interpretation, Discussion, and Analysis of Findings and Results –
Interpretation, Discussion, and Analysis of outcomes and results of Analytics Tools and Models used
· Tip: Support your Interpretation, Discussion, and Analysis of Results with the numbers you developed in your:
· Analytics Tools and Models used results
· Business Analytics Case Analysis EXCEL model(s) and outcomes and results
· Recommendations
Assignment information:
The worksheet Purchasing Survey in the Performance Lawn Care database provides data related to predicting the level of business (Usage Level) obtained from a third-party survey of purchasing managers of customers Performance Lawn Care.
The seven PLE attributes rated by each respondent are
8 The data and description of this case are based on the HATCO example on pages 28–29 in Joseph F. Hair, Jr., Rolph E. Anderson, Ronald L. Tatham, and William C. Black, Multivariate Analysis, 5th ed. (Upper Saddle River, NJ: Prentice Hall, 1998).
· Delivery speed —the amount of time it takes to deliver the product once an order is confirmed
· Price level —the perceived level of price charged by PLE
· Price flexibility —the perceived willingness of PLE representatives to negotiate price on all types of purchases
· Manufacturing image —the overall image of the manufacturer
· Overall service —the overall level of service necessary for maintaining a satisfactory relationship between PLE and the purchaser
· Sales force image —the overall image of the PLE’s sales force
· Product quality —perceived level of quality
Responses to these seven variables were obtained using a graphic rating scale, where a 10-centimeter line was drawn between endpoints labeled “poor” and “excellent.” Respondents indicated their perceptions using a mark on the line, which was measured from the left endpoint. The result was a scale from 0 to 10 rounded to one decimal place.
Two measures were obtained that reflected the outcomes of the respondent’s purchase relationships with PLE:
· Usage level —how much of the firm’s total product is purchased from PLE, measured on a 100-point scale, ranging from 0% to 100%
· Satisfaction level —how satisfied the purchaser is with past purchases from PLE, measured on the same graphic rating scale as perceptions 1 through 7
The data also include four characteristics of the responding firms:
· Size of firm —size relative to others in this market (0=small;1=large)(0=small;1=large)
· Purchasing structure —the purchasing method used in a particular company (1=centralized procurement,0=dec ...
Education plays a vital role in nation’s overall development process. To be effective, analysis must be timely and cope with data scales. The scale of the data and the rates at which they arrive make manual inspection infeasible. Predictive analytics can help and improve the quality of education by analyzing the historical data of the student and allow the decision makers address factors such as increased drop-out rate, fees structure in the upcoming years, unemployment, Recommender Systems for Professional Development and curriculum Development. This paper presents an analytical study of student progress report and help to plan accordingly to achieve success.