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Libros sobre el tema "Online Ratings"

Autor: Grafiati
Publicado: 1 de agosto de 2021
Última modificación: 25 de enero de 2023

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1

Leong, Pamela. Rating Professors Online. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-35936-2.

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2

Palloff, Rena M. Assessing the Online Learner. New York: John Wiley & Sons, Ltd., 2008.

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3

1957-, Morgan Chris, ed. The student assessment handbook: New directions in traditional and online assessment. New York: RoutledgeFalmer, 2003.

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4

Heckner, Markus. Tagging, rating, posting: Studying forms of user contribution for web-based information management and information retrieval. Boizenburg: VWH, Verlag Werner Hülsbusch, 2009.

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5

1947-, Pratt Keith, ed. Assessing the online learner: Resources and strategies for faculty. San Francisco: Jossey-Bass, 2009.

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6

Online student ratings of instruction. San Francisco, Calif: Jossey-Bass Publishers, 2003.

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7

Sorenson, D. Lynn y Trav D. Johnson. Online Student Ratings of Instruction. Wiley & Sons, Incorporated, John, 2011.

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8

Manipurated: How business owners can fight fraudulent online ratings and reviews. 2015.

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9

Sorenson, D. Lynn y Trav D. Johnson. Online Student Ratings of Instruction: New Directions for Teaching and Learning, Number 96. Wiley & Sons, Incorporated, John, 2011.

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10

Sorenson, D. Lynn y Trav D. Johnson. Online Student Ratings of Instruction: New Directions for Teaching and Learning, Number 96. Wiley & Sons, Incorporated, John, 2011.

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11

Cooperman, Tod y Gabriel Levitt. Pharmacychecker.com's Guide To Low-cost Canadian & U.S. Pharmacies: Ratings And Profiles Of 42 Popular Mail-order And Online Pharmacies. Consumerlab.Com, 2004.

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12

(Editor), D. Lynn Sorenson y Trav D. Johnson (Editor), eds. Online Student Ratings of Instruction: New Directions for Teaching and Learning (J-B TL Single Issue Teaching and Learning). Jossey-Bass, 2004.

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13

Aminian, Ali. Online Preoperative Risk Assessment Tools. Editado por Tomasz Rogula, Philip Schauer y Tammy Fouse. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780190608347.003.0006.

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Despite the presence of robust data on safety and efficacy of bariatric and metabolic surgery, many patients and physicians do not consider surgery to treat obesity, diabetes, and metabolic syndrome. One reason may be inaccurate beliefs about the risk-benefit ratios of medical and surgical treatments of obesity. Estimating the risk of postoperative complications can improve surgical decision-making and informed patient consent. Furthermore, there would be a considerable benefit in identifying modifiable preoperative conditions that are associated with increased risk of postoperative adverse events. The methodology and characteristics of online risk assessment tools in bariatric surgery are presented in this chapter.
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14

Tesch, Tabea. Online Produkttests Zur Generierung Von Online Reviews: Eine Analyse der Effekte Auf das Review Rating und Die Review Qualität. Springer Fachmedien Wiesbaden GmbH, 2022.

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15

Leong, Pamela. Rating Professors Online: How Culture, Technology, and Consumer Expectations Shape Modern Student Evaluations. Palgrave Macmillan, 2020.

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16

Leong, Pamela. Rating Professors Online: How Culture, Technology, and Consumer Expectations Shape Modern Student Evaluations. Springer International Publishing AG, 2021.

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17

Brown, Michael A. Social Media Performance Evaluation and Success Measurements. IGI Global, 2017.

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18

Online Assessment and Measurement: Case Studies from Higher Education, K-12, and Corporate. Information Science Publishing, 2006.

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19

Walden, Randy. Learn How To Manage and Market Your Business Online Reputation: Star Rating is the #1 Factor Used By Consumers to Judge a Business. CreateSpace Independent Publishing Platform, 2015.

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20

Almanac of Business and Industrial Financial Ratios 2000. Prentice Hall Trade, 2000.

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21

Mooshammer, Sandra. He, she, it - Vertrauen muss mit? : Auswirkungen geschlechtsneutraler Stimmen in Sprachassistenten auf ihre Vertrauenswürdigkeit. Technische Universität Dresden, 2021. http://dx.doi.org/10.25368/2022.414.

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Almost 70 % of the currently existing language assistance systems only use female voices. Assistants with male voices or with the option to choose between different options, on the other hand, are clearly in the minority. Technologies that emit social cues are treated like social actors in accordance with the CASA paradigm. As a result, stereotypes, for example, can be applied to voice assistants who indicate a specific gender - an effect that has already been observed in various research. With the development of the gender-neutral voice Q through a merger of Danish companies and organizations, the question arose in 2019 whether this would avoid the use of stereotypes or, on the contrary, neutral voices are perceived as unpleasant. This was considered in the master's thesis with regard to trust in a language assistance system. For this purpose, a gender-neutral voice was developed and compared in an online experiment with a male and a female voice that spoke about a stereotypically male, a stereotypically female or a neutral topic. It was found that the neutral voice was assigned a lower level of trustworthiness in some variables - even if it was perceived as male or female. The gender assignment, in turn, was dependent on which gender the test subjects assigned the topic about which the voice was speaking. The results suggest that the ambiguity and unfamiliarity of the neutral voice leads to a poorer rating. It must therefore be doubted that such projects can lead to a broad-based overcoming of stereotypes, but on the contrary even bring about and consolidate negative reactions to entities that do not correspond to the gender norm.
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