IDEAS home Printed from https://ideas.repec.org/a/eee/epplan/v66y2018icp183-194.html
   My bibliography  Save this article

Towards program theory validation: Crowdsourcing the qualitative analysis of participant experiences

Author

Listed:
  • Harman, Elena
  • Azzam, Tarek

Abstract

This exploratory study examines a novel tool for validating program theory through crowdsourced qualitative analysis. It combines a quantitative pattern matching framework traditionally used in theory-driven evaluation with crowdsourcing to analyze qualitative interview data. A sample of crowdsourced participants are asked to read an interview transcript and identify whether program theory components (Activities and Outcomes) are discussed and to highlight the most relevant passage about that component. The findings indicate that using crowdsourcing to analyze qualitative data can differentiate between program theory components that are supported by a participant’s experience and those that are not. This approach expands the range of tools available to validate program theory using qualitative data, thus strengthening the theory-driven approach.

Suggested Citation

  • Harman, Elena & Azzam, Tarek, 2018. "Towards program theory validation: Crowdsourcing the qualitative analysis of participant experiences," Evaluation and Program Planning, Elsevier, vol. 66(C), pages 183-194.
    • Handle: RePEc:eee:epplan:v:66:y:2018:i:c:p:183-194
    DOI: 10.1016/j.evalprogplan.2017.08.008
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0149718917301970
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.evalprogplan.2017.08.008?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Costner, Herbert L., 1989. "The validity of conclusions in evaluation research: A further development of Chen and Rossi's theory-driven approach," Evaluation and Program Planning, Elsevier, vol. 12(4), pages 345-353, January.
    2. Chen, Huey-Tsyh & Rossi, Peter H., 1989. "Issues in the theory-driven perspective," Evaluation and Program Planning, Elsevier, vol. 12(4), pages 299-306, January.
    3. Carol H. Weiss, 1997. "How Can Theory-Based Evaluation Make Greater Headway?," Evaluation Review, , vol. 21(4), pages 501-524, August.
    4. Chen, Huey-Tsyh & Rossi, Peter H., 1987. "The theory-driven approach to validity," Evaluation and Program Planning, Elsevier, vol. 10(1), pages 95-103, January.
    5. repec:cup:judgdm:v:5:y:2010:i:5:p:411-419 is not listed on IDEAS
    6. Deane, Kelsey L. & Harré, Niki, 2014. "Program theory-driven evaluation science in a youth development context," Evaluation and Program Planning, Elsevier, vol. 45(C), pages 61-70.
    7. Bickman, Leonard, 1989. "Barriers to the use of program theory," Evaluation and Program Planning, Elsevier, vol. 12(4), pages 387-390, January.
    8. Brousselle, Astrid & Champagne, François, 2011. "Program theory evaluation: Logic analysis," Evaluation and Program Planning, Elsevier, vol. 34(1), pages 69-78, February.
    9. Azzam, Tarek & Harman, Elena, 2016. "Crowdsourcing for quantifying transcripts: An exploratory study," Evaluation and Program Planning, Elsevier, vol. 54(C), pages 63-73.
    10. Berinsky, Adam J. & Huber, Gregory A. & Lenz, Gabriel S., 2012. "Evaluating Online Labor Markets for Experimental Research: Amazon.com's Mechanical Turk," Political Analysis, Cambridge University Press, vol. 20(3), pages 351-368, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Park, Chul Hyun & Welch, Eric W. & Sriraj, P.S., 2016. "An integrative theory-driven framework for evaluating travel training programs," Evaluation and Program Planning, Elsevier, vol. 59(C), pages 7-20.
    2. Benson, Paul R. & Fisher, Gene A. & Diana, Augusto & Simon, Lorna & Gamache, Gail & Tessler, Richard C. & McDermeit, Melissa, 1996. "A state network of family support services: The massachusetts family support demonstration project," Evaluation and Program Planning, Elsevier, vol. 19(1), pages 27-39, February.
    3. Kent, Douglas R. & Donaldson, Stewart I. & Wyrick, Phelan A. & Smith, Peggy J., 2000. "Evaluating criminal justice programs designed to reduce crime by targeting repeat gang offenders," Evaluation and Program Planning, Elsevier, vol. 23(1), pages 115-124, February.
    4. Harman, Elena & Azzam, Tarek, 2018. "Incorporating public values into evaluative criteria: Using crowdsourcing to identify criteria and standards," Evaluation and Program Planning, Elsevier, vol. 71(C), pages 68-82.
    5. Pan, Jing Yu & Liu, Dahai, 2022. "Mask-wearing intentions on airplanes during COVID-19 – Application of theory of planned behavior model," Transport Policy, Elsevier, vol. 119(C), pages 32-44.
    6. Michele Cantarella & Chiara Strozzi, 2021. "Workers in the crowd: the labor market impact of the online platform economy [An evaluation of instrumental variable strategies for estimating the effects of catholic schooling]," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 30(6), pages 1429-1458.
    7. Robbett, Andrea & Matthews, Peter Hans, 2018. "Partisan bias and expressive voting," Journal of Public Economics, Elsevier, vol. 157(C), pages 107-120.
    8. von dem Knesebeck, Olaf & Joksimovic, Ljiljana & Badura, Bernhard & Siegrist, Johannes, 2002. "Evaluation of a community-level health policy intervention," Health Policy, Elsevier, vol. 61(1), pages 111-122, July.
    9. Park, JungKun & Ahn, Jiseon & Thavisay, Toulany & Ren, Tianbao, 2019. "Examining the role of anxiety and social influence in multi-benefits of mobile payment service," Journal of Retailing and Consumer Services, Elsevier, vol. 47(C), pages 140-149.
    10. Chunhao Wei & Han Chen & Yee Ming Lee, 2022. "COVID-19 preventive measures and restaurant customers’ intention to dine out: the role of brand trust and perceived risk," Service Business, Springer;Pan-Pacific Business Association, vol. 16(3), pages 581-600, September.
    11. Masha Shunko & Julie Niederhoff & Yaroslav Rosokha, 2018. "Humans Are Not Machines: The Behavioral Impact of Queueing Design on Service Time," Management Science, INFORMS, vol. 64(1), pages 453-473, January.
    12. Tim Benijts, 2014. "A Business Sustainability Model for Government Corporations. A Belgian Case Study," Business Strategy and the Environment, Wiley Blackwell, vol. 23(3), pages 204-216, March.
    13. Brodeur, Abel & Cook, Nikolai & Heyes, Anthony, 2022. "We Need to Talk about Mechanical Turk: What 22,989 Hypothesis Tests Tell Us about Publication Bias and p-Hacking in Online Experiments," IZA Discussion Papers 15478, Institute of Labor Economics (IZA).
    14. Harris, Kevin & Adams, Andrew, 2016. "Power and discourse in the politics of evidence in sport for development," Sport Management Review, Elsevier, vol. 19(2), pages 97-106.
    15. Lude, Maximilian & Prügl, Reinhard, 2021. "Experimental studies in family business research," Journal of Family Business Strategy, Elsevier, vol. 12(1).
    16. Mattozzi, Andrea & Snowberg, Erik, 2018. "The right type of legislator: A theory of taxation and representation," Journal of Public Economics, Elsevier, vol. 159(C), pages 54-65.
    17. Jasper Grashuis & Theodoros Skevas & Michelle S. Segovia, 2020. "Grocery Shopping Preferences during the COVID-19 Pandemic," Sustainability, MDPI, vol. 12(13), pages 1-10, July.
    18. Jeanette A.M.J. Deetlefs & Mathew Chylinski & Andreas Ortmann, 2015. "MTurk ‘Unscrubbed’: Exploring the good, the ‘Super’, and the unreliable on Amazon’s Mechanical Turk," Discussion Papers 2015-20, School of Economics, The University of New South Wales.
    19. Torvatn, Hans, 1999. "Using program theory models in evaluation of industrial modernization programs: three case studies," Evaluation and Program Planning, Elsevier, vol. 22(1), pages 73-82.
    20. Jun Zhang & Joon Soo Lim, 2021. "Mitigating negative spillover effects in a product-harm crisis: strategies for market leaders versus market challengers," Journal of Brand Management, Palgrave Macmillan, vol. 28(1), pages 77-98, January.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:epplan:v:66:y:2018:i:c:p:183-194. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/evalprogplan .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.