IDEAS home Printed from https://ideas.repec.org/a/ibf/beaccr/v4y2012i2p113-124.html
   My bibliography  Save this article

An Architecture For Dynamic E-Learning Environments Based On Student Activity And Learning Styles

Author

Listed:
  • John A. Kaliski
  • Queen E. Booker
  • Paul L. Schumann

Abstract

Using e-learning systems, computer assisted technologies, or learning management systems to supplement or replace the classroom experience is becoming more common in education. The use of these technologies generates a large volume of transactional data that record how each student progressed through the learning materials in the e-learning system. This data, which is currently underutilized, could be used to understand student learning behaviors, and to help both the instructor and the student benefit more from the course content. This paper describes an architecture using business intelligence methodology for using the data captured by e-learning systems to understand what students are doing (or not doing) in the e-learning system, and thereby to make changes that enhance student learning.

Suggested Citation

  • John A. Kaliski & Queen E. Booker & Paul L. Schumann, 2012. "An Architecture For Dynamic E-Learning Environments Based On Student Activity And Learning Styles," Business Education and Accreditation, The Institute for Business and Finance Research, vol. 4(2), pages 113-124.
  • Handle: RePEc:ibf:beaccr:v:4:y:2012:i:2:p:113-124
    as

    Download full text from publisher

    File URL: http://www.theibfr2.com/RePEc/ibf/beaccr/bea-v4n2-2012/BEA-V4N2-2012-10.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Henri Barki & Ryad Titah & Céline Boffo, 2007. "Information system use-related activity : An expanded behavioral conceptualization of individual-level information system use," Post-Print hal-02311855, HAL.
    2. Ryad Titah & Henri Barki & Céline Boffo, 2007. "Information system use-related activity : An expanded behavioral conceptualization of individual-level information system use," Post-Print hal-02312468, HAL.
    3. Henri Barki & Ryad Titah & Céline Boffo, 2007. "Information System Use--Related Activity: An Expanded Behavioral Conceptualization of Individual-Level Information System Use," Information Systems Research, INFORMS, vol. 18(2), pages 173-192, June.
    4. Margherita Pagani, 2006. "Determinants of adoption of High Speed Data Services in the business market : Evidence for a combined technology acceptance model with task technology fit model," Post-Print hal-02313097, HAL.
    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. Kwan Soo Hong & DonHee Lee, 2018. "Impact of operational innovations on customer loyalty in the healthcare sector," Service Business, Springer;Pan-Pacific Business Association, vol. 12(3), pages 575-600, September.
    2. Yu Tong & Sharon Swee-Lin Tan & Hock-Hai Teo, 2015. "The Road to Early Success: Impact of System Use in the Swift Response Phase," Information Systems Research, INFORMS, vol. 26(2), pages 418-436, June.
    3. Jean-Charles Pillet & Kevin Carillo & Claudio Vitari & Federico Pigni, 2020. "What Does It Do? Theorizing Functional Ambiguity As A Factor Influencing User Perceptions Of Information Technology," Post-Print hal-03026903, HAL.
    4. John D'Ambra & Concepción S. Wilson & Shahriar Akter, 2013. "Application of the task-technology fit model to structure and evaluate the adoption of E-books by Academics," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 64(1), pages 48-64, January.
    5. Jani Merikivi & Antti Salovaara & Matti Mäntymäki & Lilong Zhang, 2018. "On the way to understanding binge watching behavior: the over-estimated role of involvement," Electronic Markets, Springer;IIM University of St. Gallen, vol. 28(1), pages 111-122, February.
    6. Suoniemi, Samppa & Terho, Harri & Zablah, Alex & Olkkonen, Rami & Straub, Detmar W., 2021. "The impact of firm-level and project-level it capabilities on CRM system quality and organizational productivity," Journal of Business Research, Elsevier, vol. 127(C), pages 108-122.
    7. Ann-Frances Cameron & Jane Webster, 2013. "Multicommunicating: Juggling Multiple Conversations in the Workplace," Information Systems Research, INFORMS, vol. 24(2), pages 352-371, June.
    8. Do Giang Nguyen & Minh-Tri Ha, 2022. "What Makes Users Continue to Want to Use the Digital Platform? Evidence From the Ride-Hailing Service Platform in Vietnam," SAGE Open, , vol. 12(1), pages 21582440211, January.
    9. Jean-Charles Pillet & Kevin Carillo & Claudio Vitari & Federico Pigni, 2020. "What Does It Do? Theorizing Functional Ambiguity As A Factor Influencing User Perceptions Of Information Technology," Grenoble Ecole de Management (Post-Print) hal-03026903, HAL.
    10. Hilal Atasoy & Rajiv D. Banker & Paul A. Pavlou, 2021. "Information Technology Skills and Labor Market Outcomes for Workers," Information Systems Research, INFORMS, vol. 32(2), pages 437-461, June.
    11. Sun, Jonghak & Teng, James T.C., 2017. "The construct of information systems use benefits: Theoretical explication of its underlying dimensions and the development of a measurement scale," International Journal of Information Management, Elsevier, vol. 37(5), pages 400-416.
    12. Sven Dittes & Stefan Smolnik, 2019. "Towards a digital work environment: the influence of collaboration and networking on employee performance within an enterprise social media platform," Journal of Business Economics, Springer, vol. 89(8), pages 1215-1243, December.
    13. Kwahk, Kee-Young & Ahn, Hyunchul & Ryu, Young U., 2018. "Understanding mandatory IS use behavior: How outcome expectations affect conative IS use," International Journal of Information Management, Elsevier, vol. 38(1), pages 64-76.
    14. Shaw, Norman, 2014. "The role of the professional association: A grounded theory study of Electronic Medical Records usage in Ontario, Canada," International Journal of Information Management, Elsevier, vol. 34(2), pages 200-209.
    15. Efpraxia D. Zamani & Nancy Pouloudi & George M. Giaglis & Jonathan Wareham, 2022. "Appropriating Information Technology Artefacts through Trial and Error: The Case of the Tablet," Information Systems Frontiers, Springer, vol. 24(1), pages 97-119, February.
    16. Bogicevic, Vanja & Bujisic, Milos & Bilgihan, Anil & Yang, Wan & Cobanoglu, Cihan, 2017. "The impact of traveler-focused airport technology on traveler satisfaction," Technological Forecasting and Social Change, Elsevier, vol. 123(C), pages 351-361.
    17. Hillol Bala & Viswanath Venkatesh, 2016. "Adaptation to Information Technology: A Holistic Nomological Network from Implementation to Job Outcomes," Management Science, INFORMS, vol. 62(1), pages 156-179, January.
    18. Andrew Burton-Jones & Camille Grange, 2013. "From Use to Effective Use: A Representation Theory Perspective," Information Systems Research, INFORMS, vol. 24(3), pages 632-658, September.
    19. Andrew Burton-Jones & Olga Volkoff, 2017. "How Can We Develop Contextualized Theories of Effective Use? A Demonstration in the Context of Community-Care Electronic Health Records," Information Systems Research, INFORMS, vol. 28(3), pages 468-489, September.
    20. Hilal Atasoy & Rajiv D. Banker & Paul A. Pavlou, 2016. "On the Longitudinal Effects of IT Use on Firm-Level Employment," Information Systems Research, INFORMS, vol. 27(1), pages 6-26, March.

    More about this item

    Keywords

    E-learning; Learning Management Systems; Business Intelligence; Business Education; Business Education Research;
    All these keywords.

    JEL classification:

    • C88 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other Computer Software
    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • M00 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - General - - - General
    • M19 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - Other
    • Z00 - Other Special Topics - - General - - - General

    Statistics

    Access and download statistics

    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:ibf:beaccr:v:4:y:2012:i:2:p:113-124. 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: Mercedes Jalbert (email available below). General contact details of provider: .

    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.