IDEAS home Printed from https://ideas.repec.org/a/gam/jdataj/v6y2021i7p74-d591808.html
   My bibliography  Save this article

Performing Learning Analytics via Generalised Mixed-Effects Trees

Author

Listed:
  • Luca Fontana

    (MOX— Laboratory for Modeling and Scientific Computing, Department of Mathematics, The Polytechnic University of Milan, 20133 Milan, Italy)

  • Chiara Masci

    (MOX— Laboratory for Modeling and Scientific Computing, Department of Mathematics, The Polytechnic University of Milan, 20133 Milan, Italy)

  • Francesca Ieva

    (MOX— Laboratory for Modeling and Scientific Computing, Department of Mathematics, The Polytechnic University of Milan, 20133 Milan, Italy)

  • Anna Maria Paganoni

    (MOX— Laboratory for Modeling and Scientific Computing, Department of Mathematics, The Polytechnic University of Milan, 20133 Milan, Italy)

Abstract

Nowadays, the importance of educational data mining and learning analytics in higher education institutions is being recognised. The analysis of university careers and of student dropout prediction is one of the most studied topics in the area of learning analytics. From the perspective of estimating the likelihood of a student dropping out, we propose an innovative statistical method that is a generalisation of mixed-effects trees for a response variable in the exponential family: generalised mixed-effects trees (GMET). We performed a simulation study in order to validate the performance of our proposed method and to compare GMET to classical models. In the case study, we applied GMET to model undergraduate student dropout in different courses at Politecnico di Milano. The model was able to identify discriminating student characteristics and estimate the effect of each degree-based course on the probability of student dropout.

Suggested Citation

  • Luca Fontana & Chiara Masci & Francesca Ieva & Anna Maria Paganoni, 2021. "Performing Learning Analytics via Generalised Mixed-Effects Trees," Data, MDPI, vol. 6(7), pages 1-31, July.
    • Handle: RePEc:gam:jdataj:v:6:y:2021:i:7:p:74-:d:591808
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2306-5729/6/7/74/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2306-5729/6/7/74/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hajjem, Ahlem & Larocque, Denis & Bellavance, François, 2017. "Generalized mixed effects regression trees," Statistics & Probability Letters, Elsevier, vol. 126(C), pages 114-118.
    2. W. J. Browne & S. V. Subramanian & K. Jones & H. Goldstein, 2005. "Variance partitioning in multilevel logistic models that exhibit overdispersion," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 168(3), pages 599-613, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Buczak, Philip, 2024. "Mixed-Effects Frequency-Adjusted Borders Ordinal Forest: A Tree Ensemble Method for Ordinal Prediction with Hierarchical Data," OSF Preprints ny6we, Center for Open Science.

    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. Elias Giannakis & Sophia Efstratoglou & Artemis Antoniades, 2018. "Off-Farm Employment and Economic Crisis: Evidence from Cyprus," Agriculture, MDPI, vol. 8(3), pages 1-11, March.
    2. Anoop Jain & Lia C.H. Fernald & Kirk R. Smith & S.V. Subramanian, 2019. "Sanitation in Rural India: Exploring the Associations between Dwelling Space and Household Latrine Ownership," IJERPH, MDPI, vol. 16(5), pages 1-14, February.
    3. M. Lippi Bruni & L. Nobilio & C. Ugolini, 2007. "Economic Incentives in General Practice: the Impact of Pay for Participation Programs on Diabetes Care," Working Papers 607, Dipartimento Scienze Economiche, Universita' di Bologna.
    4. Sanjay K. Mohanty & Guru Vasishtha, 2021. "Contextualizing multidimensional poverty in urban India," Poverty & Public Policy, John Wiley & Sons, vol. 13(3), pages 234-253, September.
    5. Merlo, Juan & Ohlsson, Henrik & Chaix, Basile & Lichtenstein, Paul & Kawachi, Ichiro & Subramanian, S.V., 2013. "Revisiting causal neighborhood effects on individual ischemic heart disease risk: A quasi-experimental multilevel analysis among Swedish siblings," Social Science & Medicine, Elsevier, vol. 76(C), pages 39-46.
    6. Schnepf, Sylke V. & Durrant, Gabriele B. & Micklewright, John, 2014. "Which Schools and Pupils Respond to Educational Achievement Surveys? A Focus on the English PISA Sample," IZA Discussion Papers 8411, Institute of Labor Economics (IZA).
    7. Parish, Susan L. & Rose, Roderick A. & Andrews, Megan E. & Shattuck, Paul T., 2009. "Receipt of professional care coordination among families raising children with special health care needs: A multilevel analysis of state policy needs," Children and Youth Services Review, Elsevier, vol. 31(1), pages 63-70, January.
    8. Anh Thu Quang Pham & Pundarik Mukhopadhaya & Ha Vu, 2020. "Targeting Administrative Regions for Multidimensional Poverty Alleviation: A Study on Vietnam," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 150(1), pages 143-189, July.
    9. Merlo, Juan & Viciana-Fernández, Francisco J. & Ramiro-Fariñas, Diego, 2012. "Bringing the individual back to small-area variation studies: A multilevel analysis of all-cause mortality in Andalusia, Spain," Social Science & Medicine, Elsevier, vol. 75(8), pages 1477-1487.
    10. William J. Browne, 2022. "A celebration of Harvey Goldstein’s lifetime contributions: Memories of working with Harvey Goldstein on multilevel modelling methods and applications," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(3), pages 753-758, July.
    11. Lippi Bruni, Matteo & Nobilio, Lucia & Ugolini, Cristina, 2009. "Economic incentives in general practice: The impact of pay-for-participation and pay-for-compliance programs on diabetes care," Health Policy, Elsevier, vol. 90(2-3), pages 140-148, May.
    12. Scribner, Richard Allen & Theall, Katherine P. & Simonsen, Neal R. & Mason, Karen E. & Yu, Qingzhao, 2009. "Misspecification of the effect of race in fixed effects models of health inequalities," Social Science & Medicine, Elsevier, vol. 69(11), pages 1584-1591, December.
    13. Fikru, Mahelet G., 2016. "Determinants of International Standards in sub-Saharan Africa: The role of institutional pressure from different stakeholders," Ecological Economics, Elsevier, vol. 130(C), pages 296-307.
    14. David Cutts & Edward Fieldhouse, 2009. "What Small Spatial Scales Are Relevant as Electoral Contexts for Individual Voters? The Importance of the Household on Turnout at the 2001 General Election," American Journal of Political Science, John Wiley & Sons, vol. 53(3), pages 726-739, July.
    15. Paolo Berta & Chiara Seghieri & Giorgio Vittadini, 2013. "Comparing health outcomes among hospitals: the experience of the Lombardy Region," Health Care Management Science, Springer, vol. 16(3), pages 245-257, September.
    16. Venkataramanan, R. & Kumar, Abhishek & Mantena, Sreekar & Subramanian, S.V., 2021. "Geographical variation in mobile phone ownership and SMS literacy among women (age 15–49) in India: A cross-sectional analysis based on National Family Health Survey-4," Technology in Society, Elsevier, vol. 64(C).
    17. Armando Alfaro-Tapia & Jeniffer K. Alvarez-Baca & Eduardo Fuentes-Contreras & Christian C. Figueroa, 2021. "Biological Control May Fail on Pests Applied with High Doses of Insecticides: Effects of Sub-Lethal Concentrations of a Pyrethroid on the Host-Searching Behavior of the Aphid Parasitoid Aphidius colem," Agriculture, MDPI, vol. 11(6), pages 1-14, June.
    18. Le Zhang & Chuanqing Liao & Huan Zhang & Xiaobo Hua, 2018. "Multilevel Modeling of Rural Livelihood Strategies from Peasant to Village Level in Henan Province, China," Sustainability, MDPI, vol. 10(9), pages 1-13, August.
    19. Kelvyn Jones & Ron Johnston & James Forrest & Chris Charlton & David Manley, 2018. "Ethnic and class residential segregation: exploring their intersection – a multilevel analysis of ancestry and occupational class in Sydney," Urban Studies, Urban Studies Journal Limited, vol. 55(6), pages 1163-1184, May.
    20. Gianluca Fiorentini & Elisa Iezzi & Matteo Lippi Bruni & Cristina Ugolini, 2011. "Incentives in primary care and their impact on potentially avoidable hospital admissions," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 12(4), pages 297-309, August.

    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:gam:jdataj:v:6:y:2021:i:7:p:74-:d:591808. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.