Machine learning methods to understand how predictors of achievement change over time: Methodological challenges, solutions, and future directions.

Rosa  Lavelle-Hill; Anne C. Frenzel; Thomas Götz; Stephanie Lichtenfeld; H. Marsh; Reinhard  Pekrun; Michiko Sakaki; G. Smith; Kou  Murayama

Machine learning methods to understand how predictors of achievement change over time: Methodological challenges, solutions, and future directions.

Rosa Lavelle-Hill, Anne C. Frenzel, Thomas Götz, Stephanie Lichtenfeld, H. Marsh, Reinhard Pekrun, Michiko Sakaki, G. Smith, Kou Murayama

Department of Developmental and Educational Psychology

Publications: Contribution to conference › Paper › Peer Reviewed

Original language	English
Publication status	Published - May 2023
Event	4th Symposium on Big Data and Research Syntheses in Psychology - Frankfurt am Main, Germany Duration: 8 May 2023 → 10 May 2023

Conference

Conference	4th Symposium on Big Data and Research Syntheses in Psychology
Country/Territory	Germany
City	Frankfurt am Main
Period	8/05/23 → 10/05/23

Austrian Fields of Science 2012

501002 Applied psychology
501016 Educational psychology

Cite this

Lavelle-Hill, R., Frenzel, A. C., Götz, T., Lichtenfeld, S., Marsh, H., Pekrun, R., Sakaki, M., Smith, G., & Murayama, K. (2023). Machine learning methods to understand how predictors of achievement change over time: Methodological challenges, solutions, and future directions.. Paper presented at 4th Symposium on Big Data and Research Syntheses in Psychology, Frankfurt am Main, Germany.

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note = "4th Symposium on Big Data and Research Syntheses in Psychology ; Conference date: 08-05-2023 Through 10-05-2023",

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Lavelle-Hill, R, Frenzel, AC, Götz, T, Lichtenfeld, S, Marsh, H, Pekrun, R, Sakaki, M, Smith, G & Murayama, K 2023, 'Machine learning methods to understand how predictors of achievement change over time: Methodological challenges, solutions, and future directions.', Paper presented at 4th Symposium on Big Data and Research Syntheses in Psychology, Frankfurt am Main, Germany, 8/05/23 - 10/05/23.

Machine learning methods to understand how predictors of achievement change over time: Methodological challenges, solutions, and future directions. / Lavelle-Hill, Rosa ; Frenzel, Anne C.; Götz, Thomas et al.
2023. Paper presented at 4th Symposium on Big Data and Research Syntheses in Psychology, Frankfurt am Main, Germany.

Publications: Contribution to conference › Paper › Peer Reviewed

TY - CONF

T1 - Machine learning methods to understand how predictors of achievement change over time: Methodological challenges, solutions, and future directions.

AU - Lavelle-Hill, Rosa

AU - Frenzel, Anne C.

AU - Götz, Thomas

AU - Lichtenfeld, Stephanie

AU - Marsh, H.

AU - Pekrun, Reinhard

AU - Sakaki, Michiko

AU - Smith, G.

AU - Murayama, Kou

PY - 2023/5

Y1 - 2023/5

M3 - Paper

T2 - 4th Symposium on Big Data and Research Syntheses in Psychology

Y2 - 8 May 2023 through 10 May 2023

ER -