### Abstract

quickly as possible after they have occurred, while keeping the false-positive rate at a low predefined level. The methodology is applied to a data base of students graduated with Science Degrees at Macquarie University in the last 10 years.

Language | English |
---|---|

Title of host publication | Proceedings of the 34th International Workshop on Statistical Modelling |

Subtitle of host publication | Volume II |

Editors | Luis Meira-Machado, Gustavo Soutinho |

Place of Publication | Guimaraes, Portugal |

Pages | 212-215 |

Number of pages | 4 |

Volume | 2 |

ISBN (Electronic) | 9789892096308 |

Publication status | Published - 2019 |

Event | International Workshop on Statistical Modelling (34th : 2019) - Guimaraes, Portugal Duration: 7 Jul 2019 → 12 Jul 2019 |

### Conference

Conference | International Workshop on Statistical Modelling (34th : 2019) |
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Country | Portugal |

City | Guimaraes |

Period | 7/07/19 → 12/07/19 |

### Fingerprint

### Keywords

- transformation models
- change-point detection
- student learning

### Cite this

*Proceedings of the 34th International Workshop on Statistical Modelling: Volume II*(Vol. 2, pp. 212-215). Guimaraes, Portugal.

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*Proceedings of the 34th International Workshop on Statistical Modelling: Volume II.*vol. 2, Guimaraes, Portugal, pp. 212-215, International Workshop on Statistical Modelling (34th : 2019), Guimaraes, Portugal, 7/07/19.

**Which pathways lead to success? Transformation models and change-point detection for the early identification of students at risk.** / Manuguerra, Maurizio; Sofronov, Georgy.

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › Research › peer-review

TY - GEN

T1 - Which pathways lead to success?

T2 - Transformation models and change-point detection for the early identification of students at risk

AU - Manuguerra, Maurizio

AU - Sofronov, Georgy

PY - 2019

Y1 - 2019

N2 - In modern Universities, the timely identification of students at risk is valuable to limit failure and withdrawal rates. In this study we define the concept of students’ academic pathways, and use this and other variables to detect when students become at risk. We approach the problem modelling the latent variable “student learning” in the framework of transformation models, and use an indicator function readably available in this framework to detect change-points that depend on the observations already made but do not depend on the future which is not yet observed. We show how change-points can be detected asquickly as possible after they have occurred, while keeping the false-positive rate at a low predefined level. The methodology is applied to a data base of students graduated with Science Degrees at Macquarie University in the last 10 years.

AB - In modern Universities, the timely identification of students at risk is valuable to limit failure and withdrawal rates. In this study we define the concept of students’ academic pathways, and use this and other variables to detect when students become at risk. We approach the problem modelling the latent variable “student learning” in the framework of transformation models, and use an indicator function readably available in this framework to detect change-points that depend on the observations already made but do not depend on the future which is not yet observed. We show how change-points can be detected asquickly as possible after they have occurred, while keeping the false-positive rate at a low predefined level. The methodology is applied to a data base of students graduated with Science Degrees at Macquarie University in the last 10 years.

KW - transformation models

KW - change-point detection

KW - student learning

M3 - Conference proceeding contribution

VL - 2

SP - 212

EP - 215

BT - Proceedings of the 34th International Workshop on Statistical Modelling

A2 - Meira-Machado, Luis

A2 - Soutinho, Gustavo

CY - Guimaraes, Portugal

ER -