Early identification of at-risk students using a personal response system

被引:17
|
作者
Griff, Edwin R. [1 ]
Matter, Stephen F. [1 ]
机构
[1] Univ Cincinnati, Dept Biol Sci, Cincinnati, OH 45221 USA
关键词
D O I
10.1111/j.1467-8535.2007.00806.x
中图分类号
G40 [教育学];
学科分类号
040101 ; 120403 ;
摘要
The early identification of at-risk students using a personal response system was investigated. The personal response system (PRS) data from Biology courses was analyzed. There was a significant relationship between the distribution of grades and the order in which students registered their PRS clickers. Students who registered their devices early had a much higher probability of success than those registering later. The term 'gateway' course refers to an introductory course required for continuation and matriculation in a particular major or specialty. Many programs and pedagogical approaches from remedial and supplemental instruction to peer-led problem-based learning have been developed to help at-risk students and improve success rates. It was observed that there was a significant relationship between the distribution of grades and the order in which students registered their PRS clicker.
引用
收藏
页码:1124 / 1130
页数:7
相关论文
共 50 条
  • [1] Early Identification of At-Risk Students Using Iterative Logistic Regression
    Zhang, Li
    Rangwala, Huzefa
    ARTIFICIAL INTELLIGENCE IN EDUCATION, PART I, 2018, 10947 : 613 - 626
  • [2] Early identification of 'at-risk' students by the parents of paediatric patients
    O'Keefe, M
    Whitham, J
    MEDICAL EDUCATION, 2005, 39 (09) : 958 - 965
  • [3] Early Alert System for Detection of At-Risk Students
    Ravikumar, Rejitha
    Aljanahi, Fatma
    Rajan, Amala
    Akre, Vishwesh
    2018 FIFTH HCT INFORMATION TECHNOLOGY TRENDS (ITT): EMERGING TECHNOLOGIES FOR ARTIFICIAL INTELLIGENCE, 2018, : 138 - 142
  • [4] MINING ENROLMENT DATA FOR EARLY IDENTIFICATION OF AT-RISK STUDENTS
    Lee, Yew Haur
    Chong, Sylvia
    INTED2015: 9TH INTERNATIONAL TECHNOLOGY, EDUCATION AND DEVELOPMENT CONFERENCE, 2015, : 4214 - 4220
  • [5] Course Success Prediction and Early Identification of At-Risk Students Using Explainable Artificial Intelligence
    Ujkani, Berat
    Minkovska, Daniela
    Hinov, Nikolay
    ELECTRONICS, 2024, 13 (21)
  • [6] An ensembling model for early identification of at-risk students in higher education
    Gupta, Anika
    Garg, Deepak
    Kumar, Parteek
    COMPUTER APPLICATIONS IN ENGINEERING EDUCATION, 2022, 30 (02) : 589 - 608
  • [7] Using learning analytics to develop early-warning system for at-risk students
    Gökhan Akçapınar
    Arif Altun
    Petek Aşkar
    International Journal of Educational Technology in Higher Education, 16
  • [8] Lightweight, Early Identification of At-Risk CS1 Students
    Liao, Soohyun Nam
    Zingaro, Daniel
    Laurenzano, Michael A.
    Griswold, William G.
    Porter, Leo
    PROCEEDINGS OF THE 2016 ACM CONFERENCE ON INTERNATIONAL COMPUTING EDUCATION RESEARCH (ICER'16), 2016, : 123 - 131
  • [9] Early identification of at-risk nursing students: A student support model
    Hopkins, T. Hampton
    JOURNAL OF NURSING EDUCATION, 2008, 47 (06) : 254 - 259
  • [10] Using learning analytics to develop early-warning system for at-risk students!
    Akcapinar, Gokhan
    Altun, Arif
    Askar, Petek
    INTERNATIONAL JOURNAL OF EDUCATIONAL TECHNOLOGY IN HIGHER EDUCATION, 2019, 16 (01)