ERCoRe Learning Model Potential for Enhancing Student Retention among Different Academic Ability

被引:3
|
作者
Ismirawati, Nur [1 ,2 ]
Corebima, Aloysius Duran [3 ]
Zubaidah, Siti [3 ]
Syamsuri, Istamar [3 ]
机构
[1] State Univ Malang, Grad Sch, Malang, Indonesia
[2] Univ Muhammadiyah Parepare, Biol Educ Programme, Parepare, Indonesia
[3] State Univ Malang, Biol Dept, Malang, Indonesia
关键词
academic ability; conventional learning; ERCoRe learning; learning model; student retention;
D O I
10.14689/ejer.2018.77.2
中图分类号
G40 [教育学];
学科分类号
040101 ; 120403 ;
摘要
Purpose: This research was conducted to investigate the potential of the ERCoRe learning model in empowering the retention of students' of different academic ability. Research Methods: This was a quasi-experimental research using pre-test and post-test non-equivalent control group design of 2x2. There were two independent variables. The first variable was the learning model consisting of the ERCoRe model and conventional learning, and the second variable was academic ability, consisting of upper and lower levels of academic ability. The dependent variable was the students' retention. The samples for this research were the students of class X in Pangkep District, Indonesia. The data from this research were analysed by using ANCOVA, followed by Least Significant Different (LSD). Findings: The ERCoRe learning model was shown to have more potential for improving the students' retention than conventional learning (11.58%). The interaction between the ERCoRe learning model and academic ability did not have an effect on students' retention, but it was seen from the combination groups that the retention of the higher academic ability students who experienced ERCoRe learning was higher (significantly different) than that of the other combination groups. Implications for Research and Practice: Teachers need to implement the ERCoRe learning model because this learning model can improve the level of students' retention. (c) 2018 Ani Publishing Ltd. All rights reserved
引用
收藏
页码:19 / 34
页数:16
相关论文
共 50 条
  • [41] Learning support and academic achievement among Malaysian adolescents: the mediating role of student engagement
    Jelas Z.M.
    Azman N.
    Zulnaidi H.
    Ahmad N.A.
    Learning Environments Research, 2016, 19 (2) : 221 - 240
  • [42] Harnessing ICT potential The adoption and analysis of ICT systems for enhancing the student learning experience
    Dawson, Shane
    Heathcote, Liz
    Poole, Gary
    INTERNATIONAL JOURNAL OF EDUCATIONAL MANAGEMENT, 2010, 24 (02) : 116 - +
  • [43] Enhancing skills of academic researchers: The development of a participatory threefold peer learning model
    Barnard, Sarah
    Mallaband, Becky
    Mackley, Kerstin Leder
    INNOVATIONS IN EDUCATION AND TEACHING INTERNATIONAL, 2019, 56 (02) : 173 - 183
  • [44] ENHANCING STUDENT SUCCESS THROUGH PROFESSIONALISED ACADEMIC ADVISING: A MODEL FOR IDENTIFYING ACADEMIC ADVISORS FOR SOUTH AFRICAN HIGHER EDUCATION CONTEXTS
    de Klerk, D.
    Jadhav, A.
    Hundermark, G.
    SOUTH AFRICAN JOURNAL OF HIGHER EDUCATION, 2024, 38 (05) : 210 - 229
  • [45] Enhancing academic staff retention in an open distance e-Learning higher education institution in South Africa
    Molotsi, Tebogo Kefilwe
    Bezuidenhout, Adele
    Joubert, Yvonne
    INDEPENDENT JOURNAL OF TEACHING AND LEARNING, 2023, 18 (01):
  • [46] Transforming Undergraduate STEM Education: The Learning Assistant Model and Student Retention and Graduation Rates
    Feng, Li
    Close, Eleanor W.
    Luxford, Cynthia J.
    Pierson, Jiwoo An
    Olmstead, Alice
    Shim, Jieon
    Koka, Venkata Sowjanya
    Galloway, Heather C.
    RESEARCH IN HIGHER EDUCATION, 2025, 66 (01)
  • [47] Online, timed practice exams in organic chemistry: Enhancing student accountability for learning and long-term retention
    Asirvatham, Margaret R.
    ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, 2013, 245
  • [48] Reproducing Predictive Learning Analytics in CS1: Toward Generalizable and Explainable Models for Enhancing Student Retention
    Zhidkikh, Denis
    Heilala, Ville
    Van Petegem, Charlotte
    Dawyndt, Peter
    Jarvinen, Miitta
    Viitanen, Sami
    De Wever, Bram
    Mesuere, Bart
    Lappalainen, Vesa
    Kettunen, Lauri
    Hamalainen, Raija
    JOURNAL OF LEARNING ANALYTICS, 2024, 11 (01): : 132 - 150
  • [49] ICT, learning environment and student characteristics as potential cross-country predictors of academic achievement
    Erdogdu, Funda
    EDUCATION AND INFORMATION TECHNOLOGIES, 2022, 27 (05) : 7135 - 7159
  • [50] ICT, learning environment and student characteristics as potential cross-country predictors of academic achievement
    Funda Erdogdu
    Education and Information Technologies, 2022, 27 : 7135 - 7159