Building a Motivating and Autonomy Environment to Support Adaptive Learning

被引:3
作者
Cheng, Qiong [1 ]
Benton, David [1 ]
Quinn, Andrew [1 ]
机构
[1] Univ North Carolina Charlotte, Charlotte, NC 28223 USA
来源
2021 IEEE FRONTIERS IN EDUCATION CONFERENCE (FIE 2021) | 2021年
关键词
data structures and algorithms; growth mindset; self-determination theory; adaptive learning; active learning; ENGAGEMENT; SCIENCE;
D O I
10.1109/FIE49875.2021.9637397
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This Innovative Practice Full paper presents an effort on fostering student motivation and autonomy in support of adaptive learning. Higher education has been transformed by digital technology to be more interactive, self-paced, and adaptive to students. But this technology presupposes that students possess autonomy and are innately well motivated. Unfortunately, many students entering college lack motivation and self-control. These dispositions retard self-paced adaptive learning and limit the effectiveness of imparting improved adaptability in this technology. Taking inspiration from the self-determination theory, we investigated, in the context of adaptive learning, the importance of nurturing student autonomy and enhancing student situated motivation. In this paper, we present our experiential study in a gateway core course of computer science, in which adaptive preparation and learning pedagogy has been adopted for four semesters, one semester without motivating support and others with this support. By comparing and analyzing student engagement and performance over these four semesters, we observe that nurturing student autonomy and enhancing motivation are critical factors in maximizing the effectiveness of adaptive learning.
引用
收藏
页数:7
相关论文
共 35 条
[1]  
Alvarado C, 2018, SIGCSE'18: PROCEEDINGS OF THE 49TH ACM TECHNICAL SYMPOSIUM ON COMPUTER SCIENCE EDUCATION, P876, DOI [10.1145/3210551, 10.1145/3159450.3159508]
[2]  
[Anonymous], 2013, COMPUTER SCI CURRICU
[3]  
Blum L, 2007, SIGCSE 2007: PROCEEDINGS OF THE THIRTY-EIGHTH SIGCSE TECHNICAL SYMPOSIUM ON COMPUTER SCIENCE EDUCATION, P19, DOI 10.1145/1227504.1227320
[4]  
Bockmon R, 2020, 51 ACM TECHNICAL S C, P899
[5]  
Buffardi K, 2014, PROCEEDINGS OF THE 45TH ACM TECHNICAL SYMPOSIUM ON COMPUTER SCIENCE EDUCATION (SIGCSE'14), P724
[6]   A Systematic Review Exploring the Differences in Reported Data for Pre-College Educational Activities for Computer Science, Engineering, and Other STEM Disciplines [J].
Decker, Adrienne ;
McGill, Monica M. .
EDUCATION SCIENCES, 2019, 9 (02)
[7]  
Edgcomb A, 2016, PROC ASEE ANN C
[8]  
Edgcomb A., 2015, PROC ASEE ANN C
[9]  
Edgcomb A, 2015, PROC FRONT EDUC CONF, P2004
[10]  
Edgcomb A, 2015, PROC FRONT EDUC CONF, P1820