DEVELOPING A LEARNING ANALYTICS MODEL TO EXPLORE COMPUTER SCIENCE STUDENT MOTIVATION IN THE UK

被引：1

作者：

Al Ansari, Hafsa ^{[1
]}

Ward, Rupert ^{[1
]}

Hill, Richard ^{[1
]}

机构：

[1] Univ Huddersfield, Sch Comp & Engn, Huddersfield, W Yorkshire, England

来源：

IEEE 21ST INTERNATIONAL CONFERENCE ON ADVANCED LEARNING TECHNOLOGIES (ICALT 2021) | 2021年

关键词：

Learning Analytics; Motivation; Self-Determination Theory; Learning Design; Self-Regulated Learning; SELF-DETERMINATION; AUTONOMY SUPPORT; NEEDS; ORIENTATION; BEHAVIOR; VALIDITY; SCALE;

D O I：

10.1109/ICALT52272.2021.00140

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 study investigates enhancing student learning and performance by exploring student motivation through the use of learning analytics. A mixed-methods approach will be used to collect data from Computer Science students within the UK higher education sector. The collected data will be analyzed using thematic analysis to develop a theoretical framework that will be tested subsequently using structural equation modeling. The identification of student motivation factors helps tutors and learning analysts to better understand student learning motivation and adapt their learning practices accordingly.

引用

页码：442 / 444

页数：3

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