Using Learning Analytics to Identify Student Learning Profiles for Software Development Courses

被引:0
作者
Apel, Sebastian [1 ]
Soechtig, Philipp [2 ]
Windisch, Hans-Michael [1 ]
机构
[1] Tech Hsch Ingolstadt, Fac Comp Sci, Ingolstadt Bavaria, Germany
[2] Tech Hsch Ingolstadt, Dep Strategy & Qual, Ingolstadt Bavaria, Germany
来源
PROCEEDINGS OF THE 5TH EUROPEAN CONFERENCE ON SOFTWARE ENGINEERING EDUCATION, ECSEE 2023 | 2023年
关键词
Learning Analytics; Learning Profiles; Learning Management System;
D O I
10.1145/3593663.3593679
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Often lecturers encounter the problem of not knowing how students use the course materials during a semester. In our approach we devised a web-based system that presents all learning materials in a digital format, allowing us to record student learning activities. The recorded usage data enabled extensive analyses of student learning behaviour which can support lecturers with improving the materials as well as understanding students' learning material preferences and learning profiles, which can be composed by combining different usage modes depending on the material used. For the lectures we analysed, a higher success in the exam can be correlated to higher usage of the learning material according to our research data. Furthermore, student preferences regarding the form of presentation (f.e. slides over videos) could also be seen.
引用
收藏
页码:31 / 37
页数:7
相关论文
共 20 条
  • [1] Anderson L.W., 2001, TAXONOMY LEARNING TE
  • [2] [Anonymous], 2017, A view of the current state of the art to enhance e-learning
  • [3] [Anonymous], Reveal-Framework
  • [4] [Anonymous], Project AIStudyBuddy
  • [5] [Anonymous], Project DABALUGA
  • [6] [Anonymous], Project KI4TUK
  • [7] Baumann Thomas, 2019, Evaluation of a digital UDL-based learning environment in inclusive chemistry education
  • [8] H5P, US
  • [9] Hattie John, 2018, Visible Learning. Lernen auf den Punkt gebracht
  • [10] IMS-LTI, ABOUT US