Abstract:

Engineering degree programmes usually comprise subjects on the basics of design theory, such as technical drawing and calculations for bearing or bolts at the very beginning. These subjects are often attended by up to 500 students. These students have differing technical knowledge due to varying prior experience from internships, vocational trainings, or technical school degrees. For the students, the total effort required for such modules divides into some 50 % classroom learning phases and 50 % self-learning phases followed by a summative final examination. Due to large groups, presence learning consists mainly of teacher-centred lectures. For the self-learning phases, students are provided with exercises, learning videos, recommended books, etc. However, preliminary studies show that students find it difficult to benefit from these since they fail to select appropriate self-learning material suitable for their individual level of expertise. Therefore, this paper examines the extent to which students in the first semester benefit from a learning environment with individualized learning paths. For this purpose, an adaptive E-Learning environment (AdE-Le) has been developed to structure the individual self-learning phase, which records the students' level of knowledge and suggests learning activities based on this. The learning activities include e-learning materials, but also references to book pages or chapters or standards and guidelines. The technical implementation was done in the learning management system “Moodle” through prerequisite-linked moodle activities like moodle activity tests (including the mathematical module “Stack”) and moodle activity lessons. Differentiated feedback is provided for each answer given by the student and users are directed to a learning activity within the lessons that matches their prior answer. So far, AdE-Le was used by 106 students in addition to teacher-centred lectures at a Germany university in the winter semester 22/23. For the evaluation, the results of a questionnaire before use, a questionnaire after use and the exam results are analysed and statistically evaluated. Overall, the students who used AdE-Le considered this helpful because AdE-Le often correctly identified their individual deficits. In addition, the individualized feedback is considered very helpful. The suggested learning activities are rated as very appropriate. To assess the learning success of Ade-Le, the final exams of students were compared to those who did not use AdE-Le. The central result of the evaluation shows a positive significant correlation between the use of AdE-Le and the examination results in the task whose learning outcomes are addressed by AdE-Le. For examination tasks not supported by AdE-Le content, there are no differences between the two test groups. Therefore, the better examination result of the AdE-Le supported group can be attributed to the individual support provided by the AdE-Le and not on the fact that only the higher-performing students have used AdE-Le.

Keywords:

Adaptive e-learning, Individual learning path, Engineering Design Education.